Clinical decision support software for diabetic foot risk stratification: development and formative evaluation

Journal of Foot and Ankle Research

Sandra C. Thompson¹  David G. Glance²  Deborah E. Schoen³ 

[1] Director Western Australian Centre for Rural Health, Faculty of Medicine, Dentistry & Health Sciences, The University of Western Australia, M702, 35 Stirling Highway, Crawley 6009, WA, Australia;Director Centre for Software Practice, The University of Western Australia, M002, 35 Stirling Highway, Crawley 6009, WA, Australia;Western Australian Centre for Rural Health, Faculty of Medicine, Dentistry & Health Sciences, The University of Western Australia, M706, 35 Stirling Highway, Crawley 6009, WA, Australia

关键词: Clinical;    Decision Support Systems;    Diabetic Angiopathies;    Diabetic Neuropathies;    Foot ulcer;    Diabetes;   

Others  :  1235165
DOI  :  10.1186/s13047-015-0128-z

 received in 2015-05-12, accepted in 2015-11-26,  发布年份 2015

【 摘 要 】

Background

Identifying people at risk of developing diabetic foot complications is a vital step in prevention programs in primary healthcare settings. Diabetic foot risk stratification systems predict foot ulceration. The aim of this study was to explore the views and experiences of potential end users during development and formative evaluations of an electronic diabetic foot risk stratification tool based on evidence-based guidelines and determine the accuracy of the tool.

Methods

Formative evaluation of the risk tool occurred in five stages over an eight-month period and employed a mixed methods research design consisting of semi-structured interviews, focus group and participant observation, online survey, expert review, comparison to the Australian Guidelines and clinical testing.

Results

A total of 43 healthcare practitioners trialled the computerised clinical decision support system during development, with multiple software changes made as a result of feedback. Individual and focus group participants exposed critical design flaws. Live testing revealed risk stratification errors and functional limitations providing the basis for practical improvements. In the final product, all risk calculations and recommendations made by the clinical decision support system reflect current Australian Guidelines.

Conclusions

Development of the computerised clinical decision support system using evidence-based guidelines can be optimised by a multidisciplinary iterative process of feedback, testing and software adaptation by experts in modern development technologies.

【 授权许可】

   
2015 Schoen et al.

【 图 表 】

Fig. 1.

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