Skip to main content
Top
Published in: Journal of General Internal Medicine 3/2017

01-03-2017 | Original Research

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

Authors: 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

Published in: Journal of General Internal Medicine | Issue 3/2017

Login to get access

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.
Appendix
Available only for authorised users
Literature
1.
go back to reference 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. 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.
2.
go back to reference Blumenthal D, Abrams M, Nuzum R. The Affordable Care Act at 5 years. N Engl J Med. 2015;372(25):2451–8.CrossRefPubMed Blumenthal D, Abrams M, Nuzum R. The Affordable Care Act at 5 years. N Engl J Med. 2015;372(25):2451–8.CrossRefPubMed
4.
go back to reference 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 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
5.
go back to reference 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 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
6.
go back to reference 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 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
7.
go back to reference 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 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
8.
go back to reference 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 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
9.
go back to reference 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 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.
go back to reference 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 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.
go back to reference 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 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.
go back to reference 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 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.
go back to reference 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 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.
go back to reference 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. 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.
go back to reference 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. 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.
go back to reference Bodenheimer T, Berenson RA, Rudolf P. The primary care–specialty income gap: why it matters. Ann Intern Med. 2007;146(4):301–6.CrossRefPubMed 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.
go back to reference Goodson JD. Unintended consequences of resource-based relative value scale reimbursement. JAMA. 2007;298(19):2308–10.CrossRefPubMed Goodson JD. Unintended consequences of resource-based relative value scale reimbursement. JAMA. 2007;298(19):2308–10.CrossRefPubMed
18.
go back to reference 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 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.
go back to reference 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 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.
go back to reference 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 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
22.
go back to reference 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 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.
go back to reference 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 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.
go back to reference 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 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.
go back to reference Wetterneck TB, Linzer M, McMurray JE, et al. Worklife and satisfaction of general internists. Arch Intern Med. 2002;162(6):649–56.CrossRefPubMed Wetterneck TB, Linzer M, McMurray JE, et al. Worklife and satisfaction of general internists. Arch Intern Med. 2002;162(6):649–56.CrossRefPubMed
27.
go back to reference 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 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.
go back to reference 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 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.
go back to reference 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 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.
go back to reference de Jonge P, Huyse FJ, Stiefel FC. Case and care complexity in the medically ill. Med Clin North Am. 2006;90:679–92.CrossRefPubMed 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.
go back to reference 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. 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.
go back to reference 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 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
34.
go back to reference 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. 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.
36.
go back to reference Gupta R, Bodenheimer T. How primary care practices can improve continuity of care. JAMA Intern Med. 2013;173(20):1885–6.CrossRefPubMed Gupta R, Bodenheimer T. How primary care practices can improve continuity of care. JAMA Intern Med. 2013;173(20):1885–6.CrossRefPubMed
37.
go back to reference 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 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.
go back to reference 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 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.
go back to reference 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 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.
go back to reference 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 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
42.
go back to reference 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 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.
go back to reference 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. 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.
go back to reference 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. 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.
go back to reference 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 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.
go back to reference 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 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.
go back to reference 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 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
Metadata
Title
Defining Team Effort Involved in Patient Care from the Primary Care Physician’s Perspective
Authors
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
Publication date
01-03-2017
Publisher
Springer US
Published in
Journal of General Internal Medicine / Issue 3/2017
Print ISSN: 0884-8734
Electronic ISSN: 1525-1497
DOI
https://doi.org/10.1007/s11606-016-3897-6

Other articles of this Issue 3/2017

Journal of General Internal Medicine 3/2017 Go to the issue
Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin
Prof. Florian Limbourg
Prof. Anoop Chauhan
Developed by: Springer Medicine
Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine

Highlights from the ACC 2024 Congress

Year in Review: Pediatric cardiology

Watch Dr. Anne Marie Valente present the last year's highlights in pediatric and congenital heart disease in the official ACC.24 Year in Review session.

Year in Review: Pulmonary vascular disease

The last year's highlights in pulmonary vascular disease are presented by Dr. Jane Leopold in this official video from ACC.24.

Year in Review: Valvular heart disease

Watch Prof. William Zoghbi present the last year's highlights in valvular heart disease from the official ACC.24 Year in Review session.

Year in Review: Heart failure and cardiomyopathies

Watch this official video from ACC.24. Dr. Biykem Bozkurt discusses last year's major advances in heart failure and cardiomyopathies.