Measuring the impact of a health information exchange intervention on provider-based notifiable disease reporting using mixed methods: a study protocol

BackgroundHealth 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.Methods/DesignThe 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.DiscussionBy 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.

[1]  Jason S. Shapiro,et al.  Evaluating public health uses of health information exchange , 2007, J. Biomed. Informatics.

[2]  W Katherine Yih,et al.  Integrating clinical practice and public health surveillance using electronic medical record systems. , 2012, American journal of public health.

[3]  Samuel L Groseclose,et al.  Evaluation of reporting timeliness of public health surveillance systems for infectious diseases , 2004, BMC public health.

[4]  Rebecca A. Hills,et al.  Public Health Practice within a Health Information Exchange: Information Needs and Barriers to Disease Surveillance , 2012, Online journal of public health informatics.

[5]  A. Davidson,et al.  Assessing the relationship between health information exchanges and public health agencies. , 2009, Journal of public health management and practice : JPHMP.

[6]  J. Marc Overhage,et al.  A comparison of the completeness and timeliness of automated electronic laboratory reporting and spontaneous reporting of notifiable conditions. , 2008, American journal of public health.

[7]  Mustafa Fidahussein,et al.  Practical challenges in the secondary use of real-world data: the notifiable condition detector. , 2011, AMIA ... Annual Symposium proceedings. AMIA Symposium.

[8]  Lonnie Blevins,et al.  The Indiana network for patient care: a working local health information infrastructure. An example of a working infrastructure collaboration that links data from five health systems and hundreds of millions of entries. , 2005, Health affairs.

[9]  Julie J McGowan,et al.  Electronic laboratory data quality and the value of a health information exchange to support public health reporting processes. , 2011, AMIA ... Annual Symposium proceedings. AMIA Symposium.

[10]  J. Ovretveit The contribution of new social science research to patient safety. , 2009, Social science & medicine.

[11]  Joan S. Ash,et al.  Qualitative evaluation of health information exchange efforts , 2007, J. Biomed. Informatics.

[12]  A. Strauss,et al.  Basics of Qualitative Research , 1992 .

[13]  S. Ramsey,et al.  A controlled time-series trial of clinical reminders: using computerized firm systems to make quality improvement research a routine part of mainstream practice. , 2000, Health services research.

[14]  R. Lazarus,et al.  Viewpoint Paper: Electronic Support for Public Health: Validated Case Finding and Reporting for Notifiable Diseases Using Electronic Medical Data , 2009, J. Am. Medical Informatics Assoc..

[15]  David W. Bates,et al.  Health information exchange and patient safety , 2007, J. Biomed. Informatics.

[16]  Eric C. Pan,et al.  The value of health care information exchange and interoperability. , 2005, Health affairs.

[17]  Adam Fletcher,et al.  Realist randomised controlled trials: a new approach to evaluating complex public health interventions. , 2012, Social science & medicine.

[18]  Shaun J. Grannis,et al.  Leveraging Health Information Exchange to Support Public Health Situational Awareness: The Indiana Experience , 2010, Online journal of public health informatics.

[19]  Kim M. Unertl,et al.  Health information exchange usage in emergency departments and clinics: the who, what, and why , 2011, J. Am. Medical Informatics Assoc..

[20]  J. Øvretveit The contribution of new social science research to patient safety. , 2009 .

[21]  David A. Chambers,et al.  National Institutes of Health approaches to dissemination and implementation science: current and future directions. , 2012, American journal of public health.

[22]  Martha Stanbury,et al.  "Blueprint version 2.0": updating public health surveillance for the 21st century. , 2013, Journal of public health management and practice : JPHMP.

[23]  Potential effects of electronic laboratory reporting on improving timeliness of infectious disease notification--Florida, 2002-2006. , 2008, MMWR. Morbidity and mortality weekly report.

[24]  F. Mostashari,et al.  Benefits and barriers to electronic laboratory results reporting for notifiable diseases: the New York City Department of Health and Mental Hygiene experience. , 2007, American journal of public health.

[25]  Nancy L. Leech,et al.  Linking Research Questions to Mixed Methods Data Analysis Procedures 1 , 2006 .

[26]  Carolyn Chew-Graham,et al.  The use of mixed methodology in evaluating complex interventions: identifying patient factors that moderate the effects of a decision aid. , 2007, Family practice.

[27]  C. McDonald,et al.  A randomized, controlled trial of clinical information shared from another institution. , 2002, Annals of emergency medicine.

[28]  John Creswell,et al.  The Use of “Mixing” Procedure of Mixed Methods in Health Services Research , 2013, Medical care.

[29]  Effect of electronic laboratory reporting on the burden of lyme disease surveillance--New Jersey, 2001-2006. , 2008, MMWR. Morbidity and mortality weekly report.

[30]  D. Weber,et al.  Completeness of Communicable Disease Reporting, North Carolina, USA, 1995–1997 and 2000–2006 , 2011, Emerging infectious diseases.

[31]  S. Groseclose,et al.  Completeness of notifiable infectious disease reporting in the United States: an analytical literature review. , 2002, American journal of epidemiology.

[32]  Alexander C. Wagenaar,et al.  The Value of Interrupted Time-Series Experiments for Community Intervention Research , 2000, Prevention Science.

[33]  Kaija Saranto,et al.  The utilization rate of the regional health information exchange: how it impacts on health care delivery outcomes. , 2012, Journal of public health management and practice : JPHMP.

[34]  A. Onwuegbuzie,et al.  Mixed Methods Research: A Research Paradigm Whose Time Has Come , 2004 .

[35]  A. O’Cathain,et al.  Three techniques for integrating data in mixed methods studies , 2010, BMJ : British Medical Journal.