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Principles of Health IT Application in
Healthcare
Nawanan Theera-Ampornpunt, MD, PhD
For Ramathibodi M.S. & Ph.D. Programs in Data Science for Healthcare & Clinical Informatics
Oct 4, 2021 SlideShare.net/Nawanan
Except
where citing
other works
2
Manufacturing
Image Source: Guardian.co.uk
3
Banking
Image Source: http://www.oknation.net/blog/phuketpost/2013/10/19/entry-3
4
Health care
ER - Image Source: nj.com
5
(At an undisclosed nearby hospital)
Health care
6
• Life-or-Death
• Many & varied stakeholders
• Strong professional values
• Evolving standards of care
• Fragmented, poorly-coordinated systems
• Large, ever-growing & changing body of
knowledge
• High volume, low resources, little time
Why Health care Isn’t Like Any Others?
7
But...Are We That Different?
Input Process Output
Transfer
Banking
Value-Add
- Security
- Convenience
- Customer Service
Location A Location B
8
Input Process Output
Assembling
Manufacturing
Raw
Materials
Finished
Goods
Value-Add
- Innovation
- Design
- QC
But...Are We That Different?
9
But...Are We That Different?
Input Process Output
Patient Care
Health care
Sick Patient Well Patient
Value-Add
- Technology & medications
- Clinical knowledge & skills
- Quality of care; process improvement
- Information
10
• Large variations & contextual dependence
Why Health care Isn’t Like Any Others?
Input Process Output
Patient
Presentation
Decision-
Making
Biological
Responses
11
Information is Everywhere in Medicine
Shortliffe EH. Biomedical informatics in the education of
physicians. JAMA. 2010 Sep 15;304(11):1227-8.
12
“Information” in Medicine
Shortliffe EH. Biomedical informatics in the education of physicians. JAMA. 2010 Sep 15;304(11):1227-8.
13
13
13
WHO (2009)
WHO Six Building Blocks of Health System
14
14
14
WHO (2009)
WHO Health System Framework
15
Use of information and communications
technology (ICT) in health & healthcare
settings
Source: The Health Resources and Services Administration, Department of Health
and Human Service, USA
Slide adapted from: Dr. Boonchai Kijsanayotin
Health IT
16
Use of information and communications
technology (ICT) for health; Including
• Treating patients
• Conducting research
• Educating the health workforce
• Tracking diseases
• Monitoring public health.
Sources: 1) WHO Global Observatory of eHealth (GOe) (www.who.int/goe)
2) World Health Assembly, 2005. Resolution WHA58.28
Slide adapted from: Mark Landry, WHO WPRO & Dr. Boonchai Kijsanayotin
eHealth
17
eHealth  Health IT
Slide adapted from: Dr. Boonchai Kijsanayotin
eHealth & Health IT
18
The Anatomy of Health IT
Health
Information
Technology
Goal
Value-Add
Means
19
Various Forms of Health IT
Hospital Information System (HIS) Computerized Provider Order Entry (CPOE)
Electronic
Health
Records
(EHRs)
Picture Archiving and
Communication System
(PACS)
20
Still Many Other Forms of Health IT
m-Health
Health Information
Exchange (HIE)
Biosurveillance
Information Retrieval
Telemedicine &
Telehealth
Images from Apple Inc., Geekzone.co.nz, Google, Microsoft, PubMed.gov, and American Telecare, Inc.
Personal Health Records
(PHRs)
21
Back to
something simple...
22
What Clinicians Want?
To treat & to
care for their
patients to their
best abilities,
given limited
time &
resources
Image Source: http://en.wikipedia.org/wiki/File:Newborn_Examination_1967.jpg (Nevit Dilmen)
23
High Quality Care
• Safe
• Timely
• Effective
• Patient-Centered
• Efficient
• Equitable
Institute of Medicine, Committee on Quality of Health Care in America. Crossing the quality chasm:
a new health system for the 21st century. Washington, DC: National Academy Press; 2001. 337 p.
24
Information is Everywhere in Healthcare
Shortliffe EH. Biomedical informatics in the education of
physicians. JAMA. 2010 Sep 15;304(11):1227-8.
25
(IOM, 2001)
(IOM, 2000) (IOM, 2011)
Landmark IOM Reports
26
Landmark IOM Reports: Summary
• Humans are not perfect and are bound to
make errors
• High-light problems in the U.S. health care
system that systematically contributes to
medical errors and poor quality
• Recommends reform that would change
how health care works and how
technology innovations can help improve
quality/safety
27
Why We Need Health IT
• Health care is very complex (and inefficient)
• Health care is information-rich
• Quality of care depends on timely
availability & quality of information
• Clinical knowledge body is too large to be in
any clinician’s brain, and the short time
during a visit makes it worse
• “To err is human”
• Practice guidelines are put “on-the-shelf”
28
Image Source: (Left) http://docwhisperer.wordpress.com/2007/05/31/sleepy-heads/
(Right) http://graphics8.nytimes.com/images/2008/12/05/health/chen_600.jpg
To Err is Human 1: Attention
29
Image Source: Suthan Srisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital, Mahidol University
To Err is Human 2: Memory
30
To Err is Human 3: Cognition
• Cognitive Errors - Example: Decoy Pricing
The Economist Purchase Options
• Economist.com subscription $59
• Print subscription $125
• Print & web subscription $125
Ariely (2008)
16
0
84
The Economist Purchase Options
• Economist.com subscription $59
• Print & web subscription $125
68
32
# of
People
# of
People
31
• It already happens....
(Mamede et al., 2010; Croskerry, 2003;
Klein, 2005)
• What if health IT can help?
What If This Happens in Healthcare?
32
• Medication Errors
–Drug Allergies
–Drug Interactions
• Ineffective or inappropriate treatment
• Redundant orders
• Failure to follow clinical practice guidelines
Common Errors
33
We need “Change”
“...we need to upgrade our medical
records by switching from a paper to
an electronic system of record
keeping...”
President Barack Obama
June 15, 2009
34
The Anatomy of Health IT Revisited
Health
Information
Technology
Goal
Value-Add
Means
35
Ultimate Goals of Health IT
•Individual’s Health
•Population’s Health
•Organization’s Health
36
Dimensions of Quality Health Care
• Safety
• Timeliness
• Effectiveness
• Efficiency
• Equity
• Patient-centeredness
(IOM, 2001)
37
CLASS EXERCISE #2
For each of Institute of Medicine’s
6 dimensions of quality health care,
suggest ways health IT can help.
Safety Timeliness Effectiveness
Efficiency Equity Patient-centeredness
38
Safety?
39
Safety
• Legible handwriting
• Proper display of patient information (e.g. abnormal labs)
• Alerts
– Drug-Allergy Checks
– Drug-Drug Interaction Checks
– Drug-Lab Interaction Checks
• Dose calculator
• Prevention of medication errors
• Timely information
– Histories
– Diagnoses/Problem List
– Labs
– Medication List
40
Timeliness?
41
Timeliness
• Timely information for emergencies, transfers, normal visits
– Histories
– Diagnoses/Problem List
– Labs
– Medication List
• Effective communications between providers
• Effective triage & patient monitoring
42
Effectiveness?
43
Effectiveness
• Reminders/advice for
– Guideline adherence
– Preventive care
– Specialist consults
• Templates/forms
– Order sets
– Care planning, nursing assessments & interventions,
nursing documentation
• Availability of patient information
• Continuity of care (even in referrals)
• Effective display of information (e.g. graphs, user-friendly
screens)
• Assistance in decision-making (e.g. differential diagnosis)
• Access to evidence/references at the point of care
44
Efficiency?
45
Efficiency
• Fast/lean/efficient processes of care
– Automation -> faster care, fewer workers
– Process redesigns/reengineering (e.g. parallel processes/access)
– Changes in role assignments -> productivity gains or more time for patient
• Predictable patterns/“Just-in-time” (staffing, resource allocation,
inventory, bed management)
• Flexibility “Organizational slacks” (buffers)
• Drug-formulary checks & policy enforcement
• Reduction of redundant tests
• Efficient management of bed occupancy/hospital capacity
• Cost-savings & time-savings from preventable errors
• Space-savings (e.g. medical records, PACS)
• Effective communications
46
Equity?
47
Equity
• Reduction of barriers to care, improved access
to care
– Physical barriers (telemedicine, tele-consultation)
– Structural barriers (information exchange among
hospitals)
– Functional barriers (information access by patients,
networks of patients)
– Cultural barriers (tailored information for different
patients)
48
Patient-Centeredness?
49
Patient-Centeredness
• Patient’s access to
– Own clinical information
– General health information
– Tailored health information
• Patient engagement/compliance
• Patient empowerment
– Patients’ networking & knowledge sharing
• Patient satisfaction with quality & efficient care
• Patient’s control of information (privacy)
50
Documented Benefits of Health IT
• Literature suggests improvement through
– Guideline adherence (Shiffman et al, 1999;Chaudhry et al, 2006)
– Better documentation (Shiffman et al, 1999)
– Practitioner decision making or process of care
(Balas et al, 1996;Kaushal et al, 2003;Garg et al, 2005)
– Medication safety
(Kaushal et al, 2003;Chaudhry et al, 2006;van Rosse et al, 2009)
– Patient surveillance & monitoring (Chaudhry et al, 2006)
– Patient education/reminder (Balas et al, 1996)
– Cost savings and better financial performance
(Parente & Dunbar, 2001;Chaudhry et al, 2006;Amarasingham et al, 2009;
Borzekowski, 2009)
51
But...
• “Don’t implement technology just for technology’s
sake.”
• “Don’t make use of excellent technology.
Make excellent use of technology.”
(Tangwongsan, Supachai. Personal communication, 2005.)
• “Health care IT is not a panacea for all that ails
medicine.” (Hersh, 2004)
• “We worry, however, that [electronic records] are
being touted as a panacea for nearly all the ills of
modern medicine.”
(Hartzband & Groopman, 2008)
52
Common “Goals” for Adopting HIT
“Computerize”
“Go paperless”
“Digital Hospital”
“Modernize”
“Get a HIS”
“Have EMRs”
“Share data”
53
The Common Denominator
•Health Information Technology
•Electronic Health Records
•Health Information Exchange
54
Some Misconceptions about HIT
Current
Environment
Bad
New, Modern,
Electronic
Environment
Good
If
Then
Always
55
• Health IT as a replacement or supplement of
clinicians?
– The demise of the “Greek Oracle” model (Miller & Masarie, 1990)
The “Greek Oracle” Model
The “Fundamental Theorem” Model
Friedman (2009)
Wrong Assumption
Correct Assumption
Fundamental Theorem of Informatics
56
Some risks
• Alert fatigue
Unintended Consequences of Health IT
57
Workarounds
58
Take-Home Messages
• Health IT has documented benefits to
quality & efficiency of care
• Implementing health IT will not
automatically fix all problems
• Health IT is not without risks
• Find the ways health IT can help
• Focus on the ultimate goals
• Benefits of health IT may vary by
context
59
NEXT
Health IT in
Clinical Settings
60
References
• Amarasingham R, Plantinga L, Diener-West M, Gaskin DJ, Powe NR. Clinical information
technologies and inpatient outcomes: a multiple hospital study. Arch Intern Med.
2009;169(2):108-14.
• Balas EA, Austin SM, Mitchell JA, Ewigman BG, Bopp KD, Brown GD. The clinical value of
computerized information services. A review of 98 randomized clinical trials. Arch Fam
Med. 1996;5(5):271-8.
• Borzekowski R. Measuring the cost impact of hospital information systems: 1987-1994. J
Health Econ. 2009;28(5):939-49.
• Chaudhry B, Wang J, Wu S, Maglione M, Mojica W, Roth E, Morton SC, Shekelle PG.
Systematic review: impact of health information technology on quality, efficiency, and
costs of medical care. Ann Intern Med. 2006;144(10):742-52.
• DeLone WH, McLean ER. Information systems success: the quest for the dependent
variable. Inform Syst Res. 1992 Mar;3(1):60-95.
• Friedman CP. A "fundamental theorem" of biomedical informatics.
J Am Med Inform Assoc. 2009 Apr;16(2):169-70.
• Garg AX, Adhikari NKJ, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J, et al.
Effects of computerized clinical decision support systems on practitioner performance
and patient outcomes: a systematic review. JAMA. 2005;293(10):1223-38.
• Hartzband P, Groopman J. Off the record--avoiding the pitfalls of going electronic. N Engl
J Med. 2008 Apr 17;358(16):1656-1658.
61
References
• Hersh W. Health care information technology: progress and barriers. JAMA. 2004 Nov
10:292(18):2273-4.
• Institute of Medicine, Committee on Quality of Health Care in America. To err is human:
building a safer health system. Kohn LT, Corrigan JM, Donaldson MS, editors.
Washington, DC: National Academy Press; 2000. 287 p.
• Institute of Medicine, Committee on Quality of Health Care in America. Crossing the
quality chasm: a new health system for the 21st century. Washington, DC: National
Academy Press; 2001. 337 p.
• Kaushal R, Shojania KG, Bates DW. Effects of computerized physician order entry and
clinical decision support systems on medication safety: a systematic review. Arch. Intern.
Med. 2003;163(12):1409-16.
• Parente ST, Dunbar JL. Is health information technology investment related to the
financial performance of US hospitals? An exploratory analysis. Int J Healthc Technol
Manag. 2001;3(1):48-58.
• Shiffman RN, Liaw Y, Brandt CA, Corb GJ. Computer-based guideline implementation
systems: a systematic review of functionality and effectiveness. J Am Med Inform Assoc.
1999;6(2):104-14.
• Van Rosse F, Maat B, Rademaker CMA, van Vught AJ, Egberts ACG, Bollen CW. The effect
of computerized physician order entry on medication prescription errors and clinical
outcome in pediatric and intensive care: a systematic review. Pediatrics.
2009;123(4):1184-90.

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Principles of Health IT Application in Healthcare (October 4, 2021)

  • 1. 1 Principles of Health IT Application in Healthcare Nawanan Theera-Ampornpunt, MD, PhD For Ramathibodi M.S. & Ph.D. Programs in Data Science for Healthcare & Clinical Informatics Oct 4, 2021 SlideShare.net/Nawanan Except where citing other works
  • 4. 4 Health care ER - Image Source: nj.com
  • 5. 5 (At an undisclosed nearby hospital) Health care
  • 6. 6 • Life-or-Death • Many & varied stakeholders • Strong professional values • Evolving standards of care • Fragmented, poorly-coordinated systems • Large, ever-growing & changing body of knowledge • High volume, low resources, little time Why Health care Isn’t Like Any Others?
  • 7. 7 But...Are We That Different? Input Process Output Transfer Banking Value-Add - Security - Convenience - Customer Service Location A Location B
  • 9. 9 But...Are We That Different? Input Process Output Patient Care Health care Sick Patient Well Patient Value-Add - Technology & medications - Clinical knowledge & skills - Quality of care; process improvement - Information
  • 10. 10 • Large variations & contextual dependence Why Health care Isn’t Like Any Others? Input Process Output Patient Presentation Decision- Making Biological Responses
  • 11. 11 Information is Everywhere in Medicine Shortliffe EH. Biomedical informatics in the education of physicians. JAMA. 2010 Sep 15;304(11):1227-8.
  • 12. 12 “Information” in Medicine Shortliffe EH. Biomedical informatics in the education of physicians. JAMA. 2010 Sep 15;304(11):1227-8.
  • 13. 13 13 13 WHO (2009) WHO Six Building Blocks of Health System
  • 14. 14 14 14 WHO (2009) WHO Health System Framework
  • 15. 15 Use of information and communications technology (ICT) in health & healthcare settings Source: The Health Resources and Services Administration, Department of Health and Human Service, USA Slide adapted from: Dr. Boonchai Kijsanayotin Health IT
  • 16. 16 Use of information and communications technology (ICT) for health; Including • Treating patients • Conducting research • Educating the health workforce • Tracking diseases • Monitoring public health. Sources: 1) WHO Global Observatory of eHealth (GOe) (www.who.int/goe) 2) World Health Assembly, 2005. Resolution WHA58.28 Slide adapted from: Mark Landry, WHO WPRO & Dr. Boonchai Kijsanayotin eHealth
  • 17. 17 eHealth  Health IT Slide adapted from: Dr. Boonchai Kijsanayotin eHealth & Health IT
  • 18. 18 The Anatomy of Health IT Health Information Technology Goal Value-Add Means
  • 19. 19 Various Forms of Health IT Hospital Information System (HIS) Computerized Provider Order Entry (CPOE) Electronic Health Records (EHRs) Picture Archiving and Communication System (PACS)
  • 20. 20 Still Many Other Forms of Health IT m-Health Health Information Exchange (HIE) Biosurveillance Information Retrieval Telemedicine & Telehealth Images from Apple Inc., Geekzone.co.nz, Google, Microsoft, PubMed.gov, and American Telecare, Inc. Personal Health Records (PHRs)
  • 22. 22 What Clinicians Want? To treat & to care for their patients to their best abilities, given limited time & resources Image Source: http://en.wikipedia.org/wiki/File:Newborn_Examination_1967.jpg (Nevit Dilmen)
  • 23. 23 High Quality Care • Safe • Timely • Effective • Patient-Centered • Efficient • Equitable Institute of Medicine, Committee on Quality of Health Care in America. Crossing the quality chasm: a new health system for the 21st century. Washington, DC: National Academy Press; 2001. 337 p.
  • 24. 24 Information is Everywhere in Healthcare Shortliffe EH. Biomedical informatics in the education of physicians. JAMA. 2010 Sep 15;304(11):1227-8.
  • 25. 25 (IOM, 2001) (IOM, 2000) (IOM, 2011) Landmark IOM Reports
  • 26. 26 Landmark IOM Reports: Summary • Humans are not perfect and are bound to make errors • High-light problems in the U.S. health care system that systematically contributes to medical errors and poor quality • Recommends reform that would change how health care works and how technology innovations can help improve quality/safety
  • 27. 27 Why We Need Health IT • Health care is very complex (and inefficient) • Health care is information-rich • Quality of care depends on timely availability & quality of information • Clinical knowledge body is too large to be in any clinician’s brain, and the short time during a visit makes it worse • “To err is human” • Practice guidelines are put “on-the-shelf”
  • 28. 28 Image Source: (Left) http://docwhisperer.wordpress.com/2007/05/31/sleepy-heads/ (Right) http://graphics8.nytimes.com/images/2008/12/05/health/chen_600.jpg To Err is Human 1: Attention
  • 29. 29 Image Source: Suthan Srisangkaew, Department of Pathology, Facutly of Medicine Ramathibodi Hospital, Mahidol University To Err is Human 2: Memory
  • 30. 30 To Err is Human 3: Cognition • Cognitive Errors - Example: Decoy Pricing The Economist Purchase Options • Economist.com subscription $59 • Print subscription $125 • Print & web subscription $125 Ariely (2008) 16 0 84 The Economist Purchase Options • Economist.com subscription $59 • Print & web subscription $125 68 32 # of People # of People
  • 31. 31 • It already happens.... (Mamede et al., 2010; Croskerry, 2003; Klein, 2005) • What if health IT can help? What If This Happens in Healthcare?
  • 32. 32 • Medication Errors –Drug Allergies –Drug Interactions • Ineffective or inappropriate treatment • Redundant orders • Failure to follow clinical practice guidelines Common Errors
  • 33. 33 We need “Change” “...we need to upgrade our medical records by switching from a paper to an electronic system of record keeping...” President Barack Obama June 15, 2009
  • 34. 34 The Anatomy of Health IT Revisited Health Information Technology Goal Value-Add Means
  • 35. 35 Ultimate Goals of Health IT •Individual’s Health •Population’s Health •Organization’s Health
  • 36. 36 Dimensions of Quality Health Care • Safety • Timeliness • Effectiveness • Efficiency • Equity • Patient-centeredness (IOM, 2001)
  • 37. 37 CLASS EXERCISE #2 For each of Institute of Medicine’s 6 dimensions of quality health care, suggest ways health IT can help. Safety Timeliness Effectiveness Efficiency Equity Patient-centeredness
  • 39. 39 Safety • Legible handwriting • Proper display of patient information (e.g. abnormal labs) • Alerts – Drug-Allergy Checks – Drug-Drug Interaction Checks – Drug-Lab Interaction Checks • Dose calculator • Prevention of medication errors • Timely information – Histories – Diagnoses/Problem List – Labs – Medication List
  • 41. 41 Timeliness • Timely information for emergencies, transfers, normal visits – Histories – Diagnoses/Problem List – Labs – Medication List • Effective communications between providers • Effective triage & patient monitoring
  • 43. 43 Effectiveness • Reminders/advice for – Guideline adherence – Preventive care – Specialist consults • Templates/forms – Order sets – Care planning, nursing assessments & interventions, nursing documentation • Availability of patient information • Continuity of care (even in referrals) • Effective display of information (e.g. graphs, user-friendly screens) • Assistance in decision-making (e.g. differential diagnosis) • Access to evidence/references at the point of care
  • 45. 45 Efficiency • Fast/lean/efficient processes of care – Automation -> faster care, fewer workers – Process redesigns/reengineering (e.g. parallel processes/access) – Changes in role assignments -> productivity gains or more time for patient • Predictable patterns/“Just-in-time” (staffing, resource allocation, inventory, bed management) • Flexibility “Organizational slacks” (buffers) • Drug-formulary checks & policy enforcement • Reduction of redundant tests • Efficient management of bed occupancy/hospital capacity • Cost-savings & time-savings from preventable errors • Space-savings (e.g. medical records, PACS) • Effective communications
  • 47. 47 Equity • Reduction of barriers to care, improved access to care – Physical barriers (telemedicine, tele-consultation) – Structural barriers (information exchange among hospitals) – Functional barriers (information access by patients, networks of patients) – Cultural barriers (tailored information for different patients)
  • 49. 49 Patient-Centeredness • Patient’s access to – Own clinical information – General health information – Tailored health information • Patient engagement/compliance • Patient empowerment – Patients’ networking & knowledge sharing • Patient satisfaction with quality & efficient care • Patient’s control of information (privacy)
  • 50. 50 Documented Benefits of Health IT • Literature suggests improvement through – Guideline adherence (Shiffman et al, 1999;Chaudhry et al, 2006) – Better documentation (Shiffman et al, 1999) – Practitioner decision making or process of care (Balas et al, 1996;Kaushal et al, 2003;Garg et al, 2005) – Medication safety (Kaushal et al, 2003;Chaudhry et al, 2006;van Rosse et al, 2009) – Patient surveillance & monitoring (Chaudhry et al, 2006) – Patient education/reminder (Balas et al, 1996) – Cost savings and better financial performance (Parente & Dunbar, 2001;Chaudhry et al, 2006;Amarasingham et al, 2009; Borzekowski, 2009)
  • 51. 51 But... • “Don’t implement technology just for technology’s sake.” • “Don’t make use of excellent technology. Make excellent use of technology.” (Tangwongsan, Supachai. Personal communication, 2005.) • “Health care IT is not a panacea for all that ails medicine.” (Hersh, 2004) • “We worry, however, that [electronic records] are being touted as a panacea for nearly all the ills of modern medicine.” (Hartzband & Groopman, 2008)
  • 52. 52 Common “Goals” for Adopting HIT “Computerize” “Go paperless” “Digital Hospital” “Modernize” “Get a HIS” “Have EMRs” “Share data”
  • 53. 53 The Common Denominator •Health Information Technology •Electronic Health Records •Health Information Exchange
  • 54. 54 Some Misconceptions about HIT Current Environment Bad New, Modern, Electronic Environment Good If Then Always
  • 55. 55 • Health IT as a replacement or supplement of clinicians? – The demise of the “Greek Oracle” model (Miller & Masarie, 1990) The “Greek Oracle” Model The “Fundamental Theorem” Model Friedman (2009) Wrong Assumption Correct Assumption Fundamental Theorem of Informatics
  • 56. 56 Some risks • Alert fatigue Unintended Consequences of Health IT
  • 58. 58 Take-Home Messages • Health IT has documented benefits to quality & efficiency of care • Implementing health IT will not automatically fix all problems • Health IT is not without risks • Find the ways health IT can help • Focus on the ultimate goals • Benefits of health IT may vary by context
  • 60. 60 References • Amarasingham R, Plantinga L, Diener-West M, Gaskin DJ, Powe NR. Clinical information technologies and inpatient outcomes: a multiple hospital study. Arch Intern Med. 2009;169(2):108-14. • Balas EA, Austin SM, Mitchell JA, Ewigman BG, Bopp KD, Brown GD. The clinical value of computerized information services. A review of 98 randomized clinical trials. Arch Fam Med. 1996;5(5):271-8. • Borzekowski R. Measuring the cost impact of hospital information systems: 1987-1994. J Health Econ. 2009;28(5):939-49. • Chaudhry B, Wang J, Wu S, Maglione M, Mojica W, Roth E, Morton SC, Shekelle PG. Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. 2006;144(10):742-52. • DeLone WH, McLean ER. Information systems success: the quest for the dependent variable. Inform Syst Res. 1992 Mar;3(1):60-95. • Friedman CP. A "fundamental theorem" of biomedical informatics. J Am Med Inform Assoc. 2009 Apr;16(2):169-70. • Garg AX, Adhikari NKJ, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA. 2005;293(10):1223-38. • Hartzband P, Groopman J. Off the record--avoiding the pitfalls of going electronic. N Engl J Med. 2008 Apr 17;358(16):1656-1658.
  • 61. 61 References • Hersh W. Health care information technology: progress and barriers. JAMA. 2004 Nov 10:292(18):2273-4. • Institute of Medicine, Committee on Quality of Health Care in America. To err is human: building a safer health system. Kohn LT, Corrigan JM, Donaldson MS, editors. Washington, DC: National Academy Press; 2000. 287 p. • Institute of Medicine, Committee on Quality of Health Care in America. Crossing the quality chasm: a new health system for the 21st century. Washington, DC: National Academy Press; 2001. 337 p. • Kaushal R, Shojania KG, Bates DW. Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. Arch. Intern. Med. 2003;163(12):1409-16. • Parente ST, Dunbar JL. Is health information technology investment related to the financial performance of US hospitals? An exploratory analysis. Int J Healthc Technol Manag. 2001;3(1):48-58. • Shiffman RN, Liaw Y, Brandt CA, Corb GJ. Computer-based guideline implementation systems: a systematic review of functionality and effectiveness. J Am Med Inform Assoc. 1999;6(2):104-14. • Van Rosse F, Maat B, Rademaker CMA, van Vught AJ, Egberts ACG, Bollen CW. The effect of computerized physician order entry on medication prescription errors and clinical outcome in pediatric and intensive care: a systematic review. Pediatrics. 2009;123(4):1184-90.