Evaluation Domains and Measurement Approaches for Assessing the Performance of China's Family Doctor Contract Services: A Scoping Review Protocol

This scoping review protocol outlines a systematic plan to map and analyze the fragmented evaluation domains and measurement approaches for China's Family Doctor Contract Services, aiming to establish a consensus-based evidence base for future assessments and core outcome set development.

The Gist

Imagine China is building a massive, nationwide "Family Doctor Network." Think of this like a giant neighborhood watch, but instead of watching for burglars, these teams of doctors and nurses are watching over the health of regular people in their communities. The goal is for everyone to have a personal health "buddy" by 2035.

However, there's a problem. The government has said, "Okay, we've signed up enough people; now let's make sure the service is actually good." But nobody agrees on how to measure "good."

Some people measure it by how many people signed up (the "Structure").
Some measure it by how many times people visit the doctor (the "Process").
Others measure it by whether people actually get healthier (the "Outcome").

It's like trying to judge a restaurant, but one critic counts the number of forks on the table, another counts how many times the waiter smiled, and a third only cares if the food tasted good. They are all talking past each other, and there's no single menu of what "good service" actually looks like.

What This Paper Is About

This document is a plan (a protocol) for a big research project. The authors, Yang Wang and her team, want to go on a "treasure hunt" through all the existing reports, government rules, and studies from 2019 to today.

Their mission? To build a master map of how China is currently trying to measure these family doctor services. They want to find out:

1. What are they measuring? (Are they counting visits? Checking blood pressure? Asking about happiness?)
2. How are they measuring it? (Are they using fancy scientific scales, simple checklists, or just guessing?)

The "Three-Legged Stool" Analogy

To make sense of this mess, the researchers are using a famous theory called the Donabedian Model. Imagine a three-legged stool that holds up the quality of healthcare:

1. Structure (The Legs): This is the foundation. Do the doctors have enough chairs? Are there enough medical supplies? Is the team trained?
2. Process (The Seat): This is what happens when you sit down. Did the doctor listen? Did they explain things clearly? Did they follow the rules?
3. Outcome (The Person Sitting): This is the result. Is the patient healthier? Are they happier? Did they save money?

The researchers are going to sort every single piece of data they find into one of these three buckets.

How They Will Do It (The Detective Work)

They aren't just reading one book; they are digging through three different types of evidence:

• The Rulebook: Government documents that say what should be measured.
• The Numbers: Studies that count things (like "500 patients visited").
• The Stories: Interviews with doctors and patients about what they feel is important.

They will use a special visual tool called a Sankey Diagram. Imagine a river with many small streams flowing into a big lake.

• The streams are the different sources (Government, Studies, Interviews).
• The water is the things they are measuring.
• The lake is the final map.

This map will show them where the streams are flowing. Are all the streams flowing into "Patient Satisfaction"? Or is there a huge dry patch where "Chronic Disease Control" should be? This will reveal the gaps.

Why Does This Matter?

Right now, the system is like a jigsaw puzzle where everyone is trying to force pieces into the wrong spots. Some pieces are missing, and some are duplicated.

By creating this "Master Map," the researchers hope to:

1. Stop the confusion: Show everyone exactly what is being measured and what is being ignored.
2. Build a Consensus: Help the government, doctors, and patients agree on a single, standard way to say, "Yes, this family doctor service is working well."
3. Fix the Future: Ensure that by 2035, when they aim for 75% coverage, they aren't just counting heads, but actually improving lives.

In short: This paper is the blueprint for organizing the chaos of "how do we know if family doctors are doing a good job?" so that China can build a better, healthier future for its citizens.

Technical Summary

Based on the provided preprint, here is a detailed technical summary of the scoping review protocol titled "Evaluation Domains and Measurement Approaches for Assessing the Performance of China's Family Doctor Contract Services: A Scoping Review Protocol."

1. Problem Statement

China's Family Doctor Contract Services (FDCS) are transitioning from a phase of expanding coverage to one of improving service quality, guided by national standardized guidelines released in 2018. However, the current landscape for evaluating FDCS performance is characterized by fragmentation and a lack of consensus:

• Policy vs. Practice Misalignment: Government documents and research studies utilize a diverse, ununified mix of indicators spanning structure, process, and outcome domains without a standard framework.
• Measurement Heterogeneity: Different studies assess the same outcome dimensions (e.g., "health" or "satisfaction") using vastly different tools (e.g., Likert scales vs. EQ-5D-5L vs. SF-36), complicating data aggregation and comparison.
• Absence of a Core Outcome Set (COS): There is no established, consensus-based set of core outcomes to guide future evaluations, hindering the ability to identify gaps or standardize quality improvement efforts.

2. Methodology

This study is a scoping review protocol designed to map the existing evaluation ecosystem. It adheres to the JBI (Joanna Briggs Institute) methodology for scoping reviews.

• Research Question: What evaluation domains and measurement approaches have been used to assess FDCS performance in mainland China since the standardized development phase (2019 onwards)?
• Theoretical Framework: All data will be categorized using the Donabedian Model (Structure, Process, Outcome).
• Data Sources & Search Strategy:
  • Timeframe: Literature published from January 1, 2019, onwards.
  • Languages: English and Chinese.
  • Databases: CNKI, Wanfang, PubMed, Web of Science, Embase, and Google Scholar.
  • Source Types: Three distinct tracks:
    1. Policy Documents: Government-issued guidelines from national and provincial health commissions.
    2. Quantitative Studies: Empirical studies measuring FDCS performance indicators.
    3. Qualitative Studies: Research exploring stakeholder perceptions and experiences.
  • Exclusion Criteria: Opinion pieces, studies on intention to contract (rather than actual performance), clinical trials independent of FDCS management, and non-mainland China contexts.
• Study Selection & Data Extraction:
  • Two independent reviewers will screen titles/abstracts and full texts using Rayyan software.
  • Three Custom Extraction Forms will be used:
    1. Policy: Issuing agency, jurisdiction, mandated indicators.
    2. Qualitative: Themes, participant settings, conceptual interpretations.
    3. Quantitative: Study characteristics, specific metrics, tool names (e.g., scales), psychometric properties, and data sources.
• Data Analysis & Synthesis:
  • Step 1 (Sankey Diagram): A visual mapping of the flow from "Evidence Source" $\to$ "Donabedian Category (S-P-O)" $\to$ "Specific Sub-domains" to reveal alignment and gaps.
  • Step 2 (Instrument Inventory Table): A catalog of measurement tools used for "Outcome" domains, detailing constructs, item counts, and psychometric properties.
  • Step 3 (Narrative Synthesis): Qualitative analysis of dominant measurement trajectories and under-represented domains.

3. Key Contributions

• First Comprehensive Map: This review aims to provide the first systematic mapping of the FDCS evaluation ecosystem during China's standardized development phase.
• Triangulation of Perspectives: It uniquely integrates three distinct evidence streams (policy mandates, quantitative research, and qualitative insights) to compare "intended" evaluation domains against "actual" measurement practices.
• Methodological Foundation: Unlike other reviews focusing on clinical effectiveness, this study focuses strictly on evaluation methodology, serving as the necessary groundwork for developing a consensus-based Core Outcome Set (COS) for FDCS.
• Granular Instrument Analysis: By cataloging specific measurement tools and their psychometric properties, the review addresses the issue of non-comparable metrics in current literature.

4. Results

• Status of Results: As this document is a protocol (published March 23, 2026, but describing a study registered in September 2024), no empirical results are yet available.
• Expected Outputs: The protocol outlines that the final study will produce:
  1. A Sankey Diagram visualizing the distribution and alignment of evaluation domains across policy and research.
  2. A comprehensive inventory of measurement instruments used for outcome assessment.
  3. Identification of gaps where policy mandates exist but research measurement is lacking (and vice versa).

5. Significance

• Standardization: The findings will provide the evidence base required to develop a standardized, consensus-based Core Outcome Set (COS) for FDCS, moving the field away from fragmented indicators.
• Policy Guidance: By identifying misalignments between government mandates and research practices, the review will help policymakers refine evaluation standards to better reflect high-quality development goals.
• Quality Improvement: Establishing a clear, unified framework for measurement will enable more accurate monitoring of FDCS performance, facilitating targeted interventions to improve primary care delivery and resident health outcomes in China.
• Global Relevance: As China's FDCS model is a major primary care initiative, the methodological framework developed here could offer insights for other nations implementing similar family doctor systems.