Michael Matheny, MD MS; Tejal Gandhi, MD MPH; John Orav, PhD; Zahra Ladak-Merchant, BDS MPH;

1. Impact of an Automated Test Results Management System on Patients’ Satisfaction of Test Result Communication Michael Matheny, MD MS; Tejal Gandhi, MD MPH; John Orav, PhD; Zahra Ladak-Merchant, BDS MPH; David Bates, MD MS; Gilad Kuperman, MD PhD; Eric Poon, MD MPH Brigham & Women’s Hospital, Boston, MA

2. BackgroundTest Result Communication • Test result communication between patients and physicians is a critical part of the diagnostic and therapeutic process • However, follow-up of test results in the primary care setting is often challenging: • High volume of test results • Test results arrive when physician not focused on the patient • Lack of systems to ensure reliability and efficiency • Causes missed and delayed follow-up of normal and abnormal test results

3. BackgroundPatient Satisfaction • These problems reduce patient satisfaction with their medical care, and impair future patient-physician interactions • Improving patient satisfaction has been identified as one of the most important issues currently facing healthcare

4. Objective • To evaluate the impact of an EHR-imbedded automated test results notification system on patient satisfaction of test results communication

5. MethodsStudy Setting • Partners HealthCare System • Brigham & Women’s Hospital • Massachusetts General Hospital • Faulkner Hospital • McLean Hospital • Newton-Wellesley Hospital • Free Standing Outpatient Clinics • Longitudinal Medical Record (LMR) • Released July 2000 • Scheduling • Medication lists • Problem lists • Health maintenance record • Clinic notes (free form & templates)

6. MethodsStudy Setting • Baseline state of test results management • Test results were embedded directly into the patients’ electronic health record • No automated test results tracking • All test results were mailed to the physician’s clinic office • Physicians were paged directly for critical results

7. MethodsIntervention • Results Manager - an electronic test results management system embedded into the LMR • Features: • Tracks and displays all test results associated with an ordering physician • Prioritizes by degree of test result abnormality • Facilitates review of test results in context of patient’s history • Generates test result letters • Allows clinicians to set reminders for future testing

8. MethodsResults Manager Summary Screen

9. MethodsResults Manager Letter Generation Screen

10. MethodsStudy Design

11. MethodsRandomization • Rolling implementation of Results Manager for participating clinics was completed by March, 2004 • Stratified randomization of 26 primary care clinics based on 3 characteristics: • BWH (13) vs. MGH (7) hospital affiliation • 6 were free-standing • Academic (16) vs. Community setting (10) • Low (12) vs. High (14) average patient socioeconomic status

12. MethodsStudy Criteria • Inclusion Criteria • All patients in participating clinics who had any of the following tests: • Chemistry • Hematology • Pathology • Microbiology • Radiology • Exclusion Criteria • Primary care physician determined that patient should not be contacted

13. MethodsSurvey • Outcomes were measured on a dichotomized Likert scale • Primary Outcome Measure • Overall satisfaction with test result communication • Secondary Outcome Measures • Satisfaction with PCP listening skills • Satisfaction with information given about treatment and condition • Satisfaction with general PCP communication • Meeting of expectation of method of test result communication

14. MethodsSecondary Outcome Measure • Whether a patient’s expectations were met by the method of test result communication was determined by: • Test result type: normal / abnormal • Defined as requiring follow-up or a management plan change • Method of test result receipt • Patient’s expected delivery method for test • Hierarchy of test result communication • Same Visit > Telephone > Letter > Email > Next Visit > Never • If receipt was by a more desired method, it was counted

15. MethodsData Analysis • Multivariate logistic regression models • Generalized estimating equations (SAS 9.1) • adjusted for patient age, gender, race, and insurance status • Clustered by primary care physician

16. Results Demographics

17. ResultsSurvey Administration • 1531 patients were called at least once • 706 did not answer • 20 had incorrect information • 35 had numbers that were out of service • 770 patients were successfully contacted • 128 refused • 8 had poor mentation or were too ill (self-report) • 64 requested callback but were unavailable for future contact • 570 successfully administered surveys • Response Rates: 37% / 74%

18. Results Responders vs. Non-Responders After Contact

19. Results Outcomes * Interaction term of Post & Intervention

20. Results Outcomes * Interaction term of Post & Intervention

21. Results Outcomes * Interaction term of Post & Intervention

22. Discussion • Patient Satisfaction with Overall Test Result Commutation OR ~4 • Patient Satisfaction with Diagnosis & Treatment Information OR ~4.5 • Meeting of Patient Expectations of Test Result Receipt Method OR ~3

23. Discussion • Intervention included a number of potential workflow improvements • Tracking of test results ordered by provider, and concise summary page for management • Template-based results letter generator • Can imbed actual test results into letter • Improve patient-friendly interpretations of results • One-click patient contact information

24. Discussion • Improvements in Secondary Outcomes suggested that they were significant factors in improving overall patient satisfaction • Method of Test Results Delivery More Commonly Met Patient Expectations • Patients were More Satisfied with Discussion regarding Diagnosis & Treatment relating to test results

25. DiscussionLimitations • Generalizibility • Tool custom built within an internally developed outpatient electronic health record (LMR) • Commercial vendors have been quick to adopt successful new functionality • Number and Variety of clinics should mitigate this problem as well

26. DiscussionLimitations • Survey Response Rate • Bias introduced by method of patient contact: • Distrust of Medical System or Surveyor • Poor Health, Mentation, or Hearing • SES Bias from Lack of Telephone Service • Reduced by the same bias effect across all arms

27. Conclusions • An automated management system that provides centralized test result tracking and facilitates contact with patients improved overall patient satisfaction with communication of test results • Increased patient satisfaction with the method of test results delivery and discussion of treatments/conditions suggest that the improvements in overall satisfaction found are related to these factors

28. Acknowledgements • Co-Authors • Tejal K. Gandhi, MD MPH • John Orav, PhD • Zahra Ladak-Merchant, BDS MPH • David W. Bates, MD MS • Gilad J. Kuperman, MD PhD • Eric G. Poon, MD MPH • Funding • AHRQ U18-HS-11046 • NLM T15-LM-07092

29. The End Michael Matheny, MD MS mmatheny@dsg.harvard.eduBrigham & Women’s HospitalThorn 30975 Francis StreetBoston, MA 02115