Evaluation of a staff training programme to reimplement a comprehensive health assessment. Issue 4 (20th November 2018)

• Record Type: Journal Article
• Authors: Turcotte, Luke A; Tran, Jake; Moralejo, Joshua; Curtin-Telegdi, Nancy; Eckel, Leslie; Hirdes, John P
• Is Part Of: BMJ open quality. Volume 7:Issue 4(2018)
• Publication Date: 2018-11-20
• Subjects: decision support, clinical -- health professions education -- continuous quality improvement -- implementation science -- information technology; Medical care -- Quality control -- Periodicals; 362.106805
• DOI: 10.1136/bmjoq-2018-000353
• Languages: English
• ISSNs: 2399-6641

Abstract

Abstract : Background: Health information systems with applications in patient care planning and decision support depend on high-quality data. A postacute care hospital in Ontario, Canada, conducted data quality assessment and focus group interviews to guide the development of a cross-disciplinary training programme to reimplement the Resident Assessment Instrument–Minimum Data Set (RAI-MDS) 2.0 comprehensive health assessment into the hospital's clinical workflows. Methods: A hospital-level data quality assessment framework based on time series comparisons against an aggregate of Ontario postacute care hospitals was used to identify areas of concern. Focus groups were used to evaluate assessment practices and the use of health information in care planning and clinical decision support. The data quality assessment and focus groups were repeated to evaluate the effectiveness of the training programme. Results: Initial data quality assessment and focus group indicated that knowledge, practice and cultural barriers prevented both the collection and use of high-quality clinical data. Following the implementation of the training, there was an improvement in both data quality and the culture surrounding the RAI-MDS 2.0 assessment. Conclusions: It is important for facilities to evaluate the quality of their health information to ensure that it is suitable for decision-making purposes. This study demonstrates the use of a data quality assessment framework that can be applied for quality improvement planning.