Frimpong JA, Liu X, Liu L, Zhang R. Adoption of Electronic Health Record Among Substance Use Disorder Treatment Programs: Nationwide Cross-Sectional Survey Study.
J Med Internet Res 2023;
25:e45238. [PMID:
38096006 PMCID:
PMC10755658 DOI:
10.2196/45238]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 10/20/2023] [Accepted: 11/22/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND
Electronic health record (EHR) systems have been shown to be associated with improvements in care processes, quality of care, and patient outcomes. EHR also has a crucial role in the delivery of substance use disorder (SUD) treatment and is considered important for addressing SUD crises, including the opioid epidemic. However, little is known about the adoption of EHR in SUD treatment programs or the organizational-level factors associated with the adoption of EHR in SUD treatment.
OBJECTIVE
We examined the adoption of EHR in SUD programs, with a focus on changes in adoption from 2014 to 2017, and identified organizational-level factors associated with EHR adoption.
METHODS
We used data from the 2014 and 2017 National Drug Abuse Treatment System Surveys. Our analysis included 1027 SUD programs (531 in 2014 and 496 in 2017). We used chi-square and Mann-Whitney U tests for categorical and continuous variables, respectively, to assess changes in EHR adoption, technology use, program, and client characteristics. We also investigated differences in characteristics and barriers to adoption by EHR adoption status (adopted EHR vs had not adopted or were planning to adopt EHR). We then conducted multivariate logistic regressions to examine internal and external factors associated with EHR adoption.
RESULTS
The adoption of EHR increased significantly from 57.6% (306/531) in 2014 to 69.2% (343/496) in 2017 (P<.001), showing that nearly one-third (153/496, 30.8%) of SUD programs had not yet adopted an EHR system by 2017. We identified a significant increase in technology use and ownership by a parent company (P=.01 and P<.001) and a decrease in the percentage of uninsured patients in 2017 (P<.001), compared to 2014. Our analysis further showed significant differences by adoption status for three major barriers to adoption: (1) start-up costs, (2) ongoing financial costs, and (3) privacy or security concerns (P<.001). Programs that used computerized scheduling (adjusted odds ratio [AOR] 3.02, 95% CI 2.23-4.09) and billing systems (AOR 2.29, 95% CI 1.62-3.25) were more likely to adopt EHR. Similarly, ownership type, such as private nonprofit (AOR 1.86, 95% CI 1.31-2.65) and public (AOR 2.14, 95% CI 1.27-3.67), or interest in participating in a patient-centered medical home (AOR 1.93, 95% CI 1.29-2.92), were associated with an increased likelihood to adopt EHR. Overall, SUD programs were more likely to adopt an EHR system in 2017 compared to 2014 (AOR 1.44, 95% CI 1.07-1.94).
CONCLUSIONS
Our findings highlighted that SUD programs may be on track to achieve widespread EHR adoption. However, there is a need for focused strategies, resources, and policies explicitly designed to systematically address barriers and tackle obstacles to expanding the adoption of EHR systems. These efforts must be holistic and address factors at multiple organizational levels.
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