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Patients' experience and satisfaction in primary care: secondary analysis using multilevel modelling
Chris Salisbury1, Marc Wallace, Alan A Montgomery
1University of Bristol, Bristol BS8 2AA, UK. c.salisbury@bristol.ac.uk
BMJ (Clinical Research Ed.)
|October 14, 2010
Summary
Patient survey responses often reflect patient differences, not just practice or doctor performance. Experience-based measures better distinguish practices than general satisfaction, but most variation is patient-related.
Area of Science:
- Health services research
- General practice
- Patient experience
Background:
- Patient surveys are widely used to assess general practice and doctor performance.
- Understanding the sources of variation in patient responses is crucial for accurate performance evaluation.
Purpose of the Study:
- To determine if patient survey responses reflect differences between general practices, doctors, or patients themselves.
- To investigate the hierarchical nature of patient data in surveys.
Main Methods:
- Secondary analysis of a general practice access study.
- Utilized multilevel modeling at practice, doctor, and patient levels.
- Included data from 4573 patients, 150 doctors, and 27 practices across nine primary care trusts in England.
Main Results:
- Experience-based measures (e.g., appointment wait times) discriminated better between practices than overall satisfaction.
- Most variance in reported performance (over 79%) was at the patient level, including patient characteristics.
- Differences between doctors accounted for minimal variance in communication skills (6.3%).
Conclusions:
- Multilevel modeling is essential for analyzing patient survey data.
- Patient experience measures are more effective than general satisfaction for practice-level assessment.
- Patient satisfaction surveys are limited in distinguishing individual doctor performance due to high patient-level variance.
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