Clinical Cycle Management

It’s indisputable that there are tremendous insights to be gleaned from the interaction with clinicians and EMR software. Arcadia Healthcare Solutions did a great job of illustrating this in its recent data visualization “A Day in the Life,” research into click-level data. The data visualization was motivated by a WBUR piece authored by three prominent Boston physicians, who decried the impact of poorly-designed or poorly-implemented electronic medical records on patient care.

Inspired by an exchange in last Friday’s #HITsm tweetchat, it spurred a need to highlight the massive opportunities that exist to harvest EMR operational data for workflow improvement. In the tweetchat, healthcare workflow guru, Chuck Webster, MD postured that we should be focused on workflow as the issue rather than the data. Chuck’s thesis is supported by his plethora of research on the topic. In his research, Chuck postures that MU incentivized the wrong things, resulting in poor EMR interoperability, functionality, reporting, navigation & stability.

While its true that big-bang EMR implementations – with prescriptive workflows – were a direct result of the incentives put in place, they were a means to an end.  One of my colleagues, Robert Downey, Vice President, Product Development, elaborated on this point at Galen’s Partner Advisory Council:

The Broken Promises of the EMR

• They will save money
  • Save the healthcare organization money…
    • In-patient cost increases of 6% to 10%
    • Ambulatory cost increase of 2% to 3% (ignoring initial capital investments)
  • Save the “system” money…
    • Increased overall claims
• They will dramatically improve care
  • Early studies show little difference
    • Best practices met (in-patient)
      • 8% for advanced EMR usage
      • 7% for basic EMR usage
      • 9% for no usage
    • Quality Metrics (ambulatory)
      • No statistical difference between paper and EMR

A Means to an End…

• Structured data gathering
• Facilitate large scale “clinical” trials
• Prerequisite for essentially everything else

Poorly Suited to Unlock the Data

• Largely designed for data entry
  • Workflow Tacked On
  • CDS Tacked On
  • [Everything Else] Tacked On
• Don’t play well with others
  • Interface Hell
  • Few, if any APIs
  • Complex, “evolved” data schema
• Inherently a multi-platform, multi-vendor problem
  • Clinical (EMRs, care partners)
  • Claims (Clearinghouses, Payers)
  • Billing (HIM, PM, FMS CRMs)
  • Biometrics (Remote Patient Monitoring, IoT)
  • HR / Administrative (Peoplesoft, time tracking, etc.)
  • Financial
  • Genomic Data
  • Analytical (Risk analysis, population definitions, etc.)

It’s with this background that we introduce the opportunity to transform the EMR from a transactional system of record, to strategic asset, through time-stamped event data-driven workflow optimization: Clinical Cycle Management. Profiling an EMR application allows for robust and rich usage data gathering, including clicks, mouse movements, and time spent.

Analysis of these workflows, using a temporal query tool, allows for identification of bottlenecks, poor workflows, and other time sinks. It shows both individual user activity, as well as aggregate data, and lets you define logical EMR “tasks.” It provides the basis for realizing workflow optimization efficiency gains through: 1. Workspace modification, 2. Training, 3. Automation through macros, 4. EMR UI Augmentation.

Such analysis would also facilitate the ability to introduce real-time clinical decision support through workflow interventions. For instance, a doctor prescribing antibiotics for uncomplicated bronchitis or a doctor ordering an x-ray for lower back pain with no additional symptoms. Shown to the right is an illustration of the concept of  “smart tip” UI augmentation feature for the clinician. UI augmentation such as this improves user interaction, provides clinical decision support, and automates some UI-related tasks.

Taking this a step further, clinician generated clinical automation would completely automate a clinician decision. Below is an illustration of the concept for a clinician-generated clinical automation for liver pain.

Incredible potential exists, but data-driven optimization is no trivial endeavor. Gain perspectives from HDO leaders who have successfully navigated EMR clinical optimization and refine your EMR strategy to transform it from a short-term clinical documentation data repository to a long-term asset by downloading our EMR Optimization Whitepaper.