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21.10.2016 | Original Research

Defining Team Effort Involved in Patient Care from the Primary Care Physician’s Perspective

verfasst von: Andrew S. Hwang, MD MPH, Steven J. Atlas, MD MPH, Johan Hong, AB, Jeffrey M. Ashburner, PhD, MPH, Adrian H. Zai, MD, PhD, MPH, Richard W. Grant, MD, MPH, Clemens S. Hong, MD, MPH

Erschienen in: Journal of General Internal Medicine | Ausgabe 3/2017

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Abstract

Background

A better understanding of the attributes of patients who require more effort to manage may improve risk adjustment approaches and lead to more efficient resource allocation, improved patient care and health outcomes, and reduced burnout in primary care clinicians.

Objective

To identify and characterize high-effort patients from the physician’s perspective.

Design

Cohort study.

Participants

Ninety-nine primary care physicians in an academic primary care network.

Main Measures

From a list of 100 randomly selected patients in their panels, PCPs identified patients who required a high level of team-based effort and patients they considered complex. For high-effort patients, PCPs indicated which factors influenced their decision: medical/care coordination, behavioral health, and/or socioeconomic factors. We examined differences in patient characteristics based on PCP-defined effort and complexity.

Key Results

Among 9594 eligible patients, PCPs classified 2277 (23.7 %) as high-effort and 2676 (27.9 %) as complex. Behavioral health issues were the major driver of effort in younger patients, while medical/care coordination issues predominated in older patients. Compared to low-effort patients, high-effort patients were significantly (P < 0.01 for all) more likely to have higher rates of medical (e.g. 23.2 % vs. 6.3 % for diabetes) and behavioral health problems (e.g. 9.8 % vs. 2.9 % for substance use disorder), more frequent primary care visits (10.9 vs. 6.0 visits), and higher acute care utilization rates (25.8 % vs. 7.7 % for emergency department [ED] visits and 15.0 % vs. 3.9 % for hospitalization). Almost one in five (18 %) patients who were considered high-effort were not deemed complex by the same PCPs.

Conclusions

Patients defined as high-effort by their primary care physicians, not all of whom were medically complex, appear to have a high burden of psychosocial issues that may not be accounted for in current chronic disease-focused risk adjustment approaches.

Nur mit Berechtigung zugänglich

Abrams M, Nuzum R, Mika S, Lawlor G. How the Affordable Care Act will strengthen primary care and benefit patients, providers, and payers. Issue Brief (Commonw Fund). 2011;1:1–28.

Blumenthal D, Abrams M, Nuzum R. The Affordable Care Act at 5 years. N Engl J Med. 2015;372(25):2451–8.CrossRefPubMed

Ash AS, Ellis RP. Risk-adjusted payment and performance assessment for primary care. Med Care. 2012;50(8):643–53.CrossRefPubMedPubMedCentral

Goroll AH, Berenson RA, Schoenbaum SC, et al. Fundamental reform of payment for adult primary care: comprehensive payment for comprehensive care. J Gen Int Med. 2007;22:410–5.CrossRef

Weir S, Aweh G, Clark RE. Case selection for a Medicaid chronic care management program. Health Care Financ Rev. 2008;30(1):61–74.PubMedPubMedCentral

Freund T, Mahler C, Erler A, Gensichen J, Ose D, Szecsenyi J, Peters-Klimm F. Identification of patients likely to benefit from care management programs. Am J Manag Care. 2011;17(5):345–52.PubMed

Ash AS, Zhao Y, Ellis RP, Schlein Kramer M. Finding future high-cost cases: comparing prior cost versus diagnosis-based methods. Health Serv Res. 2001;36(6 Pt 2):194–206.PubMedPubMedCentral

Petersen LA, Pietz K, Woodard LD, Byrne M. Comparison of the predictive validity of diagnosis-based risk adjusters for clinical outcomes. Med Care. 2005;43(1):61–7.PubMed

Ash AS, Ellis RP, Pope GC, et al. Using diagnoses to describe populations and predict costs. Health Care Financ Rev. 2000;21:7–28.PubMedPubMedCentral

10.

Ellis RP, Pope GC, Iezzoni LI, et al. Diagnosis-based risk adjustment for Medicare capitation payments. Health Care Financ Rev. 1996;17:101–28.PubMedPubMedCentral

11.

Kronick R, Gilmer T, Dreyfus T, Lee L. Improving health-based payment for Medicaid beneficiaries: CDPS. Health Care Financ Rev. 2000;21:29–64.PubMedPubMedCentral

12.

Safford MM, Allison JJ, Kiefe CI. Patient complexity: more than comorbidity. The vector model of complexity. J Gen Intern Med. 2007;22(Suppl 3):382–90.CrossRefPubMedPubMedCentral

13.

Grant RW, Ashburner JM, Hong CS, Chang Y, Barry MJ, Atlas SJ. Defining patient complexity from the primary care physician’s perspective: a cohort study. Ann Intern Med. 2011;155(12):797–804.CrossRefPubMed

14.

Hwang AS, Atlas SJ, Cronin P, Ashburner JM, Shah SJ, He W, Hong CS. Appointment “no-shows” are an independent predictor of subsequent quality of care and resource utilization outcomes. J Gen Intern Med. 2015.

15.

Christianson JB, Zismer DK, White KM, Zeglin J. Exploring Alternative Approaches to Valuing Physician Services: A Report by Staff from the University of Minnesota. Washington: Division of Health Policy and Management for Medicare Payment Advisory Commission (Med PAC); 2011.

16.

Bodenheimer T, Berenson RA, Rudolf P. The primary care–specialty income gap: why it matters. Ann Intern Med. 2007;146(4):301–6.CrossRefPubMed

17.

Goodson JD. Unintended consequences of resource-based relative value scale reimbursement. JAMA. 2007;298(19):2308–10.CrossRefPubMed

18.

Jacobson CJ Jr, Bolon S, Elder N, et al. Temporal and subjective work demands in office-based patient care: an exploration of the dimensions of physician work intensity. Med Care. 2011;49(1):52–8.CrossRefPubMed

19.

Dyrbye LN, West CP, Burriss TC, Shanafelt TD. Providing primary care in the United States: the work no one sees. Arch Intern Med. 2012;172(18):1420–1.CrossRefPubMed

20.

Chen MA, Hollenberg JP, Michelen W, Peterson JC, Casalino LP. Patient care outside of office visits: a primary care physician time study. J Gen Intern Med. 2011;26(1):58–63.CrossRefPubMed

21.

Doerr E, Galpin K, Jones-Taylor C, et al. Between-visit workload in primary care. J Gen Intern Med. 2010;25(12):1289–92.CrossRefPubMedPubMedCentral

22.

Arndt B, Tuan WJ, White J, Schumacher J. Panel workload assessment in US primary care: accounting for non-face-to-face panel management activities. J Am Board Fam Med. 2014;27(4):530–7.CrossRefPubMed

23.

Petterson SM, Liaw WR, Tran C, Bazemore AW. Estimating the residency expansion required to avoid projected primary care physician shortages by 2035. Ann Fam Med. 2015;13(2):107–14.CrossRefPubMedPubMedCentral

24.

Mainous AG 3rd, Ramsbottom-Lucier M, Rich EC. The role of clinical workload and satisfaction with workload in rural primary care physician retention. Arch Fam Med. 1994;3(9):787–92.CrossRefPubMed

25.

Wetterneck TB, Linzer M, McMurray JE, et al. Worklife and satisfaction of general internists. Arch Intern Med. 2002;162(6):649–56.CrossRefPubMed

26.

Bodenheimer T. Primary care—will it survive? N Engl J Med. 2006;355(9):861–4.CrossRefPubMed

27.

Schaufeli WB, Maassen GH, Bakker AB, Sixma HJ. Stability and change in burnout: a 10-year follow-up study among primary care physicians. J Occup Organ Psycho. 2011;84(2):248–67.CrossRef

28.

An PG, Rabatin JS, Manwell LB, Linzer M, Brown RL, Schwartz MD, MEMO Investigators. Burden of difficult encounters in primary care: data from the minimizing error, maximizing outcomes study. Arch Intern Med. 2009;169(4):410–4.CrossRefPubMed

29.

Atlas SJ, Chang Y, Lasko TA, Chueh HC, Grant RW, Barry MJ. Is this “my” patient? Development and validation of a predictive model to link patients to primary care providers. J Gen Intern Med. 2006;21:973–8.CrossRefPubMedPubMedCentral

30.

de Jonge P, Huyse FJ, Stiefel FC. Case and care complexity in the medically ill. Med Clin North Am. 2006;90:679–92.CrossRefPubMed

31.

Nalichowski R, Keogh D, Chueh HC, Murphy SN. Calculating the benefits of a Research Patient Data Repository. AMIA Annu Symp Proc. 2006:1044. Ann Fam Med. 2014;12(6):573–6.

32.

Hong CS, Atlas SJ, Ashburner JM, Chang Y, He W, Ferris TG, Grant RW. Evaluating a model to predict primary care physician-defined complexity in a large academic primary care practice-based research network. J Gen Intern Med. 2015;30(12):1741–7.CrossRefPubMedPubMedCentral

33.

Bodenheimer T, Sinsky C. From triple to quadruple aim: care of the patient requires care of the provider. Ann Fam Med. 2014;12(6):573–6.CrossRefPubMedPubMedCentral

34.

Hong CS, Siegel AL, Ferris TG. Caring for high-need, high-cost patients: what makes for a successful care management program? The Commonwealth Fund. 2014.

35.

Garfield SR. The delivery of medical care. Perm J. 2006;10(2):46–56.CrossRefPubMedPubMedCentral

36.

Gupta R, Bodenheimer T. How primary care practices can improve continuity of care. JAMA Intern Med. 2013;173(20):1885–6.CrossRefPubMed

37.

Reid MC, Engles-Horton LL, Weber MB, Kerns RD, Rogers EL, O’Connor PG. Use of opioid medications for chronic noncancer pain syndromes in primary care. J Gen Intern Med. 2002;17(3):173–9.CrossRefPubMedPubMedCentral

38.

Chelminski PR, Ives TJ, Felix KM, et al. A primary care, multi-disciplinary disease management program for opioid-treated patients with chronic non-cancer pain and a high burden of psychiatric comorbidity. BMC Health Serv Res. 2005;5(1):3.CrossRefPubMedPubMedCentral

39.

Archer J, Bower P, Gilbody S, Lovell K, Richards D, Gask L, Dickens C, Coventry P. Collaborative care for depression and anxiety problems. Cochrane Database Syst Rev. 2012;10, CD006525.PubMed

40.

Woltmann E, Grogan-Kaylor A, Perron B, Georges H, Kilbourne AM, Bauer MS. Comparative effectiveness of collaborative chronic care models for mental health conditions across primary, specialty, and behavioral health care settings: systematic review and meta-analysis. Am J Psychiatry. 2012;169(8):790–804.CrossRefPubMed

41.

WinkelmanR, Mehmud S. A Comparative Analysis of Claims-Based Tools for Health Risk Assessment. Society of Actuaries. April 20, 2007. http:// www.soa.org/Files/Research/Projects/risk-assessmentc.pdf. Accessibility verified June 2, 2015.

42.

Rosen AK, Reid R, Broemeling AM, Rakovski CC. Applying a risk-adjustment framework to primary care: can we improve on existing measures? Ann Fam Med. 2003;1(1):44–51.CrossRefPubMedPubMedCentral

43.

Bodenheimer T, Berry-Millet R. Care management of patients with complex health care needs. Princeton: Robert Wood Johnson Foundation; 2009. December 2009. Research synthesis report 19.

44.

Collins C, Hewson DL, Munger R, Wade T. Evolving Models of Behavioral Health Integration in Primary Care. New York, NY: Milbank Memorial Fund; 2010. Available at: www.milbank.org/uploads/documents/10430EvolvingCare/10430EvolvingCare.html. Accessed May 8, 2015.

45.

Ader J, Stille CJ, Keller D, Miller BF, Barr MS, Perrin JM. The medical home and integrated behavioral health: advancing the policy agenda. Pediatrics. 2015;135(5):909–17.CrossRefPubMed

46.

Zulman DM, Grant RW. Transforming care for complex patients: addressing interconnected medical, social, and behavioral challenges. J Gen Intern Med. 2016;31(3):263–4.CrossRefPubMed

47.

Hong CS, Atlas SJ, Chang Y, Subramanian SV, Ashburner JM, Barry MJ, Grant RW. Relationship between patient panel characteristics and primary care physician clinical performance rankings. JAMA. 2010;304(10):1107–13.CrossRefPubMed

Titel: Defining Team Effort Involved in Patient Care from the Primary Care Physician’s Perspective
verfasst von: Andrew S. Hwang, MD MPH
Steven J. Atlas, MD MPH
Johan Hong, AB
Jeffrey M. Ashburner, PhD, MPH
Adrian H. Zai, MD, PhD, MPH
Richard W. Grant, MD, MPH
Clemens S. Hong, MD, MPH
Publikationsdatum: 21.10.2016
Verlag: Springer US
Erschienen in: Journal of General Internal Medicine / Ausgabe 3/2017
Print ISSN: 0884-8734
Elektronische ISSN: 1525-1497
DOI: https://doi.org/10.1007/s11606-016-3897-6

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Defining Team Effort Involved in Patient Care from the Primary Care Physician’s Perspective