Improved patient satisfaction and diagnostic accuracy in skin diseases with a Visual Clinical Decision Support System—A feasibility study with general practitioners

Abstract

Patient satisfaction is an important indicator of health care quality, and it remains an important goal for optimal treatment outcomes to reduce the level of misdiagnoses and inappropriate or absent therapeutic actions. Digital support tools for differential diagnosis to assist clinicians in reaching the correct diagnosis may be helpful, but how the use of these affect patients is not clear. The primary objective of this feasibility study was to investigate patient experience and satisfaction in a primary care setting where general practitioners (GPs) used a visual clinical decision support system (CDSS) compared with standard consultations. Secondary objectives were diagnostic accuracy and length of consultation. Thirty-one patients with a dermatologist-confirmed skin diagnosis were allocated to consult GPs that had been randomized to conduct either standard consultations (SDR, n = 21) or CDSS (n = 16) on two separate study days one week apart. All patients were diagnosed independently by multiple GPs (n = 3–8) in both the SDR and CDSS study arms. Using the CDSS, more patients felt involved in the decision making (P = 0.05). In addition, more patients were exposed to images during the consultations (P = 6.8e-27), and 83% of those that were shown images replied they felt better supported in the consultation. The use of CDSS significantly improved the diagnostic accuracy (34%, P = 0.007), and did not increase the duration of the consultation (median 10 minutes in both arms). This study shows for the first time that compared with standard GP consultations, CDSS assist the GP on skin related diagnoses and improve patient satisfaction and diagnostic accuracy without impacting the duration of the consultations. This is likely to increase correct treatment choices, patient adherence, and overall result in better healthcare outcomes.

Evaluation of medical decision support systems (DDX generators) using real medical cases of varying complexity and origin

“…Isabel Health [ 21 ]: IsabelHealth is a commercial DDX generator built using machine learning technology [ 4 ]. It is a "black box" system for the user, where the thesauri used cannot be reviewed or improved by the tester.…”

“…Clinical decision systems (CDSS) are increasingly used in practice [ 1 – 4 ]. However, all new methods in medicine, whether diagnostic or therapeutic, must be tested to demonstrate feasibility of use and benefit to patients.…”

Workload And Workflow Implications Associated With The Use Of Electronic Clinical Decision Support Tools Used By Health Professionals In General Practice: A Scoping Review

“…In ve studies, clinicians provided a selfreport of time spent, using either a paper or electronic case report form. 87,93,94,101,106 A member of the research team manually timed the duration of study consultations or scenarios in four studies. 83,91,97,99 Five studies captured time data electronically from log les within the eCDS tool itself, including clinician time spent using particular elements of the tool or completing certain activities.…”

“…Twenty-four studies reported an objective of time. included: (i) time spent using or interacting with an eCDS tool (ranging from three seconds 83 to between 0.5-13 minutes [84][85][86][87][88][89][90][91] ) and/or (ii) consultation duration 83,[92][93][94][95][96][97][98][99][100][101][102][103][104][105][106] .…”

Evaluating Feasibility and Acceptance of a Mobile Clinical Decision Support System in Botswana

“…This suggests a critical need for a CDSS to ameliorate current challenges within dermatology and other subspecialties in Botswana. Previous studies have demonstrated the promise of VisualDx CDSS as a platform which could contribute to increased provider con dence and a reduction in diagnostic errors in primary care settings [12,13].…”