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All content in this area was uploaded by Ross Lordon on Nov 24, 2015
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Mapping Workflows in a Surgical Clinic to Guide Implementation of a Patient-Centered Postoperative
mHealth Wound Assessment System
Ross Lordon, BS1, Heather Evans, MD1, Andrea Hartzler, PhD2, Cheryl Armstrong, BSN RN MPH1,
Sarah Whitehead, ARNP MN1, Patrick Sanger, PhD1, William Lober, MD1
1University of Washington, Seattle, Washington; 2Group Health Research Institute, Seattle, Washington
Intro: The successful adoption of novel health information technology (HIT) is often challenging and susceptible to a
multitude of problems. Poor design, lack of planning, ineffective implementation, or an absence of socio-technical support
post-implementation, can cause technology to be underutilized or abandoned entirely. Effective implementation demands
a comprehensive understanding of the current work processes of the target environment. Once established, it is imperative
to closely align new technology with current work processes to minimize frustration during implementation1. Anticipating
user needs, such as nurses integrating patient generated mobile health (mHealth) data with the electronic health record
(EHR), for implementation is paramount.1 Specifically, our team is implementing an mHealth platform to facilitate patient
self-tracking and communication with providers about the signs and symptoms of surgical site infections after hospital
discharge. Patients utilize an mHealth application and providers access the patient generated data on a computer based
dashboard. Unfortunately, we lack guidance on workflow mapping for implementation of mHealth platforms in clinical
settings. The majority of guidance on HIT workflows focuses on EHRs and decision support, such as alerts and
reminders.2 To explore this gap, we examined the adaptation of existing HIT workflow assessment tools recommended for
EHRs, such as benchmarking and flowcharting,3 to prepare for the implementation of an mHealth platform in surgery
care. Methods: We conducted semi-structured interviews with staff in a plastic surgery clinic to map the existing
workflows for utilizing wound photos submitted by post-operative patients. We formally documented these workflow
processes using business process-modeling notation (BPMN), a form of flowcharting.3 Once the existing workflows had
been visualized in the first BPMN diagram, we produced a second BPMN diagram depicting the proposed changes to the
existing workflow. We presented the second BPMN diagram to all the stakeholders involved with the mHealth platform
implementation. Barriers, opportunities, and weaknesses were identified and included in subsequent revisions.
Results: After three rounds of iterative revisions, the BPMN diagram helped us to align the implementation of the
mHealth platform with current clinic work processes. Next we used our findings to draft a new BPMN diagram depicting
workflow processes after future implementation of the mHealth platform. Then we presented this to the clinic and
mHealth development team to guide the implementation process. Using this diagram, the mHealth development team and
clinic staff identified specific components of the workflows that will provide evaluation metrics to assess process
improvements after implementation. Examples of metrics include, nurses’ time spent discussing wound concerns with
patients, time spent documenting concerns in the EHR, and time to resolve reported problems. Discussion: Generating
BPMN diagrams demonstrating clinic workflow processes before and after the mHealth platform implementation helped
us gain the confidence of the clinic staff, streamline the implementation planning process, and lay down a critical
foundation for the implementation of our mHealth platform in clinical care. Through this iterative process, we gained
insights into the multiple ways a patient could initiate communication about wound concerns. We incorporated these
insights into new workflows and evaluation metrics to facilitate future implementations. Thus, the BPMN diagrams
helped inform the new workflow processes with the intent of minimizing disruption to the current workflow within the
clinic. The subsequent implementation phase will incorporate producing a third BPMN diagram to depict the actual post
implementation workflows. This will allow us to compare the anticipated new workflows to the actual post
implementation workflows. In future work we will also observe the pre-implementation workflows in the clinic to
complement the stakeholder interviews. Conclusion: There is a need for a structured approach to mHealth platform
implementation in clinical settings. Translating existing HIT workflow assessment tools to the mHealth domain has
shown tremendous value in guiding our implementation process.
1. Barnett T. mHIMMS Roadmap: A Structured Approach 2014 [3/12/2015]. Available from:
http://www.himss.org/ResourceLibrary/GenResourceDetail.aspx?ItemNumber=28994.
2. AHRQ. Health Information Technology: Best Practices Transforming Quality, Safety, and Efficiency; [cited
3/12/15]. Available from: http://healthit.ahrq.gov/health-it-tools-and-resources/workflow-assessment-health-it-
toolkit/research.
3. AHRQ. Workflow Assessment for Health IT Toolkit » All Workflow Tools [3/12/2015]. Available from:
http://healthit.ahrq.gov/health-it-tools-and-resources/workflow-assessment-health-it-toolkit/all-workflow-tools.
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