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Measuring Regional Quality of Health Care Using Unsolicited Online Data: Text Analysis Study
Roy Johannus Petrus Hendrikx1, Hanneke Wil-Trees Drewes2, Marieke Spreeuwenberg3,4
1Tranzo Scientific Center for Care and Welfare, Tilburg University, Tilburg, Netherlands.
JMIR Medical Informatics
|December 17, 2019
Summary
Analyzing online patient reviews reveals key insights into healthcare quality. Text comments offer general feedback for policymakers but limited region-specific data, though outliers provide valuable information.
Area of Science:
- Health Services Research
- Computational Linguistics
- Public Health Policy
Background:
- Regional population management (PM) initiatives need data on experienced quality of care.
- Unsolicited online provider ratings offer potential for regional health analysis.
- This study investigates incorporating qualitative comments from online ratings into regional health evaluations.
Purpose of the Study:
- To gain deeper insights into population management (PM) initiatives through rating rationales.
- To enable comparisons between different PM initiatives by analyzing comment data.
- To explore the value of qualitative text comments alongside quantitative ratings.
Main Methods:
- Utilized 2008-2017 unsolicited ratings and comments from the Dutch Zorgkaart database.
- Performed sentiment analysis (negative, neutral, positive) and explored word frequencies (unigrams, bigrams).
- Applied machine learning (naïve Bayes, random forest) to predict sentiment and identify PM initiatives.
Main Results:
- Analyzed 449,263 ratings: 303,930 positive, 97,739 neutral, 47,592 negative.
- Negative comments frequently mentioned not being "taken seriously"; positive comments focused on listening, explaining, and knowledge.
- Machine learning predicted sentiment but struggled to differentiate specific PM initiatives.
Conclusions:
- Qualitative comments from online ratings provide valuable context for understanding reasons behind healthcare ratings.
- While offering useful overarching insights for policymakers, comments yield limited region-specific data due to overlap.
- Identifying specific outliers within PM initiatives offers unique, actionable information.
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