Using Real-world Data for Decision Support: Recommendations from a Primary Care Provider Survey

Abstract

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.

Ähnliche Arbeiten