Continuity of care after hospital discharge is a common issue for patients who underwent major surgery. Computerized clinical Decision Support Systems (CDSSs) can help physicians stratify patients based on clinical and social characteristics, make predictions about relevant care milestones and outcomes, and make personalized decisions as early as possible, including safe discharge planning, based on timely activation of the relevant services. To enhance the clinical uptake and effectiveness of these technologies, it is crucial to determine whether patients feel that their personal priorities for their health, recovery and discharge are taken into account. However, there is a significant gap in empirical research regarding patient perspectives on CDSS utilization. As a part of the PREPARE Rehab Project, a) a CDSS to support continuity of care after hospital discharge, and b) two questionnaires investigating physicians’ and patients’ expectations towards its use, are being developed by a group of researchers, clinicians, computer scientists and technicians. This brief report describes how a pilot questionnaire on patient expectations of AI-based CDSS was developed, administered and analyzed in a musculoskeletal research hospital, based on a pilot population of twenty patients, as a part of the nine clinical partners involved in whole project. These preliminary results show a degree of consistency between answers, confirming some hypotheses from the few literature available. The results are discussed in light of expert clinician insight and limitations to overcome. These results provide empirical background to fine-tune a final version of a patient questionnaire, and address CDSS improvements before introduction into routine clinical use.
La frammentazione delle cure post-dimissione è un problema frequente per i pazienti sottoposti a interventi di chirurgia maggiore. I sistemi elettronici di supporto alle decisioni cliniche (CDSS) possono contribuire a stratificare i pazienti con artroplastica di anca e ginocchio in base a fattori clinici e sociali rilevanti, aiutando i medici a prevedere gli esiti riabilitativi, stimare i tempi di recupero e pianificare dimissioni sicure e tempestive. Per migliorare tali tecnologie, occorre verificare se rispondano alle reali priorità dei pazienti, tema oggi poco studiato. Nell’ambito del progetto di ricerca Europeo PREPARE Rehab, un team multidisciplinare sta sviluppando a) un dispositivo CDSS e b) due questionari per rilevare le aspettative di medici e pazienti. Lo scopo di questo articolo è descrivere i risultati preliminari di una sperimentazione pilota condotta su venti pazienti in riabilitazione post-artroplastica presso un ospedale ortopedico di ricerca (uno dei nove casi clinici del progetto). I risultati mostrano un certo grado di coerenza fra le risposte ottenute, confermando alcune ipotesi avanzate dalla scarsa letteratura sul tema. I risultati sono discussi alla luce dell’esperienza clinica e di ricerca, compresi i limiti di cui tenere conto nell’avanzamento dello studio. Tali risultati forniscono una base empirica per perfezionare la versione finale del questionario, e indirizzare miglioramenti ai sistemi di supporto alle decisioni cliniche prima della loro introduzione nella pratica di routine.
Patient expectations of AI-based computerized clinical decision support system for improving continuity of care after hospitalization: a cross-sectional study on rehabilitation after total hip or knee replacement for osteoarthritis, with pilot questionnaire = Aspettative dei pazienti nei confronti di un sistema informatizzato di supporto decisionale clinico basato sull’intelligenza artificiale per migliorare la continuità delle cure dopo il ricovero ospedaliero: uno studio trasversale sulla riabilitazione dopo la protesi totale dell’anca o del ginocchio per l’osteoartrite, con questionario pilota / F. Pennestrì, C.P.. - In: RECENTI PROGRESSI IN MEDICINA. - ISSN 0034-1193. - 117:9(2026 Sep 01), pp. 402-409. [10.1701/4764.47841]
Patient expectations of AI-based computerized clinical decision support system for improving continuity of care after hospitalization: a cross-sectional study on rehabilitation after total hip or knee replacement for osteoarthritis, with pilot questionnaire = Aspettative dei pazienti nei confronti di un sistema informatizzato di supporto decisionale clinico basato sull’intelligenza artificiale per migliorare la continuità delle cure dopo il ricovero ospedaliero: uno studio trasversale sulla riabilitazione dopo la protesi totale dell’anca o del ginocchio per l’osteoartrite, con questionario pilota
A. Orenti;G. BanfiUltimo
2026
Abstract
Continuity of care after hospital discharge is a common issue for patients who underwent major surgery. Computerized clinical Decision Support Systems (CDSSs) can help physicians stratify patients based on clinical and social characteristics, make predictions about relevant care milestones and outcomes, and make personalized decisions as early as possible, including safe discharge planning, based on timely activation of the relevant services. To enhance the clinical uptake and effectiveness of these technologies, it is crucial to determine whether patients feel that their personal priorities for their health, recovery and discharge are taken into account. However, there is a significant gap in empirical research regarding patient perspectives on CDSS utilization. As a part of the PREPARE Rehab Project, a) a CDSS to support continuity of care after hospital discharge, and b) two questionnaires investigating physicians’ and patients’ expectations towards its use, are being developed by a group of researchers, clinicians, computer scientists and technicians. This brief report describes how a pilot questionnaire on patient expectations of AI-based CDSS was developed, administered and analyzed in a musculoskeletal research hospital, based on a pilot population of twenty patients, as a part of the nine clinical partners involved in whole project. These preliminary results show a degree of consistency between answers, confirming some hypotheses from the few literature available. The results are discussed in light of expert clinician insight and limitations to overcome. These results provide empirical background to fine-tune a final version of a patient questionnaire, and address CDSS improvements before introduction into routine clinical use.| File | Dimensione | Formato | |
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