Abstract. Information technology holds the promise to enhance the ... Key words: information technology; emer- ... suggest the best method for data storage of health ... Mayo Clinic College of Medicine (VS), Rochester, MN; and Swedish.
ACAD EMERG MED
d
November 2004, Vol. 11, No. 11
d
1155
www.aemj.org
Information Technology Principles for Management, Reporting, and Research Michael Gillam, MD, Todd Rothenhaus, MD, Vernon Smith, MD, Meera Kanhouwa, MD, MHA Abstract Information technology holds the promise to enhance the ability of individuals and organizations to manage emergency departments, improve data sharing and reporting, and facilitate research. The Society for Academic Emergency Medicine (SAEM) Consensus Committee has identified nine principles to outline a path of optimal features and designs for current and future information technology systems. The principles roughly summarized include the following: utilize open database standards with clear data dictionaries, provide administrative access to necessary data, appoint and recognize individuals with emergency department informatics expertise, allow automated alert and proper identification for enrollment of cases into research, provide visual and statistical tools and training to analyze data,
embed automated configurable alarm functionality for clinical and nonclinical systems, allow multiexport standard and format configurable reporting, strategically acquire mission-critical equipment that is networked and capable of automated feedback regarding functional status and location, and dedicate resources toward informatics research and development. The SAEM Consensus Committee concludes that the diligent application of these principles will enhance emergency department management, reporting, and research and ultimately improve the quality of delivered health care. Key words: information technology; emergency department; informatics. ACADEMIC EMERGENCY MEDICINE 2004; 11:1155–1161.
The term ‘‘emergency room’’ has been abandoned by the specialty of emergency medicine (EM) in favor of the more inclusive term ‘‘emergency department’’ (ED). This reflects the multifaceted nature of EM, which includes serving as a location for not only emergent care, but also the education of care providers, EM research, involvement in public health, emergency medical services, toxicology, disaster management, and much more. The ED enterprise requires sophisticated management or quality will suffer, and that management is highly data-dependent. Without data, ED managers are ‘‘driving with blinders,’’ forced into a trial-and-error mode in which even determining the success of a trial is a matter of subjective feeling and guesswork. Emergency department management occurs on multiple levels, including long-term and near-term planning as well as real-time management of the minute-to-minute ED clinical operation. Ensuring access to data and data management tools for man-
agers, clinicians, academicians, and the other members of the ED is a critical function of the ED manager and the focus of this article.
From the Division of Emergency Medicine, Evanston Northwestern Healthcare, Northwestern University Medical School (MG), Evanston, IL; Department of Emergency Medicine, Boston University School of Medicine, and Boston Medical Center (TR), Boston, MA; Mayo Clinic College of Medicine (VS), Rochester, MN; and Swedish Medical Center (MK), Seattle, WA. Address for correspondence and reprints: Michael Gillam, MD, Evanston Northwestern Healthcare, Division of Emergency Medicine, 2650 Ridge Avenue, Evanston, IL 60201. E-mail: gillam@ mailblocks.com. doi:10.1197/j.aem.2004.08.009
CONSENSUS STATEMENT 1 Information systems should adhere to open database standards that allow any or all data to be retrieved and exported by authorized users. A data dictionary and methods for decryption should be supplied. Current health information technology (IT) vendors, especially ED information system (EDIS) vendors, have developed systems with relatively proprietary data storage schemas. While interoperability of the EDIS with other hospital systems is expected, open access to the raw data of the EDIS is rarely a feature. No standard currently exists to suggest the best method for data storage of health information in EDIS systems. However, the consensus panel agrees that the ability to search and mine ED data will become an essential strategic element of ED operations in the future.1–3 Vendors should be encouraged to store data in industry-standard database formats and make available to customers a schematic of how data are stored and represented within the EDIS. While a number of vendors have created tools within the EDIS to create ad hoc queries of EDIS data, the panel encourages provision of a more powerful tool for direct access to data (in particular, the Structured Query Language). An open database structure allows administrators, researchers, and other investigators the ability to use
1156
Gillam et al.
third-party tools (i.e., Crystal Reports, Microsoft Query Analyzer) to analyze and graphically represent the results of an infinite number of queries. Furthermore, open access to EDIS data allows complex queries of data across multiple information systems. For example, 1) an investigator should be able to query an EDIS database for all patient visits for nausea/vomiting within two weeks of a visit in which a macrolide antibiotic was prescribed, 2) an individual physician should be able to query data on return visits within 72 hours resulting in admission for patients he or she has seen and be provided with a benchmark for providers within the same institution, and 3) an investigator from hospital leadership should be able to query ED visits against a known table of patients enrolled in an established clinic database. In lieu of open data access, vendors should provide the means to export EDIS data in a format suitable for the establishment of a queryable data warehouse accessible to these and other standards-based thirdparty tools or to provide robust, self-contained query tools within the application with the ability to perform universal queries and automatically export data in real time to other systems as needed using commonly accepted standards. Whoever has information fastest and uses it wins. —Karen Watterson
CONSENSUS STATEMENT 2 Emergency departments should be provided with the data necessary to manage their departments administratively, academically, and for clinical care. Data should be provided in a standard digital format. At minimum, data to be provided include the following: d d
d
d d d d
Admission/discharge/transfer information Performance metrics (time of arrival, time to triage, time to bed placement, time to room, time to physician first seen, time first medication given, time orders placed, time orders completed, time bed requested, time bed obtained, time transferred to floor, and so on) Any and all needed laboratory data (current and historical) Medication administration data (current and historical) Archived medical records Billing data On-staff physician contact information (e.g., office, home, and pager, addresses)
The panel consensus is that EDs without comprehensive information systems should still be provided with admission/discharge/transfer data (data in the hospital registration system), laboratory data relevant to ED operations (both aggregate data on utilization and patient-specific data), and pharmacy data (aggregate departmental and provider prescribing patterns and individual patient administration). Data available
d
IT AND REPORTING
from other hospital systems should be made available in electronic format to ED administration. Comprehensive EDIS systems should provide the functionality necessary to provide care in an accurate and timely fashion. Emergency care providers working with an EDIS should have ready electronic access to all current and legacy patient data, including laboratory results, diagnostic test results, consultations, and outpatient and inpatient medical records. Data archived in other hospital ITsystems should be viewable within the EDIS directly or via context mapping (Clinical Context Object Workgroup) to streamline access to other hospital systems.4,5 ED administrators, researchers, and other investigators should have the ability to query all data relevant to a particular ED visit as well as aggregate data for the entire department. Standard ED metrics, including time of arrival, time to triage, time to bed placement, time to room, time to physician first seen, time first medication given, time orders placed, time orders completed, time bed requested, time bed obtained, and time transferred to floor, are essential to managing and analyzing the discrete steps and bottlenecks in ED workflows.6 These metrics should be captured automatically, without significant manual entry by providers. Objective evidence of the benefit of passive tracking systems in the ED should be sought. Physicians and other providers working in the ED should have ready access to staff physician rosters, on-call rosters, administrative and emergency numbers, disaster plans, policies and procedures, and other hospital administrative data. Such data should be available in electronic form, preferably on a hospital-wide intranet. Technology is dominated by two types of people: those who understand what they do not manage, and those who manage what they do not understand. —Archibald Putt
CONSENSUS STATEMENT 3 Emergency medicine departments should recognize and appoint individuals with expertise in EM informatics, create organizational structures to support scholarly work, and recognize accomplishments in informatics. Medical informatics is a well-recognized discipline in medicine, spawning a number of major organizations and a number of journals. Because the ED is a uniquely situated player in the health care enterprise with unique information needs, the panel believes that academic EM departments should seek to identify individuals with specific skills and interest in medical informatics and encourage individual investigation in informatics research, strategic partnerships with medical informaticians in other specialties, and membership and participation in national organizations.7–9 Experts in EM informatics are in a particular position to do the following:
ACAD EMERG MED
d
d
d
d
d
d
November 2004, Vol. 11, No. 11
d
1157
www.aemj.org
Stay abreast of major developments in health care information technology as they pertain to EM Represent EM in collaborative informatics projects with other academic departments Provide strategic planning and oversight in major research initiatives requiring data collection, analysis, and management Represent departmental interests with hospital IT leadership Most importantly, lead the charge in IT implementations in the ED
The panel also believes that membership and representation by the EM community at large within larger health informatics organizations should be fostered by the Society for Academic Emergency Medicine (SAEM). The society should pursue representation and task members with particular expertise in informatics to become involved with projects such as the National Health Information Infrastructure (Department of Health and Human Services), the Unified Medical Language System (National Library of Medicine), the Integrated Advanced Information Management Systems project (National Library of Medicine), industry standards development projects such as Health Level 7 (HL7), and national biosurveillance initiatives.
CONSENSUS STATEMENT 4 Emergency department registration and information systems should facilitate the identification and enrollment of patients in ongoing research. The timely, accurate, and expedient collection of data for research in EM can build the foundation for future knowledge and progress in EM. Several challenges face data collection efforts in EM. High ED patient volumes can drain clinician time. Research typically has little, if any, direct impact on immediate patient care and therefore is often overlooked. Multiple providers working shifts, many of whom will have forgotten or simply were not informed that studies are under way, can result in lost opportunities for recruiting. The recall of specific enrollment criteria can also pose patient recruitment challenges. Information technology is particularly adept at performing routine processes without common human failings. Figuratively speaking, computer systems never forget, are always vigilant, and can effortlessly perform simple and complex decision tree analysis. Automated systems for identifying patients eligible for studies could facilitate patient recruitment through reminders. These systems could make use of existing digital data, including chief complaints, vital signs, or admission diagnoses. Automated patient recruitment systems also offer the promise of reducing patient sampling bias or convenience sampling. The idea of automated identification and/or registration for clinical trials and research is not new. There have been calls for automated collection and delivery
of data for biosurveillance and injury reporting since computerized records became available.10,11 Indiana University School of Medicine has used systems to identify and enroll patients for breast cancer treatment.12 Computer systems have been shown in other studies to significantly improve patient recruitment.13,14 The consensus panel recommends making a concerted effort in EM to design systems with the ability to facilitate patient recruiting in EM to develop a foundation upon which future scientific and management principles are built.
CONSENSUS STATEMENT 5 Emergency department administrators, clinicians, and researchers should be provided with a choice of visual and statistical tools with which to analyze their data and the training to use them effectively. It has been said that a picture is worth a thousand words. Nowhere is this more apparent than in the realm of data analysis. Images can convey huge amounts of data in a moment, as well as messages or meanings that are not readily apparent when observing the raw data. Data visualization can be defined as ‘‘the use of computer-supported, interactive, and dynamic visual representations of data to amplify cognition.’’15 Data analysis tools can be as simple as those in Excel (Microsoft Corp., Redmond, WA) or as complex as SAS (SAS Institute Inc., Cary, NC) and as plain as a spreadsheet or as elaborate as SPSS MapInfo (SPSS Inc., Chicago, IL), which provides geographical mapping and spatial analysis for data sets. Data mining, the process of finding knowledge hidden within existing data stores, has been a commonly used technique for many years by other industries.16,17 The Food and Drug Administration and World Health Organization both use data mining approaches to detect adverse drug events.18 Many tools exist for performing different types of data mining tasks, including Enterprise Miner from SAS, Clementine from SPSS, and Oracle Data Mining (Oracle Corp., Redwood Shores, CA). Given the value data mining has demonstrated in other industries, the Consensus Committee recommends giving a choice of visual and statistical tools to specific ED personnel. The committee also recommends that, given the complex nature of many of these tools, training in their use should be provided. The availability of technically skilled individuals at the hospital organization but outside of the ED is viewed as beneficial but not completely adequate. The committee believes that the ability of the ED to have an independent cohort of skilled individuals for data mining is necessary for optimal benefits to be realized from data mining.
CONSENSUS STATEMENT 6 Emergency departments should have software-based automated alarm functionality available for monitoring their data from clinical and nonclinical software systems.
1158 d
d d
Gillam et al.
Thresholds should be user configurable based on chosen rules. Alarms should act in a real-time fashion. Triggered alarms should be able to contact individuals by e-mail, pager, or fax and should be scalable to alert multiple individuals.
The Institute of Medicine report in 1999 recognized that ‘‘to err is human.’’19 Humans have been found to be unreliable in tasks that require sustained attention. Exacerbating this problem is the 24/7 nature of hospital work. Although few studies have specifically studied the effect of fatigue on adverse events in medicine, a report by the Association of Professional Sleep Societies concluded that nighttime operators’ fatigue contributed to four well-known disasters: Exxon Valdez, Bhopal, Chernobyl, and Three Mile Island.20 Fatigue has also been implicated in aircraft crashes21 and in poor driving and collisions among truck drivers.22 Computers can perform tasks of vigilance without the effects of fatigue. Additionally, computers can perform surveillance of large amounts of data in a reliable fashion with consistent performance. The Consensus Committee recommends that computers play an increasing and critical role in monitoring clinical data and performing epidemiologic surveillance. The Consensus Committee envisions several scenarios that demonstrate the types of alarming and monitoring systems needed. For example, systems should be able to monitor for both syndromic-type data and specific diagnoses. Severe acute respiratory syndrome and anthrax can both present with flu-like symptoms. A spike in the incidence of this syndrome should trigger an alert to relevant authorities. Knowledge of meningitis epidemics could trigger physicians to lower their threshold for performing lumbar punctures. A sudden surge in meningitis cases should trigger alerts to all practicing physicians. Automated systems to perform these and other types of surveillance and alert individuals by e-mail, pager, or fax could replace the unmaintainable task of daily human review of these data. More methods exist for triggering alarms and thresholds than could be covered in this brief review. Various statistical approaches are optimized for business data and others for particular cohorts of patients or disease. Given the extreme variability of the methods and the evolving knowledge set behind the application of these approaches, the Consensus Committee recommends that the threshold triggers for alarms be user-configurable and support simple to complex rules.
CONSENSUS STATEMENT 7 Emergency departments should have the ability to export reports or other data under circumstances as deemed necessary by ED administrators.
d d
d
d
IT AND REPORTING
Methods should allow for secure export. Methods should support deidentification of data when needed. Methods should allow reports to be sent at multiple intervals, including real time.
The need for data reporting in EM is acute and not yet optimized on either a local or a national level. Data reporting needs to occur for a variety of situations, including syndromic surveillance and biodefense, injury surveillance and prevention, and reporting for public health. Currently, the United States has no single nationwide system to alert health and emergency officials of a fast-moving epidemic or biological attack. Congress and the President have recognized the need for data reporting, and a key provision of the recently enacted (summer 2002) Homeland Security Funding Bill contains a provision for up to $4.5 billion to assist the Centers for Disease Control and Prevention (CDC) and state health departments in creating an ED-based syndromic surveillance system with local area reporting occurring horizontally to state health departments and national reporting occurring vertically to the CDC. Multiple national efforts exist to create networks of shared data, including the Health Alert Network,23 National Electronic Disease Surveillance System (NEDSS),24 the Frontlines of Medicine Project,25 and National Biosurveillance Testbed.26 The Health Alert Network is being developed as part of the CDC’s Public Health Emergency Preparedness & Response Program. IT specifications have been delineated and validated. The Health Alert Network is a communications system for state public health departments, hospitals, clinics, EDs, laboratories, law enforcement, fire service, emergency medical services, volunteer services, and other health agencies. The NEDSS is an initiative that promotes the use of data and information system standards to advance the development of efficient, integrated, and interoperable surveillance systems at federal, state, and local levels. A primary goal of the NEDSS is the ongoing, automatic capture and analysis of data that are already available electronically. The Frontlines of Medicine Project is a collaborative effort of EM (including emergency medical services and clinical toxicology), public health, federal, state, and local emergency agencies, law enforcement, and informatics to develop a nonproprietary, ‘‘open systems’’ approach for reporting and sharing ED patient data. The National Biosurveillance Testbed in Washington, DC, aims to create a research-quality archive of ED visit data for scientists to develop and test innovative approaches to performing biothreat surveillance and discovering surrogate measures for quality of care. The Consensus Committee suggests that the autonomy of EDs to direct the Health Insurance Portability and Accountability Act–compliant sharing of data is
ACAD EMERG MED
d
November 2004, Vol. 11, No. 11
d
1159
www.aemj.org
an essential step to ensuring these national public health efforts benefit the greatest number of patients.
CONSENSUS STATEMENT 8 Emergency department leadership should be encouraged to strategically acquire mission-critical equipment that is networked and capable of automated feedback regarding functional status and location. Supported functions should include, but are not limited to, battery charge, need for repair, need for routine maintenance, and need for supply refill. Joint Commission on Accreditation of Healthcare Organizations standard EC.1.6 outlines the requirement for hospitals to have plans for managing and maintaining equipment.27 Few systems today support means to automatically identify the status of equipment in the ED from a single central location. Manual means of checking equipment can be time-consuming and can fail if operators are not vigilant. Practicing physicians can relate anecdotal stories of care delay due to equipment failure. These failure points can arise from unexpected sources not originally recognized as mission-critical. Delivering emergency care is a highly integrated system-dependent process. The failure of a single element in the system can ripple back to an ED, resulting in critical delays in the delivery of care. In complex systems theory, the sensitivity of output to initial conditions is a marker of a function with chaotic features. Chaotic refers to a pattern of complexity and is not to be confused with random. This phenomenon is also seen in the ‘‘butterfly effect,’’ the phenomenon whereby a small change at one place in a complex system can have a large effect elsewhere (e.g., a butterfly flapping its wings in Brazil might, through a summation of small effects, lead to a tornado in Texas).28 Recognizing that the ED is a system with chaotic features helps us to understand that the ED is subject to multiple, largely unpredictable points of failure. These are often related to things that require vigilant attention to maintain optimal performance. The failure of a printer can prevent patients from receiving thorough descriptions of discharge diagnoses. The failure of a software system can prevent the timely retrieval of an electrocardiogram. Emergently securing an airway closing from anaphylaxis can be impeded by a burned-out bulb on a fiber-optic bronchoscope. Automated systems that monitor mission-critical equipment can remove perturbations from the ED, alert individuals to trigger repair or replacement requests, and prevent discovery of system problems at their moment of critical need. Uptime monitoring for computer systems is widely regarded as necessary in the health care field29,30,31 and others.31 Evidence for the widespread need for tools to monitor systems, processes, tools, and per-
sonnel is largely anecdotal. However, as the cost for integrated wireless systems decreases, the cost–benefit ratio for monitoring improves. The Consensus Committee recommends that ED leadership encourage the development and procurement of mission-critical equipment with the ability to broadcast functional status to central monitoring systems across a network.
CONSENSUS STATEMENT 9 The field of EM should dedicate resources toward informatics research and development. Suggested areas include, but are not limited to, the following: d d
d
d
Wireless tracking technologies Maintaining evidence-based medicine practice through the digital-age information explosion Data sharing between EDs and public health agencies for bioterrorism and emerging disease surveillance Data mining—determining metrics useful for optimizing ED care.
The application of IT to medicine (medical informatics) holds the promise of improving organizational management,32 improving patient care,33 and supporting evidence-based practice.34 The Consensus Committee recommends several areas as representing high-potential informatics technologies that should be given priority research attention and funding. Wireless Tracking. Technologies for tracking patients, providers, and assets have begun to show promise for use in routine ED care. Both radiofrequency identification (RFID) and ultrawide band (UWB) technologies are available. UWB is a newer technology allowing for real-time, multiaxis tracking at a higher resolution than RFID (down to 1 cm3) with improved interference tolerance. Fleet Hospital Three operated by the U.S. Navy in Southern Iraq is using RFID technology to track the status and location of hundreds of wounded soldiers, airmen, prisoners of war, refugees, and others arriving for treatment.35 Summa Health Systems in Akron, Ohio, uses RFID tracking in the ED to identify patient flow bottlenecks and track real-time patient throughput. RFID is being studied in a Memphis ED to reduce patient waiting times.36,37 In Singapore and Taiwan, tracking technology has been essential in containing the outbreak of severe acute respiratory syndrome. Previously, severe acute respiratory syndrome contact tracing using manual methods took two full days. With RFID, contact tracing takes minutes.38,39 Toronto has deployed RFID tracking to ensure newborns are not abducted from nurseries.40 Johns Hopkins is testing RFID to track intravenous bags. Georgetown University Hospital is preparing a head-to-head trial of RFID versus bar codes to track blood products from donor to patient. M. D. Anderson Cancer Center in Houston is
1160 looking at RFID for inventory control after internal thefts of the highly expensive medications Procrit and Neupogen.41 Tracking technology holds the possibility of allowing EDs to improve their surge capacity, enhance situational awareness on a day-to-day basis and during disasters, perform highly effective contact tracing should biothreats emerge, and increase their ability to manage patient throughput. Evidence-based Medicine. The typical primary care physician must stay abreast of approximately 10,000 diseases and syndromes, 3,000 medications, and 1,100 laboratory tests.42 The amount of scientific information available is increasing faster each year. In 2003, the National Library of Medicine catalogued almost 570,000 article citations from the biomedical literature alone.43 According to Berkeley researchers, more information was produced and stored in the past five years than at any time in human history.44 The amount of knowledge to be reviewed across the specialties increases yearly. These data suggest that the ability for a physician to keep track of practicechanging literature is diminishing. It is likely that physicians are practicing based on medical knowledge that may be ten years out of date. If strong evidence for a change in the treatment of a common disease were published in the obstetrics literature today, the propagation delay of this knowledge to other medical fields is unknown. Because cross-publishing is discouraged, months or years might pass before every EM clinician updates his or her clinical practice behavior. Conversely, it is possible that emergency physicians have faced conflicts with consultants who are unfamiliar with the EM literature. In the face of the information explosion in medicine, defining, developing, and evaluating tools that help physicians practice evidence-based medicine is viewed as a high priority by the Consensus Committee. Data Sharing. Data sharing between EDs holds the promise of improving patient care and research in EM. In the absence of an electronically integrated medical record, many of today’s patient records are not available as patients travel between hospitals. The lack of information in the ED has been shown to prolong patient stay.45 In surgical fields, lack of patient data can increase patient mortality for procedures.46 In light of the Institute of Medicine report on decreasing medical errors, the Consensus Committee recommends committing resources to enhance data sharing between EDs and hospitals. Human Factors. The field of human factors concerns itself with human capabilities, human limitations, and man–machine interactions. The goal of human factors research is to optimize human performance and the human–computer interface. Human factors research
Gillam et al.
d
IT AND REPORTING
in high-risk industries, where safety is paramount, has provided the foundation of evidence-based principles to redesign tasks and systems, improve outcomes, and reduce or counter human error.47 Human factors research has been performed extensively in aviation, establishing that poor system design increases the severity of mishaps.48 Applying human factors to medicine is believed to be helpful in accelerating quality improvement in health care.49 The Federal Aviation Administration has a division dedicated to human factors research and engineering.50 The field of medicine could benefit from a similar division dedicated to human factors design in EM. The Consensus Committee recommends funding and research within the field of human factors in EM. Data Mining. Emergency medicine–specific metrics for use in continuous quality improvement are urgently needed. Continuous quality improvement begins with a baseline metric from which to improve. The choice of metric is critical. Without a properly chosen metric, measured progress might not actually reflect improvement in the quality of care or the health of the system. There is a need for consistently defined measures across the EM health care industry.51 The promise of widely recognized, shared metrics for ED performance is the ability to compare performances between EDs, recognize disparities, and catalyze process improvement across all of EM. The Consensus Committee recommends directing research toward uncovering the value of existing digital data in EDs and researching new data elements that can serve as surrogate markers for financial and organizational efficiency and quality of care. References 1. Castellani B, Castellani J. Data mining: qualitative analysis with health informatics data. Qual Health Res. 2003; 13:1005–18. 2. Hagland M. Data mining. Stronger computer tools allow deeper analysis of medical research, patient care and insurance data. Healthc Inform. 2004; 21:33–6. 3. Veletsos A. Getting to the bottom of hospital finances. Florida Hospital, an experienced data miner, stretches its extensive use of data mining to deliver financial results that will improve its bottom line. Health Manag Technol. 2003; 24:30–1. 4. Shablinsky I, Starren J, Friedman C. What do ER physicians really want? A method for elucidating ER information needs. Proc AMIA Symp. 1999; 390–4. 5. Smith MS, Feied CF. The next-generation emergency department. Ann Emerg Med. 1998; 32:65–74. 6. Cordell WH, Overhage JM, Waeckerle JF. Strategies for improving information management in emergency medicine to meet clinical, research, and administrative needs. Ann Emerg Med. 1998; 31:172–8. 7. Cordell WH. Information technologies for emergency medicine. Acad Emerg Med. 1994; 1:194–7. 8. Teich JM, Waeckerle JF. Emergency medical informatics. Ann Emerg Med. 1997; 30:667–9. 9. Walker K. Emergency medicine. Informatics in the ED: progress in the new millennium? MD Comput. 2000; 17:30–2.
ACAD EMERG MED
d
November 2004, Vol. 11, No. 11
d
www.aemj.org
10. Weiss HB, Dill SM, Forjuoh SN, et al. Injury surveillance: a statewide survey of emergency department data collection practices. Ann Emerg Med. 1996; 28:635–40. 11. Irvin CB, Nouhan PP, Rice K. Syndromic analysis of computerized emergency department patients’ chief complaints: an opportunity for bioterrorism and influenza surveillance. Ann Emerg Med. 2003; 41:447–52. 12. Breitfeld PP, Weisburd M, Overhage JM, Sledge G Jr, Tierney WM. Pilot study of a point-of-use decision support tool for cancer clinical trials eligibility. J Am Med Inform Assoc. 1999; 6:466–77. 13. Butte AJ, Weinstein DA, Kohane IS. Enrolling patients into clinical trials faster using RealTime Recuiting. Proc AMIA Symp. 2000; 111–5. 14. Weiner DL. Computerized recruiting for clinical trials in real time. Ann Emerg Med. 2003; 41:242–6. 15. Meyer RD, Cook D. Visualization of data. Curr Opin Biotechnol. 2000; 11:89–96. 16. Hobbs GR. Data mining and healthcare informatics. Am J Health Behav. 2001; 25:285–9. 17. Hagland M. Data mining: stronger computer tools allow deeper analysis of medical research, patient care and insurance data. Healthc Inform. 2004; 21:33–6. 18. Jones JK. The role of data mining technology in the identification of signals of possible adverse drug reactions: value and limitations. Curr Ther Res. 2001; 62:664–72. 19. Kohn LT, Corrigan JM, Donaldson MS (eds). To Err Is Human: Building a Safer Health System. Committee on Quality of Health Care in America. Washington, DC: Institute of Medicine, 1999. 20. Mitler MM, Carskadon MA, Czeisler CA, Dement WC, Dinges DF, Graeber RC. Catastrophes, sleep, and public policy: consensus report. Sleep. 1988; 11:100–9. 21. Rosekind MR, Gregory KB, Miller DL, Co EL, Lebacqz JV. Aircraft Accident Report: Uncontrolled Collision with Terrain, American International Airways Flight 808, Douglas DC-8, N814CK, U.S. Naval Air Station, Guantanamo Bay, Cuba, August 18, 1993. Washington, DC: National Transportation Safety Board, 1994. 22. Wylie CD, Shultz T, Miller JC. Commercial Motor Vehicle Driver Fatigue and Alertness Study. Columbia, MD: Essex Corporation, Oct 1996. 23. Centers for Disease Control and Prevention. Public Health Information Technology Functions and Specifications (for Emergency Preparedness and Bioterrorism). Available at: http://www.cdc.gov/cic/functions-specs/IT_Functions_ Specifications_final_21402.pdf. Accessed May 15, 2004. 24. Centers for Disease Control and Prevention. An Overview of the NEDSS Initiative. Available at: http://www.cdc.gov/ nedss/About/overview.html. Accessed May 15, 2004. 25. Barthell EN, Cordell WH, Moorhead JC, et al. The Frontlines of Medicine Project: a proposal for the standardized communication of emergency department data for public health uses including syndromic surveillance for biological and chemical terrorism. Ann Emerg Med. 2002; 39:422–9. 26. Institute for Medical Informatics. Project Sentinel at the National Biosurveillance Testbed. Available at: http:// www.imedi.org/testbed.htm. Accessed Jan 2004. 27. Joint Commission on Accreditation of Healthcare Organizations. Available at: http://www. commonsensedirections.org/html/Adjunct%20Pages/ JCAHO.htm. Accessed May 15, 2004. 28. Hilborn RC. Chaos and Nonlinear Dynamics. New York, NY: Oxford University Press, 1994. 29. Liu BJ, Cao F, Zhou MZ, Mogel G, Documet L. Trends in PACS image storage and archive. Comput Med Imaging Graph. 2003; 27:165–74.
1161 30. Huffman S. The goal of uptime. With the right framework you can fashion a guaranteed system availability contract that works for you. Healthc Inform. 2002; 19:65–6. 31. Chauhaun A. Business Considerations for Uptime. Microsoft TechNet. April 1, 2000. Available at: http://www. microsoft.com/technet/itsolutions/ecommerce/plan/ buscons.mspx. Accessed May 15, 2004. 32. Ruffin M. Medical informatics. The future is here. Physician Exec. 1996; 22:22–8. 33. Carter JH. Medical informatics in postgraduate training: a way to improve office based practitioner information management. J Gen Intern Med. 1991; 6:349–54. 34. Johnson T, Ventura R. Applied informatics for quality assessment and improvement. J Nurs Care Qual. 2004; 19:100–4. 35. RFID technology helps Navy hospital track wounded soldiers and POWs in Iraq, CR80News. Available at: http://www. cr80news.com/library/2003/05/01/rfid-technology-helpsnavy-hospital-track-wounded-soldiers-and-pows-in-iraq/. Accessed May 15, 2004. 36. Achieving better patient care with supply management technology. Urgent Matters. 2003; 1(1). Available at: http:// www.urgentmatters.org/enewsletter/vol1_issue1/ demonstrating_emerging_technology.htm. Accessed May 15, 2004. 37. Shelby County Regional Medical Centre Patient Tracking. Available at: http://www.idtechex.com/knowledgebase/en/ casestudy.asp?casestudyid=310. Accessed May 15, 2004. 38. Nadarajan B. New system offers faster contact tracing. The Straits Times Interactive. May 21, 2004. Available at: http:// straitstimes.asia1.com.sg/sars/story/0,4395,187218,00.html. Accessed May 15, 2004. 39. Taiwan uses RFID to combat SARS. RFID Journal. Aug 1, 2003. Available at: http://www.rfidjournal.com/article/view/520. Accessed May 15, 2004. 40. RFID: coming to a hospital near you. Boardroom Minutes. Available at: http://www.sun.com/br/0404_ezine/ hc_rfid.html. Accessed May 15, 2004. 41. Hospitals start pilot testing RFID to curb drug diversion. Drug Top Arch. 2004; May 17. Available at: http:// www.drugtopics.com/be_core/content/journals/d/data/ 2004/0517/d12rfid05a.html. Accessed May 15, 2004. 42. Davenport TH, Glaser J. Just-in-time delivery comes to knowledge management. Harv Bus Rev. 2002; 80:107–11, 126. 43. National Library of Medicine. PubMed. Available at: http://www.ncbi.nlm.nih.gov/entrez/utils/pmqty. fcgi?db=m&dopt=q&term=2003[dp]. Accessed May 15, 2004. 44. Lyman P, Varian HR. How much information. University of California, Berkeley, 2003. Available at: http://www. sims.berkeley.edu/how-much-info/. Accessed May 15, 2004. 45. Stiell A, Forster AJ, Stiell IG, van Walraven C. Prevalence of information gaps in the emergency department and the effect on patient outcomes. Can Med Assoc J. 2003; 169:1023–8. 46. Bahn CH, Annest LS. Reoperation without medical records: avoidable? J Thorac Cardiovasc Surg. 1986; 91:139–41. 47. Weinger MB, Slagle J. Human factors research in anesthesia patient safety. Proc AMIA Symp. 2001; 756–60. 48. Krulak DC. Human factors in maintenance: impact on aircraft mishap frequency and severity. Aviat Space Environ Med. 2004; 75:429–32. 49. Silver MP, Geis MS, Bateman KA. Improving health care systems performance: a human factors approach. Am J Med Qual. 2004; 19:93–102. 50. Federal Aviation Administration, Human Factors Research and Engineering Division. Available at: http:// www.hf.faa.gov/. Accessed May 15, 2004. 51. Proctor J. The business of emergency medicine: a model for success. Emerg Med Clin North Am. 2004; 22:19–45.