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Islam MS, Kalmady SV, Hindle A, Sandhu R, Sun W, Sepehrvand N, Greiner R, Kaul P. Diagnostic and Prognostic Electrocardiogram-Based Models for Rapid Clinical Applications. Can J Cardiol 2024:S0828-282X(24)00523-3. [PMID: 38992812 DOI: 10.1016/j.cjca.2024.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 07/04/2024] [Accepted: 07/05/2024] [Indexed: 07/13/2024] Open
Abstract
Leveraging artificial intelligence (AI) for the analysis of electrocardiograms (ECGs) has the potential to transform diagnosis and estimate the prognosis of not only cardiac but, increasingly, noncardiac conditions. In this review, we summarize clinical studies and AI-enhanced ECG-based clinical applications in the early detection, diagnosis, and estimating prognosis of cardiovascular diseases in the past 5 years (2019-2023). With advancements in deep learning and the rapid increased use of ECG technologies, a large number of clinical studies have been published. However, most of these studies are single-centre, retrospective, proof-of-concept studies that lack external validation. Prospective studies that progress from development toward deployment in clinical settings account for < 15% of the studies. Successful implementations of ECG-based AI applications that have received approval from the Food and Drug Administration have been developed through commercial collaborations, with approximately half of them being for mobile or wearable devices. The field is in its early stages, and overcoming several obstacles is essential, such as prospective validation in multicentre large data sets, addressing technical issues, bias, privacy, data security, model generalizability, and global scalability. This review concludes with a discussion of these challenges and potential solutions. By providing a holistic view of the state of AI in ECG analysis, this review aims to set a foundation for future research directions, emphasizing the need for comprehensive, clinically integrated, and globally deployable AI solutions in cardiovascular disease management.
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Affiliation(s)
- Md Saiful Islam
- Canadian VIGOUR Centre, University of Alberta, Edmonton, Alberta, Canada; Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
| | - Sunil Vasu Kalmady
- Canadian VIGOUR Centre, University of Alberta, Edmonton, Alberta, Canada; Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada
| | - Abram Hindle
- Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada
| | - Roopinder Sandhu
- Canadian VIGOUR Centre, University of Alberta, Edmonton, Alberta, Canada; Smidt Heart Institute, Cedars-Sinai Medical Center Hospital System, Los Angeles, California, USA
| | - Weijie Sun
- Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada
| | - Nariman Sepehrvand
- Canadian VIGOUR Centre, University of Alberta, Edmonton, Alberta, Canada; Department of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Russell Greiner
- Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada; Alberta Machine Intelligence Institute, Edmonton, Alberta, Canada
| | - Padma Kaul
- Canadian VIGOUR Centre, University of Alberta, Edmonton, Alberta, Canada; Department of Medicine, University of Alberta, Edmonton, Alberta, Canada.
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Corrêa R, Froner MB, Tabak BM. Assessing the Impact of Behavioral Sciences Interventions on Chronic Disease Prevention and Management: A Systematic Review of Randomized Controlled Trials. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2024; 21:837. [PMID: 39063414 PMCID: PMC11277013 DOI: 10.3390/ijerph21070837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2024] [Revised: 06/15/2024] [Accepted: 06/21/2024] [Indexed: 07/28/2024]
Abstract
Studies have highlighted the importance of applying Behavioral Sciences interventions to develop equity in the prevention of chronic diseases in the public health domain. Our study aims to assess the evidence of this influence. We undertook a systematic review study using the electronic databases PubMed, Web of Science, Scopus and Cochrane, searching for work published between 2013 and 2023. The research analyzed the influence of Behavioral Sciences intervention studies on public health. This review was registered and published in PROSPERO, registration number CRD42023412377. The systematic search identified 2951 articles. The review analyzed 26 studies. The quality assessment of the articles showed an overall average of 74%, with the majority of studies being of high quality. The interventions with the best evidence for chronic diseases used framing messages, nudges and vouchers. Messages with incentives also showed satisfactory evidence. The most prevalent outcomes were related to screening tests and patient adherence to treatment. The current state of decision-making remains mainly at the patient level, with potential for further exploration of the roles of healthcare professionals and decision-makers in future research efforts. Limitations relate to the heterogeneity of the study sample, which hinders a more precise analysis of specific interventions and outcomes in chronic diseases.
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Affiliation(s)
- Rafael Corrêa
- School of Public Policy and Government, Getulio Vargas Foundation, SGAN 602 Módulos A,B,C, Asa Norte, Brasília 70830-020, Brazil; (M.B.F.); (B.M.T.)
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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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Persell SD, Petito LC, Lee JY, Meeker D, Doctor JN, Goldstein NJ, Fox CR, Rowe TA, Linder JA, Chmiel R, Peprah YA, Brown T. Reducing Care Overuse in Older Patients Using Professional Norms and Accountability : A Cluster Randomized Controlled Trial. Ann Intern Med 2024; 177:324-334. [PMID: 38315997 DOI: 10.7326/m23-2183] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2024] Open
Abstract
BACKGROUND Effective strategies are needed to curtail overuse that may lead to harm. OBJECTIVE To evaluate the effects of clinician decision support redirecting attention to harms and engaging social and reputational concerns on overuse in older primary care patients. DESIGN 18-month, single-blind, pragmatic, cluster randomized trial, constrained randomization. (ClinicalTrials.gov: NCT04289753). SETTING 60 primary care internal medicine, family medicine and geriatrics practices within a health system from 1 September 2020 to 28 February 2022. PARTICIPANTS 371 primary care clinicians and their older adult patients from participating practices. INTERVENTION Behavioral science-informed, point-of-care, clinical decision support tools plus brief case-based education addressing the 3 primary clinical outcomes (187 clinicians from 30 clinics) were compared with brief case-based education alone (187 clinicians from 30 clinics). Decision support was designed to increase salience of potential harms, convey social norms, and promote accountability. MEASUREMENTS Prostate-specific antigen (PSA) testing in men aged 76 years and older without previous prostate cancer, urine testing for nonspecific reasons in women aged 65 years and older, and overtreatment of diabetes with hypoglycemic agents in patients aged 75 years and older and hemoglobin A1c (HbA1c) less than 7%. RESULTS At randomization, mean clinic annual PSA testing, unspecified urine testing, and diabetes overtreatment rates were 24.9, 23.9, and 16.8 per 100 patients, respectively. After 18 months of intervention, the intervention group had lower adjusted difference-in-differences in annual rates of PSA testing (-8.7 [95% CI, -10.2 to -7.1]), unspecified urine testing (-5.5 [CI, -7.0 to -3.6]), and diabetes overtreatment (-1.4 [CI, -2.9 to -0.03]) compared with education only. Safety measures did not show increased emergency care related to urinary tract infections or hyperglycemia. An HbA1c greater than 9.0% was more common with the intervention among previously overtreated diabetes patients (adjusted difference-in-differences, 0.47 per 100 patients [95% CI, 0.04 to 1.20]). LIMITATION A single health system limits generalizability; electronic health data limit ability to differentiate between overtesting and underdocumentation. CONCLUSION Decision support designed to increase clinicians' attention to possible harms, social norms, and reputational concerns reduced unspecified testing compared with offering traditional case-based education alone. Small decreases in diabetes overtreatment may also result in higher rates of uncontrolled diabetes. PRIMARY FUNDING SOURCE National Institute on Aging.
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Affiliation(s)
- Stephen D Persell
- Division of General Internal Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago; and Center for Primary Care Innovation, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (S.D.P., J.A.L.)
| | - Lucia C Petito
- Division of Biostatistics, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (L.C.P.)
| | - Ji Young Lee
- Division of General Internal Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (J.Y.L., T.A.R., Y.A.P., T.B.)
| | | | - Jason N Doctor
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California (J.N.D.)
| | - Noah J Goldstein
- UCLA Anderson School of Management, UCLA Geffen School of Medicine, Los Angeles, California (N.J.G., C.R.F.)
| | - Craig R Fox
- UCLA Anderson School of Management, UCLA Geffen School of Medicine, Los Angeles, California (N.J.G., C.R.F.)
| | - Theresa A Rowe
- Division of General Internal Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (J.Y.L., T.A.R., Y.A.P., T.B.)
| | - Jeffrey A Linder
- Division of General Internal Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago; and Center for Primary Care Innovation, Institute for Public Health and Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (S.D.P., J.A.L.)
| | - Ryan Chmiel
- Information Services, Northwestern Memorial HealthCare, Chicago, Illinois (R.C.)
| | - Yaw Amofa Peprah
- Division of General Internal Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (J.Y.L., T.A.R., Y.A.P., T.B.)
| | - Tiffany Brown
- Division of General Internal Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois (J.Y.L., T.A.R., Y.A.P., T.B.)
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Segal JB. Reducing Low-Value Health Care. Ann Intern Med 2024; 177:397-398. [PMID: 38315995 DOI: 10.7326/m24-3501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2024] Open
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Hashemi S, Bai L, Gao S, Burstein F, Renzenbrink K. Sharpening clinical decision support alert and reminder designs with MINDSPACE: A systematic review. Int J Med Inform 2024; 181:105276. [PMID: 37948981 DOI: 10.1016/j.ijmedinf.2023.105276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 10/07/2023] [Accepted: 10/28/2023] [Indexed: 11/12/2023]
Abstract
BACKGROUND Clinical decision support (CDS) alerts and reminders aim to influence clinical decisions, yet they are often designed without considering human decision-making behaviour. While this behaviour is comprehensively described by behavioural economics (BE), the sheer volume of BE literature poses a challenge to designers when identifying behavioural effects with utility to alert and reminder designs. This study tackles this challenge by focusing on the MINDSPACE framework for behaviour change, which collates nine behavioural effects that profoundly influence human decision-making behaviour: Messenger, Incentives, Norms, Defaults, Salience, Priming, Affect, Commitment, and Ego. METHOD A systematic review searching MEDLINE, Embase, PsycINFO, and CINAHL Plus to explore (i) the usage of MINDSPACE effects in alert and reminder designs and (ii) the efficacy of those alerts and reminders in influencing clinical decisions. The search queries comprised ten Boolean searches, with nine focusing on the MINDSPACE effects and one focusing on the term mindspace. RESULTS 50 studies were selected from 1791 peer-reviewed journal articles in English from 1970 to 2022. Except for ego, eight of nine MINDSPACE effects were utilised to design alerts and reminders, with defaults and norms utilised the most in alerts and reminders, respectively. Overall, alerts and reminders informed by MINDSPACE effects showed an average 71% success rate in influencing clinical decisions (alerts 73%, reminders 69%). Most studies utilised a single effect in their design, with higher efficacy for alerts (64%) than reminders (41%). Others utilised multiple effects, showing higher efficacy for reminders (28%) than alerts (9%). CONCLUSION This review presents sufficient evidence demonstrating the MINDSPACE framework's merits for designing CDS alerts and reminders with human decision-making considerations. The framework can adequately address challenges in identifying behavioural effects pertinent to the effective design of CDS alerts and reminders. The review also identified opportunities for future research into other relevant effects (e.g., framing).
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Affiliation(s)
- Sarang Hashemi
- Department of Human-Centred Computing, Faculty of Information Technology, Monash University, Melbourne, VIC, Australia.
| | - Lu Bai
- Department of Human-Centred Computing, Faculty of Information Technology, Monash University, Melbourne, VIC, Australia
| | - Shijia Gao
- Department of Human-Centred Computing, Faculty of Information Technology, Monash University, Melbourne, VIC, Australia
| | - Frada Burstein
- Department of Human-Centred Computing, Faculty of Information Technology, Monash University, Melbourne, VIC, Australia
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Bednorz A, Mak JKL, Jylhävä J, Religa D. Use of Electronic Medical Records (EMR) in Gerontology: Benefits, Considerations and a Promising Future. Clin Interv Aging 2023; 18:2171-2183. [PMID: 38152074 PMCID: PMC10752027 DOI: 10.2147/cia.s400887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 11/05/2023] [Indexed: 12/29/2023] Open
Abstract
Electronic medical records (EMRs) have many benefits in clinical research in gerontology, enabling data analysis, development of prognostic tools and disease risk prediction. EMRs also offer a range of advantages in clinical practice, such as comprehensive medical records, streamlined communication with healthcare providers, remote data access, and rapid retrieval of test results, ultimately leading to increased efficiency, enhanced patient safety, and improved quality of care in gerontology, which includes benefits like reduced medication use and better patient history taking and physical examination assessments. The use of artificial intelligence (AI) and machine learning (ML) approaches on EMRs can further improve disease diagnosis, symptom classification, and support clinical decision-making. However, there are also challenges related to data quality, data entry errors, as well as the ethics and safety of using AI in healthcare. This article discusses the future of EMRs in gerontology and the application of AI and ML in clinical research. Ethical and legal issues surrounding data sharing and the need for healthcare professionals to critically evaluate and integrate these technologies are also emphasized. The article concludes by discussing the challenges related to the use of EMRs in research as well as in their primary intended use, the daily clinical practice.
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Affiliation(s)
- Adam Bednorz
- John Paul II Geriatric Hospital, Katowice, Poland
- Institute of Psychology, Humanitas Academy, Sosnowiec, Poland
| | - Jonathan K L Mak
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), University of Tampere, Tampere, Finland
| | - Dorota Religa
- Division of Clinical Geriatrics, Department of Neurobiology, Care sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
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Brown T, Zelch B, Lee JY, Doctor JN, Linder JA, Sullivan MD, Goldstein NJ, Rowe TA, Meeker D, Knight T, Friedberg MW, Persell SD. A Qualitative Description of Clinician Free-Text Rationales Entered within Accountable Justification Interventions. Appl Clin Inform 2022; 13:820-827. [PMID: 36070799 PMCID: PMC9451951 DOI: 10.1055/s-0042-1756366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Requiring accountable justifications-visible, clinician-recorded explanations for not following a clinical decision support (CDS) alert-has been used to steer clinicians away from potentially guideline-discordant decisions. Understanding themes from justifications across clinical content areas may reveal how clinicians rationalize decisions and could help inform CDS alerts. METHODS We conducted a qualitative evaluation of the free-text justifications entered by primary care physicians from three pilot interventions designed to reduce opioid prescribing and, in older adults, high-risk polypharmacy and overtesting. Clinicians encountered alerts when triggering conditions were met within the chart. Clinicians were asked to change their course of action or enter a justification for the action that would be displayed in the chart. We extracted all justifications and grouped justifications with common themes. Two authors independently coded each justification and resolved differences via discussion. Three physicians used a modified Delphi technique to rate the clinical appropriateness of the justifications. RESULTS There were 560 justifications from 50 unique clinicians. We grouped these into three main themes used to justify an action: (1) report of a particular diagnosis or symptom (e.g., for "anxiety" or "acute pain"); (2) provision of further contextual details about the clinical case (e.g., tried and failed alternatives, short-term supply, or chronic medication); and (3) noting communication between clinician and patient (e.g., "risks and benefits discussed"). Most accountable justifications (65%) were of uncertain clinical appropriateness. CONCLUSION Most justifications clinicians entered across three separate clinical content areas fit within a small number of themes, and these common rationales may aid in the design of effective accountable justification interventions. Justifications varied in terms of level of clinical detail. On their own, most justifications did not clearly represent appropriate clinical decision making.
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Affiliation(s)
- Tiffany Brown
- Division of General Internal Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States
| | - Brittany Zelch
- Loyola University Chicago Stritch School of Medicine, Maywood, Illinois, United States
| | - Ji Young Lee
- Division of General Internal Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States
| | - Jason N. Doctor
- Leonard D. Schaeffer Center for Health Policy & Economics, University of Southern California, Los Angeles, California, United States
| | - Jeffrey A. Linder
- Division of General Internal Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States
| | - Mark D. Sullivan
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington, United States
| | - Noah J. Goldstein
- Anderson School of Management, University of California at Los Angeles, Los Angeles, California, United States
| | - Theresa A. Rowe
- Division of General Internal Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States
| | - Daniella Meeker
- Leonard D. Schaeffer Center for Health Policy & Economics, University of Southern California, Los Angeles, California, United States
| | - Tara Knight
- Leonard D. Schaeffer Center for Health Policy & Economics, University of Southern California, Los Angeles, California, United States
| | - Mark W. Friedberg
- Blue Cross Blue Shield of Massachusetts, Boston, Massachusetts, United States,Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States
| | - Stephen D. Persell
- Division of General Internal Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States,Center for Primary Care Innovation, Institute for Public Health and Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States,Address for correspondence Stephen D. Persell, MD, MPH 750N Lake Shore Dr., 10th Floor, Chicago, IL 60611United States
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