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A comparison of hospital episode statistics and traditional methods to identify outcomes in a randomized trial; a sub-study of HEAT-PPCI
Abstract Background This study aims to compare information from hospital episode statistics (HES) and traditional direct patient contact to identify readmission and clinical events in the follow-up of a randomized controlled trial (RCT). Methods The study followed 1812 patients for 28 days using dir...
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Published in: | Journal of public health (Oxford, England) England), 2020-02, Vol.42 (1), p.175-182 |
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Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Get full text |
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Summary: | Abstract
Background
This study aims to compare information from hospital episode statistics (HES) and traditional direct patient contact to identify readmission and clinical events in the follow-up of a randomized controlled trial (RCT).
Methods
The study followed 1812 patients for 28 days using direct contact (DC). In addition, we obtained HES for this period. We examined medical records for all suspected readmissions and determined confirmed events by adjudication. We compared the ability of the individual DC and HES methods to determine readmission and the occurrence of trial-specific events, confirmed at adjudication.
Results
In the ascertainment of readmission, compared to DC, HES demonstrated a trend towards better sensitivity (identifying 153/166 = 92.2% versus 144/166 = 86.7%; difference = 5.4%, 95% CI: 0.1–11.5%) and better specificity (1492/1492 = 100% versus 1426/1492 = 95.5%; difference = 4.4%, 95% CI: 4.2–5.6%).
An examination of HES coding does not identify rates for specific events that match those from adjudication, with limitations in both sensitivity and specificity.
Conclusion
HES is effective in the ascertainment of readmission and is a useful tool in follow-up. Information from HES provides a reflection of a patient’s course and associated cost, as perceived by the healthcare system. Future studies could modify outcome definitions to reflect episode coding. |
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ISSN: | 1741-3842 1741-3850 |
DOI: | 10.1093/pubmed/fdy225 |