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Clinical Information Systems: Instant Ubiquitous Clinical Data for Error Reduction and Improved Clinical Outcomes Craig F. Feied, MD, Jonathan A. Handler, MD, Mark S. Smith, MD, Michael Gillam, MD, Meera Kanhouwa, MD, MHA, Todd Rothenhaus, MD, Keith Conover, MD, Tony Shannon, MD Abstract Immediate access to existing clinical information is inadequate in current medical practice; lack of existing information causes or contributes to many classes of medical error, including diagnostic and treatment error. A review of the literature finds ample evidence to support a description of the problems caused by data that are missing or unavailable but little evidence to support one proposed solution over another. A primary recommendation of the Consensus Committee is that hospitals and
departments should adopt systems that provide fast, ubiquitous, and unified access to all types of existing data. Additional recommendations cover a variety of related functions and operational concepts, from backups and biosurveillance to speed, training, and usability. Key words: electronic medical record; clinical results; information technology; computer. ACADEMIC EMERGENCY MEDICINE 2004; 11:1162–1169.
Despite many advances in health care over the past half century, on-demand access to clinical information continues to be inadequate in most settings,1,2 contributing to duplication of effort, excess costs, adverse events, and reduced efficiency. Improvements in clinical information acquisition, storage, retrieval, sharing, and presentation are a primary goal in the nation’s health care strategy. The first and most pressing problem is that alreadyexisting information generally is not available when and where it is needed. Information that often is not readily available includes test results, images, chart notes or entire charts, and information about the care process itself. As we move toward a future in which comprehensive electronic medical records are globally accessible, the most important first step is simply to get all existing data into the hands of clinicians and other end users.
It is no accident that the National Health Information Infrastructure, a major initiative recently undertaken by the U.S. Department of Health and Human Services, focuses initially not on computerized order entry, electronic documentation, or practice guidelines, but rather on achieving shared access to existing medical data. This is a daunting task at the national level; medical care in the United States involves roughly 4,000 hospitals, 250,000 physicians, and 1,000,000 nurses, consuming 14% of the gross domestic product, or about $1.2 trillion each year. Data sharing must first meet the needs of patients, clinicians, and clinical departments, then of institutions and integrated care enterprises, then of cities and regions, and, finally, of the nation as a whole. The task begins with the integration of data from existing hospital and departmental systems; emergency medicine plays an important defining role in this initial effort for a variety of reasons,3 including the fact that all hospital functions exist in one place within the emergency department (ED). Perhaps more than physicians from any other specialty, emergency physicians need access to large amounts of clinical information with the greatest possible speed and the widest possible context. The daily work of emergency medicine involves the simultaneous evaluation and treatment of multiple previously unknown patients with a variety of acute problems that may be related to any organ system and any medical subspecialty.4 The need for rapid access to complete data through a simple and reliable interface is particularly acute because the ED is the most disruptive and chaotic
From the Institute for Medical Informatics (CFF, JAH, MSS, MG), Washington, DC; National Center for Emergency Medicine Informatics (CFF), Washington, DC; MedStar Health (CFF), Washington, DC; Northwestern University School of Medicine (JAH), Chicago, IL; Washington Hospital Center, Georgetown University Medical Center (MSS), Washington, DC; Evanston-Northwestern Healthcare (MG), Chicago, IL; Swedish Medical Center, Patient Safety Institute (MK), Seattle, WA; Boston Medical Center (TR), Boston, MA; Pittsburgh Mercy Health System (KC), Pittsburgh, PA; and Sunderland Royal Hospital (TS), Sunderland, England. Address for correspondence and reprints: Craig F. Feied, MD, 110 Irving Street, NW, Washington, DC 20010. E-mail:
[email protected]. doi:10.1197/j.aem.2004.08.010
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environment that exists in medicine; more than one half of tasks being performed by emergency physicians are interrupted, and approximately one third of tasks are suspended or abandoned due to interruptions requiring a higher-priority task to be performed immediately.5 Those who have made or observed the transition from data-poor to data-rich practice environments have no doubt that improved availability of information leads to improved clinical care. There is ample anecdotal evidence that rapid ubiquitous access to clinical information helps clinicians to do a better job,6 but there are relatively few credible published data measuring the clinical impact of informatics initiatives of any type.7 Although the task of evaluating such impact is difficult,8 and although research in the area of medical informatics rates poorly when measurement practice is examined,9 this is an important area for future research.
REDUCING ERROR Many adverse patient outcomes are believed to be caused by clinical error.10–13 Although some believe the Institute of Medicine’s 1999 report ‘‘To Err Is Human’’14 overstated the magnitude of the problem in claiming that medical error is responsible for more deaths than motor vehicle collisions, nobody disputes the fact that medical error exists and that the incidence of error can and should be reduced.15–19 Conferences sponsored by the American Association for the Advancement of Science and the Patient Safety Institute describe clinical error as the second highest cause of death and advise that physician error is largely due to decision making with an incomplete case history.20,21 A comprehensive root-cause analysis identified knowledge deficiencies about drugs, checking errors, and inadequate availability of patient information as the leading types of errors.22 A review of hospital practice in the National Health System of the United Kingdom found that many errors arose from sources such as ‘‘dependence on diagnoses made by inexperienced clinicians, poor records, poor communication .’’ and other causes related to lack of complete knowledge.23 The American Hospital Association agrees, listing ‘‘incomplete patient information’’ first in its list of common sources of error.24 Other sources of error listed by the American Hospital Association are shown in Table 1.24 Certain types of error may be reduced through computerized physician order entry, computerized documentation, and other data entry tasks performed by physicians, using computer algorithms to encourage desirable behaviors or to enforce clinical practice rules. However, there is a heavy social cost associated with compelling clinicians to perform data entry tasks.25 There is scant evidence to show that computerized physician order entry actually improves clinical
1163 TABLE 1. Common Sources of Medical Error as Listed by the American Hospital Association24 Incomplete patient information (e.g., not knowing about patients’ allergies, other medicines they are taking, previous diagnoses, and laboratory results) Unavailable drug information (such as lack of up-to-date warnings) Miscommunication of drug orders, which can involve poor handwriting, confusion between drugs with similar names, misuse of zeroes and decimal points, confusion of metric and other dosing units, and inappropriate abbreviations Lack of appropriate labeling as a drug is prepared and repackaged into smaller units Environmental factors such as lighting, heat, noise, and interruptions that can distract health professionals from their medical tasks
outcomes, and it is possible that deploying computerized physician order entry could increase certain types of errors.26 Order creation in the real world is a complex and collaborative process, and direct ordering by physicians may disrupt existing checks-and-balances mechanisms.27 Furthermore, merely enforcing rules at the time of data entry cannot prevent all types of clinically important errors.28 For example, process errors of reasoning have been observed in 100% of studied trauma resuscitation cases,29 and reviews consistently find that a large proportion of diagnoses are incorrect across all specialties. Recent autopsy surveys have found that even after 40 years of continual improvement, the primary cause of death still is incorrectly diagnosed in approximately 25% of cases and that up to 9% of the incorrect diagnoses are responsible for or strongly contribute to the death.30 Some of the error reduction that has been credited to physician order entry actually is achieved simply by using the order entry process to help make existing information visible, rather than from the act of a physician placing an order. For example, when medication errors related to allergy were reviewed in one study, most contributing factors were classified as ‘‘MD [prescribing physician] not aware of allergy.’’31 Improved awareness of information such as patient allergies does not depend on a computerized physician order entry system; a substantial part of the value associated with any decision-support process comes primarily from the availability and integration of current and historical patient data, such as prior medications and allergies, that can help inform clinical decision making. Physicians entering data are a convenient target for decision-support modules, but some of the benefits of this type may be equally achievable simply with improved environmental availability of existing information. Reducing the rate of errors related to incorrect diagnostic approaches, poor thinking, and poor communication may require fundamental changes in the way medical decision making is performed,32–34 but many types of error, including many incorrect
1164 diagnoses and treatments, have their roots in decisions that have been based on incomplete information: ‘‘not knowing’’ or ‘‘not seeing.’’ To address errors of this type through any mechanism, increased amounts of relevant information must be made more readily accessible.35
DELIVERING CLINICAL INFORMATION Paper records cannot meet clinical information needs, partly because important components of the clinical record often are not available when needed. The American Forces Press Service reported a survey in which some military facilities were able to find only 25% of requested records,36 and a 1995 audit commission for the U.K. National Health Service reported that 35% of records were not found in the medical records library and that one of six case notes was not available in many hospitals.37,38 Electronic data are essential, yet an electronic medical record is not the same as a clinical information delivery system, and the mere existence of an electronic medical record does not guarantee that clinical information will be available when needed. One study found that essential preanesthesia information from outside the hospital was needed and unavailable in 8% of cases, while information from within the hospital was needed and unavailable in 22% of cases, despite the existence of an electronic medical record system.2 National access to uniform clinical data for all patients would benefit the 8% of patients for whom external data were needed and unavailable, but such data must somehow be available within an institution before they can be shared regionally or nationally. Having an electronic medical record also does not guarantee that data contained within it will be correct. Data captured automatically, such as from a pharmacy dispensing system, often are reliable, but data entered by a physician often are not. For example, a study of geriatric medications listed in an electronic medical record found that physicians had recorded complete and correct medication data in only 81% of cases.39 In ED data that were reported to a state agency, 16% of admitted patients were missing completely; another 64% were incorrectly listed as having been discharged, and only 9% of admitted patients had the correct hospital listed.40 The use of standard codes does not necessarily improve accuracy in describing the clinical encounter; in one study, 40% of patients who underwent placement of a central catheter could not be identified from internal charge codes or from International Classification of Diseases and Current Procedural Terminology codes using hospital and health maintenance organization databases.41 Conversely, the immediate clinical value of information does not depend on the use of restricted or standardized coding vocabularies;
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access to existing free-text data can provide substantial benefit. Replacing free-text data with standards-based coding reduces variability but may do so at the cost of reduced information content. Given the great variability that exists in the types and forms of medical data, the urgency of the problem, and the impossibility of modifying or replacing all existing legacy systems within a reasonable amount of time, what is needed today are data platforms that can aggregate all types of information and make it available in a unified context. Such systems can provide immediate access to existing data and can facilitate progress toward additional solutions (such as decision support modules, physician-entered orders, and physicianentered documentation) that will need to make use of the same data. The primary requirement today is for comprehensive data systems that can deliver seamless access to all existing clinical and management information, regardless of source. Such systems must receive data from new sources as needed and must provide easy, fast, and open access to the data for any authorized and authenticated user. It is important that clinical departments, hospitals, and health care enterprises begin to aggregate and distribute data through clinical information systems immediately, because ultimate success in this endeavor likely will not come overnight. Clinical improvement through improved clinical information infrastructures comes gradually, as an enterprise improves internal processes to take advantage of new resources and methods.42 A review of the literature finds that although there is ample evidence of the problem, validated data to support proposed solutions are lacking. There are many anecdotal reports of successful projects and a few reports of unsuccessful projects. Glowing reports are found for systems that have since been abandoned; the literature does not appear to reflect deinstallations and failures after initial success. Much of the published discussion is vague and theoretical. Where real evidence is available, it most often comes from industries outside medicine and the applicability of such evidence to the field of medicine remains unknown. The Consensus Committee on clinical information systems therefore has based each of its observations and recommendations on expert opinion and experience, guided by what weak published evidence is available.
CONSENSUS RECOMMENDATIONS Purpose of a Clinical Information System. The primary purpose of a clinical information system is straightforward: show all relevant information. Show it everywhere. Make it clear. Make it concise. Make it fast. Make it easy. A clinical information system should be the basis for a global solution that ultimately will provide instant access to all prior information of all
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types, automatic capture of all possible new information, fast and easy charting of new information, and decision support that is smart but not intrusive. Benchmarks. Systems should be assessed and compared based on their performance in a series of ‘‘standard activities’’ that reflect typical casemixes and practice patterns of emergency physicians. Research is needed to define what mix of activities best characterizes modern emergency practice and to define benchmarks based on those activities. Outcomes. The impact of improved information availability on clinical care should be measured. Changes to information delivery systems should be assessed in terms of the concrete patient, public health, risk management, financial, and other outcomes that we wish to improve. Research is needed to define outcomes that can be improved through better clinical information systems and to determine the best way to measure changes in those outcomes. Discussion. Outcome measures should be chosen carefully. In recent years, much emphasis has been placed on pseudo-outcomes that are of uncertain benefit to the patient. For example, time in department has been widely adopted as an outcome measure, yet there are many situations in which a shorter time in the department is not better for the patient. Amount and Type of Data. All existing information of all types should be available within a clinical information system. When the need for a new data source is identified, it should be possible to add that data source easily. Research is needed to define not only the minimum data set required to support adequate clinical care, but also the incremental value of adding more data of different types. Discussion. Existing clinical information systems vary by orders of magnitude in the amount and variety of data they can provide to the clinician, but a few successful systems have demonstrated the ability to make many thousands of data elements accessible without creating confusion for the user. Data of all types should be retained; requirements for clinical care and for research undergo constant change, and it is impossible to know what data will be needed to answer the questions of tomorrow. It is not possible for a system to contain too much data, although it is possible to show so much data as to create confusion. Data Presentation. Clinical systems should help clinicians to see the right amount of the right type of data wherever and whenever needed. Data presentation should be context-driven, and clinicians should
1165 be able to change what the system shows them in any given context, showing or hiding specific data elements to meet current data needs. Research is needed to define groupings of data elements that can be managed together and to define groups of essential data elements that should be displayed in common clinical contexts such as at triage, at case review, at admission, and at discharge. Usability and Training. A system should be learnable and usable for basic clinical functions with little or no formal training. Functions necessary for clinical care should be memorable after a hiatus in system use. Research is needed to determine whether the amount of training needed by a system is correlated to error rates or user efficiency and to identify other usability factors that affect error rates or user efficiency. Discussion. The ED is a high-intensity clinical environment in which new residents, students, and agency nurses must become productive immediately upon arrival. The costs of intensive training cannot reasonably be borne in such an environment. Furthermore, the less intuitive a system is, the more it is prone to human factors breakdowns. Many successful intuitive systems of comparable complexity do not require formal training; the need for significant amounts of training may be an indication of poor system design that can lead to problems. Speed. Clinical information should be accessible in the shortest possible amount of time. Most results should be available with subsecond response times. Research is needed to quantify changes in error rate or productivity that may occur in a clinical setting as a function of information access speed. Discussion. In an emergency, seconds count. Slower systems create more opportunity for cognitive drift and for interruptions to the task, thus more opportunity for error. Availability and Downtime. Clinical systems should remain functional around the clock. If a system is designed in such a way that it must be taken offline for more than a few minutes during routine maintenance, equivalent data should be made available through some other system during that period. Research is needed to quantify the clinical and administrative costs of downtime. Discussion. Clinical care is delivered around the clock, and it is neither safe nor efficient for medicine to be practiced without information access and computer support. It is unacceptable that the quality of care should be systematically degraded for longer than a reboot cycle during regular scheduled
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maintenance. Hot-plug and redundant fail-over technologies are now very affordable even when using commodity hardware and software, and data set replication is built into nearly all current database systems; thus, any well-designed system should be able to route queries to backup servers whenever primary systems must be taken offline for any needed upgrades. Failure to accomplish this at reasonable cost may be an indication of fundamental flaws in system design.
Discussion. A few existing systems have demonstrated that it is technically simple and relatively inexpensive to aggregate information from many different sources and make all of the information available in one place. The barriers to achieving this are largely political, as when silo administrators defend their departments, and commercial, as when vendors manage data flows restrictively (‘‘holding data hostage’’) as part of a business strategy. These are not good reasons to limit data aggregation.
Backup Systems. Backup systems must be maintained, tested, and exercised regularly to ensure that patient care can continue during primary system outages. Testing and exercise of backup systems should be performed without turning off primary clinical information systems. Research is needed to quantify changes in outcomes when clinical information systems are turned off or when manual or electronic backup systems are being exercised.
Data Sharing. Electronic clinical records should be released immediately upon the certification of a clinician that there is an immediate clinical need for the release of those records. Clinical information systems should be capable of transmitting such records across a firewall by a variety of secure electronic means, including secure e-mail, secure FTP, and secure Webbased transfers. Systems should also support direct facsimile transmission and should be capable of tracking and auditing all such transfers. Research is needed to help define effective approaches to the clinically indicated release of clinical information with or without patient consent.
Security. Clinician access to clinical data should not be unnecessarily restricted. To the extent that clinical care can be improved by information availability, the information should be kept readily available and unrestricted to the greatest extent permitted by law. Research is necessary to better define the balance of clinical and financial risks associated with making data more or less readily available and to identify the least intrusive means of securing access to clinical data. Discussion. One of the most important causes of clinical error is lack of awareness of existing information; thus, security measures that impede access to clinical data may increase error rates. The liability (malpractice and otherwise) resulting from clinical errors is real, immediate, and substantial, while the liability associated with breaches of privacy and security remains poorly defined. Furthermore, existing and proposed regulatory rules require that information be kept available as well as secure and private. When clinical information needs are in conflict with privacy or security rules, the best possible clinical outcomes should be supported even at the expense of security and privacy. Completeness. Data from disparate sources should be aggregated or joined for completeness whenever possible so that clinicians are not forced to go to multiple different systems to obtain important information. Research is needed to define and measure the impact of increasing or decreasing the number of different systems that must be used to obtain clinical information.
Discussion. It often happens that a patient in the ED is incapable of giving consent for another hospital to release records at a time when clinical care demands that the records be released. Emergency physicians have long accepted the concept of implied consent and not infrequently send key portions of the medical record (such as an electrocardiogram) to a colleague even in the absence of explicit patient consent. This practice is widely believed to represent low risk to the institution and high benefit to the patient, but there is little evidence as to the real risks and rewards. Ubiquitous Computing. Clinical information systems should make all data and computer-supported activities available wherever and whenever needed, using wireless mobile technology if necessary to achieve this goal. Research is needed to better define the impact of delayed information access on outcomes and the extent to which scalability and surge capacity are enhanced by the use of mobile devices for data access. Discussion. Emergency care sometimes overflows the normal spatial boundaries of traditional care areas, as when simple overcrowding, disasters, or surge events force clinical care into standby areas. Data must continue to be immediately accessible when care is delivered in overflow areas. Alternative Interfaces. Clinical data should be accessible through a variety of traditional and nontraditional interfaces.
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Research is needed to investigate alternative interfaces that may be less intrusive, better fitted to the needs of handicapped staff, or better able to be used by staff wearing protective equipment and in other special situations. Voice-interactive, gesture-recognition, and ‘‘anticipation-of-needs’’ interfaces are among those that should be explored. Discussion. It is not sufficient for clinical systems to be available merely to people who are able-bodied and functioning at their highest level. Currently available clinical systems cannot be used by blind clinicians, and most current workstation installations are not wheelchair-accessible. The need for data continues during a contamination event, yet certain types of personal protective equipment can render a standard workstation unusable. Data Are Data. Clinical data systems should be capable of receiving, storing, and presenting all existing forms of data and should be extensible and flexible enough to receive new forms of data as necessary. Research is needed to better define clinical data meta-types and to identify emerging data types that will need to be accommodated by clinical information systems. Discussion. As medicine continues to advance, data will continue to arrive in new and different forms. For example, an 80-lead vest-based electrocardiogram has recently been introduced, but traditional clinical information systems have no mechanism for acquiring, maintaining, or presenting these data. Furthermore, although a false dichotomy has arisen to separate data into clinical and nonclinical categorizations, clinical value can be derived from traditionally nonclinical sources, and vice versa. Clinical data systems should be able to receive, aggregate, and present any type of data for clinical and analytical support. Context and Cohort. Clinical systems should make it possible to see and explore the cohorts to which a patient belongs and contexts in which the patient is receiving care. Research is needed to define specific cohorts that are of clinical interest and to measure the effect of adding cohort knowledge to the patient care experience. Discussion. Clinical care is delivered in a variety of nested and overlapping contexts and cohorts that often are implicit and sometimes go unrecognized. For example, when treating hypertension, one important context is the patient’s history of blood pressure measurements, because choosing an appropriate treatment depends on knowledge of that context. An important cohort for such a patient might be the group of all other similar patients who have received that same drug,
1167 particularly if the Food and Drug Administration has recently released an alert based on the collective experience of those patients. Some cohorts are of widespread interest, such as the cohort of patients who did not fill their prescriptions or those who have not had a screening test that is indicated for their age and gender. Public Health and Biosurveillance. Clinical systems should deliver real-time data as needed to support local, regional, and national biosurveillance and public health needs. They should automate the reporting of reportable diseases and make it easy to add new diseases to that list of reportable entities. Clinical systems should also be capable of receiving and displaying alerts from public health authorities. Research is needed to determine how best to combine data from many different reporting entities and what data elements and algorithms will allow us to perform effective surveillance. Sensitivity and specificity must be assessed for each surveillance measure. Situational Awareness. Clinical systems should enhance situational awareness by routinely exposing health and disease trends in the community. Research is needed to identify baseline geotemporal activity patterns for common clinical problems and to define thresholds for heightened response. Discussion. Situational awareness goes beyond simple biosurveillance, which is aimed at identifying outbreaks requiring a coordinated public health response. Situational awareness aims to create clinical environments in which clinicians naturally have a shared awareness of community health trends on a daily basis. The data necessary to develop and support situational awareness already exist in every hospital and ED but are rarely used for this purpose. Ease of Access to Data. Clinical systems should reduce to a reasonable minimum the number of steps required to obtain any information. From a main screen, complete test results for any patient should be available in one or two steps. Research is needed to determine what paths are taken by clinicians as they seek and retrieve clinical data and to define which data are most useful or most used and which are most often overlooked. Discussion. The greater the effort required to obtain information, the higher the likelihood that the information will go unseen. ‘‘Flat’’ systems in which most functions are available in one place are more appropriate for the ED than are ‘‘deep’’ systems with many nested levels of navigation. Most data should be accessible from main screens with just a double click.
1168 Alerts. Systems should be capable of alerting clinicians under certain conditions, such as when results are delayed beyond expectation or when criteria are met for a high risk of clinical error. Research is needed to define what alerts and alarms are useful in clinical emergency care. Discussion. Certain types of results are at particularly high risk of being overlooked. For example, a low platelet count often is substantially delayed because of the need for manual verification. It is important that there should be some mechanism for bringing such results to the attention of the clinician, whether by pop-up or by pager notification. Standards. Systems should have the ability to import and export data that are compliant with multiple different present and future standards. Research is needed to better define a comprehensive ‘‘standards landscape’’ map for systems that will support clinical information needs in the ED. Discussion. Internal data stores need not match any published standard, so long as sufficient metadata are maintained to permit easy import and export of data formatted to common published standards. Common Tasks. A clinical system should meet the regularly recurring data needs of the clinician and the clinician–manager. Systems should be able to perform common management-related data tasks along with common single-patient clinical data tasks. Research is needed to define common data access tasks that should be easily performed by a clinical information system. Discussion. Lookup of single-patient results is not sufficient to meet the data needs of clinicians. Many common clinical and management tasks require data that should be readily accessible. Some examples are listed in Table 2.
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Patient Identifiers. Patient photographs and patient identifiers should be visible in order to reduce ‘‘wrong patient’’ problems. Research is needed to assess the extent to which patient photographs and other identifiers displayed within the patient record can reduce the frequency of ‘‘wrong patient’’ problems and to clarify any pertinent regulatory rules. Discussion. Charting and order writing on the wrong patient are common errors. Many such errors are caught; many undoubtedly are not. It is impossible to know how often results are reviewed by a physician who mistakenly believes them to belong to a different patient, but many examples exist of bad outcomes arising from such confusion. Openness. All data elements should be exportable according to some published standard and should be accessible using third-party software. The exportable elements should be defined in a published data dictionary. Research is needed to develop data transformation tools to aid in format conversion and standards interoperability. Discussion. The mere fact that a product uses standards internally does not make it ‘‘open.’’ Systems must accept incoming data via published standards and must be able to export all data according to some published standard. It is desirable if a system can additionally accept standards-based queries for every stored data element, responding to a query by delivering data according to some published standard.
CONCLUSIONS One of the key problems facing clinicians today is that too much time is spent gathering clinical information from fragmented and incomplete sources, with a high risk that important information, being hard to find, will be overlooked. Comprehensive clinical information
TABLE 2. Examples of Common Data Tasks That Should Be Supported Find out to what service and what bed a patient was admitted yesterday, and who is listed as the admitting physician Find the patient seen ‘‘some day last week’’ who had a complaint of palpitations and was discharged on alprazolam, and see the results of her chest radiograph Show all the patients seen yesterday who had any abnormal test result Find the laboratory and radiography results for a patient when the spelling of the name is uncertain Show all the patients on this shift who have elevated cardiac enzyme levels and have not been admitted to a coronary care bed Show all prior diagnoses and procedures for a patient Show all the patients admitted to internal medicine since midnight who belong to a particular health maintenance organization Show all the patients who meet the criteria for heparin-induced thrombocytopenia Show the distribution of presenting complaints in patients who died in-hospital over the past nine months Show all patients who received an emergency department diagnosis of thrombophlebitis since the beginning of the year Show all patients who received lumbar punctures in the emergency department last month Show all patients who returned to the hospital within three days after discharge List every diagnosis given to a patient in the emergency department during the past year, in descending order by the number of times that diagnosis was used
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