Measuring the impact of a health information exchange intervention on provider-based notifiable disease reporting using mixed methods: a study protocol
1 Indiana University, School of Informatics and Computing, Indianapolis, IN, USA
2 Regenstrief Institute, Center for Biomedical Informatics, Indianapolis, IN, USA
3 Department of Veterans Affairs, Health Services Research & Development Service, Center for Implementing Evidence-Based Practice, Indianapolis, IN, USA
4 Indiana University, School of Medicine, Indianapolis, IN, USA
5 University of Washington, School of Public Health, Seattle, WA, USA
BMC Medical Informatics and Decision Making 2013, 13:121 doi:10.1186/1472-6947-13-121Published: 30 October 2013
Health information exchange (HIE) is the electronic sharing of data and information between clinical care and public health entities. Previous research has shown that using HIE to electronically report laboratory results to public health can improve surveillance practice, yet there has been little utilization of HIE for improving provider-based disease reporting. This article describes a study protocol that uses mixed methods to evaluate an intervention to electronically pre-populate provider-based notifiable disease case reporting forms with clinical, laboratory and patient data available through an operational HIE. The evaluation seeks to: (1) identify barriers and facilitators to implementation, adoption and utilization of the intervention; (2) measure impacts on workflow, provider awareness, and end-user satisfaction; and (3) describe the contextual factors that impact the effectiveness of the intervention within heterogeneous clinical settings and the HIE.
The intervention will be implemented over a staggered schedule in one of the largest and oldest HIE infrastructures in the U.S., the Indiana Network for Patient Care. Evaluation will be conducted utilizing a concurrent design mixed methods framework in which qualitative methods are embedded within the quantitative methods. Quantitative data will include reporting rates, timeliness and burden and report completeness and accuracy, analyzed using interrupted time-series and other pre-post comparisons. Qualitative data regarding pre-post provider perceptions of report completeness, accuracy, and timeliness, reporting burden, data quality, benefits, utility, adoption, utilization and impact on reporting workflow will be collected using semi-structured interviews and open-ended survey items. Data will be triangulated to find convergence or agreement by cross-validating results to produce a contextualized portrayal of the facilitators and barriers to implementation and use of the intervention.
By applying mixed research methods and measuring context, facilitators and barriers, and individual, organizational and data quality factors that may impact adoption and utilization of the intervention, we will document whether and how the intervention streamlines provider-based manual reporting workflows, lowers barriers to reporting, increases data completeness, improves reporting timeliness and captures a greater portion of communicable disease burden in the community.