TY - JOUR
AU - S. Aquino
A1 - 
AB - Parkinson's Disease (PD) is a progressive neurodegenerative condition that requires timely intervention to manage symptoms and prevent deterioration. This study investigates the essential requirements for a speech-based decision support tool to monitor PD progression in a community-integrated care setting. While still at an early design stage, the envisioned tool may take the form of mobile or desktop software accessible to patients, carers, and professionals in home and clinical settings. A mixed-methods approach, including surveys (n=31), focus groups (n=12), interviews (n=11), and policy document analysis, was used to gather insights from health and social care staff in Wales. Four major themes emerged: essential technical requirements (reliability, ease of use), workforce needs (training, analytic transparency), patient considerations (preferences, privacy), and systemic integration (interoperability, funding). Findings highlight the potential of speech-based AI systems for early, objective detection of PD deterioration. However, clinician trust, digital literacy, and user-centered design remain critical for adoption. Co-design with people with PD (PwPD), carers, and staff is strongly recommended for future development and evaluation. This study contributes to the growing field of intelligent systems in digital health and decision support.
AD - Imperial College London, Cwm Taf Morgannwg University Health Board.
AN - 40588907
BT - Stud Health Technol Inform
C5 - Healthcare Disparities; HIT & Telehealth
DA - Jun 26
DO - 10.3233/shti250699
DP - NLM
JF - Stud Health Technol Inform
LA - eng
N2 - Parkinson's Disease (PD) is a progressive neurodegenerative condition that requires timely intervention to manage symptoms and prevent deterioration. This study investigates the essential requirements for a speech-based decision support tool to monitor PD progression in a community-integrated care setting. While still at an early design stage, the envisioned tool may take the form of mobile or desktop software accessible to patients, carers, and professionals in home and clinical settings. A mixed-methods approach, including surveys (n=31), focus groups (n=12), interviews (n=11), and policy document analysis, was used to gather insights from health and social care staff in Wales. Four major themes emerged: essential technical requirements (reliability, ease of use), workforce needs (training, analytic transparency), patient considerations (preferences, privacy), and systemic integration (interoperability, funding). Findings highlight the potential of speech-based AI systems for early, objective detection of PD deterioration. However, clinician trust, digital literacy, and user-centered design remain critical for adoption. Co-design with people with PD (PwPD), carers, and staff is strongly recommended for future development and evaluation. This study contributes to the growing field of intelligent systems in digital health and decision support.
PY - 2025
SN - 0926-9630
SP - 188
EP - 192+
ST - Designing a Speech-Based Decision Support Tool for Parkinson's Disease in Integrated Care
T1 - Designing a Speech-Based Decision Support Tool for Parkinson's Disease in Integrated Care
T2 - Stud Health Technol Inform
TI - Designing a Speech-Based Decision Support Tool for Parkinson's Disease in Integrated Care
U1 - Healthcare Disparities; HIT & Telehealth
U3 - 10.3233/shti250699
VL - 328
VO - 0926-9630
Y1 - 2025
ER -