Etiometry’s T3 Heuristic Evaluation

Five students and a Human Factors Psychology professor participated in a heuristic evaluation of clinical decision support software, called T3, to help improve usability. T3 gathers physiological monitoring data from a variety of sources, e.g. pulse oximeters, electrocardiographs, and ventilators, and uses the data to compute two novel risk indexes. To effectively support clinical decision-making, T3 should present the patient data it collects, as well as the risk indexes that it computes, in an easy to understand interactive display. The evaluation identified 38 potential usability issues, about half of which were deemed ‘not an issue’ or rated as minor. The team developed 11 recommendations for changes to help improve usability of T3. Given the volume and complexity of the information that T3 displays, this is a short list, suggesting relatively good usability. However, none of the evaluators has the clinical training or experience of typical users; it is possible that clinical users would identify additional usability issues.

Risikoidentifikation bei Polypharmazie in einer Pflegeheimpopulation

Zusammenfassung Einleitung Multimorbidität im Alter ist u. a. ein Grund für intensivierte Pharmakotherapie. Gleichzeitig kann es mit steigender Medikamentenzahl zu einer Zunahme der Multimorbidität kommen, insbesondere wenn Interaktionen zwischen den Wirkstoffen zu unerwünschten Arzneiwirkungen (UAW) führen. Ziel dieser Untersuchung war es, in einer Pilotstudie Patienten zu identifizieren, die einem erhöhten Risiko für UAW unterliegen. Methoden In einer Querschnittserhebung wurden 918 in Heimen lebende psychiatrisch behandelte Alterspatienten untersucht (Altersmittel: 79,3 (±11,6) Jahre; 31,8 % Männer). Es kamen exemplarisch verschiedene Methoden zur Identifikation von möglichen Risikopatienten zur Anwendung: eine die Interaktionen der Gesamtmedikation erfassende „Clinical-Decision-Support-Software“(CDSS)-Onlinedatenbank, mediQ, und eine Negativliste, die pauschal zu vermeidende Präparate indiziert, die PRISCUS-Liste. Ergebnis Es hatten 76,3 % aller Studienpatienten bei Betrachtung der Gesamtmedikation ein klinisch relevantes Interaktionsrisiko (IR), 2,2 % standen unter einem darüber hinausgehenden potenziell starken UAW-Risiko durch Interaktionen. Ungefähr ein Viertel der untersuchten Studienpopulation erhielt potenziell inadäquate Medikamente gemäß PRISCUS. Schlussfolgerung Diese unterschiedlichen Zahlen zeigen die Komplexität der eindeutigen Identifikation von Risikopatienten am Beispiel dieser beiden, auf unterschiedlicher Grundlage basierenden Instrumente. Trotz des technischen Fortschritts sollte der Schwerpunkt der UAW-Vermeidung unverändert darauf liegen, Medikamente erst nach besonders gründlicher Prüfung der klinischen Indikation zu verordnen und eine adäquate Verlaufskontrolle zu gewährleisten. Die neuen CDSS oder Negativlisten bieten hierbei Unterstützung.

Impact of Emergency Medicine Consultants and Clinical Advisors on a NHS 111 Clinical Assessment Service

ObjectiveTo compare outcome of clinical advice given by emergency physicians (EPs) versus non-physician clinical advisors (NPCAs) on a UK National Health Service 111 centre.MethodThis was a prospective study conducted between July 2016 and February 2017. We targeted calls in which call handlers using standard NHS 111 clinical decision support software would have advised the caller to attend a hospital ED. These calls were passed to a clinical assessment service (CAS) and reviewed by either an EP (July to November 2016) or an NPCA (December 2016 to February 2017).ResultsDuring the preintervention year, 80.2% of callers were advised to attend the ED within 1 or 4 hours, 1.2% were referred to out of hours (OOH) primary care and 0.3% to self-care. During the study, call handlers designated 2606 calls as needing to attend the ED in 1 or 4 hours and passed these on to the clinical advisors. There was a reduction of 75%–81% in cases advised to attend the ED in both intervention groups; EPs advised 396 of 1558 callers (25.4%) to attend ED; NPCAs advised 194 of 1048 callers (18.5%) to attend ED. For calls not requiring the ED, EPs recommended self/home care management in 38.1% of these calls, NPCAs recommended self-care for 15.7% (difference=22.4%; 95% CI 19.0% to 25.7%). EPs recommended 4.5% to attend OOH primary care, while NPCAs recommended OOH primary care for 42.1% (difference=37.6%, 95% CI 34.3% to 40.8%).ConclusionsA CAS within NHS 111 using clinicians decreases referrals to the ED. EPs use fewer services and resources. Further work needs to be undertaken to determine the workforce skill mix for an NHS 111 CAS.