Using IT to drive hospital outcomes

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Using IT to drive hospital outcomes

  1. 1. Emerging Technologies in eHealth: Using IT To Drive Hospital Quality Outcomes Dr Aloke Mullick, MS (Surgery) Head, Clinical Transformation Solutions OHUM, India
  2. 2. Are we using the ones that are available….. NEED FOR NEW TECHNOLOGY
  3. 3. How safe is healthcare delivery….. HEALTHCARE QUALITY
  4. 4. Healthcare quality paradigms Material • Lean inventory Management • Wastage avoidance Process • Reduced wait times Efficiency • Improved revenue cycles • Prevention outcomes Patient • Safety outcomes Outcomes • Inpatient clinical outcomes
  5. 5. How safe is healthcare delivery DANGEROUS ULTRA-SAFE (>1/1000) (<1/100K) 100,000 HealthCare Driving Total lives lost per year 10,000 1,000 Scheduled Airlines 100 Mountain Chemical European 10 Climbing Manufacturing Railroads Bungee Chartered Nuclear Jumping Flights Power 1 1 10 100 1,000 10,000 100,000 1,000,000 10,000,000 Number of encounters for each fatality Source: Berwick, D.M.
  6. 6. 1935 2009
  7. 7. The great advance…….. 1935 2009
  8. 8. The paper trail……………….. WARNING, our physicians and nurses are attempting to use antiquated manual record-keeping systems and their own limited memories in an often futile attempt to deliver a complex set of services without error. The logic of these human beings has been tested incompletely at some point in the past, but we offer no warranty expressed or implied that any individual decision made or action taken will be provably correct. Moreover, we do not know the effect of aging, distractions, overwork, and failure to communicate on the overall care you will receive. Because we do not take a systems approach to health care services, by signing this consent you agree to participate in this admittedly error- prone and potentially life-threatening activity. Courtesy: Charles Safran, MD
  9. 9. The quality chasm…. “98,000 hospital patients • “Virtually every patient die every year in the experiences a gap between US alone because of the best evidence and the adverse events” care they receive” Institute of Medicine, 1999 – Institute of Medicine, 2001
  10. 10. The call Create systems of care that are safe, timely, efficient, effective, equitable, and patient-centered. Institute of Medicine
  11. 11. The three supports of an effective clinical IT system Safe: CPOE reduces errors in drug prescribing and dosing Effective: Patient Automated centered: reminder systems, Enhanced CDSS systems to information improve access and compliance with communication clinical guidelines for patients
  12. 12. Key IT drivers of healthcare quality IT ENABLED QUALITY HEALTHCARE
  13. 13. Case for CPOE CPOE can reduce prescription CPOE Systems by errors by up to 70% reducing medication errors, Leap Frog Group can pay for themselves in 26 months Massachusetts Tech Collaborative and New England Healthcare Institute
  14. 14. Case for CDSS 20,000 biomedical journals 500,000 indexed in PubMed annually >150,000 articles per month 6,000 articles a day Medical References Services Quarterly 2007;26:1-19
  15. 15. More Data Over Genomics the Last 3 Years Digital Pathology Than Previous Digital Radiology 40,000 years Combined E-Health Initiatives/Linkages 40,000 BCE Electronic Medical Record cave paintings bone tools 3500 writing 0 C.E. Digital Cardiology paper 105 1450 printing 1870 electricity, telephone transistor 1947 computing 1950 Late 1960s 1993 The Web 1999 2009 Source: UC Berkeley, School of Information Management and Systems.
  16. 16. Doctors struggling to cope •Finish medical school and residency knowing everything Read and retain 2 articles • every single night •At the end of 1st year 1,225 years behind W Stead. JAMIA 2005;12:113-20 , Alper BS, Hand JA, Elliott SG, et al. J Med Libr Assoc 2004;92:429-37.
  17. 17. Clinical Reminders Clinical requirements Dia betes Pa tient Dialog for processing multiple reminders: • Diabe tic Foot Care Education • Diabe tic Foot Exam • Diabe tic Eye Exam • Recommende d Labs • Other Health Activities Acquisition of health da ta be yond care delivere d exclusively thr ough VHA Standardized Da ta Elements
  18. 18. Order sets
  19. 19. Bar coded medication administration • Right Medication • Right Dose • Right Route • Right Patient • Right Provider • Right Time
  20. 20. EBM guidelines and real time Decision Support at the point of care EVIDENCE BASED MEDICINE
  21. 21. - XML-format - Indexed with MeSH (Snomed CT), ICD-10 -, ATC- and Lab-codes
  22. 22. EBM at the POC
  23. 23. DS Engine: reports Interaction of Glitazone With Insulin, and Contraindication in heart failure
  24. 24. Real time clinical IT Other Inputs EBM Guidelines Patient Safety Measures Decision Inpatient Quality Measures Support Real-time Clinical Status Effectors Alerts CIS/CPOE CDR Prompts/Reminders Order Sets Clinical System Templated care plans Normalization, Transformation, Patient alerts Analytic Application Lab Pharmacy Imaging
  25. 25. Prevention, Safety, Inpatient Outcomes THE QUALITY PARADIGM
  26. 26. The Core performance measures • Ambulatory care Prevention conditions • Immunizations • Iatrogenic conditions Safety • Post-op complications Inpatient • Disease mortality • Procedure Rx Quality mortality
  27. 27. Prevention indicators o Bacterial pneumonia • Hypertension Cx – Dehydration • Adult asthma Cx – Pediatric gastroenteritis • Pediatric asthma Cx – Urinary tract infection • COPD Cx – Perforated appendix • Diabetes Cx - short term – Low birth weight • Diabetes Cx - long term – Angina without procedure • Uncontrolled diabetes – Congestive heart failure • Lower extremity amputation
  28. 28. Safety indicators – Complications of anesthesia – Death in low mortality DRGs – Decubitus ulcer – Foreign body left during procedure – Iatrogenic pneumothorax – Infections due to medical care – Postoperative hemorrhage or hematoma – Postoperative hip fracture – Postoperative physiological and metabolic derangement – Postoperative PE or DVT – Postoperative sepsis – Obstetric trauma to mother and neonate
  29. 29. Inpatient Rx quality indicators  Mortality Indicators for Inpatient  Mortality Indicators for Conditions Inpatient Procedures – Acute myocardial infarction – Angioplasty – Congestive heart failure – CABG – Gastrointestinal hemorrhage – Craniotomy – Hip fracture – Esophageal resection – Pneumonia – Hip replacement – Acute stroke – Pancreatic resection – Malaria – Colonic resection – Gastroenteritis – Pediatric heart surgery
  30. 30. The quality grid Patient Effectiveness Safety Timeliness Centeredness Preventive Curative Rehabilitation Terminal Care Source: Institute of Medicine, 2001.
  31. 31. Actual results after clinical IT implementation Inpatient Mortality 2.10% 2.05% 2.05% 2.00% Clean Surgery Infection Rate 1.95% 5.00% Percent 4.72% 1.90% 4.50% 1.85% 1.83% 4.00% 1.80% 3.50% 1.75% Percent 3.00% 2.50% 1.70% Jul 2003-Sep 2005 Feb 2007-Feb 2008 2.00% Time Period 1.43% 1.50% 1.00% 0.50% 0.00% Jan-Sep 2005 Feb 2007-Feb 2008 Courtesy: Midland Memorial, Tx Time Period
  32. 32. The difference was technology Follow up 100 90 VA Treatment Non VA 80 Screening 70 Diagnosis 60 Hypertension 50 Hyperlipidemia 40 Diabetes 30 CAD 20 10 Chronic Care 0 Non VA VA 0 50 100 In patient Out patient No 1 in 33 out of 45 core performance No 1 in patient satisfaction 3 years in a row measures amongst ALL US hospitals Rand study
  33. 33. Where do we stand……. Medical record fully electronic: Stage 7 Data interoperability 0.3% 0 Physician documentation (structured templates), Stage 6 full CDSS (variance & compliance), Full PACS 0.5% 0 Stage 5 Closed loop medication administration 2.5% 0 Stage 4 Computerized Provider Order Entry 2.5% 0 Stage 3 Nursing Clinical documentation (flow sheets), 35.7% 0 CDSS (error checking) PACS (Radiology) Stage 2 CDR, CMV, CDSS inference engine, 31.4% 0.7% Stage 1 AncillariesLab, Radiology, Pharmacy 11.5% 18.3% Stage 0 All three ancillaries not installed 15.6% 80% Adapted from HIMSS Analytics USA India
  34. 34. What Governments can and should do……… POLICY INITIATIVES
  35. 35. United States • 98000 Americans die of medical errors per year 2004 • Nearly 70 billion USD committed for e-health • Only 1.5% private US • E-prescription act under ARRA, with hospitals use (MMA) meaningful use comprehensive EHRs • Barcodes on most provisions in place prescription drugs • Goal for every hospital to have EHRs by 2014 2001 2009
  36. 36. United Kingdom 20 billion USD NPfIT Largest civilian IT program in the world National data ‘Spine’ in PACS live in place all clusters Phased EHR Expected to Choose and deployment be fully live book live in progress by 2015
  37. 37. Mexico Complete national VistA indigenized to medical record system include local work-flows based on the VA VistA and Spanish language system capability VistA based More than 50% public Program completely run hospitals live on the by Mexican resources VistA EHR
  38. 38. The funding problem in health IT USD 2500 2350 2000 • Per capita healthcare spend 1500 in bottom 20% is 2% of top 1000 850 5% nations USD 500 370 50 170 0 20% 40% 60% 80% 95% USD 95% 90 • Per capita health IT spend 80% 35 in bottom 20% is so low, 60% 10 that the requirement to use 40% 3 USD the right solutions for maximum gain is even 20% 0.5 greater 0 50 100
  39. 39. What our policy makers should do….. Mandate Mandate e- usage of ordering of ICD-10PCS labs and by all e- imaging health systems Mandate Mandate bar publishing of coding for all core prescription performance drugs measures Mandate e- Support prescribing formation of and e- corporate pressure groups medicine like ‘leap-frog’ administration
  40. 40. Its never that simple….. PITFALLS
  41. 41. Automation may go awry too….  To err is human.  To really screw things up takes a computer. – Anon.
  42. 42. The poorly maintained decision support  Where do guidelines come from?  Are they consistent with evidence?  Are they current and valid?  Who updates them?  Are there regular audits?  Would anyone know, if there were a malfunction?
  43. 43. CPOE as a source of error  In one tertiary, academic medical center, using a mature, commercially available system: – 22 different types of failures were facilitated by using the system – Errors occurred several times a week, if not daily – All errors were traced to improper system setup, and less than adequate training of user staff Koppel, et al., 2005. JAMA, 293(10): 1197-1203.
  44. 44. Hardware and networks for high demand systems  If not carefully secured, your wireless network may leave you exposed... Courtesy: Colorado Patient Safety
  45. 45. An idea for every one… 18 Big ideas To Fix Healthcare NOW Idea No 13: Clinical Information Systems One model which works is the VistA system, which has been keeping the records of over 7 million vets since 1996. Why not just use VistA nationwide? Readers' Digest: Nov, 2008
  46. 46. Questions in the end please………….. THANK YOU

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