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R Scott Evans

Publications and source records attributed to R Scott Evans.

17 recordsLinked to original sources
PubMed2005

A case for manual entry of structured, coded laboratory data from multiple sources into an ambulatory electronic health record.

Laboratory results provide necessary information for the management of ambulatory patients. To realize the benefits of an electronic health record (EHR) and coded laboratory data (e.g., decision support and improved data access and display), results from laboratories that are external to the health care enterprise need to be integrated with internal results. We describe the development and clinical impact of integrating external results into the EHR at Intermountain Health Care (IHC). During 2004, over 14,000 external laboratory results for 128 liver transplant patients were added to the EHR. The results were used to generate computerized alerts that assisted clinicians with managing laboratory tests in the ambulatory setting. The external results were sent from 85 different facilities and can now be viewed in the EHR integrated with IHC results. We encountered regulatory, logistic, economic, and data quality issues that should be of interest to others developing similar applications.

Ambulatory Care Information Systems↗
PubMed2005

Enhanced notification of critical ventilator events.

Mechanical ventilators are designed to generate alarms when patients become disconnected or experience other critical ventilator events. However, these alarms can blend in with other accustomed sounds of the intensive care unit. Ventilator alarms that go unnoticed for extended periods of time often result in permanent patient harm or death. We developed a system to monitor critical ventilator events through our existing hospital network. Whenever an event is identified, the new system takes control of every computer in the patient's intensive care unit and generates an enhanced audio and visual alert indicating that there is a critical ventilator event and identifies the room number. Once the alert is acknowledged or the event is corrected, all the computers are restored back to the pre-alert status and/or application. This paper describes the development and implementation of this system and reports the initial results, user acceptance, and the increase in valuable information and patient safety.

Computer Systems↗
PubMed2005

Risk factors for adverse drug events: a 10-year analysis.

BACKGROUND: Many adverse drug events (ADEs) are the result of known pharmacologic properties, and some result from medication errors. However, some are the result of patient-specific risk factors. OBJECTIVE: To identify inpatient risk factors for ADEs. METHODS: Conditional logistic regression was used to analyze all pharmacist-verified ADEs by therapeutic class of drugs and severity during a 10-year study period. All inpatients > or = 18 years of age from a 520-bed tertiary teaching hospital were included. Each case patient was matched with up to 16 control patients. Odds ratios for patient factors associated with ADEs were calculated from different therapeutic classes of drugs. RESULTS: Odds ratios for numerous risk factors were identified for 4376 ADEs and were found to vary depending on therapeutic classification. The risk factors for the different classifications were grouped by (1) patient characteristics--female (OR 1.5-1.7), age (0.7-0.9), weight (1.2-1.4), creatinine clearance (0.8-4.7), and number of comorbidities (1.1-12.6); (2) drug administration--dosage (1.2-3.7), administration route (1.4-149.9), and number of concomitant drugs (1.2-2.4); and (3) patient type--service (1.2-4.9), nursing division (1.5-3.8), and diagnosis-related group (1.5-5.7). CONCLUSIONS: Some risk factors are consistent for all ADEs and across multiple therapeutic classes of drugs, while others are class specific. High-risk agents should be closely monitored based on patient characteristics (gender, age, weight, creatinine clearance, number of comorbidities) and drug administration (dosage, administration route, number of concomitant drugs).

Adolescent↗
PubMed2005

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.

Computer Systems↗
PubMed2005

Development of an information model for storing organ donor data within an electronic medical record.

OBJECTIVE: To develop a model to store information in an electronic medical record (EMR) for the management of transplant patients. The model for storing donor information must be designed to allow clinicians to access donor information from the transplant recipient's record and to allow donor data to be stored without needlessly proliferating new Logical Observation Identifier Names and Codes (LOINC) codes for already-coded laboratory tests. DESIGN: Information required to manage transplant patients requires the use of a donor's medical information while caring for the transplant patient. Three strategies were considered: (1) link the transplant patient's EMR to the donor's EMR; (2) use pre-coordinated observation identifiers (i.e., LOINC codes with *(wedge)DONOR specified in the system axes) to identify donor data stored in the transplant patient's EMR; and (3) use an information model that allows donor information to be stored in the transplant patient's record by allowing the "source" of the data (donor) and the "name" of the result (e.g., blood type) to be post-coordinated in the transplant patient's EMR. RESULTS: We selected the third strategy and implemented a flexible post-coordinated information model. There was no need to create new LOINC codes for already-coded laboratory tests. The model required that the data structure in the EMR allow for the storage of the "subject" of the test. CONCLUSION: The selected strategy met our design requirements and provided an extendable information model to store donor data. This model can be used whenever it is necessary to refer to one patient's data from another patient's EMR.

Databases as Topic↗
PubMed2005

Trauma patient hospital-associated infections: risks and outcomes.

BACKGROUND: Trauma patients with surgical procedures, acute lung injury (ALI), systemic inflammatory response syndrome (SIRS), and longer exposure to invasive devices may be at increased risk for hospital-associated infection (HAI). HAIs have been shown to affect outcome measures, but the extent is not well studied. METHODS: An infection control team identified HAIs in trauma patients from 1996 through 2001. The authors evaluated the relation of HAI to surgical procedures, ALI, SIRS, and device exposure time by comparing groups with and without HAI using Fisher's exact and Mann-Whitney tests. Using multiple linear and logistic regressions, the authors evaluated associations of HAI, age, and Injury Severity Score (ISS) with length of stay (LOS), cost of care, and mortality. They used Cox proportional hazard regression to further explore the relations of HAI, age, and ISS to LOS. RESULTS: In 501 of 5,537 trauma patients with HAI (9.1%), the percent having surgical procedures, ALI, and SIRS was significantly higher (p < 0.001). Exposure to all devices studied was significantly longer (p < 0.001) in HAI patients. When the population was controlled for age and ISS, HAI patients had longer lengths of stay (LOSs) and higher costs. Age had less effect than ISS on LOS, and the effect of increases in age was greater as ISS increased. ISS had a greater effect than HAIs on LOS. HAIs increased LOS more in patients less severely injured. When comparing patients with and without HAI, no difference in mortality rates was detected. CONCLUSION: In this study of trauma patients, ISS had the greatest effect on LOS, but increased age and presence of HAI did increase LOS and cost of care. HAI increased LOS more in the less severely injured patients.

Adult↗
PubMed2005

Unit-wide notification of ventilator disconnections.

The alarms generated by mechanical ventilators when patients become disconnected can blend in with other typical sounds of the intensive care unit. Ventilator alarms that go unnoticed for extended periods of time often result in permanent patient harm or death. We developed a unit-wide system to monitor ventilator disconnection alarms. When a disconnection is identified, the system takes control of every computer in the patient's intensive care unit and generates an enhanced audio and visual alert. This system was tested in four ICUs at LDS Hospital. Acceptance by medical personnel was very high and patient safety was improved through early intervention that avoided prolonged hypoxia. In addition, the system facilitated root cause analyses and new safety strategies.

Equipment Failure↗
PubMed2004

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.

Adult↗
PubMed2004

System-wide surveillance for clinical encounters by patients previously identified with MRSA and VRE.

Methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococci (VRE) have emerged as major infection control problems worldwide. Patients previously infected or colonized with MRSA or VRE need to be identified and often isolated as soon as they visit a health care facility. Infection control personnel usually are not aware when these patients enter their facilities. We developed a system-wide surveillance system to alert infection control personnel when patients with previous MRSA or VRE cultures from LDS Hospital have subsequent clinical encounters at any inpatient or outpatient facility at Intermountain Health Care (IHC). This paper describes this system and includes the results from an initial study on the potential epidemiological benefits provided to help improve patient care. The study found that patients with previous MRSA and VRE had subsequent encounters at 62 different IHC facilities up to 304 miles away from 1 day to over 5 years later. In addition, the new surveillance system was able to alert infection control personnel when ever these patients visited any IHC inpatient or outpatient facility.

Enterococcus↗
PubMed2003

Cost of opioid-related adverse drug events in surgical patients.

Opioids have demonstrated efficacy and often are drugs of choice in the management of postoperative pain. However, their use is often limited by adverse drug events (ADEs). The objective of this study was to determine the ADE rate in adult surgical patients who received opioids and the impact of opioid ADEs on length of stay (LOS), costs, and mortality. A hospital-based computerized system detected potential ADEs. Adult patients were selected if they received at least one dose of opioid medication during a surgical hospitalization between 1 January 1990 and 31 December 1999. Control patients were matched based on matching length of stay ([LOS] at least as long as time to ADE), age (within 10 years), sex, admission year, major disease category (MDC), and without an ADE. Linear regression models were used to determine the predictors of increased LOS, total hospital costs, and log-transformed total hospital costs. 60,722 patients received opioid medication during their surgical hospitalization and 2.7% experienced an opioid-related ADE. The most common clinical manifestations were nausea and vomiting (67%), and rash, hives, or itching (33.5%). No statistically significant difference was seen in mortality between ADE/non-ADE patients. ADE patients had statistically significant increases in LOS (0.53 days) and in log-transformed cost (16%). The estimated log cost difference of 16%, if applied to the median cost patient in the non-ADE group, averaged US$ 840. Opioid-related ADEs are common in hospitalized patients and increase LOS and total hospital costs.

Economics, Pharmaceutical↗
PubMed2003

Decision support in medicine: lessons from the HELP system.

PURPOSE: This report describes an ongoing transition from the HELP Hospital Information System to HELP II, a replacement Health Information System built to manage clinical information captured in a variety of medical settings. The focus of the article is on the medical decision support provided by this system and studied by researchers at the University of Utah and Intermountain Health Care (IHC), a large health care organization in Utah, for many years. METHODS: Select success features of the original HELP system's decision support environment are identified and lessons learned are related. Plans for transferring these features to HELP II are discussed. RESULTS: The article focuses on four features: (1) the importance of easy access to patient data essential for decision support, (2) the commitment to continued measurement and revision of both the logic and the interventional strategy in a decision support application, (3) experience with data mining as a tool for developing decision support tools, and (4) the role of clinical reports in supporting the decision making process.

Decision Support Systems, Clinical↗
PubMed2003

Adverse drug events in trauma patients.

BACKGROUND: Adverse drug events (ADEs) are noxious and unintended results of drug therapy. ADEs have been shown to be a risk to hospitalized patients. The purpose of this study was to determine the rate and nature of ADEs in trauma patients and to characterize the population at risk. METHODS: An electronic medical record, a hospital wide computerized surveillance program, and a clinical pharmacist prospectively investigated ADEs in 4,320 trauma patients from 1996 through 1999. RESULTS: The rate of ADEs in trauma patients (98/4320, 2.3%) was twice that of non-trauma hospital patients (1,111/96,218, 1.2%, p < 0.001). Traumatized females had ADEs 1.5 times more often than traumatized males (2.7% versus 1.8%, p = 0.052). The medication class most often associated with ADEs was analgesics with 54% involving morphine and 20% involving meperidine. The most common ADEs were nausea, vomiting, and itching. Only one ADE was directly attributed to a medical error. CONCLUSIONS: Trauma patients are at double the risk for ADEs. Analgesics are particularly associated with ADEs and use should be carefully monitored.

Adolescent↗
PubMed2003

Development of an information model for solid organ transplantation.

Information required to manage transplant patients and donors is complex, voluminous and requires the reporting and use of one person's medical information within another person's record. One strategy using a vocabulary model (i.e., LOINC codes with *DONOR specified in the system axes) will lead to problems with combinatorial explosion. After evaluating workflow processes, data collection forms, decision support and functional requirements, we designed and implemented an extendable information model to support the process of care following liver transplantation.

Decision Making, Computer-Assisted↗
PubMed2002

Clinical and economic outcomes of conventional amphotericin B-associated nephrotoxicity.

A retrospective 9-year cohort study was conducted to identify the hospitalization costs, length of hospital stay, and mortality associated with nephrotoxicity (NT) among 494 inpatients who were treated with conventional amphotericin B (CAB). Survival regression methods were used to model the effect of NT. The rate of NT was 12%; the overall in-hospital mortality rate was 22%. After adjustment for confounding, NT was associated with a 2.7-fold higher risk of death (P<.001). Although the unadjusted effects of NT on length of hospital stay and hospitalization costs after the initiation of CAB were consistent with small increases, such effects were not significant in multivariate models (time ratio, 1.2 [P=.2]; cost ratio, 1.1 [P=.8]). The greater the number of days before the onset of NT that were included in the analysis, the greater the apparent effect of NT on costs. CAB-associated NT was associated with increased mortality, but it did not impact the costs and length of hospital stay.

Amphotericin B↗
PubMedDate not supplied

Detecting adverse events using information technology.

CONTEXT: Although patient safety is a major problem, most health care organizations rely on spontaneous reporting, which detects only a small minority of adverse events. As a result, problems with safety have remained hidden. Chart review can detect adverse events in research settings, but it is too expensive for routine use. Information technology techniques can detect some adverse events in a timely and cost-effective way, in some cases early enough to prevent patient harm. OBJECTIVE: To review methodologies of detecting adverse events using information technology, reports of studies that used these techniques to detect adverse events, and study results for specific types of adverse events. DESIGN: Structured review. METHODOLOGY: English-language studies that reported using information technology to detect adverse events were identified using standard techniques. Only studies that contained original data were included. MAIN OUTCOME MEASURES: Adverse events, with specific focus on nosocomial infections, adverse drug events, and injurious falls. RESULTS: Tools such as event monitoring and natural language processing can inexpensively detect certain types of adverse events in clinical databases. These approaches already work well for some types of adverse events, including adverse drug events and nosocomial infections, and are in routine use in a few hospitals. In addition, it appears likely that these techniques will be adaptable in ways that allow detection of a broad array of adverse events, especially as more medical information becomes computerized. CONCLUSION: Computerized detection of adverse events will soon be practical on a widespread basis.

Accidental Falls↗