Evaluating interprofessional primary care teams in high-income countries: A scoping review protocol on the conceptualization and measurement of team functioning, effectiveness, performance and collaboration in primary care
Bibliographic record
Abstract
INTRODUCTION: The delivery of primary care (PC) services by interprofessional teams serves as the cornerstone for building high-performing PC systems. Interprofessional team-based care is a collaborative approach to primary care delivery where healthcare professionals from multiple disciplines work together to provide comprehensive and coordinated care. Despite this recognition, the assessment of the impact of interprofessional PC teams is limited or mixed. There is a lack of clarity on how to define and measure team functioning, collaboration, performance, and effectiveness in PC, posing challenges for the evaluation of interprofessional PC teams. This review aims to dissect and analyze the definitions (conceptualizations and operationalization), measures, and measurement methodologies employed in defining and evaluating team functioning, collaboration, performance, and team effectiveness in PC. In the context of interprofessional PC teams, this review will answer the following questions: 1) How are the terms team functioning, performance, effectiveness, and collaboration conceptualized? 2) What are measures of team functioning, performance, effectiveness, and collaboration? 3) What instruments are used to evaluate team functioning, performance, effectiveness, and collaboration?. METHODS: A systematic approach will be undertaken to conduct this review. A comprehensive search across various academic databases, including PubMed, Medline, CINHAL, Scopus, and Web of Science, will be conducted. Keywords such as "team functioning," "performance measurement," "team effectiveness," "team collaboration," "primary care," and "primary healthcare" will be utilized to ensure the inclusion of relevant studies. Inclusion criteria will be established to filter studies focusing explicitly on interprofessional teams. The review will encompass both qualitative and quantitative studies, ensuring a holistic understanding of the subject matter. By synthesizing this information, the review aims to present an encompassing overview of the conceptualization, measurement and instruments employed to evaluate team functioning, performance, effectiveness, and collaboration within PC settings. DISCUSSION: Globally, governments are investing in the implementation of interprofessional PC teams. The lack of clear definitions and measurement of team outcomes underscores the importance of conducting a comprehensive review. This review will aim to address this gap in knowledge and help inform practice and policy, ultimately contributing to optimizing team functioning, performance, effectiveness, and collaboration within PC settings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.133 | 0.107 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.015 | 0.014 |
| Bibliometrics | 0.024 | 0.024 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".