Exploring practical approaches to maximising data quality in electronic healthcare records in the primary care setting and associated benefits

Exploiting the information contained within electronic healthcare records (EHR) data will be key to addressing major challenges to public health both nationally and globally, ultimately offering a means of maximising efficiency and equality in care. There are, however, significant challenges in using EHRs effectively and particularly in ensuring the quality of data recorded. Incorrect or missing data could render records as useless or indeed misleading such that conclusions drawn from the data could have a negative impact. Amongst other difficulties, recording data can be time consuming to the extent of conflicting with the GP’s primary focus of patient consultation in an already time-constrained environment. Understanding the requirements of and the demands upon GPs must be central to addressing the issue of data quality (DQ) within EHRs. As part of on-going work into DQ at the Clinical Practice Research Datalink (CPRD) and in collaboration with the University of Sussex (UoS), a workshop session was held at the SAPC (Society for Academic Primary Care) conference in 2014 with the aim of exploring issues of DQ in primary care EHRs from the perspective of different users of GP data and with particular focus on how and why data is recorded in the first instance. The intended outcome was a furthered understanding of both the challenges and the direct benefits to GPs of ensuring high quality data with a view to establishing a workable approach to recording data and maximising benefits to all users of EHRs

A pragmatic approach for measuring data quality in primary care databases

There is currently no widely recognised methodology for undertaking data quality assessment in electronic health records used for research. In an attempt to address this, we have developed a protocol for measuring and monitoring data quality in primary care research databases, whereby practice-based data quality measures are tailored to the intended use of the data. Our approach was informed by an in-depth investigation of aspects of data quality in the Clinical Practice Research Datalink Gold database and presentations of the results to data users. Although based on a primary care database, much of our proposed approach would be equally applicable to other health care databases

Quality of recording of diabetes in the UK: how does the GP’s method of coding clinical data affect incidence estimates? Cross-sectional study using the CPRD database

Objective: To assess the effect of coding quality on estimates of the incidence of diabetes in the UK between 1995 and 2014. Design: A cross-sectional analysis examining diabetes coding from 1995 to 2014 and how the choice of codes (diagnosis codes vs codes which suggest diagnosis) and quality of coding affect estimated incidence. Setting: Routine primary care data from 684 practices contributing to the UK Clinical Practice Research Datalink (data contributed from Vision (INPS) practices). Main outcome measure: Incidence rates of diabetes and how they are affected by (1) GP coding and (2) excluding ‘poor’ quality practices with at least 10% incident patients inaccurately coded between 2004 and 2014. Results: Incidence rates and accuracy of coding varied widely between practices and the trends differed according to selected category of code. If diagnosis codes were used, the incidence of type 2 increased sharply until 2004 (when the UK Quality Outcomes Framework was introduced), and then flattened off, until 2009, after which they decreased. If non-diagnosis codes were included, the numbers continued to increase until 2012. Although coding quality improved over time, 15% of the 666 practices that contributed data between 2004 and 2014 were labelled ‘poor’ quality. When these practices were dropped from the analyses, the downward trend in the incidence of type 2 after 2009 became less marked and incidence rates were higher. Conclusions: In contrast to some previous reports, diabetes incidence (based on diagnostic codes) appears not to have increased since 2004 in the UK. Choice of codes can make a significant difference to incidence estimates, as can quality of recording. Codes and data quality should be checked when assessing incidence rates using GP data

Exploring practical approaches to maximising data quality in electronic healthcare records in the primary care setting and associated benefits. Report of panel-led discussion held at SAPC in July 2014

BackgroundElectronic healthcare records provide information about patient care over time which not only affords the opportunity to improve patient care directly through effective monitoring and identification of care requirements but also offers a unique platform for both clinical and service-model research essential to the longer-term development of the health service. The quality of the recorded data can, however, be variable and can compromise the validity of data use both for primary and secondary purposes.ObjectivesIn order to explore the challenges and benefits of and approaches to recording high quality primary care electronic records, a Clinical Practice Research Datalink (CPRD) sponsored workshop was held at the Society of Academic Primary Care (SAPC) conference in 2014 with the aim of engaging GPs and other data users.MethodsThe workshop was held as a structured discussion, led by an expert panel and focused around three questions: (1) What are the data quality priorities for clinicians and researchers? How do these priorities differ or overlap? (2) What challenges might GPs face in provision of good data quality both for treating their patients and for research? Do these aims conflict? (3) What tools (such as data metrics and visualisations or software components) could assist the GP in improving data quality and patient management and could this tie in with analytical processes occurring at the research stage?ResultsThe discussion highlighted both overlap and differences in the perceived data quality priorities and challenges for different user groups. Five key areas of focus were agreed upon and recommendations determined for moving forward in improving quality.ConclusionsThe importance of good high quality electronic healthcare records has been set forth along with the need for a practical user-considered and collaborative approach to its improvement.</jats:sec