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Original Investigation
January 2019

Association of Team-Based Primary Care With Health Care Utilization and Costs Among Chronically Ill Patients

Author Affiliations
  • 1Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
  • 2Department of Pediatrics, Harvard Medical School, Division of General Pediatrics, Department of Medicine, Boston Children’s Hospital, Boston, Massachusetts
  • 3Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
  • 4Department of Medicine, Stanford University School of Medicine, Stanford, California
JAMA Intern Med. 2019;179(1):54-61. doi:10.1001/jamainternmed.2018.5118
Key Points

Question  What is the association of a team-based primary care transformation collaborative initiative with patient health care utilization and costs?

Findings  In this study, among chronically ill patients in 18 practices who were exposed to team-based care, there was an 18% reduction in hospitalizations, a 25% reduction in emergency department visits, and a 36% reduction in ambulatory care–sensitive emergency department visits relative to 76 comparison practices. Among healthier patients, there was an increase in outpatient visits and hospitalizations.

Meaning  Team-based approaches to primary care transformation may benefit patients with chronic illness by reducing the use of acute care; however, it may lead to higher use among healthier patients.


Importance  Empirical study findings to date are mixed on the association between team-based primary care initiatives and health care use and costs for Medicaid and commercially insured patients, especially those with multiple chronic conditions.

Objective  To evaluate the association of establishing team-based primary care with patient health care use and costs.

Design, Setting, and Participants  We used difference-in-differences to compare preutilization and postutilization rates between intervention and comparison practices with inverse probability weighting to balance observable differences. We fit a linear model using generalized estimating equations to adjust for clustering at 18 academically affiliated primary care practices in the Boston, Massachusetts, area between 2011 and 2015. The study included 83 953 patients accounting for 138 113 patient-years across 18 intervention practices and 238 455 patients accounting for 401 573 patient-years across 76 comparison practices. Data were analyzed between April and August 2018.

Exposures  Practices participated in a 4-year learning collaborative that created and supported team-based primary care.

Main Outcomes and Measures  Outpatient visits, hospitalizations, emergency department visits, ambulatory care–sensitive hospitalizations, ambulatory care–sensitive emergency department visits, and total costs of care.

Results  Of 322 408 participants, 176 259 (54.7%) were female; 64 030 (19.9%) were younger than 18 years and 258 378 (80.1%) were age 19 to 64 years. Intervention practices had fewer participants, with 2 or more chronic conditions (n = 51 155 [37.0%] vs n = 186 954 [46.6%]), more participants younger than 18 years (n = 337 931 [27.5%] vs n = 74 691 [18.6%]), higher Medicaid enrollment (n = 39 541 [28.6%] vs n = 81 417 [20.3%]), and similar sex distributions (75 023 women [54.4%] vs 220 097 women [54.8%]); however, after inverse probability weighting, observable patient characteristics were well balanced. Intervention practices had higher utilization in the preperiod. Patients in intervention practices experienced a 7.4% increase in annual outpatient visits relative to baseline (95% CI, 3.5%-11.3%; P < .001) after adjusting for patient age, sex, comorbidity, zip code level sociodemographic characteristics, clinician characteristics, and plan fixed effects. In a subsample of patients with 2 or more chronic conditions, there was a statistically significant 18.6% reduction in hospitalizations (95% CI, 1.5%-33.0%; P = .03), 25.2% reduction in emergency department visits (95% CI, 6.6%-44.0%; P = .007), and a 36.7% reduction in ambulatory care–sensitive emergency department visits (95% CI, 9.2%-64.0%; P = .009). Among patients with less than 2 comorbidities, there was an increase in outpatient visits (9.2%; 95% CI, 5.10%-13.10%; P < .001), hospitalizations (36.2%; 95% CI, 12.2-566.6; P = .003), and ambulatory care–sensitive hospitalizations (50.6%; 95% CI, 7.1%-329.2%; P = .02).

Conclusions and Relevance  While establishing team-based care was not associated with differences in the full patient sample, there were substantial reductions in utilization among a subset of chronically ill patients. Team-based care practice transformation in primary care settings may be a valuable tool in improving the care of sicker patients, thereby reducing avoidable use; however, it may lead to greater use among healthier patients.

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    2 Comments for this article
    Favorable subgroup
    Benjamin Andrews, MD | Christ Community Health Services
    The authors seem to focus their discussion on the favorable subgroup results--in the chronically ill subset--rather than the disappointing primary results that showed no difference in overall utilization across the entire clinic populations, except increase in outpatient visits. This continues a trend of mixed evidence for PCMH-type interventions.

    Without concomitant outcomes data, this study seems to show that team-based care might be too much for some and just right for others. But how do we titrate the intervention to reach only those who will benefit?
    Enhanced Primary Healthcare
    Paul Nelson, MD, MS | Family Health Care, P.C.; retired
    For 1991 through 1997, my small group practice of three physicians participated in a primary care capitated HMO with a referral pool and hospital pool for which we were at 50% full risk. There was an employer panel and a Medicare panel. We never had a negative risk sharing year.

    Normally, it would take about 1 year for an employer group member/family to "buy in" to an engaged primary healthcare relationship. The Medicare members usually took 1 1/2 - 2 years. During these intervals, there was an increased, but small, turnover by members based
    on all sorts of issues.

    A statistical attribution for assigning a PCP seems fool-hardy to me. No future engaged group would ever accept this as a basis for risk management. Our hospital utilization control was length of stay related rather than admission related. There was an increased utilization during the initial engagement period for both panels.