Post on 07-May-2015
IT for Hospitals
Nawanan Theera‐Ampornpunt, MD, PhD
SlideShare.net/Nawanan
Oct. 22, 2013For Ramathibodi Hospital Administration School
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A Few Words About Me...
2003 M.D. (1st-Class Honors) Ramathibodi
2009 M.S. (Health Informatics) University of Minnesota
2011 Ph.D. (Health Informatics) University of Minnesota
Currently• Deputy Executive Director for Informatics (CIO), Chakri Naruebodindra
Medical Institute, Faculty of Medicine Ramathibodi Hospital
Contacts
nawanan.the@mahidol.ac.th
SlideShare.net/Nawanan
www.tc.umn.edu/~theer002
groups.google.com/group/ThaiHealthIT
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Healthcare & Health ITAdopting Health ITHealth IT Applications in Hospitals IT Management
Outline
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Health care & Health IT
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Manufacturing
Image Source: Guardian.co.uk
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Banking
Image Source: Cablephet.com
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Health care
ER ‐ Image Source: nj.com
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Life‐or‐DeathMany & 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?
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Large variations & contextual dependence
Why Health care Isn’t Like Any Others?
Input Process Output
Patient Presentation
Decision‐Making
Biological Responses
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But...Are We That Different?
Input Process Output
Transfer
Banking
Value‐Add‐ Security‐ Convenience‐ Customer Service
Location A Location B
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Input Process Output
Assembling
Manufacturing
Raw Materials
Finished Goods
Value‐Add‐ Innovation‐ Design‐ QC
But...Are We That Different?
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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
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Why Adopting Health IT?
“To Computerize”“To Go paperless”
“Digital Hospital”
“To Modernize”
“To Get a HIS”
“To Have EMRs”
“To Share data”
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“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)
Some Quotes
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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)
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High Quality Care
SafeTimelyEffectiveEfficientEquitablePatient‐Centered
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. IOM (2001)
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Information is Everywhere in Health Care
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Achieving Quality Care with Information
SafeDrug allergiesMedication Reconciliation
Timely Complete information at point of care
EffectiveBetter clinical decision‐making
Image Source: http://www.flickr.com/photos/childrensalliance/3191862260/
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Achieving Quality Care with Information
Efficient Faster care Time & cost savingsReducing unnecessary tests
EquitableAccess to providers & knowledge
Patient‐Centered Empowerment & better self‐care
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That’s Where Health IT Plays A Role...
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The Anatomy of the Word “Health IT”
HealthInformationTechnology
Goal
Value‐Add
Tools
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Various Forms of Health IT
Hospital Information System (HIS) Computerized Provider Order Entry (CPOE)
Electronic Health Records (EHRs)
Picture Archiving and Communication System
(PACS)
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Still Many Other Forms of Health IT
m‐Health
Health Information Exchange (HIE)
Biosurveillance
Information RetrievalTelemedicine &
Telehealth
Images from Apple Inc., Geekzone.co.nz, Google, PubMed.gov, and American Telecare, Inc.
Personal Health Records (PHRs)
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Guideline adherenceBetter documentationPractitioner decision making or process of care
Medication safetyPatient surveillance & monitoring
Patient education/reminder
Value of Health IT (in Literature)
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Fundamental Theorem of Informatics
(Friedman, 2009)Friedman (2009)
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Is There A Role for Health IT?
IOM (2000)
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Landmark IOM Reports
IOM (2001)IOM (2000)
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Humans are not perfect and are bound to make errors
Highlight 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
Landmark IOM Reports: Summary
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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 Short time during a visit Practice guidelines are put “on‐the‐shelf” “To err is human”
Summary: Why We Need Health IT
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Perception errors
To Err Is Human
Image Source: interaction‐dynamics.com
31 Image Source: aafp.org
Lack of Attention
To Err Is Human
32 Image Source: Dr. Suthan Srisangkaew
Human Brain’s Limited Memory
To Err Is Human
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Cognitive Errors - Example: Decoy Pricing
The Economist Purchase Options
• Economist.com subscription $59• Print subscription $125• Print & web subscription $125
Ariely (2008)
16084
The Economist Purchase Options
• Economist.com subscription $59• Print & web subscription $125
6832
# of People
# of People
To Err Is Human
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It already happens....(Mamede et al., 2010; Croskerry, 2003; Klein, 2005)
What if health IT can help?
What If This Happens in Healthcare?
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Adopting Health IT
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Adoption of Health IT: Assumptions
Adoption Use Outcomes
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“...We will make wider use of electronic records and other health information technology, to help control
costs and reduce dangerous medical errors.”
U.S.’s Efforts on Health IT Adoption
Source: Wikisource.org Image Source: Wikipedia.org
President George W. BushSixth State of the Union Address, January 31, 2006
?
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1991: IOM’s CPR Report published
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)
2009‐2010: ARRA/HITECH Act & “Meaningful use” regulations
Public Policy in Informatics: A US’s Case
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U.S. Adoption of Health IT
• U.S. lags behind other Western countries (Schoen et al, 2006;Jha et al, 2008)
• Money and misalignment of benefits is the biggest reason
Ambulatory (Hsiao et al, 2009) Hospitals (Jha et al, 2010)
Basic EHRs w/ notes 9.2%Comprehensive EHRs 2.7%CPOE for medications 34%
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We Need “Change”
“...we need to upgrade our medical records by switching from a paper to an electronic system of record keeping...”
President Barack ObamaJune 15, 2009
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“...Our recovery plan will invest in electronic health records and new technology
that will reduce errors, bring down costs, ensure privacy, and save lives.”
President Barack ObamaAddress to Joint Session of Congress
February 24, 2009
The Birth of “Meaningful Use”
Source: WhiteHouse.gov
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Contains HITECH Act(Health Information Technology for Economic and Clinical Health Act)
~ 20 billion dollars for Health IT investments
Incentives & penalties for providers
American Recovery & Reinvestment Act
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What is in the HITECH Act?
(Blumenthal, 2010)
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“Meaningful Use”
“Meaningful Use” of a PumpkinPumpkin
Image Source & Idea Courtesy of Pat Wise at HIMSS, Oct. 2009
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“Meaningful Use” of Health IT
Stage 1‐ Electronic capture of health information‐ Information sharing‐ Data reporting
Stage 2
Use of EHRsto improve processes of care
Stage 3
Use of EHRs to improve outcomes
Better Health
Blumenthal (2010)
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Adoption Studies: Descriptive AspectPongpirul et al. (2004)
2011
Theera‐Ampornpunt (2011)
2004
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Adoption Estimates
Estimate (Partial or Complete Adoption) NationwideBasic EHR, outpatient 86.6%Basic EHR, inpatient 50.4%Basic EHR, both settings 49.8%Comprehensive EHR, outpatient 10.6%Comprehensive EHR, inpatient 5.7%Comprehensive EHR, both settings 5.3%order entry of medications, outpatient 96.5%order entry of medications, inpatient 91.4%order entry of medications, both settings 90.2%order entry of all orders, outpatient 88.6%order entry of all orders, inpatient 81.7%order entry of all orders, both settings 79.4%
Theera‐Ampornpunt (2011)
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Health IT Applications in Hospitals
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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)
Enterprise‐wide Hospital IT
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Pharmacy applications Laboratory Information System (LIS) Radiology Information System (RIS) Specialized applications (ER, OR, LR, Anesthesia, Critical Care, Dietary Services, Blood Bank)
Incident management & reporting system
Departmental IT
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EHRs & HIS
The Challenge ‐ Knowing What It Means
Electronic Medical Records (EMRs)
Computer‐Based Patient Records
(CPRs)
Electronic Patient Records (EPRs)
Electronic Health Records (EHRs)
Personal Health Records (PHRs)
Hospital Information System
(HIS)
Clinical Information System (CIS)
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Just electronic documentation?
Or do they have other values?
EHR Systems
Diag‐nosis
History & PE
Treat‐ments ...
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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
Functions that Should Be Part of EHR Systems
IOM (2003), Blumenthal et al (2006)
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Computerized Physician Order Entry (CPOE)
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Values
No handwriting!!! Structured data entry: Completeness, clarity, fewer mistakes (?)
No transcription errors! Streamlines workflow, increases efficiency
Computerized Physician Order Entry (CPOE)
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The real place where most of the values of health IT can be achieved
Expert systemsBased on artificial intelligence, machine learning, rules, or statistics
Examples: differential diagnoses, treatment options
Clinical Decision Support Systems (CDSs)
(Shortliffe, 1976)
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Alerts & reminders Based on specified logical conditions Examples:Drug‐allergy checksDrug‐drug interaction checksDrug‐disease checksDrug‐lab checksDrug‐formulary checks Reminders for preventive services or certain actions (e.g. smoking cessation)
Clinical practice guideline integration
Clinical Decision Support Systems (CDSSs)
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Example of “Alerts & Reminders”
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Reference information or evidence‐based knowledge sourcesDrug reference databasesTextbooks & journalsOnline literature (e.g. PubMed)Tools that help users easily access references (e.g. Infobuttons)
CDS Examples
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Infobuttons
Image Source: https://webcis.nyp.org/webcisdocs/what-are-infobuttons.html
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Pre‐defined documentsOrder sets, personalized “favorites” Templates for clinical notes Checklists Forms
Can be either computer‐based or paper‐based
CDS Examples
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Order Sets
Image Source: http://www.hospitalmedicine.org/ResourceRoomRedesign/CSSSIS/html/06Reliable/SSI/Order.cfm
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Simple UI designed to help clinical decision makingAbnormal lab highlightsGraphs/visualizations for lab resultsFilters & sorting functions
CDS Examples
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Abnormal Lab Highlights
Image Source: http://geekdoctor.blogspot.com/2008/04/designing-ideal-electronic-health.html
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Clinical Decision Support Systems (CDSSs)
External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
WorkingMemory
CLINICIAN
Elson, Faughnan & Connelly (1997)
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Clinical Decision Support Systems (CDSSs)
External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
WorkingMemory
CLINICIANAbnormal lab highlights
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Clinical Decision Support Systems (CDSSs)
External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
WorkingMemory
CLINICIANDrug‐Allergy
Checks
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Clinical Decision Support Systems (CDSSs)
External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
WorkingMemory
CLINICIANDrug‐Drug Interaction Checks
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Clinical Decision Support Systems (CDSSs)
External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
WorkingMemory
CLINICIANClinical Practice
Guideline Reminders
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Clinical Decision Support Systems (CDSSs)
External Memory
Knowledge Data
Long Term Memory
Knowledge Data
Inference
DECISION
PATIENT
Perception
Attention
WorkingMemory
CLINICIAN
Diagnostic/Treatment Expert Systems
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IBM’s Watson
Image Source: socialmediab2b.com
72Image Source: englishmoviez.com
Rise of the Machines?
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CDSS as a replacement or supplement of clinicians? The demise of the “Greek Oracle” model (Miller & Masarie, 1990)
Clinical Decision Support Systems (CDSSs)
The “Greek Oracle” Model
The “Fundamental Theorem” Model
Friedman (2009)
Wrong Assumption
Correct Assumption
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Some risks Alert fatigue
Clinical Decision Support Systems (CDSSs)
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Workarounds
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Ordering Transcription Dispensing Administration
Health IT for Medication Safety
CPOEAutomatic Medication Dispensing
Electronic Medication
Administration Records (e‐MAR)
BarcodedMedication
Administration
BarcodedMedication Dispensing
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Health Information Exchange (HIE)
Hospital A Hospital B
Clinic C
Government
Lab Patient at Home
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Achieving HIE (or eHealth)
WHO & ITU
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นวนรรน ธีระอัมพรพันธุ์. ตํานานความเชื่อและข้อเท็จจริงเกี่ยวกับมาตรฐานสารสนเทศทางสุขภาพ. ใน: Health Data Standards Expo: From Reimbursement to Clinical Excellence; 2011 Aug 8-9; Bangkok, Thailand. Bangkok (Thailand): Mahidol University, Faculty of Medicine Ramathibodi Hospital; 2011 Aug.
Myths & Truths on Standards
http://www.slideshare.net/nawanan/myths-and-truths-on-health-information-standards
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MythsWe don’t need standards Standards are IT people’s jobsWe should exclude vendors from thisWe need the same software to share dataWe need to always adopt international standards
We need to always use local standards
Myths & Truths on Standards
Theera-Ampornpunt (2011)
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Standards: Why?
The Large N Problem
N = 2, Interface = 1
# Interfaces = N(N-1)/2
N = 3, Interface = 3
N = 5, Interface = 10
N = 100, Interface = 4,950
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IT Management
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Balanced Focus of Informatics
People
Techno‐logyProcess
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Health IT: ของดี (อาจจะ) มีประโยชน์(แต่ก็อาจมีโทษ)
บริบท (local contexts) มีความสําคญัต้องมีการบริหารจัดการที่เหมาะสม
ประเด็นพิจารณา
อะไรคือบริบทที่เกี่ยวข้อง?จะจัดการมันอย่างไร?
ความเดิมตอนที่แล้ว...
85 The sailboat image source: Uwe Kils via http://en.wikipedia.org/wiki/Sailing
The destination
The boatThe sailor(s) & people on board
The tailwind The headwind
The direction
The speed
The past journey
The sea
The sail
The current location
Context
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Direction & Destination
รพ.มหาวิทยาลัย 900 เตียงVision เป็นโรงพยาบาลชั้นนําของ
ภูมิภาคเอเชียทีม่ีความเป็นเลศิใน
ด้านบริการ การศึกษา และวิจัย
รพ.เอกชน 200 เตียงVision เป็นโรงพยาบาล High Tech
High Touch ชั้นนําของประเทศ
87
“The Sail”
Carr (2004) Carr (2003)
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Strategic
Operational
ClinicalAdministrative
4 Quadrants of Hospital IT
CPOE
ADT
LIS
EHRs
CDSS
HIE
ERP
Business Intelligence
VMI
PHRs
MPIWord
Processor
Social Media
PACS
CRM
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Resources/capabilities
Valuable ?
Non-Substitutable?
Rare ?
Inimitable ?
NoCompetitive
Disadvantage
Yes
No Competitivenecessity
NoCompetitive
parity
Yes
Yes
NoPreemptiveadvantage
Yes
Sustainablecompetitiveadvantage
From a teaching slide by Nelson F. Granados, 2006 at University of Minnesota Carlson School of Management
IT As A Strategic Advantage
90
“The Sail”
รพ.มหาวิทยาลัย 900 เตียง
Vision เป็นโรงพยาบาลชั้นนําของภูมิภาคเอเชียทีม่ีความเป็นเลศิในด้านบริการ การศึกษา และวิจัย
Current IT Environment เป็น รพ.แรกๆ ที่มี HIS ซึ่งพัฒนาเอง และ
ต่อยอดจาก MPI, ADT ไปสู่ CPOE (แต่ยังขาด advanced CDSS) ระบบ HIS เข้ากับ workflow ของ รพ. เป็นอย่างดี
ปัจจุบัน ระบบ HIS ยังใช้เทคโนโลยีเดียวกับช่วงที่พัฒนาใหม่ๆ (20 ปีก่อน) เป็นหลัก มีการนําเทคโนโลยีใหม่ๆ มาใช้อย่างช้าๆ
รพ.เอกชน 200 เตียงVision เป็นโรงพยาบาล High Tech
High Touch ชั้นนําของประเทศ
Current IT Environment มี MPI, ADT, EHRs, CPOE แต่ยังมี
CDSS จํากัด
ยังไม่มี Customer Relationship
Management (CRM)
ยังไม่มี Personal Health Records
(PHRs)
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Resources/capabilities
Valuable ?
Non-Substitutable?
Rare ?
Inimitable ?
NoCompetitive
Disadvantage
Yes
No Competitivenecessity
NoCompetitive
parity
Yes
Yes
NoPreemptiveadvantage
Yes
Sustainablecompetitiveadvantage
From a teaching slide by Nelson F. Granados, 2006 at University of Minnesota Carlson School of Management
IT As A Strategic Advantage
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“The Sailors”
People
Techno‐logyProcess
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“The Sailors”
รพ.มหาวิทยาลัย 900 เตียง
บุคลากรมีอายุเฉลีย่ 42 ปี (range 20-65)
แผนก IT มีทั้งบุคลากรใหม่และทีเ่คยพัฒนาระบบ HIS ตั้งแต่แรกเริ่ม
แพทย์มีความเป็นตัวของตัวเองสูง, มักทํางานเอกชนด้วย, มี turn-over rate สูง
พยาบาลและวิชาชีพอื่นมักมองว่าแพทย์คืออภิสทิธิ์ชน และมีเรื่องถกเถียงกันบ่อยๆ
รพ.เอกชน 200 เตียง บุคลากรมีอายุเฉลีย่ 32 ปี
(range 20-57)
แผนก IT เข้มแข็ง
แพทย์ไม่ค่อยมี interaction กับ
บุคลากรอื่น, รายได้เป็นแรงดึงดูดหลัก
ผู้บริหารได้รับการยอมรับจากบุคลากร
ทุกวิชาชีพว่ามีวิสัยทัศน์และบริหารงาน
ได้ดี
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IT Outsourcing Decision Tree
Does service offer competitive advantage?
Is external deliveryreliable and lower cost?
Keep Internal
Keep Internal
OUTSOURCE!
Yes
No
Yes
No
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IT Outsourcing Decision Tree: Ramathibodi’s Case
Does service offer competitive advantage?
Is external deliveryreliable and lower cost?
Keep Internal
Keep Internal
OUTSOURCE!
Yes
No
Yes
No
Core HIS, CPOEStrategic advantages• Agility due to local workflow accommodations• Secondary data utilization (research, QI)• Roadmap to national leader in informatics
External delivery unreliable• Non‐Core HISExternal delivery higher cost• ERP maintenance/ongoing customization
ERP initial implementation,
PACS, RIS, Departmental
systems, IT Training
96Image source: Jeremy Kemp via http://en.wikipedia.org/wiki/Hype_cycle
http://www.gartner.com/technology/research/methodologies/hype‐cycle.jsp
Gartner Hype Cycle
97Rogers (2003)
Rogers’ Diffusion of Innovations: Adoption Curve
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Communications of project plans & progresses
Workflow considerations
Management support of IT projects
Common visions
Shared commitment
Multidisciplinary user involvement
Project management
Training
Innovativeness
Organizational learning
Theera‐Ampornpunt (2009, 2011) [Unpublished]
Hospital IT Adoption Success Factors
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Lorenzi & Riley (2004) Leviss (Editor) (2010)
Resources on Change Management
100
Healthcare is complex Health IT can benefit healthcare through
Information delivery
Process improvement
Empowering providers & patients
The world is moving toward health IT Management of hospital IT is crucial to success
Balance of “People, Process & Technology”
Know your organization (“context”)
Strategic mindset
Project & change management
Summary
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Patients Are Counting on Us...
Image Source: http://www.flickr.com/photos/childrensalliance/3191862260/
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Q & A...
Download Slides
SlideShare.net/Nawanan
Contacts
nawanan.the@mahidol.ac.th
www.tc.umn.edu/~theer002
groups.google.com/group/ThaiHealthIT
103
Ariely D. Predictably irrational: the hidden forces that shape our decisions. New York City (NY):HarperCollins; 2008. 304 p.
Blumenthal D. Launching HITECH. N Engl J Med. 2010 Feb 4;362(5):382‐5. Blumenthal D, DesRoches C, Donelan K, Ferris T, Jha A, Kaushal R, Rao S, Rosenbaum 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 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.
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.
Hersh W. Health care information technology: progress and barriers. JAMA. 2004 Nov 10:292(18):2273‐4.
References
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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 [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 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, 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 seven nations. Int J Med Inform. 2008;77(12):848‐54.
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Miller RA, Masarie FE. The demise of the "Greek Oracle" model for medical diagnostic systems. Methods Inf Med. 1990 Jan;29(1):1‐2.
Pongpirul K, Sriratana S. Computerized information system in hospitals in Thailand: a national survey. J Health Sci. 2005 Sep‐Oct;14(5):830‐9. Thai.
Rogers EM. Diffusion of innovations. 5th ed. New York City (NY): Free Press;2003. 551 p. Schoen C, Osborn R, Huynh PT, Doty M, Puegh J, Zapert K. On the front lines of care: primary care
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Theera‐Ampornpunt N. Thai hospitals' adoption of information technology: a theory development and nationwide survey [dissertation]. Minneapolis (MN): University of Minnesota; 2011 Dec. 376 p.
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