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Impact of EHR on Quality of Care Farrokh Alemi, Ph.D.

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Presentation on theme: "Impact of EHR on Quality of Care Farrokh Alemi, Ph.D."— Presentation transcript:

1 Impact of EHR on Quality of Care Farrokh Alemi, Ph.D.

2 Objectives Review the literature Discuss the mechanism Outline future directions

3 Use of Computerized Physician Order Entry in Hospitals Studies cited in Health Information Technology in the United States: The Information Base for Progress Goal

4 Use of Computerized Physician Order Entry in Hospitals Studies cited in Health Information Technology in the United States: The Information Base for Progress Goal In some areas, 80% of Urban Hospitals Use CPOE

5 Where is the beef? Why are hospitals implementing CPOE?

6 Operational Efficiency Four Eras of IT in Health Care CQI / TQM Efficacy of Care Patient Safety Patient Financial Systems Departmental Clinical Systems Process Integration Workflow Transformation Data Integration: Patient-Centric View Clinical Decision Support – CPOE TODAY ANALYTICS & CONTINUOUS IMPROVEMENT Institute of Medicine reports Technology Infusion from Other Industries From John Cuddeback MD

7 Develop improved practiceDeploy improved practice RETROSPECTIVEReal TimeInformation Knowledge Data ANALYTICAL SYSTEMS Population Level Analytical systems are essential for integration and transformation. Analytical models, risk adjustment Ad hoc query tools—exploratory analysis, hypothesis generation/testing Comparative data, “best” practices Support for quality improvement teams Practice profile reports for clinicians POINT- OF - CARE SYSTEMS Patient Level Administrative systems (scheduling, ADT) Clinical observations, assessment, plan Orders—tied to protocols, w/ decision support Tests, results, documentation of care (eMAR) Capture outcomes, key process variables Error / near-miss reporting External Data DATA WAREHOUSES TRANSACTION SYSTEMS CLINICAL DATA REPOSITORY Improved Practice Concept or reality? From John Cuddeback MD

8 Rate of Drug Events 4031 adult admissions 11 medical and surgical units 2 tertiary care hospitals Over a 6-month period Detected by self-report Classified as ADEs or potential ADEs Bates et al., JAMA 1995;274:29-34

9 Rate of Drug Events 247 ADEs & 194 potential ADEs In 100 non-obstetrical admissions 6.5 ADEs 5.5 potential ADEs Bates et al., JAMA 1995;274:29-34

10 Rate of Drug Events Ordering 49% Transcription 11% Dispensing 14% Administration 26% 48% of errors intercepted No errors intercepted ! 23% of errors intercepted 37% of errors intercepted Bates et al., JAMA 1995;274:29-34

11 Can CPOE Reduce ADE? How exactly it will do so?

12 Rate of Errors after CPOE Before and after study Baseline & 3 subsequent years One hospital All patients Three medical units Seven to ten-week periods Bates DW, Teich JM, Lee J, Seger D, Kuperman GJ, Ma'Luf N, Boyle D, Leape L. The impact of computerized physician order entry on medication error prevention. J Am Med Inform Assoc Jul-Aug;6(4):

13 Rate of Errors after CPOE Medication errors fell 81% From 142 to 27 per 1,000 patient-days Non-intercepted serious medication errors fell 86% Bates DW, Teich JM, Lee J, Seger D, Kuperman GJ, Ma'Luf N, Boyle D, Leape L. The impact of computerized physician order entry on medication error prevention. J Am Med Inform Assoc Jul-Aug;6(4):

14 Rates of Errors after CPOE Bates DW, Teich JM, Lee J, Seger D, Kuperman GJ, Ma'Luf N, Boyle D, Leape L. The impact of computerized physician order entry on medication error prevention. J Am Med Inform Assoc Jul-Aug;6(4): months after CPOE Allergy warning system Drug-drug interaction system

15 Rates of Errors after CPOE Bates DW, Teich JM, Lee J, Seger D, Kuperman GJ, Ma'Luf N, Boyle D, Leape L. The impact of computerized physician order entry on medication error prevention. J Am Med Inform Assoc Jul-Aug;6(4): months after CPOE Allergy warning system Drug-drug interaction system Just storing and retrieving data is not much of a benefit. Analyze and use the data.

16 Medication Errors in an ICU 22-bed general ICU Sampled before and after 28 weeks before Hand Written Prescribing 2, 10, 25 and 37 weeks after CPOE Unit pharmacist recorded details of errors Shulman R, Singer M, Goldstone J, Bellingan G. Medication errors: a prospective cohort study of hand-written and computerized physician order entry in the intensive care unit. Crit Care Oct 5;9(5):R Epub 2005 Aug 8.

17 Less Medication Errors Shulman R, Singer M, Goldstone J, Bellingan G. Medication errors: a prospective cohort study of hand-written and computerized physician order entry in the intensive care unit. Crit Care Oct 5;9(5):R Epub 2005 Aug 8.

18 Types of Errors HWPCPOE Drug prescribed on incorrect drug chart section (e.g. continuous IV infusion prescribed on 'when required' part of drug chart) 2 (2.8%) 1 (0.9%) Drug needed but not given as not prescribed properly 3 (4.2%) 5 (4.3%) Inappropriate/inadequate additional information on prescription to adequately administer the drug appropriately 8 (11.3%) 12 (10.3%) Dose/units/frequency omitted on prescription 22 (31%) 1 (0.9%) Prescription not signed or change not signed/dated 10 (14.1%) 39 (33.3%)

19 Types of Errors HWPCPOE Still wrong next day after pharmacist recommended appropriate correction that was agreed with doctor 0 (0%)3 (2.6%) Dose error 12 (16.9%) 31 (26.5%) Wrong drug prescribed3 (4.2%)6 (5.1%) Incorrect route/unit5 (7%)8 (6.8%) Formulary not followed without reason3 (4.2%)1 (0.9%) Administration not in accordance with prescription 3 (4.2%)3 (2.6%) Required drug not prescribed0 (0%)7 (6%)

20 Severity of Errors Error categoryMinorModerateMajor HWP non-intercepted errors4300 CPOE non-intercepted errors9340 HWP intercepted errors7190 CPOE intercepted errors2153

21 21

22 10

23 Rise in Mortality after CPOE CPOE 13 months before 6 days implementation 5 months after Subjects Children Admitted via inter-facility transport Regional, academic, tertiary-care level children’s hospital Han, Y. Y. et al. Paediatrics 2005;116:

24 Copyright ©2005 American Academy of Pediatrics Han, Y. Y. et al. Paediatrics 2005;116: Rise in Mortality after CPOE

25 Inability to "preregister" patients (resolved) Time needed to enter orders Need for a second physician Nurses away from the bedside Changes to health care team dynamics Delays from centralization of pharmacy Han, Y. Y. et al. Paediatrics 2005;116:

26 EXAMPLE OF UNINTENDED CONSEQUENCES With antibiotic administration, subsequent dosing schedules were not timed according to the time of initial dose administration but rather at predetermined default times Han, Y. Y. et al. Paediatrics 2005;116:

27 Same Mortality after CPOE CPOE 13 months before 13 months after Subjects Tertiary care PICU 20 beds 1100 annual admissions Number of subjects 2533 children admitted 284 transported from other facilities Campbell EM, Sittig DF, Ash JS, Guappone KP, Dykstra RH. J Am Med Inform Assoc Sep-Oct;13(5):

28 Same Mortality after CPOE Total Patients Mortality, % Relative Risk95% CIP All patients – Before CPOE After CPOE Transfers – Before CPOE After CPOE Campbell EM, Sittig DF, Ash JS, Guappone KP, Dykstra RH. J Am Med Inform Assoc Sep-Oct;13(5):

29 Same Mortality after CPOE Pre-set orders 12 infant ICU-specific 16-PICU specific Extra- corporeal life support Renal replacement therapy Complex cardiac Transplant surgery Frequent orders preset Active involvement Campbell EM, Sittig DF, Ash JS, Guappone KP, Dykstra RH. J Am Med Inform Assoc Sep-Oct;13(5):

30 Same Mortality after CPOE Visiting prior implementation Active Involvement in design More order sets Pre-set completed sentences Code-set filtering Process redesign Emergency medication dispensing Pre-registering transports Continuous improvement Campbell EM, Sittig DF, Ash JS, Guappone KP, Dykstra RH. J Am Med Inform Assoc Sep-Oct;13(5):

31 EXAMPLE OF INTENDED CONSEQUENCES The first infant transported into the ICU: the resident was able to place an entire set of orders in <5 minutes without errors in a highly stressed environment Campbell EM, Sittig DF, Ash JS, Guappone KP, Dykstra RH. J Am Med Inform Assoc Sep-Oct;13(5):

32 What could go wrong? Ash JS, Berg M, Coiera E. J Am Med Inform Assoc Mar-Apr;11(2): HospitalSize (beds)CPOE System Up Since Percent Orders Entered Wishard Memorial, Indianapolis, IN 340Homegrown % Massachusetts General Hospital, Boston, MA 893Homegrown % Faulkner Hospital, Boston, MA 150Meditech200395% Brigham & Women's Hospital, Boston, MA 725Homegrown199190% Alamance Regional Medical Center, Burlington, NC 238Eclipsys199895%

33 What could go wrong? Ash JS, Berg M, Coiera E. J Am Med Inform Assoc Mar-Apr;11(2): Unintended ConsequenceFrequency (%) n = 324 More/new work for clinicians19.8 Workflow issues17.6 Never ending system demands14.8 Paper persistence10.8 Changes in communication patterns and practices 10.1 Emotions7.7 New kinds of errors7.1 Changes in the power structure6.8 Overdependence on technology5.2 Total100

34 What could go wrong? 1. More work for clinicians Slows speed of clinical documentation Recovers over time Learning to use CPOE takes time Excessive clinical alerts Research not related to care Poor integration of multiple systems 2. Unfavorable workflow issues 3. Never ending system demands 4. Problems related to paper persistence 5. Untoward changes in communication patterns and practices 6. Negative emotions 7. Generation of new kinds of errors 8. Unexpected changes in the power structure 9. Overdependence on the technology Ash JS, Berg M, Coiera E. J Am Med Inform Assoc Mar-Apr;11(2):

35 What could go wrong? 1. More work for clinicians 2. Unfavorable workflow issues Rigid modeling of work processes Fails to support all actors Simultaneous multiple orders 3. Never ending system demands 4. Problems related to paper persistence 5. Untoward changes in communication patterns and practices 6. Negative emotions 7. Generation of new kinds of errors 8. Unexpected changes in the power structure 9. Overdependence on the technology Ash JS, Berg M, Coiera E. J Am Med Inform Assoc Mar-Apr;11(2):

36 What could go wrong? 1. More work for clinicians 2. Unfavorable workflow issues 3. Never ending system demands More users require more access time More software updates Overhead in maintenance Single user exceptions for order sets Changes in practice 4. Problems related to paper persistence 5. Untoward changes in communication patterns and practices 6. Negative emotions 7. Generation of new kinds of errors 8. Unexpected changes in the power structure 9. Overdependence on the technology Ash JS, Berg M, Coiera E. J Am Med Inform Assoc Mar-Apr;11(2):

37 What could go wrong? 1. More work for clinicians 2. Unfavorable workflow issues 3. Never ending system demands 4. Problems related to paper persistence Integration with other clinical systems Temporary, handwritten data storage Paper reminders 5. Untoward changes in communication patterns and practices 6. Negative emotions 7. Generation of new kinds of errors 8. Unexpected changes in the power structure 9. Overdependence on the technology Ash JS, Berg M, Coiera E. J Am Med Inform Assoc Mar-Apr;11(2):

38 What could go wrong? 1. More work for clinicians 2. Unfavorable workflow issues 3. Never ending system demands 4. Problems related to paper persistence 5. Untoward changes in communication patterns and practices Replaces the nexus of previously interpersonal conversations Order entry may precede or remotely follow rounds 6. Negative emotions 7. Generation of new kinds of errors 8. Unexpected changes in the power structure 9. Overdependence on the technology Ash JS, Berg M, Coiera E. J Am Med Inform Assoc Mar-Apr;11(2):

39 What could go wrong? 1. More work for clinicians 2. Unfavorable workflow issues 3. Never ending system demands 4. Problems related to paper persistence 5. Untoward changes in communication patterns and practices 6. Negative emotions “At first we hated every second of it.” “This is how everyone should work.” 7. Generation of new kinds of errors 8. Unexpected changes in the power structure 9. Overdependence on the technology Ash JS, Berg M, Coiera E. J Am Med Inform Assoc Mar-Apr;11(2):

40 What could go wrong? 1. More work for clinicians 2. Unfavorable workflow issues 3. Never ending system demands 4. Problems related to paper persistence 5. Untoward changes in communication patterns and practices 6. Negative emotions 7. Generation of new kinds of errors Problematic electronic data presentations Confusing order option presentations Inappropriate text entries Misunderstandings related to production versions Workflow process mismatches 8. Unexpected changes in the power structure 9. Overdependence on the technology Ash JS, Berg M, Coiera E. J Am Med Inform Assoc Mar-Apr;11(2):

41 What could go wrong? 1. More work for clinicians 2. Unfavorable workflow issues 3. Never ending system demands 4. Problems related to paper persistence 5. Untoward changes in communication patterns and practices 6. Negative emotions 7. Generation of new kinds of errors 8. Unexpected changes in the power structure Controls on who may do what and when Physicians report loss of professional autonomy Tends to encourage centralization IT department gains in power 9. Overdependence on the technology Ash JS, Berg M, Coiera E. J Am Med Inform Assoc Mar-Apr;11(2):

42 What could go wrong? 1. More work for clinicians 2. Unfavorable workflow issues 3. Never ending system demands 4. Problems related to paper persistence 5. Untoward changes in communication patterns and practices 6. Negative emotions 7. Generation of new kinds of errors 8. Unexpected changes in the power structure 9. Overdependence on the technology System failures increasingly wreak havoc May increase access to protocols & educational materials Ash JS, Berg M, Coiera E. J Am Med Inform Assoc Mar-Apr;11(2):

43 Future CPOE systems increase Knowledge about use of system increases Lessons learned are not lost

44 Take Home Lesson Impact on Quality is Complex


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