Does Access to EHR Information Improve ED Performance? Slide Presentatation

Slide Presentation from the AHRQ 2008 Annual Conference

On September 9, 2008, Stuart M. Speedie, Ph.D., Jing Du, Nawanan Theera-Ampornpunt, M.D., Young-Taek Park, and Donald Connelly, M.D., Ph.D. (PI), made this presentation at the 2008 Annual Conference. Select to access the PowerPoint® presentation (504 KB; Plugin Software Help).

Slide 1

Does access to electronic health record (EHR) information improve emergency department (ED) performance?

Stuart M. Speedie, Ph.D.
Jing Du
Nawanan Theera-Ampornpunt, M.D.
Young-Taek Park
Donald Connelly, M.D., Ph.D. (PI)
University of Minnesota

Slide 2

Project: A Community-Shared Clinical Abstract to Improve Patient Care Partners:

• Fairview Health Services.
• Allina Hospitals and Clinics.
• HealthPartners.
• University of Minnesota.

Slide 3

EHR Environment

The diagram shows:

• System A runs an Epic EHR Instance.
• System B runs an Epic EHR Instance.
  • Integrated ambulatory—inpatient system.
• System C runs an Epic EHR Instance.
  • Integrated ambulatory—inpatient system.

Notes:

• The EHR environment consists of three systems (A, B, and C). One runs an instance of the Epic outpatient EHR and two run instances of the Epic inpatient and outpatient EHRs.

Slide 4

Project Vision

• At the time patients undergo transitions in care, providers will have ready access (via a shared clinical abstract) to the data needed to make informed clinical decisions so as to favorably impact the quality of care and patient safety.

• Focus: Transitions of care into the emergency department (ED).

Slide 5

Evaluation Description

• Disease Foci: Congestive heart failure (CHF), Diabetes* and Asthma*
• Sites: EDs in three hospitals—one for each organization.
• Index ED visit: first patient ED visit during the baseline time period
• Internal patients—those that have clinical information in the organization's EHR prior to the index ED visit.
• External patients—those that do not have any significant clinical information in the organization's EHR prior to the index ED visit.

• Note: *Supported by a University of Minnesota internal grant.

Slide 6

Underlying Model

The graph's vertical axis presents "Outcome Improvement" while two separate horizontal axes present "Completeness of Clinical Data" and "Amount of Clinical Data." The result of the line graph shows a steady increase in outcome improvement as the amount and completeness of clinical data increases.

Slide 7

Hypothesized Impact

The graph displays the disparity in "Outcome Improvement" between "Internal" and "External" patients over time. The "Outcome Improvement" for "Internal" patients is greater relative to the "Baseline."

Slide 8

Baseline hypotheses

External patients vs. Internal patients will exhibit:

• Longer ED visit duration.
• Greater incidence of hospitalization.
• Greater incidence of mortality.
• More lab tests.
• More imaging procedures.
• More medications.

Slide 9

Current Methods

• Period: 7-1-2006 through 12-31-2007.
• Identified patients from ED billing records with an ICD9 diagnosis code of interest (not necessarily the reason for visit).
• Patient IDs used to extract relevant data from the organization's data warehouse.
• Simple descriptive analyses.

Slide 10

Demographics

The table presents the results for "Total," "Internal," and "External" for various "Demographics."

• Number: 10,446; 6,949 (66.5%); 3,497 (33.5%).
• Percent Female: 52%; 56%; 53%.
• Mean Age: 60.5 years; 60.5 years; 57.5 years.
• ED System A: 3583; 39%; 61%.
• ED System B: 5998; 84%; 16%.
• ED System C*: 865; 58% 42%.
• % CHF**: 32%; 33%; 30%.
• % Diabetes**: 51%; 51%; 51%.
• % Asthma**: 29%; 32%; 29%.

• Note: * Data available only for CHF patients.
  ** Patients may have multiple diseases.

Slide 11

Internal (Int)—External (Ext) Differences

The chart displays various ED data (i.e., Age, Gender, ED length of stay (LOS), Hosp. Admits, Hosp. LOS, ED Mortality, Lab Tests, Medications, Imaging) cross referenced with ED visits for "Overall," "CHF," "Diabetes," and "Asthma."

Slide 12

Conclusions

• Findings that partially supporting the hypothesis.
  • Hospital admissions are greater for external patients.
  • Hospital LOS is longer for external patients.
  • N of medications is greater for external patients.
  • N of imaging studies is greater for external patients.
• Findings of No difference.
  • mortality.
  • Labs.
• Findings that partially contradict to our hypothesis.
  • ED LOS at one hospital is greater for internal patients.
• But demographic differences between external and internal patients require further, more sophisticated analyses.

Slide 13

Acknowledgements

• This project was funded in part under grant number UC1 HS16155 from the Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services.
• This project was funded in part by the Academic Health Center of the University of Minnesota.