Deployment of a human-centred clinical decision support system for pulmonary embolism: evaluation of impact on quality of diagnostic decisions.

Pulmonary embolism (PE) is a serious condition that presents a diagnostic challenge for which diagnostic errors often happen. The literature suggests that a gap remains between PE diagnostic guidelines and adherence in healthcare practice. While system-level decision support tools exist, the clinical impact of a human-centred design (HCD) approach of PE diagnostic tool design is unknown. DESIGN: Before-after (with a preintervention period as non-concurrent control) design study. SETTING: Inpatient units at two tertiary care hospitals. PARTICIPANTS: General internal medicine physicians and their patients who underwent PE workups. INTERVENTION: After a 6-month preintervention period, a clinical decision support system (CDSS) for diagnosis of PE was deployed and evaluated over 6 months. A CDSS technical testing phase separated the two time periods. MEASUREMENTS: PE workups were identified in both the preintervention and CDSS intervention phases, and data were collected from medical charts. Physician reviewers assessed workup summaries (blinded to the study period) to determine adherence to evidence-based recommendations. Adherence to recommendations was quantified with a score ranging from 0 to 1.0 (the primary study outcome). Diagnostic tests ordered for PE workups were the secondary outcomes of interest. RESULTS: Overall adherence to diagnostic pathways was 0.63 in the CDSS intervention phase versus 0.60 in the preintervention phase (p=0.18), with fewer workups in the CDSS intervention phase having very low adherence scores. Further, adherence was significantly higher when PE workups included the Wells prediction rule (median adherence score=0.76 vs 0.59, p=0.002). This difference was even more pronounced when the analysis was limited to the CDSS intervention phase only (median adherence score=0.80 when Wells was used vs 0.60 when Wells was not used, p=0.001). For secondary outcomes, using both the D-dimer blood test (42.9% vs 55.7%, p=0.014) and CT pulmonary angiogram imaging (61.9% vs 75.4%, p=0.005) was lower during the CDSS intervention phase. CONCLUSION: A clinical decision support intervention with an HCD improves some aspects of the diagnostic decision, such as the selection of diagnostic tests and the use of the Wells probabilistic prediction rule for PE.

Alignment of patient-centredness definitions with real-life patient and clinician experiences: A qualitative study.

INTRODUCTION: Patient-centred care (PCC) has come to the forefront for many institutions, funding agencies and clinicians, and is integrated into care. Does a disconnect in understanding still exist between patients, healthcare organizations and clinicians in what PCC means and how outstanding issues might be addressed? METHODS: We conducted interviews and focus groups with self-reported chronic care patients and clinicians providing care to these patients exploring PCC experiences, expectations and practices. These data were initially analysed using inductive thematic analysis. This paper reports on the findings of a secondary analysis examining the alignment between patients and clinicians on five key predetermined dimensions of PCC. RESULTS: Eighteen patients participated, representing a range of chronic conditions. Thirty-eight clinicians participated. One thousand and three hundred patient and 1800 clinician codes were identified and grouped into 5 main topics with 140 unique themes (patients) and 9 main topics with 54 unique themes (clinicians). A total of 166 quotes (patient = 93, clinician = 73) were identified for this PCC definition alignment analysis. Partial or complete alignment of patient and clinician perspectives was seen on most dimensions. Key disconnects were observed in patient involvement, patient empowerment and clinician-patient communication. Only 18% of patients reported experiencing patient-centred communication, whereas 57% of clinicians reported using patient-focused communication approaches. CONCLUSION: Overall, study patients and clinicians endorse that many PCC elements occur. This study highlights key differences between patients and clinicians, suggesting persistent challenges. Clinician participants relayed their PCC approaches of informing and educating patients; however, patients often perceive these approaches as didactic, role-diminishing and noncollaborative. Collaborative approaches, such as shared decision-making, hold promise to bridge persistent PCC gaps and should be integrated into medical education programmes. PATIENT OR PUBLIC CONTRIBUTION: This project was conceived and executed with a co-design approach wherein patients with chronic conditions who are trained in research (i.e., see descriptions of Patient and Community Engagement Research in the text) were involved in all stages of the research project alongside other researchers on the project team. Healthcare providers were involved as participants and as principal investigators in the project.

Human-centred design processes for clinical decision support: A pulmonary embolism case study.

BACKGROUND: Clinical Decision Support Systems (CDSS) can make patient care more efficient, cost-effective, and guideline-concordant. Many are created by clinicians who understand the challenges, but may publish concepts before considering subtle but important design details. Human-Centred Design (HCD) approaches provide necessary methods ensuring solid CDSS design. This article highlights HCD approaches in a pulmonary embolism CDSS case study context. METHODS: This pulmonary embolism CDSS results from collaborative work between computer science, psychology, and medicine. HCD methods used include: evaluations of pre-clinical prototype recordings, iterative usability expert reviews with software refinement, formative usability testing, and (separately-published) clinical pilot study. RESULTS: HCD methods were instrumental in iteratively creating an easy to use and functionally-sound CDSS. Retrospective evaluations revealed that participants spent considerable time on items that were out of order from natural cognitive diagnostic workflows. Features missing between original and study version were noted, confusing interface elements reworked, and currently-active decision tree branches were visually emphasized. From iterative usability reviews, positioning of information within the decision tree was radically reworked, information separated into levels of support for different user groups, and supportive versus directive language issues addressed. Formative studies identified issues such as interface adjustments and hospital workflow integration. CONCLUSIONS: Human-centred design approaches provide methods for integrating the skills and knowledge of many disciplines, illustrated by example in this pulmonary embolism CDSS creation. Advantages of leveraging many design guidelines as well as revealing new design considerations that would otherwise have remained hidden are described. The findings reported here support future CDSS design through HCD inclusion.

Translating research into practice through user-centered design: An application for osteoarthritis healthcare planning.

OBJECTIVE: To identify the needs and requirements of the end users, to inform the development of a user-interface to translate an existing evidence-based decision support tool into a practical and usable interface for health service planning for osteoarthritis (OA) care. MATERIALS AND METHODS: We used a user-centered design (UCD) approach that emphasized the role of the end-users and is well-suited to knowledge translation (KT). The first phase used a needs assessment focus group (n=8) and interviews (n=5) with target users (health care planners) within a provincial health care organization. The second phase used a participatory design approach, with two small group sessions (n=6) to explore workflow, thought processes, and needs of intended users. RESULTS: The needs assessment identified five design recommendations: ensuring the user-interface supports the target user group, allowing for user-directed data explorations, input parameter flexibility, clear presentation, and provision of relevant definitions. The second phase identified workflow insights from a proposed scenario. Graphs, the need for a visual overview of the data, and interactivity were key considerations to aid in meaningful use of the model and knowledge translation. CONCLUSION: A UCD approach is well suited to identify health care planners' requirements when using a decision support tool to improve health service planning and management of OA. We believe this is one of the first applications to be used in planning for health service delivery. We identified specific design recommendations that will increase user acceptability and uptake of the user-interface and underlying decision support tool in practice. Our approach demonstrated how UCD can be used to enable knowledge translation.