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SP2.2.12Safety and Quality using GIRFT parameters; the use of hospital coded data as a quality measure
Author(s) -
Helen Fifer,
Muhammad Ibrar Hussain,
Tamsyn Grey,
Arin Saha,
Mark Peter
Publication year - 2021
Publication title -
british journal of surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.202
H-Index - 201
eISSN - 1365-2168
pISSN - 0007-1323
DOI - 10.1093/bjs/znab361.047
Subject(s) - medicine , emergency medicine , clinical governance , quality management , medical emergency , health care , operations management , economics , economic growth , management system
Aim Several indicators measure performance of hospital departments. Despite keeping accurate personal logbooks, surgeons rarely interrogate hospital-level data though these are used nationally (such as on HES databases) to assess performance. This study assessed the accuracy of hospital-level data. Methods Patients who were recorded as having had a length of stay (LoS) of > 7 days, readmissions and patients who had a return to theatre were identified. A weekly ‘Safety and Quality (SnQ)’ governance meeting was established where consultant general surgeons assessed and analysed these data. Differences between hospital level data and outcomes after consultant review were compared. Results Over a six month study period, there were 306 patients (32 elective, 274 acute) who had a LoS of > 7 days. After review, just 33 patients (13%) had a prolonged LoS due to a complication whereas the majority were due to non-surgical reasons. There were 789 coded readmissions. Most coded readmissions were actually planned with 318 patients (43%) having an unplanned readmission. There were 47 recorded cases of a ‘return to theatre’ but after review, one-third (15 cases) were for planned central venous access and 22 cases were planned returns. Conclusions This responsive and accurate clinical governance system can assess performance beyond standard morbidity and mortality review. Hospital-level data often miss nuance; in this study, most coded readmissions were planned rather than unplanned and these discrepancies may reflect poorly on the department if entered onto national databases. Engagement with these data can help units improve outcomes and accuracy of their performance metrics.

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