Modeling and Analysis of Clinical Care for Health Information Technology Improvement (Washington)

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Summary:

Electronic health records (EHRs) and health information technology (IT) applications have great potential to reduce healthcare costs while increasing efficiency and quality. However, there is resistance to EHR adoption due to high startup costs, unpredictable benefits, and disruption to the workflow of clinical care. Two fundamental steps to realize the full potential of health IT are to identify the optimal role of computing in clinical care and to design systems to improve care in predictable ways.

The project developed new techniques for model-based analysis and design of health IT systems using MATH, a method that captures workflow improvements and connects them to health IT software design. MATHflow is the modeling tool that supports concurrent engineering of workflow and health IT, and represents clinician workflow tasks and the information resources required to support them. The project also aimed to demonstrate how these techniques can be applied to design systems that are highly usable and predictably beneficial to healthcare in outpatient clinics treating multiple sclerosis (MS) and chronic pain, and for an emergency department (ED).

The specific aims of the project were as follows:

  • Apply ethnographic research to discover the way care is actually done with existing information resources at each clinic. 
  • Model research findings as baseline workflows using the new modeling techniques of MATHflow. 
  • Analyze how care should be improved methodically in measurable ways with new health IT design concepts. 
  • Develop software prototypes of the most promising designs to evaluate usability, workflow impact, and technical feasibility. 
  • Refine MATH, a model-based design method, based on experience with each successive clinic. 

The project modeled and analyzed clinical care workflows, networks, and decision making at three sites: The Veterans Affairs Puget Sound Multiple Sclerosis Regional Program, the University of Washington Medicine Center for Pain Relief, and the Baylor University Medical Center ED. Researchers captured and documented baseline clinical workflows using MATH, and then analyzed how health IT could improve workflow in measurable ways using the MATHflow modeling tool. Five health IT system prototypes were modeled, designed, and evaluated to address the needs of: 1) case management for MS, 2) procedure ordering for pain care, 3) patient data collection and analysis for pain care, 4) room turn-around measurement for ED care, and 5) ED decision support for admissions.

Study results found that that new workflow modeling tools such as MATH and MATHflow can explicitly represent both the clinical workflow and the needed improvements in a single, integrated model. These new techniques for model-based analysis and design have promise to reduce unnecessary health IT variation and correct the gap between health IT and the needs of clinical care. Closer adherence to optimal procedures and workflows can “build in” care quality to health IT systems.

Modeling and Analysis of Clinical Care for Health Information Technology Improvement - 2012

Summary Highlights

  • Principal Investigator: 
  • Funding Mechanism: 
    PAR: HS11-198: Understanding Clinical Information Needs and Health Care Decision Making Processes in the Context of Health Information Technology (IT) (R01)
  • Grant Number: 
    R01 HS 021233
  • Project Period: 
    September 2012 - August 2016
  • AHRQ Funding Amount: 
    $1,830,993
  • PDF Version: 
    (PDF, 293.35 KB)

Summary: Electronic health records (EHRs) and associated applications of health information technology (IT) have great potential to reduce health care costs while increasing access and quality. However, EHR adoption faces resistance based on serious concerns such as high start-up costs, unpredictable benefits, and disruption to clinical care workflow. Many popular design paradigms for health IT focus on software features without explaining how these features will increase efficiency and quality. A well-designed health IT application with good usability will make routine performance of safe, efficient, and effective procedures the easiest course of action. Failure to incorporate these principles into health IT design produces unpredictable, even negative effects on clinical care. Yet unusable health IT applications that do not match workflow needs are so common that some physicians have adapted the term ‘shadow system’ to describe the temporary records that users create to compensate for the gap between the way the EHR organizes information and the way it is needed for the appropriate workflow of clinical care. Until health IT can reliably add value to care, its potential for controlling costs while improving quality will remain elusive.

The goal of this research is to understand and document how clinical work, including constraints of context and information resources, is actually accomplished and analyze how the efficiency and quality of care could be measurably improved, with an emphasis on health IT as the means. The project is modeling and analyzing clinical care workflows, networks, and decisionmaking at three sites: the Veterans Affairs Puget Sound Multiple Sclerosis Regional Program, the University of Washington Medicine Center for Pain Relief, and the Baylor Hospital Health Care Admissions Program.

Specific Aims:

  • Apply the techniques of contextual research and ethnographic research to discover and document the workflow of how clinical care is actually done for multiple sclerosis, and analyze how it could be improved with modern health IT using the Modeling and Analysis Toolsuite for Healthcare (MATH.) (Ongoing)
  • Apply refined techniques to a second study site for a different area of chronic care, pain management, to begin understanding the generality of MATH for a specialty with referrals from both primary care and other specialists, and distinct coordination requirements for co-morbidities and treatment with narcotics. (Upcoming)
  • Apply re-refined techniques to a third study site, the area of hospital admissions, with intensive care transitions that require inpatient care coordination, a large number of providers, nonscheduled care, and high fluctuations of workload and interruptions. (Upcoming)
  • Identify the methodological principles that are general across all three domains for improving care with better health IT, and document our method for capturing, analyzing, and evaluating
    health IT improvement for the performance of clinical care. (Upcoming)

2012 Activities: The project moved through preparatory stages. Dr. Butler received institutional review board approval. Despite some delays related to purchasing the new version of the MATH software, training was held on schedule. The project team held the kick-off meeting with Veterans Affairs Puget Sound Multiple Sclerosis Regional Program, the first study site. The meeting included an overview of project objectives and ensured buy-in from managers. Dr. Butler has also begun working with Dr. Eric Eisenstein, Assistant Professor at Duke Clinical Research Institute’s Outcomes Research and Assessment Group, to define innovative measures to evaluate the impact of new health IT on clinical workflows. As last self-reported in the AHRQ Research Reporting System, project progress and activities are mostly on track. The project budget funds are currently somewhat underspent due to delays in purchasing the newest version of the MATH software, which will be delivered in the second quarter.

Preliminary Impact and Findings: This project has no findings to date.

Target Population: Chronic Care*, Multiple Sclerosis, Veterans

Strategic Goal: Develop and disseminate health IT evidence and evidence-based tools to support patient-centered care, the coordination of care across transitions in care settings, and the use of electronic exchange of health information to improve quality of care.

Business Goal: Implementation and Use

* This target population is one of AHRQ's priority populations.

Modeling and Analysis of Clinical Care for Health Information Technology Improvement - Final Report

Citation:
Butler K. Modeling and Analysis of Clinical Care for Health Information Technology Improvement - Final Report. (Prepared by University of Washington under Grant No. R01 HS021233). Rockville, MD: Agency for Healthcare Research and Quality, 2016. (PDF, 1.36 MB)

The findings and conclusions in this document are those of the author(s), who are responsible for its content, and do not necessarily represent the views of AHRQ. No statement in this report should be construed as an official position of AHRQ or of the U.S. Department of Health and Human Services.
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