Laurel K Taylor McGill University 6 June 2007 Orlando, Florida

1. Enhancing Health Management: Predicting Physician Utilization ofIntegrated Electronic Prescribing Laurel K Taylor McGill University 6 June 2007 Orlando, Florida

2. Messages • Things can be better in health care • Technology is a key facilitator for improvement • Technology uptake extremely variable • Utilization of technology can be predicted / modified

3. Provide complete information on current drugs for physicians and pharmacists Reduce prescribing and transcription errors Improve match between need and therapy Enhance compliance Improve disease management and patient outcomes Increase clinical and cost effectiveness of treatment Electronic Decision Support SystemsThe Potential Safety Quality Cost

4. 9+ physicians 3% 1 physicians 27% 5-8 physicians 16% 3-4 physicians 30% 2 physicians 24% 49% of patients visit 3 or more physicians Inappropriate Prescriptions -The Canadian Context- Proportion of patients with at least one inappropriate prescription Number of prescribing physicians Source: Tamblyn, CMAJ, 1993

5. Multiple Pharmacies41% Only 1 Pharmacy 59% Many patients visit multiple pharmacies Inappropriate Prescriptions -The Canadian Context- Source: Tamblyn, CMAJ, 1993

6. Inconsistent features across applications Lack of integration with existing IT systems Poor integration with provider work flow Lack of systematic and rigorous evaluation methodology Electronic Decision Support SystemsThe Challenges

7. Electronic Decision Support SystemsThe Challenges Extreme variability in physician utilization Unrealized benefits

8. Primary Care And IT -The Canadian Context- • 23% - electronic medical records • 15% - access to hospital records • 11% - e-prescribing capabilities • 8% - electronic test ordering International Health Policy Survey of Primary Care Physicians in Seven Countries, The Commonwealth Fund, 2006

9. Research Objectives To define and analyze predictors of physician utilization of electronic prescribing through an integrated drug and disease management system.

10. Research Setting MOXXI Project(Medical Office of the XXI Century) • 61 general practitioners • 26 practice sites • Located in an urban Canadian centre • Developed physician and practice characteristics based on 18 months of data prior to implementation • Survey data • Medical services claims database • Medication services claims database • Collected 6 months of electronic prescribing utilization data subsequent to implementation of an electronic integrated drug and disease management system. • Electronic audit trails

11. MOXXIPerceived Benefits of the System Drug Cost Information Stop/Change Function Info on ER visits & Hospitalization Drug Monograph Current Medications List Refill Compliance Indicator List of RX prescribed by Others Drug Interactions Re-prescribing function Printed Prescription Not Beneficial Very Beneficial Physician Questionnaire Rating 4 Months Post Implementation (October 2005 – February 2006)

12. MOXXI -Patient Characteristics-

13. MOXXI-Physician Characteristics-

14. MOXXI-Practice Characteristics-

15. MOXXIUtilization Indicator – e-Rx/visits Study Period: 1 Oct, 2005 – 3 July, 2006 Include all patients consented before index date. Numerator: Select all patients included in the denominator. Select visit if e-Rx written (prescription, not dins) from MOXXI . # e-Rx Denominator: Select patients that had an outpatient visit during the study period. Select patients consenting to MOXXI before 1 Oct 2005. Select patients visiting physician in outpatient setting # visits

16. MOXXIResults: Full Model R2=.4997

17. MOXXIResults: Full Model R2=.4997

18. MOXXIResults: Final Model R2=.4633

19. MOXXI- Implications for Practice- • Implementation may require staged approach • Modular approach to physicians with little or no computer experience • Early intervention where necessary • Deeper understanding of credible evidence for practice decisions • Integration into current workflow important

20. MOXXI - Implications for Policy- • IT availability insufficient to sustain utilization • Need to identify strategies to enhance adoption and utilization • May require availability of customized training programs • Rigorous evaluation of clinical applications for features, workflow integration assessment

21. Acknowledgements Support for this research was provided by: • The Commonwealth Fund. ”The views presented here are those of the authors and should not be attributed to The Commonwealth Fund or its directors, officers, or staff.” • Canadian Institutes of Health Research NET Grant • Canadian Health Services Research Foundation

22. Medical Office Of The XXI Century (MOXXI) -Backup Slides- *Total Patient Consents = 9052 *Total e-Rx Written = 7990

23. Régie de l’assurance maladie MOXXI System Overview Doctor’s Office eRx MOXXI Server Printer Real-time adjudication eRx Pharmacy Chart Patient

24. 34% Late majority 34% Early majority 16% Laggards 2 ½% Innovators Technology Adoption Model 13 ½% Early adaptors Time of adoption innovations

25. Understanding Predictors of UtilizationThe TAM (Technology Acceptance) Model • Developed by Davis in 1989 for predicting user acceptance of computers Perceived Ease of Use Behavior Intention Perceived Usefulness Computer Usage

26. Understanding Predictors of UtilizationThe Physician Typology Model Receptive Traditionalist Pragmatist Seeker Evidence Experience Nonconformity Practicality Green, Gorenflo and Wyszewianski, 2002

27. Medical Office Of The XXI Century (MOXXI) Utilization Indicator – e-Rx/Rx Study Period: 1 Oct, 2005 – 3 July, 2006 Include all patients consented before index date. Numerator: Select the DINs from denominator and match to an eRx during the study period # e-Rx DINs Denominator: Select patient if ≥ 1 dispensed DIN during study period Select patients consenting MOXXI patients before 1 Oct 2005. Select patients with RAMQ coverage (75% not gaps) during study period Select DINs prescribed during study period # visits *Total Patient Consents = 9052 *Total e-Rx Written = 7990