Lillian Min1,2,3,4, Jin-Kyung Ha2, Carole E Aubert3,4,5,6, Timothy P Hofer3,4,7, Jeremy B Sussman3,4,7, Kenneth M Langa1,4,7,8, Mary Tinetti9, Hyungjin Myra Kim10,11, Matthew L Maciejewski12,13, Leah Gillon3, Angela Larkin3, Chiao-Li Chan2, Eve A Kerr3,4,7, Dawn Bravata14,15,16,17, William C Cushman18,19. 1. Veterans Affairs Geriatric Research, Education, and Clinical Center, Veterans Affairs Ann Arbor Medical Center, Ann Arbor, Michigan. 2. Division of Geriatric and Palliative Medicine, Department of Medicine, University of Michigan, Ann Arbor. 3. Veterans Affairs Center for Clinical Management Research, Health Services Research and Development Center of Innovation, Ann Arbor, Michigan. 4. Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor. 5. Department of General Internal Medicine, Bern University Hospital, University of Bern, Bern, Switzerland. 6. Institute of Primary Healthcare, University of Bern, Bern, Switzerland. 7. Division of General Internal Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor. 8. Institute for Social Research, University of Michigan, Ann Arbor. 9. Section of Geriatrics, Department of Medicine, Yale School of Medicine, New Haven, Connecticut. 10. Consulting for Statistics, Computing & Analytics Research, University of Michigan, Ann Arbor. 11. Department of Biostatistics, University of Michigan Medical School, Ann Arbor. 12. Center of Innovation to Accelerate Discovery and Practice Transformation, Veterans Affairs Healthcare System, Durham, North Carolina. 13. Department of Population Health Sciences, Duke University, Durham, North Carolina. 14. Veterans Affairs Health Services Research and Development Center for Health Information and Communication, Richard L. Roudebush Veterans Affairs Medical Center, Indianapolis, Indiana. 15. Department of Medicine, Indiana University School of Medicine, Indianapolis. 16. Department of Neurology, Indiana University School of Medicine, Indianapolis. 17. Center for Health Services Research, Regenstrief Institute, Indianapolis, Indiana. 18. Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis. 19. Medical Service, Memphis Veterans Affairs Medical Center, Memphis, Tennessee.
Abstract
Importance: Simple measures of hypertension treatment, such as achievement of blood pressure (BP) targets, ignore the intensity of treatment once the BP target is met. High-intensity treatment involves increased treatment burden and can be associated with potential adverse effects in older adults. A method was previously developed to identify older patients receiving intense hypertension treatment by low BP and number of BP medications using national Veterans Health Administration and Medicare Part D administrative pharmacy data to evaluate which BP medications a patient is likely taking on any given day. Objective: To further develop and validate a method to more precisely quantify dose intensity of hypertension treatment using only health system administrative pharmacy fill data. Design, Setting, and Participants: Observational, cross-sectional study of 319 randomly selected older veterans in the national Veterans Health Administration health care system who were taking multiple BP-lowering medications and had a total of 3625 ambulatory care visits from July 1, 2011, to June 30, 2013. Measure development and medical record review occurred January 1, 2017, through November 30, 2018, and data analysis was conducted from December 1, 2019, to August 31, 2020. Main Outcomes and Measures: For each BP-lowering medication, a moderate hypertension daily dose (HDD) was defined as half the maximum dose above which no further clinical benefit has been demonstrated by that medication in hypertension trials. Patients' total HDD was calculated using pharmacy data (pharmacy HDDs), accounting for substantial delays in refills (>30 days) when a patient's pill supply was stretched (eg, cutting existing pills in half). As an external comparison, the pharmacy HDDs were correlated with doses manually extracted from clinicians' visit notes (clinically noted HDDs). How well the pharmacy HDDs correlated with clinically noted HDDs was calculated (using C statistics). To facilitate interpretation, HDDs were described in association with the number of medications. Results: A total of 316 patients (99.1%) were male; the mean (SD) age was 75.6 (7.2) years. Pharmacy HDDs were highly correlated (r = 0.92) with clinically noted HDDs, with a mean (SD) of 2.7 (1.8) for pharmacy HDDs and 2.8 (1.8) for clinically noted HDDs. Pharmacy HDDs correlated with high-intensity, clinically noted HDDs ranging from a C statistic of 92.8% (95% CI, 92.0%-93.7%) for 2 or more clinically noted HDDs to 88.1% (95% CI, 85.5%-90.6%) for 6 or more clinically noted HDDs. Conclusions and Relevance: This study suggests that health system pharmacy data may be used to accurately quantify hypertension regimen dose intensity. Together with clinic-measured BP, this tool can be used in future health system-based research or quality improvement efforts to fine-tune, manage, and optimize hypertension treatment in older adults.
Importance: Simple measures of hypertension treatment, such as achievement of blood pressure (BP) targets, ignore the intensity of treatment once the BP target is met. High-intensity treatment involves increased treatment burden and can be associated with potential adverse effects in older adults. A method was previously developed to identify older patients receiving intense hypertension treatment by low BP and number of BP medications using national Veterans Health Administration and Medicare Part D administrative pharmacy data to evaluate which BP medications a patient is likely taking on any given day. Objective: To further develop and validate a method to more precisely quantify dose intensity of hypertension treatment using only health system administrative pharmacy fill data. Design, Setting, and Participants: Observational, cross-sectional study of 319 randomly selected older veterans in the national Veterans Health Administration health care system who were taking multiple BP-lowering medications and had a total of 3625 ambulatory care visits from July 1, 2011, to June 30, 2013. Measure development and medical record review occurred January 1, 2017, through November 30, 2018, and data analysis was conducted from December 1, 2019, to August 31, 2020. Main Outcomes and Measures: For each BP-lowering medication, a moderate hypertension daily dose (HDD) was defined as half the maximum dose above which no further clinical benefit has been demonstrated by that medication in hypertension trials. Patients' total HDD was calculated using pharmacy data (pharmacy HDDs), accounting for substantial delays in refills (>30 days) when a patient's pill supply was stretched (eg, cutting existing pills in half). As an external comparison, the pharmacy HDDs were correlated with doses manually extracted from clinicians' visit notes (clinically noted HDDs). How well the pharmacy HDDs correlated with clinically noted HDDs was calculated (using C statistics). To facilitate interpretation, HDDs were described in association with the number of medications. Results: A total of 316 patients (99.1%) were male; the mean (SD) age was 75.6 (7.2) years. Pharmacy HDDs were highly correlated (r = 0.92) with clinically noted HDDs, with a mean (SD) of 2.7 (1.8) for pharmacy HDDs and 2.8 (1.8) for clinically noted HDDs. Pharmacy HDDs correlated with high-intensity, clinically noted HDDs ranging from a C statistic of 92.8% (95% CI, 92.0%-93.7%) for 2 or more clinically noted HDDs to 88.1% (95% CI, 85.5%-90.6%) for 6 or more clinically noted HDDs. Conclusions and Relevance: This study suggests that health system pharmacy data may be used to accurately quantify hypertension regimen dose intensity. Together with clinic-measured BP, this tool can be used in future health system-based research or quality improvement efforts to fine-tune, manage, and optimize hypertension treatment in older adults.
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