The Electronic Health Record: What is it's potential for enabling health?

Transcription

1 The Electronic Health Record: What is it's potential for enabling health? W. Ed Hammond Professor Emeritus Duke University PEP 2007 Sāo Paulo, Brazil 7 October 2007 Chair, HL

2 What I m I m going to talk about My views of the EHR Why we need help in health care a system most think is broken The evolution of the EHR: from paper to computer What can the EHR do for health? Issues that must be overcome What we need to do What the future might hold 7 Oct 2007 ehammond PEP

3 7 Oct 2007 ehammond PEP

4 Today s s patient care documentation Paper based, free form, unstructured Ranges from illegible unstructured handwriting to dictated notes and typed to machine generated Organized into sections depending on purpose or test, source and time Arranged loosely in book or folder by some category and chronologically Data rarely removed and may exist in multiple volumes Available less that 35% of the time 7 Oct 2007 ehammond PEP

5 How does provider use paper record? Flips through pages looking for specific pieces of data Search based on suspicion and interest Time pressures shorten search depth Why do providers miss so many important pieces of data? How much does the paper record contribute to poor health care? 7 Oct 2007 ehammond PEP

6 Current approaches to EHR The electronic copy is a duplication in concept of the paper record. We store data the way we did with the paper record, usually unstructured and usually in the form the data is generated, i.e. documents Retrieval of data follows the same philosophy as the paper system Flips through pages looking for specific pieces of data Search based on suspicion and interest Time pressures shorten search depth Why do providers miss so many important pieces of data? It is almost as difficult to get data out of an EHR as it is with the paper record 7 Oct 2007 ehammond PEP

7 We further complicate by Clinical Data Repository Data Warehouse Hospital Information System Billing Records Research Databases Disease-specific Databases (diabetes) Site specific databases (emergency room) Department-specific Databases (Lab, Pharmacy) Electronic health record??? 7 Oct 2007 ehammond PEP

8 Why is IT in healthcare a high priority? Volume of data about a patient has increased tremendously over the past decades Increasing number of diagnostic tests Increasing numbers and modality of images Genetic testing From bytes to kilobytes to megabytes to gigabytes to terabytes to 7 Oct 2007 ehammond PEP

9 Why is IT in healthcare a high priority? Number of choices in treatments increasing significantly Treatments are becoming more personalized Patients are becoming more knowledgeable and want to participate in decisions relating to their own care Patient safety has become a priority Costs of care continue to increase High performance metrics and high quality care are in demand 7 Oct 2007 ehammond PEP

10 Why is IT in healthcare a high priority? Sources and amount of knowledge have increased exponentially over the past decades 900,000 Amount of new Biomedical knowledge articles per introduced year each year 10,000 would take more Randomized than controlled 200 years trials to annually assimilate into one s practice reading and understanding two papers 4,000 each Guidelines night current available Undergraduate 150 Disease and management graduate profiles education is based on 20,000 out of date concepts Genes Continuing medical education is inadequate 1,700 Disease associated mutations We can t learn fast enough to be effective New knowledge requires new skills and new understanding Current model is evidence-based medicine 7 Oct 2007 ehammond PEP

11 Why we need a solution Patient safety Increased concerns related to safety of prescription drugs Demand for quality: In U.S. over 54% receive appropriate care Cost containment in face of increasing costs of healthcare Efficient and effective health care delivery Health surveillance and biodefense Natural disaster Accommodating an aging and mobile population Effective management of chronic disease Equal access to care - uninsured Consumer sophistication in health Increasing importance of secondary uses of data translational medicine Movement from illness care to wellness care Practice of medicine that is predictive, personalized and preemptive 7 Oct 2007 ehammond PEP

12 Why it has not been easy Time-pressure of activities Tasks are frequently interrupted Workflow is idiosyncratic Managing several problems per patient and several patients at once Interacting with many professionals to get things done Working under pressure of life and death and uncertainty Change is difficult to accept 7 Oct 2007 ehammond PEP

13 Evolution of EHR Efforts to computerize the patient record began in the 1960s. Early focus was on administrative, billing, and hospital systems Early systems were very expensive Early systems often resulted in failure No one really knew what a computerized patient record should look like and still don t 7 Oct 2007 ehammond PEP

14 Evolution of the EHR IOM publication in 1991 resulted in creation of computer-based patient record Little interest in outpatient systems Deployed systems change slowly No business case established, no funding model, little evidence of ROI Value underplayed Now the focus in most countries but still an open problem 7 Oct 2007 ehammond PEP

15 Technology vs Use of Technology Growth of Technology Rate of Application Rate of application of technology significantly lags availability of technology today. 7 Oct 2007 ehammond PEP

16 Setting The Stage In today s world, the EHR consists of any data in any form, largely unorganized and unfiltered. It ranges from document images to unstructured narrative text to coded data using a variety of coding systems. The codes come from a variety of controlled vocabularies but are primarily local. Within a single institution, multiple terminologies are used and neither data elements nor terminologies are defined. 7 Oct 2007 ehammond PEP

17 Today s s Interoperability Even within a single institution, data from different departments and services cannot be merged because of the differences in terminology, the differences in data elements collected, the differences in vendors, and the differences in how vendors implement standards. No existing enterprise, regional or national systems are able to merge data from different systems. Usually the data is encapsulated by site and presented by views. 7 Oct 2007 ehammond PEP

18 Where the EHR must serve Acute Care Chronic Care Wellness Care Data Data Data Outcome Evaluation Control Treatment Outcomes Treatment Diagnoses Symptoms Behavior Modification Prevention Screening Decision Support Decision Support Decision Support Genomic Medicine HOME HEALTH NURSING HOME & LTC INTENSIVE CARE HOSPITAL EMERGENCY SPECIALTY PRIMARY 7 Oct 2007 ehammond PEP Early responders EMT Pharmacy

19 Approaches to EHR Today Document-centric (paper converted to images) Clinical data repository stored as generated by many systems, usually free form narrative Stored as documents (CDA) Structured EHR with Structured Data Only store in EHR what varies with patient Only store in EHR what is useful for patient care Use codes; permit free text modifiers Store by category not by transaction Complex structures defined by clinical templates or archetypes Document structure via clinical document architecture Supports non-textual data such as images, videos, sounds, drawings Non-patient-specific data stored in external, shared databases 7 Oct 2007 ehammond PEP

20 So, how do we get there? Interoperability is mandatory for the integration of data and must exist throughout the collection, analysis, use and presentation of the data. Interoperability demands standards. Functional Interoperability Semantic Interoperability Business Interoperability 7 Oct 2007 ehammond PEP

21 Standards for interoperability Data Elements (HL7, CEN, ASTM, CDISC, cabig, DCM, ) A single term for each element Data type Expert-defined, precise definition Units Value set of possible values (function of data type) Structures built from data elements (HL7, CEN, openehr) Templates or archetypes Compound elements, complex structures Clinical Statements Structured Clinical Documents (CDA, CCD, CCR) Transport Standards (data, audio, images, waveforms) (HL7, CEN, ASTM) Communication Standards Security and Confidentiality Standards (Authentication, Digital Signature) EHR Content, Architecture and Functional Requirements; Certification Decision Support including Research protocols and guideline specifications Medical devices, barcodes Patient identifiers, provider identifiers, profiles for data interchange (XDS) Implementation guides, tool sets 7 Oct 2007 ehammond PEP

22 Further thoughts For interoperability to occur, all of the components must be present. The puzzle is not complete until all the pieces are in place. Funding must be adequate, complete and sustained. The required funding will be reasonable, with savings. Change management and training must be funded. Time is important. Simple systems are the best. Complex systems often result from not understanding the problems and focus on the solution. Reusability of data provides the return on investment. Understand what and how the data is to be used. Stakeholders must communicate and work together. 7 Oct 2007 ehammond PEP

23 The EHR System EHR Architecture designed for fast and varied retrieval and presentation; independent of collection modality Content focused on informational value; contains only data contributing to current and future health of person; store only what varies with patient Structured for unambiguous clarity, understanding and interoperability Support common core throughout varied sites of care One person, one EHR Imbedded Decision Support Generally transparent to user Rich in functionality Service functionality varies with site Includes workflow and process management 7 Oct 2007 ehammond PEP

24 Multiple Views of EHR Institutional view Site specific (inpatient, outpatient, emergency, long term, home) Provider centric Shared view Aggregated and complete view of patient Supports push and pull scenarios Data centric Personal view Appropriate clinical data organized around personal health plan Management of person s health Supports a personal health plan and provides decision support specific to person Patient centric All derived from a common source. 7 Oct 2007 ehammond PEP

25 The Inpatient View Deals with acute events and data has mostly immediate value for decision making and intervention. After intervention occurs, data has less or no value (short persistence). Required functionality deals primarily with service activities ordering, results review, rounding, admission and discharge More tolerance for time impact of IT on providers Administrative support provides value to physicians providing data without extending effort More complex environment More interactive 7 Oct 2007 ehammond PEP

26 The Inpatient View Presentation of data for direct patient care Ease documentation requirements Evidence-based care pathways/clinical guidelines/protocols Multiple views and filtered views of data, usually time-oriented Computer-assisted creation of discharge summaries Task and workflow management Automatic linkage to task management Coupled to scheduling for radiology and diagnostic tests Patient location, patient status Asynchronous communications among healthcare providers and workers 7 Oct 2007 ehammond PEP

27 Outpatient View Wellness over illness Trend data important Chronic disease management Persistence of data is longer Interaction time is important Data content matches population record and personal health record 7 Oct 2007 ehammond PEP

28 Population or Summary Record A summary record from all sites and sources of care Linkage of data for new sites of care as well as population surveillance, research, quality, analysis Data arrives as identified data, available as de-identified Provides Utilization data Accurate and timely statistics about health and disease in population Accurate reporting of events, disease, and outcomes Early discovery of outbreaks, new disease, bioterrorist attacks Immunization, infectious disease tracking Creation of on-the-fly randomized clinical trials 7 Oct 2007 ehammond PEP

29 Personal Health Record Model to meet consumer needs and understanding and permit individual responsibility for planning and execution of their own care. Source for personal health plan Focus on individual responsibilities, functioning, behavior and work management not just data repository. Contains personalized linkage to knowledge, particularly in disease and treatment options. Focused on individual data: my data, my meanings Information displays driven by query, personal preferences, and behavioral needs. Some home entry of data coupled with controlled downloads from provider encounters plus personal sensors and medical devices. Person-controlled release. Provide encouragement for good health 7 Oct 2007 ehammond PEP

30 Personal Health Record PHR has three components Clinical data that will be similar to the summary health record plus data that is entered directly or by sensor into the PHR. Clinical data is downloaded from sites of care. Data may be uploaded to site EHRs. Management of a person s health including prompts for appointments, medication refills, screening tests, immunizations, etc. Decision support algorithms suggest what provider should be doing in terms of frequency of visit, tests, etc. Access to knowledge that is tailored to a person s needs and is driven by clinical data. 7 Oct 2007 ehammond PEP

31 Literature Mining Expert Panel Clinical Biomarkers Genomics Risk Assessment Personal Health Plan Imaging Outcome Tracking Home Enhancement Tools PATIENT PHYSICIAN HEALTHCARE TEAM Lifestyle Pharmaceuticals Procedures Other Investigations 7 Oct 2007 ehammond PEP From: Snyderman, Williams

32 So the EHRS must Support multiple clinical domains and therapeutic areas Become a part of the patient care team and provide data and give advice supported by literature when and where appropriate Filter and screen superfluous data; present data appropriate for circumstances Support both push and pull data interchange Enhance belief of data integrity, sound decision support, competent workflow management, and provide adequate privacy and security Provide data that is reusable 7 Oct 2007 ehammond PEP

33 The value Patient care Completeness, timely, linkages, focus, consistency, enabling Safety, quality, cost, effectiveness, efficiency, accessibility, usability Supports wellness care as well as illness care Satisfaction and quality of life over age Health surveillance, support in natural disasters Research Education Management of national resources Evaluation 7 Oct 2007 ehammond PEP

34 Difficult Lessons You may have to start more than once Evolution is difficult and expensive Design generic don t lock in a particular technology Make EHR a goal and not a strategy Encourage consistency and systematic approach in design Change as necessary for best results; change will happen. Data elements/terminology: must get it right Security and privacy must be adequately addressed Don t confuse flexibility and customization Best of breed vs single, integrated system Avoid surprises keep all informed 7 Oct 2007 ehammond PEP

35 What we must do Fix terminologies so users have a single terminology for all purposes! Mapping is not a solution! Commit to a clear national strategy and define a process to implement and refine that strategy Government take leadership in defining the standards, the terminology, the infrastructures for regional and national networks, and other enablers to provide national and global interoperability. Create a deadline by which all should be using common, structured data. Adopt modular, growable structures so we can build functionality over time. Start with intra-institutional interoperability first. Create tools to enable change and transition to what is required. 7 Oct 2007 ehammond PEP

36 Issues Is EHR for humans, computers or both? Our approach is often fragmented in content, function, records, and use. What is the role of terminology? Why do we want structured data? Natural language vs structured data Clinical Document Architecture vs EHR Record sharing vs record aggregation Send it all then selected entry by receiving site We ignore the potential for unforeseen consequences. 7 Oct 2007 ehammond PEP

37 What do we want? An aggregated, comprehensive electronic health record that provides appropriate data at the point and time of care (filtered) An integrated decision support system that delivers appropriate knowledge at the point and time of care in a non-invasive manner A system that provides an easy and natural humancomputer interface A system that supports logical workflows A system that enhances provider/patient interactions forming a responsible partnership A system that is affordable and maintainable (KISS) 7 Oct 2007 ehammond PEP

38 What do we want A system that helps not hinders A system that assures patient safety and insures quality care A system that supports public health Health surveillance Epidemiology data in my area of care Disease prevalence by region, age, gender, race, social status A system that enables transitional medicine; shorten time from bench top to bedside 7 Oct 2007 ehammond PEP

39 What the future might bring An EHR designed to take full advantage of technology and embraces new concepts Push technology that delivers what the provider needs in form, time, content, and based on the next event Dashboard presentations based on closed loop systems Providers not only accept EHR but change the way they practice medicine (a necessity) Connectivity and completeness Enables accessibility wherever Reusability Establish and track metrics for health outcomes, quality of care, performance, access, disparities, and efficiency Permits projects for resource requirements for health care 7 Oct 2007 ehammond PEP