A presentation in February 2011 presented at the Ramathibodi Hospital Administration School, Faculty of Medicine Ramathibodi Hospital, Mahidol University in Bangkok, Thailand. Presentation partly in English and partly in Thai.
1. Health Informatics
for Hospital Executives
Nawanan Th
N Theera-Ampornpunt, MD MS
A t MD,
Feb 14, 2011
Ramathibodi Hospital Administration School
SlideShare.net/Nawanan
2. A Few Words About Me...
Me
2003 Doctor of M di i (1st-Class Honors) Ramathibodi
D f Medicine (1 Cl H )
2009 M.S. (Health Informatics) University of Minnesota
Currently
• Ph.D. Candidate (Health Informatics) University of Minnesota
( ) y
• Medical Systems Analyst, Health Informatics Division,
Ramathibodi
Contacts
@
@Nawanan @
@ThaiHealthIT
ranta@mahidol.ac.th
SlideShare.net/Nawanan
www.tc.umn.edu/~theer002
2
groups.google.com/group/ThaiHealthIT
3. Outline
• Healthcare & Health IT
• Health IT Applications
• H lth I f
Health Informatics A A Fi ld
ti As Field
• IT Management
3
7. Healthcare
ea t ca e
7 ER - Image Source: nj.com
8. Why Healthcare Isn’t Like Any Others?
y y
• 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
volume, resources,
little time
8
9. Why Healthcare Isn’t Like Any Others?
y y
• Large variations & contextual dependence
Input Process Output
Patient Decision-
Decision Biological
Presentation Making Responses
9
10. But...Are We That Different?
Banking
Input Process Output
Transfer
Location A Location B
Value-Add
- Security
- Convenience
- Customer Service
10
11. But...Are We That Different?
Manufacturing
Input Process Output
Raw Assembling Finished
Materials Goods
Value-Add
- Innovation
- Design
- QC
11
12. But...Are We That Different?
Healthcare
Input Process Output
Sick Patient Patient Care Well Patient
Value-Add
- Technology & medications
- Clinical knowledge & skills
- Quality of care; process improvement
- Information
12
14. Various Forms of Health IT
Hospital Information System (HIS) Computerized Provider Order Entry (CPOE)
Electronic
Health
Records Picture Archiving and
g
(EHRs) Communication System
(PACS)
14
15. Still Many Other Forms of Health IT
Health Information
Exchange (
g (HIE))
m-Health
m Health
Biosurveillance
Personal Health Records
(PHRs)
Telemedicine &
Information Retrieval Telehealth
15 Images from Apple Inc., Geekzone.co.nz, Google, PubMed.gov, and American Telecare, I
16. Why Adopting Health IT?
“To Go paperless”
To paperless “To Computerize
To Computerize”
“To Get a HIS”
“Digital Hospital”
Digital Hospital
“To H
“T Have EMR ”
EMRs”
“To Modernize”
“To Share data”
To data
16
17. Some Quotes
Q
• “Don’t implement technology just for
Don t
technology’s sake.”
• “Don’t make use of excellent technology.
Make excellent use of technology ”
technology.
(Tangwongsan, Supachai. Personal communication, 2005.)
• “Health care IT is not a panacea for all
Health
that ails medicine.” (Hersh, 2004)
17
18. Health IT: What’s In A Word?
Health Goal
Information Value-Add
Technology
T h l Tools
18
19. Dimensions of Quality Healthcare
y
• Safety
• Timeliness
• Effectiveness
• Efficiency
• Equity
E it
• Patient centeredness
Patient-centeredness
19 (IOM, 2001)
20. Value o Health IT
a ue of ea t
• Guideline adherence
• Better documentation
• Practitioner decision making
or process of care
f
• Medication safety
• Patient surveillance &
monitoring
• Patient education/reminder
20
24. Landmark IOM Reports: Summary
p y
• Humans are not perfect and are
bound to make errors
• Hi hli ht problems i th U S
Highlight bl in the U.S.
health care system that
systematically contributes t
t ti ll t ib t to
medical errors and poor quality
• Recommends reform that would
change how health care works and
g
how technology innovations can
help improve q
p p quality/safety
y y
24
25. Why We Need Health IT
• Health care is very complex
(and inefficient)
• Health care is information rich
information-rich
• Quality of care depends on timely
availability & quality
il bilit lit
of information
• Clinical knowledge body is too large
• Short time during a visit
g
• Practice guidelines are put
“on-the-shelf”
on the shelf
• “To err is human”
25
26. To Err Is Human
• Perception errors
26 Image Source: interaction-dynamics.com
27. To Err Is Human
• L k of Attention
Lack f Att ti
Image Source: aafp.org
27
28. To Err Is Human
• Cognitive Errors - Example: Decoy Pricing
# of
The Economist Purchase Options People
• Economist.com subscription $59 16
• Print subscription $125 0
• Print & web subscription $125 84
# of
The Economist Purchase Options People
• Economist.com subscription $59 68
• Print & web subscription
p $
$125 32
(Ariely, 2008)
28
29. What If This Happens in Healthcare?
• It already h
l d happens....
(Mamede et al., 2010; Croskerry, 2003; Klein, 2005)
• What if health IT can help?
29
31. U.S.’s Efforts on Health IT Adoption
?
“...We will make wider use of electronic records
We
and other health information technology, to help
control costs and reduce dangerous
medical errors.”
President George W Bush
W.
Sixth State of the Union Address, January 31, 2006
31 Source: Wikisource.org Image Source: Wikipedia.org
32. Public Policy in Informatics: A US’s Case
1991: IOM s CPR Report published
IOM’s
1996: HIPAA enacted
2000-2001: IOM’s To Err Is Human &
Crossing the Quality Chasm published
2004: George W. Bush’s Executive
Order establishing ONCHIT (ONC)
g ( )
2009-2010: ARRA/HITECH Act &
“Meaningful use” regulations
Meaningful use
32
33. U.S. Adoption of Health IT
p
Ambulatory (Hsiao et al, 2009) Hospitals (Jha et al, 2009)
Basic EHRs w/ notes 7.6%
Comprehensive EHRs
p 1.5%
CPOE 17%
• U.S. lags behind other Western countries
(Schoen et al, 2006;Jha et al, 2008)
• Money and misalignment of benefits is the
biggest reason
gg
33
34. We Need “Change”
“...we need to upgrade our medical
records by switching from a p p to
y g paper
an electronic system of record
keeping...”
President Barack Ob
P id t B k Obama
June 15, 2009
34
35. The Birth of “Meaningful Use”
“...Our recovery p
y plan will invest in
electronic health records and new technology
that will reduce errors, bring down costs,
ensure privacy and save lives ”
privacy, lives.
President Barack Obama
Address to Joint Session of Congress
February 24, 2009
35 Source: WhiteHouse.gov
36. American Recovery & Reinvestment Act
• Contains HITECH Act
(Health Information Technology for Economic
and Clinical Health Act)
• ~ 20 billion dollars for Health IT investments
• Incentives & penalties for providers
36
37. National Leadership
Office of the National Coordinator for Health Information
Technology (ONC -- formerly ONCHIT)
David Blumenthal, MD, MPP
National Coordinator for
Health Information Technology
(2009 - Feb 2011) [Just
Photo courtesy of U.S. Department of Health & Human Services
37
38. What is in the HITECH Act?
38 (Blumenthal, 2010)
39. “Meaningful Use”
g
“Meaningful Use”
“M i f lU ”
Pumpkin
of a Pumpkin
39 Image Source & Idea Courtesy of Pat Wise at HIMSS, Oct. 2009
40. “Meaningful Use” of Health IT
g
Stage 1
- Electronic capture of Better
health information
- Information sharing
Stage 3
Health
- D t reporting
Data ti
Stage 2 Use of
EHRs to
Use of improve
EHRs to outcomes
improve
processes of
care
40
(Blumenthal, 2010)
42. Enterprise-wide
Enterprise wide Hospital IT
• Master Patient Index (MPI)
• Admit-Discharge-Transfer (ADT)
• Electronic Health Records (EHRs)
• Computerized Physician Order Entry
(CPOE)
• Clinical Decision Support Systems
(CDSSs)
• Picture Archiving and Communication
System (PACS)
• Nursing applications
• Enterprise Resource Planning (ERP)
42
43. Departmental IT
• Pharmacy applications
• Laboratory Information System (
y y (LIS)
)
• Specialized applications (ER, OR,
LR, Anesthesia,
LR Anesthesia Critical Care
Care,
Dietary Services, Blood Bank)
• Incident management & reporting
system
43
44. EHRs & HIS
The Challenge - Knowing What It Means
Electronic Health
Records (EHRs)
Hospital
Information
Electronic Medical
El t i M di l System (HIS)
S t
Records (EMRs)
Electronic Patient
Records (EPRs)
Clinical
Information
Personal Health
Computer-Based System (CIS)
Records (PHRs)
Patient Records
(CPRs)
44
45. EHR Systems
Just l t i d
J t electronic documentation?
t ti ?
History Diag- Treat-
...
& PE nosis ments
Or do they have other values?
45
46. Functions that Should Be Part of EHR Systems
• Computerized Medication Order Entry
• Computerized Laboratory Order Entry
• Computerized Laboratory Results
• Physician Notes
• Patient Demographics
• Problem Lists
• Medication Lists
• Discharge Summaries
• Diagnostic Test Results
• Radiologic Reports
46 (IOM, 2003; Blumenthal et al, 2006)
48. Computerized Physician Order Entry (CPOE)
Values
• No handwriting!!!
• Structured data entry: Completeness, clarity,
fewer mistakes (?)
• No transcription errors!
• Entry point for CDSSs
• Streamlines workflow, increases efficiency
, y
48
49. Clinical Decision Support Systems (CDSSs)
• The real place where most of the
values of health IT can be achieved
l f h lth b hi d
• Expert systems
• Based on artificial intelligence
intelligence,
machine learning, rules, or
statistics
• Examples: differential
diagnoses,
diagnoses treatment options
(Shortliffe, 1976)
49
50. Clinical Decision Support Systems (CDSSs)
• Alerts & reminders
• Based on specified logical conditions
p
• Examples:
• Drug-allergy checks
• Drug drug interaction checks
Drug-drug
• Drug-disease checks
• Drug-lab checks
• Drug-formulary checks
g y
• Reminders for preventive services or
certain actions (e g smoking cessation)
(e.g.
• Clinical practice guideline integration
50
51. Clinical Decision Support Systems (CDSSs)
• Evidence-based knowledge sources e g drug
Evidence based e.g.
database, literature
• Simple UI designed to help clinical decision
making
51
52. A Basic Architecture of A CDSS
User
U User I t f
U Interface
Inference Engine
Knowledge Patient
Other Data Base Data
• System states • Rules
• Epidemiological/ • Statistical data
surveillance data • Literature
• Etc. • Etc.
52
53. Clinical Decision Support Systems (CDSSs)
PATIENT
Perception
CLINICIAN
Attention
Long Term Memory External Memory
Working
Memory
Knowledge Data Knowledge Data
Inference
DECISION
53 From a teaching slide by Don Connelly, 2006
54. Clinical Decision Support Systems (CDSSs)
PATIENT
Perception
CLINICIAN
Abnormal lab
Attention highlights
Long Term Memory External Memory
Working
Memory
Knowledge Data Knowledge Data
Inference
DECISION
54
55. Clinical Decision Support Systems (CDSSs)
PATIENT
Perception
CLINICIAN
Abnormal lab
Attention highlights
Long Term Memory External Memory
Working
Memory
Knowledge Data Knowledge Data
Inference
DECISION
55
56. Clinical Decision Support Systems (CDSSs)
PATIENT
Perception
CLINICIAN
Drug-Allergy
Attention Checks
Long Term Memory External Memory
Working
Memory
Knowledge Data Knowledge Data
Inference
DECISION
56
57. Clinical Decision Support Systems (CDSSs)
PATIENT
Drug-Drug
Perception Interaction
CLINICIAN
Checks
Attention
Long Term Memory External Memory
Working
Memory
Knowledge Data Knowledge Data
Inference
DECISION
57
58. Clinical Decision Support Systems (CDSSs)
PATIENT
Perception Clinical
CLINICIAN Practice
Guideline
Attention Reminders
Long Term Memory External Memory
Working
Memory
Knowledge Data Knowledge Data
Inference
DECISION
58
59. Clinical Decision Support Systems (CDSSs)
PATIENT
Perception
CLINICIAN
Attention
Long Term Memory External Memory
Working
Memory
Knowledge Data Knowledge Data
Inference Diagnostic/Treatment
Expert Systems
DECISION
59
60. Clinical Decision Support Systems (CDSSs)
• CDSS as a replacement or supplement of
clinicians?
• The demise of the “Greek Oracle” model (Miller & Masarie, 1990)
The “Greek Oracle” Model
The “Fundamental Theorem”
60 (Friedman, 2009)
63. Health IT for Medication Safety
Ordering
g Transcription Dispensing
g Administration
Automatic Electronic
CPOE
C O
Medication Medication
Dispensing Administration
Records
(e-MAR)
Barcoded
Medication Barcoded
Dispensing
Di i Medication
Administration
63
64. Health Information Exchange (HIE)
g ( )
Government
Hospital A Hospital B
Clinic C
Lab
L b Patient t H
P ti t at Home
64
65. 4 Quadrants of Hospital IT
p
Strategic
Business
Intelligence
g HIE
PHRs
CDSS
Social
Media CPOE
Administrative Clinical
VMI EHRs
ERP
LIS
ADT
Word
Processor MPI
Operational
65 (Theera-Ampornpunt [unpublished], 2010-2011)
67. Biomedical/Health Informatics
• “[T]he field that is concerned with the optimal
use of information, often aided by the use of
technology, to improve individual health, health
care, public health, and biomedical research”
(Hersh, 2009)
• “[T]he application of the science of information
as data plus meaning to problems of
biomedical interest” (Bernstam et al, 2010)
67
68. DIKW Pyramid
Wisdom
Knowledge
Information
Data
D t
68
71. M/B/H Informatics and Other Fields
Social
Sc e ces
Sciences Statistics &
(Psychology,
Sociology, Research
Linguistics, Methods
Cognitive & Law & Ethics) Medical
Decision Sciences &
Science Public Health
Engineering Management
Library
Computer & Biomedical/
Science,
S i
Information Health
Information
Science Informatics
Retrieval, KM
And More!
71
74. ความเดิมตอนที่แล้ว...
• H lth IT: ของดี
Health IT (อาจจะ) มีประโยชน์
(แต่ก็อาจมีโทษ)
• บริบท (local contexts) มีความสําคัญ
• ต้องมีการบริหารจัดการที่เหมาะสม
ตองมการบรหารจดการทเหมาะสม
ประเด็็นพิิจารณา
• อะไรคือบริบทที่เกียวข้อง?
่
• จะจัดการมันอย่างไร?
74
75. Context
The current
location
The tailwind The headwind
The past The
journey
j direction
di i The destination
The speed
The sailor(s) &
( ) The sail
people on The boat
The sea
board
75 The sailboat image source: Uwe Kils via http://en.wikipedia.org/wiki/Sailing
76. Direction & Destination
รพ.มหาวิทยาลัย 900 เตียง รพ.เอกชน 200 เตีียง
Vision เป็นโรงพยาบาลชั้นนําของ Vision เป็นโรงพยาบาล High Tech
ภูมภาคเอเชียที่มีความเป็นเลิศใน
ภมิภาคเอเชยทมความเปนเลศใน High Touch ชันนําของประเทศ
ชนนาของประเทศ
้
ด้านบริการ การศึกษา และวิจัย
76
77. “The Sail
The Sail”
Carr (2004) Carr (2003)
77
78. 4 Quadrants of Hospital IT
p
Strategic
Business
Intelligence
g HIE
PHRs
CDSS
Social
Media CPOE
Administrative Clinical
VMI EHRs
ERP
LIS
ADT
Word
Processor MPI
Operational
78 (Theera-Ampornpunt [unpublished], 2010-2011)
79. IT As A Strategic Advantage
g g
Sustainable
Yes
competitive
advantage
Yes Inimitable
I i it bl ?
Yes Rare ?
No
Preemptive
Yes Non-Substitutable? No advantage
Competitive
Valuable
V l bl ? parity
No
Competitive
No necessity
Competitive
C titi
Resources/ Disadvantage
capabilities
79 From a teaching slide by Nelson F. Granados, 2006 at University of Minnesota Carlson School of Management
80. “The Sail
The Sail”
รพ.มหาวิทยาลัย 900 เตียง รพ.เอกชน 200 เตีียง
Vision เป็นโรงพยาบาลชั้นนําของ
เปนโรงพยาบาลชนนาของ Vision เป็นโรงพยาบาล High Tech
เปนโรงพยาบาล
ภูมภาคเอเชียที่มีความเป็นเลิศใน
ิ High Touch ชันนําของประเทศ
้
ด้านบริการ การศึกษา และวิจัย
Current IT Environment
Current IT Environment
• เป็น รพ.แรกๆ ที่มี HIS ซึ่งพัฒนาเอง • มี MPI, ADT, EHRs, CPOE แต่ยงมี
ั
และตอยอดจาก MPI,
แล ต่อยอดจาก MPI ADT ไปส่ CPOE
ไปสู CDSS จํากัด
จากด
(แต่ยงขาด CDSS) ระบบ HIS เข้ากับ
ั • ยังไม่มี Customer Relationship
workflow ของ รพ. เป็นอย่างดี Management (CRM)
• ปัจจุบัน ระบบ HIS ยังใช้เทคโนโลยี
เดียวกับช่วงที่พัฒนาใหม่ๆ (20 ปีก่อน)
เปนหลก มการนาเทคโนโลยใหมๆ
เป็นหลัก มีการนําเทคโนโลยีใหม่ๆ มา
ใช้อย่างช้าๆ
80
81. IT As A Strategic Advantage
g g
Sustainable
Yes
competitive
advantage
Yes Inimitable
I i it bl ?
Yes Rare ?
No
Preemptive
Yes Non-Substitutable? No advantage
Competitive
Valuable
V l bl ? parity
No
Competitive
No necessity
Competitive
C titi
Resources/ Disadvantage
capabilities
81 From a teaching slide by Nelson F. Granados, 2006 at University of Minnesota Carlson School of Management
82. “The Sailors”
The Sailors
People
Techno-
Process
logy
82
84. Context
The current
location
The tailwind The headwind
The past The
journey
j direction
di i The destination
The speed
The sailor(s) &
( ) The sail
people on The boat
The sea
board
84 The sailboat image source: Uwe Kils via http://en.wikipedia.org/wiki/Sailing
85. “The Boat”
The Boat
• Size
• Resources
• Structures
• Work Processes
• Facilities/Geograph
Facilities/Geography
• Etc.
85
86. “The Sea
The Sea”
• T
Target customers
t t
• Local competitiveness
• Relationship of hospital to local players
• Inter-organizational collaboration
g
• IT market environment
• National/international trend
• Regulations
• Standard of care
• Etc.
86
87. SWOT Analysis
“The B t”
“Th Boat” “The S ”
“Th Sea”
“The Tailwind”
The Tailwind Strengths Opportunities “The Tailwind”
The Tailwind
“The Headwind” Weaknesses Threats “The Headwind”
87
89. Context
The current
location
The tailwind The headwind
The past The
journey
j direction
di i The destination
The speed
The sailor(s) &
( ) The sail
people on The boat
The sea
board
89 The sailboat image source: Uwe Kils via http://en.wikipedia.org/wiki/Sailing
90. Gartner’s Sourcing Life Cycle
g y
Strategic
g Tactical
Sourcing Strategy Evaluation and Selection
g Alignment g Identification
g Organization assessment g Criteria development
g Core competencies g Organization fit
g Market scan g Selection process
g Make-or-buy decisions g Partnership
g Risk analysis opportunities
Sourcing
Contract
Management
Development
g Relationship
g Governance model
g Performance
g Metrics
assessment
g Payment models
g Goals: reach business
objectives, efficiency, g Terms and conditions
q
quality, innovation
y, g Provision
g Transition for changes
90 From a teaching slide by Nelson F. Granados, 2006
91. IT Outsourcing Decision Tree
Keep Internal
No
Is external delivery
No reliable and lower cost?
Does service offer Yes OUTSOURCE!
competitive advantage?
titi d t ?
Yes Keep Internal
91 From a teaching slide by Nelson F. Granados, 2006
92. IT Outsourcing Decision Tree:
Ramathibodi s
Ramathibodi’s Case
External delivery unreliable
• Non-Core HIS
HIS,
External delivery higher cost
• ERP maintenance/ongoing
customization
Keep Internal
No
Is external delivery
No reliable and lower cost?
Does service offer Yes OUTSOURCE!
competitive advantage?
titi d t ?
ERP initial
implementation,
Yes Keep Internal
PACS, RIS,
PACS RIS
Core HIS, CPOE Departmental
Strategic advantages systems,
• Agility due to local workflow accommodations IT Training
• Secondary data utilization (research, QI)
• Roadmap to national leader in informatics
92
93. Gartner Hype Cycle
Image source: Jeremy Kemp via http://en.wikipedia.org/wiki/Hype_cycle
93 http://www.gartner.com/technology/research/methodologies/hype-cycle.jsp
95. Unified Theory of Acceptance and Use of
Technology (UTAUT)
Performance
Usefulness
Expectancy
p y
Ease of Use Effort
Expectancy
Behavioral
B h i l Use
Social Norm Intention Behavior
Social
& Opinions Influence
Facilitating
IT Support
Conditions
Voluntariness
Gender Age Experience
of Use
95 Venkatesh et al. (2003)
96. Adoption Strategies: “The Tipping Point” Version
The Th
Th Three Rules of Epidemics
R l f E id i
• The Law of the Few
• Connectors Change Agents
Opinion Leaders
• Mavens Super-Users
• Salesmen Champions
• The Stickiness Factor Ease of Use
• The Power of Context Social Norm &
Opinions
IT Support
Gladwell (2000)
96
97. Hospital IT Adoption Success Factors
• Communications of project plans & progresses
• W kfl
Workflow considerations
id i
• Management support of IT projects
• Common visions
• Shared commitment
• Multidisciplinary user involvement
• Project management
• Training
• Innovativeness
• Organizational learning
97 Theera-Ampornpunt (2009) [Unpublished]
99. Summary
• Healthcare is complex
• H lth IT can b
Health benefit h lth
fit healthcare th
through
h
• Information delivery
• Process improvement
• Empowering providers & patients
• The world is moving toward health IT
• Health informatics is related to & relies on the field of IT, but
they
th are not th same
t the
• Management of hospital IT is crucial to success
• Know your organization (“context”)
• Strategic mindset
• Project & change management
99
100. Final Words...
• Don’t forget our real aim...
Adoption Use Outcomes
100
101. Q&A
A...
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Contacts
@Nawanan @ThaiHealthIT
ranta@mahidol.ac.th
www.tc.umn.edu/~theer002
groups.google.com/group/ThaiHealthIT
101
102. References
• Ariely D. Predictably irrational: the hidden forces that shape our decisions. New York City
(NY):HarperCollins; 2008. 304 p.
• Bernstam EV S i h JW J h
B EV, Smith JW, Johnson TR. What is biomedical informatics? J Biomed Inform. 2010
TR Wh i bi di l i f i ? J Bi dI f 2010
Feb;43(1):104‐10.
• Blumenthal D. Launching HITECH. N Engl J Med. 2010 Feb 4;362(5):382‐5.
• Blumenthal D, DesRoches C D
Bl th l D D R h C, Donelan K F i T Jh A K h l R R S R
l K, Ferris T, Jha A, Kaushal R, Rao S, Rosenbaum S.
b S
Health information technology in the United States: the information base for progress
[Internet]. Princeton (NJ): Robert Wood Johnson Foundation; 2006.
• Carr NG. Does IT matter? Information technology and the corrosion of competitive
Carr NG. Does IT matter? Information technology and the corrosion of competitive
advantage. Boston (MA):Harvard Business Press;2004. 208 p.
• Carr NG. IT doesn’t matter. Harvard Bus Rev. 2003 May 1;81(5):41‐9.
• Croskerry P. The importance of cognitive errors in diagnosis and strategies to minimize them.
y p g g g
Acad Med. 2003 Aug;78(8):775‐80. 81 p. Available from:
http://www.rwjf.org/files/publications/other/EHRReport0609.pdf
• Friedman CP. A "fundamental theorem" of biomedical informatics. J Am Med Inform Assoc.
2009 Apr;16(2):169‐70.
• Gladwell M. The Tipping Point: how little things can make a big difference. New York City
(NY):Little Brown;2000. 304 p.
• Hersh W. A stimulus to define informatics and health information technology. BMC Med
h i l d fi i f i dh l hi f i h l d
Inform Decis Mak. 2009;9:24.
102
• Hersh W. Health care information technology: progress and barriers. JAMA. 2004 Nov
10:292(18):2273‐4
103. References
• Hsiao C, Beatty PC, Hing ES, Woodwell DA. Electronic medical record/electronic health record
use by office‐based physicians: United States, 2008 and preliminary 2009 [Internet]. 2009
b ff b d h d d l [ ]
[cited 2010 Apr 12]; Available from: http://www.cdc.gov/nchs/data/hestat/emr_ehr/
emr_ehr.pdf
• Institute of Medicine, Board on Health Care Services, Committee on Data Standards for
Institute of Medicine Board on Health Care Services Committee on Data Standards for
Patient Safety. Key Capabilities of an electronic health record system: letter report [Internet].
Washington, DC: National Academy of Sciences;2003.
31 p. Available from: http://www.nap.edu/catalog/10781.html
• 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.
• Jha AK DesRoches CM Campbell EG Donelan K Rao SR Ferris TG Shields A Rosenbaum S
AK, DesRoches CM, Campbell EG, Donelan K, Rao SR, Ferris TG, Shields A, Rosenbaum S,
Blumenthal D. Use of electronic health records in U.S. hospitals. N Engl J Med.
2009;360(16):1628‐38.
• Jha AK, Doolan D, Grandt D, Scott T, Bates DW. The use of health information technology in
, , , , gy
seven nations. Int J Med Inform. 2008;77(12):848‐54.
103