A clinical decision support system (CDSS) is a health information technology system designed to directly assist healthcare professionals with clinical decisions, in which the characteristics of an individual patient are matched to a clinical knowledge base, and patient-specific assessments and recommendations are then presented to the healthcare professional or patient for a decision.1,2 In the field of transplantation, they have been shown to improve physician performance around medication management and laboratory practices among transplant recipients3 but less clearly, patient outcomes. A CDSS has recently been shown to improve timely organ procurement organization notification and organ donation.4
In this issue of Transplantation, Knight and colleagues5 describe the first CDSS designed to aid donor multidisciplinary teams with the workup of potential living kidney donors. A home-grown CDSS was adapted and coded to incorporate a patient-completed questionnaire and to allow a nurse to review and confirm patient-entered information and add the results of laboratory and radiological investigations. Raw data can also be used to derive values for parameters, such as body mass index. Their CDSS used adapted British Transplantation Society Guidelines for Living Donor Kidney Transplantation to recommend clinical decisions for potential donors in 4 distinct categories: major and minor contraindications to kidney donation; additional investigations required; special considerations unique to the potential donor such as kidney biopsy; and safest choice of right or left kidney for donation using anatomical and functional data. A retrospective ‘clinical audit’ was performed by testing the CDSS against the multidisciplinary team (real) decisions by retrospectively entering data for 45 consecutive donors over a 3-month period. The CDSS identified that 7 patients with major contraindications proceeded to donation and only 43% of additional investigations suggested by the CDSS, according to British Transplantation Society guidelines, were completed. The exact significance of these findings is unclear since documentation around patient-centered decisions and investigations, as well as explicit discussion and consent was lacking with some donors. Adherence to guidelines may vary by center of donor assessment, and these findings require external validation.
This novel application of a CDSS to support living kidney donor assessment has the potential to improve the safety and efficiency of donor assessment and merits a larger, prospective study. The streamlining of donor assessment will hopefully reduce time from first contact by a potential donor to an acceptance decision and their time to donation. The CDSS can also be expanded to serve as a decision aid for potential kidney donors, can be modified to allow prospective donors the convenience of completing the online questions at different times (ie, save and continue later) and reduce hospital visits, all of which may improve patient experience. Patient feedback will be vital for further development of the CDSS.
Although the use of CDSS have generally been shown to be modestly beneficial with respect to patient outcomes across a variety of healthcare settings,6,7 the use of CDSS can have unintended consequences which can lead to patient harm.8 For example, automation biases can result in errors of omission in which healthcare providers fail to adequately consider relevant information beyond that which is used by the CDSS.8 They also have the potential to produce errors of commission if healthcare providers blindly follow the recommendations of the CDSS even when it contradicts their training and other available sources of information.8 As such, a guideline-based CDSS supports guideline-based practice but does not replace decision making by the multidisciplinary team. This is particularly the case for the evaluation of potential kidney donors as the “evidence for most guideline recommendations is sparse and [includes] many “ungraded” expert consensus recommendations.”9 As such, any CDSS for the evaluation of potential kidney donors will require ongoing redesign and modification as the evidence around donor assessment evolves. The additional work of verifying data entered into a CDSS and the cost of such a tool may be a barrier for many transplant programs that may question what this adds above and beyond an electronic health record. In addition, the effectiveness (and safety) of any CDSS depends on multiple factors beyond the performance and usability of the software. A checklist to improve the likelihood of successful development and implementation of guideline-based CDSS has recently been developed and provides relevant guidance for any transplant program considering such an initiative.10
Despite potential barriers to implementing a CDSS for evaluation of potential kidney donors, the study by Knight et al holds great promise for improving the process. Their study demonstrated that a CDSS can highlight potential contraindications that warrant further evaluation and/or formal discussion with potential donors about their specific risks as part of the consent process, thereby improving compliance with local kidney donor transplantation guidelines. This study serves as an important “proof-of-concept” in which the acceptance and adoption of CDSS for living kidney donor evaluations will be enhanced if future studies demonstrate improvements in the safety and timeliness of living kidney donation.
1. Neapolitan R, Jiang X, Ladner DP, et al. A primer on Bayesian decision analysis with an application to a personalized kidney transplant decision. Transplantation
2. Sim I, Gorman P, Greenes RA, et al. Clinical decision support systems for the practice of evidence-based medicine. J Am Med Inform Assoc
3. Niazkhani Z, Pirnejad H, Rashidi Khazaee P. The impact of health information technology on organ transplant care: a systematic review. Int J Med Inform
4. Zier JL, Spaulding AB, Finch M, et al. Improved time to notification of impending brain death and increased organ donation using an electronic clinical decision support system. Am J Transplant
5. Knight SR, Cao KN, South M, et al. Development of a clinical decision support system for living kidney donor assessment based on national guidelines. Transplantation
6. Roshanov PS, Fernandes N, Wilczynski JM, et al. Features of effective computerised clinical decision support systems: meta-regression of 162 randomised trials. BMJ
7. Moja L, Kwag KH, Lytras T, et al. Effectiveness of computerized decision support systems linked to electronic health records: a systematic review and meta-analysis. Am J Public Health
8. Coiera E, Westbrook J, Wyatt J. The safety and quality of decision support systems. Yearb Med Inform
9. Lentine KL, Kasiske BL, Levey AS, et al. KDIGO clinical practice guideline on the evaluation and care of living kidney donors. Transplantation
. 2017;101(8S Suppl 1):S1–S109.
10. Van de Velde S, Kunnamo I, Roshanov P, et al. The GUIDES checklist: development of a tool to improve the successful use of guideline-based computerised clinical decision support. Implement Sci