Quality indicators for the detection and management of chronic kidney disease in primary care: An exploratory study using electronic medical record data in Australia.
Project Details
The aim of this project was to explore and compare CKD detection and management in four large general practice repositories from Australia (Patron), Singapore (NUHS Datahub), Sweden (NVH Region Uppsala) and Canada (UTOPIAN).
Patron ID: PAT091
Project Lead:
Chronic kidney disease (CKD) is a common but under-recognised condition globally and is associated with diabetes and an increased risk of cardiovascular disease (CVD) and mortality across Australian and international contexts (1-6). The evidence around CKD and its associated burden provides an impetus to prioritise strategies which focus on CKD detection and management.
On average, 85% of Australians visit their GP at least once every year (4), and two million visit a GP each week (7). GPs are therefore well positioned to identify patients with CKD and implement early intervention efforts to reduce disease progression and prevent the development of CVD. (8-10). Given that GPs are integral to the care provided to patients with diagnosed and undiagnosed CKD, this project used de-identified data embedded in general practice electronic medical records (EMRS) to evaluate processes of care against a set of indicators for CKD. This use of EMR data provided an opportunity to examine the practice of using EMR data as a source for research (as EMRs are increasing being seen as a valid and feasible way to evaluate health care), assist in early detection of disease, assess clinical outcomes and highlight inequities.(10)
In 2017, Tu and colleagues developed a set of primary care quality indicators for CKD in the Canadian setting, to be used to assess the current state of detection and management of CKD using data extracted from general practice EMR (11). The aim of this project was to use Tu's CKD indicators to explore and compare CKD detection and management in four large general practice repositories from Australia (Patron), Singapore (NUHS Datahub), Sweden (NVH Region Uppsala) and Canada (UTOPIAN). Through this process, we explored differences in general practices datasets, barriers to international comparative studies and methods to overcome these barriers.
Investigators from each country sought funding for their own component of the study. Each country analysed their respective dataset, generated a summary of patient demographics to describe the participant cohort and assessed the EMR data against 17 quality indicators for CKD. These indicators related to the prevalence and the incidence of CKD in each country’s repository, the proportion of patients who have been referred to a kidney specialist, and the proportion of patients with CKD who died between 30 June 2017 to 30 June 2019. Number, percentage and 95% confidence intervals are reported on for each indicator. CKD indicator measurements included those around pathology testing to detect CKD progression in patients with renal impairment; pathology testing to detect CKD in patients with diabetes and hypertension; the prescribing of anti-hypertensives and statin medications for patients with CKD, diabetes and/or albuminuria.
References:
1. Mills KT, Xu Y, Zhang W, Bundy JD, Chen C-S, Kelly TN, et al. A systematic analysis of worldwide population-based data on the global burden of chronic kidney disease in 2010. Kidney International. 2015;88(5):950-7.
2.Chadban SJ, Briganti EM, Kerr PG, Dunstan DW, Welborn TA, Zimmet PZ, et al. Prevalence of Kidney Damage in Australian Adults: The AusDiab Kidney Study. Journal of the American Society of Nephrology. 2003;14(suppl 2):S131.
3.Brück K, Stel VS, Gambaro G, Hallan S, Völzke H, Ärnlöv J, et al. CKD Prevalence Varies across the European General Population. Journal of the American Society of Nephrology. 2016;27(7):2135-47.
4.Wen CP, Cheng TYD, Tsai MK, Chang YC, Chan HT, Tsai SP, et al. All-cause mortality attributable to chronic kidney disease: a prospective cohort study based on 462 293 adults in Taiwan. The Lancet. 2008;371(9631):2173-82.
5.Orlandi PF, Huang J, Fukagawa M, Hoy W, Jha V, Oh K-H, et al. A collaborative, individual-level analysis compared longitudinal outcomes across the International Network of Chronic Kidney Disease (iNETCKD) cohorts. Kidney International. 2019;96(5):1217-33.
6.Australian Institute of Health and Welfare AIHW. Chronic kidney disease Canberra ACT: Australian Goverment 2019 [Available from:
https://www.aihw.gov.au/reports-data/health-conditions-disability-deaths/chronic-kidney-disease/overview.
7.Hayes P. No one knows you like your GP. newsGP [Internet]. 2018 24/3/20]; (14/5/2018). Available from:
https://www1.racgp.org.au/newsgp/racgp/no-one-knows-you-like-your-gp.
8.Khanam M, Kitsos A, Stankovich J, Castelino R, Jose M, Kinsman L, et al. Chronic kidney disease monitoring in Australian general practice. Australian Journal for General Practitioners. 2019;48:132-7.
9.Rushforth B, Stokes T, Andrews E, Willis TA, McEachan R, Faulkner S, et al. Developing 'high impact' guideline-based quality indicators for UK primary care: a multi-stage consensus process. BMC family practice. 2015;16:156-.
10.Canaway R, Boyle DIR, Manski-Nankervis J-AE, Bell J, Hocking JS, Clarke K, et al. Gathering data for decisions: best practice use of primary care electronic records for research. Medical Journal of Australia. 2019;210(S6):S12-S6.
11.Tu K, Bevan L, Hunter K, Rogers J, Young J, Nesrallah G. Quality indicators for the detection and management of chronic kidney disease in primary care in Canada derived from a modified Delphi panel approach
Research Outcomes
Final Report
This study evaluated chronic kidney disease (CKD) detection and management in Australian primary care using 16 quality indicators applied to a large dataset of over 360,000 patients.
Among 24,348 patients with evidence of CKD, only 28% had a diagnosis formally recorded. For undiagnosed patients with impaired kidney function, follow-up testing was inconsistent, just over half received a repeat eGFR and fewer than one-third had an albumin creatinine ratio test within six months. Monitoring among those with a CKD diagnosis was somewhat stronger, with blood pressure recorded for 71% of patients, although fewer than half achieved target levels.
These findings highlight gaps in CKD diagnosis and follow-up but also demonstrate that primary care data can be used to generate meaningful quality indicators for improving detection and management.
Research Publications
- Peer reviewed publication - Petzke, D., Hallinan, C.M., Trevena, J. et al. Exploration of chronic kidney disease screening, diagnosis and management in Australian general practice using electronic medical record data. BMC Nephrol 26, 405 (2025). https://doi.org/10.1186/s12882-025-04345-3
- Conference poster - Petzke D, Hallinan C, Trevena J, Manski Nankervis J A. Exploration of chronic kidney disease screening, diagnosis and management in Australian general practice using electronic medical record data. Australian Journal of General Practice (AJGP). Academic Post registrar abstract supplement 2024 https://www1.racgp.org.au/getattachment/32e8fa75-0650-4a6b-a919-5781c1cc5246/Supplements.aspx