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Samal L, Kilgallon JL, Lipsitz S, Baer HJ, McCoy A, Gannon M, Noonan S, Dunk R, Chen SW, Chay WI, Fay R, Garabedian PM, Wu E, Wien M, Blecker S, Salmasian H, Bonventre JV, McMahon GM, Bates DW, Waikar SS, Linder JA, Wright A, Dykes P. Clinical Decision Support for Hypertension Management in Chronic Kidney Disease: A Randomized Clinical Trial. JAMA Intern Med 2024; 184:484-492. [PMID: 38466302 PMCID: PMC10928544 DOI: 10.1001/jamainternmed.2023.8315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 12/11/2023] [Indexed: 03/12/2024]
Abstract
Importance Chronic kidney disease (CKD) affects 37 million adults in the United States, and for patients with CKD, hypertension is a key risk factor for adverse outcomes, such as kidney failure, cardiovascular events, and death. Objective To evaluate a computerized clinical decision support (CDS) system for the management of uncontrolled hypertension in patients with CKD. Design, Setting, and Participants This multiclinic, randomized clinical trial randomized primary care practitioners (PCPs) at a primary care network, including 15 hospital-based, ambulatory, and community health center-based clinics, through a stratified, matched-pair randomization approach February 2021 to February 2022. All adult patients with a visit to a PCP in the last 2 years were eligible and those with evidence of CKD and hypertension were included. Intervention The intervention consisted of a CDS system based on behavioral economic principles and human-centered design methods that delivered tailored, evidence-based recommendations, including initiation or titration of renin-angiotensin-aldosterone system inhibitors. The patients in the control group received usual care from PCPs with the CDS system operating in silent mode. Main Outcomes and Measures The primary outcome was the change in mean systolic blood pressure (SBP) between baseline and 180 days compared between groups. The primary analysis was a repeated measures linear mixed model, using SBP at baseline, 90 days, and 180 days in an intention-to-treat repeated measures model to account for missing data. Secondary outcomes included blood pressure (BP) control and outcomes such as percentage of patients who received an action that aligned with the CDS recommendations. Results The study included 174 PCPs and 2026 patients (mean [SD] age, 75.3 [0.3] years; 1223 [60.4%] female; mean [SD] SBP at baseline, 154.0 [14.3] mm Hg), with 87 PCPs and 1029 patients randomized to the intervention and 87 PCPs and 997 patients randomized to usual care. Overall, 1714 patients (84.6%) were treated for hypertension at baseline. There were 1623 patients (80.1%) with an SBP measurement at 180 days. From the linear mixed model, there was a statistically significant difference in mean SBP change in the intervention group compared with the usual care group (change, -14.6 [95% CI, -13.1 to -16.0] mm Hg vs -11.7 [-10.2 to -13.1] mm Hg; P = .005). There was no difference in the percentage of patients who achieved BP control in the intervention group compared with the control group (50.4% [95% CI, 46.5% to 54.3%] vs 47.1% [95% CI, 43.3% to 51.0%]). More patients received an action aligned with the CDS recommendations in the intervention group than in the usual care group (49.9% [95% CI, 45.1% to 54.8%] vs 34.6% [95% CI, 29.8% to 39.4%]; P < .001). Conclusions and Relevance These findings suggest that implementing this computerized CDS system could lead to improved management of uncontrolled hypertension and potentially improved clinical outcomes at the population level for patients with CKD. Trial Registration ClinicalTrials.gov Identifier: NCT03679247.
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Affiliation(s)
- Lipika Samal
- Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - John L. Kilgallon
- Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Hackensack Meridian School of Medicine, Nutley, New Jersey
| | - Stuart Lipsitz
- Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Heather J. Baer
- Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Allison McCoy
- Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee
| | - Michael Gannon
- Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Eastern Virginia Medical School, Norfolk
| | - Sarah Noonan
- Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- USC School of Medicine Greenville, Greenville, South Carolina
| | - Ryan Dunk
- Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Sarah W. Chen
- Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Weng Ian Chay
- Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Richard Fay
- Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | | | - Edward Wu
- Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Alabama College of Osteopathic Medicine, Dothan
| | - Matthew Wien
- Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Saul Blecker
- Department of Medicine, NYU Grossman School of Medicine, New York, New York
| | | | - Joseph V. Bonventre
- Division of Renal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Gearoid M. McMahon
- Division of Renal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - David W. Bates
- Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Sushrut S. Waikar
- Section of Nephrology, Boston Medical Center, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts
| | - Jeffrey A. Linder
- Division of General Internal Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Adam Wright
- Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee
| | - Patricia Dykes
- Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
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Kullgren JT, Kim HM, Slowey M, Colbert J, Soyster B, Winston SA, Ryan K, Forman JH, Riba M, Krupka E, Kerr EA. Using Behavioral Economics to Reduce Low-Value Care Among Older Adults: A Cluster Randomized Clinical Trial. JAMA Intern Med 2024; 184:281-290. [PMID: 38285565 PMCID: PMC10825788 DOI: 10.1001/jamainternmed.2023.7703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 11/22/2023] [Indexed: 01/31/2024]
Abstract
Importance Use of low-value care is common among older adults. It is unclear how to best engage clinicians and older patients to decrease use of low-value services. Objective To test whether the Committing to Choose Wisely behavioral economic intervention could engage primary care clinicians and older patients to reduce low-value care. Design, Setting, and Participants Stepped-wedge cluster randomized clinical trial conducted at 8 primary care clinics of an academic health system and a private group practice between December 12, 2017, and September 4, 2019. Participants were primary care clinicians and older adult patients who had diabetes, insomnia, or anxiety or were eligible for prostate cancer screening. Data analysis was performed from October 2019 to November 2023. Intervention Clinicians were invited to commit in writing to Choosing Wisely recommendations for older patients to avoid use of hypoglycemic medications to achieve tight glycemic control, sedative-hypnotic medications for insomnia or anxiety, and prostate-specific antigen tests to screen for prostate cancer. Committed clinicians had their photographs displayed on clinic posters and received weekly emails with alternatives to these low-value services. Educational handouts were mailed to applicable patients before scheduled visits and available at the point of care. Main Outcomes and Measures Patient-months with a low-value service across conditions (primary outcome) and separately for each condition (secondary outcomes). For patients with diabetes, or insomnia or anxiety, secondary outcomes were patient-months in which targeted medications were decreased or stopped (ie, deintensified). Results The study included 81 primary care clinicians and 8030 older adult patients (mean [SD] age, 75.1 [7.2] years; 4076 men [50.8%] and 3954 women [49.2%]). Across conditions, a low-value service was used in 7627 of the 37 116 control patient-months (20.5%) and 7416 of the 46 381 intervention patient-months (16.0%) (adjusted odds ratio, 0.79; 95% CI, 0.65-0.97). For each individual condition, there were no significant differences between the control and intervention periods in the odds of patient-months with a low-value service. The intervention increased the odds of deintensification of hypoglycemic medications for diabetes (adjusted odds ratio, 1.85; 95% CI, 1.06-3.24) but not sedative-hypnotic medications for insomnia or anxiety. Conclusions and Relevance In this stepped-wedge cluster randomized clinical trial, the Committing to Choose Wisely behavioral economic intervention reduced low-value care across 3 common clinical situations and increased deintensification of hypoglycemic medications for diabetes. Use of scalable interventions that nudge patients and clinicians to achieve greater value while preserving autonomy in decision-making should be explored more broadly. Trial Registration ClinicalTrials.gov Identifier: NCT03411525.
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Affiliation(s)
- Jeffrey T. Kullgren
- Veterans Affairs Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
- Department of Health Management and Policy, University of Michigan School of Public Health, Ann Arbor
- University of Michigan Center for Bioethics and Social Sciences in Medicine, Ann Arbor
| | - H. Myra Kim
- Veterans Affairs Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
| | - Megan Slowey
- Center for Health and Research Transformation, Ann Arbor, Michigan
| | - Joseph Colbert
- University of Michigan Center for Bioethics and Social Sciences in Medicine, Ann Arbor
| | - Barbara Soyster
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
| | | | - Kerry Ryan
- University of Michigan Center for Bioethics and Social Sciences in Medicine, Ann Arbor
| | - Jane H. Forman
- Veterans Affairs Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan
| | - Melissa Riba
- Center for Health and Research Transformation, Ann Arbor, Michigan
| | - Erin Krupka
- University of Michigan School of Information, Ann Arbor
| | - Eve A. Kerr
- Veterans Affairs Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor
- University of Michigan Institute for Healthcare Policy and Innovation, Ann Arbor
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