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Enhancing Health Management: Predicting Physician Utilization of Integrated Electronic Prescribing Laurel K Taylor McGill University 6 June 2007 Orlando,

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Presentation on theme: "Enhancing Health Management: Predicting Physician Utilization of Integrated Electronic Prescribing Laurel K Taylor McGill University 6 June 2007 Orlando,"— Presentation transcript:

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

2 Messages oThings can be better in health care oTechnology is a key facilitator for improvement oTechnology uptake extremely variable oUtilization of technology can be predicted / modified

3 Electronic Decision Support Systems The Potential Electronic Decision Support Systems The Potential oProvide complete information on current drugs for physicians and pharmacists oReduce prescribing and transcription errors oImprove match between need and therapy oEnhance compliance oImprove disease management and patient outcomes oIncrease clinical and cost effectiveness of treatment

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

5 Only 1 Pharmacy 59% Multiple Pharmacies 41% Many patients visit multiple pharmacies Source: Tamblyn, CMAJ, 1993 Inappropriate Prescriptions -The Canadian Context-

6 Electronic Decision Support Systems The Challenges Electronic Decision Support Systems The Challenges oInconsistent features across applications oLack of integration with existing IT systems oPoor integration with provider work flow oLack of systematic and rigorous evaluation methodology

7 Electronic Decision Support Systems The Challenges Electronic Decision Support Systems The Challenges Extreme variability in physician utilization Unrealized benefits

8 Primary Care And IT -The Canadian Context- o 23% - electronic medical records o 15% - access to hospital records o 11% - e-prescribing capabilities o 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) o 61 general practitioners o 26 practice sites o Located in an urban Canadian centre o Developed physician and practice characteristics based on 18 months of data prior to implementation o Survey data o Medical services claims database o Medication services claims database o Collected 6 months of electronic prescribing utilization data subsequent to implementation of an electronic integrated drug and disease management system. o Electronic audit trails

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

12 MOXXI -Patient Characteristics- Participating Not Participating Sex n (%) Male 7471 (40.2) 29166 (40.2) Female 11133 (59.8) 40873 (56.4) Age (years) <30 1334 (7.2) 23226 (32.0) 30-45 2728 (14.7) 16439 (22.7) 46-60 6045 (32.5) 17140 (23.6) >60 8497 (45.6) 13233 (18.3) n (SD) Average # Visits 4.4 (3.7) 2.5 (2.6)

13 n (%) Year of Graduation >1980 31 (51) 1960-1979 30 (49) Sex Male 33 (54) Prior Computer Experience <5 hours/week 36 (58) 5-15 22 (35) >15 3 (5) Physician Typology Pragmatist 39 (64) Receptive 9 (15) Seeker 10 (16) Traditionalist 3 (5) MOXXI -Physician Characteristics-

14 MeanSDRange Number of Unique Patients 184087719-3880 Number of Patient Visits 4193170323-9085 Continuity of Care Index 0.570.090.22-0.72 Average Medication Use 2.840.831.27-4.74 MOXXI -Practice Characteristics-

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

16 MOXXI Results: Full Model R 2 =.4997 Physician CharacteristicsE-Rx Ratep-valueSexMaleFemale33.227.5.2528ref Grad Year 19651981199936.330.824.8.2787 Typology SeekerReceptivePragmatistTraditionalist24.037.732.54.5.0732.0042.0058Ref Prior Computer Experience < 5 hrs/week 5-15 hrs/week > 15 hrs/week 27.035.848.8.0040

17 MOXXI Results: Full Model R 2 =.4997 Physician/Practice CharacteristicsE-Rx Rate p-value Continuity of Care Lowest Quartile Second Quartile Third Quartile Highest Quartile 33.7 34.3 28.8 25.6 ref.7063.4717.5843 Average Medication Use (2.9 drugs) 30.6.0358 Patient Volume Lowest Quartile Second Quartile Third Quartile Highest Quartile 34.529.336.122.4ref.6209.7881.3103

18 MOXXI Results: Final Model R 2 =.4633 Physician/Practice CharacteristicsEstimatesp-valueTypologySeekerReceptivePragmatistTraditionalist.1971.3310.2989Ref.0404.0010.0010Ref Prior Computer Experience.0096.0018 Medication Use.0758.0027 Practice Volume Third Quartile.0740.0974

19 MOXXI - Implications for Practice- o oImplementation may require staged approach o oModular approach to physicians with little or no computer experience o oEarly intervention where necessary o oDeeper understanding of credible evidence for practice decisions o oIntegration into current workflow important

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

21 Acknowledgements Support for this research was provided by: o o 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. o Canadian Institutes of Health Research NET Grant o Canadian Health Services Research Foundation

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

23 Printer ChartPatient MOXXI Server Pharmacy eRx eRx Doctors Office Régie de lassurance maladie Real-time adjudication MOXXI System Overview

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

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

26 Seeker ReceptiveTraditionalist Evidence Pragmatist Experience Nonconformity Practicality Green, Gorenflo and Wyszewianski, 2002 Understanding Predictors of Utilization The Physician Typology Model

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


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