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Table of Contents
EDITORIAL  
Year : 2015  |  Volume : 18  |  Issue : 3  |  Page : 290-292
Converting data into information and knowledge: The promise and the reality of electronic medical records


Department of Anesthesiology, Mayo Clinic Hospital, Phoenix, Arizona 85054, USA

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Date of Web Publication1-Jul-2015
 

How to cite this article:
Poterack KA, Ramakrishna H. Converting data into information and knowledge: The promise and the reality of electronic medical records. Ann Card Anaesth 2015;18:290-2

How to cite this URL:
Poterack KA, Ramakrishna H. Converting data into information and knowledge: The promise and the reality of electronic medical records. Ann Card Anaesth [serial online] 2015 [cited 2019 Dec 6];18:290-2. Available from: http://www.annals.in/text.asp?2015/18/3/290/159795


The purpose of the anesthetic record has always been to "accurately and comprehensively capture a patient's anesthetic experience in a succinct format." [1] Like the rest of medical documentation, it is used to facilitate future patient care, support accurate billing, provide a legal record, as well as serving as source material for research, quality improvement, and population health management. A serendipitous result in the case of the anesthesia record has been that its format facilitated the synthesis of large volumes of data on single patients, enabling visual comparisons and identification of trends and relationships that suggested changes in clinical care and workflows, as well as potential directions for future research. Early anesthesia records (pre-1890s), like nearly all medical records, were ledger-based rather than individual patient-based; literally, they were contained in ledger books with descriptive entries handwritten in for each successive anesthetic or patient visit. This changed in the decades around 1900, with a switch to individual patient-based records, both in anesthesia specifically (E.A. Codman and Harvey Cushing at the Massachusetts General Hospital) [2] and medical records more generally (Henry Plummer at the Mayo Clinic). [3] Since this time, when Codman and Cushing first utilized a time-based graph of vital signs and anesthetic events, the anesthesia record has in fact changed very little in its basic format. The switch to this "modern" anesthesia record was significant because it facilitated the visual comparisons of data mentioned above to take place. When these pieces of "data" could be compared (e.g., drugs administered and vital signs measured), patterns of interactions could be observed producing "information" (e.g., blood pressure is frequently reduced after thiopental administration); further observation of and research into these interactions eventually resulted in the creation of "knowledge" (e.g., the pharmacodynamic effects of thiopental can produce significant hypotension, especially in hypovolemic patients or those with limited cardiac reserve).

Over a century later, we are in the midst of the next significant change in anesthesia records, and medical records as the conversion from paper to electronic records takes place. This has facilitated the next quantum change in knowledge generation. Now bringing previously unimaginable volumes of data into databases allows for potential improvements and efficiencies in patient care, billing, research, quality improvement, as well as offering clinical decision support and resource allocation in ways that were simply not possible on paper. [4] However, despite all the potential advantages, adoption of electronic records in the US and worldwide is still not universal. While assessments of anesthesia information management system (AIMS) usage in the US vary widely, from about 30% in all hospitals up to 75% in academic centers, it is clear that most anesthetics performed in the US in 2015 are still charted on paper. [5],[6] This compares with up to 82% of all US physicians using electronic health records (EHR) to enter and read clinical notes. [7] Moreover, in spite of the promise, there is very little evidence to show that the potential, economic value, and patient care benefits of AIMS or EHR have been realized. To quote an expert, "systems that are in use in multiple locations, that have satisfied users, and that effectively and efficiently contribute to the quality and safety of care are few and far between." [8]

Why does this situation exist? The answers are complex and controversial, but it is important to note that EHR vendors have traditionally focused on reimbursement, regulatory, and medical-legal requirements, not usability (user interface or "user experience [UX]") or interoperability. These same vendors have also largely marketed integrated, enterprise-wide "one size fits all" systems to hospital leadership, not the end clinical users of their systems, depriving those same clinical users of much say in their adoption. [9] And in cases where end users, specifically anesthesiologists do have a say, they have often not embraced electronic systems due to actual and perceived problems with usability, data accuracy, as well as the difficulty with showing positive return on investment. [10]

A realistic assessment of AIMS in 2015 shows strengths and weaknesses. What an AIMS does well - it collects physiologic data from a multitude of devices autonomously, accurately, rapidly, and seamlessly, and translates them into a legible record, freeing the anesthetist to monitor and treat the patient rather than record vital signs. What an AIMS does not do well in many cases is integrate easily into existing workflows without producing delay, distracting, and disruption (poor "UX"). Data entry that requires user input is often nonintuitive, and while every AIMS is capable of producing a nice legible static output of a single case, many are challenged when other types of output, say to an external database or reporting system, is required. To paraphrase many frustrated users, "our AIMS is okay, except for the fact that it's hard to get data into it and hard to get data back out again."

The future potential of an AIMS that interacts with a well-designed EHR is undeniable. The large volume data collection referenced above, made possible by electronic systems, will be crucial in providing data about potential effects of anesthetic choices not only on perioperative morbidity and mortality, but on long-term outcomes as well. [11] There is now a body of evidence suggesting possible effects of anesthetic choices on cancer recurrence; more robust and comprehensive data from well-designed electronic databases will help convert this from early information about possible associations into practice-changing knowledge. [12]

It is clear, however, that a promising future has not been enough to make the adoption of AIMS and EHRs universal. Obviously, it needs to become easier and more intuitive to get data into and out of these systems. While open source EHRs exist, the market in the US has been dominated by proprietary vended systems. However, there is an emerging movement toward open application programming interfaces on the part of large EHR vendors that may make data input and output easier and more user-friendly. The two largest integrated EHR vendors in the US market, Epic [13] and Cerner, [14] have begun to take significant steps in this direction. Still in its early stages, this movement facilitates the development of custom applications by third parties (or users themselves) for data entry, reporting, patient access, or whatever else a particular user might require. As a gross oversimplification, this in a sense turns the integrated EHR into an "operating system" (think iOS or Android) and allows users to buy/build custom "apps" to perform specific tasks. In the not so distant future, the large vended EHR products may become the transactional base system, running in the background, and the end user (clinician, researcher, billing personnel, and even patient) may be using any one (or several) out of thousands of apps to "get stuff into the record" and "get it back out again." At that point, users may not even really be aware of which "EHR" or "AIMS" they are using; they will only know the tools they need to know in order to take care of patients, generate bills, explore new relationships between data, enter data from their own wearable activity monitor, etc. It is then that the promise of electronic records will be realized.

 
   References Top

1.
Kadry B, Feaster WW, Macario A, Ehrenfeld JM. Anesthesia information management systems: Past, present, and future of anesthesia records. Mt Sinai J Med 201;79:154-65.  Back to cited text no. 1
    
2.
Molnár C, Nemes C, Szabó S, Fülesdi B. Harvey Cushing, a pioneer of neuroanesthesia. J Anesth 2008;22:483-6.  Back to cited text no. 2
    
3.
Rocca WA, Yawn BP, St Sauver JL, Grossardt BR, Melton LJ 3 rd . History of the Rochester Epidemiology Project: Half a century of medical records linkage in a US population. Mayo Clin Proc 2012;87:1202-13.  Back to cited text no. 3
    
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Egger Halbeis CB, Epstein RH. The value proposition of anesthesia information management systems. Anesthesiol Clin 2008;26:665-79, vi.  Back to cited text no. 4
    
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Stol IS, Ehrenfeld JM, Epstein RH. Technology diffusion of anesthesia information management systems into academic anesthesia departments in the United States. Anesth Analg 2014;118:644-50.  Back to cited text no. 5
    
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Stonemetz J, Dutton RP. Anesthesiology information management systems (AIMS) market update. ASA Newsl 2014;78:38-40.  Back to cited text no. 6
    
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Despite Increased Use of Electronic Medical Records, Fewer U.S. Doctors Believe it Improves Health Outcomes, Accenture Survey Shows; Accenture; 2015. Available from: http://www.newsroom.accenture.com/news/ despite-increased-use-of-electronic-medical-records-fewer-usdoctors-believe-it-improves-health-outcomes-accenture-survey-shows.htm. [Last accessed on 2015 Mar 22].  Back to cited text no. 7
    
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Wears RL, Berg M. Computer technology and clinical work: Still waiting for Godot. JAMA 2005;293:1261-3.  Back to cited text no. 8
[PUBMED]    
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McEvoy JW. The Turing test and a call to action to improve electronic health record documentation. Am J Med 2014;127:572-3.  Back to cited text no. 9
    
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Stonemetz J. Anesthesia information management systems marketplace and current vendors. Anesthesiol Clin 2011;29:367-75.  Back to cited text no. 10
    
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Poeran J, Mazumdar M, Memtsoudis SG. Anesthesia, outcomes, and public health: Changing health care while "asleep". Reg Anesth Pain Med 2014;39:192-4.  Back to cited text no. 11
    
12.
Durieux ME. Anesthesia and cancer recurrence: Improved understanding, but no reason for change. Anesth Analg 2014;118:8-9.  Back to cited text no. 12
    
13.
Houston SK. Epic's App Exchange, Will the Most Popular EHR Open Up or Remain Closed? iMedical Apps MEDPAGE TODAY; 2015. Available from: http://www.imedicalapps.com/2015/03/epic-emr-app-exchange/. [Last accessed on 2015 Mar 22].  Back to cited text no. 13
    
14.
Wicklund E. EHR Vendors Extending Platforms with Apps and APIs. Healthcare IT News; 2015. Available from: http://www.healthcareitnews.com/news/ehr-vendors-extending-platforms-apps-apis. [Last accessed on 2015 Mar 22].  Back to cited text no. 14
    

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Correspondence Address:
Karl A Poterack
Department of Anesthesiology, Mayo Clinic Hospital, Phoenix, Arizona 85054
USA
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0971-9784.159795

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