Core content for the subspecialty of clinical informatics.

The Core Content for Clinical Informatics defines the boundaries of the discipline and informs the Program Requirements for Fellowship Education in Clinical Informatics. The Core Content includes four major categories: fundamentals, clinical decision making and care process improvement, health information systems, and leadership and management of change. The AMIA Board of Directors approved the Core Content for Clinical Informatics in November 2008.

Assessing data quality in manual entry of ventilator settings.

OBJECTIVE: To evaluate the data quality of ventilator settings recorded by respiratory therapists using a computer charting application and assess the impact of incorrect data on computerized ventilator management protocols. DESIGN An analysis of 29,054 charting events gathered over 12 months from 678 ventilated patients (1,736 ventilator days) in four intensive care units at a tertiary care hospital. MEASUREMENTS: Ten ventilator settings were examined, including fraction of inspired oxygen (Fio (2)), positive end-expiratory pressure (PEEP), tidal volume, respiratory rate, peak inspiratory flow, and pressure support. Respiratory therapists entered values for each setting approximately every two hours using a computer charting application. Manually entered values were compared with data acquired automatically from ventilators using an implementation of the ISO/IEEE 11073 Medical Information Bus (MIB). Data quality was assessed by measuring the percentage of time that the two sources matched. Charting delay, defined as the interval between data observation and data entry, also was measured. RESULTS: The percentage of time that settings matched ranged from 99.0% (PEEP) to 75.9% (low tidal volume alarm setting). The average charting delay for each charting event was 6.1 minutes, including an average of 1.8 minutes spent entering data in the charting application. In 559 (3.9%) of 14,263 suggestions generated by computerized ventilator management protocols, one or more manually charted setting values did not match the MIB data. CONCLUSION: Even at institutions where manual charting of ventilator settings is performed well, automatic data collection can eliminate delays, improve charting efficiency, and reduce errors caused by incorrect data.

Use of a personal digital assistant for managing antibiotic prescribing for outpatient respiratory tract infections in rural communities.

OBJECTIVE: To assess the acceptability and usage of a standalone personal digital assistant (PDA)-based clinical decision-support system (CDSS) for the diagnosis and management of acute respiratory tract infections (RTIs) in the outpatient setting. DESIGN: Observational study performed as part of a larger randomized trial in six rural communities in Utah and Idaho from January 2002 to March 2004. Ninety-nine primary care providers received a PDA-based CDSS for use at the point-of-care, and were asked to use the tool with at least 200 patients with suspected RTIs. MEASUREMENTS: Clinical data were collected electronically from the devices at periodic intervals. Providers also completed an exit questionnaire at the end of the study period. RESULTS: Providers logged 14,393 cases using the CDSS, the majority of which (n=7624; 53%) were from family practitioners. Overall adherence with CDSS recommendations for the five most common diagnoses (pharyngitis, otitis media, sinusitis, bronchitis, and upper respiratory tract infection) was 82%. When antibiotics were prescribed (53% of cases), adherence with the CDSS-recommended antibiotic was high (76%). By logistic regression analysis, the odds of adherence with CDSS recommendations increased significantly with each ten cases completed (P=0.001). Questionnaire respondents believed the CDSS was easy to use, and most (44/65; 68%) did not believe it increased their encounter time with patients, regardless of prior experience with PDAs. CONCLUSION: A standalone PDA-based CDSS for acute RTIs used at the point-of-care can encourage better outpatient antimicrobial prescribing practices and easily gather a rich set of clinical data.

Viewpoint: a pragmatic approach to constructing a minimum data set for care of patients with HIV in developing countries.

Providing quality health care requires access to continuous patient data that developing countries often lack. A panel of medical informatics specialists, clinical human immunodeficiency virus (HIV) specialists, and program managers suggests a minimum data set for supporting the management and monitoring of patients with HIV and their care programs in developing countries. The proposed minimum data set consists of data for registration and scheduling, monitoring and improving practice management, and describing clinical encounters and clinical care. Data should be numeric or coded using standard definitions and minimal free text. To enhance accuracy, efficiency, and availability, data should be recorded electronically by those generating them. Data elements must be sufficiently detailed to support clinical algorithms/guidelines and aggregation into broader categories for consumption by higher level users (e.g., national and international health care agencies). The proposed minimum data set will evolve over time as funding increases, care protocols change, and additional tests and treatments become available for HIV-infected patients in developing countries.

Detection and prevention of medication errors using real-time bedside nurse charting.

OBJECTIVE: Charting systems with decision support have been developed to assist with medication charting, but many of the features of these programs are not properly used in their clinical application. An analysis of medication error reports at LDS Hospital revealed the occurrence of errors that should have been detected and prevented by decision support features if real-time entry at the bedside had taken place. The aim of this study was to increase the real-time bedside charting behavior of nurses. DESIGN: A quasiexperimental before and after design was used. The study took place in two 40-bed surgical units, one of which served as the study unit, the other as control unit. The study unit received educational intervention about error avoidance through real-time bedside charting, and 12 weeks of monitoring and performance feedback. The real-time and bedside charting rates for the study and control units were measured before and after the intervention. RESULTS: Before the intervention on the study unit, the real-time charting rate was 59% and the bedside rate was 40%. At the conclusion of a 12-week intervention period, the real-time rate increased to 73% and the bedside rate increased to 63%. Postintervention real-time rates were 75% after eight weeks and remained at 75% after one year. Equivalent control unit real-time rates varied from 53% to 57%, and bedside rates varied from 34% to 44% during the same intervals. CONCLUSION: Targeted educational intervention and monitored feedback yielded measurable improvements in the effective use of the computerized medication charting system and must be an ongoing process.

The effect of a computerized reminder system on the prevention of postoperative venous thromboembolism.

STUDY OBJECTIVE: To measure the effect of an altered process of care, directed by a computerized reminder system, on rates of symptomatic postoperative venous thromboembolism. DESIGN: Comparisons of preintervention and postintervention measurements. SETTING: A university-affiliated community hospital in Utah. PATIENTS: Two-thousand seventy-seven consecutive patients who underwent major operations in four surgical divisions between January 1, 1997, and October 31, 1997 (preintervention), and 2,093 consecutive patients who underwent the same procedures between January 1, 1998, and October 31,1998 (postintervention). INTERVENTION: A program to prevent venous thromboembolism developed from American College of Chest Physicians guidelines, and an altered work process directed by a computerized reminder system. MEASUREMENTS: Rates of symptomatic, objectively confirmed deep vein thrombosis (DVT), pulmonary embolism (PE), and death attributable to venous thromboembolism occurring within 90 days of the date of surgery. RESULTS: The preintervention and postintervention cohorts did not differ with respect to age, severity of illness, number of risk factors for venous thromboembolism, or individual risk factors for venous thromboembolism. The overall prophylaxis rate increased from 89.9% before implementation of the computerized reminder system to 95.0% after implementation (p < 0.0001). The combined 90-day rate of symptomatic DVT, PE, and death attributable to PE remained the same (preintervention, 1.0%; postintervention, 1.2%; odds ratio, 1.21; 95% confidence interval, 0.67 to 2.20). Forty of 46 venous thromboembolic complications (87%) occurred despite the delivery of American College of Chest Physicians-recommended measures to prevent venous thromboembolism. CONCLUSIONS: Computerized reminder systems combined with altered care procedures increase the rate of prophylaxis against venous thromboembolism without decreasing the rate of symptomatic venous thromboembolism when the baseline rate of prophylaxis is high. A population of surgical patients exists who are resistant to American College of Chest Physicians-recommended prophylactic measures against venous thromboembolism. New strategies are needed to address prophylaxis-resistant venous thromboembolism.

Computerized clinical decision-support in respiratory care.

Computers were initially used in health care for billing and administrative functions. More recently computers have been used to present clinical information such as laboratory results and pharmacy orders. Many medical informatics researchers believe that the ultimate goal of the "electronic health record" should be to advance computerized clinical decision-support. This report considers the challenges of developing electronic-health-record systems and integrating them into useful computerized decision-support systems and presents a "pyramid of progress" concept that involves 5 steps: (1) to gather electronic health data into a standardized and coded format, (2) to validate the quality of that electronic health data, (3) to optimize presentation of electronic health data and explore computerized decision-support, (4) to develop and share computerized knowledge bases that are based on clinical evidence as well as consensus, and (5) to tailor and to implement the computerized strategies so that they fit into the workflow process of patient care. This report discusses 3 examples of successful computerized clinical decision-support (use of antibiotics, laboratory alerting, and ventilator management) and discusses strategies essential to making computerized clinical decision-support more widely available and useful.

Surveillance of medical device-related hazards and adverse events in hospitalized patients.

CONTEXT: Although adverse drug events have been extensively evaluated by computer-based surveillance, medical device errors have no comparable surveillance techniques. OBJECTIVES: To determine whether computer-based surveillance can reliably identify medical device-related hazards (no known harm to patient) and adverse medical device events (AMDEs; patient experienced harm) and to compare alternative methods of detection of device-related problems. DESIGN, SETTING, AND PARTICIPANTS: This descriptive study was conducted from January through September 2000 at a 520-bed tertiary teaching institution in the United States with experience in using computer tools to detect and prevent adverse drug events. All 20 441 regular and short-stay patients (excluding obstetric and newborn patients) were included. MAIN OUTCOME MEASURES: Medical device events as detected by computer-based flags, telemetry problem checklists, International Classification of Diseases, Ninth Revision (ICD-9) discharge code (which could include AMDEs present at admission), clinical engineering work logs, and patient survey results were compared with each other and with routine voluntary incident reports to determine frequencies, proportions, positive predictive values, and incidence rates by each technique. RESULTS: Of the 7059 flags triggered, 552 (7.8%) indicate a device-related hazard or AMDE. The estimated 9-month incidence rates (number per 1000 admissions [95% confidence intervals]) for AMDEs were 1.6 (0.9-2.5) for incident reports, 27.7 (24.9-30.7) for computer flags, and 64.6 (60.4-69.1) for ICD-9 discharge codes. Few of these events were detected by more than 1 surveillance method, giving an overall incidence of AMDE detected by at least 1 of these methods of 83.7 per 1000 (95% confidence interval, 78.8-88.6) admissions. The positive predictive value of computer flags for detecting device-related hazards and AMDEs ranged from 0% to 38%. CONCLUSIONS: More intensive surveillance methods yielded higher rates of medical device problems than found with traditional voluntary reporting, with little overlap between methods. Several detection methods had low efficiency in detecting AMDEs. The high rate of AMDEs suggests that AMDEs are an important patient safety issue, but additional research is necessary to identify optimal AMDE detection strategies.

Automated syndromic surveillance for the 2002 Winter Olympics.

The 2002 Olympic Winter Games were held in Utah from February 8 to March 16, 2002. Following the terrorist attacks on September 11, 2001, and the anthrax release in October 2001, the need for bioterrorism surveillance during the Games was paramount. A team of informaticists and public health specialists from Utah and Pittsburgh implemented the Real-time Outbreak and Disease Surveillance (RODS) system in Utah for the Games in just seven weeks. The strategies and challenges of implementing such a system in such a short time are discussed. The motivation and cooperation inspired by the 2002 Olympic Winter Games were a powerful driver in overcoming the organizational issues. Over 114,000 acute care encounters were monitored between February 8 and March 31, 2002. No outbreaks of public health significance were detected. The system was implemented successfully and operational for the 2002 Olympic Winter Games and remains operational today.

Rapid deployment of an electronic disease surveillance system in the state of Utah for the 2002 Olympic Winter Games.

The key to minimizing the effects of an intentionally caused disease outbreak is early detection of the attack and rapid identification of the affected individuals. The Bush administration's leadership in advocating for biosurveillance systems capable of monitoring for bioterrorism attacks suggests that we should move quickly to establish a nationwide early warning biosurveillance system as a defense against this threat. The spirit of collaboration and unity inspired by the events of 9-11 and the 2002 Olympic Winter Games in Salt Lake City provided the opportunity to demonstrate how a prototypic biosurveillance system could be rapidly deployed. In seven weeks we were able to implement an automated, real-time disease outbreak detection system in the State of Utah and monitored 80,684 acute care visits occurring during a 28-day period spanning the Olympics. No trends of immediate public health concern were identified.

Using point of service clinical documentation to reduce variability in charge capture.

Data collected at bedside to document patient care can also be used to generate an itemized summary of charges including activity-based clinician charges. This approach becomes advantageous when the charge capture operation is transparent to the clinician who would otherwise have to review the care documentation, recall the appropriate charging rules, and exercise discretion in capturing charges. Documented procedures and supplies convert directly into patient charge rules. Documented patient care is more difficult to translate into activity-based charges because nursing care can vary in intensity and duration depending on the patient's needs. The problem can be overcome by embedding time or data-driven logic into the charging rules. Using this approach in the labor and delivery units of 7 IHC hospitals (114 beds), we generated consistent charge summaries. We improved the accuracy of patient charges from 65% to over 98% of our charge summaries having no missed charges.

Avaliaçäo de um sistema especialista na detecçäo de infecçöes hospitalares / Specialist system evaluation in detection of hospitalar infections

Um sistema especialista foi avaliado na sua capacidade em detectar infeccções em pacientes pediátricos hospitalizados. O sistema teve uma sensitividade de 100 por cento na detecção de bacteremias e 57 por cento na detecção de infecções cirúrgicas, quando comparado a um "gold-standard".