Complexity and the science of implementation in health IT - Knowledge gaps and future visions

OBJECTIVES The intent of this paper is in the examination of health IT implementation processes - the barriers to and facilitators of successful implementation, identification of a beginning set of implementation best practices, the identification of gaps in the health IT implementation body of knowledge, and recommendations for future study and application. METHODS A literature review resulted in the identification of six health IT related implementation best practices which were subsequently debated and clarified by participants attending the NI2012 Research Post Conference held in Montreal in the summer of 2012. Using the framework for implementation research (CFIR) to guide their application, the six best practices were applied to two distinct health IT implementation studies to assess their applicability. RESULTS Assessing the implementation processes from two markedly diverse settings illustrated both the challenges and potentials of using standardized implementation processes. In support of what was discovered in the review of the literature, "one size fits all" in health IT implementation is a fallacy, particularly when global diversity is added into the mix. At the same time, several frameworks show promise for use as "scaffolding" to begin to assess best practices, their distinct dimensions, and their applicability for use. CONCLUSIONS Health IT innovations, regardless of the implementation setting, requires a close assessment of many dimensions. While there is no "one size fits all", there are commonalities and best practices that can be blended, adapted, and utilized to improve the process of implementation. This paper examines health IT implementation processes and identifies a beginning set of implementation best practices, which could begin to address gaps in the health IT implementation body of knowledge.

[1]  Craig Standing,et al.  The implementation of electronic health records: A case study of bush computing the Ngaanyatjarra Lands , 2011, Int. J. Medical Informatics.

[2]  Blackford Middleton,et al.  Why Do Patients in Acute Care Hospitals Fall? Can Falls Be Prevented? , 2009, The Journal of nursing administration.

[3]  G. Aarons,et al.  Advancing a Conceptual Model of Evidence-Based Practice Implementation in Public Service Sectors , 2010, Administration and Policy in Mental Health and Mental Health Services Research.

[4]  Craig E. Kuziemsky,et al.  A Complex Adaptive Systems Perspective of Health Information Technology Implementation , 2013, ITCH.

[5]  Richard J. Holden,et al.  Using a sociotechnical framework to understand adaptations in health IT implementation , 2013, Int. J. Medical Informatics.

[6]  Stacy L. Frazier,et al.  Toward the Effective and Efficient Measurement of Implementation Fidelity , 2010, Administration and Policy in Mental Health and Mental Health Services Research.

[7]  Brian S. Mittman,et al.  Synthesis of Research Paper: Overview of the Veterans Health Administration (VHA) Quality Enhancement Research Initiative (QUERI) , 2004, J. Am. Medical Informatics Assoc..

[8]  A. Localio,et al.  Role of computerized physician order entry systems in facilitating medication errors. , 2005 .

[9]  Craig Standing,et al.  Mobile technology and healthcare: the adoption issues and systemic problems , 2008, Int. J. Electron. Heal..

[10]  L. Palinkas,et al.  Dynamic adaptation process to implement an evidence-based child maltreatment intervention , 2012, Implementation Science.

[11]  Jeanne Century,et al.  A Framework for Measuring Fidelity of Implementation: A Foundation for Shared Language and Accumulation of Knowledge , 2010 .

[12]  A. Broström,et al.  Creatures of habit: accounting for the role of habit in implementation research on clinical behaviour change , 2012, Implementation Science.

[13]  Cornelia M. Ruland,et al.  Evaluation of different features of an eHealth application for personalized illness management support: Cancer patients' use and appraisal of usefulness , 2013, Int. J. Medical Informatics.

[14]  Blackford Middleton,et al.  Fall prevention in acute care hospitals: a randomized trial. , 2010, JAMA.

[15]  Suzanne Bakken,et al.  Model Formulation: Translating Clinical Informatics Interventions into Routine Clinical Care: How Can the RE-AIM Framework Help? , 2009, J. Am. Medical Informatics Assoc..

[16]  Stephenie R. Chaudoir,et al.  Measuring factors affecting implementation of health innovations: a systematic review of structural, organizational, provider, patient, and innovation level measures , 2013, Implementation Science.

[17]  C. Dowrick,et al.  Implementation Science Development of a Theory of Implementation and Integration: Normalization Process Theory , 2022 .

[18]  Arthur L Kellermann,et al.  What it will take to achieve the as-yet-unfulfilled promises of health information technology. , 2013, Health affairs.

[19]  J. Lowery,et al.  Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science , 2009, Implementation science : IS.

[20]  Deborah Bybee,et al.  Fidelity Criteria: Development, Measurement, and Validation , 2003 .

[21]  Rainu Kaushal,et al.  Bridging Informatics and Implementation Science: Evaluating a Framework to Assess Electronic Health Record Implementations in Community Settings , 2012, AMIA.

[22]  A Kitson,et al.  Enabling the implementation of evidence based practice: a conceptual framework. , 1998, Quality in health care : QHC.

[23]  Cornelia M. Ruland,et al.  Participatory design with children in the development of a support system for patient-centered care in pediatric oncology , 2008, J. Biomed. Informatics.

[24]  L. Lipsitz,et al.  Understanding health care as a complex system: the foundation for unintended consequences. , 2012, JAMA.

[25]  Y. Han,et al.  Unexpected Increased Mortality After Implementation of a Commercially Sold Computerized Physician Order Entry System , 2005, Pediatrics.

[26]  M. Berg,et al.  ICT in health care: sociotechnical approaches. , 2003, Methods of Information in Medicine.

[27]  Janice M. Morse Preventing in-patient falls: The nurse's pivotal role. , 2017, Nursing.

[28]  Thomas M Vogt,et al.  Evaluating the impact of health promotion programs: using the RE-AIM framework to form summary measures for decision making involving complex issues. , 2006, Health education research.

[29]  Christoph U. Lehmann,et al.  Implementation of computerized provider order entry in a neonatal intensive care unit: Impact on admission workflow , 2012, Int. J. Medical Informatics.

[30]  Andrew Booth,et al.  Implementation Science BioMed Central Debate A conceptual framework for implementation fidelity , 2007 .

[31]  J. Waldman Thinking systems need systems thinking , 2007 .

[32]  Thomas R. Yackel,et al.  Case report: Unintended errors with EHR-based result management: a case series , 2010, J. Am. Medical Informatics Assoc..

[33]  Y. Han,et al.  Han YY, Carcillo JA, Venkataraman ST, Clark RS, Watson RS, Nguyen TC, Bayir H, Orr RA. Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system. Pediatrics , 2011 .

[34]  E M Rogers,et al.  Lessons for guidelines from the diffusion of innovations. , 1995, The Joint Commission journal on quality improvement.

[35]  Michael I. Harrison,et al.  Viewpoint Paper: Unintended Consequences of Information Technologies in Health Care - An Interactive Sociotechnical Analysis , 2007, J. Am. Medical Informatics Assoc..

[36]  Kim M. Unertl,et al.  The Science Behind Health Information Technology Implementation: Understanding Failures and Building on Successes , 2012, AMIA.

[37]  S. Shortell,et al.  Improving the quality of health care in the United Kingdom and the United States: a framework for change. , 2001, The Milbank quarterly.

[38]  Jacqueline A Pugh,et al.  Implementation Science Implementation Research Design: Integrating Participatory Action Research into Randomized Controlled Trials , 2022 .