US organ donation breakthrough collaborative increases organ donation.

More than 92000 Americans are on waiting lists for organ transplants, and an average of 17 of them die each day while waiting. The US Organ Donation Breakthrough Collaborative (ODBC), which began in 2003 at the request of the Secretary of the US Department of Health and Human Services, was a formal, concerted effort of the donation and transplantation community to bring about a major change to improve the organ donation system. The nationwide Collaborative was housed within a Health and Human Services agency, the Health Resources and Services Administration (HRSA) Division of Transplantation, and included participation of the organ procurement organizations (OPOs) throughout the United States and the American hospitals with the largest organ-donor potential. HRSA leaders used the Breakthrough Series Collaborative method, originally developed by the Institute for Healthcare Improvement, as the model for the intervention. Expert practitioners drawn from hospitals and OPOs that had already demonstrated their ability to achieve and sustain high organ donation rates were chosen as faculty for the collaborative and best practices were gleaned from their institutions. The number of organ donors in Collaborative hospitals increased 14.1% in the first year, a 70% greater increase than the 8.3% increase experienced by non-Collaborative hospitals. Moreover, the increased organ recovery continued into the post-Collaborative periods. Between October 2003 and September 2006, the number of total US organ donors increased 22.5%, an increase 4-fold greater than the 5.5% increase measured over the same number of years in the immediate pre-Collaborative period. The study did not involve a randomized design, but time-series analysis using statistical process control charts shows a highly significant discontinuity in the rate of increase in participating hospitals concurrent with the Collaborative program, and strongly suggests that the activities of the Collaborative were a major contributor to this increase. Given the stable nature of the historical increases over many years, the HRSA estimates that more than 4000 annual additional transplants have occurred in association and apparently as a result of these increases in organ donation.

Effect of computer order entry on prevention of serious medication errors in hospitalized children.

OBJECTIVE: Although initial research suggests that computerized physician order entry reduces pediatric medication errors, no comprehensive error surveillance studies have evaluated the effect of computerized physician order entry on children. Our objective was to evaluate comprehensively the effect of computerized physician order entry on the rate of inpatient pediatric medication errors. METHODS: Using interrupted time-series regression analysis, we reviewed all charts, orders, and incident reports for 40 admissions per month to the NICU, PICU, and inpatient pediatric wards for 7 months before and 9 months after implementation of commercial computerized physician order entry in a general hospital. Nurse data extractors, who were unaware of study objectives, used an established error surveillance method to detect possible errors. Two physicians who were unaware of when the possible error occurred rated each possible error. RESULTS: In 627 pediatric admissions, with 12,672 medication orders written over 3234 patient-days, 156 medication errors were detected, including 70 nonintercepted serious medication errors (22/1000 patient-days). Twenty-three errors resulted in patient injury (7/1000 patient-days). In time-series analysis, there was a 7% decrease in level of the rates of nonintercepted serious medication errors. There was no change in the rate of injuries as a result of error after computerized physician order entry implementation. CONCLUSIONS: The rate of nonintercepted serious medication errors in this pediatric population was reduced by 7% after the introduction of a commercial computerized physician order entry system, much less than previously reported for adults, and there was no change in the rate of injuries as a result of error. Several human-machine interface problems, particularly surrounding selection and dosing of pediatric medications, were identified. Additional refinements could lead to greater effects on error rates.

Time series analysis of variables associated with daily mean emergency department length of stay.

STUDY OBJECTIVE: We measure the effect of various input, throughput, and output factors on daily emergency department (ED) mean length of stay per patient (daily mean length of stay). METHODS: The study was a retrospective review of 93,274 ED visits between April 15, 2002, and December 31, 2003. The association between the daily mean length of stay and the independent variables was assessed with autoregressive moving average time series analysis (ARIMA). The following independent variables were measured per 24-hour period: number of elective surgical admissions, ED volume, number of ED admissions, number of ED ICU admissions, number of ED clinical attending hours, hospital medical-surgical occupancy (hospital occupancy), and day of the week. RESULTS: Three factors were independently associated with daily mean length of stay in time series analysis: number of elective surgical admissions, number of ED admissions, and hospital occupancy. The daily mean length of stay increased by 0.21 minutes for every additional elective surgical admission, 2.2 minutes for every additional admission, and 4.1 minutes for every 5% increase in hospital occupancy. Elective surgical admissions were associated with a maximum of 35 hours of additional ED dwell time. The model accounted for 31.5% of the variability in daily mean length of stay. The final model parameters for the ARIMA analysis were autoregressive term (1) moving average (1). CONCLUSION: Hospital occupancy and the number of ED admissions are associated with daily mean length of stay. Every additional elective surgical admission prolonged the daily mean length of stay by 0.21 minutes per ED patient. Autocorrelation exists between the daily mean length of stay of the current day and the previous day.

Medication errors related to computerized order entry for children.

OBJECTIVE: The objective of this study was to determine the frequency and types of pediatric medication errors attributable to design features of a computerized order entry system. METHODS: A total of 352 randomly selected, inpatient, pediatric admissions were reviewed retrospectively for identification of medication errors, 3 to 12 months after implementation of computerized order entry. Errors were identified and classified by using an established, comprehensive, active surveillance method. Errors attributable to the computer system were classified according to type. RESULTS: Among 6916 medication orders in 1930 patient-days, there were 104 pediatric medication errors, of which 71 were serious (37 serious medication errors per 1000 patient-days). Of all pediatric medication errors detected, 19% (7 serious and 13 with little potential for harm) were computer related. The rate of computer-related pediatric errors was 10 errors per 1000 patient-days, and the rate of serious computer-related pediatric errors was 3.6 errors per 1000 patient-days. The following 4 types of computer-related errors were identified: duplicate medication orders (same medication ordered twice in different concentrations of syrup, to work around computer constraints; 2 errors), drop-down menu selection errors (wrong selection from a drop-down box; 9 errors), keypad entry error (5 typed instead of 50; 1 error), and order set errors (orders selected from a pediatric order set that were not appropriate for the patient; 8 errors). In addition, 4 preventable adverse drug events in drug ordering occurred that were not considered computer-related but were not prevented by the computerized physician order entry system. CONCLUSIONS: Serious pediatric computer-related errors are uncommon (3.6 errors per 1000 patient-days), but computer systems can introduce some new pediatric medication errors that are not typically seen in a paper ordering system.