David Ratz, MS

In patients with gastrointestinal (GI) malignancies, malnutrition is common. In addition, it has various negative implications, including high risk for surgical complications, prolonged hospitalization, decreased quality of life (QOL), increased mortality, and poor tolerance for treatments such as chemotherapy and radiotherapy.¹

A 2014 French study of 1903 patients hospitalized for cancer reported a 39% overall prevalence of malnutrition; 39% in patients with cancers of the colon/rectum, 60% for pancreatic cancer, and 67% for cancers of the esophagus/stomach.² Malnutrition was defined as body mass index (BMI) < 18.5 for individuals aged < 75 years or BMI < 21 for individuals aged ≥ 75 years, and/or weight loss > 10% since disease onset. Malnutrition also was strongly associated with worsened performance status.

The etiology of malnutrition in GI cancers is often multifactorial. It includes systemic tumor effects, such as inflammatory mediators contributing to hypermetabolism and cachexia, local tumor-associated mechanical obstruction, GI toxicities caused by antineoplastic therapy or other medications, and psychological factors that contribute to anorexia.³ Patient-related risk factors such as older age, other chronic diseases, and history of other GI surgeries also play a role.¹

Other studies have demonstrated that malnutrition in patients with GI malignancies undergoing surgical resection is associated with high rates of severe postoperative complications, increased length of stay (LOS) and time on a ventilator for patients treated in the intensive care unit, and poor QOL in the postoperative survival period.^4-6 Several randomized controlled trials conducted in patients with GI cancers have shown that enteral and parenteral nutrition supplementations in the perioperative period improve various outcomes, such as reduction of postoperative complication rates, fewer readmissions, improved chemotherapy tolerance, and improved QOL.^7-10 Thus, in the management of patients with GI malignancies, it is highly important to implement early nutritional screening and establish a diagnosis of malnutrition to intervene and reduce postoperative morbidity and mortality.¹

However, tools and predictors of malnutrition are often imperfect. The Academy of Nutrition and Dietetics and the American Society for Parenteral and Enteral Nutrition (AND/ASPEN) weight-based criteria define malnutrition and nutritionally-at-risk as BMI < 18.5, involuntary loss of at least 10% of body weight within 6 months or 5% within 1 month, or loss of 10 lb within 6 months.¹¹ While the ASPEN criteria are often used to define malnourishment, they may not fully capture the population at risk, and there does not exist a gold-standard tool for nutritional screening. A 2002 study that performed a critical appraisal of 44 nutritional screening tools found that no single tool was fully sufficient for application, development, evaluation, and consistent screening.¹² As such, consistently screening for malnutrition to target interventions in the perioperative period for GI surgical oncology has been challenging.¹³ More recent tools such as the perioperative nutrition screen (PONS) have been validated as rapid, effective screening tools to predict postoperative outcomes.¹⁴ Additionally, implementation of perioperative nutritional protocols, such as enhanced recovery after surgery (ERAS) in colon cancer (CC) surgery, also has shown improved perioperative care and outcomes.¹⁵

Preoperative nutritional interventions have been implemented in practice and have focused mostly on the immediate perioperative period. This has been shown to improve surgical outcomes. The Veterans Health Administration (VHA) provides comprehensive care to patients in a single-payer system, allowing for capture of perioperative data and the opportunity for focused preoperative interventions to improve outcomes.

Methods

This was a retrospective record review of colorectal malignancies treated with curative intent at the Veterans Affairs Ann Arbor Healthcare System (VAAAHS) in Michigan between January 1, 2015, and December 31, 2019. We examined nutritional status, degree of longitudinal weight loss, and subsequent clinical outcomes, including delayed postoperative recovery and delays in chemotherapy in 115 patients with CC and 33 patients with rectal cancer (RC) undergoing curative surgical resection at VAAAHS. To avoid additional confounding effects of advanced cancer, only early-stage, curable disease was included. This study was approved by the VAAAHS Institutional Review Board.

Analysis

The data were described using mean (SD) for continuous variables and number and percentages for categorical variables. Where appropriate, Fisher exact test, Pearson χ² test, Spearman ρ, and Mann-Whitney U test were used for tests of significance. SAS (SAS Institute) was utilized for multivariable analysis. The significance level was P = .05 for all tests.

Results

There were 115 patients in the CC cohort and 33 in the RC cohort. The mean (SD) age at diagnosis was 70 (9.1) for CC group and 59 (1.4) for RC group (Table 1). 

Weight Trends

From 1 year to 6 months before diagnosis, 40 of 80 patients lost weight in the CC cohort (mean change, +1.9%) and 6 of 22 patients lost weight in the RC cohort (mean change, + 0.5%). From 6 months before diagnosis to time of diagnosis, 47 of 74 patients lost weight in the CC cohort (mean change, -1.5%) and 14 of 21 patients lost weight in the RC cohort (mean change, -2.5%). From time of diagnosis to time of surgery, 36 of 104 patients with CC and 14 of 32 patients with RC lost weight with a mean weight change of and +0.1% and -0.3%, respectively. In the 6 months before surgery, any amount of weight loss was observed in 58 patients (66%) in the CC group and in 12 patients (57%) in the RC group. In this time frame, in the CC cohort, 32 patients (36%) were observed to have at least 3% weight loss, and 23 (26%) were observed to have at least 5% weight loss (Table 3). 

Nutrition Consultations

In the CC group, preoperative nutrition consultations (either inpatient or outpatient) occurred in 17 patients (15%). Inpatient postoperative nutrition evaluations occurred in 110 patients (96%) (Table 5). 

In the RC group, preoperative inpatient or outpatient nutrition consultations occurred in 12 patients (36%). Eight of those occurred before initiation of neoadjuvant chemoradiotherapy. All 33 patients received an inpatient postoperative nutrition evaluation during admission. Oral or enteral nutrition supplements were prescribed 19 times (58%). Postoperative outpatient nutrition consultations occurred for 24 patients (73%). Of the 19 patients who were readmitted to the hospital, 3 (16%) had a nutrition reconsultation on readmission.

Outcomes

The primary outcomes observed were delayed recovery, hospital readmission and LOS, and completion of adjuvant chemotherapy as indicated. Delayed recovery was observed in 35 patients with CC (40%) and 21 patients with RC (64%). Multivariable analysis in the CC cohort demonstrated that weight change was significantly associated with delayed recovery. Among those with ≥ 3% weight loss in the 6-month preoperative period (the weight measurement 6 months prior to diagnosis to date of surgery), 20 patients (63%) had delayed recovery compared with 15 patients (27%) without ≥ 3% weight loss who experienced delayed recovery (χ² = 10.84; P < .001).

Weight loss of ≥ 3% in the 6-month preoperative period also was significantly associated with complications. Of patients with at least 3% preoperative weight loss, 16 (50%) experienced complications, while 8 (14%) with < 3% preoperative weight loss experienced complications (χ² = 11.20; P < .001). Notably, ≥ 3% weight loss in the 1-year preoperative period before surgery was not significantly associated with delayed recovery. Any degree of 30-day postoperative weight loss was not correlated with delayed recovery. Finally, low preoperative albumin also was not correlated with delayed recovery (Fisher exact; P = .13). Table 3 displays differences based on presence of delayed recovery in the 88 patients with CC 6 months before surgery. Of note, ≥ 10-lb weight loss in the 6 months preceding surgery also correlated with delayed recovery (P = .01).In our cohort, 3% weight loss over 6 months had a sensitivity of 57%, specificity of 77%, positive predictive value 63%, and negative predictive value 73% for delayed recovery. By comparison, a 10-lb weight loss in 6 months per ASPEN criteria had a sensitivity of 40%, specificity of 85%, positive predictive value 64%, and negative predictive value 68% for delayed recovery.

Hospital Readmissions and LOS

Hospital readmissions occurred within the first 30 days in 11 patients (10%) in the CC cohort and 12 patients (36%) in the RC cohort. Readmissions occurred between 31 and 60 days in 4 (3%) and 7 (21%) of CC and RC cohorts, respectively. The presence of ≥ 3% weight loss in the 6-month preoperative period was significantly associated with 60-day readmissions. Among those with ≥ 3% preoperative weight loss, 8 patients (25%) had readmissions within 60 days vs 3 patients (5%) without 3% preoperative weight loss who had readmissions within 60 days (Fisher exact; P = .02).

Mean (SD) LOS was 6.4 (4.7) days (range, 1-28) for patients with CC and 8.8 (5.1) days (range, 3-23) for patients with RC. Mean (SD) LOS increased to 10.2 (4.3) days and 9.7 (6.0) days in patients with delayed recovery in the CC and RC cohorts, respectively. The mean (SD) LOS was 5.2 (2.8) days and 6.3 (2.2) days in patients without delayed recovery in the CC and RC cohorts, respectively. There was no significant difference when examining association between percent weight change and LOS for either initial admission (r_s= -0.1409; 2-tailed P = .19) or for initial and readmission combined (r_s = -0.13532; 2-tailed P = .21) within the CC cohort.

Chemotherapy

Within the CC cohort, 31 patients (27%) had an indication for adjuvant chemotherapy. Of these, 25 of 31 (81%) started chemotherapy within 12 weeks of surgical resection, and of these, 17 of 25 patients (68%) completed chemotherapy as indicated. Within the RC cohort all 33 patients had an indication for adjuvant chemotherapy, of these 18 of 33 patients (55%) began within 12 weeks of surgical resection, and 10 of 18 (56%) completed chemotherapy as indicated.

Among the CC cohort who began but did not complete adjuvant chemotherapy, there was no significant association between completion of chemotherapy and preoperative weight loss. Of patients with ≥ 3% preoperative weight loss, 3 (43%) did not complete chemotherapy vs 3 patients (27%) without preoperative weight loss who did not complete chemotherapy as indicated (Fisher exact; P = .63). Finally, low preoperative albumin did not significantly correlate with lack of completion of adjuvant chemotherapy (Fisher exact; P = .99).

Discussion

This study highlights several important findings. There were no patients in our cohort that met ASPEN malnourishment criteria with a BMI < 18.5. Twenty percent of patients lost at least 10 lb in 6 months before the operation. Notably, patients had significant associations with adverse outcomes with less pronounced weight loss than previously noted. As has been established previously, malnourishment can be difficult to screen for, and BMI also is often an imprecise tool.¹² In the CC cohort, weight loss ≥ 3% from 6 months before surgery was significantly associated with delayed recovery, complications, and hospital readmissions. We did not identify a statistically significant effect on chemotherapy completion. However, the numerical difference was suggestive of a difference, and a type 2 error is possible due to our limited sample size.

Our findings imply that the effects of even mild malnutrition are even more profound than previously thought. Significantly, this applies to overweight and obese patients as well, as these constituted a significant fraction of our cohort. A finding of ≥ 3% weight loss at the time of CC diagnosis may provide an opportunity for a focused nutrition intervention up to the time of surgery. Second, although nutrition consultation was frequent in the inpatient setting during the hospital admission (96%-100%), rates of nutrition evaluation were as low as 15% before surgery and 12% after surgery, representing a key area for improvement and focused intervention. An optimal time for intervention and nutrition prehabilitation would be at time of diagnosis before surgery with plans for continued aggressive monitoring and subsequent follow-up. Our finding seems to provide a more sensitive tool to identify patients at risk for delayed recovery compared with the ASPEN-driven assessment. Given the simplicity and the clinical significance, our test consisting of 3% weight loss over 6 months, with its sensitivity of 57%, may be superior to the ASPEN 10-lb weight loss, with its sensitivity of 40% in our cohort.

Previous Studies

Our findings are consistent with previous studies that have demonstrated that perioperative weight loss and malnutrition are correlated with delayed recovery and complications, such as wound healing, in patients with GI cancer.^2,4,5,8 In a retrospective study of more than 7000 patients with CC, those who were overweight or obese were found to have an improved overall survival compared with other BMI categories, and those who were underweight had an increased 30-day mortality and postoperative complications.¹⁶

In another retrospective study of 3799 patients with CC, those who were overweight and obese had an improved 5-year survival rate compared with patients whose weight was normal or underweight. Outcomes were found to be stage dependent.¹⁷ In this study cohort, all patients were either overweight or obese and remained in that category even with weight loss. This may have contributed to overall improved outcomes.

Implications and Next Steps

Our study has several implications. One is that BMI criteria < 18.5 may not be a good measure for malnutrition given that about 75% of the patients in our cohort were overweight or obese and none were underweight. We also show a concrete, easily identifiable finding of percent weight change that could be addressed as an automated electronic notification and potentially identify a patient at risk and serve as a trigger for both timely and early nutrition intervention. It seems to be more sensitive than the ASPEN criterion of 10-lb weight loss in 6 months before surgery. Sensitivity is especially appealing given the ease and potential of embedding this tool in an electronic health record and the clinical importance of the consequent intervention. Preoperative as opposed to perioperative nutrition optimization at time of CC diagnosis is essential, as it may help improve postsurgical outcomes as well as oncologic outcomes, including completion of adjuvant chemotherapy. Finally, although our study found that rates of inpatient postoperative nutrition consultation were high, rates of outpatient nutrition consultation in the preoperative period were low. This represents a missed opportunity for intervention before surgery. Similarly, rates of postoperative nutrition follow-up period were low, which points to an area for improvement in longitudinal and holistic care.

We suggest modifications to nutrition intervention protocols, such as ERAS, which should start at the time of GI malignancy diagnosis.¹⁸ Other suggestions include standard involvement of nutritionists in inpatient and outpatient settings with longitudinal follow-up in the preoperative and postoperative periods and patient enrollment in a nutrition program with monitoring at time of diagnosis at the VHA. Our findings as well as previous literature suggest that the preoperative period is the most important time to intervene with regard to nutrition optimization and represents an opportunity for intensive prehabilitation. Future areas of research include incorporating other important measures of malnourishment independent of BMI into future study designs, such as sarcopenia and adipose tissue density, to better assess body composition and predict prognostic risk in CC.^18,19

Strengths and Limitations

This study is limited by its single-center, retrospective design and small sample sizes, and we acknowledge the limitations of our data set. However, the strength of this VHA-based study is that the single-payer system allows for complete capture of perioperative data as well as the opportunity for focused preoperative interventions to improve outcomes. To our knowledge, there is no currently existing literature on improving nutrition protocols at the VHA for patients with a GI malignancy. These retrospective data will help inform current gaps in quality improvement and supportive oncology as it relates to optimizing malnourishment in veterans undergoing surgical resection for their cancer.

Conclusions

In the CC cohort, weight loss of ≥ 3% from 6 months prior to time of surgery was significantly associated with delayed recovery, complications, and hospital readmissions. Our findings suggest that patients with CC undergoing surgery may benefit from an intensive, early nutrition prehabilitation. Preoperative nutrition optimization may help improve postsurgical outcomes as well as oncologic outcomes, including completion of adjuvant chemotherapy. Further research would be able to clarify these hypotheses.

In patients with gastrointestinal (GI) malignancies, malnutrition is common. In addition, it has various negative implications, including high risk for surgical complications, prolonged hospitalization, decreased quality of life (QOL), increased mortality, and poor tolerance for treatments such as chemotherapy and radiotherapy.¹

A 2014 French study of 1903 patients hospitalized for cancer reported a 39% overall prevalence of malnutrition; 39% in patients with cancers of the colon/rectum, 60% for pancreatic cancer, and 67% for cancers of the esophagus/stomach.² Malnutrition was defined as body mass index (BMI) < 18.5 for individuals aged < 75 years or BMI < 21 for individuals aged ≥ 75 years, and/or weight loss > 10% since disease onset. Malnutrition also was strongly associated with worsened performance status.

The etiology of malnutrition in GI cancers is often multifactorial. It includes systemic tumor effects, such as inflammatory mediators contributing to hypermetabolism and cachexia, local tumor-associated mechanical obstruction, GI toxicities caused by antineoplastic therapy or other medications, and psychological factors that contribute to anorexia.³ Patient-related risk factors such as older age, other chronic diseases, and history of other GI surgeries also play a role.¹

Other studies have demonstrated that malnutrition in patients with GI malignancies undergoing surgical resection is associated with high rates of severe postoperative complications, increased length of stay (LOS) and time on a ventilator for patients treated in the intensive care unit, and poor QOL in the postoperative survival period.^4-6 Several randomized controlled trials conducted in patients with GI cancers have shown that enteral and parenteral nutrition supplementations in the perioperative period improve various outcomes, such as reduction of postoperative complication rates, fewer readmissions, improved chemotherapy tolerance, and improved QOL.^7-10 Thus, in the management of patients with GI malignancies, it is highly important to implement early nutritional screening and establish a diagnosis of malnutrition to intervene and reduce postoperative morbidity and mortality.¹

However, tools and predictors of malnutrition are often imperfect. The Academy of Nutrition and Dietetics and the American Society for Parenteral and Enteral Nutrition (AND/ASPEN) weight-based criteria define malnutrition and nutritionally-at-risk as BMI < 18.5, involuntary loss of at least 10% of body weight within 6 months or 5% within 1 month, or loss of 10 lb within 6 months.¹¹ While the ASPEN criteria are often used to define malnourishment, they may not fully capture the population at risk, and there does not exist a gold-standard tool for nutritional screening. A 2002 study that performed a critical appraisal of 44 nutritional screening tools found that no single tool was fully sufficient for application, development, evaluation, and consistent screening.¹² As such, consistently screening for malnutrition to target interventions in the perioperative period for GI surgical oncology has been challenging.¹³ More recent tools such as the perioperative nutrition screen (PONS) have been validated as rapid, effective screening tools to predict postoperative outcomes.¹⁴ Additionally, implementation of perioperative nutritional protocols, such as enhanced recovery after surgery (ERAS) in colon cancer (CC) surgery, also has shown improved perioperative care and outcomes.¹⁵

Preoperative nutritional interventions have been implemented in practice and have focused mostly on the immediate perioperative period. This has been shown to improve surgical outcomes. The Veterans Health Administration (VHA) provides comprehensive care to patients in a single-payer system, allowing for capture of perioperative data and the opportunity for focused preoperative interventions to improve outcomes.

Methods

This was a retrospective record review of colorectal malignancies treated with curative intent at the Veterans Affairs Ann Arbor Healthcare System (VAAAHS) in Michigan between January 1, 2015, and December 31, 2019. We examined nutritional status, degree of longitudinal weight loss, and subsequent clinical outcomes, including delayed postoperative recovery and delays in chemotherapy in 115 patients with CC and 33 patients with rectal cancer (RC) undergoing curative surgical resection at VAAAHS. To avoid additional confounding effects of advanced cancer, only early-stage, curable disease was included. This study was approved by the VAAAHS Institutional Review Board.

Analysis

The data were described using mean (SD) for continuous variables and number and percentages for categorical variables. Where appropriate, Fisher exact test, Pearson χ² test, Spearman ρ, and Mann-Whitney U test were used for tests of significance. SAS (SAS Institute) was utilized for multivariable analysis. The significance level was P = .05 for all tests.

Results

There were 115 patients in the CC cohort and 33 in the RC cohort. The mean (SD) age at diagnosis was 70 (9.1) for CC group and 59 (1.4) for RC group (Table 1). 

Weight Trends

From 1 year to 6 months before diagnosis, 40 of 80 patients lost weight in the CC cohort (mean change, +1.9%) and 6 of 22 patients lost weight in the RC cohort (mean change, + 0.5%). From 6 months before diagnosis to time of diagnosis, 47 of 74 patients lost weight in the CC cohort (mean change, -1.5%) and 14 of 21 patients lost weight in the RC cohort (mean change, -2.5%). From time of diagnosis to time of surgery, 36 of 104 patients with CC and 14 of 32 patients with RC lost weight with a mean weight change of and +0.1% and -0.3%, respectively. In the 6 months before surgery, any amount of weight loss was observed in 58 patients (66%) in the CC group and in 12 patients (57%) in the RC group. In this time frame, in the CC cohort, 32 patients (36%) were observed to have at least 3% weight loss, and 23 (26%) were observed to have at least 5% weight loss (Table 3). 

Nutrition Consultations

In the CC group, preoperative nutrition consultations (either inpatient or outpatient) occurred in 17 patients (15%). Inpatient postoperative nutrition evaluations occurred in 110 patients (96%) (Table 5). 

In the RC group, preoperative inpatient or outpatient nutrition consultations occurred in 12 patients (36%). Eight of those occurred before initiation of neoadjuvant chemoradiotherapy. All 33 patients received an inpatient postoperative nutrition evaluation during admission. Oral or enteral nutrition supplements were prescribed 19 times (58%). Postoperative outpatient nutrition consultations occurred for 24 patients (73%). Of the 19 patients who were readmitted to the hospital, 3 (16%) had a nutrition reconsultation on readmission.

Outcomes

The primary outcomes observed were delayed recovery, hospital readmission and LOS, and completion of adjuvant chemotherapy as indicated. Delayed recovery was observed in 35 patients with CC (40%) and 21 patients with RC (64%). Multivariable analysis in the CC cohort demonstrated that weight change was significantly associated with delayed recovery. Among those with ≥ 3% weight loss in the 6-month preoperative period (the weight measurement 6 months prior to diagnosis to date of surgery), 20 patients (63%) had delayed recovery compared with 15 patients (27%) without ≥ 3% weight loss who experienced delayed recovery (χ² = 10.84; P < .001).

Weight loss of ≥ 3% in the 6-month preoperative period also was significantly associated with complications. Of patients with at least 3% preoperative weight loss, 16 (50%) experienced complications, while 8 (14%) with < 3% preoperative weight loss experienced complications (χ² = 11.20; P < .001). Notably, ≥ 3% weight loss in the 1-year preoperative period before surgery was not significantly associated with delayed recovery. Any degree of 30-day postoperative weight loss was not correlated with delayed recovery. Finally, low preoperative albumin also was not correlated with delayed recovery (Fisher exact; P = .13). Table 3 displays differences based on presence of delayed recovery in the 88 patients with CC 6 months before surgery. Of note, ≥ 10-lb weight loss in the 6 months preceding surgery also correlated with delayed recovery (P = .01).In our cohort, 3% weight loss over 6 months had a sensitivity of 57%, specificity of 77%, positive predictive value 63%, and negative predictive value 73% for delayed recovery. By comparison, a 10-lb weight loss in 6 months per ASPEN criteria had a sensitivity of 40%, specificity of 85%, positive predictive value 64%, and negative predictive value 68% for delayed recovery.

Hospital Readmissions and LOS

Hospital readmissions occurred within the first 30 days in 11 patients (10%) in the CC cohort and 12 patients (36%) in the RC cohort. Readmissions occurred between 31 and 60 days in 4 (3%) and 7 (21%) of CC and RC cohorts, respectively. The presence of ≥ 3% weight loss in the 6-month preoperative period was significantly associated with 60-day readmissions. Among those with ≥ 3% preoperative weight loss, 8 patients (25%) had readmissions within 60 days vs 3 patients (5%) without 3% preoperative weight loss who had readmissions within 60 days (Fisher exact; P = .02).

Mean (SD) LOS was 6.4 (4.7) days (range, 1-28) for patients with CC and 8.8 (5.1) days (range, 3-23) for patients with RC. Mean (SD) LOS increased to 10.2 (4.3) days and 9.7 (6.0) days in patients with delayed recovery in the CC and RC cohorts, respectively. The mean (SD) LOS was 5.2 (2.8) days and 6.3 (2.2) days in patients without delayed recovery in the CC and RC cohorts, respectively. There was no significant difference when examining association between percent weight change and LOS for either initial admission (r_s= -0.1409; 2-tailed P = .19) or for initial and readmission combined (r_s = -0.13532; 2-tailed P = .21) within the CC cohort.

Chemotherapy

Within the CC cohort, 31 patients (27%) had an indication for adjuvant chemotherapy. Of these, 25 of 31 (81%) started chemotherapy within 12 weeks of surgical resection, and of these, 17 of 25 patients (68%) completed chemotherapy as indicated. Within the RC cohort all 33 patients had an indication for adjuvant chemotherapy, of these 18 of 33 patients (55%) began within 12 weeks of surgical resection, and 10 of 18 (56%) completed chemotherapy as indicated.

Among the CC cohort who began but did not complete adjuvant chemotherapy, there was no significant association between completion of chemotherapy and preoperative weight loss. Of patients with ≥ 3% preoperative weight loss, 3 (43%) did not complete chemotherapy vs 3 patients (27%) without preoperative weight loss who did not complete chemotherapy as indicated (Fisher exact; P = .63). Finally, low preoperative albumin did not significantly correlate with lack of completion of adjuvant chemotherapy (Fisher exact; P = .99).

Discussion

This study highlights several important findings. There were no patients in our cohort that met ASPEN malnourishment criteria with a BMI < 18.5. Twenty percent of patients lost at least 10 lb in 6 months before the operation. Notably, patients had significant associations with adverse outcomes with less pronounced weight loss than previously noted. As has been established previously, malnourishment can be difficult to screen for, and BMI also is often an imprecise tool.¹² In the CC cohort, weight loss ≥ 3% from 6 months before surgery was significantly associated with delayed recovery, complications, and hospital readmissions. We did not identify a statistically significant effect on chemotherapy completion. However, the numerical difference was suggestive of a difference, and a type 2 error is possible due to our limited sample size.

Our findings imply that the effects of even mild malnutrition are even more profound than previously thought. Significantly, this applies to overweight and obese patients as well, as these constituted a significant fraction of our cohort. A finding of ≥ 3% weight loss at the time of CC diagnosis may provide an opportunity for a focused nutrition intervention up to the time of surgery. Second, although nutrition consultation was frequent in the inpatient setting during the hospital admission (96%-100%), rates of nutrition evaluation were as low as 15% before surgery and 12% after surgery, representing a key area for improvement and focused intervention. An optimal time for intervention and nutrition prehabilitation would be at time of diagnosis before surgery with plans for continued aggressive monitoring and subsequent follow-up. Our finding seems to provide a more sensitive tool to identify patients at risk for delayed recovery compared with the ASPEN-driven assessment. Given the simplicity and the clinical significance, our test consisting of 3% weight loss over 6 months, with its sensitivity of 57%, may be superior to the ASPEN 10-lb weight loss, with its sensitivity of 40% in our cohort.

Previous Studies

Our findings are consistent with previous studies that have demonstrated that perioperative weight loss and malnutrition are correlated with delayed recovery and complications, such as wound healing, in patients with GI cancer.^2,4,5,8 In a retrospective study of more than 7000 patients with CC, those who were overweight or obese were found to have an improved overall survival compared with other BMI categories, and those who were underweight had an increased 30-day mortality and postoperative complications.¹⁶

In another retrospective study of 3799 patients with CC, those who were overweight and obese had an improved 5-year survival rate compared with patients whose weight was normal or underweight. Outcomes were found to be stage dependent.¹⁷ In this study cohort, all patients were either overweight or obese and remained in that category even with weight loss. This may have contributed to overall improved outcomes.

Implications and Next Steps

Our study has several implications. One is that BMI criteria < 18.5 may not be a good measure for malnutrition given that about 75% of the patients in our cohort were overweight or obese and none were underweight. We also show a concrete, easily identifiable finding of percent weight change that could be addressed as an automated electronic notification and potentially identify a patient at risk and serve as a trigger for both timely and early nutrition intervention. It seems to be more sensitive than the ASPEN criterion of 10-lb weight loss in 6 months before surgery. Sensitivity is especially appealing given the ease and potential of embedding this tool in an electronic health record and the clinical importance of the consequent intervention. Preoperative as opposed to perioperative nutrition optimization at time of CC diagnosis is essential, as it may help improve postsurgical outcomes as well as oncologic outcomes, including completion of adjuvant chemotherapy. Finally, although our study found that rates of inpatient postoperative nutrition consultation were high, rates of outpatient nutrition consultation in the preoperative period were low. This represents a missed opportunity for intervention before surgery. Similarly, rates of postoperative nutrition follow-up period were low, which points to an area for improvement in longitudinal and holistic care.

We suggest modifications to nutrition intervention protocols, such as ERAS, which should start at the time of GI malignancy diagnosis.¹⁸ Other suggestions include standard involvement of nutritionists in inpatient and outpatient settings with longitudinal follow-up in the preoperative and postoperative periods and patient enrollment in a nutrition program with monitoring at time of diagnosis at the VHA. Our findings as well as previous literature suggest that the preoperative period is the most important time to intervene with regard to nutrition optimization and represents an opportunity for intensive prehabilitation. Future areas of research include incorporating other important measures of malnourishment independent of BMI into future study designs, such as sarcopenia and adipose tissue density, to better assess body composition and predict prognostic risk in CC.^18,19

Strengths and Limitations

This study is limited by its single-center, retrospective design and small sample sizes, and we acknowledge the limitations of our data set. However, the strength of this VHA-based study is that the single-payer system allows for complete capture of perioperative data as well as the opportunity for focused preoperative interventions to improve outcomes. To our knowledge, there is no currently existing literature on improving nutrition protocols at the VHA for patients with a GI malignancy. These retrospective data will help inform current gaps in quality improvement and supportive oncology as it relates to optimizing malnourishment in veterans undergoing surgical resection for their cancer.

Conclusions

In the CC cohort, weight loss of ≥ 3% from 6 months prior to time of surgery was significantly associated with delayed recovery, complications, and hospital readmissions. Our findings suggest that patients with CC undergoing surgery may benefit from an intensive, early nutrition prehabilitation. Preoperative nutrition optimization may help improve postsurgical outcomes as well as oncologic outcomes, including completion of adjuvant chemotherapy. Further research would be able to clarify these hypotheses.

In patients with gastrointestinal (GI) malignancies, malnutrition is common. In addition, it has various negative implications, including high risk for surgical complications, prolonged hospitalization, decreased quality of life (QOL), increased mortality, and poor tolerance for treatments such as chemotherapy and radiotherapy.¹

A 2014 French study of 1903 patients hospitalized for cancer reported a 39% overall prevalence of malnutrition; 39% in patients with cancers of the colon/rectum, 60% for pancreatic cancer, and 67% for cancers of the esophagus/stomach.² Malnutrition was defined as body mass index (BMI) < 18.5 for individuals aged < 75 years or BMI < 21 for individuals aged ≥ 75 years, and/or weight loss > 10% since disease onset. Malnutrition also was strongly associated with worsened performance status.

The etiology of malnutrition in GI cancers is often multifactorial. It includes systemic tumor effects, such as inflammatory mediators contributing to hypermetabolism and cachexia, local tumor-associated mechanical obstruction, GI toxicities caused by antineoplastic therapy or other medications, and psychological factors that contribute to anorexia.³ Patient-related risk factors such as older age, other chronic diseases, and history of other GI surgeries also play a role.¹

Other studies have demonstrated that malnutrition in patients with GI malignancies undergoing surgical resection is associated with high rates of severe postoperative complications, increased length of stay (LOS) and time on a ventilator for patients treated in the intensive care unit, and poor QOL in the postoperative survival period.^4-6 Several randomized controlled trials conducted in patients with GI cancers have shown that enteral and parenteral nutrition supplementations in the perioperative period improve various outcomes, such as reduction of postoperative complication rates, fewer readmissions, improved chemotherapy tolerance, and improved QOL.^7-10 Thus, in the management of patients with GI malignancies, it is highly important to implement early nutritional screening and establish a diagnosis of malnutrition to intervene and reduce postoperative morbidity and mortality.¹

However, tools and predictors of malnutrition are often imperfect. The Academy of Nutrition and Dietetics and the American Society for Parenteral and Enteral Nutrition (AND/ASPEN) weight-based criteria define malnutrition and nutritionally-at-risk as BMI < 18.5, involuntary loss of at least 10% of body weight within 6 months or 5% within 1 month, or loss of 10 lb within 6 months.¹¹ While the ASPEN criteria are often used to define malnourishment, they may not fully capture the population at risk, and there does not exist a gold-standard tool for nutritional screening. A 2002 study that performed a critical appraisal of 44 nutritional screening tools found that no single tool was fully sufficient for application, development, evaluation, and consistent screening.¹² As such, consistently screening for malnutrition to target interventions in the perioperative period for GI surgical oncology has been challenging.¹³ More recent tools such as the perioperative nutrition screen (PONS) have been validated as rapid, effective screening tools to predict postoperative outcomes.¹⁴ Additionally, implementation of perioperative nutritional protocols, such as enhanced recovery after surgery (ERAS) in colon cancer (CC) surgery, also has shown improved perioperative care and outcomes.¹⁵

Preoperative nutritional interventions have been implemented in practice and have focused mostly on the immediate perioperative period. This has been shown to improve surgical outcomes. The Veterans Health Administration (VHA) provides comprehensive care to patients in a single-payer system, allowing for capture of perioperative data and the opportunity for focused preoperative interventions to improve outcomes.

Methods

This was a retrospective record review of colorectal malignancies treated with curative intent at the Veterans Affairs Ann Arbor Healthcare System (VAAAHS) in Michigan between January 1, 2015, and December 31, 2019. We examined nutritional status, degree of longitudinal weight loss, and subsequent clinical outcomes, including delayed postoperative recovery and delays in chemotherapy in 115 patients with CC and 33 patients with rectal cancer (RC) undergoing curative surgical resection at VAAAHS. To avoid additional confounding effects of advanced cancer, only early-stage, curable disease was included. This study was approved by the VAAAHS Institutional Review Board.

Analysis

The data were described using mean (SD) for continuous variables and number and percentages for categorical variables. Where appropriate, Fisher exact test, Pearson χ² test, Spearman ρ, and Mann-Whitney U test were used for tests of significance. SAS (SAS Institute) was utilized for multivariable analysis. The significance level was P = .05 for all tests.

Results

There were 115 patients in the CC cohort and 33 in the RC cohort. The mean (SD) age at diagnosis was 70 (9.1) for CC group and 59 (1.4) for RC group (Table 1). 

Weight Trends

From 1 year to 6 months before diagnosis, 40 of 80 patients lost weight in the CC cohort (mean change, +1.9%) and 6 of 22 patients lost weight in the RC cohort (mean change, + 0.5%). From 6 months before diagnosis to time of diagnosis, 47 of 74 patients lost weight in the CC cohort (mean change, -1.5%) and 14 of 21 patients lost weight in the RC cohort (mean change, -2.5%). From time of diagnosis to time of surgery, 36 of 104 patients with CC and 14 of 32 patients with RC lost weight with a mean weight change of and +0.1% and -0.3%, respectively. In the 6 months before surgery, any amount of weight loss was observed in 58 patients (66%) in the CC group and in 12 patients (57%) in the RC group. In this time frame, in the CC cohort, 32 patients (36%) were observed to have at least 3% weight loss, and 23 (26%) were observed to have at least 5% weight loss (Table 3). 

Nutrition Consultations

In the CC group, preoperative nutrition consultations (either inpatient or outpatient) occurred in 17 patients (15%). Inpatient postoperative nutrition evaluations occurred in 110 patients (96%) (Table 5). 

In the RC group, preoperative inpatient or outpatient nutrition consultations occurred in 12 patients (36%). Eight of those occurred before initiation of neoadjuvant chemoradiotherapy. All 33 patients received an inpatient postoperative nutrition evaluation during admission. Oral or enteral nutrition supplements were prescribed 19 times (58%). Postoperative outpatient nutrition consultations occurred for 24 patients (73%). Of the 19 patients who were readmitted to the hospital, 3 (16%) had a nutrition reconsultation on readmission.

Outcomes

The primary outcomes observed were delayed recovery, hospital readmission and LOS, and completion of adjuvant chemotherapy as indicated. Delayed recovery was observed in 35 patients with CC (40%) and 21 patients with RC (64%). Multivariable analysis in the CC cohort demonstrated that weight change was significantly associated with delayed recovery. Among those with ≥ 3% weight loss in the 6-month preoperative period (the weight measurement 6 months prior to diagnosis to date of surgery), 20 patients (63%) had delayed recovery compared with 15 patients (27%) without ≥ 3% weight loss who experienced delayed recovery (χ² = 10.84; P < .001).

Weight loss of ≥ 3% in the 6-month preoperative period also was significantly associated with complications. Of patients with at least 3% preoperative weight loss, 16 (50%) experienced complications, while 8 (14%) with < 3% preoperative weight loss experienced complications (χ² = 11.20; P < .001). Notably, ≥ 3% weight loss in the 1-year preoperative period before surgery was not significantly associated with delayed recovery. Any degree of 30-day postoperative weight loss was not correlated with delayed recovery. Finally, low preoperative albumin also was not correlated with delayed recovery (Fisher exact; P = .13). Table 3 displays differences based on presence of delayed recovery in the 88 patients with CC 6 months before surgery. Of note, ≥ 10-lb weight loss in the 6 months preceding surgery also correlated with delayed recovery (P = .01).In our cohort, 3% weight loss over 6 months had a sensitivity of 57%, specificity of 77%, positive predictive value 63%, and negative predictive value 73% for delayed recovery. By comparison, a 10-lb weight loss in 6 months per ASPEN criteria had a sensitivity of 40%, specificity of 85%, positive predictive value 64%, and negative predictive value 68% for delayed recovery.

Hospital Readmissions and LOS

Hospital readmissions occurred within the first 30 days in 11 patients (10%) in the CC cohort and 12 patients (36%) in the RC cohort. Readmissions occurred between 31 and 60 days in 4 (3%) and 7 (21%) of CC and RC cohorts, respectively. The presence of ≥ 3% weight loss in the 6-month preoperative period was significantly associated with 60-day readmissions. Among those with ≥ 3% preoperative weight loss, 8 patients (25%) had readmissions within 60 days vs 3 patients (5%) without 3% preoperative weight loss who had readmissions within 60 days (Fisher exact; P = .02).

Mean (SD) LOS was 6.4 (4.7) days (range, 1-28) for patients with CC and 8.8 (5.1) days (range, 3-23) for patients with RC. Mean (SD) LOS increased to 10.2 (4.3) days and 9.7 (6.0) days in patients with delayed recovery in the CC and RC cohorts, respectively. The mean (SD) LOS was 5.2 (2.8) days and 6.3 (2.2) days in patients without delayed recovery in the CC and RC cohorts, respectively. There was no significant difference when examining association between percent weight change and LOS for either initial admission (r_s= -0.1409; 2-tailed P = .19) or for initial and readmission combined (r_s = -0.13532; 2-tailed P = .21) within the CC cohort.

Chemotherapy

Within the CC cohort, 31 patients (27%) had an indication for adjuvant chemotherapy. Of these, 25 of 31 (81%) started chemotherapy within 12 weeks of surgical resection, and of these, 17 of 25 patients (68%) completed chemotherapy as indicated. Within the RC cohort all 33 patients had an indication for adjuvant chemotherapy, of these 18 of 33 patients (55%) began within 12 weeks of surgical resection, and 10 of 18 (56%) completed chemotherapy as indicated.

Among the CC cohort who began but did not complete adjuvant chemotherapy, there was no significant association between completion of chemotherapy and preoperative weight loss. Of patients with ≥ 3% preoperative weight loss, 3 (43%) did not complete chemotherapy vs 3 patients (27%) without preoperative weight loss who did not complete chemotherapy as indicated (Fisher exact; P = .63). Finally, low preoperative albumin did not significantly correlate with lack of completion of adjuvant chemotherapy (Fisher exact; P = .99).

Discussion

This study highlights several important findings. There were no patients in our cohort that met ASPEN malnourishment criteria with a BMI < 18.5. Twenty percent of patients lost at least 10 lb in 6 months before the operation. Notably, patients had significant associations with adverse outcomes with less pronounced weight loss than previously noted. As has been established previously, malnourishment can be difficult to screen for, and BMI also is often an imprecise tool.¹² In the CC cohort, weight loss ≥ 3% from 6 months before surgery was significantly associated with delayed recovery, complications, and hospital readmissions. We did not identify a statistically significant effect on chemotherapy completion. However, the numerical difference was suggestive of a difference, and a type 2 error is possible due to our limited sample size.

Our findings imply that the effects of even mild malnutrition are even more profound than previously thought. Significantly, this applies to overweight and obese patients as well, as these constituted a significant fraction of our cohort. A finding of ≥ 3% weight loss at the time of CC diagnosis may provide an opportunity for a focused nutrition intervention up to the time of surgery. Second, although nutrition consultation was frequent in the inpatient setting during the hospital admission (96%-100%), rates of nutrition evaluation were as low as 15% before surgery and 12% after surgery, representing a key area for improvement and focused intervention. An optimal time for intervention and nutrition prehabilitation would be at time of diagnosis before surgery with plans for continued aggressive monitoring and subsequent follow-up. Our finding seems to provide a more sensitive tool to identify patients at risk for delayed recovery compared with the ASPEN-driven assessment. Given the simplicity and the clinical significance, our test consisting of 3% weight loss over 6 months, with its sensitivity of 57%, may be superior to the ASPEN 10-lb weight loss, with its sensitivity of 40% in our cohort.

Previous Studies

Our findings are consistent with previous studies that have demonstrated that perioperative weight loss and malnutrition are correlated with delayed recovery and complications, such as wound healing, in patients with GI cancer.^2,4,5,8 In a retrospective study of more than 7000 patients with CC, those who were overweight or obese were found to have an improved overall survival compared with other BMI categories, and those who were underweight had an increased 30-day mortality and postoperative complications.¹⁶

In another retrospective study of 3799 patients with CC, those who were overweight and obese had an improved 5-year survival rate compared with patients whose weight was normal or underweight. Outcomes were found to be stage dependent.¹⁷ In this study cohort, all patients were either overweight or obese and remained in that category even with weight loss. This may have contributed to overall improved outcomes.

Implications and Next Steps

Our study has several implications. One is that BMI criteria < 18.5 may not be a good measure for malnutrition given that about 75% of the patients in our cohort were overweight or obese and none were underweight. We also show a concrete, easily identifiable finding of percent weight change that could be addressed as an automated electronic notification and potentially identify a patient at risk and serve as a trigger for both timely and early nutrition intervention. It seems to be more sensitive than the ASPEN criterion of 10-lb weight loss in 6 months before surgery. Sensitivity is especially appealing given the ease and potential of embedding this tool in an electronic health record and the clinical importance of the consequent intervention. Preoperative as opposed to perioperative nutrition optimization at time of CC diagnosis is essential, as it may help improve postsurgical outcomes as well as oncologic outcomes, including completion of adjuvant chemotherapy. Finally, although our study found that rates of inpatient postoperative nutrition consultation were high, rates of outpatient nutrition consultation in the preoperative period were low. This represents a missed opportunity for intervention before surgery. Similarly, rates of postoperative nutrition follow-up period were low, which points to an area for improvement in longitudinal and holistic care.

We suggest modifications to nutrition intervention protocols, such as ERAS, which should start at the time of GI malignancy diagnosis.¹⁸ Other suggestions include standard involvement of nutritionists in inpatient and outpatient settings with longitudinal follow-up in the preoperative and postoperative periods and patient enrollment in a nutrition program with monitoring at time of diagnosis at the VHA. Our findings as well as previous literature suggest that the preoperative period is the most important time to intervene with regard to nutrition optimization and represents an opportunity for intensive prehabilitation. Future areas of research include incorporating other important measures of malnourishment independent of BMI into future study designs, such as sarcopenia and adipose tissue density, to better assess body composition and predict prognostic risk in CC.^18,19

Strengths and Limitations

This study is limited by its single-center, retrospective design and small sample sizes, and we acknowledge the limitations of our data set. However, the strength of this VHA-based study is that the single-payer system allows for complete capture of perioperative data as well as the opportunity for focused preoperative interventions to improve outcomes. To our knowledge, there is no currently existing literature on improving nutrition protocols at the VHA for patients with a GI malignancy. These retrospective data will help inform current gaps in quality improvement and supportive oncology as it relates to optimizing malnourishment in veterans undergoing surgical resection for their cancer.

Conclusions

In the CC cohort, weight loss of ≥ 3% from 6 months prior to time of surgery was significantly associated with delayed recovery, complications, and hospital readmissions. Our findings suggest that patients with CC undergoing surgery may benefit from an intensive, early nutrition prehabilitation. Preoperative nutrition optimization may help improve postsurgical outcomes as well as oncologic outcomes, including completion of adjuvant chemotherapy. Further research would be able to clarify these hypotheses.

In the era of multidrug resistant organisms spreading to healthcare facilities, as well as in the community, prevention of healthcare-associated infections (HAIs) has become one of the most important issues in the world. HAIs impact morbidity and mortality of patients, increase healthcare costs,^1,2 and are associated with a longer length of stay in the hospital.^3,4 In Japan, HAIs are a salient problem; more than 9% of patients admitted to the intensive care unit (ICU) developed an infection during their ICU stay,⁵ and the numbers of multidrug resistant organism isolates causing HAIs have been increasing annually.⁶

Hand hygiene is the most important strategy for preventing the spread of MDROs and reducing HAIs.⁷ Heightened attention to hand hygiene has occurred because of the recent global outbreak of coronavirus disease 2019 (COVID-19), which first appeared in Wuhan, China.⁸ Because no proven antiviral or vaccine is currently available for the disease, hand hygiene, appropriate cough etiquette, and physical distancing, including school closures, are the only way to prevent spread of the illness.^9,10 The virus appears to be highly contagious and spread by droplet or contact routes. The spread of COVID-19 in healthcare facilities has been significant,¹¹ and it could be a source of further spread of the disease in the community.

Unfortunately, hand hygiene adherence remains low in most settings.¹² The World Health Organization (WHO) created a strategy to improve hand hygiene adherence,¹³ which has been implemented in many countries.¹⁴ This strategy consists of five key components: (1) system change, (2) training/education, (3) evaluation and feedback, (4) reminders in the workplace, and (5) institutional safety climate.¹³ Implementing a multimodal intervention including these five elements has increased hand hygiene adherence among healthcare workers (HCWs) and appears to reduce HAIs in different locations.^15-17 Improving hand hygiene practice among HCWs is considered one of the most important ways to decrease the incidence of HAIs.^15,18,19

There are two types of practice for hand hygiene: either hand washing with soap and water or using alcohol-based hand rub (AHR). The former requires water, soap, a sink, and paper towels, whereas the latter requires only hand rub, which is easy to use and requires one-third the length of time as the former.²⁰ Therefore, AHR is strongly recommended, especially in acute and intensive care settings in hospitals, which require urgent care of patients. Importantly, previous studies demonstrated that greater use of AHR resulted in significant reductions in HAIs.^7,14

In Japan, the data related to hand hygiene adherence is limited. Previous studies at four hospitals in different regions of Japan demonstrated that hand hygiene rates were suboptimal²¹ and lower than reported adherence rates from other international studies.¹⁴ One study at three hospitals showed rates could be improved by a multimodal intervention tailored by each institution.²² A 5-year follow-up study demonstrated the sustainability of the multimodal intervention²³; however, hand hygiene adherence rates remained low at approximately 32%.

We hypothesized that perhaps focusing attention on just one single region (or prefecture) could boost hand hygiene rates. Niigata prefecture is located 200 miles north of Tokyo and is the largest prefecture facing the Japan Sea. There are five major tertiary hospitals in Niigata, and they communicate frequently and discuss infection control issues as a group. To investigate hand hygiene adherence before touching patients, and to evaluate the improvement of hand hygiene adherence induced by a multimodal intervention, we performed a pre- and postintervention study among HCWs at four of these tertiary care hospitals in Niigata.

Participating hospitals

Four tertiary care hospitals in Niigata, Japan, volunteered to participate in the study. The characteristics of the four participating hospitals are summarized in Table 1. All hospitals are public or community based. Hospital A included two units, consisting of a cardiovascular-cerebral ICU and an emergency department (ED), and Hospitals B, C, and D included various units containing surgical or medical wards, an ICU, or an ED. All four hospitals have at least one designated infection-­prevention nurse and an infection-prevention department. In addition, there is an infection control network system among the hospitals, and they communicate well to update the information related to local, domestic, or global infectious diseases through regular seminars and by distributing and exchanging electronic communication.

Preintervention

The preintervention infrastructure and existing activities to improve HCW hand hygiene in each hospital are summarized in Table 1. These activities were developed by each individual hospital and had been in place for at least 6 months before the study intervention. All hospitals used AHR and did direct observation for hand washing in designated wards or units and monitoring of AHR consumption; however, Hospital B did not have a wash basin in each room and no use of portable AHR. Preintervention hand hygiene data were collected from June to August 2018.

Intervention

To improve hand hygiene adherence, we initiated a multimodal intervention from September 2018 to February 2019 based on WHO recommendations¹³ and the findings from prior hand hygiene studies.²² Each facility was provided the same guidance on how to improve hand hygiene adherence and was asked to tailor their intervention to their settings (Table 2 and Appendix Figure). Suggested interventions included feedback regarding hand hygiene adherence observed during the preintervention period, interventions related to AHR, direct observation of and feedback regarding hand hygiene, new posters promoting hand hygiene in the workplace, a 1-month campaign for hand hygiene, seminars for HCWs related to hand hygiene, creation of a handbook for education/training, feedback regarding hand hygiene adherence during the intervention period, and others. The infection control team at each hospital designed the plans and strategies to improve hand hygiene adherence. Postintervention data were collected from February 2019 to March 2019.

Observation of Hand Hygiene Adherence

Hand hygiene adherence before patient contact was evaluated by board-certified infection control nurses. To reduce observation bias, external nurses from other participating hospitals conducted the observations. To minimize intraobserver variation, the same training as the previous study in Japan²¹ was provided. Hand hygiene observations were usually performed during the day Monday to Friday from 8 am to 1 pm because of observers’ availability.

Use of either AHR or soap and water before patient contact was defined as appropriate hand hygiene.^24,25 Hand hygiene adherence before patient contact for each provider-patient encounter was observed and recorded using a data collection form used in the previous studies.^19,26 The following information was obtained: unit name, time of initiation and completion of observations, HCW type (physician or nurse), and the type of hand hygiene (ie, AHR, hand washing with soap and water, or none). The observers kept an appropriate distance from the observed HCWs to avoid interfering with their regular clinical practice. In addition, we informed HCWs in the hospital that their clinical practices were going to be observed; however, they were not informed their hand hygiene adherence was going to be monitored.

Statistical Analysis

Overall hand hygiene adherence rates from the pre- and postintervention periods were compared based on hospitals and HCW subgroups. The Pearson’s chi-square test was used for the comparison of hand hygiene adherence rates between pre- and postintervention periods, and 95% CIs were estimated using binomial distribution. Poisson regression was used to look at changes in hand hygiene adherence with adjustment for HCW type. A two-tailed P value of <.05 was considered statistically significant. The study protocol was reviewed and approved by the ethics committees at all participating hospitals.

Overall Changes

In total, there were 2,018 and 1,630 observations of hand hygiene during the preintervention and postintervention periods, respectively. Most observations were of nurses: 1,643 of the 2,018 preintervention observations (81.4%) and 1,245 of the 1,630 postintervention observations (76.4%).

Findings from the HCW observations are summarized in Figure A. The overall postintervention hand hygiene adherence rate (548 of 1,630 observations; 33.6%; 95% CI, 31.3%-35.9%) was significantly higher than the preintervention rate (453 of 2,018 observations; 22.4%; 95% CI, 20.6%-24.3%; P < .001). This finding persisted after adjustment for the type of HCW (nurse vs physician), with proper hand hygiene adherence occurring 1.55 times more often after the intervention than before (95% CI, 1.37-1.76; P < .001). The overall improvement in hand hygiene adherence rates in the postintervention period was seen in all four hospitals (Figure B). However, the hand hygiene adherence rates of nurses in Hospitals C and D were lower than those in Hospitals A and B both before and after the intervention.

Changes by HCW Type

The rates of hand hygiene adherence in both physicians and nurses were higher in the postintervention period than in the preintervention period. However, the improvement of hand hygiene adherence among nurses—from 415 of 1,643 (25.2%) to 487 of 1,245 (39.1%) for an increase of 13.9 percentage points (95% CI,10.4-17.3)—was greater than that in physicians—from 38 of 375 (10.1%) to 61 of 385 (15.8%) for an increase of 5.7 percentage points (95% CI, 1.0-8.1; P < .001; Figure B). In general, nurse hand hygiene adherence was higher than that in physicians both in the preintervention period, with nurses at 25.2% (95% CI, 23.2%-27.4%) vs physicians at 10.1% (95% CI, 7.1%-13.2%; P < .001), and in the postintervention period, with nurses at 39.1% (95% CI, 36.4%-41.8%) vs physicians at 15.8% (95% CI, 12.2%-19.5%; P < .001).

Changes by Hospital

Overall, improvement of hand hygiene adherence was observed in all hospitals. However, the improvement rates differed in each hospital: They were 6.5 percentage points in Hospital A, 11.3 percentage points in Hospital C, 11.4 percentage points in Hospital D, and 18.4 percentage points in Hospital B. Hospital B achieved the highest postintervention adherence rates (42.6%), along with the highest improvement. The improvements of hand hygiene adherence in physicians were higher in Hospitals B (8.4 percentage points) and D (8.3 percentage points) than they were in Hospitals A (4.1 percentage points) and C (4.0 percentage points).

Interventions performed at each hospital to improve hand hygiene adherence are summarized in Table 2 and the Appendix Figure. All hospitals performed feedback of hand hygiene adherence after the preintervention period. Interventions related to AHR were frequently initiated; self-carry AHR was provided in two hospitals (Hospitals C and D), and location of AHR was moved (Hospitals B and D). In addition, new AHR products that caused less skin irritation were introduced in Hospital B. Direct observation by hospital staff (separate from our study observers) was also done as part of Hospital A and D’s improvement efforts. Other interventions included a 1-month campaign for hand hygiene including a contest for senryu (humorous 17-syllable poems; Table 2; Appendix Table), posters, seminars, and creation of a handbook related to hand hygiene. Posters emphasizing the importance of hand hygiene created by the local hospital infection control teams were put on the wall in several locations near wash basins. Seminars (1-hour lectures to emphasize the importance of hand hygiene) were provided to nurses. A 10-page hand hygiene handbook was created by one local infection control team and provided to nurses.

Our study demonstrated that the overall rate of hand hygiene adherence improved from 22.4% to 33.6% after multimodal intervention; however, the adherence rates even after intervention were suboptimal. The results were comparable with those of a previous study in Japan,²² which underscores how suboptimal HCW hand hygiene in Japan threatens patient safety. Hand hygiene among HCWs is one of the most important methods to prevent HAIs and to reduce spread of multidrug resistant organisms. High adherence has proven challenging because it requires behavior modification. We implemented WHO hand hygiene adherence strategies²⁷ and evaluated the efficacy of a multimodal intervention in hopes of finding the specific factors that could be related to behavior modification for HCWs.

We observed several important relationships between the intervention components and their improvement in hand hygiene adherence. Among the four participating hospitals, Hospital B was the most successful with improvement of hand hygiene adherence from 24.2% to 42.6%. One unique intervention for Hospital B was the introduction of new AHR products for the people who had felt uncomfortable with current products. Frequent hand washing or the use of certain AHR products could irritate skin causing dry or rough hands, which could reduce hand hygiene practices. In Japan, there are several AHR products available. Among them, a few products contain skin moisturizing elements; these products are 10%-20% higher in cost than nonmoisturizing products. The HCWs in our study stated that the new products were more comfortable to use, and they requested to introduce them as daily use products. Thus, use of a product containing a hand moisturizer may reduce some factors negatively affecting hand hygiene practice and improve adherence rates.

Although this study was unable to determine which components are definitively associated with improving hand hygiene adherence, the findings suggest initiation of multiple intervention components simultaneously may provide more motivation for change than initiating only one or two components at a time. It is also possible that certain intervention components were more beneficial than others. Consistent with a previous study, improving hand hygiene adherence cannot be simply achieved by improving infrastructure (eg, introducing portable AHR) alone, but rather depends on altering the behavior of physicians and nurses.

This study was performed at four tertiary care hospitals in Niigata that are affiliated with Niigata University. They are located closely in the region, within 100 km, have quarterly conferences, and use a mutual monitoring system related to infection prevention. The members of infection control communicate regularly, which we thought would optimize improvements in hand hygiene adherence, compared with the circumstances of previous studies. In this setting, HCWs have similar education and share knowledge related to infection control, and the effects of interventions in each hospital were equally evaluated if similar interventions were implemented. In the current study, the interventions at each hospital were similar, and there was limited variety; therefore, specific, novel interventions that could affect hand hygiene adherence significantly were difficult to find.

There are a few possible reasons why hand hygiene adherence rates were low in the current study. First, part of this study was conducted during the summer so that the consciousness and caution for hand hygiene might be lower, compared with that in winter. In general, HCWs become more cautious for hand hygiene practice when they take care of patients diagnosed with influenza or respiratory syncytial virus infection. Second, the infrastructure for hand hygiene practice in the hospitals in Japan is inadequate and not well designed. Because of safety reasons, a single dispenser of AHR is placed at the entrance of each room in general and not at each bedside. The number of private rooms is limited, and most of the rooms in wards have multiple beds per room, with no access to AHR within the room. In fact, the interventions at all four hospitals included a change in the location and/or access of AHR. Easier access to AHR is likely a key step to improving hand hygiene adherence rates. Finally, there was not an active intervention to include hospital or unit leaders. This is important given the involvement of leaders in hand hygiene practice significantly changed the hand adherence rates in a previous study.¹⁹

Given the suboptimal hand hygiene adherence rates in Japan noted in this and previous Japanese studies,^21,22 the spread of COVID-19 within the hospital setting is a concern. Transmission of COVID-19 by asymptomatic carriers has been suggested,¹¹ which emphasizes the importance of regular standard precautions with good hand hygiene practice to prevent further transmission.

Although the hand hygiene rate was suboptimal, we were able to achieve a few sustainable, structural modifications in the clinical environment after the intervention. These include adding AHR in new locations, changing the location of existing AHR to more appropriate locations, and introducing new products. These will remain in the clinical environment and will contribute to hand hygiene adherence in the future.

This study has several limitations. First, the presence of external observers in their clinical settings might have affected the behavior of HCWs.²⁸ Although they were not informed that their hand hygiene adherence was going to be monitored, the existence of an external observer in their clinical setting might have changed normal behavior. Second, the infrastructure and interventions for hand hygiene adherence before the intervention were different in each hospital, so there is a possibility that hospitals with less infrastructure for hand hygiene adherence had more room for improvement with the interventions. Third, we included observations at different units at each hospital, which might affect the results of the study because of the inclusion of different medical settings and HCWs. Fourth, the number of physician hand hygiene observations was limited: We conducted our observations between 8 am and 1 pm on weekdays because of observer availability, and many physicians visited their patients during other times of the day. Finally, we were unable to determine whether the improvements seen in each hospital were caused by specific intervention components. However, it is known that recognizing the importance of hand hygiene varies in different regions and countries in the world, and the goal for hand hygiene interventions is to establish a culture of hand hygiene practice.¹³ Further evaluation is necessary to assess sustainability.

In conclusion, a multimodal intervention to improve hand hygiene adherence successfully improved HCWs’ hand hygiene adherence in Niigata, Japan; however, the adherence rates are still relatively low compared with those reported from other countries. Further intervention is required to improve hand hygiene adherence.

In the era of multidrug resistant organisms spreading to healthcare facilities, as well as in the community, prevention of healthcare-associated infections (HAIs) has become one of the most important issues in the world. HAIs impact morbidity and mortality of patients, increase healthcare costs,^1,2 and are associated with a longer length of stay in the hospital.^3,4 In Japan, HAIs are a salient problem; more than 9% of patients admitted to the intensive care unit (ICU) developed an infection during their ICU stay,⁵ and the numbers of multidrug resistant organism isolates causing HAIs have been increasing annually.⁶

Hand hygiene is the most important strategy for preventing the spread of MDROs and reducing HAIs.⁷ Heightened attention to hand hygiene has occurred because of the recent global outbreak of coronavirus disease 2019 (COVID-19), which first appeared in Wuhan, China.⁸ Because no proven antiviral or vaccine is currently available for the disease, hand hygiene, appropriate cough etiquette, and physical distancing, including school closures, are the only way to prevent spread of the illness.^9,10 The virus appears to be highly contagious and spread by droplet or contact routes. The spread of COVID-19 in healthcare facilities has been significant,¹¹ and it could be a source of further spread of the disease in the community.

Unfortunately, hand hygiene adherence remains low in most settings.¹² The World Health Organization (WHO) created a strategy to improve hand hygiene adherence,¹³ which has been implemented in many countries.¹⁴ This strategy consists of five key components: (1) system change, (2) training/education, (3) evaluation and feedback, (4) reminders in the workplace, and (5) institutional safety climate.¹³ Implementing a multimodal intervention including these five elements has increased hand hygiene adherence among healthcare workers (HCWs) and appears to reduce HAIs in different locations.^15-17 Improving hand hygiene practice among HCWs is considered one of the most important ways to decrease the incidence of HAIs.^15,18,19

There are two types of practice for hand hygiene: either hand washing with soap and water or using alcohol-based hand rub (AHR). The former requires water, soap, a sink, and paper towels, whereas the latter requires only hand rub, which is easy to use and requires one-third the length of time as the former.²⁰ Therefore, AHR is strongly recommended, especially in acute and intensive care settings in hospitals, which require urgent care of patients. Importantly, previous studies demonstrated that greater use of AHR resulted in significant reductions in HAIs.^7,14

In Japan, the data related to hand hygiene adherence is limited. Previous studies at four hospitals in different regions of Japan demonstrated that hand hygiene rates were suboptimal²¹ and lower than reported adherence rates from other international studies.¹⁴ One study at three hospitals showed rates could be improved by a multimodal intervention tailored by each institution.²² A 5-year follow-up study demonstrated the sustainability of the multimodal intervention²³; however, hand hygiene adherence rates remained low at approximately 32%.

We hypothesized that perhaps focusing attention on just one single region (or prefecture) could boost hand hygiene rates. Niigata prefecture is located 200 miles north of Tokyo and is the largest prefecture facing the Japan Sea. There are five major tertiary hospitals in Niigata, and they communicate frequently and discuss infection control issues as a group. To investigate hand hygiene adherence before touching patients, and to evaluate the improvement of hand hygiene adherence induced by a multimodal intervention, we performed a pre- and postintervention study among HCWs at four of these tertiary care hospitals in Niigata.

Participating hospitals

Four tertiary care hospitals in Niigata, Japan, volunteered to participate in the study. The characteristics of the four participating hospitals are summarized in Table 1. All hospitals are public or community based. Hospital A included two units, consisting of a cardiovascular-cerebral ICU and an emergency department (ED), and Hospitals B, C, and D included various units containing surgical or medical wards, an ICU, or an ED. All four hospitals have at least one designated infection-­prevention nurse and an infection-prevention department. In addition, there is an infection control network system among the hospitals, and they communicate well to update the information related to local, domestic, or global infectious diseases through regular seminars and by distributing and exchanging electronic communication.

Preintervention

The preintervention infrastructure and existing activities to improve HCW hand hygiene in each hospital are summarized in Table 1. These activities were developed by each individual hospital and had been in place for at least 6 months before the study intervention. All hospitals used AHR and did direct observation for hand washing in designated wards or units and monitoring of AHR consumption; however, Hospital B did not have a wash basin in each room and no use of portable AHR. Preintervention hand hygiene data were collected from June to August 2018.

Intervention

To improve hand hygiene adherence, we initiated a multimodal intervention from September 2018 to February 2019 based on WHO recommendations¹³ and the findings from prior hand hygiene studies.²² Each facility was provided the same guidance on how to improve hand hygiene adherence and was asked to tailor their intervention to their settings (Table 2 and Appendix Figure). Suggested interventions included feedback regarding hand hygiene adherence observed during the preintervention period, interventions related to AHR, direct observation of and feedback regarding hand hygiene, new posters promoting hand hygiene in the workplace, a 1-month campaign for hand hygiene, seminars for HCWs related to hand hygiene, creation of a handbook for education/training, feedback regarding hand hygiene adherence during the intervention period, and others. The infection control team at each hospital designed the plans and strategies to improve hand hygiene adherence. Postintervention data were collected from February 2019 to March 2019.

Observation of Hand Hygiene Adherence

Hand hygiene adherence before patient contact was evaluated by board-certified infection control nurses. To reduce observation bias, external nurses from other participating hospitals conducted the observations. To minimize intraobserver variation, the same training as the previous study in Japan²¹ was provided. Hand hygiene observations were usually performed during the day Monday to Friday from 8 am to 1 pm because of observers’ availability.

Use of either AHR or soap and water before patient contact was defined as appropriate hand hygiene.^24,25 Hand hygiene adherence before patient contact for each provider-patient encounter was observed and recorded using a data collection form used in the previous studies.^19,26 The following information was obtained: unit name, time of initiation and completion of observations, HCW type (physician or nurse), and the type of hand hygiene (ie, AHR, hand washing with soap and water, or none). The observers kept an appropriate distance from the observed HCWs to avoid interfering with their regular clinical practice. In addition, we informed HCWs in the hospital that their clinical practices were going to be observed; however, they were not informed their hand hygiene adherence was going to be monitored.

Statistical Analysis

Overall hand hygiene adherence rates from the pre- and postintervention periods were compared based on hospitals and HCW subgroups. The Pearson’s chi-square test was used for the comparison of hand hygiene adherence rates between pre- and postintervention periods, and 95% CIs were estimated using binomial distribution. Poisson regression was used to look at changes in hand hygiene adherence with adjustment for HCW type. A two-tailed P value of <.05 was considered statistically significant. The study protocol was reviewed and approved by the ethics committees at all participating hospitals.

Overall Changes

In total, there were 2,018 and 1,630 observations of hand hygiene during the preintervention and postintervention periods, respectively. Most observations were of nurses: 1,643 of the 2,018 preintervention observations (81.4%) and 1,245 of the 1,630 postintervention observations (76.4%).

Findings from the HCW observations are summarized in Figure A. The overall postintervention hand hygiene adherence rate (548 of 1,630 observations; 33.6%; 95% CI, 31.3%-35.9%) was significantly higher than the preintervention rate (453 of 2,018 observations; 22.4%; 95% CI, 20.6%-24.3%; P < .001). This finding persisted after adjustment for the type of HCW (nurse vs physician), with proper hand hygiene adherence occurring 1.55 times more often after the intervention than before (95% CI, 1.37-1.76; P < .001). The overall improvement in hand hygiene adherence rates in the postintervention period was seen in all four hospitals (Figure B). However, the hand hygiene adherence rates of nurses in Hospitals C and D were lower than those in Hospitals A and B both before and after the intervention.

Changes by HCW Type

The rates of hand hygiene adherence in both physicians and nurses were higher in the postintervention period than in the preintervention period. However, the improvement of hand hygiene adherence among nurses—from 415 of 1,643 (25.2%) to 487 of 1,245 (39.1%) for an increase of 13.9 percentage points (95% CI,10.4-17.3)—was greater than that in physicians—from 38 of 375 (10.1%) to 61 of 385 (15.8%) for an increase of 5.7 percentage points (95% CI, 1.0-8.1; P < .001; Figure B). In general, nurse hand hygiene adherence was higher than that in physicians both in the preintervention period, with nurses at 25.2% (95% CI, 23.2%-27.4%) vs physicians at 10.1% (95% CI, 7.1%-13.2%; P < .001), and in the postintervention period, with nurses at 39.1% (95% CI, 36.4%-41.8%) vs physicians at 15.8% (95% CI, 12.2%-19.5%; P < .001).

Changes by Hospital

Overall, improvement of hand hygiene adherence was observed in all hospitals. However, the improvement rates differed in each hospital: They were 6.5 percentage points in Hospital A, 11.3 percentage points in Hospital C, 11.4 percentage points in Hospital D, and 18.4 percentage points in Hospital B. Hospital B achieved the highest postintervention adherence rates (42.6%), along with the highest improvement. The improvements of hand hygiene adherence in physicians were higher in Hospitals B (8.4 percentage points) and D (8.3 percentage points) than they were in Hospitals A (4.1 percentage points) and C (4.0 percentage points).

Interventions performed at each hospital to improve hand hygiene adherence are summarized in Table 2 and the Appendix Figure. All hospitals performed feedback of hand hygiene adherence after the preintervention period. Interventions related to AHR were frequently initiated; self-carry AHR was provided in two hospitals (Hospitals C and D), and location of AHR was moved (Hospitals B and D). In addition, new AHR products that caused less skin irritation were introduced in Hospital B. Direct observation by hospital staff (separate from our study observers) was also done as part of Hospital A and D’s improvement efforts. Other interventions included a 1-month campaign for hand hygiene including a contest for senryu (humorous 17-syllable poems; Table 2; Appendix Table), posters, seminars, and creation of a handbook related to hand hygiene. Posters emphasizing the importance of hand hygiene created by the local hospital infection control teams were put on the wall in several locations near wash basins. Seminars (1-hour lectures to emphasize the importance of hand hygiene) were provided to nurses. A 10-page hand hygiene handbook was created by one local infection control team and provided to nurses.

Our study demonstrated that the overall rate of hand hygiene adherence improved from 22.4% to 33.6% after multimodal intervention; however, the adherence rates even after intervention were suboptimal. The results were comparable with those of a previous study in Japan,²² which underscores how suboptimal HCW hand hygiene in Japan threatens patient safety. Hand hygiene among HCWs is one of the most important methods to prevent HAIs and to reduce spread of multidrug resistant organisms. High adherence has proven challenging because it requires behavior modification. We implemented WHO hand hygiene adherence strategies²⁷ and evaluated the efficacy of a multimodal intervention in hopes of finding the specific factors that could be related to behavior modification for HCWs.

We observed several important relationships between the intervention components and their improvement in hand hygiene adherence. Among the four participating hospitals, Hospital B was the most successful with improvement of hand hygiene adherence from 24.2% to 42.6%. One unique intervention for Hospital B was the introduction of new AHR products for the people who had felt uncomfortable with current products. Frequent hand washing or the use of certain AHR products could irritate skin causing dry or rough hands, which could reduce hand hygiene practices. In Japan, there are several AHR products available. Among them, a few products contain skin moisturizing elements; these products are 10%-20% higher in cost than nonmoisturizing products. The HCWs in our study stated that the new products were more comfortable to use, and they requested to introduce them as daily use products. Thus, use of a product containing a hand moisturizer may reduce some factors negatively affecting hand hygiene practice and improve adherence rates.

Although this study was unable to determine which components are definitively associated with improving hand hygiene adherence, the findings suggest initiation of multiple intervention components simultaneously may provide more motivation for change than initiating only one or two components at a time. It is also possible that certain intervention components were more beneficial than others. Consistent with a previous study, improving hand hygiene adherence cannot be simply achieved by improving infrastructure (eg, introducing portable AHR) alone, but rather depends on altering the behavior of physicians and nurses.

This study was performed at four tertiary care hospitals in Niigata that are affiliated with Niigata University. They are located closely in the region, within 100 km, have quarterly conferences, and use a mutual monitoring system related to infection prevention. The members of infection control communicate regularly, which we thought would optimize improvements in hand hygiene adherence, compared with the circumstances of previous studies. In this setting, HCWs have similar education and share knowledge related to infection control, and the effects of interventions in each hospital were equally evaluated if similar interventions were implemented. In the current study, the interventions at each hospital were similar, and there was limited variety; therefore, specific, novel interventions that could affect hand hygiene adherence significantly were difficult to find.

There are a few possible reasons why hand hygiene adherence rates were low in the current study. First, part of this study was conducted during the summer so that the consciousness and caution for hand hygiene might be lower, compared with that in winter. In general, HCWs become more cautious for hand hygiene practice when they take care of patients diagnosed with influenza or respiratory syncytial virus infection. Second, the infrastructure for hand hygiene practice in the hospitals in Japan is inadequate and not well designed. Because of safety reasons, a single dispenser of AHR is placed at the entrance of each room in general and not at each bedside. The number of private rooms is limited, and most of the rooms in wards have multiple beds per room, with no access to AHR within the room. In fact, the interventions at all four hospitals included a change in the location and/or access of AHR. Easier access to AHR is likely a key step to improving hand hygiene adherence rates. Finally, there was not an active intervention to include hospital or unit leaders. This is important given the involvement of leaders in hand hygiene practice significantly changed the hand adherence rates in a previous study.¹⁹

Given the suboptimal hand hygiene adherence rates in Japan noted in this and previous Japanese studies,^21,22 the spread of COVID-19 within the hospital setting is a concern. Transmission of COVID-19 by asymptomatic carriers has been suggested,¹¹ which emphasizes the importance of regular standard precautions with good hand hygiene practice to prevent further transmission.

Although the hand hygiene rate was suboptimal, we were able to achieve a few sustainable, structural modifications in the clinical environment after the intervention. These include adding AHR in new locations, changing the location of existing AHR to more appropriate locations, and introducing new products. These will remain in the clinical environment and will contribute to hand hygiene adherence in the future.

This study has several limitations. First, the presence of external observers in their clinical settings might have affected the behavior of HCWs.²⁸ Although they were not informed that their hand hygiene adherence was going to be monitored, the existence of an external observer in their clinical setting might have changed normal behavior. Second, the infrastructure and interventions for hand hygiene adherence before the intervention were different in each hospital, so there is a possibility that hospitals with less infrastructure for hand hygiene adherence had more room for improvement with the interventions. Third, we included observations at different units at each hospital, which might affect the results of the study because of the inclusion of different medical settings and HCWs. Fourth, the number of physician hand hygiene observations was limited: We conducted our observations between 8 am and 1 pm on weekdays because of observer availability, and many physicians visited their patients during other times of the day. Finally, we were unable to determine whether the improvements seen in each hospital were caused by specific intervention components. However, it is known that recognizing the importance of hand hygiene varies in different regions and countries in the world, and the goal for hand hygiene interventions is to establish a culture of hand hygiene practice.¹³ Further evaluation is necessary to assess sustainability.

In conclusion, a multimodal intervention to improve hand hygiene adherence successfully improved HCWs’ hand hygiene adherence in Niigata, Japan; however, the adherence rates are still relatively low compared with those reported from other countries. Further intervention is required to improve hand hygiene adherence.

In the era of multidrug resistant organisms spreading to healthcare facilities, as well as in the community, prevention of healthcare-associated infections (HAIs) has become one of the most important issues in the world. HAIs impact morbidity and mortality of patients, increase healthcare costs,^1,2 and are associated with a longer length of stay in the hospital.^3,4 In Japan, HAIs are a salient problem; more than 9% of patients admitted to the intensive care unit (ICU) developed an infection during their ICU stay,⁵ and the numbers of multidrug resistant organism isolates causing HAIs have been increasing annually.⁶

Hand hygiene is the most important strategy for preventing the spread of MDROs and reducing HAIs.⁷ Heightened attention to hand hygiene has occurred because of the recent global outbreak of coronavirus disease 2019 (COVID-19), which first appeared in Wuhan, China.⁸ Because no proven antiviral or vaccine is currently available for the disease, hand hygiene, appropriate cough etiquette, and physical distancing, including school closures, are the only way to prevent spread of the illness.^9,10 The virus appears to be highly contagious and spread by droplet or contact routes. The spread of COVID-19 in healthcare facilities has been significant,¹¹ and it could be a source of further spread of the disease in the community.

Unfortunately, hand hygiene adherence remains low in most settings.¹² The World Health Organization (WHO) created a strategy to improve hand hygiene adherence,¹³ which has been implemented in many countries.¹⁴ This strategy consists of five key components: (1) system change, (2) training/education, (3) evaluation and feedback, (4) reminders in the workplace, and (5) institutional safety climate.¹³ Implementing a multimodal intervention including these five elements has increased hand hygiene adherence among healthcare workers (HCWs) and appears to reduce HAIs in different locations.^15-17 Improving hand hygiene practice among HCWs is considered one of the most important ways to decrease the incidence of HAIs.^15,18,19

There are two types of practice for hand hygiene: either hand washing with soap and water or using alcohol-based hand rub (AHR). The former requires water, soap, a sink, and paper towels, whereas the latter requires only hand rub, which is easy to use and requires one-third the length of time as the former.²⁰ Therefore, AHR is strongly recommended, especially in acute and intensive care settings in hospitals, which require urgent care of patients. Importantly, previous studies demonstrated that greater use of AHR resulted in significant reductions in HAIs.^7,14

In Japan, the data related to hand hygiene adherence is limited. Previous studies at four hospitals in different regions of Japan demonstrated that hand hygiene rates were suboptimal²¹ and lower than reported adherence rates from other international studies.¹⁴ One study at three hospitals showed rates could be improved by a multimodal intervention tailored by each institution.²² A 5-year follow-up study demonstrated the sustainability of the multimodal intervention²³; however, hand hygiene adherence rates remained low at approximately 32%.

We hypothesized that perhaps focusing attention on just one single region (or prefecture) could boost hand hygiene rates. Niigata prefecture is located 200 miles north of Tokyo and is the largest prefecture facing the Japan Sea. There are five major tertiary hospitals in Niigata, and they communicate frequently and discuss infection control issues as a group. To investigate hand hygiene adherence before touching patients, and to evaluate the improvement of hand hygiene adherence induced by a multimodal intervention, we performed a pre- and postintervention study among HCWs at four of these tertiary care hospitals in Niigata.

Participating hospitals

Four tertiary care hospitals in Niigata, Japan, volunteered to participate in the study. The characteristics of the four participating hospitals are summarized in Table 1. All hospitals are public or community based. Hospital A included two units, consisting of a cardiovascular-cerebral ICU and an emergency department (ED), and Hospitals B, C, and D included various units containing surgical or medical wards, an ICU, or an ED. All four hospitals have at least one designated infection-­prevention nurse and an infection-prevention department. In addition, there is an infection control network system among the hospitals, and they communicate well to update the information related to local, domestic, or global infectious diseases through regular seminars and by distributing and exchanging electronic communication.

Preintervention

The preintervention infrastructure and existing activities to improve HCW hand hygiene in each hospital are summarized in Table 1. These activities were developed by each individual hospital and had been in place for at least 6 months before the study intervention. All hospitals used AHR and did direct observation for hand washing in designated wards or units and monitoring of AHR consumption; however, Hospital B did not have a wash basin in each room and no use of portable AHR. Preintervention hand hygiene data were collected from June to August 2018.

Intervention

To improve hand hygiene adherence, we initiated a multimodal intervention from September 2018 to February 2019 based on WHO recommendations¹³ and the findings from prior hand hygiene studies.²² Each facility was provided the same guidance on how to improve hand hygiene adherence and was asked to tailor their intervention to their settings (Table 2 and Appendix Figure). Suggested interventions included feedback regarding hand hygiene adherence observed during the preintervention period, interventions related to AHR, direct observation of and feedback regarding hand hygiene, new posters promoting hand hygiene in the workplace, a 1-month campaign for hand hygiene, seminars for HCWs related to hand hygiene, creation of a handbook for education/training, feedback regarding hand hygiene adherence during the intervention period, and others. The infection control team at each hospital designed the plans and strategies to improve hand hygiene adherence. Postintervention data were collected from February 2019 to March 2019.

Observation of Hand Hygiene Adherence

Hand hygiene adherence before patient contact was evaluated by board-certified infection control nurses. To reduce observation bias, external nurses from other participating hospitals conducted the observations. To minimize intraobserver variation, the same training as the previous study in Japan²¹ was provided. Hand hygiene observations were usually performed during the day Monday to Friday from 8 am to 1 pm because of observers’ availability.

Use of either AHR or soap and water before patient contact was defined as appropriate hand hygiene.^24,25 Hand hygiene adherence before patient contact for each provider-patient encounter was observed and recorded using a data collection form used in the previous studies.^19,26 The following information was obtained: unit name, time of initiation and completion of observations, HCW type (physician or nurse), and the type of hand hygiene (ie, AHR, hand washing with soap and water, or none). The observers kept an appropriate distance from the observed HCWs to avoid interfering with their regular clinical practice. In addition, we informed HCWs in the hospital that their clinical practices were going to be observed; however, they were not informed their hand hygiene adherence was going to be monitored.

Statistical Analysis

Overall hand hygiene adherence rates from the pre- and postintervention periods were compared based on hospitals and HCW subgroups. The Pearson’s chi-square test was used for the comparison of hand hygiene adherence rates between pre- and postintervention periods, and 95% CIs were estimated using binomial distribution. Poisson regression was used to look at changes in hand hygiene adherence with adjustment for HCW type. A two-tailed P value of <.05 was considered statistically significant. The study protocol was reviewed and approved by the ethics committees at all participating hospitals.

Overall Changes

In total, there were 2,018 and 1,630 observations of hand hygiene during the preintervention and postintervention periods, respectively. Most observations were of nurses: 1,643 of the 2,018 preintervention observations (81.4%) and 1,245 of the 1,630 postintervention observations (76.4%).

Findings from the HCW observations are summarized in Figure A. The overall postintervention hand hygiene adherence rate (548 of 1,630 observations; 33.6%; 95% CI, 31.3%-35.9%) was significantly higher than the preintervention rate (453 of 2,018 observations; 22.4%; 95% CI, 20.6%-24.3%; P < .001). This finding persisted after adjustment for the type of HCW (nurse vs physician), with proper hand hygiene adherence occurring 1.55 times more often after the intervention than before (95% CI, 1.37-1.76; P < .001). The overall improvement in hand hygiene adherence rates in the postintervention period was seen in all four hospitals (Figure B). However, the hand hygiene adherence rates of nurses in Hospitals C and D were lower than those in Hospitals A and B both before and after the intervention.

Changes by HCW Type

The rates of hand hygiene adherence in both physicians and nurses were higher in the postintervention period than in the preintervention period. However, the improvement of hand hygiene adherence among nurses—from 415 of 1,643 (25.2%) to 487 of 1,245 (39.1%) for an increase of 13.9 percentage points (95% CI,10.4-17.3)—was greater than that in physicians—from 38 of 375 (10.1%) to 61 of 385 (15.8%) for an increase of 5.7 percentage points (95% CI, 1.0-8.1; P < .001; Figure B). In general, nurse hand hygiene adherence was higher than that in physicians both in the preintervention period, with nurses at 25.2% (95% CI, 23.2%-27.4%) vs physicians at 10.1% (95% CI, 7.1%-13.2%; P < .001), and in the postintervention period, with nurses at 39.1% (95% CI, 36.4%-41.8%) vs physicians at 15.8% (95% CI, 12.2%-19.5%; P < .001).

Changes by Hospital

Overall, improvement of hand hygiene adherence was observed in all hospitals. However, the improvement rates differed in each hospital: They were 6.5 percentage points in Hospital A, 11.3 percentage points in Hospital C, 11.4 percentage points in Hospital D, and 18.4 percentage points in Hospital B. Hospital B achieved the highest postintervention adherence rates (42.6%), along with the highest improvement. The improvements of hand hygiene adherence in physicians were higher in Hospitals B (8.4 percentage points) and D (8.3 percentage points) than they were in Hospitals A (4.1 percentage points) and C (4.0 percentage points).

Interventions performed at each hospital to improve hand hygiene adherence are summarized in Table 2 and the Appendix Figure. All hospitals performed feedback of hand hygiene adherence after the preintervention period. Interventions related to AHR were frequently initiated; self-carry AHR was provided in two hospitals (Hospitals C and D), and location of AHR was moved (Hospitals B and D). In addition, new AHR products that caused less skin irritation were introduced in Hospital B. Direct observation by hospital staff (separate from our study observers) was also done as part of Hospital A and D’s improvement efforts. Other interventions included a 1-month campaign for hand hygiene including a contest for senryu (humorous 17-syllable poems; Table 2; Appendix Table), posters, seminars, and creation of a handbook related to hand hygiene. Posters emphasizing the importance of hand hygiene created by the local hospital infection control teams were put on the wall in several locations near wash basins. Seminars (1-hour lectures to emphasize the importance of hand hygiene) were provided to nurses. A 10-page hand hygiene handbook was created by one local infection control team and provided to nurses.

Our study demonstrated that the overall rate of hand hygiene adherence improved from 22.4% to 33.6% after multimodal intervention; however, the adherence rates even after intervention were suboptimal. The results were comparable with those of a previous study in Japan,²² which underscores how suboptimal HCW hand hygiene in Japan threatens patient safety. Hand hygiene among HCWs is one of the most important methods to prevent HAIs and to reduce spread of multidrug resistant organisms. High adherence has proven challenging because it requires behavior modification. We implemented WHO hand hygiene adherence strategies²⁷ and evaluated the efficacy of a multimodal intervention in hopes of finding the specific factors that could be related to behavior modification for HCWs.

We observed several important relationships between the intervention components and their improvement in hand hygiene adherence. Among the four participating hospitals, Hospital B was the most successful with improvement of hand hygiene adherence from 24.2% to 42.6%. One unique intervention for Hospital B was the introduction of new AHR products for the people who had felt uncomfortable with current products. Frequent hand washing or the use of certain AHR products could irritate skin causing dry or rough hands, which could reduce hand hygiene practices. In Japan, there are several AHR products available. Among them, a few products contain skin moisturizing elements; these products are 10%-20% higher in cost than nonmoisturizing products. The HCWs in our study stated that the new products were more comfortable to use, and they requested to introduce them as daily use products. Thus, use of a product containing a hand moisturizer may reduce some factors negatively affecting hand hygiene practice and improve adherence rates.

Although this study was unable to determine which components are definitively associated with improving hand hygiene adherence, the findings suggest initiation of multiple intervention components simultaneously may provide more motivation for change than initiating only one or two components at a time. It is also possible that certain intervention components were more beneficial than others. Consistent with a previous study, improving hand hygiene adherence cannot be simply achieved by improving infrastructure (eg, introducing portable AHR) alone, but rather depends on altering the behavior of physicians and nurses.

This study was performed at four tertiary care hospitals in Niigata that are affiliated with Niigata University. They are located closely in the region, within 100 km, have quarterly conferences, and use a mutual monitoring system related to infection prevention. The members of infection control communicate regularly, which we thought would optimize improvements in hand hygiene adherence, compared with the circumstances of previous studies. In this setting, HCWs have similar education and share knowledge related to infection control, and the effects of interventions in each hospital were equally evaluated if similar interventions were implemented. In the current study, the interventions at each hospital were similar, and there was limited variety; therefore, specific, novel interventions that could affect hand hygiene adherence significantly were difficult to find.

There are a few possible reasons why hand hygiene adherence rates were low in the current study. First, part of this study was conducted during the summer so that the consciousness and caution for hand hygiene might be lower, compared with that in winter. In general, HCWs become more cautious for hand hygiene practice when they take care of patients diagnosed with influenza or respiratory syncytial virus infection. Second, the infrastructure for hand hygiene practice in the hospitals in Japan is inadequate and not well designed. Because of safety reasons, a single dispenser of AHR is placed at the entrance of each room in general and not at each bedside. The number of private rooms is limited, and most of the rooms in wards have multiple beds per room, with no access to AHR within the room. In fact, the interventions at all four hospitals included a change in the location and/or access of AHR. Easier access to AHR is likely a key step to improving hand hygiene adherence rates. Finally, there was not an active intervention to include hospital or unit leaders. This is important given the involvement of leaders in hand hygiene practice significantly changed the hand adherence rates in a previous study.¹⁹

Given the suboptimal hand hygiene adherence rates in Japan noted in this and previous Japanese studies,^21,22 the spread of COVID-19 within the hospital setting is a concern. Transmission of COVID-19 by asymptomatic carriers has been suggested,¹¹ which emphasizes the importance of regular standard precautions with good hand hygiene practice to prevent further transmission.

Although the hand hygiene rate was suboptimal, we were able to achieve a few sustainable, structural modifications in the clinical environment after the intervention. These include adding AHR in new locations, changing the location of existing AHR to more appropriate locations, and introducing new products. These will remain in the clinical environment and will contribute to hand hygiene adherence in the future.

This study has several limitations. First, the presence of external observers in their clinical settings might have affected the behavior of HCWs.²⁸ Although they were not informed that their hand hygiene adherence was going to be monitored, the existence of an external observer in their clinical setting might have changed normal behavior. Second, the infrastructure and interventions for hand hygiene adherence before the intervention were different in each hospital, so there is a possibility that hospitals with less infrastructure for hand hygiene adherence had more room for improvement with the interventions. Third, we included observations at different units at each hospital, which might affect the results of the study because of the inclusion of different medical settings and HCWs. Fourth, the number of physician hand hygiene observations was limited: We conducted our observations between 8 am and 1 pm on weekdays because of observer availability, and many physicians visited their patients during other times of the day. Finally, we were unable to determine whether the improvements seen in each hospital were caused by specific intervention components. However, it is known that recognizing the importance of hand hygiene varies in different regions and countries in the world, and the goal for hand hygiene interventions is to establish a culture of hand hygiene practice.¹³ Further evaluation is necessary to assess sustainability.

In conclusion, a multimodal intervention to improve hand hygiene adherence successfully improved HCWs’ hand hygiene adherence in Niigata, Japan; however, the adherence rates are still relatively low compared with those reported from other countries. Further intervention is required to improve hand hygiene adherence.

Millions of patients use urinary collection devices. For men, both indwelling and condom-style urinary catheters (known as “external catheters”) are commonly used. National infection prevention guidelines recommend condom catheters as a preferred alternative to indwelling catheters for patients without urinary retention^1,2 to reduce the risk of catheter-associated urinary tract infection (UTI). Unfortunately, little outcome data comparing condom catheters with indwelling urethral catheters exists. We therefore assessed the incidence of infectious and noninfectious complications in condom catheter and indwelling urethral catheter users.

Study Overview

As part of a larger prospective, observational study,³ we compared complications in patients who received a condom catheter during hospitalization with those in patients who received an indwelling urethral catheter. Hospitalized patients with either a condom catheter or indwelling urethral catheter were identified at two Veterans Affairs (VA) medical centers and followed for 30 days after initial catheter placement. Patient-reported data were collected during in-person patient interviews at baseline (within three days of catheter placement), and by in-person or phone interviews at 14 days and 30 days postplacement (Supplementary Appendix A and B). Questions were primarily closed-ended, except for a final question inviting open comments. Information about the catheter and any reported complications was also collected from electronic medical record documentation for each patient. Institutional review board approval was received from both participating study sites.

Data Collection and Inclusion Criteria

Hospitalized patients who had a condom or indwelling urethral catheter placed were eligible to participate if they met the following criteria: (1) were hospitalized on an acute care unit; (2) had a new condom catheter or indwelling urethral catheter placed during this hospital stay that was not present on admission; (3) had a device in place for three days or less; (4) were at least 18 years old; and (5) were able to speak English. Patients were excluded if they: (1) did not have the capacity to give consent or participate in the interview/assessment process; (2) refused to provide written informed consent to participate; or (3) had previously participated in this project.

As the larger study was focused on indwelling urethral catheter users, participants with a condom catheter were recruited from only one facility, while those with an indwelling urethral catheter were recruited from both hospitals. Indwelling catheter patients that had a possible contraindication to condom catheter use (such as urinary retention or perioperative use for a surgical procedure) were excluded to make the groups comparable. Any indication for condom catheterization was permitted.

Information about catheter-related complications was collected from two sources: directly from patients and through medical record review. Patients were interviewed at baseline and approximately 14 days and 30 days after catheter placement. The follow-up assessments asked patients about their symptoms and experience over the previous two weeks. We also conducted a medical record review covering the 30 days after initial catheter placement.

Study Measures

A patient was considered to have an infectious complication in the medical record review if a medical professional documented a UTI (for condom catheter patients) or catheter-associated UTI (for indwelling urethral catheter patients) in the medical record. Patients who either reported being told they had a UTI or reported they had fever, chills, burning with urination, urinary frequency, urinary urgency, or other symptoms suggestive of an infection that required the patient to see a doctor were considered to have a self-reported infectious complication. Noninfectious complications included symptoms such as pain or discomfort, trauma, a sense of urgency or bladder spasms, blood in their urine, leaking urine after catheter removal, and difficulty with starting or stopping a urine stream. Secondary outcomes focused on patient perspectives about their devices, including sexual function.

Data Analysis

The primary outcome was the percentage of patients who experienced a complication related to a urinary catheter during the 30 days after the catheter was initially placed. Comparisons by group—condom versus indwelling catheter—were conducted using chi-square tests (Fisher’s exact test when necessary) for categorical variables and the Student’s t-test for continuous variables. All analyses were performed using SAS (Cary, North Carolina). All statistical tests were two-sided with alpha set to .05.

RESULTS

Of the 76 patients invited to participate after having a condom catheter placed, 49 consented (64.5%). Of those, 36 had sufficient data for inclusion in this analysis. The comparison group consisted of 44 patients with an indwelling urethral catheter. There were no statistically significant differences between the two groups in terms of age, race, or ethnicity (Table 1). There were statistically significant differences in patient-reported reasons for catheter placement, but these were due to the exclusion criteria used for indwelling urethral catheter patients.

Both patient-reported and clinician-reported (ie, recorded in the patient’s medical record) outcomes are described in Table 2. In total, 80.6% of condom catheter users reported experiencing at least one catheter-related complication during the month after initial catheter placement compared with 88.6% of indwelling catheter users (P = .32). A similar number of condom catheter patients and indwelling urethral catheter patients experienced an infectious complication according to both self-report data (8.3% condom, 6.8% indwelling; P = .99) and medical record review (11.1% condom, 6.8% indwelling; P = .69).

At least one noninfectious complication was identified in 77.8% of condom catheter patients (28 of 36) and 88.6% of indwelling urethral catheter patients (39 of 44) using combined self-report and medical record review data (P = .19); most of these were based on self-reported data. Significantly fewer condom catheter patients reported complications during placement (eg, pain, discomfort, bleeding, or other trauma) compared with those with indwelling catheters (13.9% vs 43.2%, P < .001). Pain, discomfort, bleeding, or other trauma during catheter removal were commonly reported by both condom catheter and indwelling urethral catheter patients (40.9% vs 42.1%, respectively; P = .99).

Patient-reported noninfectious complications were often not documented in the medical record: 75.0% of condom catheter patients and 86.4% of indwelling catheter patients reported complications, in comparison with the 25.0% of condom catheter patients and 27.3% of indwelling urethral catheter patients with noninfectious complications identified during medical record review.

 

 

DISCUSSION

Our study revealed three important findings. First, noninfectious complications greatly outnumbered infectious complications, regardless of the device type. Second, condom catheter users reported significantly less pain related to placement of their device compared with the indwelling urethral catheter group. Finally, many patients reported complications that were not documented in the medical record.

The only randomized trial comparing these devices enrolled 75 men hospitalized at a single VA medical center and found that using a condom catheter rather than an indwelling catheter in patients without urinary retention lowered the composite endpoint of bacteriuria, symptomatic UTI, or death.⁴ Additionally, patients in this trial reported that the condom catheter was significantly more comfortable (90% vs 58%; P = .02) and less painful (5% vs 36%; P = .02) than the indwelling catheter,⁴ supporting a previous study in hospitalized male Veterans.⁵

Importantly, we included patient-reported complications that may be of concern to patients but inconsistently documented in the medical record. Pain associated with removal of both condom catheters and indwelling urethral catheters was reported in over 40% in both groups but was not documented in the medical record. One patient with a condom catheter described removal this way: “It got stuck on my hair, so was hard to get off…” Condom catheters also posed some issues with staying in place as has been previously described.⁶ As one condom catheter user said: “When I was laying down it was okay, but every time I moved around…it would slide off.”

Recent efforts to reduce catheter-associated UTI,^7-9 which have focused on reducing the use of indwelling urethral catheters,^10,11 have been relatively successful. Clinical policy makers should consider similar efforts to address the noninfectious harms of both catheter types. Such efforts could include further decreasing any type of catheter use along with improved training of those placing such devices.¹² Substantial improvement will require a systematic approach to surveilling noninfectious complications of both types of urinary catheters.

Our study has several limitations. First, we conducted the study at two VA hospitals; therefore, the results may not be generalizable to a non-VA population. Second, we only included 80 patients because we recruited a limited number of condom catheter users. Third, although we tried to compare two similar groups of patients, it is possible that indwelling catheter patients had greater morbidity, which necessitated the use of an indwelling catheter instead of a condom catheter. Finally, we found a large discrepancy between what our patients reported and the information gained from a review of their medical records. While complications reported by the patient may not constitute a medically defined complication, due to the well-known phenomenon of poor documentation of catheter complications in general,¹³ we believe that what patients report is important for understanding the full scope of potential problems.

Limitations notwithstanding, we provide comparison data between condom and indwelling urethral catheters. Condom catheter users reported significantly less pain related to initial placement of their device compared with those using an indwelling urethral catheter. For both devices, patients experienced noninfectious complications much more commonly than infectious ones, underscoring the need to systematically address such complications, perhaps through a surveillance system that includes the patient’s perspective. The patient’s voice is important and necessary in view of the apparent underreporting of noninfectious harms in the medical record.

 

 

Acknowledgments

The authors thank the following individuals who assisted with data collection for the study: Laura Dillon, Jeanaya McKinley, Laura Peña, Jason Mann, Marylena Rouse, Kathy Swalwell, Suzanne Winter, Jane Wong, and Debbie Zawol.

Disclaimer

The funding sources played no role in the design, conducting, or evaluation of this study. The findings and conclusions in this manuscript are those of the authors and do not necessarily represent the official position of the Department of Veterans Affairs.

Millions of patients use urinary collection devices. For men, both indwelling and condom-style urinary catheters (known as “external catheters”) are commonly used. National infection prevention guidelines recommend condom catheters as a preferred alternative to indwelling catheters for patients without urinary retention^1,2 to reduce the risk of catheter-associated urinary tract infection (UTI). Unfortunately, little outcome data comparing condom catheters with indwelling urethral catheters exists. We therefore assessed the incidence of infectious and noninfectious complications in condom catheter and indwelling urethral catheter users.

Study Overview

As part of a larger prospective, observational study,³ we compared complications in patients who received a condom catheter during hospitalization with those in patients who received an indwelling urethral catheter. Hospitalized patients with either a condom catheter or indwelling urethral catheter were identified at two Veterans Affairs (VA) medical centers and followed for 30 days after initial catheter placement. Patient-reported data were collected during in-person patient interviews at baseline (within three days of catheter placement), and by in-person or phone interviews at 14 days and 30 days postplacement (Supplementary Appendix A and B). Questions were primarily closed-ended, except for a final question inviting open comments. Information about the catheter and any reported complications was also collected from electronic medical record documentation for each patient. Institutional review board approval was received from both participating study sites.

Data Collection and Inclusion Criteria

Hospitalized patients who had a condom or indwelling urethral catheter placed were eligible to participate if they met the following criteria: (1) were hospitalized on an acute care unit; (2) had a new condom catheter or indwelling urethral catheter placed during this hospital stay that was not present on admission; (3) had a device in place for three days or less; (4) were at least 18 years old; and (5) were able to speak English. Patients were excluded if they: (1) did not have the capacity to give consent or participate in the interview/assessment process; (2) refused to provide written informed consent to participate; or (3) had previously participated in this project.

As the larger study was focused on indwelling urethral catheter users, participants with a condom catheter were recruited from only one facility, while those with an indwelling urethral catheter were recruited from both hospitals. Indwelling catheter patients that had a possible contraindication to condom catheter use (such as urinary retention or perioperative use for a surgical procedure) were excluded to make the groups comparable. Any indication for condom catheterization was permitted.

Information about catheter-related complications was collected from two sources: directly from patients and through medical record review. Patients were interviewed at baseline and approximately 14 days and 30 days after catheter placement. The follow-up assessments asked patients about their symptoms and experience over the previous two weeks. We also conducted a medical record review covering the 30 days after initial catheter placement.

Study Measures

A patient was considered to have an infectious complication in the medical record review if a medical professional documented a UTI (for condom catheter patients) or catheter-associated UTI (for indwelling urethral catheter patients) in the medical record. Patients who either reported being told they had a UTI or reported they had fever, chills, burning with urination, urinary frequency, urinary urgency, or other symptoms suggestive of an infection that required the patient to see a doctor were considered to have a self-reported infectious complication. Noninfectious complications included symptoms such as pain or discomfort, trauma, a sense of urgency or bladder spasms, blood in their urine, leaking urine after catheter removal, and difficulty with starting or stopping a urine stream. Secondary outcomes focused on patient perspectives about their devices, including sexual function.

Data Analysis

The primary outcome was the percentage of patients who experienced a complication related to a urinary catheter during the 30 days after the catheter was initially placed. Comparisons by group—condom versus indwelling catheter—were conducted using chi-square tests (Fisher’s exact test when necessary) for categorical variables and the Student’s t-test for continuous variables. All analyses were performed using SAS (Cary, North Carolina). All statistical tests were two-sided with alpha set to .05.

RESULTS

Of the 76 patients invited to participate after having a condom catheter placed, 49 consented (64.5%). Of those, 36 had sufficient data for inclusion in this analysis. The comparison group consisted of 44 patients with an indwelling urethral catheter. There were no statistically significant differences between the two groups in terms of age, race, or ethnicity (Table 1). There were statistically significant differences in patient-reported reasons for catheter placement, but these were due to the exclusion criteria used for indwelling urethral catheter patients.

Both patient-reported and clinician-reported (ie, recorded in the patient’s medical record) outcomes are described in Table 2. In total, 80.6% of condom catheter users reported experiencing at least one catheter-related complication during the month after initial catheter placement compared with 88.6% of indwelling catheter users (P = .32). A similar number of condom catheter patients and indwelling urethral catheter patients experienced an infectious complication according to both self-report data (8.3% condom, 6.8% indwelling; P = .99) and medical record review (11.1% condom, 6.8% indwelling; P = .69).

At least one noninfectious complication was identified in 77.8% of condom catheter patients (28 of 36) and 88.6% of indwelling urethral catheter patients (39 of 44) using combined self-report and medical record review data (P = .19); most of these were based on self-reported data. Significantly fewer condom catheter patients reported complications during placement (eg, pain, discomfort, bleeding, or other trauma) compared with those with indwelling catheters (13.9% vs 43.2%, P < .001). Pain, discomfort, bleeding, or other trauma during catheter removal were commonly reported by both condom catheter and indwelling urethral catheter patients (40.9% vs 42.1%, respectively; P = .99).

Patient-reported noninfectious complications were often not documented in the medical record: 75.0% of condom catheter patients and 86.4% of indwelling catheter patients reported complications, in comparison with the 25.0% of condom catheter patients and 27.3% of indwelling urethral catheter patients with noninfectious complications identified during medical record review.

 

 

DISCUSSION

Our study revealed three important findings. First, noninfectious complications greatly outnumbered infectious complications, regardless of the device type. Second, condom catheter users reported significantly less pain related to placement of their device compared with the indwelling urethral catheter group. Finally, many patients reported complications that were not documented in the medical record.

The only randomized trial comparing these devices enrolled 75 men hospitalized at a single VA medical center and found that using a condom catheter rather than an indwelling catheter in patients without urinary retention lowered the composite endpoint of bacteriuria, symptomatic UTI, or death.⁴ Additionally, patients in this trial reported that the condom catheter was significantly more comfortable (90% vs 58%; P = .02) and less painful (5% vs 36%; P = .02) than the indwelling catheter,⁴ supporting a previous study in hospitalized male Veterans.⁵

Importantly, we included patient-reported complications that may be of concern to patients but inconsistently documented in the medical record. Pain associated with removal of both condom catheters and indwelling urethral catheters was reported in over 40% in both groups but was not documented in the medical record. One patient with a condom catheter described removal this way: “It got stuck on my hair, so was hard to get off…” Condom catheters also posed some issues with staying in place as has been previously described.⁶ As one condom catheter user said: “When I was laying down it was okay, but every time I moved around…it would slide off.”

Recent efforts to reduce catheter-associated UTI,^7-9 which have focused on reducing the use of indwelling urethral catheters,^10,11 have been relatively successful. Clinical policy makers should consider similar efforts to address the noninfectious harms of both catheter types. Such efforts could include further decreasing any type of catheter use along with improved training of those placing such devices.¹² Substantial improvement will require a systematic approach to surveilling noninfectious complications of both types of urinary catheters.

Our study has several limitations. First, we conducted the study at two VA hospitals; therefore, the results may not be generalizable to a non-VA population. Second, we only included 80 patients because we recruited a limited number of condom catheter users. Third, although we tried to compare two similar groups of patients, it is possible that indwelling catheter patients had greater morbidity, which necessitated the use of an indwelling catheter instead of a condom catheter. Finally, we found a large discrepancy between what our patients reported and the information gained from a review of their medical records. While complications reported by the patient may not constitute a medically defined complication, due to the well-known phenomenon of poor documentation of catheter complications in general,¹³ we believe that what patients report is important for understanding the full scope of potential problems.

Limitations notwithstanding, we provide comparison data between condom and indwelling urethral catheters. Condom catheter users reported significantly less pain related to initial placement of their device compared with those using an indwelling urethral catheter. For both devices, patients experienced noninfectious complications much more commonly than infectious ones, underscoring the need to systematically address such complications, perhaps through a surveillance system that includes the patient’s perspective. The patient’s voice is important and necessary in view of the apparent underreporting of noninfectious harms in the medical record.

 

 

Acknowledgments

The authors thank the following individuals who assisted with data collection for the study: Laura Dillon, Jeanaya McKinley, Laura Peña, Jason Mann, Marylena Rouse, Kathy Swalwell, Suzanne Winter, Jane Wong, and Debbie Zawol.

Disclaimer

The funding sources played no role in the design, conducting, or evaluation of this study. The findings and conclusions in this manuscript are those of the authors and do not necessarily represent the official position of the Department of Veterans Affairs.

Millions of patients use urinary collection devices. For men, both indwelling and condom-style urinary catheters (known as “external catheters”) are commonly used. National infection prevention guidelines recommend condom catheters as a preferred alternative to indwelling catheters for patients without urinary retention^1,2 to reduce the risk of catheter-associated urinary tract infection (UTI). Unfortunately, little outcome data comparing condom catheters with indwelling urethral catheters exists. We therefore assessed the incidence of infectious and noninfectious complications in condom catheter and indwelling urethral catheter users.

Study Overview

As part of a larger prospective, observational study,³ we compared complications in patients who received a condom catheter during hospitalization with those in patients who received an indwelling urethral catheter. Hospitalized patients with either a condom catheter or indwelling urethral catheter were identified at two Veterans Affairs (VA) medical centers and followed for 30 days after initial catheter placement. Patient-reported data were collected during in-person patient interviews at baseline (within three days of catheter placement), and by in-person or phone interviews at 14 days and 30 days postplacement (Supplementary Appendix A and B). Questions were primarily closed-ended, except for a final question inviting open comments. Information about the catheter and any reported complications was also collected from electronic medical record documentation for each patient. Institutional review board approval was received from both participating study sites.

Data Collection and Inclusion Criteria

Hospitalized patients who had a condom or indwelling urethral catheter placed were eligible to participate if they met the following criteria: (1) were hospitalized on an acute care unit; (2) had a new condom catheter or indwelling urethral catheter placed during this hospital stay that was not present on admission; (3) had a device in place for three days or less; (4) were at least 18 years old; and (5) were able to speak English. Patients were excluded if they: (1) did not have the capacity to give consent or participate in the interview/assessment process; (2) refused to provide written informed consent to participate; or (3) had previously participated in this project.

As the larger study was focused on indwelling urethral catheter users, participants with a condom catheter were recruited from only one facility, while those with an indwelling urethral catheter were recruited from both hospitals. Indwelling catheter patients that had a possible contraindication to condom catheter use (such as urinary retention or perioperative use for a surgical procedure) were excluded to make the groups comparable. Any indication for condom catheterization was permitted.

Information about catheter-related complications was collected from two sources: directly from patients and through medical record review. Patients were interviewed at baseline and approximately 14 days and 30 days after catheter placement. The follow-up assessments asked patients about their symptoms and experience over the previous two weeks. We also conducted a medical record review covering the 30 days after initial catheter placement.

Study Measures

A patient was considered to have an infectious complication in the medical record review if a medical professional documented a UTI (for condom catheter patients) or catheter-associated UTI (for indwelling urethral catheter patients) in the medical record. Patients who either reported being told they had a UTI or reported they had fever, chills, burning with urination, urinary frequency, urinary urgency, or other symptoms suggestive of an infection that required the patient to see a doctor were considered to have a self-reported infectious complication. Noninfectious complications included symptoms such as pain or discomfort, trauma, a sense of urgency or bladder spasms, blood in their urine, leaking urine after catheter removal, and difficulty with starting or stopping a urine stream. Secondary outcomes focused on patient perspectives about their devices, including sexual function.

Data Analysis

The primary outcome was the percentage of patients who experienced a complication related to a urinary catheter during the 30 days after the catheter was initially placed. Comparisons by group—condom versus indwelling catheter—were conducted using chi-square tests (Fisher’s exact test when necessary) for categorical variables and the Student’s t-test for continuous variables. All analyses were performed using SAS (Cary, North Carolina). All statistical tests were two-sided with alpha set to .05.

RESULTS

Of the 76 patients invited to participate after having a condom catheter placed, 49 consented (64.5%). Of those, 36 had sufficient data for inclusion in this analysis. The comparison group consisted of 44 patients with an indwelling urethral catheter. There were no statistically significant differences between the two groups in terms of age, race, or ethnicity (Table 1). There were statistically significant differences in patient-reported reasons for catheter placement, but these were due to the exclusion criteria used for indwelling urethral catheter patients.

Both patient-reported and clinician-reported (ie, recorded in the patient’s medical record) outcomes are described in Table 2. In total, 80.6% of condom catheter users reported experiencing at least one catheter-related complication during the month after initial catheter placement compared with 88.6% of indwelling catheter users (P = .32). A similar number of condom catheter patients and indwelling urethral catheter patients experienced an infectious complication according to both self-report data (8.3% condom, 6.8% indwelling; P = .99) and medical record review (11.1% condom, 6.8% indwelling; P = .69).

At least one noninfectious complication was identified in 77.8% of condom catheter patients (28 of 36) and 88.6% of indwelling urethral catheter patients (39 of 44) using combined self-report and medical record review data (P = .19); most of these were based on self-reported data. Significantly fewer condom catheter patients reported complications during placement (eg, pain, discomfort, bleeding, or other trauma) compared with those with indwelling catheters (13.9% vs 43.2%, P < .001). Pain, discomfort, bleeding, or other trauma during catheter removal were commonly reported by both condom catheter and indwelling urethral catheter patients (40.9% vs 42.1%, respectively; P = .99).

Patient-reported noninfectious complications were often not documented in the medical record: 75.0% of condom catheter patients and 86.4% of indwelling catheter patients reported complications, in comparison with the 25.0% of condom catheter patients and 27.3% of indwelling urethral catheter patients with noninfectious complications identified during medical record review.

 

 

DISCUSSION

Our study revealed three important findings. First, noninfectious complications greatly outnumbered infectious complications, regardless of the device type. Second, condom catheter users reported significantly less pain related to placement of their device compared with the indwelling urethral catheter group. Finally, many patients reported complications that were not documented in the medical record.

The only randomized trial comparing these devices enrolled 75 men hospitalized at a single VA medical center and found that using a condom catheter rather than an indwelling catheter in patients without urinary retention lowered the composite endpoint of bacteriuria, symptomatic UTI, or death.⁴ Additionally, patients in this trial reported that the condom catheter was significantly more comfortable (90% vs 58%; P = .02) and less painful (5% vs 36%; P = .02) than the indwelling catheter,⁴ supporting a previous study in hospitalized male Veterans.⁵

Importantly, we included patient-reported complications that may be of concern to patients but inconsistently documented in the medical record. Pain associated with removal of both condom catheters and indwelling urethral catheters was reported in over 40% in both groups but was not documented in the medical record. One patient with a condom catheter described removal this way: “It got stuck on my hair, so was hard to get off…” Condom catheters also posed some issues with staying in place as has been previously described.⁶ As one condom catheter user said: “When I was laying down it was okay, but every time I moved around…it would slide off.”

Recent efforts to reduce catheter-associated UTI,^7-9 which have focused on reducing the use of indwelling urethral catheters,^10,11 have been relatively successful. Clinical policy makers should consider similar efforts to address the noninfectious harms of both catheter types. Such efforts could include further decreasing any type of catheter use along with improved training of those placing such devices.¹² Substantial improvement will require a systematic approach to surveilling noninfectious complications of both types of urinary catheters.

Our study has several limitations. First, we conducted the study at two VA hospitals; therefore, the results may not be generalizable to a non-VA population. Second, we only included 80 patients because we recruited a limited number of condom catheter users. Third, although we tried to compare two similar groups of patients, it is possible that indwelling catheter patients had greater morbidity, which necessitated the use of an indwelling catheter instead of a condom catheter. Finally, we found a large discrepancy between what our patients reported and the information gained from a review of their medical records. While complications reported by the patient may not constitute a medically defined complication, due to the well-known phenomenon of poor documentation of catheter complications in general,¹³ we believe that what patients report is important for understanding the full scope of potential problems.

Limitations notwithstanding, we provide comparison data between condom and indwelling urethral catheters. Condom catheter users reported significantly less pain related to initial placement of their device compared with those using an indwelling urethral catheter. For both devices, patients experienced noninfectious complications much more commonly than infectious ones, underscoring the need to systematically address such complications, perhaps through a surveillance system that includes the patient’s perspective. The patient’s voice is important and necessary in view of the apparent underreporting of noninfectious harms in the medical record.

 

 

Acknowledgments

The authors thank the following individuals who assisted with data collection for the study: Laura Dillon, Jeanaya McKinley, Laura Peña, Jason Mann, Marylena Rouse, Kathy Swalwell, Suzanne Winter, Jane Wong, and Debbie Zawol.

Disclaimer

The funding sources played no role in the design, conducting, or evaluation of this study. The findings and conclusions in this manuscript are those of the authors and do not necessarily represent the official position of the Department of Veterans Affairs.

Abstract

• Background: Although transfusion guidelines have changed considerably over the past 2 decades, the adoption of patient blood management programs has not been fully realized across hospitals in the United States.
• Objective: To evaluate trends in red blood cell (RBC), platelet, and plasma transfusion at 3 Veterans Health Administration (VHA) hospitals from 2000 through 2010.
• Methods: Data from all hospitalizations were collected from January 2000 through December 2010. Blood bank data (including the type and volume of products administered) were available electronically from each hospital. These files were linked to inpatient data, which included ICD-9-CM diagnoses (principal and secondary) and procedures during hospitalization. Statistical analyses were conducted using generalized linear models to evaluate trends over time. The unit of observation was hospitalization, with categorization by type.
• Results: There were 176,521 hospitalizations in 69,621 patients; of these, 13.6% of hospitalizations involved transfusion of blood products (12.7% RBCs, 1.4% platelets, 3.0% plasma). Transfusion occurred in 25.2% of surgical and 5.3% of medical hospitalizations. Transfusion use peaked in 2002 for surgical hospitalizations and declined afterwards (P < 0.001). There was no significant change in transfusion use over time (P = 0.126) for medical hospitalizations. In hospitalizations that involved transfusions, there was a 20.3% reduction in the proportion of hospitalizations in which ≥ 3 units of RBCs were given (from 51.7% to 41.1%; P < 0.001) and a 73.6% increase when 1 RBC unit was given (from 8.0% to 13.8%; P < 0.001) from 2000-2010. Of the hospitalizations with RBC transfusion, 9.6% involved the use of 1 unit over the entire study period. The most common principal diagnoses for medical patients receiving transfusion were anemia, malignancy, heart failure, pneumonia and renal failure. Over time, transfusion utilization increased in patients who were admitted for infection (P = 0.009).
• Conclusion: Blood transfusions in 3 VHA hospitals have decreased over time for surgical patients but remained the same for medical patients. Further study examining appropriateness of blood products in medical patients appears necessary.

Key words: Transfusion; red blood cells; plasma; platelets; veterans.

Transfusion practices during hospitalization have changed considerably over the past 2 decades. Guided by evidence from randomized controlled trials, patient blood management programs have been expanded [1]. Such programs include recommendations regarding minimization of blood loss during surgery, prevention and treatment of anemia, strategies for reducing transfusions in both medical and surgical patients, improved blood utilization, education of health professionals, and standardization of blood management-related metrics [2]. Some of the guidelines have been incorporated into the Choosing Wisely initiative of the American Board of Internal Medicine Foundation, including: (a) don’t transfuse more units of blood than absolutely necessary, (b) don’t transfuse red blood cells for iron deficiency without hemodynamic instability, (c) don’t routinely use blood products to reverse warfarin, and (d) don’t perform serial blood counts on clinically stable patients [3]. Although there has been growing interest in blood management, only 37.8% of the 607 AABB (formerly, American Association of Blood Banks) facilities in the United States reported having a patient blood management program in 2013 [2].

While the importance of blood safety is recognized, data regarding the overall trends in practices are conflicting. A study using the Nationwide Inpatient Sample indicated that there was a 5.6% annual mean increase in the transfusion of blood products from 2002 to 2011 in the United States [4]. This contrasts with the experience of Kaiser Permanente in Northern California, in which the incidence of RBC transfusion decreased by 3.2% from 2009 to 2013 [5]. A decline in rates of intraoperative transfusion was also reported among elderly veterans in the United States from 1997 to 2009 [6].

We conducted a study in hospitalized veterans with 2 main objectives: (a) to evaluate trends in utilization of red blood cells (RBCs), platelets, and plasma over time, and (b) to identify those groups of veterans who received specific blood products. We were particularly interested in transfusion use in medical patients.

Methods

Participants were hospitalized veterans at 3 Department of Veterans Affairs (VA) medical centers. Data from all hospitalizations were collected from January 2000 through December 2010. Blood bank data (including the type and volume of products administered) were available electronically from each hospital. These files were linked to inpatient data, which included ICD-9-CM diagnoses (principal and secondary) and procedures during hospitalization.

Statistical analyses were conducted using generalized linear models to evaluate trends over time. The unit of observation was hospitalization, with categorization by type. Surgical hospitalizations were defined as admissions in which any surgical procedure occurred, whereas medical hospitalizations were defined as admissions without any surgery. Alpha was set at 0.05, 2-tailed. All analyses were conducted in Stata/MP 14.1 (StataCorp, College Station, TX). The study received institutional review board approval from the VA Ann Arbor Healthcare System.

Results

From 2000 through 2010, there were 176,521 hospitalizations in 69,621 patients. Within this cohort, 6% were < 40 years of age, 66% were 40 to 69 years of age, and 28% were 70 years or older at the time of admission. In this cohort, 96% of patients were male. Overall, 13.6% of all hospitalizations involved transfusion of a blood product (12.7% RBCs, 1.4% platelets, 3.0% plasma).

Transfusion occurred in 25.2% of surgical hospitalizations and 5.3% of medical hospitalizations. For surgical hospitalizations, transfusion use peaked in 2002 (when 30.9% of the surgical hospitalizations involved a trans-fusion) and significantly declined afterwards (P < 0.001). By 2010, 22.5% of the surgical hospitalizations involved a transfusion. Most of the surgeries where blood products were transfused involved cardiovascular procedures. For medical hospitalizations only, there was no significant change in transfusion use over time, either from 2000 to 2010 (P = 0.126) or from 2002 to 2010 (P = 0.072). In 2010, 5.2% of the medical hospitalizations involved a transfusion.

Rates of transfusion varied by principal diagnosis (Figure 1). For patients admitted with a principal diagnosis of infection (n = 20,981 hospitalizations), there was an increase in the percentage of hospitalizations in which transfusions (RBCs, platelet, plasma) were administered over time (P = 0.009) (Figure 1). For patients admitted with a principal diagnosis of malignancy (n = 12,904 hospitalizations), cardiovascular disease (n = 40,324 hospitalizations), and other diagnoses (n = 102,312 hospitalizations), there were no significant linear trends over the entire study period (P = 0.191, P = 0.052, P = 0.314, respectively). Rather, blood utilization peaked in year 2002 and significantly declined afterwards for patients admitted for malignancy (P < 0.001) and for cardiovascular disease (P < 0.001).

The most common principal diagnoses for medical patients receiving any transfusion (RBCs, platelet, plasma) are listed in Table 1. For medical patients with a principal diagnosis of anemia, 88% of hospitalizations involved a transfusion (Table 1). Transfusion occurred in 6% to 11% of medical hospitalizations with malignancies, heart failure, pneumonia or renal failure (Table 1). A considerable proportion (43%) of medical patients with gastrointestinal hemorrhage received a transfusion.

Discussion

We also observed secular trends in the volume of RBCs administered. There was an increase in the percentage of hospitalizations in which 1 or 2 RBC units were used and a decline in transfusion of 3 or more units. The reduction in the use of 3 or more RBC units may reflect the adoption and integration of recommendations in patient blood management by clinicians,

which encourage assessment of the patients’ symptoms in determining whether additional units are necessary [7]. Such guidelines also endorse the avoidance of routine
administration of 2 units of RBCs if 1 unit is sufficient [8]. We have previously shown that, after coronary artery bypass grafting, 2 RBC units doubled the risk of pneumonia [9]; additional analyses indicated that 1 or 2 units of RBCs were associated with increased postoperative morbidity [10]. In addition, our previous research indicated that the probability of infection increased considerably between 1 and 2 RBC units, with a more gradual increase beyond 2 units [11]. With this evidence in mind, some studies at single sites have reported that there was a dramatic decline from 2 RBC units before initiation of patient blood management programs to 1 unit after the programs were implemented [12,13].

Medical patients who received a transfusion were often admitted for reason of anemia, cancer, organ failure, or pneumonia. Some researchers are now reporting that blood use, at certain sites, is becoming more common in medical rather than surgical patients, which may be due to an expansion of patient blood management procedures in surgery [16]. There are a substantial number of patient blood management programs among surgical specialties and their adoption has expanded [17]. Although there are fewer patient blood management programs in the nonsurgical setting, some have been targeted to internal medicine physicians and specifically, to hospitalists [1,18]. For example, a toolkit from the Society of Hospital Medicine centers on anemia management and includes anemia assessment, treatment, evaluation of RBC transfusion risk, blood conservation, optimization of coagulation, and patient-centered decision-making [19]. Additionally, bundling of patient blood management strategies has been launched to help encourage a wider adoption of such programs [20].

While guidelines regarding use of RBCs are becoming increasingly recognized, recommendations for the use of platelets and plasma are hampered by the paucity of evidence from randomized controlled trials [21,22]. There is moderate-quality evidence for the use of platelets with therapy-induced hypoproliferative thrombocytopenia in hospitalized patients [21], but low quality evidence for other uses. Moreover, a recent review of plasma transfusion in bleeding patients found no randomized controlled trials on plasma use in hospitalized patients, although several trials were currently underway [22].

Our findings need to be considered in the context of the following limitations. The data were from 3 VA hospitals, so the results may not reflect patterns of usage at other hospitals. However, AABB reports that there has been a general decrease in transfusion of allogeneic whole blood and RBC units since 2008 at the AABB-affiliated sites in the United States [2]; this is similar to the pattern that we observed in surgical patients. In addition, we report an overall view of trends without having details regarding which specific factors influenced changes in transfusion during this 11-year period. It is possible that the severity of hospitalized patients may have changed with time which could have influenced decisions regarding the need for transfusion.

In conclusion, the use of blood products decreased in surgical patients since 2002 but remained the same in medical patients in this VA population. Transfusions increased over time for patients who were admitted to the hospital for reason of infection, but decreased since 2002 for those admitted for cardiovascular disease or cancer. The number of RBC units per hospitalization decreased over time. Additional surveillance is needed to determine whether recent evidence regarding blood management has been incorporated into clinical practice for medical patients, as we strive to deliver optimal care to our veterans.

Corresponding author: Mary A.M. Rogers, PhD, MS, Dept. of Internal Medicine, Univ. of Michigan, 016-422W NCRC, Ann Arbor, MI 48109-2800, maryroge@umich.edu.

Funding/support: Department of Veterans Affairs, Clinical Sciences Research & Development Service Merit Review Award (EPID-011-11S). The contents do not represent the views of the U.S. Department of Veterans Affairs or the U.S. Government.

Financial disclosures: None.

Author contributions: conception and design, MAMR, SS; analysis and interpretation of data, MAMR, JDB, DR, LK, SS; drafting of article, MAMR; critical revision of the article, MAMR, MTG, DR, LK, SS, VC; statistical expertise, MAMR, DR; obtaining of funding, MTG, SS, VC; administrative or technical support, MTG, LK, SS, VC; collection and assembly of data, JDB, LK.

Abstract

• Background: Although transfusion guidelines have changed considerably over the past 2 decades, the adoption of patient blood management programs has not been fully realized across hospitals in the United States.
• Objective: To evaluate trends in red blood cell (RBC), platelet, and plasma transfusion at 3 Veterans Health Administration (VHA) hospitals from 2000 through 2010.
• Methods: Data from all hospitalizations were collected from January 2000 through December 2010. Blood bank data (including the type and volume of products administered) were available electronically from each hospital. These files were linked to inpatient data, which included ICD-9-CM diagnoses (principal and secondary) and procedures during hospitalization. Statistical analyses were conducted using generalized linear models to evaluate trends over time. The unit of observation was hospitalization, with categorization by type.
• Results: There were 176,521 hospitalizations in 69,621 patients; of these, 13.6% of hospitalizations involved transfusion of blood products (12.7% RBCs, 1.4% platelets, 3.0% plasma). Transfusion occurred in 25.2% of surgical and 5.3% of medical hospitalizations. Transfusion use peaked in 2002 for surgical hospitalizations and declined afterwards (P < 0.001). There was no significant change in transfusion use over time (P = 0.126) for medical hospitalizations. In hospitalizations that involved transfusions, there was a 20.3% reduction in the proportion of hospitalizations in which ≥ 3 units of RBCs were given (from 51.7% to 41.1%; P < 0.001) and a 73.6% increase when 1 RBC unit was given (from 8.0% to 13.8%; P < 0.001) from 2000-2010. Of the hospitalizations with RBC transfusion, 9.6% involved the use of 1 unit over the entire study period. The most common principal diagnoses for medical patients receiving transfusion were anemia, malignancy, heart failure, pneumonia and renal failure. Over time, transfusion utilization increased in patients who were admitted for infection (P = 0.009).
• Conclusion: Blood transfusions in 3 VHA hospitals have decreased over time for surgical patients but remained the same for medical patients. Further study examining appropriateness of blood products in medical patients appears necessary.

Key words: Transfusion; red blood cells; plasma; platelets; veterans.

Transfusion practices during hospitalization have changed considerably over the past 2 decades. Guided by evidence from randomized controlled trials, patient blood management programs have been expanded [1]. Such programs include recommendations regarding minimization of blood loss during surgery, prevention and treatment of anemia, strategies for reducing transfusions in both medical and surgical patients, improved blood utilization, education of health professionals, and standardization of blood management-related metrics [2]. Some of the guidelines have been incorporated into the Choosing Wisely initiative of the American Board of Internal Medicine Foundation, including: (a) don’t transfuse more units of blood than absolutely necessary, (b) don’t transfuse red blood cells for iron deficiency without hemodynamic instability, (c) don’t routinely use blood products to reverse warfarin, and (d) don’t perform serial blood counts on clinically stable patients [3]. Although there has been growing interest in blood management, only 37.8% of the 607 AABB (formerly, American Association of Blood Banks) facilities in the United States reported having a patient blood management program in 2013 [2].

While the importance of blood safety is recognized, data regarding the overall trends in practices are conflicting. A study using the Nationwide Inpatient Sample indicated that there was a 5.6% annual mean increase in the transfusion of blood products from 2002 to 2011 in the United States [4]. This contrasts with the experience of Kaiser Permanente in Northern California, in which the incidence of RBC transfusion decreased by 3.2% from 2009 to 2013 [5]. A decline in rates of intraoperative transfusion was also reported among elderly veterans in the United States from 1997 to 2009 [6].

We conducted a study in hospitalized veterans with 2 main objectives: (a) to evaluate trends in utilization of red blood cells (RBCs), platelets, and plasma over time, and (b) to identify those groups of veterans who received specific blood products. We were particularly interested in transfusion use in medical patients.

Methods

Participants were hospitalized veterans at 3 Department of Veterans Affairs (VA) medical centers. Data from all hospitalizations were collected from January 2000 through December 2010. Blood bank data (including the type and volume of products administered) were available electronically from each hospital. These files were linked to inpatient data, which included ICD-9-CM diagnoses (principal and secondary) and procedures during hospitalization.

Statistical analyses were conducted using generalized linear models to evaluate trends over time. The unit of observation was hospitalization, with categorization by type. Surgical hospitalizations were defined as admissions in which any surgical procedure occurred, whereas medical hospitalizations were defined as admissions without any surgery. Alpha was set at 0.05, 2-tailed. All analyses were conducted in Stata/MP 14.1 (StataCorp, College Station, TX). The study received institutional review board approval from the VA Ann Arbor Healthcare System.

Results

From 2000 through 2010, there were 176,521 hospitalizations in 69,621 patients. Within this cohort, 6% were < 40 years of age, 66% were 40 to 69 years of age, and 28% were 70 years or older at the time of admission. In this cohort, 96% of patients were male. Overall, 13.6% of all hospitalizations involved transfusion of a blood product (12.7% RBCs, 1.4% platelets, 3.0% plasma).

Transfusion occurred in 25.2% of surgical hospitalizations and 5.3% of medical hospitalizations. For surgical hospitalizations, transfusion use peaked in 2002 (when 30.9% of the surgical hospitalizations involved a trans-fusion) and significantly declined afterwards (P < 0.001). By 2010, 22.5% of the surgical hospitalizations involved a transfusion. Most of the surgeries where blood products were transfused involved cardiovascular procedures. For medical hospitalizations only, there was no significant change in transfusion use over time, either from 2000 to 2010 (P = 0.126) or from 2002 to 2010 (P = 0.072). In 2010, 5.2% of the medical hospitalizations involved a transfusion.

Rates of transfusion varied by principal diagnosis (Figure 1). For patients admitted with a principal diagnosis of infection (n = 20,981 hospitalizations), there was an increase in the percentage of hospitalizations in which transfusions (RBCs, platelet, plasma) were administered over time (P = 0.009) (Figure 1). For patients admitted with a principal diagnosis of malignancy (n = 12,904 hospitalizations), cardiovascular disease (n = 40,324 hospitalizations), and other diagnoses (n = 102,312 hospitalizations), there were no significant linear trends over the entire study period (P = 0.191, P = 0.052, P = 0.314, respectively). Rather, blood utilization peaked in year 2002 and significantly declined afterwards for patients admitted for malignancy (P < 0.001) and for cardiovascular disease (P < 0.001).

The most common principal diagnoses for medical patients receiving any transfusion (RBCs, platelet, plasma) are listed in Table 1. For medical patients with a principal diagnosis of anemia, 88% of hospitalizations involved a transfusion (Table 1). Transfusion occurred in 6% to 11% of medical hospitalizations with malignancies, heart failure, pneumonia or renal failure (Table 1). A considerable proportion (43%) of medical patients with gastrointestinal hemorrhage received a transfusion.

Discussion

We also observed secular trends in the volume of RBCs administered. There was an increase in the percentage of hospitalizations in which 1 or 2 RBC units were used and a decline in transfusion of 3 or more units. The reduction in the use of 3 or more RBC units may reflect the adoption and integration of recommendations in patient blood management by clinicians,

which encourage assessment of the patients’ symptoms in determining whether additional units are necessary [7]. Such guidelines also endorse the avoidance of routine
administration of 2 units of RBCs if 1 unit is sufficient [8]. We have previously shown that, after coronary artery bypass grafting, 2 RBC units doubled the risk of pneumonia [9]; additional analyses indicated that 1 or 2 units of RBCs were associated with increased postoperative morbidity [10]. In addition, our previous research indicated that the probability of infection increased considerably between 1 and 2 RBC units, with a more gradual increase beyond 2 units [11]. With this evidence in mind, some studies at single sites have reported that there was a dramatic decline from 2 RBC units before initiation of patient blood management programs to 1 unit after the programs were implemented [12,13].

Medical patients who received a transfusion were often admitted for reason of anemia, cancer, organ failure, or pneumonia. Some researchers are now reporting that blood use, at certain sites, is becoming more common in medical rather than surgical patients, which may be due to an expansion of patient blood management procedures in surgery [16]. There are a substantial number of patient blood management programs among surgical specialties and their adoption has expanded [17]. Although there are fewer patient blood management programs in the nonsurgical setting, some have been targeted to internal medicine physicians and specifically, to hospitalists [1,18]. For example, a toolkit from the Society of Hospital Medicine centers on anemia management and includes anemia assessment, treatment, evaluation of RBC transfusion risk, blood conservation, optimization of coagulation, and patient-centered decision-making [19]. Additionally, bundling of patient blood management strategies has been launched to help encourage a wider adoption of such programs [20].

While guidelines regarding use of RBCs are becoming increasingly recognized, recommendations for the use of platelets and plasma are hampered by the paucity of evidence from randomized controlled trials [21,22]. There is moderate-quality evidence for the use of platelets with therapy-induced hypoproliferative thrombocytopenia in hospitalized patients [21], but low quality evidence for other uses. Moreover, a recent review of plasma transfusion in bleeding patients found no randomized controlled trials on plasma use in hospitalized patients, although several trials were currently underway [22].

Our findings need to be considered in the context of the following limitations. The data were from 3 VA hospitals, so the results may not reflect patterns of usage at other hospitals. However, AABB reports that there has been a general decrease in transfusion of allogeneic whole blood and RBC units since 2008 at the AABB-affiliated sites in the United States [2]; this is similar to the pattern that we observed in surgical patients. In addition, we report an overall view of trends without having details regarding which specific factors influenced changes in transfusion during this 11-year period. It is possible that the severity of hospitalized patients may have changed with time which could have influenced decisions regarding the need for transfusion.

In conclusion, the use of blood products decreased in surgical patients since 2002 but remained the same in medical patients in this VA population. Transfusions increased over time for patients who were admitted to the hospital for reason of infection, but decreased since 2002 for those admitted for cardiovascular disease or cancer. The number of RBC units per hospitalization decreased over time. Additional surveillance is needed to determine whether recent evidence regarding blood management has been incorporated into clinical practice for medical patients, as we strive to deliver optimal care to our veterans.

Corresponding author: Mary A.M. Rogers, PhD, MS, Dept. of Internal Medicine, Univ. of Michigan, 016-422W NCRC, Ann Arbor, MI 48109-2800, maryroge@umich.edu.

Funding/support: Department of Veterans Affairs, Clinical Sciences Research & Development Service Merit Review Award (EPID-011-11S). The contents do not represent the views of the U.S. Department of Veterans Affairs or the U.S. Government.

Financial disclosures: None.

Author contributions: conception and design, MAMR, SS; analysis and interpretation of data, MAMR, JDB, DR, LK, SS; drafting of article, MAMR; critical revision of the article, MAMR, MTG, DR, LK, SS, VC; statistical expertise, MAMR, DR; obtaining of funding, MTG, SS, VC; administrative or technical support, MTG, LK, SS, VC; collection and assembly of data, JDB, LK.

Abstract

• Background: Although transfusion guidelines have changed considerably over the past 2 decades, the adoption of patient blood management programs has not been fully realized across hospitals in the United States.
• Objective: To evaluate trends in red blood cell (RBC), platelet, and plasma transfusion at 3 Veterans Health Administration (VHA) hospitals from 2000 through 2010.
• Methods: Data from all hospitalizations were collected from January 2000 through December 2010. Blood bank data (including the type and volume of products administered) were available electronically from each hospital. These files were linked to inpatient data, which included ICD-9-CM diagnoses (principal and secondary) and procedures during hospitalization. Statistical analyses were conducted using generalized linear models to evaluate trends over time. The unit of observation was hospitalization, with categorization by type.
• Results: There were 176,521 hospitalizations in 69,621 patients; of these, 13.6% of hospitalizations involved transfusion of blood products (12.7% RBCs, 1.4% platelets, 3.0% plasma). Transfusion occurred in 25.2% of surgical and 5.3% of medical hospitalizations. Transfusion use peaked in 2002 for surgical hospitalizations and declined afterwards (P < 0.001). There was no significant change in transfusion use over time (P = 0.126) for medical hospitalizations. In hospitalizations that involved transfusions, there was a 20.3% reduction in the proportion of hospitalizations in which ≥ 3 units of RBCs were given (from 51.7% to 41.1%; P < 0.001) and a 73.6% increase when 1 RBC unit was given (from 8.0% to 13.8%; P < 0.001) from 2000-2010. Of the hospitalizations with RBC transfusion, 9.6% involved the use of 1 unit over the entire study period. The most common principal diagnoses for medical patients receiving transfusion were anemia, malignancy, heart failure, pneumonia and renal failure. Over time, transfusion utilization increased in patients who were admitted for infection (P = 0.009).
• Conclusion: Blood transfusions in 3 VHA hospitals have decreased over time for surgical patients but remained the same for medical patients. Further study examining appropriateness of blood products in medical patients appears necessary.

Key words: Transfusion; red blood cells; plasma; platelets; veterans.

Transfusion practices during hospitalization have changed considerably over the past 2 decades. Guided by evidence from randomized controlled trials, patient blood management programs have been expanded [1]. Such programs include recommendations regarding minimization of blood loss during surgery, prevention and treatment of anemia, strategies for reducing transfusions in both medical and surgical patients, improved blood utilization, education of health professionals, and standardization of blood management-related metrics [2]. Some of the guidelines have been incorporated into the Choosing Wisely initiative of the American Board of Internal Medicine Foundation, including: (a) don’t transfuse more units of blood than absolutely necessary, (b) don’t transfuse red blood cells for iron deficiency without hemodynamic instability, (c) don’t routinely use blood products to reverse warfarin, and (d) don’t perform serial blood counts on clinically stable patients [3]. Although there has been growing interest in blood management, only 37.8% of the 607 AABB (formerly, American Association of Blood Banks) facilities in the United States reported having a patient blood management program in 2013 [2].

While the importance of blood safety is recognized, data regarding the overall trends in practices are conflicting. A study using the Nationwide Inpatient Sample indicated that there was a 5.6% annual mean increase in the transfusion of blood products from 2002 to 2011 in the United States [4]. This contrasts with the experience of Kaiser Permanente in Northern California, in which the incidence of RBC transfusion decreased by 3.2% from 2009 to 2013 [5]. A decline in rates of intraoperative transfusion was also reported among elderly veterans in the United States from 1997 to 2009 [6].

We conducted a study in hospitalized veterans with 2 main objectives: (a) to evaluate trends in utilization of red blood cells (RBCs), platelets, and plasma over time, and (b) to identify those groups of veterans who received specific blood products. We were particularly interested in transfusion use in medical patients.

Methods

Participants were hospitalized veterans at 3 Department of Veterans Affairs (VA) medical centers. Data from all hospitalizations were collected from January 2000 through December 2010. Blood bank data (including the type and volume of products administered) were available electronically from each hospital. These files were linked to inpatient data, which included ICD-9-CM diagnoses (principal and secondary) and procedures during hospitalization.

Statistical analyses were conducted using generalized linear models to evaluate trends over time. The unit of observation was hospitalization, with categorization by type. Surgical hospitalizations were defined as admissions in which any surgical procedure occurred, whereas medical hospitalizations were defined as admissions without any surgery. Alpha was set at 0.05, 2-tailed. All analyses were conducted in Stata/MP 14.1 (StataCorp, College Station, TX). The study received institutional review board approval from the VA Ann Arbor Healthcare System.

Results

From 2000 through 2010, there were 176,521 hospitalizations in 69,621 patients. Within this cohort, 6% were < 40 years of age, 66% were 40 to 69 years of age, and 28% were 70 years or older at the time of admission. In this cohort, 96% of patients were male. Overall, 13.6% of all hospitalizations involved transfusion of a blood product (12.7% RBCs, 1.4% platelets, 3.0% plasma).

Transfusion occurred in 25.2% of surgical hospitalizations and 5.3% of medical hospitalizations. For surgical hospitalizations, transfusion use peaked in 2002 (when 30.9% of the surgical hospitalizations involved a trans-fusion) and significantly declined afterwards (P < 0.001). By 2010, 22.5% of the surgical hospitalizations involved a transfusion. Most of the surgeries where blood products were transfused involved cardiovascular procedures. For medical hospitalizations only, there was no significant change in transfusion use over time, either from 2000 to 2010 (P = 0.126) or from 2002 to 2010 (P = 0.072). In 2010, 5.2% of the medical hospitalizations involved a transfusion.

Rates of transfusion varied by principal diagnosis (Figure 1). For patients admitted with a principal diagnosis of infection (n = 20,981 hospitalizations), there was an increase in the percentage of hospitalizations in which transfusions (RBCs, platelet, plasma) were administered over time (P = 0.009) (Figure 1). For patients admitted with a principal diagnosis of malignancy (n = 12,904 hospitalizations), cardiovascular disease (n = 40,324 hospitalizations), and other diagnoses (n = 102,312 hospitalizations), there were no significant linear trends over the entire study period (P = 0.191, P = 0.052, P = 0.314, respectively). Rather, blood utilization peaked in year 2002 and significantly declined afterwards for patients admitted for malignancy (P < 0.001) and for cardiovascular disease (P < 0.001).

The most common principal diagnoses for medical patients receiving any transfusion (RBCs, platelet, plasma) are listed in Table 1. For medical patients with a principal diagnosis of anemia, 88% of hospitalizations involved a transfusion (Table 1). Transfusion occurred in 6% to 11% of medical hospitalizations with malignancies, heart failure, pneumonia or renal failure (Table 1). A considerable proportion (43%) of medical patients with gastrointestinal hemorrhage received a transfusion.

Discussion

We also observed secular trends in the volume of RBCs administered. There was an increase in the percentage of hospitalizations in which 1 or 2 RBC units were used and a decline in transfusion of 3 or more units. The reduction in the use of 3 or more RBC units may reflect the adoption and integration of recommendations in patient blood management by clinicians,

which encourage assessment of the patients’ symptoms in determining whether additional units are necessary [7]. Such guidelines also endorse the avoidance of routine
administration of 2 units of RBCs if 1 unit is sufficient [8]. We have previously shown that, after coronary artery bypass grafting, 2 RBC units doubled the risk of pneumonia [9]; additional analyses indicated that 1 or 2 units of RBCs were associated with increased postoperative morbidity [10]. In addition, our previous research indicated that the probability of infection increased considerably between 1 and 2 RBC units, with a more gradual increase beyond 2 units [11]. With this evidence in mind, some studies at single sites have reported that there was a dramatic decline from 2 RBC units before initiation of patient blood management programs to 1 unit after the programs were implemented [12,13].

Medical patients who received a transfusion were often admitted for reason of anemia, cancer, organ failure, or pneumonia. Some researchers are now reporting that blood use, at certain sites, is becoming more common in medical rather than surgical patients, which may be due to an expansion of patient blood management procedures in surgery [16]. There are a substantial number of patient blood management programs among surgical specialties and their adoption has expanded [17]. Although there are fewer patient blood management programs in the nonsurgical setting, some have been targeted to internal medicine physicians and specifically, to hospitalists [1,18]. For example, a toolkit from the Society of Hospital Medicine centers on anemia management and includes anemia assessment, treatment, evaluation of RBC transfusion risk, blood conservation, optimization of coagulation, and patient-centered decision-making [19]. Additionally, bundling of patient blood management strategies has been launched to help encourage a wider adoption of such programs [20].

While guidelines regarding use of RBCs are becoming increasingly recognized, recommendations for the use of platelets and plasma are hampered by the paucity of evidence from randomized controlled trials [21,22]. There is moderate-quality evidence for the use of platelets with therapy-induced hypoproliferative thrombocytopenia in hospitalized patients [21], but low quality evidence for other uses. Moreover, a recent review of plasma transfusion in bleeding patients found no randomized controlled trials on plasma use in hospitalized patients, although several trials were currently underway [22].

Our findings need to be considered in the context of the following limitations. The data were from 3 VA hospitals, so the results may not reflect patterns of usage at other hospitals. However, AABB reports that there has been a general decrease in transfusion of allogeneic whole blood and RBC units since 2008 at the AABB-affiliated sites in the United States [2]; this is similar to the pattern that we observed in surgical patients. In addition, we report an overall view of trends without having details regarding which specific factors influenced changes in transfusion during this 11-year period. It is possible that the severity of hospitalized patients may have changed with time which could have influenced decisions regarding the need for transfusion.

In conclusion, the use of blood products decreased in surgical patients since 2002 but remained the same in medical patients in this VA population. Transfusions increased over time for patients who were admitted to the hospital for reason of infection, but decreased since 2002 for those admitted for cardiovascular disease or cancer. The number of RBC units per hospitalization decreased over time. Additional surveillance is needed to determine whether recent evidence regarding blood management has been incorporated into clinical practice for medical patients, as we strive to deliver optimal care to our veterans.

Corresponding author: Mary A.M. Rogers, PhD, MS, Dept. of Internal Medicine, Univ. of Michigan, 016-422W NCRC, Ann Arbor, MI 48109-2800, maryroge@umich.edu.

Funding/support: Department of Veterans Affairs, Clinical Sciences Research & Development Service Merit Review Award (EPID-011-11S). The contents do not represent the views of the U.S. Department of Veterans Affairs or the U.S. Government.

Financial disclosures: None.

Author contributions: conception and design, MAMR, SS; analysis and interpretation of data, MAMR, JDB, DR, LK, SS; drafting of article, MAMR; critical revision of the article, MAMR, MTG, DR, LK, SS, VC; statistical expertise, MAMR, DR; obtaining of funding, MTG, SS, VC; administrative or technical support, MTG, LK, SS, VC; collection and assembly of data, JDB, LK.