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Presenting a Revolution in health care.

    The effective use of e-clinical data for
   Clinical Decision Making, Education and
                   Research

      MENZIES RESEARCH CENTRE HOBART
                       7th MARCH 2013
        Dr Terry J. Hannan MBBS;FRACP;FACHI;FACMI



29 March 2013
WHY DO WE NEED AN E-HEALTH
        BASED REVOLUTION?
• The current models of health care are;
  – Costly and non sustainable
  – Continue to deliver suboptimal care
  – Do not provide adequate access to care
  – Despite technology advances better outcomes do
    not always happen
  – For developing nations e-Health is “essential” for
    managing their treatable disease epidemics e.g.
    HIV/AIDS
PRESENTATION CONTENTS
• DEFINITIONS

• CURRENT HEALTH CARE DELIVERY AND RESEARCH
   • Moving from “benchtop to bedside” to ‘‘bedside to benchtop”

CURRENT ASSESSMENTS OF HEALTH CARE DELIVERY

•   Current measures of care delivery
•   Technology beneficial and problematical
•   Health care funding
•   e-health solving BIG problems world wide
•   2 short videos-making e-Health (including m-Health) work
•   Q&A
HEALTHCARE RESEARCH

To answer clinical questions

“benchtop to bedside” to “bedside to benchtop”

• Specific discoveries –yes, but,

    • Effectiveness/practice variations/CDM/Errors
    • Knowledge access

Data Capture: Manual vs. electronic

.
DEFINITIONS
         Health care is an information business

 Information is not a necessary adjunct to care, it
     is care, and effective patient management
    requires effective management of patients’
                     clinical data.
Donald M. Berwick President and CEO, Institute for Healthcare Improvement


    There is no health without management, and
   there is no management without information.
Gonzalo Vecina Neto, head of the Brazilian National Health Regulatory Agency
WHY DO WE NEED CHANGE?
               HEALTH CARE IS UNAFFORDABLE!
Fineberg HV. Shattuck Lecture. A successful and sustainable health system--how to get there from here.
                                  N Engl J Med. 2012;366(11):1020-7.




    29 March 2013
Australian Health Care System(2008)
              [The Research base]



                2005-06: ~ $87 billion 9% of GDP
                      •    3.8% in 1960-61
                        •    9.0% in 2005.
                      •    16-20% by 2045
         Australian Institute of Health and Welfare (AIHW) , Australia‟s Health (2008)
                                    http://www.ahmac.gov.a



29 March 2013
IS MORE $ ON HEALTH –CURRENT
                      MODELS?
Better
Health
                  THE ANSWER-NO
                  Individual US
                  States




Worse
Health             Less state      Less state
                   spending        spending




  29 March 2013
FAILURE TO COMPLY WITH GUIDELINES-COMMON
2011-Jha, A.K. and D.C. Classen, Getting moving on patient safety--harnessing electronic data for safer care. N Engl J Med.



More medical resources or spending more on Medicare is not
associated with more effective care.[Costs/quality/Access}




    29 March 2013
Unsupported Clinical Decision Making
                                                             RESOURCE UTILISATION-OVERUSE


                                                       Duplicate Lab Tests* by Group, BC, 2005.

                                         0.45
                                                                                                                              2003
                                          0.4
                                                                               # Duplicate Lab Tests in 2005 = 1.14M          2004
                                         0.35                                  COST = $4.55M                                  2005
        Number of Lab Tests (Millions)




                                          0.3

                                         0.25

                                          0.2

                                         0.15

                                          0.1

                                         0.05

                                           0
                                                    CVD           DM-CVD      CKD-CVD-DM        CKD-CVD   DM   CKD   DM-CKD




                                         * duplicate test defined as same test within 30 days




Dr. Adeera Levin, Director, Kidney Function Clinic, St. Paul's Hospital, University of British Columbia, Rm.
6010-A, 1081 Burrard St., Vancouver BC V6Z 1Y6; fax 604 806-8120; alevin@providencehealth.bc.ca
Technology is NOT the problem. RMRS 2012

    Regenstrief Institute: April 2012: 18 hospitals

    • >32 million physician orders entered by CPOE
    • Data base of 6 million patients
    • 900 million on-line coded results
    • 20 million reports-diagnostic studies,
      procedure results, operative notes and
      discharge summaries
    • 65 million radiology images
    • CLINICAL DECISION SUPPORT- BLINK TIMES
 29 March 2013
SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY
2000-To Err Is Human Building a Safer Health System. INSTITUTE OF MEDICINE.
2005 -Leape, L.L. and D.M. Berwick, Five years after To Err Is Human: what have we learned? JAMA.
2011- Health Information Technology Institute Of Medicine, Health IT and Patient Safety Building Safer
      Systems for Better Care, The National Academies
       Press: Washington D.C.
2011-Jha, A.K. and D.C. Classen, Getting moving on patient safety--harnessing electronic data for safer
      care. N Engl J Med.




  29 March 2013
Health care is a service business
• What clinicians deliver…
        –       advice
        –       medication
        –       devices
        –       surgery
        –       physical therapy




29 March 2013
Health care is an information business




29 March 2013
Health care is an information business
• What clinicians actually do…
      –    find information (prior records)
               “There is no healthcare without
      –    gather informationand therephysical, lab)
               management, (history, is no
      –    record information (notes,information.”
               management without reports, etc.)
      –    process information (risks/benefits → Neto
                                         Gonzalo Vecina decisions)
      –    transmit information (advice, orders, Health
                               Head, Brazilian National letters)
                                           Regulatory Agency
• The quality, efficiency, and effectiveness of care
  depend on our ability to manage information

29 March 2013   → Electronic Health Records
Patient-oriented information systems that may be found in a
clinical environment. J.Van Bemmel. MEDINFO.Seoul 1998
                                        Clinical Support Systems
                                 PACS
                               MRI                                         nuclear medicine
                              CT               Radio-      Pathology    lung function
                            DSA                Therapy                EEG
                          RIS                                       ECG

                                        Hospital     Clinical      Function
                         Radiology
                                        Pharmacy     Chemistry     Labs

             Endoscopy
                                                                               intensive care
           Hematology                                                        perinatal care
        Endocrinology          Obstetrics      Surgery      Neurology post-surgical care
     Nephrology                                                       peri-operative care
   Oncology                                                         coronary care


  Internal               Pediatrics     Cardiology    Psychiatry      Patient
  Medicine                                                            Monitoring


             Clinical Departmental Systems-
         the patient(s) journey through this maze
  29 March 2013
Overview of patient-oriented information systems that may be
   found in a clinical environment. J.Van Bemmel. MEDINFO.Seoul 1998

                                      Clinical Support Systems
                               PACS
                             MRI                                         nuclear medicine
                            CT               Radio-      Pathology    lung function
                          DSA                Therapy                EEG
                        RIS                                       ECG

                                      Hospital     Clinical      Function
                       Radiology
                                      Pharmacy     Chemistry     Labs

           Endoscopy
                                                                             intensive care
         Hematology                                                        perinatal care
      Endocrinology          Obstetrics      Surgery      Neurology post-surgical care
   Nephrology                                                       peri-operative care
 Oncology                                                         coronary care


Internal               Pediatrics     Cardiology    Psychiatry      Patient
Medicine                                                            Monitoring


                Clinical Departmental Systems-
29 March 2013
                the patient(s) journey through this maze
DATA/INFORMATION/KNOWLEDGE
          TSUNAMI




29 March 2013
29 March 2013
We are moving to a
                single worldwide A future of high-
                     It’s (Web 3.0) the data
                computer
                           all about affordable
                                   quality,
                  Apple created the depends on
                                   care
                                   innovation
                  platform (e.g., iPhone)
                  but not the apps →
                  driving innovation

29 March 2013
Patient Centered Computing-taking control/ Data sources
                  “The Wisdom of Crowds”
2015-every adult in the world will have a mobile phone-(WHO)




 29 March 2013
PubMed Searches per Month, January 1997 through September 2005

                   HUNGER FOR KNOWLEDGE
                    How much is “litter-ature”?[Ioannidis -2005]


                                            >70 million/month




          Steinbrook, R. N Engl J Med 2006;354:4-7

29 March 2013
CURRENT HEALTH DATA MEASURMENT TOOLS

• Lack of a robust measurement program

• No nationally agreed-on methods for systematically
  identifying, tracking, and reporting adverse events.

• A shortage of good patient-safety metrics

• Poor quality measures are plentiful.
   Current patient-safety indicators, which use billing data

     Poor sensitivity and specificity- their utility varies with
     hospitals‟ billing practices.[Case-Mix, DRGs, ABF]

Ashish K. Jha, David C. Classen, M.DGetting Moving on Patient Safety — Harnessing Electronic Data for
Safer Care..NEJM 365;19 NEJM.org 1756 November 10, 2011

 29 March 2013
CURRENT HEALTH DATA MEASURMENT TOOLS
                       “To improve care you have to measure it”


• Data collected in a post hoc fashion-NOT at the
  time of care
• Fail to engage clinicians at the time of care
  delivery
• Data unavailable for review until years after the
  care is delivered.


Getting Moving on Patient Safety — Harnessing ElectronicData for Safer Care Ashish K. Jha, M.D., M.P.H., and
    David C. Classen, M.D.NEJM 365;19 NEJM.org 1756 November 10, 2011
   29 March 2013
CCDSS & RESOURCE UTILISATION

 $3 million per year savings(1995)
      0
     -2
     -4                                                                  TOTAL
                                                                         BED
     -6
                                                                         TEST
     -8                                                                  DRUG
                                                    -10.5
    -10                                                                  OTHER
               -12.7 -11.9 -12.5                                         LOS
    -12
    -14                              -15.3 -15.2
    -16
Physician inpatient order writing on microcomputer workstations-effects on resource
    29 March 2013
utilisation. WM Tierney and others. JAMA 1993;269:379-383                         25
CCDSS(EHR) AND LONGITUDINAL COMPLEX CARE-1996-
                      WE KNOW WHAT WORKS
                      160,000 patient over 4 years

Overall antibiotic use:                                           decreased 22.8%
Mortality rates:                                                  decreased from 3.65% to 2.65%
Antibiotic-associated ADE:                                        decreased 30%
Antibiotic resistance:                                             remained STABLE
Appropriately timed preoperative a/biotics:                        40% to 99.1%
Antibiotic costs per treated patient:                              decreased $122.66 to $51.90
Acquisition costs for antibiotics:                                 fell 24.8% to 12.9%
                                                                         ($987,547) to ($612,500)

Our Case-Mix index which measures patient acuity levels
INCREASED during this period, meaning we were treating
sicker and sicker patients while better utilizing the delivery of
antibiotics. (******WENNBERG 2012)

Pestotnik, S. L. Classen, D. C. Evans, R. S. Burke, J. P. Implementing antibiotic practice guidelines through
computer-assisted decision support: clinical and financial outcomes.Ann Intern Med 1996 May 15
  29 March 2013
Goals of implementation.(2)
1. Eliminate logistic problems of paper record-
   clinical data timely, reliable, complete.

2. Reduce the work of clinical bookeeping-no
   more missed Dx, or forgotten preventive care.

3. Information „gold‟ within medical records
   available to clinical, epidemiological,
   outcomes and management research.
         The Regenstrief Medical Record System. IJMI 54 (1999) 225-253

29 March 2013
AIDS in Africa-2000
        How can e-Health work here?
       The Global AIDS Pandemic at a Glance-2000

• Leading infectious cause of adult death in the world
• Leading cause of death in adults aged 15–59
• 40 million persons now living with HIV/AIDS, 50% women
• >70% of HIV-infected persons living in Africa
• 14,000 new infections daily
• Sexual transmission responsible for more than 85% of
  infections
• 6 million in need of immediate treatment
• Fewer than 8% receiving it


            SOURCES: Quinn and Chaisson, 2004; WHO, 2003a,b   .
AIDS in Kenya-2000
       How can e-Health work here?
•  2.5 million persons infected (15% of adults)
  – Disease burden
• 4th behind South Africa, India, and Nigeria
  – International problem
• 1 million AIDS orphans (of 31 million citizens)
  – Social causes and outcomes
• Life expectancy has dropped 18 years in the past 5
   years, from 65 → 47 years
  – Human and economic social burdens
Face of HIV in Kenya(Africa)
50% HOSPITAL BEDS          POVERTY / EDUCATION




29 March 2013
COMMUNICATION INFRASTRUCTURES   ACCESS




 29 March 2013
20 years of medical records
Knowing there is a 14% prevalence of HIV/AIDS.
 How did we meet the health information management
                    needs here?
               Confidentiality and
                                     Historical “doctor
               communication
                                     knows it all”
               tools




                                                          Use of
Hierarchical
                                                          limited
decision
                                                          resources
making




 Bed block/
 Access
Academic collaboration-essential
          “Cannot do it alone!”
• 14-year collaboration between IU and MU
  1st 11 years → focus= educational exchange
  Kenyan request for an “EMR”
• In 2000-pre EMR
   >50% of the beds in Moi Hospital were filled
   with young people dying of AIDS
   no ARVs, few antibiotics for opportunistic
   infections
   despair, depression, resignation
Clinical Information Management-
       the report that changed HIV/AIDS in Africa!
Use of OpenMRS
(MMRS was precursor)
allowed us to manage
care in a timely manner
Clinical Information Management-
            the report that changed HIV/AIDS in Africa!

Use of OpenMRS                             Collecting this clinical
(MMRS was precursor)                       information allowed
allowed us to manage                       effective measurement of
care in a timely manner                    the AIDS epidemic and
                                           therefore the ability to
                                           manage it in the future.
Clinical Information Management-
            the report that changed HIV/AIDS in Africa!

Use of OpenMRS                             Collecting this clinical
(MMRS was precursor)                       information allowed
allowed us to manage                       effective measurement of
care in a timely manner                    the AIDS epidemic and
                                           therefore the ability to
                                           manage it in the future.
Clinical Information Management-
            the report that changed HIV/AIDS in Africa!

                                           Collecting this clinical
Use of OpenMRS            HIV and TB = 0   information allowed
(MMRS precursor)
allowed us to manage      Not measured!    effective measurement of
care in a timely manner                    the AIDS epidemic and
                                           therefore the ability to
                                           manage it in the future.
E-health and social/political change

“We have lit a candle in the darkness (of HIV/AIDS) in
Africa”. Prof. William Tierney.
                    Government response!
“This record system must be in every clinic in Kenya!”
Kenyan Gov’t response.




   29 March 2013
Musafa




        HIV is a treatable disease, but
          treating millions requires
         information management.
29 March 2013
WHY OPENMRS?
• OpenMRS was created in response to
  HIV/AIDS (millions). Indiana University School
  of Medicine had been collaborating with Moi
  University Faculty of Health Sciences (Eldoret,
  Kenya) for over a decade when their focus, by
  necessity, turned toward the HIV pandemic.
END USER INVOLVEMENT CRITICAL TO SUCCESS-CPOE
                  An innovative home-care program using
                  hand-held computers being piloted in the
                  region. Monica Korir, who is living with
                  HIV and is trained as an outreach worker




                    Outreach workers download
                    completed forms into Mosoriot clinic's
                    data management system daily.
                    Automated alerts flag any alarming
                    new symptoms/missed
                    appointments/medication compliance.
                    WHO/Evelyn Hockstein
Measuring Care-the impacts
   Effective clinical information management using OpenMRS
The Past…                            The Present…   The Impact…




              Clinical information
                  management
DESIGN GOALS OF OPENMRS
•   COLLABORATION:
•   SCALABILITY:
•   FLEXIBILITY:
•   RAPID FROM DESIGN:
•   USE OF STANDARDS:
•   SUPPORT HIGH QUALITY RESEARCH:
•   WEB-BASED AND SUPPORT INTERMITTENT
    CONNECTIVITY:
•   LOW COST:
•   CLINICALLY USEFUL: feedback to providers and
    caregivers is critical. If the system is NOT CLINICALLY
    USEFUL it will not be used.
AMPATH [Academic Model Providing Access to Healthcare] clinical and
           support programs capturing electronic data.
      ALL DISEASE STATES NOT JUST HIV/AIDS
 Adult HIV/AIDS clinics               Oncology clinics           Social worker assessments
 Pediatric HIV/AIDS clinics           Mental health clinics      Outreach – patient follow-up
 Primary care – rural health          Diabetes clinics           Drug adherence assessments
 clinics                              Tuberculosis clinics       Nutrition assessments
 Primary care – urban well-child      Clinic pharmacies          Food supplement distribution
 clinics                              Clinical laboratories      Microfinance program
 Antenatal and postnatal clinics
 Mother-baby register


AMPATH maintenance cost only $175/patient/year in 2007
    and is now less than $100/patient/year in 2009
   [dividing all direct USAID/PEPFAR funding per year by the number of patients actively
                                   receiving treatment.]


   29 March 2013
CUMULATIVE CLINICAL DATA
            AMPATH 2001-2012
•   Patients Enrolled     From ~100 to ~ 14,000 /M
•   Cumulative patients enrolled          450,000+
•   Patient visits/month              ~100->70,000
•   Cumulative patient visits           > 3,500,000
•   Clinical obs. /month             ~2.5-3 million
• Creating the Researchers “pot of
  gold”………>
Data capture in Kenya using the AMPATH record system
                  Researchers Pot of Gold




Cumulative AMRS Observations By Month: Mar ’06 – Jan ‘12
GLOBAL EXPANSION (REVOLUTION)
   The Millennium Development Goals Eight Goals for 2015
   PARTNERSHIP: Earth Institute Columbia University, UNDP,
       Millennium Promise and national governments.

1 Eradicate extreme poverty and hunger
2 Achieve universal primary education
3 Promote gender equality and empower women
4 Reduce child mortality
5 Improve maternal health
6 Combat HIV/AIDS, malaria and other diseases
7 Ensure environmental sustainability
8 Develop a global partnership for development
CORE PRINCIPLES FOR AN E-HEALTH SYSTEM

Data capture and management is critical to measuring health care

“We must remove ourselves from the ‘unscientific, non data driven
personal recommendations’ for care”. Dr M. Smith CHCF AMIA 2009



“The ability to feedback immediately to the people at the point of
care is critical for measuring and improving the quality of care.
[comparable and timely data from multiple sources/countries in
multiple languages] –requires a different kind of information
system to what exists now. “ A/Prof Andy Kanter April, 2011. Millennium
Villages Project
Features of OpenMRS –RELEVANCE TO AUSTRALIA
                       No. 1
Security:
Privilege-based access:
Patient repository:
Multiple identifiers per patient:
Data entry:
Data export:
Standards support:
Modular architecture:

 29 March 2013                           50
Features of OpenMRS –RELEVANCE TO AUSTRALIA
                    No 2.

Patient workflows:
Cohort management:
Relationships:
Patient merging:
Localization / internationalization:
Reporting tools:
Person attributes:


 29 March 2013                           51
GN for
                         AIDS
MTCT-Plus                                  Women’s &
                        Clinical
Program                                    Children’s
                         Trials
                                            Health
                        Group
                                           Research




           NHLBI
        Global Health              IeDEA
          Initiative
SCALABILITY 2000-2012 -May 2012 WHY NOT OZ?




 29 March 2013
THE SUCCESSFUL REVOLUTION.

        "Talkin' about a revolution":2009
“Now HIV/AIDS programs are not only in place but
some of them, ……(partnerships)…..(AMPATH) …are
openly speaking of bringing the pandemic to its
knees over the next 5 years through widespread
screening and effective treatment and prevention of
HIV [and other diseases] .”
Braitstein, P., et al., "Talkin' about a revolution": How electronic health records can facilitate the scale-up
of HIV care and treatment and catalyze primary care in resource-constrained settings. J Acquir Immune
Defic Syndr, 2009. 52 Suppl 1: p. S54-7.
    29 March 2013
Two YouTube videos.

1. Data capture for MDRTB in Pakistan-
   direct patient care level-mHealth-data
   transfer.

2. Population disease monitoring –based on
   concepts in movie (1) using OpenMRS
   and mHealth-macro level data-
   bidirectional use.
               • THANK YOU
 29 March 2013
                   • Q&A

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Menzies final hobart 29 feb13

  • 1. Presenting a Revolution in health care. The effective use of e-clinical data for Clinical Decision Making, Education and Research MENZIES RESEARCH CENTRE HOBART 7th MARCH 2013 Dr Terry J. Hannan MBBS;FRACP;FACHI;FACMI 29 March 2013
  • 2. WHY DO WE NEED AN E-HEALTH BASED REVOLUTION? • The current models of health care are; – Costly and non sustainable – Continue to deliver suboptimal care – Do not provide adequate access to care – Despite technology advances better outcomes do not always happen – For developing nations e-Health is “essential” for managing their treatable disease epidemics e.g. HIV/AIDS
  • 3. PRESENTATION CONTENTS • DEFINITIONS • CURRENT HEALTH CARE DELIVERY AND RESEARCH • Moving from “benchtop to bedside” to ‘‘bedside to benchtop” CURRENT ASSESSMENTS OF HEALTH CARE DELIVERY • Current measures of care delivery • Technology beneficial and problematical • Health care funding • e-health solving BIG problems world wide • 2 short videos-making e-Health (including m-Health) work • Q&A
  • 4. HEALTHCARE RESEARCH To answer clinical questions “benchtop to bedside” to “bedside to benchtop” • Specific discoveries –yes, but, • Effectiveness/practice variations/CDM/Errors • Knowledge access Data Capture: Manual vs. electronic .
  • 5. DEFINITIONS Health care is an information business Information is not a necessary adjunct to care, it is care, and effective patient management requires effective management of patients’ clinical data. Donald M. Berwick President and CEO, Institute for Healthcare Improvement There is no health without management, and there is no management without information. Gonzalo Vecina Neto, head of the Brazilian National Health Regulatory Agency
  • 6. WHY DO WE NEED CHANGE? HEALTH CARE IS UNAFFORDABLE! Fineberg HV. Shattuck Lecture. A successful and sustainable health system--how to get there from here. N Engl J Med. 2012;366(11):1020-7. 29 March 2013
  • 7. Australian Health Care System(2008) [The Research base] 2005-06: ~ $87 billion 9% of GDP • 3.8% in 1960-61 • 9.0% in 2005. • 16-20% by 2045 Australian Institute of Health and Welfare (AIHW) , Australia‟s Health (2008) http://www.ahmac.gov.a 29 March 2013
  • 8. IS MORE $ ON HEALTH –CURRENT MODELS? Better Health THE ANSWER-NO Individual US States Worse Health Less state Less state spending spending 29 March 2013
  • 9. FAILURE TO COMPLY WITH GUIDELINES-COMMON 2011-Jha, A.K. and D.C. Classen, Getting moving on patient safety--harnessing electronic data for safer care. N Engl J Med. More medical resources or spending more on Medicare is not associated with more effective care.[Costs/quality/Access} 29 March 2013
  • 10. Unsupported Clinical Decision Making RESOURCE UTILISATION-OVERUSE Duplicate Lab Tests* by Group, BC, 2005. 0.45 2003 0.4 # Duplicate Lab Tests in 2005 = 1.14M 2004 0.35 COST = $4.55M 2005 Number of Lab Tests (Millions) 0.3 0.25 0.2 0.15 0.1 0.05 0 CVD DM-CVD CKD-CVD-DM CKD-CVD DM CKD DM-CKD * duplicate test defined as same test within 30 days Dr. Adeera Levin, Director, Kidney Function Clinic, St. Paul's Hospital, University of British Columbia, Rm. 6010-A, 1081 Burrard St., Vancouver BC V6Z 1Y6; fax 604 806-8120; alevin@providencehealth.bc.ca
  • 11. Technology is NOT the problem. RMRS 2012 Regenstrief Institute: April 2012: 18 hospitals • >32 million physician orders entered by CPOE • Data base of 6 million patients • 900 million on-line coded results • 20 million reports-diagnostic studies, procedure results, operative notes and discharge summaries • 65 million radiology images • CLINICAL DECISION SUPPORT- BLINK TIMES 29 March 2013
  • 12. SLOW LEARNERS-ON QUALITY AND PATIENT SAFETY 2000-To Err Is Human Building a Safer Health System. INSTITUTE OF MEDICINE. 2005 -Leape, L.L. and D.M. Berwick, Five years after To Err Is Human: what have we learned? JAMA. 2011- Health Information Technology Institute Of Medicine, Health IT and Patient Safety Building Safer Systems for Better Care, The National Academies Press: Washington D.C. 2011-Jha, A.K. and D.C. Classen, Getting moving on patient safety--harnessing electronic data for safer care. N Engl J Med. 29 March 2013
  • 13. Health care is a service business • What clinicians deliver… – advice – medication – devices – surgery – physical therapy 29 March 2013
  • 14. Health care is an information business 29 March 2013
  • 15. Health care is an information business • What clinicians actually do… – find information (prior records) “There is no healthcare without – gather informationand therephysical, lab) management, (history, is no – record information (notes,information.” management without reports, etc.) – process information (risks/benefits → Neto Gonzalo Vecina decisions) – transmit information (advice, orders, Health Head, Brazilian National letters) Regulatory Agency • The quality, efficiency, and effectiveness of care depend on our ability to manage information 29 March 2013 → Electronic Health Records
  • 16. Patient-oriented information systems that may be found in a clinical environment. J.Van Bemmel. MEDINFO.Seoul 1998 Clinical Support Systems PACS MRI nuclear medicine CT Radio- Pathology lung function DSA Therapy EEG RIS ECG Hospital Clinical Function Radiology Pharmacy Chemistry Labs Endoscopy intensive care Hematology perinatal care Endocrinology Obstetrics Surgery Neurology post-surgical care Nephrology peri-operative care Oncology coronary care Internal Pediatrics Cardiology Psychiatry Patient Medicine Monitoring Clinical Departmental Systems- the patient(s) journey through this maze 29 March 2013
  • 17. Overview of patient-oriented information systems that may be found in a clinical environment. J.Van Bemmel. MEDINFO.Seoul 1998 Clinical Support Systems PACS MRI nuclear medicine CT Radio- Pathology lung function DSA Therapy EEG RIS ECG Hospital Clinical Function Radiology Pharmacy Chemistry Labs Endoscopy intensive care Hematology perinatal care Endocrinology Obstetrics Surgery Neurology post-surgical care Nephrology peri-operative care Oncology coronary care Internal Pediatrics Cardiology Psychiatry Patient Medicine Monitoring Clinical Departmental Systems- 29 March 2013 the patient(s) journey through this maze
  • 18. DATA/INFORMATION/KNOWLEDGE TSUNAMI 29 March 2013
  • 20. We are moving to a single worldwide A future of high- It’s (Web 3.0) the data computer all about affordable quality, Apple created the depends on care innovation platform (e.g., iPhone) but not the apps → driving innovation 29 March 2013
  • 21. Patient Centered Computing-taking control/ Data sources “The Wisdom of Crowds” 2015-every adult in the world will have a mobile phone-(WHO) 29 March 2013
  • 22. PubMed Searches per Month, January 1997 through September 2005 HUNGER FOR KNOWLEDGE How much is “litter-ature”?[Ioannidis -2005] >70 million/month Steinbrook, R. N Engl J Med 2006;354:4-7 29 March 2013
  • 23. CURRENT HEALTH DATA MEASURMENT TOOLS • Lack of a robust measurement program • No nationally agreed-on methods for systematically identifying, tracking, and reporting adverse events. • A shortage of good patient-safety metrics • Poor quality measures are plentiful. Current patient-safety indicators, which use billing data Poor sensitivity and specificity- their utility varies with hospitals‟ billing practices.[Case-Mix, DRGs, ABF] Ashish K. Jha, David C. Classen, M.DGetting Moving on Patient Safety — Harnessing Electronic Data for Safer Care..NEJM 365;19 NEJM.org 1756 November 10, 2011 29 March 2013
  • 24. CURRENT HEALTH DATA MEASURMENT TOOLS “To improve care you have to measure it” • Data collected in a post hoc fashion-NOT at the time of care • Fail to engage clinicians at the time of care delivery • Data unavailable for review until years after the care is delivered. Getting Moving on Patient Safety — Harnessing ElectronicData for Safer Care Ashish K. Jha, M.D., M.P.H., and David C. Classen, M.D.NEJM 365;19 NEJM.org 1756 November 10, 2011 29 March 2013
  • 25. CCDSS & RESOURCE UTILISATION $3 million per year savings(1995) 0 -2 -4 TOTAL BED -6 TEST -8 DRUG -10.5 -10 OTHER -12.7 -11.9 -12.5 LOS -12 -14 -15.3 -15.2 -16 Physician inpatient order writing on microcomputer workstations-effects on resource 29 March 2013 utilisation. WM Tierney and others. JAMA 1993;269:379-383 25
  • 26. CCDSS(EHR) AND LONGITUDINAL COMPLEX CARE-1996- WE KNOW WHAT WORKS 160,000 patient over 4 years Overall antibiotic use: decreased 22.8% Mortality rates: decreased from 3.65% to 2.65% Antibiotic-associated ADE: decreased 30% Antibiotic resistance: remained STABLE Appropriately timed preoperative a/biotics: 40% to 99.1% Antibiotic costs per treated patient: decreased $122.66 to $51.90 Acquisition costs for antibiotics: fell 24.8% to 12.9% ($987,547) to ($612,500) Our Case-Mix index which measures patient acuity levels INCREASED during this period, meaning we were treating sicker and sicker patients while better utilizing the delivery of antibiotics. (******WENNBERG 2012) Pestotnik, S. L. Classen, D. C. Evans, R. S. Burke, J. P. Implementing antibiotic practice guidelines through computer-assisted decision support: clinical and financial outcomes.Ann Intern Med 1996 May 15 29 March 2013
  • 27. Goals of implementation.(2) 1. Eliminate logistic problems of paper record- clinical data timely, reliable, complete. 2. Reduce the work of clinical bookeeping-no more missed Dx, or forgotten preventive care. 3. Information „gold‟ within medical records available to clinical, epidemiological, outcomes and management research. The Regenstrief Medical Record System. IJMI 54 (1999) 225-253 29 March 2013
  • 28. AIDS in Africa-2000 How can e-Health work here? The Global AIDS Pandemic at a Glance-2000 • Leading infectious cause of adult death in the world • Leading cause of death in adults aged 15–59 • 40 million persons now living with HIV/AIDS, 50% women • >70% of HIV-infected persons living in Africa • 14,000 new infections daily • Sexual transmission responsible for more than 85% of infections • 6 million in need of immediate treatment • Fewer than 8% receiving it SOURCES: Quinn and Chaisson, 2004; WHO, 2003a,b .
  • 29. AIDS in Kenya-2000 How can e-Health work here? • 2.5 million persons infected (15% of adults) – Disease burden • 4th behind South Africa, India, and Nigeria – International problem • 1 million AIDS orphans (of 31 million citizens) – Social causes and outcomes • Life expectancy has dropped 18 years in the past 5 years, from 65 → 47 years – Human and economic social burdens
  • 30. Face of HIV in Kenya(Africa) 50% HOSPITAL BEDS POVERTY / EDUCATION 29 March 2013
  • 31. COMMUNICATION INFRASTRUCTURES ACCESS 29 March 2013
  • 32. 20 years of medical records
  • 33. Knowing there is a 14% prevalence of HIV/AIDS. How did we meet the health information management needs here? Confidentiality and Historical “doctor communication knows it all” tools Use of Hierarchical limited decision resources making Bed block/ Access
  • 34. Academic collaboration-essential “Cannot do it alone!” • 14-year collaboration between IU and MU 1st 11 years → focus= educational exchange Kenyan request for an “EMR” • In 2000-pre EMR >50% of the beds in Moi Hospital were filled with young people dying of AIDS no ARVs, few antibiotics for opportunistic infections despair, depression, resignation
  • 35. Clinical Information Management- the report that changed HIV/AIDS in Africa! Use of OpenMRS (MMRS was precursor) allowed us to manage care in a timely manner
  • 36. Clinical Information Management- the report that changed HIV/AIDS in Africa! Use of OpenMRS Collecting this clinical (MMRS was precursor) information allowed allowed us to manage effective measurement of care in a timely manner the AIDS epidemic and therefore the ability to manage it in the future.
  • 37. Clinical Information Management- the report that changed HIV/AIDS in Africa! Use of OpenMRS Collecting this clinical (MMRS was precursor) information allowed allowed us to manage effective measurement of care in a timely manner the AIDS epidemic and therefore the ability to manage it in the future.
  • 38. Clinical Information Management- the report that changed HIV/AIDS in Africa! Collecting this clinical Use of OpenMRS HIV and TB = 0 information allowed (MMRS precursor) allowed us to manage Not measured! effective measurement of care in a timely manner the AIDS epidemic and therefore the ability to manage it in the future.
  • 39. E-health and social/political change “We have lit a candle in the darkness (of HIV/AIDS) in Africa”. Prof. William Tierney. Government response! “This record system must be in every clinic in Kenya!” Kenyan Gov’t response. 29 March 2013
  • 40. Musafa HIV is a treatable disease, but treating millions requires information management. 29 March 2013
  • 41. WHY OPENMRS? • OpenMRS was created in response to HIV/AIDS (millions). Indiana University School of Medicine had been collaborating with Moi University Faculty of Health Sciences (Eldoret, Kenya) for over a decade when their focus, by necessity, turned toward the HIV pandemic.
  • 42. END USER INVOLVEMENT CRITICAL TO SUCCESS-CPOE An innovative home-care program using hand-held computers being piloted in the region. Monica Korir, who is living with HIV and is trained as an outreach worker Outreach workers download completed forms into Mosoriot clinic's data management system daily. Automated alerts flag any alarming new symptoms/missed appointments/medication compliance. WHO/Evelyn Hockstein
  • 43. Measuring Care-the impacts Effective clinical information management using OpenMRS The Past… The Present… The Impact… Clinical information management
  • 44. DESIGN GOALS OF OPENMRS • COLLABORATION: • SCALABILITY: • FLEXIBILITY: • RAPID FROM DESIGN: • USE OF STANDARDS: • SUPPORT HIGH QUALITY RESEARCH: • WEB-BASED AND SUPPORT INTERMITTENT CONNECTIVITY: • LOW COST: • CLINICALLY USEFUL: feedback to providers and caregivers is critical. If the system is NOT CLINICALLY USEFUL it will not be used.
  • 45. AMPATH [Academic Model Providing Access to Healthcare] clinical and support programs capturing electronic data. ALL DISEASE STATES NOT JUST HIV/AIDS Adult HIV/AIDS clinics Oncology clinics Social worker assessments Pediatric HIV/AIDS clinics Mental health clinics Outreach – patient follow-up Primary care – rural health Diabetes clinics Drug adherence assessments clinics Tuberculosis clinics Nutrition assessments Primary care – urban well-child Clinic pharmacies Food supplement distribution clinics Clinical laboratories Microfinance program Antenatal and postnatal clinics Mother-baby register AMPATH maintenance cost only $175/patient/year in 2007 and is now less than $100/patient/year in 2009 [dividing all direct USAID/PEPFAR funding per year by the number of patients actively receiving treatment.] 29 March 2013
  • 46. CUMULATIVE CLINICAL DATA AMPATH 2001-2012 • Patients Enrolled From ~100 to ~ 14,000 /M • Cumulative patients enrolled 450,000+ • Patient visits/month ~100->70,000 • Cumulative patient visits > 3,500,000 • Clinical obs. /month ~2.5-3 million • Creating the Researchers “pot of gold”………>
  • 47. Data capture in Kenya using the AMPATH record system Researchers Pot of Gold Cumulative AMRS Observations By Month: Mar ’06 – Jan ‘12
  • 48. GLOBAL EXPANSION (REVOLUTION) The Millennium Development Goals Eight Goals for 2015 PARTNERSHIP: Earth Institute Columbia University, UNDP, Millennium Promise and national governments. 1 Eradicate extreme poverty and hunger 2 Achieve universal primary education 3 Promote gender equality and empower women 4 Reduce child mortality 5 Improve maternal health 6 Combat HIV/AIDS, malaria and other diseases 7 Ensure environmental sustainability 8 Develop a global partnership for development
  • 49. CORE PRINCIPLES FOR AN E-HEALTH SYSTEM Data capture and management is critical to measuring health care “We must remove ourselves from the ‘unscientific, non data driven personal recommendations’ for care”. Dr M. Smith CHCF AMIA 2009 “The ability to feedback immediately to the people at the point of care is critical for measuring and improving the quality of care. [comparable and timely data from multiple sources/countries in multiple languages] –requires a different kind of information system to what exists now. “ A/Prof Andy Kanter April, 2011. Millennium Villages Project
  • 50. Features of OpenMRS –RELEVANCE TO AUSTRALIA No. 1 Security: Privilege-based access: Patient repository: Multiple identifiers per patient: Data entry: Data export: Standards support: Modular architecture: 29 March 2013 50
  • 51. Features of OpenMRS –RELEVANCE TO AUSTRALIA No 2. Patient workflows: Cohort management: Relationships: Patient merging: Localization / internationalization: Reporting tools: Person attributes: 29 March 2013 51
  • 52. GN for AIDS MTCT-Plus Women’s & Clinical Program Children’s Trials Health Group Research NHLBI Global Health IeDEA Initiative
  • 53. SCALABILITY 2000-2012 -May 2012 WHY NOT OZ? 29 March 2013
  • 54. THE SUCCESSFUL REVOLUTION. "Talkin' about a revolution":2009 “Now HIV/AIDS programs are not only in place but some of them, ……(partnerships)…..(AMPATH) …are openly speaking of bringing the pandemic to its knees over the next 5 years through widespread screening and effective treatment and prevention of HIV [and other diseases] .” Braitstein, P., et al., "Talkin' about a revolution": How electronic health records can facilitate the scale-up of HIV care and treatment and catalyze primary care in resource-constrained settings. J Acquir Immune Defic Syndr, 2009. 52 Suppl 1: p. S54-7. 29 March 2013
  • 55. Two YouTube videos. 1. Data capture for MDRTB in Pakistan- direct patient care level-mHealth-data transfer. 2. Population disease monitoring –based on concepts in movie (1) using OpenMRS and mHealth-macro level data- bidirectional use. • THANK YOU 29 March 2013 • Q&A

Notes de l'éditeur

  1. OpenMRS was created in response to HIV/AIDS. Indiana University School of Medicine had been collaborating with Moi University Faculty of Health Sciences (Eldoret, Kenya) for over a decade when their focus, by necessity, turned toward the HIV pandemic.
  2. But patients like Musa, who you’ve already met, showed that HIV was a treatable disease. The problem wasn’t how to treat HIV, but how to scale that up to 100,000 and millions of patients. That kind of scale could only be obtained through effective information management.