Evidence map›Paper›PMID 27770385›Full record

ArticleJournal of general internal medicine2017

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

Andrew S Hwang, Steven J Atlas, Johan Hong, Jeffrey M Ashburner, Adrian H Zai, Richard W Grant, Clemens S Hong

Open access · bronzeAbstract read
In one paragraph

Article in Journal of general internal medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.8field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Complexity in pediatric primary care.Primary health care research & development · 2018
    Article
  9. Article
  10. Borrowing from Strength.Journal of general internal medicine · 2017
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 1 country.

Andrew S HwangDivision of General Internal Medicine, Department of Medicine, Massachusetts General Hospital, Gray Bigelow 730, 55 Fruit Street, Boston, MA, 02114, USA. ahwang1@partners.org.
Steven J AtlasDivision of General Internal Medicine, Department of Medicine, Massachusetts General Hospital, Gray Bigelow 730, 55 Fruit Street, Boston, MA, 02114, USA.
Johan HongStanford University School of Medicine, Stanford, CA, USA.
Jeffrey M AshburnerDivision of General Internal Medicine, Department of Medicine, Massachusetts General Hospital, Gray Bigelow 730, 55 Fruit Street, Boston, MA, 02114, USA.
Adrian H ZaiLaboratory of Computer Science, Massachusetts General Hospital, Boston, MA, USA.
Richard W GrantDivision of Research, Kaiser Permanente Northern California, Oakland, CA, USA.
Clemens S HongLos Angeles County Department of Health Services, Los Angeles, CA, USA.
Massachusetts General Hospital · USKaiser Permanente · USLos Angeles County Department of Health Services · USStanford University · US

Funding

Harvard Clinical and Translational Science CenterKL2TR001100 · NCATS · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2013 to 2017
$8.5M
Mentored Research to Improve Care for Complex Patients with DiabetesK24DK109114 · NIDDK · KAISER FOUNDATION RESEARCH INSTITUTE · PI GRANT, RICHARD W · 2016 to 2020
$914k
NCATS NIH HHS KL2 TR001100NIDDK NIH HHS K24 DK109114
6 · The paper itself

Abstract

backgroundA 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.

objectiveTo identify and characterize high-effort patients from the physician's perspective.

designCohort study.

participantsNinety-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

resultsAmong 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.

conclusionsPatients 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.

Indexed as

Cooperative BehaviorPhysicians, Primary CareAge FactorsChronic DiseaseCohort StudiesContinuity of Patient CareFemaleHumansMaleMiddle AgedNeeds AssessmentPatient Acceptance of Health CarePatient CarePractice Patterns, Physicians'Primary Health CareRisk Adjustmenthealth services researchprimary care redesignpsychosocialresource allocationrisk adjustment

Identifiers

PMID27770385
PMCPMC5331004
OpenAlexW2534798384

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.