Straight Talk: Plato's Republic, Freakonomics, and Our Electronic Health Record | CardioSource WorldNews
"Don't waste time on a technique that is not going to work."
—The Interventionalist's Maxim
The utopian promise of the electronic health record (EHR) is intoxicating—its assurance of improved care, enhanced patient safety, increased efficiency, and reduced cost resonating universally with patients, providers, and payers alike. Unfortunately, even a cursory examination today leads inexorably to the realization that the circumstance bears little resemblance to that dream—its trajectory unlikely to lead to such success in any meaningful way.
Reminiscent of the characters in "The Allegory of the Cave" from Plato's Republic,1 providers are currently forced to live in an alternate EHR reality, attempting to divine the path forward by discerning the limited, shadowy illusions of success shown to us by others rather than grasping the full reality that objective scrutiny of the EHR provides.
Quite simply, we have been financially induced to select, adopt, and implement EHRs from a veritable Duke's mixture of several hundred different software products. This class of products was, at its core, a fee-for-service billing amplification tool—developed by vendors whose fundamental tenet is "ours is better than theirs" when it comes to increasing fee-for-service billing. Return on investment in this sphere is measured in years or even decades.
Predictably, this federal financial incentive for EHR adoption has not resulted in a standardization of function and optimization of provider workflow, but rather in an explosion of new EHR offerings. The cottage industry of the health information exchange (HIE), meanwhile, faces the potentially lucrative but Herculean task of untying the Gordian Knot of information sharing between EHRs.
Reading like a case study from Levitt and Dubner's Freakonomics,2 we seem to have slowed provider productivity, increased non-care–related expenditures, and reduced face time with our patients while spending $19.2 billion on Meaningful Use incentives, increasing the number of EHR systems from 300 to more than 600, and spending additional billions on all-but-futile efforts to connect the EHR via HIE.3-8
How Did We Get Here?
The Center for Medicare and Medicaid Services defines an EHR as "an electronic version of a patient's medical history that is maintained by the provider over time, and may include all of the key administrative clinical data relevant to that person's care under a particular provider, including demographics, progress notes, problems, medications, vital signs, past medical history, immunizations, laboratory data and radiology reports. The EHR automates access to information and has the potential to streamline the clinician's workflow."9
One would come to the conclusion that the electronic record was simply an electronic chart, not a tool to improve outcomes or provider workflow. In fact, that is exactly its pedigree.
Seminal efforts in electronic record development have root in the 1960s with Harvard University's Computer Stored Ambulatory Record (COSTAR), Duke University's The Medical Record (TMR), and the Veterans Administration De-Centralized Hospital Computer Program (DHCP). By the late 1970s, there had been a significant expansion of the mainframe-based electronic medical records concept with no maturation to enhance workflow. The 1980s and early 1990s saw the development of distributed computing capability allowing the expansion of the EHR to the outpatient arena with companies such as Compaq, Data General, Cerner, HBOC, MiSys, and Allscripts entering the market. EPIC released their singular Windows-based acute care management system in the 1990s. Shortly thereafter, physician offices began to use these electronic charting systems, and the current terminology of the "EHR" came into use. The outpatient environment was more predictable, operations more straightforward, and the adaptability to distributed computing systems more easily accomplished. Notwithstanding these advances, the EHR remained fundamentally a system for enhanced billing and coding documentation.
Are We In Need of an EHR Evolution?
Given these issues, what functionality should providers, the end-users of this software, demand as the next steps in its evolution?
Quite simply, those features that will improve care and care delivery while reducing cost: full interoperability, enhanced provider workflow, and clinical decision support.
Interoperability—defined as the ability to exchange information and then use the information for clinical care—is the clear path to immediate cost savings and improved care. The recent example provided by emergency care visits in Memphis, Tennessee, furnish ample proof that truly functional data sharing reduces cost and likely improves care.10 In spite of this microenvironment success, our current EHR connected via HIE strategy has little chance of widespread implementation.11,12 Unless there is a greatly increased demand for interoperability by providers themselves, the holy grail of true interoperability will languish. This conversation must include dialogue regarding a unified data model for clinical data, as well as a unique patient identifier and must proceed more quickly than the currently proposed Meaningful Use interoperability requirements.
The provider workflow and user experience must be critically assessed, optimized, and fully integrated into the EHR. Our current systems were never designed with the provider in mind, much less any intuitable function to maximize workflow. Providers should expect contextual usability in their systems.13,14 Further, EHR developers should embrace the business process management approaches so successful in other industries while assessing the use of process-aware clinical groupware to transform the end-user experience from one of obstacle course to enhancer of care delivery.15
The big brother of clinical decision support is predictive analytics: software-based approaches to provide relevant, situation-appropriate, real-time information to the provider by contextually filtering patient-related data. In the next generation of EHRs, predictive analytics must also be integrated. Such clinical decision support and predictive analytics systems will likely continue to appear in the form of appropriate alerts to enhance safety, links to expanded relevant clinical information sources or forms of data presentation to enhance provider data assimilation.16 In the future, these systems will grow and allow real-time assistance in clinical decision making.
The current effort to simply stimulate the adoption of EHR—to move to an "electronic chart"—must now evolve into a clinically useful, provider-friendly data repository. It must reach farther than the single provider, and assist, rather than inhibit, the provision of care. Providers must lead that evolution to a clinically useful EHR—difficult though it may be. Let us not shrink from the challenge, but embrace it.
1. Plato. The Republic. Dover Thrift Editions. Ed. Joslyn T Pine and Paul Negri. Mineola: Dover, 2000 (republication of the Benjamin Jowett translation in 1894).
2. Levitt SD, Dubner SJ. Freakonomics: A Rogue Economist Explores the Hidden Side of Everything. New York: Harper, 2006.
3. Verdon D. Medical Economics. 10 February 2014. Accessed from http://medicaleconomics.modernmedicine.com/medical-economics/news/physician-outcry-ehr-functionality-cost-will-shake-health-information-technol?cid=physicanoutcry.
4. Friedberg MW, Chen PG, Van Busum KR, et al. "Factors Affecting Physician Professional Satisfaction and Their Implications for Patient Care, Health Systems, and Health Policy." Santa Monica: RAND Corporation, 2013.
5. Lowes R. "EHR Rankings Hint at Physician Revolt." Medscape. 2014 February 3. Accessed from www.medscape.com/viewarticle/820101.
6. Lynn J. "Over 600 EHR Vendors." 2012 April 11. Accessed from www.emrandhipaa.com/emr-and-hipaa/2012/04/11over-600-ehr-vendors/.
7. Lewis N. "Healthcare IT Spending to Reach $40 Billion." Information Week. 2011 May 16. Accessed from www.informationweek.com/healthcare/electronic-medical-records/healthcare-8t-spending-to-reach-40-billi/229500682.
8. Manos D. "Does 19.2B Ring a Bell?" GovernmentHealthIT. 2014 February 7. Accessed from www.govhealthit.com/blog/does-192b-ring-bell-MU-incentives-SGR.
9. Centers for Medicare & Medicaid Services. "Electronic Health Records." Accessed from http://www.cms.gov/Medicare/E-Health/EHealthRecords/index.html?redirect=/ehealthrecords/.
10. Frisse ME, Johnson KB, Nian H, et al. J Am Med Inform Assoc. 2011 November 4. [Epub ahead of print]
11. ONC Annual Meeting. January 23-24, 2014. Washington, DC. Accessed from http://webconferences.com/hhs/onc/archived-videos.html.
12. Zieger A. "HIE's unable to keep up with user demands." EMR & EHR. 2013 August 7. Accessed from www.emrandehr.com/2013/08/07/hies-unable-to-keep-up-with-user-demands/.
13. Webster C. "Contextual Usability, My Apple iPad, and Process-Aware Clinical Groupware." 2010 April 3. http://chuckwebster.com/2010/04/ehr-workflow/contextual-usability-my-ipad-and-process-aware-clinical-groupware-for-pediatric-practice.
14. Jansson A. "Contextual Usability 2012: Human-Computer Interaction." Accessed from www.it.uu.se/edu/course/homepage/contextuse/ht12/Contextual-usability-intro_2012.pdf.
15. Webster C. "Intuitive vs Intuitable EHRs: Do We Need Smarter Users or Smarter User Interfaces?" 2010 July 2. http://chuckwebster.com/2010/07/ehr-workflow/intuitive-vs-intuitable-emrs-ehrs-and-clinical-groupware-do-we-need-smarter-users-or-smarter-user-interfaces-3.
16. Musen MA, Blackford M, Greenes RA. Biomedical Informatics: Clinical Decision Support Systems. Ed. Edward H. Shortliffe and J. J. Cimino. London: Springer, 2014.
< Back to Listings