Electronic Health Record and
Quality:
The Current Evidence
Abha Agrawal, MD, FACP
COO / CMO
Norwegian American Hospital
Ch...
Agenda
•
•
•
•

Current state of EHR adoption
EHR and quality benefits
EHR and quality risks
Socio-technical model for EHR...
High global EHR adoption
US hospitals EHR Adoption has more
than tripled since 2009

http://www.healthit.gov/sites/default/files/oncdatabrief9final...
EHR adoption to date - ONC
• Registered Users
– Ambulatory - 419,542
– Hospitals – 4,569

• Payments
– $6 billion to ambul...
Irrefutable Benefits of EHR versus
Paper
• Access to information – any place, any time,
multiple people
• Legibility / ava...
Evidence: EHR and Quality
Computerized Physician Order Entry
(CPOE): Medication Safety
Events / 100 patient days, mean

55% decrease
10.7

5% decrea...
E-prescribing Reduces Medical Errors
45

% of Prescription with Error(s)

40

42.5

35

85% decrease

30
25
20
15
10

5

6...
Bar-coding reduces potential ADEs
14.00%

41% decrease
12.00%

11.50%
10.00%

8.00%

6.00%

6.80%

51% decrease

4.00%

3....
EHR and Quality Benefits (Contd.)
• Laboratory safety1
– Critical results notification: time to resolution 29%
shorter

• ...
Computerized Physician Order Entry
(CPOE): Inpatient Pediatric Mortality
20 % decrease

1.2

Mean Mortality Rate

1

1

0....
EHR’s Impact on Inpatient Outcomes
• Cross-sectional study of urban hospitals in Texas
• 41 / 72 hospitals
• Level of auto...
EHR and Ambulatory Care Quality
3-13% increase

100

90

90.1

84.2

80

93
87.6
85.1
78.6
74.2

70

74.2

65.8

64.8

60
...
2006 Systematic Review: Impact of HIT
• Impact on Quality
– Increased adherence to guideline-based care
– Enhanced disease...
2006 Systematic Review (Contd.)
• Most data from 4 benchmark institutions
–
–
–
–
–

Home-grown systems; highly customized...
Commercial / Vendor Systems
• Length of improvement cycles
• Little or no local control
• Relative immunity from consequen...
Impact of EHR on Quality: Academic vs.
Non-academic hospitals
• Impact of EHR on six process measures
• Two had statistica...
2012 Systematic Review
• Clinical decision support systems improved
process measures.
• Evidence for outcomes
(clinical, e...
Value of IT investments: The VA
Experience
• Cumulative cost: $4 billion
• Benefits: $7.16 billion
– 65% or $4.6 billion –...
EHR and Quality: The VA Experience

Byrne et al. Health Affairs 2010:29;629-638
92% of the Articles on HIT Show
Positive Results

Buntin et al. Health Affairs. 2011:30;464-471
EHR: Emerging Safety Concerns
Unintended Consequences of HIT
“No innovation comes
without strings attached.
The more technologically
advanced an
innovat...
Simulation Performance: CPOE

% prevention of
“problem” orders
Post-implementation

or in-vivo
evaluation is important
Ven...
CPOE Facilitating Medication Errors
• Tertiary care teaching hospital in Pennsylvania
• Qualitative research: focus groups...
Increased Neonatal Mortality After
CPOE Implementation
7

6.57

Mean Mortality Rate

6

5

4

3

2.8

2

1

0

Pre-CPOE (1...
Increased Neonatal
Mortality….(Contd.)
• “Lost time” in care of critically ill children and
delays in time-sensitive thera...
Alert Override / Fatigue
• Ambulatory care, 3000 prescribers1
– 90% of DDI alerts, 77 % of drug-allergy alerts

• 5 Ambula...
EHR: Safety Concern
ACP Ethics Case Studies
Physician Satisfaction with EHRs
• Physician dissatisfaction
with current EHRs
– Poor usability
– Time-consuming data
entr...
Socio-technical Model of HIT
People

External
Environment

Organization

Technology
(Hardware /
Software)

Processes
Healt...
Technology meets humanity: “Bloody
Crossroads”
EHR User Experience
EHR’s Impact on Thinking
“Our writing equipment
takes part in the forming of
our thoughts.”
- Frederick Nietzsche
EHR’s Impact on Thinking
• EHR as “cognitive partner”
–Impacts our thinking patterns.
–Influences our decision making
–“Ef...
EHR: Moving forward
• EHR user experience / usability must be
evaluated / addressed.
• Technology alone is not sufficient:...
EHRs are essential for modern medicine.
Thank you
Abha Agrawal, MD, FACP
agrawal.abha@gmail.com
iHT² Health IT Summit Beverly Hills – Case Study "The EHR & Quality: The Current Evidence" Abha Agrawal, MD, FACP, COO & V...
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iHT² Health IT Summit Beverly Hills – Case Study "The EHR & Quality: The Current Evidence" Abha Agrawal, MD, FACP, COO & VP of Medical Affairs, Norwegian American Hospital

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iHT² Health IT Summit Beverly Hills – Case Study "The EHR & Quality: The Current Evidence" Abha Agrawal, MD, FACP, COO & VP of Medical Affairs, Norwegian American Hospital

Case Study "The EHR & Quality: The Current Evidence"

∙ Understand where EHRs have demonstrated evidence based quality improvement
∙ Learn what areas for improvement exist to improve quality and physician productivity
∙ Discuss how results can be driven across diverse care settings and systems
∙ Identify unintended consequences of HIT

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  • What are some key driversWhere do we stand nowMost important – with so much momentum, policy discussion, money spent – both government money and private money, what is the evidence – a critical look at the literatureConclusions / where do we go from here..AND TAKE HOME POINTS
  • So with EHR usage increasing; with a lot of investment being made both by the govt and private sector – it is important for us to step back and review the evidence regarding EHR on quality. Just a bit of caution…As we go through the evidence, you will perhaps feel this way..
  • Background: Implementations of computerized physician order entry (CPOE) systems have previously been associated with either an increase or no change in hospital-wide mortality rates of inpatients. Despite widespread enthusiasm for CPOE as a tool to help transform quality and patient safety, no published studies to date have associated CPOE implementation with significant reductions in hospital-wide mortality rates.Objective: The objective of this study was to determine the effect on the hospital-wide mortality rate after implementation of CPOE at an academic children's hospital.Patients and Methods: We performed a cohort study with historical controls at a 303-bed, freestanding, quaternary care academic children's hospital. All nonobstetric inpatients admitted between January 1, 2001, and April 30, 2009, were included. A total of 80063 patient discharges were evaluated before the intervention (before November 1, 2007), and 17432 patient discharges were evaluated after the intervention (on or after November 1, 2007). On November 4, 2007, the hospital implemented locally modified functionality within a commercially sold electronic medical record to support CPOE and electronic nursing documentation.Results: After CPOE implementation, the mean monthly adjusted mortality rate decreased by 20% (1.008–0.716 deaths per 100 discharges per month unadjusted [95% confidence interval: 0.8%–40%]; P = .03). With observed versus expected mortality-rate estimates, these data suggest that our CPOE implementation could have resulted in 36 fewer deaths over the 18-month postimplementation time frame.
  • Background: Implementations of computerized physician order entry (CPOE) systems have previously been associated with either an increase or no change in hospital-wide mortality rates of inpatients. Despite widespread enthusiasm for CPOE as a tool to help transform quality and patient safety, no published studies to date have associated CPOE implementation with significant reductions in hospital-wide mortality rates.Objective: The objective of this study was to determine the effect on the hospital-wide mortality rate after implementation of CPOE at an academic children's hospital.Patients and Methods: We performed a cohort study with historical controls at a 303-bed, freestanding, quaternary care academic children's hospital. All nonobstetric inpatients admitted between January 1, 2001, and April 30, 2009, were included. A total of 80063 patient discharges were evaluated before the intervention (before November 1, 2007), and 17432 patient discharges were evaluated after the intervention (on or after November 1, 2007). On November 4, 2007, the hospital implemented locally modified functionality within a commercially sold electronic medical record to support CPOE and electronic nursing documentation.Results: After CPOE implementation, the mean monthly adjusted mortality rate decreased by 20% (1.008–0.716 deaths per 100 discharges per month unadjusted [95% confidence interval: 0.8%–40%]; P = .03). With observed versus expected mortality-rate estimates, these data suggest that our CPOE implementation could have resulted in 36 fewer deaths over the 18-month postimplementation time frame.
  • Background: Implementations of computerized physician order entry (CPOE) systems have previously been associated with either an increase or no change in hospital-wide mortality rates of inpatients. Despite widespread enthusiasm for CPOE as a tool to help transform quality and patient safety, no published studies to date have associated CPOE implementation with significant reductions in hospital-wide mortality rates.Objective: The objective of this study was to determine the effect on the hospital-wide mortality rate after implementation of CPOE at an academic children's hospital.Patients and Methods: We performed a cohort study with historical controls at a 303-bed, freestanding, quaternary care academic children's hospital. All nonobstetric inpatients admitted between January 1, 2001, and April 30, 2009, were included. A total of 80063 patient discharges were evaluated before the intervention (before November 1, 2007), and 17432 patient discharges were evaluated after the intervention (on or after November 1, 2007). On November 4, 2007, the hospital implemented locally modified functionality within a commercially sold electronic medical record to support CPOE and electronic nursing documentation.Results: After CPOE implementation, the mean monthly adjusted mortality rate decreased by 20% (1.008–0.716 deaths per 100 discharges per month unadjusted [95% confidence interval: 0.8%–40%]; P = .03). With observed versus expected mortality-rate estimates, these data suggest that our CPOE implementation could have resulted in 36 fewer deaths over the 18-month postimplementation time frame.
  • Let us keep this in mind. I will return to this concern that it is not just the technology but the environement, the institution in which technology is being used is very important. Let us look at one more study along these lines. Then we go to the systematic review….
  • We will talk about this a bit more..but the truth is that almost all places now will have commercial systems. Partners I understood is also switching to a commercial system…To be sure: Kaiser has reported some substantial results with a vendor system….But again they have the culture, the economy of scale etc…
  • This begins to truly raise concerns…Let me share with you one more study here…Ultimately, we focused on six process-qualitymeasures. These included the percentage of heart failure patients given ACE) inhibitor or angiotensinII receptor blocker (ARB) for left ventricularsystolic dysfunction; the percentage ofsmokers with heart failure and pneumonia, respectively,who were given smoking cessationadvice; the percentage of pneumonia patients assessed and given pneumococcal vaccination ifindicated; the percentage of pneumonia patientswhose initial blood culture in the emergency departmentpreceded their first dose of hospital administeredantibiotics; and the percentage ofpneumonia patients given the most appropriateinitial antibiotic.Pneumonia vaccination and more appropriate ABC improved…
  • Process measuresOrdering recommended preventive studyOrdering recommended clinical studyOrdering recommended therapiesClinical Outcomes – LOS, morbidity, mortalityWorkload – no of patients seen per unit of time, pt / provider satisfaction
  • Perhaps one of the best studies showing cost..Reducing unnecessary careAdverse events / readmission / reduced outpatient visitsEliminating redundanciesReduced medication errorsReduced duplicate testingAs you would understand, it is a different system. Economy of scale. Command and control.
  • This could be among the last few slides: conclusions..
  • Toward the end, we will summarize some key conclusions and common themes..Let me add another dimensions to the impact of EHRs..which is EHR impact on safety..
  • GIVE ANOTHER – POSSIBLY HUFF POST ARTICLE PRINT OUT…
  • Caused quite an uproar…Information errors:Discontinuation errorsStat / next scheduled doseDiluent options and errorsUnavailability of medications on other systemsToo many alerts / alert fatigueHuman machine interface errorsToo easy to select the wrong patientBulky non-intuitive slection screen – easy to get confusedToo many clicks – busy houseofficers – need to get the work done. – delaying in orderingInflexible chartingI have seen almost everyone of these in system at KCHC. Perhaps many in the audience will be familiar with seeing these errors..
  • Academic, tertiary care Children’s HospitalCommercial CPOE program for general med-surgRapidly implemented in NICU over 6 daysRetrospective analysis of pre-CPOE (13 months) and post-CPOE (5 months) mortalityPre-CPOE: 2.80 % (39/1394)Post-CPOE: 6.57% (36/548)Multivariate analysis: CPOE independently associated with increased odds of mortality (odds ratio: 3.28)After CPOEimplementation, order entry was not allowed untilafter the patient had physically arrived to the hospitaland been fully registered into the system, leadingto potential delays in new therapies and diagnostictesting (this policy later was rectified).The physicalprocess of entering stabilization orders often requiredan average of ten “clicks” on the computermouse per order, which translated to 1 to 2minutesper single order as compared with a few seconds previously needed to place the same order by writtenform. Because the vast majority of computer terminalswere linked to the hospital computer system viawireless signal, communication bandwidth was oftenexceeded during peak operational periods, whichcreated additional delays between each click on thecomputer mouse. Sometimes the computer screenseemed “frozen.”Before CPOE implementation, the physician expressedan intended order either through direct oralcommunication or by writing it at the patient’s bedside(often reinforced with direct oral communication),with the latter giving the nurse a visual cuethat a new order had been placed. The nurse had theopportunity to provide immediate feedback, whichsometimes resulted in a necessary revision of thatorder. In addition, these face-to-face interactions oftenfostered discussions that were relevant to patientcare and management. After CPOE implementation,because order entry and activation occurred througha computer interface, often separated by several bedspaces or separate ICU pods, the opportunities forsuch face-to-face physician–nurse communicationwere diminished
  • After CPOEimplementation, order entry was not allowed untilafter the patient had physically arrived to the hospitaland been fully registered into the system, leadingto potential delays in new therapies and diagnostictesting (this policy later was rectified).The physicalprocess of entering stabilization orders often requiredan average of ten “clicks” on the computermouse per order, which translated to 1 to 2minutesper single order as compared with a few seconds previously needed to place the same order by writtenform. Because the vast majority of computer terminalswere linked to the hospital computer system viawireless signal, communication bandwidth was oftenexceeded during peak operational periods, whichcreated additional delays between each click on thecomputer mouse. Sometimes the computer screenseemed “frozen.”Before CPOE implementation, the physician expressedan intended order either through direct oralcommunication or by writing it at the patient’s bedside(often reinforced with direct oral communication),with the latter giving the nurse a visual cuethat a new order had been placed. The nurse had theopportunity to provide immediate feedback, whichsometimes resulted in a necessary revision of thatorder. In addition, these face-to-face interactions oftenfostered discussions that were relevant to patientcare and management. After CPOE implementation,because order entry and activation occurred througha computer interface, often separated by several bedspaces or separate ICU pods, the opportunities forsuch face-to-face physician–nurse communicationwere diminished
  • NOTE BLOATCLONED NOTES“where is waldo?” you need to find that one single line that will give you an idea of a clinically relevant development in the patient’s condition and care..you need to look through pages after pages..Recombinant notes
  • Poor EHR usability, time-consuming data entry, interference with face-to-face patient care, ineffcient and less fulfilling workcontent, inability to exchange health information between EHR products, and degradationof clinical documentation were prominent sources of professional dissatisfaction.Some of these problems were more prominent among senior physicians and those lackingscribes, transcriptionists, and other staff to support data entry or manage informationflow. Physicians across the full range of specialties and practice models described otherproblems, including but not limited to frustrations with receiving template-generatednotes (i.e., degradation of clinical documentation). In addition, EHRs have been moreexpensive than anticipated for some practices, threatening practice financial sustainability.Some practices reported taking steps to address the causes of physician dissatisfactionwith EHRs. These steps were, most commonly, to allow multiple modes of data entry(including scribes and dictation with human transcriptionists) and to employ other staffmembers (e.g., flow managers) to help physicians focus their interactions with EHRs onactivities truly requiring a physician’s training.
  • So what is going on. HIT is good; it doesn’t do much. It depends where you are; it depends how you do it; it depends who uses it..etc..etc..
  • We have looked at EHRs impact on quality, safety, quantitative measures
  • We have looked at EHRs impact on quality, safety, quantitative measures
  • Surely Dr. Friedman will like it. Like all other grand rounds presenters; I received an incredibly informative session on the proper use of color, font etc for effective presentation of information. If it is true in an hour of grand rounds learning…Still can’t perform a simple google like search even in the more advanced systemsHHC – cost over 300 million dollars..close to 1.2 billion dollars – this is public information
  • Surely Dr. Friedman will like it. Like all other grand rounds presenters; I received an incredibly informative session on the proper use of color, font etc for effective presentation of information. If it is true in an hour of grand rounds learning…Still can’t perform a simple google like search even in the more advanced systemsHHC – cost over 300 million dollars..close to 1.2 billion dollars – this is public information
  • I think if you went back to the early nineteen hundreds and did a controlled clinical trial—or, not clinical but a controlled trial—on the horse versus the car, in the very early days of the car, the horse probably would have won. And if you took a snapshot of those early days and based your future projections on it, you’d say, “Well, let’s throw out the car and go with the horse. They’re obviously much more reliable.” And so on and so forth. But cars got better and people had the vision to realize that and stay with them and improve them to the point where they soon outdistanced the horse.Toocomplex..too many people to communicate with..that it is not possible to do this with paper. Searching for patients with DMVioxx recall – took just an hour to search and send all patientsPopulation medicineCare coordination
  • iHT² Health IT Summit Beverly Hills – Case Study "The EHR & Quality: The Current Evidence" 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 COO / CMO Norwegian American Hospital Chicago, IL IHT2 | Nov 7 2013
    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/oncdatabrief9final.pdf
    5. 5. EHR adoption to date - ONC • Registered Users – Ambulatory - 419,542 – Hospitals – 4,569 • Payments – $6 billion to ambulatory – $ 10 billion to hospitals http://www.healthit.gov/sites/default/files/oncdatabrief9final.pdf
    6. 6. 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
    7. 7. Evidence: EHR and Quality
    8. 8. Computerized Physician Order Entry (CPOE): Medication Safety Events / 100 patient days, mean 55% decrease 10.7 5% decrease 4.86 4.69 3.99 Serious medication errors Preventable ADEs Bates et al. JAMA. 1998; 280; 1311-16
    9. 9. E-prescribing Reduces Medical Errors 45 % of Prescription with Error(s) 40 42.5 35 85% decrease 30 25 20 15 10 5 6.6 0 Paper Stand-alone E-Rx Kaushal et al. JGIM. 2010
    10. 10. Bar-coding reduces potential ADEs 14.00% 41% decrease 12.00% 11.50% 10.00% 8.00% 6.00% 6.80% 51% decrease 4.00% 3.10% 2.00% 1.60% 0.00% Non-timing errors Potential ADEs Poon et al. NEJM. 2010
    11. 11. 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
    12. 12. Computerized Physician Order Entry (CPOE): Inpatient Pediatric Mortality 20 % decrease 1.2 Mean Mortality Rate 1 1 0.8 0.7 0.6 0.4 0.2 0 Pre-EMR Post-EMR Longhurst et al. Pediatrics. 2010; 126; 14-21
    13. 13. 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
    14. 14. EHR and Ambulatory Care Quality 3-13% increase 100 90 90.1 84.2 80 93 87.6 85.1 78.6 74.2 70 74.2 65.8 64.8 60 90 50 53 48 51.3 52.9 Paper EHR 40 35.1 32.7 30 * p <0.001 Kern et al. JGIM. 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. 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
    21. 21. EHR and Quality: The VA Experience Byrne et al. Health Affairs 2010:29;629-638
    22. 22. 92% of the Articles on HIT Show Positive Results Buntin et al. Health Affairs. 2011:30;464-471
    23. 23. EHR: Emerging Safety Concerns
    24. 24. 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.”
    25. 25. Simulation Performance: CPOE % prevention of “problem” orders Post-implementation or in-vivo evaluation is important Vendor Systems Metzger et al. Health Affairs 2010;29:655-653
    26. 26. 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
    27. 27. Increased Neonatal Mortality After CPOE Implementation 7 6.57 Mean Mortality Rate 6 5 4 3 2.8 2 1 0 Pre-CPOE (13 months) Post-CPOE (5 months) Han et al. Pediatrics. 2005;116:1506-1512
    28. 28. 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 computerdependent • Too long to place orders Han et al. Pediatrics. 2005;116:1506-1512
    29. 29. 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
    30. 30. EHR: Safety Concern ACP Ethics Case Studies
    31. 31. Physician Satisfaction with EHRs • Physician dissatisfaction with current EHRs – Poor usability – Time-consuming data entry – Less fulfilling work content – Interference with faceface care
    32. 32. Socio-technical Model of HIT People External Environment Organization Technology (Hardware / Software) Processes Health IT and Patient Safety. Institute of Medicine. 2010
    33. 33. Technology meets humanity: “Bloody Crossroads”
    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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