Harnessing the potential of electronic general practice pathology data in Australia: an examination of the quality use of pathology for type 2 diabetes patients

Chisato Imai*, Rae Anne Hardie, Guilherme Saffi Franco, Gorkem Sezgin, Kathy Tepper, Adam McLeod, Christopher Pearce, Johanna Westbrook, Andrew Georgiou

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
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Abstract

Background: Despite the importance of pathology testing in diagnosis and disease monitoring, there is little in-depth research about pathology test ordering in general practice and how it impacts patient outcomes. This is in part due to the limited availability of high-quality data. With the now-widespread use of electronic software in general practice comes the potential for electronic patient data to be used for research leading to better understanding of general practice activities, including pathology testing. Objectives: This study aimed to examine the usefulness of electronic general practice pathology data to: (1) identify patients’ characteristics, (2) monitor quality of care, (3) evaluate intervention effects, (4) identify variations in patient care, and (5) measure patient outcomes. An exemplar study evaluating kidney function testing in type 2 diabetes mellitus (type 2 diabetes) compared to guidelines was used to demonstrate the value of pathology data. Materials and methods: De-identified electronic data from approximately 200 general practices in Victoria were extracted using Outcome Health's Population Level Analysis & Reporting (POLAR) Aurora research platform. Our study population included patients ≥18 diagnosed with type 2 diabetes before July 2016. Data from July 2016 to June 2018 were used to i) determine frequency of kidney function tests (KFT), and ii) identify whether antihypertensive medications were prescribed for abnormal KFT results. Results: There were 20,514 active patients with type 2 diabetes identified from the data. The age and gender standardised estimate of diabetes prevalence was 4.9%, consistent with Australian estimates (5.2%). Sociodemographic features of prevalence, including higher prevalence in older males, were also consistent with previous Australian estimates. Kidney function testing was performed annually, as recommended by guidelines, in 75.7% of patients, with higher annual testing observed in patients managed under general practice incentive programs (80.1%) than those who were not (72.2%). Antihypertensive medications were prescribed as recommended in 77.4% of patients with suspected microalbuminuria or macroalbuminuria based on KFT results. Discussion: Evaluations using data from diabetes patients in this study illustrate the value of electronic data for identifying patients with the condition of interest (e.g. type 2 diabetes) along with sociodemographic characteristics. This allows for the ability to undertake analyses on pathology testing factors and the identification of variation compared to guidelines, which has a potential to ensure quality of care. Its potential to identify associations with incentive programs further demonstrates the advantages of the data's longitudinal nature. These include the ability to assess temporal order and time interval of tests as a marker of quality of monitoring and evaluate intervention effects on a cohort over time. Finally, analyses on antihypertensive medication prescribing in patients with suspected micro/macroalbuminuria exemplified the electronic data's usefulness in monitoring patient outcomes, such as appropriate prescribing based on pathology test results. Conclusions: Electronic general practice data is an important resource which can provide valuable insights about the quality use of pathology. There are clear benefits to patients for better monitoring, and consequent better outcomes, and to inform policymakers about the best ways to channel resources to enhance the quality of care.

Original languageEnglish
Article number104189
Pages (from-to)1-7
Number of pages7
JournalInternational Journal of Medical Informatics
Volume141
Early online date22 May 2020
DOIs
Publication statusPublished - 1 Sep 2020

Bibliographical note

Copyright the Author(s) 2020. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • Diabetes
  • Electronic health record
  • Evaluation
  • General practitioner
  • Pathology
  • Primary health care

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