Evidence map›Paper›PMID 27578837›Full record

ArticleFamily practice2016

A human factors systems approach to understanding team-based primary care: a qualitative analysis.

Marlon P Mundt, Matthew P Swedlund

Abstract read
In one paragraph

Article in Family practice, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Marlon P MundtDepartment of Family Medicine and Community Health, University of Wisconsin-Madison, Madison, WI, USA and marlon.mundt@fammed.wisc.edu.
Matthew P SwedlundDepartment of Family Medicine and Community Health, University of Wisconsin-Madison, Madison, WI, USA and.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundResearch shows that high-functioning teams improve patient outcomes in primary care. However, there is no consensus on a conceptual model of team-based primary care that can be used to guide measurement and performance evaluation of teams.

objectiveTo qualitatively understand whether the Systems Engineering Initiative for Patient Safety (SEIPS) model could serve as a framework for creating and evaluating team-based primary care.

methodsWe evaluated qualitative interview data from 19 clinicians and staff members from 6 primary care clinics associated with a large Midwestern university. All health care clinicians and staff in the study clinics completed a survey of their communication connections to team members. Social network analysis identified key informants for interviews by selecting the respondents with the highest frequency of communication ties as reported by their teammates. Semi-structured interviews focused on communication patterns, team climate and teamwork.

resultsThemes derived from the interviews lent support to the SEIPS model components, such as the work system (Team, Tools and Technology, Physical Environment, Tasks and Organization), team processes and team outcomes.

conclusionsOur qualitative data support the SEIPS model as a promising conceptual framework for creating and evaluating primary care teams. Future studies of team-based care may benefit from using the SEIPS model to shift clinical practice to high functioning team-based primary care.

Indexed as

CommunicationPatient Care TeamErgonomicsFemaleGroup ProcessesHealth PersonnelHumansInterviews as TopicMaleModels, TheoreticalMoraleOrganizational CulturePrimary Health CareQualitative ResearchSurveys and QuestionnairesSystems TheoryCommunicationelectronic health recordhealth care deliveryprimary carequalitative researchteam.

Identifiers

PMID27578837
PMCPMC5161491

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.