590 likes | 754 Views
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
E N D
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
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.
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.
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.
The Holy Grail of Medical Informatics … The Electronic Health Record aka …
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
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
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.
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.
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
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
Company DOS Windows Consortium/Open Source Unix Linux JAVA M/Mumps Industry DICOM Government NIST CMS HIPAA/NCVHS Voluntary Consensus ASC X12 HL7 NCPDP ASTM IEEE Different kinds of standards
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)
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.
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.
What are the building blocks? • Data • Patient-centered • Comprehensive • Aggregated • Organized • High data integrity • Timely • Structured, semantically understandable • Sharable • Accountable • Secure and private
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
What and how can we learn? • Knowledge • Clinical trials • Decision support • Disease demographics • Outcomes • Quality indicators • Evidence based medicine
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
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
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
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
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
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.
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
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}
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
Classes of Standards - 4 • Standards associated with the Electronic Health Record • Architecture, content, format and form, purpose • Privacy and confidentiality • Access • Persistence • Control
Standards Related to EHR - 5 • Decision Support Rules • Arden Syntax, GLIF, GEM, Prodigy • Clinical algorithms • CPOE • ePrescribing • Reimbursement Rules
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
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.
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
RelationshipLink Act Relationship 0..* 0..* 0..* 0..* 0..* 1 0..* 1 1 0..* 1 1 1 1 HL 7 RIM Core Classes Entity Role Participation Act Referral Transportation Supply Procedure Condition Node Consent Observation Medication Act complex Financial act Patient Employee Practitioner Assigned PractitionerSpecimen Organization Living Subject Material Place Health Chart
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
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
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
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.
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
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
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
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.
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
Reusable Components • HL7 Clinical Components Object Working Group (CCOW) • Defining standards for reusable component software
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.
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
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.
Other Standards • Waveforms • Data Integrity Standards • Presentation Standards • Icon Standards • Functionality standards
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.
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