Using EHR data to support clinical research both within our organizations and with partner entities.

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Presentation transcript:

Using EHR data to support clinical research both within our organizations and with partner entities

 Using EHR data to support clinical research both within our organizations and with partner entities ◦ Learning Objectives:  Learn strategies on using data to support and enhance your clinical research  Discuss how to share data and analysis across the industry

 Craig Owen ◦ Director, Clinical Analytics & Informatics ◦ MD Anderson Cancer Center, Houston, Texas  Jay Moskowitz ◦ President & CEO ◦ Health Sciences South Carolina, Columbia, South Carolina

 Craig Owen: Learn strategies on using data to support and enhance your clinical research  Jay Moskowitz: Discuss how to share data and analysis across the industry  Panel Discussion

 Employees – >18,000 including 1,500 faculty  Hospital Patient Days – 180,354  Hospital Admissions – 25,230  Revenue – approx. $3 Billion  Hospital Beds – 594

Use Case #1

Development of Policies & Procedures for Maximizing Resource Allocation

Transparent & Sustainable Information Delivery

Use Case #2

Models of Practice Change Practice change is generally a difficult and slow process. Successful change requires multiple avenues of approach including: – Communication Medicine continues to be a piecework sort of enterprise – 1 department of surgery, 137 practices – Individual providers have little insight into what others are doing. Little actual cross fertilization of ideas and practices – Process re-engineering Eliminate bottlenecks and streamline workflow so that making the correct decision is facilitated – Education Knowing what the best is through lectures, demonstrations, and education leads to providers changing how they practice Studies show that while ideas and techniques of great benefit to the providers get adopted quickly, those of marginal benefit or those that require process change/increased effort do not – Competition The people in medicine are extremely competitive and no one wants to be in the lower half by any measure

Departments identified target processes and practices where practice change was needed Performed a literature search to collect EBM guidelines – Distilled input variables necessary to build the scorecard Identified source systems that could feed the necessary data Gap analysis of missing data, poor definitions, practice issues – Created working groups to address these issues Worked with departments to create CME focused on the guidelines – Enabled discussion and feedback to modify guidelines for local practice – Identified potential implementation roadblocks early

When the reporting process was in testing, first pass data was presented to the department for discussion – A second CME was used to re-emphasize the guidelines in light of actual practice data – Data integrity was explicitly addressed and additional views of the data were created to answer questions on data validity Once final validation and acceptance of the process occurred, scorecards were managed by the departmental QI / PI committee To help understand process drift, a set of internal metrics for the QI / PI committee were created to view practice level performance as well as enable drill down to individual provider level data

MD Anderson Use Case

Critical Success Factors – Understand existing EMR strengths and weaknesses of data collection – Develop short term and long term strategies for information delivery – Focus on ease of use and sustainability Electronic source systems are more reliable than paper based ones – If it is a metric worth scoring, it is worth moving the data collection to an electronic format Sustainable information delivery – Create an automated process for gathering and processing of data – Self-Serve / automated report generation