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SAN ANTONIO –
However, whether the sources of variability stem from patient factors such as disease severity and socioeconomic status, provider factors, environmental factors, or selection biases in those who are diagnosed with obstructive sleep apnea and treated with CPAP remains to be understood, lead study author Sanjay R. Patel, MD, said at the annual meeting of the Associated Professional Sleep Societies.
In 2015, the American Academy of Sleep Medicine (AASM) endorsed CPAP adherence as a process measure, and the Centers for Medicare and Medicaid Services has used CPAP adherence as an outcome measure to limit long-term coverage of the therapy. It defines CPAP adherence as 4 or more hours of use on greater than 70% of nights in a consecutive 30-day period within the first 90 days. “Strengths of CPAP adherence as an outcome measure include the fact that it is easy to measure and it predicts improvement in sleepiness, quality of life, and blood pressure control,” said Dr. Patel, who directs the University of Pittsburgh’s Center for Sleep and Cardiovascular Outcomes Research. “One issue as to whether we should use CPAP adherence as an outcome-based quality of care measure is, does variability reflect performance at the provider and/or health care system?”
In an effort to describe CPAP adherence rates in general clinical practice as well as sources of variability, Dr. Patel and colleagues evaluated telemonitoring data maintained by Philips Respironics. The study population consisted of 714,270 patients initiated on CPAP therapy between November 2015 and August 2018 who had at least one usage session of CPAP or APAP.
Overall, 90-day adherence to CPAP was 72.5%. Age, sex, and state of residence were all significantly associated with adherence rates (P less than .05). Specifically, adherence rates ranged from 54.8% among those 18-30 years of age to 79.1% among those 61-70 years of age. “There was a plateauing of adherence rates among those in their 70s, and men tended to have a higher adherence level than women across all age groups (73.3% vs. 71.4%, respectively),” he said. “Also, people who got started on CPAP in January had a higher level of adherence than people who got started in May. The differences are relatively small compared to the large age differences, but there was a consistent trend.”
When the researchers carried out age- and sex-adjusted analyses, they observed that adherence rates were lowest in the Northeast and Southwest and highest in the Upper Midwest and Mountain West. Adherence rates ranged from 50.8% in the District of Columbia and 60.5% in New York up to 81.2% in Idaho and 81.9% in South Dakota.
“The question is, is this variability explained by quality measures?” Dr. Patel asked. “We tried to answer this question by seeing whether the variability in adherence by location correlated with other metrics of health care quality.” To accomplish this, they used Dartmouth Atlas, a project that uses Medicare data to understand drivers of health care spending and quality. To understand geographic variability in CPAP adherence, they mapped ZIP codes onto hospital referral regions (HRRs), which are regional health care markets for tertiary medical care. Each HRR has at least one hospital that performs major cardiovascular procedures and neurosurgery. ZIP codes were mapped to 306 HRRs where the majority of residents get their tertiary care.
The researchers observed that Medicare enrollees who saw a primary care physician in the past 12 months had higher rates of adherence, compared with those who did not. “Twenty-three percent of the variance in CPAP adherence across the country can be explained by this measure of having a primary care doctor,” Dr. Patel said. In addition, patients who received care from HRRs located in the middle of the United States had high adherence rates. Top performers were facilities located in Madison, Wis.; Wausau, Wis.; Dubuque, Iowa; and Bloomington, Ill. Poor performers included facilities located in the boroughs of Manhattan and the Bronx, in New York; Muskegon, Mich.; Miami; and Buffalo, N.Y.
“Some of the geographical variability may be due to patient factors such as race, income, and education level,” Dr. Patel said. “That will need to be appropriately addressed in developing a quality of care measure. Nevertheless, some of the geographic variability appears to be related to health care system and provider factors. This variability could be potentially reduced through implementation of a CPAP adherence quality outcome measure.”
Dr. Patel disclosed that he has received grant/research support from Bayer Pharmaceuticals and Philips Respironics, and has served as a consultant to the American Academy of Sleep Medicine.
SOURCE: Patel SR et al. SLEEP 2019, Abstract 0513.
SAN ANTONIO –
However, whether the sources of variability stem from patient factors such as disease severity and socioeconomic status, provider factors, environmental factors, or selection biases in those who are diagnosed with obstructive sleep apnea and treated with CPAP remains to be understood, lead study author Sanjay R. Patel, MD, said at the annual meeting of the Associated Professional Sleep Societies.
In 2015, the American Academy of Sleep Medicine (AASM) endorsed CPAP adherence as a process measure, and the Centers for Medicare and Medicaid Services has used CPAP adherence as an outcome measure to limit long-term coverage of the therapy. It defines CPAP adherence as 4 or more hours of use on greater than 70% of nights in a consecutive 30-day period within the first 90 days. “Strengths of CPAP adherence as an outcome measure include the fact that it is easy to measure and it predicts improvement in sleepiness, quality of life, and blood pressure control,” said Dr. Patel, who directs the University of Pittsburgh’s Center for Sleep and Cardiovascular Outcomes Research. “One issue as to whether we should use CPAP adherence as an outcome-based quality of care measure is, does variability reflect performance at the provider and/or health care system?”
In an effort to describe CPAP adherence rates in general clinical practice as well as sources of variability, Dr. Patel and colleagues evaluated telemonitoring data maintained by Philips Respironics. The study population consisted of 714,270 patients initiated on CPAP therapy between November 2015 and August 2018 who had at least one usage session of CPAP or APAP.
Overall, 90-day adherence to CPAP was 72.5%. Age, sex, and state of residence were all significantly associated with adherence rates (P less than .05). Specifically, adherence rates ranged from 54.8% among those 18-30 years of age to 79.1% among those 61-70 years of age. “There was a plateauing of adherence rates among those in their 70s, and men tended to have a higher adherence level than women across all age groups (73.3% vs. 71.4%, respectively),” he said. “Also, people who got started on CPAP in January had a higher level of adherence than people who got started in May. The differences are relatively small compared to the large age differences, but there was a consistent trend.”
When the researchers carried out age- and sex-adjusted analyses, they observed that adherence rates were lowest in the Northeast and Southwest and highest in the Upper Midwest and Mountain West. Adherence rates ranged from 50.8% in the District of Columbia and 60.5% in New York up to 81.2% in Idaho and 81.9% in South Dakota.
“The question is, is this variability explained by quality measures?” Dr. Patel asked. “We tried to answer this question by seeing whether the variability in adherence by location correlated with other metrics of health care quality.” To accomplish this, they used Dartmouth Atlas, a project that uses Medicare data to understand drivers of health care spending and quality. To understand geographic variability in CPAP adherence, they mapped ZIP codes onto hospital referral regions (HRRs), which are regional health care markets for tertiary medical care. Each HRR has at least one hospital that performs major cardiovascular procedures and neurosurgery. ZIP codes were mapped to 306 HRRs where the majority of residents get their tertiary care.
The researchers observed that Medicare enrollees who saw a primary care physician in the past 12 months had higher rates of adherence, compared with those who did not. “Twenty-three percent of the variance in CPAP adherence across the country can be explained by this measure of having a primary care doctor,” Dr. Patel said. In addition, patients who received care from HRRs located in the middle of the United States had high adherence rates. Top performers were facilities located in Madison, Wis.; Wausau, Wis.; Dubuque, Iowa; and Bloomington, Ill. Poor performers included facilities located in the boroughs of Manhattan and the Bronx, in New York; Muskegon, Mich.; Miami; and Buffalo, N.Y.
“Some of the geographical variability may be due to patient factors such as race, income, and education level,” Dr. Patel said. “That will need to be appropriately addressed in developing a quality of care measure. Nevertheless, some of the geographic variability appears to be related to health care system and provider factors. This variability could be potentially reduced through implementation of a CPAP adherence quality outcome measure.”
Dr. Patel disclosed that he has received grant/research support from Bayer Pharmaceuticals and Philips Respironics, and has served as a consultant to the American Academy of Sleep Medicine.
SOURCE: Patel SR et al. SLEEP 2019, Abstract 0513.
SAN ANTONIO –
However, whether the sources of variability stem from patient factors such as disease severity and socioeconomic status, provider factors, environmental factors, or selection biases in those who are diagnosed with obstructive sleep apnea and treated with CPAP remains to be understood, lead study author Sanjay R. Patel, MD, said at the annual meeting of the Associated Professional Sleep Societies.
In 2015, the American Academy of Sleep Medicine (AASM) endorsed CPAP adherence as a process measure, and the Centers for Medicare and Medicaid Services has used CPAP adherence as an outcome measure to limit long-term coverage of the therapy. It defines CPAP adherence as 4 or more hours of use on greater than 70% of nights in a consecutive 30-day period within the first 90 days. “Strengths of CPAP adherence as an outcome measure include the fact that it is easy to measure and it predicts improvement in sleepiness, quality of life, and blood pressure control,” said Dr. Patel, who directs the University of Pittsburgh’s Center for Sleep and Cardiovascular Outcomes Research. “One issue as to whether we should use CPAP adherence as an outcome-based quality of care measure is, does variability reflect performance at the provider and/or health care system?”
In an effort to describe CPAP adherence rates in general clinical practice as well as sources of variability, Dr. Patel and colleagues evaluated telemonitoring data maintained by Philips Respironics. The study population consisted of 714,270 patients initiated on CPAP therapy between November 2015 and August 2018 who had at least one usage session of CPAP or APAP.
Overall, 90-day adherence to CPAP was 72.5%. Age, sex, and state of residence were all significantly associated with adherence rates (P less than .05). Specifically, adherence rates ranged from 54.8% among those 18-30 years of age to 79.1% among those 61-70 years of age. “There was a plateauing of adherence rates among those in their 70s, and men tended to have a higher adherence level than women across all age groups (73.3% vs. 71.4%, respectively),” he said. “Also, people who got started on CPAP in January had a higher level of adherence than people who got started in May. The differences are relatively small compared to the large age differences, but there was a consistent trend.”
When the researchers carried out age- and sex-adjusted analyses, they observed that adherence rates were lowest in the Northeast and Southwest and highest in the Upper Midwest and Mountain West. Adherence rates ranged from 50.8% in the District of Columbia and 60.5% in New York up to 81.2% in Idaho and 81.9% in South Dakota.
“The question is, is this variability explained by quality measures?” Dr. Patel asked. “We tried to answer this question by seeing whether the variability in adherence by location correlated with other metrics of health care quality.” To accomplish this, they used Dartmouth Atlas, a project that uses Medicare data to understand drivers of health care spending and quality. To understand geographic variability in CPAP adherence, they mapped ZIP codes onto hospital referral regions (HRRs), which are regional health care markets for tertiary medical care. Each HRR has at least one hospital that performs major cardiovascular procedures and neurosurgery. ZIP codes were mapped to 306 HRRs where the majority of residents get their tertiary care.
The researchers observed that Medicare enrollees who saw a primary care physician in the past 12 months had higher rates of adherence, compared with those who did not. “Twenty-three percent of the variance in CPAP adherence across the country can be explained by this measure of having a primary care doctor,” Dr. Patel said. In addition, patients who received care from HRRs located in the middle of the United States had high adherence rates. Top performers were facilities located in Madison, Wis.; Wausau, Wis.; Dubuque, Iowa; and Bloomington, Ill. Poor performers included facilities located in the boroughs of Manhattan and the Bronx, in New York; Muskegon, Mich.; Miami; and Buffalo, N.Y.
“Some of the geographical variability may be due to patient factors such as race, income, and education level,” Dr. Patel said. “That will need to be appropriately addressed in developing a quality of care measure. Nevertheless, some of the geographic variability appears to be related to health care system and provider factors. This variability could be potentially reduced through implementation of a CPAP adherence quality outcome measure.”
Dr. Patel disclosed that he has received grant/research support from Bayer Pharmaceuticals and Philips Respironics, and has served as a consultant to the American Academy of Sleep Medicine.
SOURCE: Patel SR et al. SLEEP 2019, Abstract 0513.
REPORTING FROM SLEEP 2019