Health IT Summit in Chicago 2014 – “The EHR & Quality: The Current Evidence” with Abha Agrawal, MD, FACP, COO & VP of Medical Affairs, Norwegian American Hospital

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Health IT Summit in Chicago 2014 – “The EHR & Quality: The Current Evidence” with Abha Agrawal, MD, FACP, COO & VP of Medical Affairs, Norwegian American Hospital

Abha Agrawal, MD, FACP
COO & VP of Medical Affairs
Norwegian American Hospital

iHT2 case studies and presentations illustrate challenges, successes and various factors in the outcomes of numerous types of health IT implementations. They are interactive and dynamic sessions providing opportunity for dialogue, debate and exchanging ideas and best practices. This session will be presented by a thought leader in the provider, payer or government space.

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Health IT Summit in Chicago 2014 – “The EHR & Quality: The Current Evidence” with Abha Agrawal, MD, FACP, COO & VP of Medical Affairs, Norwegian American Hospital

  1. 1. Electronic Health Record and Quality: The Current Evidence Abha Agrawal, MD, FACP Chief Operating Officer / Chief Medical Officer Norwegian American Hospital Adjunct Associate Professor of Medicine Northwestern Feinberg School of Medicine Chicago, IL IHT2 | June 11 2014
  2. 2. Agenda • Current state of EHR adoption • EHR and quality benefits • EHR and quality risks • Socio-technical model for EHRs
  3. 3. High global EHR adoption
  4. 4. US hospitals EHR Adoption has more than tripled since 2009 http://www.healthit.gov/sites/default/files/oncdatabrief16.pdf
  5. 5. Irrefutable Benefits of EHR versus Paper • Access to information – any place, any time, multiple people • Legibility / availability of information • Security / privacy • Communication / coordination • Decision-support at the point-of-care
  6. 6. Evidence: EHR and Quality
  7. 7. Computerized Physician Order Entry (CPOE): Medication Safety 10.7 4.694.86 3.99 Serious medication errors Preventable ADEs 55% decrease 5% decrease Bates et al. JAMA. 1998; 280; 1311-16 Events/100patientdays,mean
  8. 8. 42.5 6.6 0 5 10 15 20 25 30 35 40 45 Paper Stand-alone E-Rx E-prescribing Reduces Medical Errors 85% decrease Kaushal et al. JGIM. 2010 %ofPrescriptionwithError(s)
  9. 9. 11.50% 3.10% 6.80% 1.60% 0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00% 14.00% Non-timing errors Potential ADEs Bar-coding reduces potential ADEs 41% decrease Poon et al. NEJM. 2010 51% decrease
  10. 10. EHR and Quality Benefits (Contd.) • Laboratory safety1 – Critical results notification: time to resolution 29% shorter • Smart monitoring2 – Remote monitoring in a 10-bed ICU decreased mortality by 46-68% • Hand-offs3 – Computerized sign-outs reduced adverse events risk 5-fold 1. Kuperman et al. JAMIA 2010 | 2. Rosenfeld et al. Crit Care Med 2000 | 3. Petersen et al Jt Comm Journal 1998
  11. 11. 1 0.7 0 0.2 0.4 0.6 0.8 1 1.2 Pre-EMR Post-EMR Computerized Physician Order Entry (CPOE): Inpatient Pediatric Mortality 20 % decrease Longhurst et al. Pediatrics. 2010; 126; 14-21 MeanMortalityRate
  12. 12. EHR’s Impact on Inpatient Outcomes • Cross-sectional study of urban hospitals in Texas • 41 / 72 hospitals • Level of automation measured using a questionnaire-based tool • Higher automation scores associated with fewer complications, lower mortality rates, lower costs • 10% increase in automation score = 15% decrease in adjusted odds of hospital deaths Amarasingham et al. Arch Int Med. 2009:169:108-114
  13. 13. 35.1 84.2 85.1 64.8 74.2 53 48 74.2 93 32.7 90.1 87.6 78.6 65.8 51.3 52.9 90 30 40 50 60 70 80 90 100 Paper EHR 3-13% increase EHR and Ambulatory Care Quality * p <0.001 Kern et al. JGIM. 2013
  14. 14. Impact of Patient Portals on Quality • Systematic review – Nov. 2013 • Impact on – Health outcomes - insufficient evidence – Utilization and efficiency – mixed results – Patient attitude / awareness – potential barrier – Relatively few evaluation studies available yet Goldzweig et al. Ann In Med. Nov. 2013
  15. 15. 2006 Systematic Review: Impact of HIT • Impact on Quality – Increased adherence to guideline-based care – Enhanced disease surveillance – Decreased medication errors • Impact on Efficiency – Decreased utilization e.g. redundant tests ordering – Mixed results on physician time • Cost – Inconclusive data Chaudhry et al. Ann Int Med. 2006: 144;742-752
  16. 16. 2006 Systematic Review (Contd.) • Most data from 4 benchmark institutions – Home-grown systems; highly customized – Decades of iterating, improving EHR systems – Local control, rapid improvement cycles – Strong informatics departments – Strong culture / expectation of EHR quality improvement • Raises concerns about generalizability of results • Possibly, EHR impact is institution-dependent Chaudhry et al. Ann Int Med. 2006: 144;742-752
  17. 17. Commercial / Vendor Systems • Length of improvement cycles • Little or no local control • Relative immunity from consequences / “hold harmless” clause • No reliable / centralized way of reporting users’ concerns / safety events.
  18. 18. Impact of EHR on Quality: Academic vs. Non-academic hospitals • Impact of EHR on six process measures • Two had statistically significant improvements. • Improvements were substantially greater in academic hospitals vs. non-academic – More sophisticated IT – Different culture / leadership / priorities – Different physician hospital relationship – Different training model • Possibly, EHR impact is context-dependent McCullough et al. Health Affairs. 2010:29;647-654
  19. 19. 2012 Systematic Review • Clinical decision support systems improved process measures. • Evidence for outcomes (clinical, economic, workload) sparse. • Positive results across diverse settings and diverse systems! Bright et al. Ann Int Med 2012:157;29-43
  20. 20. Office of the National Coordinator for Health IT review of 2007-2013 Health IT literature Jones SS et al. Annals of Internal Medicine January 2014 Buntin et al. Health Affairs. 2011:30;464-471 Effect of MU functionality on quality, safety, and efficiency
  21. 21. Value of IT investments: The VA Experience • Cumulative cost: $4 billion • Benefits: $7.16 billion – 65% or $4.6 billion – reducing unnecessary care – 27% or $1.9 billion – eliminating redundancies – Rest • Reduced work • Reduced operating expenses • Estimated net benefit >3 billion Byrne et al. Health Affairs 2010:29;629-638
  22. 22. EHR: Emerging Safety Concerns “an unchecked proliferation of unproven medical technology and sharp erosion of care standards.”
  23. 23. Unintended Consequences of HIT “No innovation comes without strings attached. The more technologically advanced an innovation, the more likely its introduction will produce many consequences, both anticipated and latent.”
  24. 24. Simulation Performance: CPOE Metzger et al. Health Affairs 2010;29:655-653 Post-implementation or in-vivo evaluation is important Vendor Systems % prevention of “problem” orders
  25. 25. CPOE Facilitating Medication Errors • Tertiary care teaching hospital in Pennsylvania • Qualitative research: focus groups / interviews of house officers • 22 types of NEW errors A. Information errors due to fragmentation of data B. Human-machine interface flaws Koppel et al. JAMA. 2005;293:1197-1203
  26. 26. 2.8 6.57 0 1 2 3 4 5 6 7 Pre-CPOE (13 months) Post-CPOE (5 months) Increased Neonatal Mortality After CPOE Implementation Han et al. Pediatrics. 2005;116:1506-1512 MeanMortalityRate
  27. 27. Increased Neonatal Mortality….(Contd.) • “Lost time” in care of critically ill children and delays in time-sensitive therapies – Order entry not allowed before patient physically arrived and fully registered • Reduced physician-nurse communication • No visible order flagging • Delays in medication dispensing and administration – everything is computer- dependent • Too long to place orders Han et al. Pediatrics. 2005;116:1506-1512
  28. 28. Alert Override / Fatigue • Ambulatory care, 3000 prescribers1 – 90% of DDI alerts, 77 % of drug-allergy alerts • 5 Ambulatory care practices2 – 90% of DDI and drug-allergy alerts • Review article3 – 49% to 96% - override of drug alerts 1. Isac et al . Arch Int Med. 2009 | 2.Weingart et al. Arch Int Med. 2003 | 3. van der sijs et al. JAMIA. 2006
  29. 29. EHR: Ethical and quality pitfalls • Copying and pasting • Ambiguities of authorship and timing • Templated notes • Prepopulated data • Transformation of core purpose of EHR – from information sharing for clinical care to reimbursement / regulatory requirements 1. Bernat. Neurology 2013. Ethical and quality pitfalls in electronic health records. 2. Hirschtick. JAMA 2012. John Lenon’s elbow. 3. Layman. The Health Care Manager. 2008. Ethical issues and the electronic health record.
  30. 30. Physician Satisfaction with EHRs • Physician dissatisfaction with current EHRs – Poor usability – Time-consuming data entry – Less fulfilling work content – Interference with face- face care RAND research report 2013
  31. 31. Technology meets humanity: “Bloody Crossroads”
  32. 32. EHR and Physician-patient Communication (“The Cost of Technology”) Toll | JAMA June 2012 | The Cost of technology
  33. 33. People Technology (Hardware / Software) ProcessesOrganization External Environment Socio-technical Model of HIT Health IT and Patient Safety. Institute of Medicine. 2010
  34. 34. EHR User Experience
  35. 35. EHR’s Impact on Thinking “Our writing equipment takes part in the forming of our thoughts.” - Frederick Nietzsche
  36. 36. EHR’s Impact on Thinking • EHR as “cognitive partner” –Impacts our thinking patterns. –Influences our decision making –“Effects of” and “effects with” technology Horsky and Patel. J of Biomed Inf. 2005:38;264-266
  37. 37. EHR: Moving forward • EHR user experience / usability must be evaluated / addressed. • Technology alone is not sufficient: workflow / culture /environment are critical. • Good implementation after thorough analysis • User engagement • Training • Constant evaluation • Understand and mitigate HIT-induced safety risks. Mandl et al. NEJM. 2012:366;2240-2242
  38. 38. EHRs are essential for modern medicine.
  39. 39. Thank you Abha Agrawal, MD, FACP agrawal.abha@gmail.com

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