Electronic Health Record

Transcription

1 Electronic Health Record Introduction to Biomedical Informatics William Hersh Copyright, 2010 Oregon Health & Science University Amatayakul, M., Brandt, M., et al. (2001). Definition of the health record for legal purposes. Journal of AHIMA, 72(9): 88A 88H. Anonymous (1999). Uniform Electronic Transactions Act. Chicago, IL, National Conference of Commissioners on Uniform State Laws. Anonymous (2000). Electronic Signatures in Global and National Commerce Act. Anonymous (2003). Key Capabilities of an Electronic Health Record System. Washington, DC, National Academies Press. Anonymous (2004). HL7 EHR System Functional Model: A Major Development Towards Consensus on Electronic Health Record System Functionality. Ann Arbor, MI, HL7. SWhitePaper.zip. Anonymous (2006a). The Legal Electronic Medical Record. Chicago, IL, Healthcare Information Management Systems Society. Anonymous (2006b). The Value of Personal Health Records A Joint Position Statement for Consumers of Health Care. Bethesda, MD, American Medical Informatics Association. amiaphrstatement.pdf. Anonymous (2007a). OpenMRS Manual, OpenMRS. Anonymous (2007b). Selecting a Practice Management System. Washington, DC, American College of Physicians. Anonymous (2008). Physician s Guide to Certification for 08 EHRs. Chicago, IL, Certification Commission for Healthcare Information Technology. Anonymous (2009). An Introduction to Health IT Certification. Chicago, IL, Certification Commission for Healthcare Information Technology. Bates, D., Ebell, M., et al. (2002). A proposal for electronic medical records in U.S. primary care. Journal of the American Medical Informatics Association, 10: Bates, D., Kuperman, G., et al. (2003). Ten commandments for effective clinical decision support: making the practice of evidence based medicine a reality. Journal of the American Medical Informatics Association, 10: Beale, T. and Heard, S. (2007). Archetype Definitions and Principles, The openehr Foundation. pdf. Boyd, A., Hosner, C., et al. (2007). An 'honest broker' mechanism to maintain privacy for patient care and academic medical research. International Journal of Medical Informatics, 76:

2 Brailer, D. (2005). Interoperability: the key to the future health care system. Health Affairs, 24: W5 19 W Brown, S., Lincoln, M., et al. (2003). VistA U.S. Department of Veterans Affairs national scale HIS. International Journal of Medical Informatics, 69: Carter, J., Backman, C., et al. (2009). The Legal Health Record in the Age of E Discovery. Chicago, IL, Healthcare Information Management Systems Society: in press. Colias, M. (2005). Disease registries. Hospitals & Health Networks. February 15, NewsArticle/data/0502HHN_FEA_Chronic_Care&domain=HHNMAG. Dick, R., Steen, E., et al., eds. (1997). The Computer Based Patient Record: An Essential Technology for Health Care, Revised Edition. Washington, DC. National Academies Press. Dolan, P. (2008). Is your EMR legal? A document can look like a medical record, but not meet the legal definition. American Medical News. October 13, Dorr, D., Wilcox, A., et al. (2006). Implementing a multidisease chronic care model in primary care using people and technology. Disease Management, 9: Dougherty, M. (2008). How legal is your EHR? Journal of AHIMA, 79(2): Fischetti, L., Mon, D., et al. (2007). Electronic Health Record System Functional Model, Release 1, February 2007, Reader s Guide. Ann Arbor, MI, Health Level Seven. onal_model_r1_final.zip. Frieden, T. and Mostashari, F. (2008). Health care as if health mattered. Journal of the American Medical Association, 299: Friedman, C., Shagina, L., et al. (2004). Automated encoding of clinical documents based on natural language processing. Journal of the American Medical Informatics Association, 11: Greenfield, S. and Kaplan, S. (2004). Creating a culture of quality: the remarkable transformation of the Department of Veterans Affairs Health Care System. Annals of Internal Medicine, 141: Handler, T., Holtmeier, R., et al. (2003). HIMSS Electronic Health Record Definitional Model. Healthcare Information Management Systems Society. Accessed: July 18, Häyrinen, K., Saranto, K., et al. (2008). Definition, structure, content, use and impacts of electronic health records: a review of the research literature. International Journal of Medical Informatics, 77: Hibble, A., Kanka, D., et al. (1998). Guidelines in general practice: the new Tower of Babel? British Medical Journal, 317: Hoffman, S. and Podgurski, A. (2008). Finding a cure: the case for regulation and oversight of electronic health record systems. Harvard Journal of Law & Technology, 22(1). Hripcsak, G., Friedman, C., et al. (1995). Unlocking clinical data from narrative reports: a study of natural language processing. Annals of Internal Medicine, 122: Kolata, G. (2005). U.S. Will Offer Doctors Free Electronic Records System. New York Times. July 21, Kuperman, G. and Gibson, R. (2003). Computer physician order entry: benefits, costs, and issues. Annals of Internal Medicine, 139: Litvin, C. (2007). In the dark the case for electronic health records. New England Journal of Medicine, 356:

3 Mamlin, B., Biondich, P., et al. (2006). Cooking up an open source EMR for developing countries: OpenMRS a recipe for successful collaboration. Proceedings of the AMIA 2006 Annual Symposium, Washington, DC. American Medical Informatics Association Maviglia, S., Zielstorff, R., et al. (2003). Automating complex guidelines for chronic disease: lessons learned. Journal of the American Medical Informatics Association, 10: Metzger, J. (2004). Using Computerized Registries in Chronic Disease Care. Oakland, CA, California Health Care Foundation. Meystre, S. and Haug, P. (2006). Natural language processing to extract medical problems from electronic clinical documents: performance evaluation. Journal of Biomedical Informatics, 39: Meystre, S., Savova, G., et al. (2008). Extracting Information from Textual Documents in the Electronic Health Record: A Review of Recent Research, , in Geissbuhler, A. and Kulikowski, C., eds. IMIA Yearbook of Medical Informatics Stuttgart, Germany. Schattauer. Morrissey, J. (2006). A Day in the Life of a Medical Record. Chicago, IL, National Alliance for Health Information Technology. Rishel, W., Handler, T., et al. (2005). A Clear Definition of the Electronic Health Record. Stamford, CT, Gartner Corp. Safran, C., Bloomrosen, M., et al. (2007). Toward a national framework for the secondary use of health data: an American Medical Informatics Association white paper. Journal of the American Medical Informatics Association, 14: 1 9. Sager, N., Friedman, C., et al. (1987). Medical Language Processing: Computer Management of Narrative Data. Reading, MA. Addison Wesley. Tierney, W., Rotich, J., et al. (2007). The AMPATH medical record system: creating, implementing, and sustaining an electronic medical record system to support HIV/AIDS care in western Kenya. Studies in Health Technology and Informatics: Weed, L. (1969). Medical Records, Medical Education, and Patient Care. Chicago. Year Book.

4 Electronic Health Record Introduction to Biomedical Informatics William Hersh Copyright, 2010 Oregon Health & Science University Some early innovations came from Mayo Clinic All physicians kept all their notes in leatherbound ledger In 1907, moved from physician centered to patient centered record Mayo was also pioneer in defining data elements to be recorded, forerunner of modern efforts in epidemiology and classification 1 4 History and perspective of the medical record Data can be organized as Practitioner (physician) centered Patient centered Orientations (not mutually exclusive) include Time oriented organized chronologically Department oriented organized by department Problem oriented organized by focus on problems Some terminology of the medical record Electronic health record (EHR) subsumes Electronic medical record (EMR) Computer based patient record (CPR) Some other terms of note Practice management system (PMS) Patient registry Personal health record (PHR) Problem oriented medical record (POMR) Legacy systems 2 5 History and perspective (cont.) Earliest medical records were physician oriented Hippocrates said over 2,500 years ago that the medical record should Accurately reflect course of disease Indicate possible causes of disease Before era of widespread medical diagnostic testing, record consisted mostly of observations The problem oriented medical record Proposed by Weed (1969) All entries grouped under particular problems An encounter for each problem is organized under four headings Subjective what patient reports Objective what clinician observes or measures Assessment what clinicians assesses Plan what clinician plans to do Most common usage is to have entire encounter organized by SOAP format, not individual problems 3 6 1

5 The modern day medical record Mixture of patient and problem oriented approaches In general, each provider or institution maintains its own record The creator of the medical record is assumed to be its owner, although patients can request access In the United States, is still predominantly paperbased Or even worse, it is hybrid, with some data on paper, some electronic, and some on both media Some limitations of the paper based record Summarized by Dick (1997), recently exemplified by A Day in the Life (Morrissey, 2006) In the Dark (Litvin, 2007) Single user one person at a time Disorganized especially for complex patients Incomplete reports missing or lost, some providers not sharing their reports with the rest Insecure no audit trail, easily copied or stolen 7 10 Flow of information in primary care practice (Bates, 2002) And then there is handwriting Can you decipher these orders? 8 11 Additional challenges in the modern era Coordinating care requires better communication among providers (Dorr, 2006) Increasing cost of care requires justification and documentation of expenditures Patients change plans, so their records should be portable US spends several $B per year copying medical records Informed consumers desire more participation in care decisions, which includes access to their records They also want security and other protections of their information No single vendor has complete solution Many take best of breed approach to matching components Some limitations (cont.) Illegibility Coumadin vs. Avandia (courtesy of David Bates, MD) 25 U/hr vs. 25 cc/hr vs.??? (courtesy of Rainu Kaushal, MD, MPH)

6 But there are still many conveniences with paper and/or writing All functions should address five health care quality criteria Improve patient safety Support delivery of effective patient care Facilitate management of chronic conditions Improve efficiency Have feasibility of implementation Definitions and attributes of the EHR some key documents IOM, Key Capabilities of an Electronic Health Record System (2003) Consensus based on IOM reports HIMSS, Electronic Health Record Definitional Model (Handler, 2003) HL7, System Functional Model (HL7, 2004; Fischetti, 2007) Attempt to define features and functions in an EHR system Gartner Clear Definition (Rishel, 2005) Research review of definitions, content, and use (Häyrinen, 2007) (Some) key features of EHR (Frieden, 2008) Standardized essential data elements Incorporate data from outside systems Facilitate medication reconciliation Registry reporting Clinicaldecision support at point of care Automated quality measurement Support for patient self management Interface with public health services Systematic outcomes evaluation Linking to community resources IOM key capabilities of EHR Health information and data Result management Order management Decision support Electronic communication and connectivity Patient support Administrative processes Reporting and population health management Other definitions and attributes for the EHR Data flow Practice management systems Registries Legal EHR

7 EHR data flow (typically in hospitals or large clinics) Departmental system Departmental system Departmental system Additional financial and administrative data Data Repository Repository is logical place for EHR data and its access Data Warehouse Regional and national systems The legal EHR Key attributes of legal medical record are discoverability and disclosure (Amatayakul, 2001) Legal EHR defined in several publications (HIMSS, 2006; Dougherty,2008) Major concerns for purchaser of legal EHR are how system deals with authorship, changeability, and audit for accuracy and validity (Dolan, 2008) Growing calls for regulation of EHRs (Hoffman, 2008) and e discovery (Carter, 2009) Practice management systems Handle non clinical functions of medical practice, e.g., Scheduling Billing Eligibility verification Selection: ACP, 2007 Often a key issue: Should a practice use same vendor for EHR and PMS? Pro: Integration, possible cheaper cost Con: One or other might not have all desired functionality Related issue: Digital signatures Important due to need to authenticate electronic medical documents Most US states have adopted Uniform Electronic Transactions Act (UETA; NCCUSL, 1999) US Congress enacted Electronic Signatures in Global and National Commerce Act (ESIGN; GPO, 2000) Both laws surprisingly vague: signature is more of an intent than specifically defined As a result, medical institutions have highly variable policies on electronic signature A major challenge is re authentication when user already logged on work flow vs. proper authentication Registries Benefits and challenges of EHR More limited form of EHR Can be separate from EHR or extract of data from it Typically oriented to one or small number of diseases, most often chronic diseases Usual functions Patient reports status of monitored conditions Exception reports outliers, overdue for care Aggregate reports how is care team delivering recommended care Overviews: Metzger, 2004; Colias, 2005 Benefits Improved physician, nursing, and other care Clinical decision support Personal health records Health information exchange Public health informatics Quality assessment Clinical research Challenges Data quality Data usability Implementation Standards and interoperability Privacy, confidentiality, and security

8 Potential benefits of the EHR Multi user ubiquitous access to patient data Multiple views of data Better communication with other providers and with patients Gamut of secondary uses of clinical data EHR can enhance communication for other providers and patients Medical record often serves as a means for providers to communicate Not only among physicians but also nurses, pharmacists, and other ancillarystaff Next step is health information exchange (HIE), where data follows the patient in care process A growing number of EHRs are linked to personal health records (PHRs; AMIA AHIMA, 2006), which allow patients to View their records Communicate with their providers (Slack, 2004) Access their health system, e.g., fill prescriptions, schedule appointments, etc Multi user ubiquitous access to patient data Paper record limited to single user at single location Electronic record can be accessed by more than one user at a time Electronic record can be accessed from any location connected to the computer system or network Secondary uses of clinical data (Safran, 2007) Re use of data from EHR for other purposes Focus of Unit 6, although each of these areas is about more than use of clinical data These areas include Personal health records patients managing their health and health care Public health reporting, biosurveillance Quality measurement and analysis Health information exchange data following the patient Clinical research advancing research through data in systems Multiple views of data Different users prefer different views of the data Views include Lists Flowsheets Graphs Computers are also good at showing trends of data Clinical decision support The raison d être of the EHR? Decision support uses EHR data to provide context specific advice, alerts, and reminders, such as Assisting with choices in diagnosis and therapy Detecting problematic situations, such as medication errors or drug drug interactions Is best delivered at point of care, especially when decisions are being made Computerized physician/provider order entry (CPOE) (Kuperman, 2003)

9 Types of decision support Information display showing general or patientspecific information in context of situation Reminder systems reminding clinicians to perform actions, such as preventive measures Alerts alerting to critical ii clinical i l situations, i e.g., interacting drugs, abnormal lab value Growing concern over alert fatigue Clinical practice guidelines guiding treatment to provide normalized care based on best evidence Challenges (cont.) Implementation challenges in making systems useful and usable for patients, clinicians, and others (Bates, 2003) Standards and interoperability how can data seamlessly flow and systems co exist (Brailer, 2006)? Privacy, security, and confidentiality can we achieve the benefits while maintaining privacy? (Boyd, 2007) Guidelines exemplify paper vs. electronic conundrum Paper guidelines are easy to use if appropriate one(s) can be found (Hibble, 1998) But probably more likely to be followed if part of decision logic of EHR Although codifying guidelines and underlying evidence is challenging (Maviglia, 2003) EHR examples Ambulatory care Centricity EMR (formerly Logician) Hospital based decision support Brigham Integrated Computing System (BICS) Both and available as a demo: Veterans Health Information Systems and Technology Architecture (VISTA) Other open source and additional examples But there are challenges Data quality documentation not always a priority for clinicians (RTI, 2007) Data usability Much data locked in clinical narrative (Hripcsak, 1995) Much research over several decades attempting natural language understanding of clinical narrative (Sager, 1987; Friedman, 2004; Meystre, 2006) Performance of systems still not adequate for routine operational use (Meystre, 2008) Example 1: Ambulatory care Logician (now Centricity EMR, GE Health, Hillsboro, OR) is a comprehensive ambulatory EHR featuring Integrated view of patient data Clinical decision support Clinician order entry Access to knowledge resources Integrated communication support

10 Integrated view of patient data Information can be browsed effectively Clinical decision support can be applied Data can be viewed in different formats Queries can be made over entire practices Different formats (cont.)

11 Example 2: Hospital based decision support Clinician order entry Brigham Integrated Computing System (BICS) Courtesy of Jonathan Teich, MD, PhD Features Information display Reminder systems Appropriate ordering Medication safety They are transitioning from text based (DOS) screens Lab order costs display Access to knowledge resources Reminder for ordering gentamicin levels Integrated communication support

12 Reminder about drug substitutions Chemotherapy safety Appropriate ordering of radiologic studies Digoxin administration in the face of low serum potassium level Possible drug allergies Templates and order sets are an example of guideline usage

13 Example 3: Both and an available demo Veterans Health Information Systems and Technology Architecture (VISTA) Available as a demo over Internet: ModernEHR success story (Brown, 2003) andhealth care quality success story (Greenfield, 2004) System being generalized and made available as open source software (Kolata, 2005) One company that has developed business around VISTA is MedSphere ( Problem list with provider alerts Selecting a patient Medication order entry Patient summary Clinical note from Cardiology

14 Vital signs and their trends Template letter for results reporting Selecting images to view Imaging results: EEG Other open source systems Clinical reminder for elevated blood pressure 63 OpenEHR ( global effort to build open source reference implementation Based on archetypes, which are formal clinical content specifications and are used and combined by templates (Beale, 2007) OpenMRS ( focused on lowcost, simple record for developing countries (Mamlin, 2006; OpenMRS, 2007) Major focus on countries with large HIV/AIDS burden, currently deployed extensively in Kenya (Tierney, 2007) 66 11