Impact of Physician Order Entry System and its Associated Automation of Order Sets on Lab Orders

1. Impact of Physician Order Entry System and its Associated Automation of Order Sets on Lab Orders The Ohio State University Medical Center

2. OSUMC – Profile Information • 4 Hospitals, 36 primary and specialty care sites • 897 Beds • 42,930 Inpatient visits • 697,843 Outpatient visits • Physician Order Entry (POE) System has 2,057 physician users and 5,998 staff users

3. POE at OSUMC • 100% of Orders Entered Electronically • Decision Support tools include: • Allergy Checking • Drug Interaction • Order Duplicate Checking • Weight-Based Dosing • Drug Route Restriction • 450 Evidence-Based Order Sets • Robust Interfaces with Most Ancillary Departments like Lab and Pharmacy

4. Information Warehouse at the OSUMC Captures: • Patient Demographic data • Patient Accounting data • Patient Management data • Lab Results and critical values • Blood bank data • Physician Order Entry data • Discharge Instructions • Readmissions • 450 Evidence-Based Order Sets • Robust Interfaces with Most Ancillary Departments like Lab and Pharmacy

5. OSUMC Information Warehouse: Conceptual view Data Acquisition Data Transfer Information Warehouse Data Access Encounter DM ICU DM Readmt DM SMS Patient Management HCC Cost Accounting Data Warehouse E X T R A C T L O A D Pharmacy DM ED Visits DM Mom/Baby DM SMS Patient Accounting Multidimensional analysis/Data Miming Rejection DM POE DM Pt Sat. DM Lab DM Blood Bank DM Adhoc query SMS COE Web reporting & dashboard Sunquest Lab System Census DM Summary Data Marts De-identify Revenue DM Patient Satisfaction OHA DM Outside data for benchmarking Ohio Hospital Association 5

6. Integrating POE DM with Other DMs Encounter Data Mart • Order set utilization, analysis and quality impact by DRG, ICD9 Procedures, Discharge diagnoses • Order set utilization and Outcomes analysis Lab Data Mart • Critical results and treatment orders • Impact of POE on lab orders and compliance

7. Over all impact of order sets on Lab orders: Results Comparison of average number of lab orders per patient for May 2000 (pre order set*) and May 2002 (post order set*) for all DRGs shows a 69% increase * Note: Order set implementation for best practice guidelines went into effect in Jan 2001

8. Impact of order sets on Lab orders by DRG: Results Comparison of average number of lab orders per patient for May 2000 (pre order set*) and May 2002 (post order set*) for DRG 302 (among the top 10 DRGs by average lab orders/patient) shows a 48.43% increase * Note: Order set implementation for best practice guidelines went into effect in Jan 2001

9. Impact of order sets on Lab orders for Cardiology related DRGs: Results Comparison of average number of lab orders per patient for May 2000 (pre order set*) and May 2002 (post order set*) for the top two Cardiology DRGs by patient volume shows an average increase of 175%. * Note: Order set implementation for best practice guidelines went into effect in Jan 2001

10. Impact of order sets on Lab orders: Conclusions • Overall Lab Orders have increased by 69% • Increase can be significantly higher or lower for specific DRGs • This significant difference is due to number of lab orders in ordersets used for those specific DRGs • DRGs with more lab orders in ordersets have a greater percent increase • Increase in lab orders can be attributed to increased orderset use • Orderset Compliance • Best Practice Guidelines