Michael E. Matheny, MD MS Biomedical Informatics Fellow Brigham & Women’s Hospital, Boston, MA

1. Impact of an Automated Test Results Management System on Patients’ Satisfaction of Test Result Communication Michael E. Matheny, MD MS Biomedical Informatics Fellow Brigham & Women’s Hospital, Boston, MA

2. Lexington, KY • University of Kentucky • Chemical Engineering Undergraduate • Medical School

3. Indianapolis, IN • Internal Medicine Residency • St. Vincent Hospital

4. Boston, MA • Massachusetts Institute of Technology • Master of Science Biomedical Informatics • Biomedical Informatics Fellowship • NLM Fellow • Harvard-MIT Health Sciences & Technology • Outpatient Urgent Care • Brigham & Women’s Hospital

5. This Study • Strong interest in applying clinical decision support to improve patient safety • Clinical Reminders • Test Results Management • AHRQ Grant (David Bates) • Results Manager Intervention (Eric Poon)

6. 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

7. BackgroundTest Result Communication Problems • 31% of women with abnormal mammograms did not receive care consistent with established guidelines • 39% of abnormal TSH at BWH were not followed up within 60 days • 36% of abnormal pap smear were lost to follow-up

8. BackgroundPhysician Workflow • 33% of physicians reported they did not always notify patients of abnormal test results • ~30% of physicians reported they did not have a reliable method of test result communication • 59% of physicians were dissatisfied with how well they managed test results despite spending over an hour a day in this activity

9. BackgroundPatient Expectations • Patients do not normally discuss their preferences for test result notification with their providers • Patients preferred telephone notification to regular mail, and found electronic notification to be uncomfortable due to security issues • Patients wanted to be notified of all test results, regardless of whether the results were abnormal

10. 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

11. BackgroundCurrent IT Environment • Increasing numbers of practices are implementing electronic health records in order to improve documentation, billing, and for the promise of improved patient care • While test result viewer applications are available in most commercial and home-grown EHRs, they typically require clinicians to separately keep track of their pending tests, and individually check a patient’s chart for the result

12. BackgroundCurrent IT Environment • A few institutions have implemented automated test result notification systems to physicians, but these systems have generally been deployed only in the inpatient setting for critically abnormal results • The follow-up workflow in the outpatient setting is very different because patients are not in a controlled environment, which presents both communication and compliance barriers

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

14. 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)

15. MethodsLMR Summary Screen

16. 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

17. MethodsPatient Test Results Screen

18. 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

19. MethodsResults Manager Summary Screen

20. MethodsResults Manager Letter Generation Screen

21. MethodsStudy Design

22. MethodsEnrollment • Power Calculations • Two independent proportions • 90% Power • 75% to 90% Proportion Change in Overall Satisfaction • 133 patient encounters in each arm • 150 selected as target enrollment

23. MethodsRandomization • 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 • Rolling implementation of Results Manager for intervention clinics was completed by March, 2004

24. MethodsStudy Criteria • Patients were randomly sampled during eligible pre and post intervention time periods • 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

25. MethodsData Collection • Telephone Administration of Survey • Internally developed survey • Trained research assistants • Administered 5 to 7 weeks after test result posting date • Up to three attempts were made to contact each patient

26. MethodsSurvey • Outcomes (except expectations) were measured by the Likert scale: • Strongly Agree • Agree • Neither Agree nor Disagree • Disagree • Strongly Disagree • All results were dichotomized

27. MethodsSurvey • Primary Outcome Measure • Overall satisfaction with test result communication • “I am satisfied with the way test results are communicated to me”

28. MethodsSurvey • Secondary Outcome Measures • Satisfaction with PCP listening skills • “My primary care doctor always listens to my concerns” • Satisfaction with information given about treatment and condition • “My primary care doctor gives me as much information about my condition and treatment as I wanted” • Satisfaction with general PCP communication • “My primary care doctor and I communicate very well”

29. 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

30. MethodsData Analysis • Multivariate logistic regression models • Generalized estimating equations (SAS 9.1) • Clustered by primary care physician • Adjusted for Patient • Age • Gender • Race • Insurance status • Self-reported health

31. MethodsData Analysis • Use of interaction term in this study design • There were 4 study groups • Multiplicative interaction term of (Pre/Post) * (Control/Intervention) can be interpreted as the relative change in outcome between comparison groups from the baseline to the follow-up evaluation • Pre/Post • Control/Intervention • Post*Intervention • Reported as a p value only • Odds Ratios are reported for both the Control arm and for the Intervention arm after full adjustment

32. Methods • Intention-to-treat analysis: All physicians from intervention practices were considered to be in the intervention arm regardless of RM use

33. Results Demographics

34. Results Enrollment

35. Results Demographics

36. ResultsSurvey Administration • 1531 attempted to be contacted • 20 had incorrect information • 35 had numbers that were out of service • 706 did not answer • 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 Rate: 37% (570/1531)

37. Results Responders vs. Non-Responders

38. Results Primary Outcome

39. Results Secondary Outcome

40. Results Secondary Outcome

41. Results Secondary Outcome

42. Results Secondary Outcome

43. Discussion • Outcomes improved with Intervention • Patient Satisfaction with Overall Test Result Commutation • Patient Satisfaction with Diagnosis & Treatment Information

44. 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

45. Discussion • Improvements in satisfaction with discussion of diagnosis & treatment suggested that it was a significant factor in improving overall patient satisfaction

46. 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

47. DiscussionLimitations • Telephone Survey Bias • Method of patient contact bias • Distrust of Medical System or Surveyor • Poor Health, Mentation, or Hearing • SES Bias from Lack of Telephone Service • Should be the same bias effect across all arms • Response Rate • Clear differences between responders and non-responders • Likely inflate satisfaction in each of the measurements (for both arms)

48. 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 discussion of treatments/conditions

49. 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

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