2022
Artificial Intelligence (AI) to improve chronic pain care: Evidence of AI learning
Piette J, Newman S, Krein S, Marinec N, Chen J, Williams D, Edmond S, Driscoll M, LaChappelle K, Maly M, Kim H, Farris K, Higgins D, Kerns R, Heapy A. Artificial Intelligence (AI) to improve chronic pain care: Evidence of AI learning. Intelligence-Based Medicine 2022, 6: 100064. DOI: 10.1016/j.ibmed.2022.100064.Peer-Reviewed Original ResearchPatient interactionsPatient subgroupsInteractive voice response callsPain-related interferenceComparative effectiveness trialChronic pain careCourse of therapyPedometer step countsDisease management programsCognitive behavioral therapyCBT-CPChronic painMore patientsPain careTreatment modalitiesTreatment recommendationsEffectiveness trialPatientsStep countBehavioral therapyClinician timeWeeksTherapy sessionsMethods DataTherapist feedback
2016
Patient-Centered Pain Care Using Artificial Intelligence and Mobile Health Tools: Protocol for a Randomized Study Funded by the US Department of Veterans Affairs Health Services Research and Development Program
Piette JD, Krein SL, Striplin D, Marinec N, Kerns RD, Farris KB, Singh S, An L, Heapy AA. Patient-Centered Pain Care Using Artificial Intelligence and Mobile Health Tools: Protocol for a Randomized Study Funded by the US Department of Veterans Affairs Health Services Research and Development Program. JMIR Research Protocols 2016, 5: e53. PMID: 27056770, PMCID: PMC4856067, DOI: 10.2196/resprot.4995.Peer-Reviewed Original ResearchInteractive voice response callsTelephone Cognitive Behavioral TherapyChronic low back painCognitive behavioral therapyPain management servicesLow back painBack painTreatment responsePatient-centered pain carePedometer-measured step countsStep countVeterans Affairs Health Services ResearchVeterans Affairs patientsPain-related interferencePain-related outcomesPain-related functioningVA healthcare systemMobile health toolsWeekly hour-long sessionsPedometer step countsSignificant treatment responseHealth services researchPain controlTreatment satisfactionPain care
2015
Mobile Health Devices as Tools for Worldwide Cardiovascular Risk Reduction and Disease Management
Piette J, List J, Rana G, Townsend W, Striplin D, Heisler M. Mobile Health Devices as Tools for Worldwide Cardiovascular Risk Reduction and Disease Management. Circulation 2015, 132: 2012-2027. PMID: 26596977, PMCID: PMC5234768, DOI: 10.1161/circulationaha.114.008723.Peer-Reviewed Original ResearchMeSH KeywordsAdultBiomedical TechnologyCardiovascular DiseasesCell PhoneDeveloping CountriesDiabetes ComplicationsDisease ManagementHealth BehaviorHealth ExpendituresHealth PromotionHealth WorkforceHumansInternetPovertyRisk Reduction BehaviorSelf CareTechnology TransferTechnology, High-CostTelemedicineConceptsMHealth interventionsMiddle-income countriesLifestyle behaviorsRisk factorsCardiovascular diseaseDisease managementShort message service interventionInteractive voice response callsDiabetic glycemic controlCardiovascular risk reductionInteractive voice responseCardiovascular preventive careCardiovascular disease managementMobile health toolsService-based interventionsGlycemic controlHospital readmissionHypertension managementRandomized trialsMedication adherencePreventive careDisease outcomePhysical activityMHealth programsMultimodal intervention
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