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DOP81 Quality improvement by semi-automated benchmarking of a core outcome quality indicator set in Inflammatory Bowel Disease: A multicentric feasibility study

Bossuyt, P.(1);Baert, D.(2);Baert, F.(3);Hoefkens, E.(1);Huys, I.(2);Lembrechts, N.(1);De Jonckere, E.(3);Dewint, P.(2);Pouillon, L.(1)

(1)Imelda General Hospital Bonheiden, Department of Gastroenterology, Bonheiden, Belgium;(2)AZ Maria Middelares, Gastroenterology, Gent, Belgium;(3)AZ Delta, Gastroenterology, Rumbeke, Belgium

Background

Quality of care in inflammatory bowel disease (IBD) depends on multiple factors and is assessed through structure, process and outcome indicators. Structure and process indicators are more static and can easily be measured by an audit. Patient-oriented outcome indicators that impact on the quality of life are more difficult to assess. 

The aim of the project was to build a platform that automatically captures key outcome quality indicators and provide benchmarking output to improve quality of care in IBD centres.

Methods

Literature was reviewed for relevant quality indicators in IBD. After two non-anonymized Delphi like review and consensus meetings, twelve quality indicators were selected for implementation. The definitions of the outcomes were aligned in consensus with the available International Consortium for Health Outcomes Measurement (ICHOM). A web-based interface was built in three large volume IBD centres in Belgium to collect data on multiple ways:  (i) Patients complete patient-reported outcome questionnaires and disease specific questions when attending the outpatient clinic and/or day clinic; (ii) The software automatically extracts data from the electronic medical files including biochemical and endoscopic reports; (iii) The medical baseline characteristics and outcome indicators for each patient are completed by the healthcare professional at inclusion and after this on a yearly basis.

Results

In total 265 patients were included in the participating IBD centres. Three indicators could be directly extracted from the patient-reported outcome questionnaires (clinical remission, fatigue, work productivity). Two items could be retrieved by use of the bot that automatically extracts biochemical and endoscopic reports from the medical files (anaemia, deep remission). The other items were collected throughout yearly confirmation by a health care professional (colorectal cancer, steroid use [systemic/topical], severe infections, hospital admission, IBD surgery [perianal/abdominal]). All items are benchmarked in an anonymous way on a benchmarking dashboard. Each centre can only see his own position in the benchmarking diagram. Additionally, the case mix per centre (type IBD, severity, demographic data) was added to the benchmarking output to provide a balanced evaluation of the outcome indicators.

Conclusion

This is the first partially automated benchmarking initiative for quality of care in IBD. The data collection is feasible and provides an objective assessment and comparison of the IBD related quality of care in different centres. Further prospective evaluation needs to confirm that implementation of benchmarking improves the performance and quality of IBD management.

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