Transcript Standards and Medical Informatics

Standards and Medical Informatics
W. Ed Hammond, Ph.D.
President, AMIA
Vice-chair, HL7 Technical Steering Committee
Chair, Data Standards Working Group, Connecting for Health
Convenor, ISO TC 215 WG2
Professor-emeritus, School of Medicine
Professor-emeritus, Pratt School of Engineering
Adjunct Professor, Fuqua School of Business
Duke University
Duke University
A scenario …
Recently, at my exercise club, my blood glucose measured
112 mg/dl. This elevated value was sent to my composite
record then to my PCP and to me. When I logged onto my
computer, a flag indicated I had a message in my personal
mail at my PCP’s web site. The message ask me to schedule
an appointment soon because of the elevated glucose, as well
as it was time for my annual physical exam.
I accessed the clinic’s web site and scheduled an appointment
with my PCP for the next week. The system identified some
additional testing for me, and scheduled me 30 minutes
before seeing my PCP for the tests.
I also looked at my on record and noticed that my glucose
had been climbing over the past 12 years to its current level.
Duke University
I arrived at the clinic, entered my health card in to a kiosk
registering my arrival. My eligibility was automatically
checked and my health plan verified. I was directed to the
lab for the blood drawing. I was also assigned a number
which provided the linkage for me on this visit. Within 2
minutes of my scheduled time, a white board identifying me
by number directed me to Exam Room 10. Here the
provider performed the annual physical examination,
sharing a terminal between us, and discussing how she
proposed to deal with the elevated glucose with exercise
and weight reduction. Since my cholesterol was also
elevated, she decided to start me on Zocor. My dentist had
recently started me on an antibiotic that intensifies the
action of the cholesterol-reducing drug. My PCP suggested
that I complete the antibiotic before I start the Zocor. She
also scheduled me to return in 3 weeks to test my liver
function because of the drug.
Duke University
This information was put into my personal web page for
download into my personal health record.
The exercise program was fed directly into my exercise
machine, and my daily progress was monitored and recorded
into my personal record. I also gave permission for the data
to be uploaded to my PCP, since I thought the added pressure
of another eye watching me would increase the incentive for
my following the program.
I was also given, interactively, a personal diet to help control
my weight. I kept an on-line log in my personal health
record.
I also accessed information about the medication I had been
given to reduce my cholesterol. I read about side effects and
some of the controversy. I knew about the side effects;
however, I decided to continue the drug at least for the next
month.
Duke University
The Holy Grail of Medical
Informatics …
The Electronic Health
Record
aka …
Duke University
A changing world of health care
• Our world is expanding
– The tremendous expansion of diagnostic tests
available,
– The almost individualization of treatment, particularly
drugs
– a vastly expanding field of knowledge
• Solution demands use of information
technology in health
– to contain costs
– to reduce medical errors
– and to increase quality
• Consumers are becoming more educated and
want to be involved
• Integrated health systems are the trend
Duke University
A changing world of health care
• From a private, independent world to a
combined and integrated community
• From unconnected, disparate heterogeneous
systems to seamlessly connected interoperable
systems
• From technologically constrained to
technologically rich
• From hospital dominated to person-focused
systems: health vs illness
• From billing records to clinically enriched
databases
• From concealing data to sharing data
Duke University
Patients – the raison d’etre
• Patients are seen asynchronously in a variety of
settings; thus data must give a single, integrated
view of the patient.
• Need complete, appropriate data for decision
making, to reduce errors and improve care.
• The spectrum of patient care -- home, outpatient,
inpatient, intensive care, emergency, nursing homes
& specialties.
• Patients are mobile -- data must be accessible
internationally
• Patients move -- patient records follow and need to
be understandable and useable in the new settings.
Duke University
Why standards in health care?
• There is an assumed and inherent need to
share data in the health care setting. The data
are of many types and form and will be used for
multiple purposes.
• We must share both data and knowledge for
both improved health care and for economic
reasons.
• Sharing becomes economically possible only if
interoperability exists.
• Interoperability occurs only if a full set of
standards in health care exist.
Duke University
Standards are an everyday thing!
•
•
•
•
VCRs, audio tapes, CDs, DVDs
Bread size - to fit toasters
ATM machines
Air controllers use English language
•
•
•
•
•
Distance between rails for trains
60 cycle, 110 volt electricity
Shoe sizes, clothes, gloves
Side of road we drive on
Size of paper
Duke University
Too many standards ….
Duke University
Steps to making a standard
• Awareness of need for standard
• Critical mass of technical expertise to create
standard
– Must insure fairness and not competitive advantage to
any single vendor
– Expertise must be both technical and domain
• MUST involve vendors, providers, consultants,
government
• Global acceptance important in today’s market
• Vendor implementation usually driven by
consumer pressure to implement
• Visible reduction in cost and effort of interfaces
using standard necessary for buy-in
Duke University
Different kinds of standards
• Company
– DOS
– Windows
• Government
– NIST
– CMS
– HIPAA/NCVHS
• Consortium/Open Source
–
–
–
–
Unix
Linux
JAVA
M/Mumps
• Industry
• Voluntary Consensus
–
–
–
–
–
ASC X12
HL7
NCPDP
ASTM
IEEE
– DICOM
Duke University
Consensus Standards
•
•
•
•
•
•
•
•
•
Volunteer-driven
Not full-time commitment
Uneven levels of participation
Uneven levels of understanding
Required resolutions of negatives
Prone to compromise – leads to ambiguity
Funding constraints
Meet only a few times per year
Specialized balloting process (ANSI: requires
90% approval)
Duke University
How to get there from here …
why standards in health care?
• There is an assumed and inherent need to
share data in the health care setting. The data
are of many types and form and will be used for
multiple purposes. Traditionally, these uses
have been addressed independently and
redundantly.
• We must share both data and knowledge for
both improved health care and for economic
reasons.
• Sharing becomes economically possible only if
interoperability exists.
• Interoperability occurs only if a full set of
standards in health care exist.
Duke University
Why haven’t we done it?
• No accepted long term vision of what IT is.
• No proven value to those of make purchasing
and financial decisions.
• No widespread stakeholder buy-in.
• Not considered a core component of health
care.
• Resistance to change.
• Unwillingness to make decisions and take
action on controversial issues.
Duke University
What are the building blocks?
• Data
–
–
–
–
–
–
–
–
–
–
Patient-centered
Comprehensive
Aggregated
Organized
High data integrity
Timely
Structured, semantically understandable
Sharable
Accountable
Secure and private
Duke University
How might we use it?
• Information for …
–
–
–
–
–
–
–
–
–
–
–
Patient care
Prevention of medical errors
Improved quality of care
Consistency in care
Cost effective care
Shared understanding of health and health care
among patient and provider
Health surveillance and biodefense
Workflow management
Research
Epidemiology
Billing
Duke University
What and how can we learn?
• Knowledge
–
–
–
–
–
–
Clinical trials
Decision support
Disease demographics
Outcomes
Quality indicators
Evidence based medicine
Duke University
What do we get?
• Wisdom
– New models for health and health care
– More cost effective care
– Better understanding of disease and disease
processes
– Better relationship among stakeholders
– A happier, healthier world
Duke University
Why data standards? (1)
• Patient-centric EHR
– Complete, aggregate data about patient
• Patient summary problem list
• Current medications list
• Allergies
• Base demographics
• Selected clinical elements
• Reimbursement data
– Insurance
– Health Plan
Duke University
Why data standards? (2)
• Population Health Record
–
–
–
–
–
–
–
Outcomes data
Utilization data
Disease tracking
Detection of disease outbreaks
Detection of bioterrorism events
General health surveillance
Immunization
Duke University
Why data standards? (3)
• Reimbursement
–
–
–
–
–
Reimbursement rules
HIPAA transactions requirements
Automation of process
Easier audits for clinical justification
Reduction of use of human resources in
reimbursement process
– Analysis of treatment by multivariate parameters
Duke University
Why data standards? (4)
• Research
– Clinical Trials
– Drug Trials
– What diseases are prevalent
• By region
• By occupation
• By category
– Variation in outcomes
• Method of treatment
• Provider
• Region
Duke University
Classes of Standards
• External standards not unique to health care
– Examples include communication standards, Internet
standards, LAN standards, XML/HTML standards, security
standards, etc.
• Application level health data standards absolutely
necessary for aggregating and sharing data
• Enhancement health-related standards that improve the
process and extend the use of IT. This group includes
clinical content and clinical knowledge standards.
Duke University
Classes of Standards - 1
• Basic communication standards that are not specific to
health
– Communication standards
• Internet standards
• LAN standards
• Web Protocols
– XML
– Security standards
– Authentication standards
– Biometric standards
– Encryption standards
– Digital signature
• Groups producing or influencing these standards
– W3C, IETF, OMG, OASIS, others
Duke University
Classes of Standards - 2
• Standards that relate to the definition, style, and
naming of the data itself
–
–
–
–
–
–
–
Reference Information Model (RIM)
Data types
Terminology
Clinical Documents
Clinical Templates
Data element master set
Business Rules that identify what data elements are
collected: how, when and by whom [implementation
manuals, conformance documents, metadata
dictionaries}
Duke University
Classes of Standards - 3
• Process standard for message development
framework
• Standards associated with data interchange
–
–
–
–
–
HL7 V2.4, V2.4 (XML) and in ballot V2.5
HL7 Version 3
DICOM – imaging domain
IEEE/CEN/ISO – medical devices
Others
Duke University
Classes of Standards - 4
• Standards associated with the Electronic Health
Record
–
–
–
–
–
Architecture, content, format and form, purpose
Privacy and confidentiality
Access
Persistence
Control
Duke University
Standards Related to EHR - 5
• Decision Support Rules
–
–
–
–
–
Arden Syntax, GLIF, GEM, Prodigy
Clinical algorithms
CPOE
ePrescribing
Reimbursement Rules
Duke University
Interoperability Standards (1)
• Personal data absolutely MUST be identified
when it is sent from the source to the
aggregating data base
• That is best (essentially error free)
accomplished when there is a single, unique
personal identifier
• Because of privacy concerns we have not yet
accepted this solution
Duke University
Interoperability Standards (2)
• Reference Information Model
– Object Model that provides framework for the
exchange and sharing of health data. EHR model must
be based on this model
– HL7 has created such a model, accepted
internationally, that is now becoming stable
– HL7 model is high level requiring subsequent refined
models for communications and storage of data.
Duke University
Reference Information Model
• An information model needs to underpin all
architecture and terminology developments to
ensure consistency of approaches and a shared
understanding.
Liaw and Grain in a government report
Duke University
HL 7 RIM Core Classes
Relationship
Link
0..*
0..*
1
Entity
Organization
Living Subject
Material
Place
Health Chart
0..*
1
Act
Relationship
0..*
0..*
1
Role
Patient
Employee
Practitioner
Assigned
Practitioner
Specimen
1
0..*
1
Participation
1
0..*
1
Act
Referral
Transportation
Supply
Procedure
Condition Node
Consent
Observation
Medication
Act complex
Financial act
Duke University
Data Element Definition Set
• Defines every data element that will be
collected including when, how and in what form
• Data must be structured
• Links data elements to vocabulary sets as well
as RIM
• Some work being done in this area by Health
Informatics Standards Board (ANSI) and
Australia
Duke University
Data Types
• Simple data types
– Numeric, strings, dates, currency, etc.
• Complex data types
– Addresses, names, coded data elements
• Tightly coupled with the RIM
• Must be consistent with terminology
• Must be used (stored) in the EHR as defined by
data type
Duke University
Terminology
• Every data element that will be shared must be
defined and coded in a terminology set (text
modifiers may be permitted)
• Problem is the existence of too many
terminologies, none of which is perfect
• Terminologies may be mapped but costs more
money, creates errors and results in the loss of
information
• Terminologies required for use must be free,
controlled and maintained
• We must have a single, domain-model-based,
constantly maintained, and freely distributed
world-wide. terminology
Duke University
Drug Terminologies
• Significant progress has been made recently in
creating a drug terminology standard. Effort
includes starting with VA drug terminology set,
adopted by FDA and assigned NDC codes, and
mapped into UMLS. HL7 route, form and
application device sets are included.
• NLM and SNOMED have apparently reached an
agreement that will make SNOMED freely
available for use in the U.S.
Duke University
Clinical Document Architecture
• XML-based definition of clinical documents
such as discharge summaries, op notes,
progress notes, radiology reports, etc.
• HL7 has ANSI approved standards. Work is
based on 3 levels: (1) header; (2) header plus
body structure and section headings; (3)
element content specification and identification
Duke University
Conveying complex concepts
• Clinical Data Model or Clinical
Templates
– Defines detail clinical object
structures
– Permits constraints on objects
– Examples
•
•
•
•
•
Clinical lab battery
Heart Murmur
Blood pressure measurement
Physical exam for chest pain
Protocol for sore throat
• Require registry
Duke University
Decision Support
• For defining knowledge and decision support
algorithms
• HL7 brings together several existing efforts in
this area
–
–
–
–
Arden Syntax
Prodigy (UK)
Guideline Interchange Format (GLIF)
GEM
Duke University
Implementation/Conformance
• Most frequently, ambiguity and options remain
in standards at all levels. Total interoperability
requires a precise definition of what will be sent
to whom under what circumstances.
• One example of this approach is the Emergency
Department implementation manual called
DEEDS.
• The Centers for Disease Control has created a
reporting system for health surveillance known
as NEDSS will also provide this level of
specification.
Duke University
Electronic Health Record
• Requires defining exactly what standards are
required
• Issue is where does standard stop and vendor
proprietary interests start.
• Includes some architecture and probably
categorization of data elements stored.
• Several efforts underway including Good
Electronic Health Record (Australia and
Europe), HL7 and AMIA
Duke University
Reusable Components
• HL7 Clinical Components Object Working
Group (CCOW)
• Defining standards for reusable component
software
Duke University
Imaging Standards
• DICOM is international standard for images and
pictures and similar media
• JTC1 defines standards for JPEG and MPEG
• DICOM also does structured reports similar to
HL7 clinical documents but for radiology and
imaging reports. Efforts are being coordinated.
Duke University
Medical Devices
• IEEE provides leadership in this area.
• Includes bed-side devices and covers primitive
layer of interface up to application.
• Standards include cable, wireless, infrared
connectivity
• Standards become international through ISO
Duke University
Security Standards
• At communications level, mostly developed
outside health industry but with influence. IETF
playing major role.
• Digital Signature and PKI standards are being
influenced by health-related participation.
Duke University
Other Standards
•
•
•
•
•
Waveforms
Data Integrity Standards
Presentation Standards
Icon Standards
Functionality standards
Duke University
What is an EHR? … my definition
• It is not a clinical repository.
• It’s purpose is to enhance the health and enable
the care of the individual. It’s contents are
solely justified for that purpose. When data
ceases to contribute, it is removed.
• Much of the data in the inpatient setting has
limited persistence - usually the more intense
the care, the shorter the persistence.
• There are other repositories – a data warehouse
that does contain and retain everything.
• The EHR documents maintenance of care,
diagnostic and treatment processes, health
status.
Duke University
Population record
• A summary record from all sites and sources of
care
• Linkage of data for new sites as care as well as
population surveillance, research, quality,
analysis
• Data arrives as identified data, available as
disidentified
Duke University
The Personal Record
• Model to meet consumer needs and
understanding
• Focus on functionality and work management,
not clinical repository
• Information display should be driven by
intelligent query and understanding of needs
• Couple with appropriate education
• Home entry of data - direct or sensors
• Person-controlled release
• Customizable
Duke University
Business Linkages
Hospital
Intensive
Care
Nursing
Home
Emergency
Department
Ambulatory
Care
Clinic
Patient role in control?
Duke University
EHR Interoperability Diagram
Billing/Claims
Profile
Enterprise
Data
Warehouse
Personal
EHR
Profile
Patient
Encounter
Research
Database
Institution
Provider
EHR
Database
Profile
Profile
Profile
Disease
Registry
Longitudinal
EHR
Profiles contain business rules
Duke University
Population or Composite Summary EHR
Patient
Encounter
Provider
EHR
Database
Population
Profile
Patient
Encounter
Population
EHR
Provider
EHR
Database
Population
Profile
Duke University
Download Process
Double
Encryption
Silicon
Encoder
ID
HL7
Message
Identifying Data,
name, address, etc.
Identifying Data,
Translated (e.g. Zip).
ID
Sensitive
Demographic
Data
Encrypted ID
Aggregated
Summary
Longitudinal
EHR
Summary Data
Duke University
Summary Longitudinal Record
Patient
controlled
access
Access log
Access list
permit
by
provider
group
clinic
other
Summary
Longitudinal
Record
Feeds PH
surveillance,
patient safety,
epidemiology
Duke University
The future
• I am always a person – a complete entity to the
provider I am seeing.
• I don’t have to worry that my known allergies
will be missed.
• I have faith that all decisions will be made by
someone who knows all about me, my
preferences, and my health.
• My data will be interchangeable and
understandable.
• My data will be secure and appropriately
protected.
Duke University