Patient-Centered Pain Care Using Artificial Intelligence and Mobile Health Tools: A Randomized Comparative Effectiveness Trial.
Journal
JAMA internal medicine
ISSN: 2168-6114
Titre abrégé: JAMA Intern Med
Pays: United States
ID NLM: 101589534
Informations de publication
Date de publication:
01 09 2022
01 09 2022
Historique:
pubmed:
9
8
2022
medline:
9
9
2022
entrez:
8
8
2022
Statut:
ppublish
Résumé
Cognitive behavioral therapy for chronic pain (CBT-CP) is a safe and effective alternative to opioid analgesics. Because CBT-CP requires multiple sessions and therapists are scarce, many patients have limited access or fail to complete treatment. To determine if a CBT-CP program that personalizes patient treatment using reinforcement learning, a field of artificial intelligence (AI), and interactive voice response (IVR) calls is noninferior to standard telephone CBT-CP and saves therapist time. This was a randomized noninferiority, comparative effectiveness trial including 278 patients with chronic back pain from the Department of Veterans Affairs health system (recruitment and data collection from July 11, 2017-April 9, 2020). More patients were randomized to the AI-CBT-CP group than to the control (1.4:1) to maximize the system's ability to learn from patient interactions. All patients received 10 weeks of CBT-CP. For the AI-CBT-CP group, patient feedback via daily IVR calls was used by the AI engine to make weekly recommendations for either a 45-minute or 15-minute therapist-delivered telephone session or an individualized IVR-delivered therapist message. Patients in the comparison group were offered 10 therapist-delivered telephone CBT-CP sessions (45 minutes/session). The primary outcome was the Roland Morris Disability Questionnaire (RMDQ; range 0-24), measured at 3 months (primary end point) and 6 months. Secondary outcomes included pain intensity and pain interference. Consensus guidelines were used to identify clinically meaningful improvements for responder analyses (eg, a 30% improvement in RMDQ scores and pain intensity). Data analyses were performed from April 2021 to May 2022. The study population included 278 patients (mean [SD] age, 63.9 [12.2] years; 248 [89.2%] men; 225 [81.8%] White individuals). The 3-month mean RMDQ score difference between AI-CBT-CP and standard CBT-CP was -0.72 points (95% CI, -2.06 to 0.62) and the 6-month difference was -1.24 (95% CI, -2.48 to 0); noninferiority criterion were met at both the 3- and 6-month end points (P < .001 for both). A greater proportion of patients receiving AI-CBT-CP had clinically meaningful improvements at 6 months as indicated by RMDQ (37% vs 19%; P = .01) and pain intensity scores (29% vs 17%; P = .03). There were no significant differences in secondary outcomes. Pain therapy using AI-CBT-CP required less than half of the therapist time as standard CBT-CP. The findings of this randomized comparative effectiveness trial indicated that AI-CBT-CP was noninferior to therapist-delivered telephone CBT-CP and required substantially less therapist time. Interventions like AI-CBT-CP could allow many more patients to be served effectively by CBT-CP programs using the same number of therapists. ClinicalTrials.gov Identifier: NCT02464449.
Identifiants
pubmed: 35939288
pii: 2794818
doi: 10.1001/jamainternmed.2022.3178
pmc: PMC9361183
doi:
Banques de données
ClinicalTrials.gov
['NCT02464449']
Types de publication
Journal Article
Randomized Controlled Trial
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
975-983Subventions
Organisme : HSRD VA
ID : IK6 HX003399
Pays : United States
Organisme : NIDDK NIH HHS
ID : P30 DK092926
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001863
Pays : United States