Background: There has been a large increase in both the number of neonatal intensive care units (NICUs) in community hospitals and the complexity of the cases treated in these units. We examined differences in neonatal mortality among infants with very low birth weight (below 1500 g) among NICUs with various levels of care and different volumes of very-low-birth-weight infants.

Methods: We linked birth certificates, hospital discharge abstracts (including interhospital transfers), and fetal and infant death certificates to assess neonatal mortality rates among 48,237 very-low-birth-weight infants who were born in California hospitals between 1991 and 2000.

Results: Mortality rates among very-low-birth-weight infants varied according to both the volume of patients and the level of care at the delivery hospital. The effect of volume also varied according to the level of care. As compared with a high level of care and a high volume of very-low-birth-weight infants (more than 100 per year), lower levels of care and lower volumes (except for those of two small groups of hospitals) were associated with significantly higher odds ratios for death, ranging from 1.19 (95% confidence interval [CI], 1.04 to 1.37) to 2.72 (95% CI, 2.37 to 3.12). Less than one quarter of very-low-birth-weight deliveries occurred in facilities with NICUs that offered a high level of care and had a high volume, but 92% of very-low-birth-weight deliveries occurred in urban areas with more than 100 such deliveries.

Conclusions: Mortality among very-low-birth-weight infants was lowest for deliveries that occurred in hospitals with NICUs that had both a high level of care and a high volume of such patients. Our results suggest that increased use of such facilities might reduce mortality among very-low-birth-weight infants.

Purpose: Recent studies and anecdotal evidence suggest that patient safety may be compromised on weekends. Our objective was to determine whether rates of complications in hospitals are higher on weekends than on weekdays.

Methods: We examined records from 4,967,114 admissions to acute care hospitals in 3 states and analyzed complication rates using the Patient Safety Indicators. We selected 8 indicators that could be assigned to a single day: complications of anesthesia, retained foreign bodies, postoperative hemorrhage, accidental cuts and lacerations during procedures, birth trauma, obstetric trauma during vaginal deliveries with and without instrumentation, and obstetric trauma during cesarean delivery. Odds ratios (ORs) comparing weekends versus weekdays were adjusted for demographics, type of admission, and admission route. In a subgroup analysis of surgical complications, we restricted the population to patients who underwent cardiac or vascular procedures.

Results: Four of the 8 complications occurred more frequently on weekends: postoperative hemorrhage (OR 1.07, 95% confidence interval [CI], 1.01-1.14), newborn trauma (OR 1.06, 95% CI, 1.03-1.10), vaginal deliveries without instrumentation (OR 1.03, 95% CI, 1.02-1.04), and obstetric trauma during cesarean sections (OR 1.36, 95% CI, 1.29-1.44). Complications related to anesthesia occurred less frequently on weekends (OR 0.86). Among patients undergoing vascular procedures, surgical complications occurred more frequently on weekends (OR 1.46, 95% CI, 1.16-1.85).

Conclusions: Rates of complications are marginally higher on weekends than on weekdays for some surgical and newborn complications, but more significantly for obstetric trauma and for surgical complications involving patients undergoing vascular procedures. Hospitals should work toward increasing the robustness of safeguards on weekends.

Context: Hospitals are under pressure to increase revenue and lower costs, and at the same time, they face dramatic variation in clinical demand.

Objective: We sought to determine the relationship between peak hospital workload and rates of adverse events (AEs).

Methods: A random sample of 24,676 adult patients discharged from the medical/surgical services at 4 US hospitals (2 urban and 2 suburban teaching hospitals) from October 2000 to September 2001 were screened using administrative data, leaving 6841 cases to be reviewed for the presence of AEs. Daily workload for each hospital was characterized by volume, throughput (admissions and discharges), intensity (aggregate DRG weight), and staffing (patient-to-nurse ratios). For volume, we calculated an "enhanced" occupancy rate that accounted for same-day bed occupancy by more than 1 patient. We used Poisson regressions to predict the likelihood of an AE, with control for workload and individual patient complexity, and the effects of clustering.

Results: One urban teaching hospital had enhanced occupancy rates more than 100% for much of the year. At that hospital, admissions and patients per nurse were significantly related to the likelihood of an AE (P 0.05); occupancy rate, discharges, and DRG-weighted census were significant at P 0.10. For example, a 0.1% increase in the patient-to-nurse ratio led to a 28% increase in the AE rate. Results at the other 3 hospitals varied and were mainly non significant.

Conclusions: Hospitals that operate at or over capacity may experience heightened rates of patient safety events and might consider re-engineering the structures of care to respond better during periods of high stress.

Objective: To describe the development of an instrument for assessing workforce perceptions of hospital safety culture and to assess its reliability and validity.

Data Sources/Study Setting: Primary data collected between March 2004 and May 2005. Personnel from 105 U.S. hospitals completed a 38-item paper and pencil survey. We received 21,496 completed questionnaires, representing a 51 percent response rate.

Study Design: Based on review of existing safety climate surveys, we developed a list of key topics pertinent to maintaining a culture of safety in high-reliability organizations. We developed a draft questionnaire to address these topics and pilot tested it in four preliminary studies of hospital personnel. We modified the questionnaire based on experience and respondent feedback, and distributed the revised version to 42,249 hospital workers.

Data Collection: We randomly divided respondents into derivation and validation samples. We applied exploratory factor analysis to responses in the derivation sample. We used those results to create scales in the validation sample, which we subjected to multitrait analysis (MTA).

Principal Findings: We identified nine constructs, three organizational factors, two unit factors, three individual factors, and one additional factor. Constructs demonstrated substantial convergent and discriminant validity in the MTA. Cronbach's  coefficients ranged from 0.50 to 0.89.

Conclusions: It is possible to measure key salient features of hospital safety climate using a valid and reliable 38-item survey and appropriate hospital sample sizes. This instrument may be used in further studies to better understand the impact of safety climate on patient safety outcomes.

Background: While trauma systems improve the outcome of injury in children, there is a paucity of information regarding trauma regionalization system function amid dramatic changes in the financial structure of health care.

Objective: To describe the distribution of acute hospitalization of children with severe trauma by level of hospital trauma care designation in California.

Methods: Retrospective observational study of a population-based cohort from 1998 to 2004. The California Office of Statewide Health Planning and Development (OSHPD) patient Discharge Data Set 1998-2004 was used. Patients were included if: age 0-19 years, trauma International Classification of Diseases, 9th Edition (ICD-9) diagnostic codes, and e-codes (n = 127,841). Differential rates of hospitalization in trauma-designated hospitals vs. non-trauma-designated hospitals were calculated for death and injury severity score. Injury severity scores (ISSs) were calculated from ICD-9 codes. Primary outcomes were hospitalization in a trauma center and death.

Results: From 1998 to 2004, 55%-60% of children 0-14 years and 55%-70% of children 15-19 years with trauma requiring hospitalization were discharged from trauma-designated hospitals. Children with severe injury were consistently hospitalized in trauma-designated hospitals (70%-78%) at a rate higher than children with moderate (60%-70%) and mild (50%-60%) injury. Trends for hospitalization in trauma-designated hospitals increased over the time span of the study (p 0.05). Approximately 20% of hospitalized children who died (I = 1,426) died 2 or more days after injury in non-trauma-designated hospitals.

Conclusions: A majority of children with trauma were cared for in trauma-designated hospitals over the study period. However, 20% of children with severe injuries and 20% of pediatric deaths greater than 2 days after injury were cared for in non-trauma-designated hospitals. Further investigation is warranted in order to enhance clinical protocols and policies that ensure access to appropriate regional trauma care for all children in need.

Objective: Despite evidence and recommendations encouraging the delivery of high-risk newborns in hospitals with subspecialty or high-level NICUs, increasing numbers are being delivered in other facilities. Causes for this are unknown. We sought to explore the impact of diffusion of specialty or midlevel NICUs on the types of hospitals in which low birth weight newborns are born.

Design: We used birth certificate, death certificate, and hospital discharge data for essentially all low birth weight, singleton California newborns born between 1993 and 2000. We identified areas likely to have been affected by the opening of a new nearby midlevel unit, analyzed changes over time in the share of births that took place in midlevel NICU hospitals, and compared patterns in areas that were and were not likely affected by the opening of a new midlevel unit. We also tracked the corresponding changes in the share of births in high-level hospitals and in those without NICU facilities (low-level).

Results: The probability of a 500- to 1499-g infant being born in a midlevel unit increased by 17 percentage points after the opening of a new nearby unit. More than three quarters of this increase was accounted for by reductions in the probability of birth in a hospital with a high-level unit (15 points), and the other portion was resulting from reductions in the share of newborns delivered in hospitals with low-level centers (2 points). Similar patterns were observed in 1500- to 2499-g newborns.

Conclusions: The introduction of new midlevel units was associated with significant shifts of births from both high-level and low-level hospitals to midlevel hospitals. In areas in which new midlevel units opened, the majority of the increase in midlevel deliveries was attributable to shifts from high-level unit births. Continued proliferation of midlevel units should be carefully assessed.

We investigated the determinants of inpatient rehabilitation costs in the Department of Veterans Affairs (VA) and examined the relationship between length of stay (LOS) and discharge costs using data from VA and community rehabilitation hospitals. We estimated regression models to identify patient characteristics associated with specialized inpatient rehabilitation costs. VA data included 3,535 patients discharged from 63 facilities in fiscal year 2001. We compared VA costs to community rehabilitation hospitals using a sample from the Uniform Data System for Medical Rehabilitation of 190,112 patients discharged in 1999 from 697 facilities. LOS was a strong predictor of cost for VA and non-VA hospitals. Functional status, measured by Functional Independence Measure (FIM) scores at admission, was statistically significant but added little explanatory value after controlling for LOS. Although FIM scores were associated with LOS, FIM scores accounted for little variance in cost after controlling for LOS. These results are most applicable to researchers conducting cost-effectiveness analyses.

Despite successful economic reforms over the past two decades, China's health care system for the nearly one billion people that live and work in rural areas is broken. Having admitted that there is a crisis, the government is now committed to looking for solutions. In this proposal, we have two overall goals to help provide insights on part of the solution. Our first objective is to collect an updated wave of highly informative data in Year 1 to build on an existing set of data already collected by our study team (from 2004) to analyze the effects of key health policies and institutions that have emerged over the past several years, including the government's rural health insurance system, the privatization of rural clinics, and new investments into township hospitals. Our second, more forward-looking goal for Years 2 and 3 is to set up and introduce an initial experiment on incentives to study one of the most serious flaws in China's health system: the practice in which doctors both prescribe and derive significant profit from drugs. The main hypothesis to be tested is whether realigning doctors' financial incentives embedded in the current organization of China's rural health system influence: a) the way doctors treat and manage their patients; b) the time and effort doctors put into patient care; and c) patient satisfaction.