A computerised decision support system for cardiovascular risk management 'live' in the electronic health record environment: development, validation and implementation-the Utrecht Cardiovascular Cohort Initiative
Members of the UCC-CVRM Study Group
(2019) Netherlands Heart Journal, volume 27, issue 9, pp. 435 - 442
(Article)
Abstract
PURPOSE: We set out to develop a real-time computerised decision support system (CDSS) embedded in the electronic health record (EHR) with information on risk factors, estimated risk, and guideline-based advice on treatment strategy in order to improve adherence to cardiovascular risk management (CVRM) guidelines with the ultimate aim of improving
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patient healthcare. METHODS: We defined a project plan including the scope and requirements, infrastructure and interface, data quality and study population, validation and evaluation of the CDSS. RESULTS: In collaboration with clinicians, data scientists, epidemiologists, ICT architects, and user experience and interface designers we developed a CDSS that provides 'live' information on CVRM within the environment of the EHR. The CDSS provides information on cardiovascular risk factors (age, sex, medical and family history, smoking, blood pressure, lipids, kidney function, and glucose intolerance measurements), estimated 10-year cardiovascular risk, guideline-compliant suggestions for both pharmacological and non-pharmacological treatment to optimise risk factors, and an estimate on the change in 10-year risk of cardiovascular disease if treatment goals are adhered to. Our pilot study identified a number of issues that needed to be addressed, such as missing data, rules and regulations, privacy, and patient participation. CONCLUSION: Development of a CDSS is complex and requires a multidisciplinary approach. We identified opportunities and challenges in our project developing a CDSS aimed at improving adherence to CVRM guidelines. The regulatory environment, including guidance on scientific evaluation, legislation, and privacy issues needs to evolve within this emerging field of eHealth.
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Keywords: Adherence, Big data, Cardiovascular risk management, Computerised decision support system, Health information technology, Real-world data, Cardiology and Cardiovascular Medicine, Journal Article
ISSN: 1568-5888
Publisher: Bohn Stafleu van Loghum
Note: Funding Information: This work is partly funded by PPS allowance from the Dutch Heart Foundation and LSH-TKI (grant number: 2018B006). UCC is partly supported by a grant from ZonMw (grant number: 80-84800-98-34001). F.W. Asselbergs is supported by UCL Hospitals NIHR Biomedical Research Centre. Funding Information: Prof. Pim?A. de Jong, Radiology; Prof. Marianne C.?Verhaar, Nephrology and Hypertension; Prof. Frank L.?J. Visseren, Vascular Medicine; Prof. Folkert W.?Asselbergs, Cardiology; Dr. Niels?P. van der Kaaij, Cardiothoracic Surgery; Dr. Imo?E. H?fer, Experimental Cardiology; Prof. Gert-Jan de Borst, Vascular Surgery; Dr. Ynte M. Ruigrok, Neurology; Dr. Monika Hollander, Julius Centre for Health Sciences and Primary Care, Primary Care; Dr. Stefan M. Dieleman, Intensive Care; Dr. A.?Titia Lely, Woman and Baby; Prof. Mari?lle H.?Emmelot-Vonk, Geriatrics; Prof. Michiel L.?Bots, Julius Centre for Health Sciences and Primary Care This project was made possible by the Applied Data Analytics in Medicine (ADAM) programme of the University Medical Centre Utrecht, Utrecht, The Netherlands. The authors would like to specifically acknowledge Prof. Dr. Wouter W.?van Solinge, PhD, ir. Hyleco H.?Nauta, Harry Pijl, MBA and Dr. S.?Haitjema, PhD, for their organisational support. The contribution of ORTEC within the framework of ADAM is acknowledged. The contribution of the expert user council is greatly appreciated. Cardiology (Kirkels), Vascular medicine (Westerink, Dorresteijn, Visseren), Vascular nurse practitioners (De Haan, Van Tellingen, Lucas), Neurology (Ruigrok), Geriatrics (Emmelot), Nephrology (van Zuilen), Vascular surgery (Van Hattum), Woman and baby (Lely). This work is partly funded by PPS allowance from the Dutch Heart Foundation and LSH-TKI (grant number: 2018B006). UCC is partly supported by a?grant from ZonMw (grant number: 80-84800-98-34001). F.W.?Asselbergs is supported by UCL Hospitals NIHR Biomedical Research Centre. Publisher Copyright: © 2019, The Author(s).
(Peer reviewed)