Structured yet simple approaches to primary care data quality improvements can indeed strike gold
Abhijeet Ghosh A C , Elizabeth Halcomb B , Sandra McCarthy B and Christine Ashley BA COORDINARE – South Eastern NSW PHN, PO Box 325, Fairy Meadow, NSW 2519, Australia.
B School of Nursing, Faculty of Science, Medicine and Health, Building 41, Northfields Avenue, University of Wollongong, Wollongong, NSW 2522, Australia.
C Corresponding author. Email: aghosh@coordinare.org.au
Australian Journal of Primary Health 27(2) 143-151 https://doi.org/10.1071/PY20247
Submitted: 21 October 2020 Accepted: 26 November 2020 Published: 10 March 2021
Journal Compilation © La Trobe University 2021 Open Access CC BY-NC-ND
Abstract
General practice data provide important opportunities for both population health and within-practice initiatives to improve health. Despite its promise, a lack of accuracy affects the use of such data. The Sentinel Practices Data Sourcing (SPDS) project is a structured chronic disease surveillance and data quality improvement strategy in general practice. A mixed-methods approach was used to evaluate data quality improvement in 99 participating practices over 12 months. Quantitative data were obtained by measuring performance against 10 defined indicators, whereas 48 semi-structured interviews provided qualitative data. Aggregated scores demonstrated improvements in all indicators, ranging from minor to substantially significant improvements. Participants reported positively on levels of support provided, and acquisition of new knowledge and skills relating to data entry and cleansing. This evaluation provides evidence of the effectiveness of a structured approach to improve the quality of primary care data. Investing in this targeted intervention has the potential to create sustained improvements in data quality, which can drive clinical practice improvement.
Keywords: data quality, general practice, surveillance, morbidity, primary care data, clinical information management.
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