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Figure.  Statin Prescribing Rates by Primary Care Appointment Time
Statin Prescribing Rates by Primary Care Appointment Time

Unadjusted data are from March 1, 2019, to February 29, 2020, and are based on each patient’s first new or return visit with their primary care practitioner. Primary care appointment times are grouped by the start of each hour (eg, 8:15 am and 8:30 am were placed in the 8 am group).

Table.  Adjusted Odds of Statin Prescribing by Primary Care Appointment Time
Adjusted Odds of Statin Prescribing by Primary Care Appointment Time
1.
Virani  SS, Alonso  A, Benjamin  EJ,  et al; American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee.  Heart disease and stroke statistics—2020 update: a report from the American Heart Association.   Circulation. 2020;141(9):e139-e596. doi:10.1161/CIR.0000000000000757PubMedGoogle ScholarCrossref
2.
Grundy  SM, Stone  NJ, Bailey  AL,  et al.  2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.   J Am Coll Cardiol. 2019;73(24):3168-3209. doi:10.1016/j.jacc.2018.11.002PubMedGoogle ScholarCrossref
3.
Salami  JA, Warraich  H, Valero-Elizondo  J,  et al.  National trends in statin use and expenditures in the US adult population from 2002 to 2013: insights from the medical expenditure panel survey.   JAMA Cardiol. 2017;2(1):56-65. doi:10.1001/jamacardio.2016.4700PubMedGoogle ScholarCrossref
4.
Kim  RH, Day  SC, Small  DS, Snider  CK, Rareshide  CAL, Patel  MS.  Variations in influenza vaccination by clinic appointment time and an active choice intervention in the electronic health record to increase influenza vaccination.   JAMA Netw Open. 2018;1(5):e181770. doi:10.1001/jamanetworkopen.2018.1770PubMedGoogle Scholar
5.
Hsiang  EY, Mehta  SJ, Small  DS,  et al.  Association of primary care clinic appointment time with clinician ordering and patient completion of breast and colorectal cancer screening.   JAMA Netw Open. 2019;2(5):e193403. doi:10.1001/jamanetworkopen.2019.3403PubMedGoogle Scholar
6.
Philpot  LM, Khokhar  BA, Roellinger  DL, Ramar  P, Ebbert  JO.  Time of day is associated with opioid prescribing for low back pain in primary care.   J Gen Intern Med. 2018;33(11):1828-1830. doi:10.1007/s11606-018-4521-8PubMedGoogle ScholarCrossref
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    Research Letter
    Health Policy
    May 11, 2021

    Assessment of Primary Care Appointment Times and Appropriate Prescribing of Statins for At-Risk Patients

    Author Affiliations
    • 1Penn Medicine Nudge Unit, University of Pennsylvania, Philadelphia
    • 2Perelman School of Medicine, University of Pennsylvania, Philadelphia
    • 3Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania
    • 4Wharton School, University of Pennsylvania, Philadelphia
    JAMA Netw Open. 2021;4(5):e219050. doi:10.1001/jamanetworkopen.2021.9050
    Introduction

    Cardiovascular disease is the leading cause of adult morbidity and mortality in the United States and globally.1 Guideline-directed statin therapy has been demonstrated to reduce the risk of major adverse cardiovascular events,2 yet half of statin-eligible patients have not been prescribed one.3 In prior work, we observed that rates of preventive care including influenza vaccination and cancer screening declined as the clinic day progressed.4,5 It is unknown whether this pattern exists with statin prescribing. Our objective was to evaluate the association between primary care appointment times and statin prescribing rates for patients with elevated risk of major adverse cardiovascular events.

    Methods

    This cohort study was approved by the University of Pennsylvania institutional review board with a waiver for consent because the study posed minimal risk and because it was infeasible given the retrospective study design. We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

    Clarity, an Epic reporting database, was used to obtain data from 28 Penn Medicine primary care practices. We included each patient’s first new or return visit with their primary care practitioner (PCP) March 1, 2019, to February 29, 2020. Statin eligibility was based on the United States Preventive Services Task Force guidelines, presence of clinical atherosclerotic cardiovascular disease (ASCVD) or familial hypercholesterolemia diagnosis, or low-density lipoprotein cholesterol greater than or equal to 190 mg/dL (to convert to millimoles per liter, multiply by 0.0259). Patients were excluded if they were already taking a statin or had documented statin intolerance. Race/ethnicity was self-reported. The primary outcome measure was presence of a statin prescription on the day of the visit.

    Appointments from 8:00 am to 4:59 pm were grouped by the hour. In the adjusted analysis, we fit a conditional logistic regression conditioned on PCP consistent with prior work.5 We used this model because it stratified the analysis by clinician, thereby avoiding comparing clinicians who only practice in the afternoon with those who only practice in the morning. Models were adjusted for patient demographic characteristics (age, sex, race/ethnicity, and income), insurance type, Charlson Comorbidity Index, clinical ASCVD diagnosis, appointment type, and fixed effects by practice and month. In addition to covariates for each hour, models were fit to compare morning (8:00 am to 11:59 am) vs afternoon (12:00 pm to 4:59 pm) appointments and a continuous time variable. Two-sided hypothesis tests used a significance level of .05, and analyses were conducted using Python version 3.8.6 (Python Software Foundation) and the statsmodels package version 0.12.1. Statistical analysis was performed from November 2020 to February 2021.

    Results

    The sample comprised 10 757 patients with a mean (SD) age of 66.0 (10.5) years; 5072 (47.2%) were female, and 7071 (65.7%) were White. Patient characteristics were similar between morning and afternoon appointments. Overall, statins were prescribed in 3864 visits (35.9%). Statins were prescribed in 2447 morning visits (37.5%) and 1417 afternoon visits (33.4%) (Figure). Compared with 8 am (reference group), the adjusted odds ratio (aOR) of statin prescribing was significantly lower at all hours except 9 am (eg, 9 am: 0.88 [95% CI, 0.76-1.02]; P = .10; 10 am: 0.85 [95% CI, 0.73-0.99]; P = .04; 12 pm: 0.63 [95% CI, 0.49-0.83]; P = .001; 3 pm: 0.69 [95% CI, 0.57-0.82]; P < .001). Compared with morning appointments, the odds of statin prescribing during afternoon appointments were significantly lower (aOR, 0.79; 95% CI, 0.73-0.87; P < .001). The overall time trend for statin prescribing decreased significantly (aOR, 0.95; 95% CI, 0.94-0.97; P < .001) (Table).

    Discussion

    Among a primary care network of 28 practices, statin prescribing decreased significantly as the day progressed, particularly in the afternoon relative to the morning. To our knowledge, this is one of the first studies to evaluate statin prescribing variations by appointment time. These findings are likely multifactorial in nature. First, as the day progresses clinicians may run behind schedule which can lead to rushed interactions, decreased bandwidth for discussions of indicated therapies, or implicit agreements to defer complex decisions.6 Second, as the day progresses, clinicians and patients are more likely to face decision fatigue, or the erosion of initiative that results from the cumulative cognitive burden of a long session of decision-making.4,5

    This study was limited by its observational design at one health system. Future interventions targeting improvements in statin prescribing should consider the influence of time of day.

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    Article Information

    Accepted for Publication: March 16, 2021.

    Published: May 11, 2021. doi:10.1001/jamanetworkopen.2021.9050

    Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Hare AJ et al. JAMA Network Open.

    Corresponding Author: Allison J. Hare, BS, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA 19104 (allison.hare@pennmedicine.upenn.edu).

    Author Contributions: Ms Hare had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Hare, Adusumalli, Patel.

    Acquisition, analysis, or interpretation of data: Hare, Adusumalli, Park.

    Drafting of the manuscript: Hare, Adusumalli, Park.

    Critical revision of the manuscript for important intellectual content: All authors.

    Statistical analysis: Hare, Adusumalli, Park.

    Obtained funding: Patel.

    Administrative, technical, or material support: Park, Patel.

    Supervision: Patel.

    Conflict of Interest Disclosures: Dr Patel reported being the founder of Catalyst Health, a technology and behavior change consulting firm; member of the medical advisory board for Healthmine Services, Life.io, and Holistic Industries; and Dr Patel also has received research funding from Deloitte, which is not related to the work described in this manuscript. No other disclosures were reported.

    Funding/Support: This study was supported by a grant from the National Institute on Aging (1R33AG057380) to Dr Patel and the University of Pennsylvania Health System through the Penn Medicine Nudge Unit.

    Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

    References
    1.
    Virani  SS, Alonso  A, Benjamin  EJ,  et al; American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee.  Heart disease and stroke statistics—2020 update: a report from the American Heart Association.   Circulation. 2020;141(9):e139-e596. doi:10.1161/CIR.0000000000000757PubMedGoogle ScholarCrossref
    2.
    Grundy  SM, Stone  NJ, Bailey  AL,  et al.  2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.   J Am Coll Cardiol. 2019;73(24):3168-3209. doi:10.1016/j.jacc.2018.11.002PubMedGoogle ScholarCrossref
    3.
    Salami  JA, Warraich  H, Valero-Elizondo  J,  et al.  National trends in statin use and expenditures in the US adult population from 2002 to 2013: insights from the medical expenditure panel survey.   JAMA Cardiol. 2017;2(1):56-65. doi:10.1001/jamacardio.2016.4700PubMedGoogle ScholarCrossref
    4.
    Kim  RH, Day  SC, Small  DS, Snider  CK, Rareshide  CAL, Patel  MS.  Variations in influenza vaccination by clinic appointment time and an active choice intervention in the electronic health record to increase influenza vaccination.   JAMA Netw Open. 2018;1(5):e181770. doi:10.1001/jamanetworkopen.2018.1770PubMedGoogle Scholar
    5.
    Hsiang  EY, Mehta  SJ, Small  DS,  et al.  Association of primary care clinic appointment time with clinician ordering and patient completion of breast and colorectal cancer screening.   JAMA Netw Open. 2019;2(5):e193403. doi:10.1001/jamanetworkopen.2019.3403PubMedGoogle Scholar
    6.
    Philpot  LM, Khokhar  BA, Roellinger  DL, Ramar  P, Ebbert  JO.  Time of day is associated with opioid prescribing for low back pain in primary care.   J Gen Intern Med. 2018;33(11):1828-1830. doi:10.1007/s11606-018-4521-8PubMedGoogle ScholarCrossref
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