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(1/268) Excess capacity: markets regulation, and values.

OBJECTIVE: To examine the conceptual bases for the conflicting views of excess capacity in healthcare markets and their application in the context of today's turbulent environment. STUDY SETTING: The policy and research literature of the past three decades. STUDY DESIGN: The theoretical perspectives of alternative economic schools of thought are used to support different policy positions with regard to excess capacity. Changes in these policy positions over time are linked to changes in the economic and political environment of the period. The social values implied by this history are articulated. DATA COLLECTION: Standard library search procedures are used to identify relevant literature. PRINCIPAL FINDINGS: Alternative policy views of excess capacity in healthcare markets rely on differing theoretical foundations. Changes in the context in which policy decisions are made over time affect the dominant theoretical framework and, therefore, the dominant policy view of excess capacity. CONCLUSIONS: In the 1990s, multiple perspectives of optimal capacity still exist. However, our evolving history suggests a set of persistent values that should guide future policy in this area.  (+info)

(2/268) How many beds should a hospital department serve?

Departmental cost functions are constructed for selected hospital departments, using total number of beds in the hospital served as a proxy output measure. Calculation of maxima or minima for the resulting cost functions reveals that, on average, different departments have extremes in their cost functions of different levels of output. A relative cost index is constructed, using parameters of the departmental cost functions, and departmental costs are compared across regions. The significance of departmental differences in optimum output is discussed with regard to sharing of services and modified system design.  (+info)

(3/268) The effects of group size and group economic factors on collaboration: a study of the financial performance of rural hospitals in consortia.

STUDY QUESTIONS: To determine factors that distinguish effective rural hospital consortia from ineffective ones in terms of their ability to improve members' financial performance. Two questions in particular were addressed: (1) Do large consortia have a greater collective impact on their members? (2) Does a consortium's economic environment determine the degree of collective impact on members? DATA SOURCES AND STUDY SETTING: Based on the hospital survey conducted during February 1992 by the Robert Wood Johnson Hospital-Based Rural Health Care project of rural hospital consortia. The survey data were augmented with data from Medicare Cost Reports (1985-1991), AHA Annual Surveys (1985-1991), and other secondary data. STUDY DESIGN: Dependent variables were total operating profit, cost per adjusted admission, and revenue per adjusted admission. Control variables included degree of group formalization, degree of inequality of resources among members (group asymmetry), affiliation with other consortium group(s), individual economic environment, common hospital characteristics (bed size, ownership type, system affiliation, case mix, etc.), year (1985-1991), and census region dummies. PRINCIPAL FINDINGS: All dependent variables have a curvilinear association with group size. The optimum group size is somewhere in the neighborhood of 45. This reveals the benefits of collective action (i.e., scale economies and/or synergy effects) and the issue of complexity as group size increases. Across analyses, no strong evidence exists of group economic environment impacts, and the environmental influences come mainly from the local economy rather than from the group economy. CONCLUSION: There may be some success stories of collaboration among hospitals in consortia, and consortium effects vary across different collaborations. RELEVANCE/IMPACT: When studying consortia, it makes sense to develop a typology of groups based on some performance indicators. The results of this study imply that government, rural communities, and consortium staff and steering committees should forge the consortium concept by expanding membership in order to gain greater financial benefits for individual hospitals.  (+info)

(4/268) UK neonatal intensive care services in 1996. On behalf of the UK Neonatal Staffing Study Collaborative Group.

A census of activity and staff levels in 1996 was conducted in UK neonatal units and achieved a 100% response from 246 units. Among the 186 neonatal intensive care units, the median (interquartile range) number of total cots was 18(14-22); level 1 intensive care cots 4(2-6); total admissions 318(262-405); very low birthweight admissions 40(28-68); and the number ventilated or given CPAP by endotracheal tube 52(32-83). Forty six (25%) intensive care units lacked the recommended minimum of one consultant with prime responsibility for neonatal medicine. As a conservative estimate 79% of intensive care units had a lower nursing provision than that recommended in previously published guidelines. There was substantial variation in activity and staffing levels among units.  (+info)

(5/268) Dynamics of bed use in accommodating emergency admissions: stochastic simulation model.

OBJECTIVE: To examine the daily bed requirements arising from the flow of emergency admissions to an acute hospital, to identify the implications of fluctuating and unpredictable demands for emergency admission for the management of hospital bed capacity, and to quantify the daily risk of insufficient capacity for patients requiring immediate admission. DESIGN: Modelling of the dynamics of the hospital system, using a discrete-event stochastic simulation model, which reflects the relation between demand and available bed capacity. SETTING: Hypothetical acute hospital in England. SUBJECTS: Simulated emergency admissions of all types except mental disorder. MAIN OUTCOME MEASURES: The risk of having no bed available for any patient requiring immediate admission; the daily risk that there is no bed available for at least one patient requiring immediate admission; the mean bed occupancy rate. RESULTS: Risks are discernible when average bed occupancy rates exceed about 85%, and an acute hospital can expect regular bed shortages and periodic bed crises if average bed occupancy rises to 90% or more. CONCLUSIONS: There are limits to the occupancy rates that can be achieved safely without considerable risk to patients and to the efficient delivery of emergency care. Spare bed capacity is therefore essential for the effective management of emergency admissions, and its cost should be borne by purchasers as an essential element of an acute hospital service.  (+info)

(6/268) Associations among hospital capacity, utilization, and mortality of US Medicare beneficiaries, controlling for sociodemographic factors.

OBJECTIVE: To explore whether geographic variations in Medicare hospital utilization rates are due to differences in local hospital capacity, after controlling for socioeconomic status and disease burden, and to determine whether greater hospital capacity is associated with lower Medicare mortality rates. DATA SOURCES/STUDY SETTING: The study population: a 20 percent sample of 1989 Medicare enrollees. Measures of resources were based on a national small area analysis of 313 Hospital Referral Regions (HRR). Demographic and socioeconomic data were obtained from the 1990 U.S. Census. Measures of local disease burden were developed using Medicare claims files. STUDY DESIGN: The study was a cross-sectional analysis of the relationship between per capita measures of hospital resources in each region and hospital utilization and mortality rates among Medicare enrollees. Regression techniques were used to control for differences in sociodemographic characteristics and disease burden across areas. DATA COLLECTION/EXTRACTION METHODS: Data on the study population were obtained from Medicare enrollment (Denominator File) and hospital claims files (MedPAR) and U.S. Census files. PRINCIPAL FINDINGS: The per capita supply of hospital beds varied by more than twofold across U.S. regions. Residents of areas with more beds were up to 30 percent more likely to be hospitalized, controlling for ecologic measures of socioeconomic characteristics and disease burden. A greater proportion of the population was hospitalized at least once during the year in areas with more beds; death was also more likely to take place in an inpatient setting. All effects were consistent across racial and income groups. Residence in areas with greater levels of hospital resources was not associated with a decreased risk of death. CONCLUSIONS: Residence in areas of greater hospital capacity is associated with substantially increased use of the hospital, even after controlling for socioeconomic characteristics and illness burden. This increased use provides no detectable mortality benefit.  (+info)

(7/268) National census of availability of neonatal intensive care. British Association for Perinatal Medicine.

OBJECTIVE: To determine whether availability of neonatal intensive care cots is a problem in any or all parts of the United Kingdom. DESIGN: Three month census from 1 April to 30 June 1999 comprising simple data sheets on transfers out of tertiary units. SETTING: The 37 largest high risk perinatal centres in the United Kingdom. PARTICIPANTS: One obstetric specialist and one neonatal specialist in each centre. MAIN OUTCOME MEASURES: Suboptimal care resulting directly from pressure on service-that is, transfers out of tertiary units (either in utero or after delivery) because the unit was "full" and not because the hospital was incapable of providing the care needed. RESULTS: All units provided data. The number of intensive care cots in each unit was between five and 16. During the three months 309 transfers occurred (equivalent to 1236 per year), of which 264 were in utero and 45 postnatal. Sixty five in utero transfers involved multiple births, hence the census related to 382 babies (1528 per year). There was considerable regional variation. The reason for transfer in most cases was "lack of neonatal beds". CONCLUSIONS: Currently most major perinatal centres in the United Kingdom are regularly unable to meet in-house demand; this has implications for the service as a whole. The NHS has set no standards to help health authorities and primary care groups develop services relating to this specialty; such a step may well be an appropriate lever for change.  (+info)

(8/268) Hospital capacity and post-transplant survival after allogeneic bone marrow transplantation: analysis of data from the Japan Society for Hematopoietic Cell Transplantation.

The association between hospital capacity and survival after allogeneic bone marrow transplantation (allo-BMT) was examined using the dataset accumulated by the Japan Society of Hematopoietic Cell Transplantations (JSHCT). The subjects were 3134 patients who received first allo-BMTs between 1991 and 1997 reported to the JSHCT. They were divided into three groups by cumulative hospital experience of allo-BMTs: low volume (capacity) (LV; < or = 25 cases), moderate volume (capacity) (MV; 26-75 cases) and high volume (capacity) (HV; > or = 76 cases). Using a proportional hazards model, the association of hospital experience with early survival at day 100 (D100S), and overall survival (OS) were examined. For leukemia patients, leukemia-free survival (LFS) was also analyzed. When HV was defined as the reference group, the hazard ratios (HRs) of OS for all subjects were 1.10 (95% confidence interval; 0.97-1.25) for MV and 1.25 for LV (1.08-1.44). The HRs with D100S were 1.20 (0.96-1.51) for MV and 1.40 (1.08-1.80) for LV. Larger values were observed for OS and D100S in cases of leukemia. Survival after BMT from sibling donors was clearly influenced by hospital experience, but this was not the case from unrelated donors. These findings suggest that size of the transplant team should be considered in order to improve the outcome of sibling BMT in general.  (+info)