A Rapid Process for Identifying and Prioritizing Technology-Based Tools for Health System Implementation

Emily R Dibble; Bradley E Iott; Allen J Flynn; Darren P King; Mark P MacEachern; Charles P Friedman; Tanner J Caverly

doi:10.2196/11195

A Rapid Process for Identifying and Prioritizing Technology-Based Tools for Health System Implementation

JMIR Cancer. 2018 Nov 27;4(2):e11195. doi: 10.2196/11195.

Authors

Emily R Dibble^#¹, Bradley E Iott^#^{1

2

3}, Allen J Flynn¹, Darren P King⁴, Mark P MacEachern⁵, Charles P Friedman^{1

2

3}, Tanner J Caverly^{1

6

7}

Affiliations

¹ Department of Learning Health Sciences, Medical School, University of Michigan, Ann Arbor, MI, United States.
² School of Information, University of Michigan, Ann Arbor, MI, United States.
³ Department of Health Management and Policy, School of Public Health, University of Michigan, Ann Arbor, MI, United States.
⁴ Division of Hematology and Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States.
⁵ Taubman Health Sciences Library, University of Michigan, Ann Arbor, MI, United States.
⁶ Ann Arbor Veterans Affairs Center for Clinical Management Research, Ann Arbor, MI, United States.
⁷ Department of Internal Medicine, Medical School, University of Michigan, Ann Arbor, MI, United States.

^# Contributed equally.

PMID: 30482740
PMCID: PMC6290266
DOI: 10.2196/11195

Abstract

Background: Health system decisions to put new technologies into clinical practice require a rapid and trustworthy decision-making process informed by best evidence.

Objective: This study aimed to present a rapid evidence review process that can be used to inform health system leaders and clinicians seeking to implement new technology tools to improve patient-clinician decision making and patient-oriented outcomes.

Methods: The rapid evidence review process we pioneered involved 5 sequential subprocesses: (1) environmental scan, (2) expert panel recruitment, (3) host evidence review panel, (4) analysis, and (5) local validation panel. We conducted an environmental scan of health information technology (IT) literature to identify relevant digital tools in oncology care. We synthesized the recent literature using current evidence review methods, creating visual summaries for use by a national panel of experts. Panelists were taken through a 6-hour modified Delphi process to prioritize tools for implementation. Findings from the rapid evidence review panel were taken to a local validation panel for further rapid review during a 3-hour session.

Results: Our rapid evidence review process shows promise for informing decision making by reducing the amount of time and resources needed to identify and prioritize adoption of IT tools. Despite evidence of improved patient outcomes, panelists had substantial concerns about implementing patient-reported outcome tracking tools, voicing concerns about liability, lack of familiarity with new technology, and additional time and workflow changes such tools would require. Instead, clinicians favored technologies that did not require clinician involvement.

Conclusions: Health system leaders can use the rapid evidence review process presented here to usefully inform local technology adoption, implementation, and use in practice.

Keywords: clinical decision support; decision support systems, clinical; evidence review; evidence-based practice; expert panel; health information technology; medical informatics applications; oncology care model; patient reported outcome measures; practice guidelines as topic.

©Emily R Dibble, Bradley E Iott, Allen J Flynn, Darren P King, Mark P MacEachern, Charles P Friedman, Tanner J Caverly. Originally published in JMIR Cancer (http://cancer.jmir.org), 27.11.2018.