Multifaceted Intervention Reduces Cost

Healthcare costs continue to increase and are estimated to be approximately $3.1 trillion per year in the United States.[1] Waste is a major contributor to this cost, accounting for an estimated $910 billion/year.[2] Laboratory tests are well documented to contribute to healthcare waste, with an estimated 30% to 50% of tests for hospitalized patients being unnecessary.[3, 4, 5] This issue has been highlighted by the American Board of Internal Medicine Foundation's Choosing Wisely campaign as an area to reduce waste.[6] Evaluating this concern locally, a University Health Systems Consortium 2011 analysis indicated that the University of Utah general internal medicine hospitalist service had a higher average direct lab cost per discharge compared to top performers, indicating an opportunity for improvement.

Multiple interventions have been described in the literature to address excessive laboratory utilization, including physician education, audit and feedback, cost information display, and administrative rules restricting certain types of ordering.[7, 8, 9, 10, 11] Despite these interventions, barriers remain common and not all interventions are sustained. For example, interventions focused mainly on education see a small improvement initially that is not sustained.[4, 12, 13] Additionally, although most studies focus on individual interventions, those that target multiple factors have been found to be more successful at producing and sustaining change.[14] Therefore, the opportunity existed to incorporate multiple etiologies into a single intervention and apply a checklist to laboratory ordering to see if combined modalities could be effective at reducing laboratory costs in a sustainable manner.

In addition to cost, there is potential patient harm resulting from unnecessary laboratory testing. For prolonged hospitalizations, anemia is a well‐recognized side effect of phlebotomy,[15, 16] and a recent evaluation of cardiac surgery patients found an average cumulative blood loss due to phlebotomy of 454 mL/hospital stay.[17] The sheer number of tests ordered can lead to false positive tests that result in additional testing and monitoring. Furthermore, patients subjected to laboratory blood draws are often awakened early in the morning, which is unpleasant and could adversely affect the patient experience.

Recognizing laboratory cost as a problem, the University of Utah general internal medicine hospitalist service implemented a multifaceted quality‐improvement initiative with a goal to reduce laboratory testing. At the time of this project, University of Utah Health Care (UUHC) developed a Value Driven Outcomes (VDO) tool to give direct data related to costs of care, including the actual cost paid by the hospital to the university‐owned laboratory vendor (ARUP Laboratories, Salt Lake City, UT) for testing.[18] The hospitalist group incorporated VDO into the initiative for routine cost feedback. This study evaluates the impact of this intervention on laboratory costs.

METHODS

RESULTS

We analyzed 48,327 inpatient visits that met inclusion criteria. We excluded 15,659 obstetrics, rehabilitation, and psychiatry visits. Seven hundred seventy‐two (2.4%) of the remaining visits were excluded due to missing data. A total of 31,896 inpatient visits by 22,545 patients were included in the analysis. There were 10,136 visits before the intervention and 21,760 visits after. Characteristics of the study groups for the full study timeframe (July 1, 2012April 30, 2014) are summarized in Table 1.

During the study period, there were 25,586 visits in the control group and 6310 visits in the intervention group. Patients in the intervention group were on average older than patients in the control group. There were more female patients in the intervention group. Mean CCI was 4.2 in the intervention group and 3.6 in the control group. The intervention group had lower LOS and 30‐day readmissions than the control group.

Descriptive statistics and simple comparisons of covariates and outcomes before and after the intervention are shown in Table 2. Age and gender distributions remained unchanged in both groups. CCI increased in the control group by 0.24 (P < 0.001) and remained unchanged in the intervention group. In the intervention group, lab cost per day was reduced from $138 before the intervention to $123 after the intervention (P < 0.001). In contrast, among control patients, cost per day increased nonsignificantly from $130 preintervention to $132 postintervention (P = 0.37). Number of tests per day significantly decreased for all specific tests in the intervention group. Readmission rates decreased significantly from 14% to 11% in the intervention group (P = 0.01). LOS remained constant in both groups.

ITS analysis results are shown in Table 3. After the intervention, the difference in monthly means between the 2 groups dropped by $16 for cost per day (P = 0.034) and by $128 for cost per visit (P = 0.02). The decreased cost in the intervention group amounts to approximately $251,427 (95% confidence interval [CI]: $20,370‐$482,484) savings over the first year. If the intervention was rolled out for the control group and had a similar impact, it could have led to an additional cost savings of $1,321,669 (95% CI: 107,081‐2,536,256). Moreover, the number of basic metabolic panel, comprehensive metabolic panel, and complete blood count test per day were reduced significantly more in the intervention group compared to the control group (<0.001, 0.004, and <0.001).

Figure 1 shows a graphical representation of the biweekly means for the 2 primary outcomeslab cost per day and lab cost per visit. Figure 2 shows all other outcomes. To the right of each figure, P values are provided for the b₂ coefficients from Table 3.

Figure 1

Figure 2

DISCUSSION

Through a multifaceted quality‐improvement initiative, the UUHC hospitalist group was able to reduce lab cost per day and per visit as well as commonly ordered routine labs as compared to an institutional control group. A multifaceted approach was selected given the literature supporting this approach as the most likely method to sustain improvement.[14] At the same time, the use of a multifaceted intervention makes it difficult to rigorously determine the relative impact of different components of the intervention. In discussing this issue, however, the hospitalist group felt that the driving factors for change were those related to process change, specifically, the use of a standardized rounding checklist to discuss lab testing and the routine review of lab costs at group meetings. The ultimate goal was to change the culture of routine test ordering into a thoughtful process of needed tests and thereby reduce costs. Prior to this intervention, the least experienced person on this team (the intern) ordered any test he or she wanted, usually without discussion. The intervention focused on this issue through standardized supervision and explicit discussion of laboratory tests. Importantly, although improvements from education initiatives typically decrease over time, the incorporation of process change in this intervention was felt to likely contribute to the sustained reduction seen at 15 months. Although use of the rounding checklist added another step to daily rounds, the routine cost feedback, including comparisons to peers, helped encourage use of the checklist. Thus, we feel that routine feedback was essential to sustaining the intervention and its impact.

Inappropriate and unnecessary testing has been recognized for decades, and multiple interventions have been attempted, including a recent article that demonstrated a 10% reduction in common laboratory ordering through an initiative mainly focused on education and ordering feedback.[25] Despite reported success of several interventions, none have combined multiple interventions and explicitly required discussion of laboratory tests on rounds. For example, although the UUHC intervention used Attali et al.[21] and Barie and Hydo's[20] work to develop the intervention, neither of these studies described how laboratory testing was discussed with the attending or supervising resident. The UUHC intervention thus builds on the current literature by combining other successful modalities with explicit discussion of laboratory testing via a rounding checklist and feedback with the novel VDO tool to reduce laboratory costs. A major strength of this intervention is the relatively low cost and the generalizability of implementing rounding checklists. Initial support from the hospital was needed to provide accurate VDO information to the hospitalist group. However, ongoing costs were minimal and related to any additional time spent during rounds to discuss laboratory tests. Thus, we feel that this intervention is feasible for wide replication.

Another strength of the study is the use of the VDO tool to measure actual costs. Whereas previous studies have relied on estimated costs with extrapolation to potential cost savings, this study used direct costs to the institution as a more accurate marker of cost savings. Additionally, most studies on lab utilization have used a before/after analysis without a control group. The presence of a control group for this analysis is important to help assess for institutional trends that may not be reflected in a before/after intervention. The reduction in cost in the intervention group despite a trend toward increased cost in the institutional control group supports the impact of this intervention.

Limitations of this study include that it was a single‐center, controlled ITS study and not a randomized controlled trial. Related to this limitation, the control group reflected a different patient population compared to the intervention group, with a longer LOS, lower CCI, and inclusion of nonmedical patients. However, these differences were relatively stable before and after the intervention. Also, ITS is considered one of the most robust research designs outside of randomized controlled trials, and it accounts for baseline differences in both levels and trends.[24] Nevertheless, it remains possible that secular trends existed that we did not capture and that affected the 2 populations differently.

A further limitation is that the baseline period was only 7 months and the intervention was 15 months. As the 7 months started in July, this could have reflected the time when interns were least experienced with ordering. Unfortunately, we did not have VDO availability for a full year prior to the intervention. We believe that any major effect due to this shortened baseline period should have been seen in the control group as well, and therefore accounted for in the analysis. Additionally, it is possible that there was spillover of the intervention to the control group, as internal medicine residents rotated throughout the hospital to other medical services (pulmonary, cardiology, hematology, and oncology). However, any effect of their rotation should have been to lower the control lab cost, thus making differences less profound.

CONCLUSIONS

A multifaceted approach to laboratory reduction through education, process change, cost feedback, and financial incentive resulted in a significant reduction in laboratory cost per day, laboratory cost per visit, and the ordering of common laboratory tests at a major academic medical center.

Healthcare costs continue to increase and are estimated to be approximately $3.1 trillion per year in the United States.[1] Waste is a major contributor to this cost, accounting for an estimated $910 billion/year.[2] Laboratory tests are well documented to contribute to healthcare waste, with an estimated 30% to 50% of tests for hospitalized patients being unnecessary.[3, 4, 5] This issue has been highlighted by the American Board of Internal Medicine Foundation's Choosing Wisely campaign as an area to reduce waste.[6] Evaluating this concern locally, a University Health Systems Consortium 2011 analysis indicated that the University of Utah general internal medicine hospitalist service had a higher average direct lab cost per discharge compared to top performers, indicating an opportunity for improvement.

Multiple interventions have been described in the literature to address excessive laboratory utilization, including physician education, audit and feedback, cost information display, and administrative rules restricting certain types of ordering.[7, 8, 9, 10, 11] Despite these interventions, barriers remain common and not all interventions are sustained. For example, interventions focused mainly on education see a small improvement initially that is not sustained.[4, 12, 13] Additionally, although most studies focus on individual interventions, those that target multiple factors have been found to be more successful at producing and sustaining change.[14] Therefore, the opportunity existed to incorporate multiple etiologies into a single intervention and apply a checklist to laboratory ordering to see if combined modalities could be effective at reducing laboratory costs in a sustainable manner.

In addition to cost, there is potential patient harm resulting from unnecessary laboratory testing. For prolonged hospitalizations, anemia is a well‐recognized side effect of phlebotomy,[15, 16] and a recent evaluation of cardiac surgery patients found an average cumulative blood loss due to phlebotomy of 454 mL/hospital stay.[17] The sheer number of tests ordered can lead to false positive tests that result in additional testing and monitoring. Furthermore, patients subjected to laboratory blood draws are often awakened early in the morning, which is unpleasant and could adversely affect the patient experience.

Recognizing laboratory cost as a problem, the University of Utah general internal medicine hospitalist service implemented a multifaceted quality‐improvement initiative with a goal to reduce laboratory testing. At the time of this project, University of Utah Health Care (UUHC) developed a Value Driven Outcomes (VDO) tool to give direct data related to costs of care, including the actual cost paid by the hospital to the university‐owned laboratory vendor (ARUP Laboratories, Salt Lake City, UT) for testing.[18] The hospitalist group incorporated VDO into the initiative for routine cost feedback. This study evaluates the impact of this intervention on laboratory costs.

METHODS

RESULTS

We analyzed 48,327 inpatient visits that met inclusion criteria. We excluded 15,659 obstetrics, rehabilitation, and psychiatry visits. Seven hundred seventy‐two (2.4%) of the remaining visits were excluded due to missing data. A total of 31,896 inpatient visits by 22,545 patients were included in the analysis. There were 10,136 visits before the intervention and 21,760 visits after. Characteristics of the study groups for the full study timeframe (July 1, 2012April 30, 2014) are summarized in Table 1.

During the study period, there were 25,586 visits in the control group and 6310 visits in the intervention group. Patients in the intervention group were on average older than patients in the control group. There were more female patients in the intervention group. Mean CCI was 4.2 in the intervention group and 3.6 in the control group. The intervention group had lower LOS and 30‐day readmissions than the control group.

Descriptive statistics and simple comparisons of covariates and outcomes before and after the intervention are shown in Table 2. Age and gender distributions remained unchanged in both groups. CCI increased in the control group by 0.24 (P < 0.001) and remained unchanged in the intervention group. In the intervention group, lab cost per day was reduced from $138 before the intervention to $123 after the intervention (P < 0.001). In contrast, among control patients, cost per day increased nonsignificantly from $130 preintervention to $132 postintervention (P = 0.37). Number of tests per day significantly decreased for all specific tests in the intervention group. Readmission rates decreased significantly from 14% to 11% in the intervention group (P = 0.01). LOS remained constant in both groups.

ITS analysis results are shown in Table 3. After the intervention, the difference in monthly means between the 2 groups dropped by $16 for cost per day (P = 0.034) and by $128 for cost per visit (P = 0.02). The decreased cost in the intervention group amounts to approximately $251,427 (95% confidence interval [CI]: $20,370‐$482,484) savings over the first year. If the intervention was rolled out for the control group and had a similar impact, it could have led to an additional cost savings of $1,321,669 (95% CI: 107,081‐2,536,256). Moreover, the number of basic metabolic panel, comprehensive metabolic panel, and complete blood count test per day were reduced significantly more in the intervention group compared to the control group (<0.001, 0.004, and <0.001).

Figure 1 shows a graphical representation of the biweekly means for the 2 primary outcomeslab cost per day and lab cost per visit. Figure 2 shows all other outcomes. To the right of each figure, P values are provided for the b₂ coefficients from Table 3.

Figure 1

Figure 2

DISCUSSION

Through a multifaceted quality‐improvement initiative, the UUHC hospitalist group was able to reduce lab cost per day and per visit as well as commonly ordered routine labs as compared to an institutional control group. A multifaceted approach was selected given the literature supporting this approach as the most likely method to sustain improvement.[14] At the same time, the use of a multifaceted intervention makes it difficult to rigorously determine the relative impact of different components of the intervention. In discussing this issue, however, the hospitalist group felt that the driving factors for change were those related to process change, specifically, the use of a standardized rounding checklist to discuss lab testing and the routine review of lab costs at group meetings. The ultimate goal was to change the culture of routine test ordering into a thoughtful process of needed tests and thereby reduce costs. Prior to this intervention, the least experienced person on this team (the intern) ordered any test he or she wanted, usually without discussion. The intervention focused on this issue through standardized supervision and explicit discussion of laboratory tests. Importantly, although improvements from education initiatives typically decrease over time, the incorporation of process change in this intervention was felt to likely contribute to the sustained reduction seen at 15 months. Although use of the rounding checklist added another step to daily rounds, the routine cost feedback, including comparisons to peers, helped encourage use of the checklist. Thus, we feel that routine feedback was essential to sustaining the intervention and its impact.

Inappropriate and unnecessary testing has been recognized for decades, and multiple interventions have been attempted, including a recent article that demonstrated a 10% reduction in common laboratory ordering through an initiative mainly focused on education and ordering feedback.[25] Despite reported success of several interventions, none have combined multiple interventions and explicitly required discussion of laboratory tests on rounds. For example, although the UUHC intervention used Attali et al.[21] and Barie and Hydo's[20] work to develop the intervention, neither of these studies described how laboratory testing was discussed with the attending or supervising resident. The UUHC intervention thus builds on the current literature by combining other successful modalities with explicit discussion of laboratory testing via a rounding checklist and feedback with the novel VDO tool to reduce laboratory costs. A major strength of this intervention is the relatively low cost and the generalizability of implementing rounding checklists. Initial support from the hospital was needed to provide accurate VDO information to the hospitalist group. However, ongoing costs were minimal and related to any additional time spent during rounds to discuss laboratory tests. Thus, we feel that this intervention is feasible for wide replication.

Another strength of the study is the use of the VDO tool to measure actual costs. Whereas previous studies have relied on estimated costs with extrapolation to potential cost savings, this study used direct costs to the institution as a more accurate marker of cost savings. Additionally, most studies on lab utilization have used a before/after analysis without a control group. The presence of a control group for this analysis is important to help assess for institutional trends that may not be reflected in a before/after intervention. The reduction in cost in the intervention group despite a trend toward increased cost in the institutional control group supports the impact of this intervention.

Limitations of this study include that it was a single‐center, controlled ITS study and not a randomized controlled trial. Related to this limitation, the control group reflected a different patient population compared to the intervention group, with a longer LOS, lower CCI, and inclusion of nonmedical patients. However, these differences were relatively stable before and after the intervention. Also, ITS is considered one of the most robust research designs outside of randomized controlled trials, and it accounts for baseline differences in both levels and trends.[24] Nevertheless, it remains possible that secular trends existed that we did not capture and that affected the 2 populations differently.

A further limitation is that the baseline period was only 7 months and the intervention was 15 months. As the 7 months started in July, this could have reflected the time when interns were least experienced with ordering. Unfortunately, we did not have VDO availability for a full year prior to the intervention. We believe that any major effect due to this shortened baseline period should have been seen in the control group as well, and therefore accounted for in the analysis. Additionally, it is possible that there was spillover of the intervention to the control group, as internal medicine residents rotated throughout the hospital to other medical services (pulmonary, cardiology, hematology, and oncology). However, any effect of their rotation should have been to lower the control lab cost, thus making differences less profound.

CONCLUSIONS

A multifaceted approach to laboratory reduction through education, process change, cost feedback, and financial incentive resulted in a significant reduction in laboratory cost per day, laboratory cost per visit, and the ordering of common laboratory tests at a major academic medical center.

Healthcare costs continue to increase and are estimated to be approximately $3.1 trillion per year in the United States.[1] Waste is a major contributor to this cost, accounting for an estimated $910 billion/year.[2] Laboratory tests are well documented to contribute to healthcare waste, with an estimated 30% to 50% of tests for hospitalized patients being unnecessary.[3, 4, 5] This issue has been highlighted by the American Board of Internal Medicine Foundation's Choosing Wisely campaign as an area to reduce waste.[6] Evaluating this concern locally, a University Health Systems Consortium 2011 analysis indicated that the University of Utah general internal medicine hospitalist service had a higher average direct lab cost per discharge compared to top performers, indicating an opportunity for improvement.

Multiple interventions have been described in the literature to address excessive laboratory utilization, including physician education, audit and feedback, cost information display, and administrative rules restricting certain types of ordering.[7, 8, 9, 10, 11] Despite these interventions, barriers remain common and not all interventions are sustained. For example, interventions focused mainly on education see a small improvement initially that is not sustained.[4, 12, 13] Additionally, although most studies focus on individual interventions, those that target multiple factors have been found to be more successful at producing and sustaining change.[14] Therefore, the opportunity existed to incorporate multiple etiologies into a single intervention and apply a checklist to laboratory ordering to see if combined modalities could be effective at reducing laboratory costs in a sustainable manner.

In addition to cost, there is potential patient harm resulting from unnecessary laboratory testing. For prolonged hospitalizations, anemia is a well‐recognized side effect of phlebotomy,[15, 16] and a recent evaluation of cardiac surgery patients found an average cumulative blood loss due to phlebotomy of 454 mL/hospital stay.[17] The sheer number of tests ordered can lead to false positive tests that result in additional testing and monitoring. Furthermore, patients subjected to laboratory blood draws are often awakened early in the morning, which is unpleasant and could adversely affect the patient experience.

Recognizing laboratory cost as a problem, the University of Utah general internal medicine hospitalist service implemented a multifaceted quality‐improvement initiative with a goal to reduce laboratory testing. At the time of this project, University of Utah Health Care (UUHC) developed a Value Driven Outcomes (VDO) tool to give direct data related to costs of care, including the actual cost paid by the hospital to the university‐owned laboratory vendor (ARUP Laboratories, Salt Lake City, UT) for testing.[18] The hospitalist group incorporated VDO into the initiative for routine cost feedback. This study evaluates the impact of this intervention on laboratory costs.

METHODS

RESULTS

We analyzed 48,327 inpatient visits that met inclusion criteria. We excluded 15,659 obstetrics, rehabilitation, and psychiatry visits. Seven hundred seventy‐two (2.4%) of the remaining visits were excluded due to missing data. A total of 31,896 inpatient visits by 22,545 patients were included in the analysis. There were 10,136 visits before the intervention and 21,760 visits after. Characteristics of the study groups for the full study timeframe (July 1, 2012April 30, 2014) are summarized in Table 1.

During the study period, there were 25,586 visits in the control group and 6310 visits in the intervention group. Patients in the intervention group were on average older than patients in the control group. There were more female patients in the intervention group. Mean CCI was 4.2 in the intervention group and 3.6 in the control group. The intervention group had lower LOS and 30‐day readmissions than the control group.

Descriptive statistics and simple comparisons of covariates and outcomes before and after the intervention are shown in Table 2. Age and gender distributions remained unchanged in both groups. CCI increased in the control group by 0.24 (P < 0.001) and remained unchanged in the intervention group. In the intervention group, lab cost per day was reduced from $138 before the intervention to $123 after the intervention (P < 0.001). In contrast, among control patients, cost per day increased nonsignificantly from $130 preintervention to $132 postintervention (P = 0.37). Number of tests per day significantly decreased for all specific tests in the intervention group. Readmission rates decreased significantly from 14% to 11% in the intervention group (P = 0.01). LOS remained constant in both groups.

ITS analysis results are shown in Table 3. After the intervention, the difference in monthly means between the 2 groups dropped by $16 for cost per day (P = 0.034) and by $128 for cost per visit (P = 0.02). The decreased cost in the intervention group amounts to approximately $251,427 (95% confidence interval [CI]: $20,370‐$482,484) savings over the first year. If the intervention was rolled out for the control group and had a similar impact, it could have led to an additional cost savings of $1,321,669 (95% CI: 107,081‐2,536,256). Moreover, the number of basic metabolic panel, comprehensive metabolic panel, and complete blood count test per day were reduced significantly more in the intervention group compared to the control group (<0.001, 0.004, and <0.001).

Figure 1 shows a graphical representation of the biweekly means for the 2 primary outcomeslab cost per day and lab cost per visit. Figure 2 shows all other outcomes. To the right of each figure, P values are provided for the b₂ coefficients from Table 3.

Figure 1

Figure 2

DISCUSSION

Through a multifaceted quality‐improvement initiative, the UUHC hospitalist group was able to reduce lab cost per day and per visit as well as commonly ordered routine labs as compared to an institutional control group. A multifaceted approach was selected given the literature supporting this approach as the most likely method to sustain improvement.[14] At the same time, the use of a multifaceted intervention makes it difficult to rigorously determine the relative impact of different components of the intervention. In discussing this issue, however, the hospitalist group felt that the driving factors for change were those related to process change, specifically, the use of a standardized rounding checklist to discuss lab testing and the routine review of lab costs at group meetings. The ultimate goal was to change the culture of routine test ordering into a thoughtful process of needed tests and thereby reduce costs. Prior to this intervention, the least experienced person on this team (the intern) ordered any test he or she wanted, usually without discussion. The intervention focused on this issue through standardized supervision and explicit discussion of laboratory tests. Importantly, although improvements from education initiatives typically decrease over time, the incorporation of process change in this intervention was felt to likely contribute to the sustained reduction seen at 15 months. Although use of the rounding checklist added another step to daily rounds, the routine cost feedback, including comparisons to peers, helped encourage use of the checklist. Thus, we feel that routine feedback was essential to sustaining the intervention and its impact.

Inappropriate and unnecessary testing has been recognized for decades, and multiple interventions have been attempted, including a recent article that demonstrated a 10% reduction in common laboratory ordering through an initiative mainly focused on education and ordering feedback.[25] Despite reported success of several interventions, none have combined multiple interventions and explicitly required discussion of laboratory tests on rounds. For example, although the UUHC intervention used Attali et al.[21] and Barie and Hydo's[20] work to develop the intervention, neither of these studies described how laboratory testing was discussed with the attending or supervising resident. The UUHC intervention thus builds on the current literature by combining other successful modalities with explicit discussion of laboratory testing via a rounding checklist and feedback with the novel VDO tool to reduce laboratory costs. A major strength of this intervention is the relatively low cost and the generalizability of implementing rounding checklists. Initial support from the hospital was needed to provide accurate VDO information to the hospitalist group. However, ongoing costs were minimal and related to any additional time spent during rounds to discuss laboratory tests. Thus, we feel that this intervention is feasible for wide replication.

Another strength of the study is the use of the VDO tool to measure actual costs. Whereas previous studies have relied on estimated costs with extrapolation to potential cost savings, this study used direct costs to the institution as a more accurate marker of cost savings. Additionally, most studies on lab utilization have used a before/after analysis without a control group. The presence of a control group for this analysis is important to help assess for institutional trends that may not be reflected in a before/after intervention. The reduction in cost in the intervention group despite a trend toward increased cost in the institutional control group supports the impact of this intervention.

Limitations of this study include that it was a single‐center, controlled ITS study and not a randomized controlled trial. Related to this limitation, the control group reflected a different patient population compared to the intervention group, with a longer LOS, lower CCI, and inclusion of nonmedical patients. However, these differences were relatively stable before and after the intervention. Also, ITS is considered one of the most robust research designs outside of randomized controlled trials, and it accounts for baseline differences in both levels and trends.[24] Nevertheless, it remains possible that secular trends existed that we did not capture and that affected the 2 populations differently.

A further limitation is that the baseline period was only 7 months and the intervention was 15 months. As the 7 months started in July, this could have reflected the time when interns were least experienced with ordering. Unfortunately, we did not have VDO availability for a full year prior to the intervention. We believe that any major effect due to this shortened baseline period should have been seen in the control group as well, and therefore accounted for in the analysis. Additionally, it is possible that there was spillover of the intervention to the control group, as internal medicine residents rotated throughout the hospital to other medical services (pulmonary, cardiology, hematology, and oncology). However, any effect of their rotation should have been to lower the control lab cost, thus making differences less profound.

CONCLUSIONS

A multifaceted approach to laboratory reduction through education, process change, cost feedback, and financial incentive resulted in a significant reduction in laboratory cost per day, laboratory cost per visit, and the ordering of common laboratory tests at a major academic medical center.