INTRODUCTION: The use of data from wearable sensors, smartphones, and apps holds promise as a clinical decision-making tool in health and mental health in primary care medicine. The aim of this study was to determine provider perspectives about the utility of these data for building digitally based decision-making tools. METHODS: This mixed quantitative and qualitative cross-sectional survey of a convenience sample of primary-care clinicians at Kaiser Permanente Northwest was conducted between April and July 2019 online via Institute for Translational Health Sciences' Research Electronic Data Capture. Study outcomes were 1) attitudes toward digital data, 2) willingness to use digital data to support clinical decision making, and 3) concerns and recommendations about implementing a digital tool for clinical decision making. RESULTS: This sample of 131 clinicians was largely white (n = 98) female (n = 91) physicians (n = 86). Although respondents (75.7%, n = 87) had a positive attitude toward using digital tools in their practice, 88 respondents (67.3%) voiced concerns about the possible lack of clinical utility, suspected difficulty in integration with clinical workflows, and worried about the potential burden placed on patients. Participants indicated that the accuracy of the data in detecting the need for treatment adjustments would need to be high and the tool should be clinically tested. CONCLUSIONS: Primary care providers find value in collecting real-world patient data to assist in clinical decision making, provided such information does not interfere with provider workflow or impose undue burden on patients. In addition, digital tools will need to demonstrate high accuracy, be able to integrate into current clinical workflows, and maintain the privacy and security of patients' data.
INTRODUCTION: The use of data from wearable sensors, smartphones, and apps holds promise as a clinical decision-making tool in health and mental health in primary care medicine. The aim of this study was to determine provider perspectives about the utility of these data for building digitally based decision-making tools. METHODS: This mixed quantitative and qualitative cross-sectional survey of a convenience sample of primary-care clinicians at Kaiser Permanente Northwest was conducted between April and July 2019 online via Institute for Translational Health Sciences' Research Electronic Data Capture. Study outcomes were 1) attitudes toward digital data, 2) willingness to use digital data to support clinical decision making, and 3) concerns and recommendations about implementing a digital tool for clinical decision making. RESULTS: This sample of 131 clinicians was largely white (n = 98) female (n = 91) physicians (n = 86). Although respondents (75.7%, n = 87) had a positive attitude toward using digital tools in their practice, 88 respondents (67.3%) voiced concerns about the possible lack of clinical utility, suspected difficulty in integration with clinical workflows, and worried about the potential burden placed on patients. Participants indicated that the accuracy of the data in detecting the need for treatment adjustments would need to be high and the tool should be clinically tested. CONCLUSIONS: Primary care providers find value in collecting real-world patient data to assist in clinical decision making, provided such information does not interfere with provider workflow or impose undue burden on patients. In addition, digital tools will need to demonstrate high accuracy, be able to integrate into current clinical workflows, and maintain the privacy and security of patients' data.
Authors: Anthony D Mancini; Lorna L Moser; Rob Whitley; Gregory J McHugo; Gary R Bond; Molly T Finnerty; Barbara J Burns Journal: Psychiatr Serv Date: 2009-02 Impact factor: 3.084
Authors: John Torous; Gerhard Andersson; Andrew Bertagnoli; Helen Christensen; Pim Cuijpers; Joseph Firth; Adam Haim; Honor Hsin; Chris Hollis; Shôn Lewis; David C Mohr; Abhishek Pratap; Spencer Roux; Joel Sherrill; Patricia A Arean Journal: World Psychiatry Date: 2019-02 Impact factor: 49.548
Authors: Ada Ng; Rachel Kornfield; Stephen M Schueller; Alyson K Zalta; Michael Brennan; Madhu Reddy Journal: Proc ACM Hum Comput Interact Date: 2019-11
Authors: Albert L Siu; Kirsten Bibbins-Domingo; David C Grossman; Linda Ciofu Baumann; Karina W Davidson; Mark Ebell; Francisco A R García; Matthew Gillman; Jessica Herzstein; Alex R Kemper; Alex H Krist; Ann E Kurth; Douglas K Owens; William R Phillips; Maureen G Phipps; Michael P Pignone Journal: JAMA Date: 2016-01-26 Impact factor: 56.272
Authors: Hardeep Singh; Christiane Spitzmueller; Nancy J Petersen; Mona K Sawhney; Michael W Smith; Daniel R Murphy; Donna Espadas; Archana Laxmisan; Dean F Sittig Journal: J Am Med Inform Assoc Date: 2012-12-25 Impact factor: 4.497
Authors: Ingrid Konstanse Ledel Solem; Cecilie Varsi; Hilde Eide; Olöf Birna Kristjansdottir; Elin Børøsund; Karlein M G Schreurs; Lori B Waxenberg; Karen E Weiss; Eleshia J Morrison; Mette Haaland-Øverby; Katherine Bevan; Heidi Andersen Zangi; Audun Stubhaug; Lise Solberg Nes Journal: J Med Internet Res Date: 2020-01-21 Impact factor: 5.428