Predictors of acute hospital costs for treatment of ischemic stroke in an academic center.
(17/3118)
BACKGROUND AND PURPOSE: We sought to determine predictors of acute hospital costs in patients presenting with acute ischemic stroke to an academic center using a stroke management team to coordinate care. METHODS: Demographic and clinical data were prospectively collected on 191 patients consecutively admitted with acute ischemic stroke. Patients were classified by insurance status, premorbid modified Rankin scale, stroke location, stroke severity (National Institutes of Health Stroke Scale score), and presence of comorbidities. Detailed hospital charge data were converted to cost by application of department-specific cost-to-charge ratios. Physician's fees were not included. A stepwise multiple regression analysis was computed to determine the predictors of total hospital cost. RESULTS: Median length of stay was 6 days (range, 1 to 63 days), and mortality was 3%. Median hospital cost per discharge was $4408 (range, $1199 to $59 799). Fifty percent of costs were for room charges, 19% for stroke evaluation, 21% for medical management, and 7% for acute rehabilitation therapies. Sixteen percent were admitted to an intensive care unit. Length of stay accounted for 43% of the variance in total cost. Other independent predictors of cost included stroke severity, heparin treatment, atrial fibrillation, male sex, ischemic cardiac disease, and premorbid functional status. CONCLUSIONS: We conclude that the major predictors of acute hospital costs of stroke in this environment are length of stay, stroke severity, cardiac disease, male sex, and use of heparin. Room charges accounted for the majority of costs, and attempts to reduce the cost of stroke evaluation would be of marginal value. Efforts to reduce acute costs should be monitored for potential cost shifting or a negative impact on quality of care. (+info)
An approach to the problems of diagnosing and treating adult smear-negative pulmonary tuberculosis in high-HIV-prevalence settings in sub-Saharan Africa.
(18/3118)
The overlap between the populations in sub-Saharan Africa infected with human immunodeficiency virus (HIV) and Mycobacterium tuberculosis has led to an upsurge in tuberculosis cases over the last 10 years. The relative increase in the proportion of notified sputum-smear-negative pulmonary tuberculosis (PTB) cases is greater than that of sputum-smear-positive PTB cases. This is a consequence of the following: the association between decreased host immunity and reduced sputum smear positivity; the difficulty in excluding other HIV-related diseases when making the diagnosis of smear-negative PTB; and an increase in false-negative sputum smears because of overstretched resources. This article examines problems in the diagnosis and treatment of smear-negative PTB in high-HIV-prevalence areas in sub-Saharan Africa. The main issues in diagnosis include: the criteria used to diagnose smear-negative PTB; the degree to which clinicians actually follow these criteria in practice; and the problem of how to exclude other respiratory diseases that can resemble, and be misdiagnosed as, smear-negative PTB. The most important aspect of the treatment of smear-negative PTB patients is abandoning 12-month "standard" treatment regimens in favour of short-course chemotherapy. Operational research is necessary to determine the most cost-effective approaches to the diagnosis and treatment of smear-negative PTB. Nevertheless, substantial improvement could be obtained by implementing the effective measures already available, such as improved adherence to diagnostic and treatment guidelines. (+info)
Comparing physician-specific two-year patient outcomes after coronary angiography: methodologic issues and results.
(19/3118)
OBJECTIVES: We sought to evaluate methodologies to compare physician-related long-term patient outcomes appropriately. BACKGROUND: Evaluation of physicians on the basis of short-term patient outcome is becoming widely practiced. These analyses fail to consider the importance of long-term outcome, and methods appropriate to such an analysis are poorly defined. METHODS: All patients undergoing coronary angiography between 1992 and 1994 who received all of their cardiac care at our institution were followed for 27+/-13 months (mean+/-SD). Patients (n = 754) were cared for by one or more of 17 staff physicians. Risk-adjusted models were developed for four candidate clinical end points and cost. Physicians were then evaluated for each outcome measure. RESULTS: Of the clinical end points, death could be modeled most accurately (c-statistic = 0.83). The c-statistics for other end points ranged from 0.63 to 0.70. Physicians with outcomes statistically different (p < 0.05) from other physicians were identified more commonly than would be expected from the play of chance (p = 0.005). However, improvement in the c-statistics by the addition of physician identifiers was very modest. Physician's evaluations by the four measures of clinical outcome were variably correlated (r = .00 to .85). Graphic display of clinical and cost results for each physician did identify certain physicians who might be judged to provide more cost-effective care than others. CONCLUSIONS: Although comparisons of groups of physicians on the basis of long-term patient outcomes may have merit, individual physician-to-physician comparisons will be more difficult, owing to 1) multiple physicians contributing care to individual patients; 2) the poor predictive capacity of models other than that for survival; and 3) the modest apparent impact of differences in physician providers on long-term patient outcome. With these caveats in mind, modeling to compare patient outcomes of individual physicians with homogeneous patient populations or to identify gross outliers (good or bad) may be practicable in some patient-care systems, but may be inappropriate in others. (+info)
Costing model for neonatal screening and diagnosis of haemoglobinopathies.
(20/3118)
AIM: To compare the costs and cost effectiveness of universal and targeted screening for the haemoglobinopathies; to compare the cost of two laboratory methods; and to estimate the cost effectiveness of programmes at different levels of prevalence and mix of haemoglobinopathy traits. METHODS: A retrospective review of laboratory and follow up records to establish workload and costs, and estimation of costs in a range of circumstances was made in a haematology department and sickle cell and thalassaemia centre, providing antenatal and neonatal screening programmes in Inner London. The costs for 47,948 babies, screened during 1994, of whom 25 had clinically significant haemoglobinopathies and 704 had haemoglobinopathy traits, were retrospectively assessed. RESULTS: The average cost per baby tested (isoelectric focusing and high power liquid chromatography) was 3.51 Pounds /3.83 Pounds respectively; the cost per case of sickle cell disease identified (IEF/HPLC) was 6738 Pounds /7355 Pounds; the cost per trait identified (IEF/HPLC) was 234 Pounds /255 Pounds; the cost per extra case of SCD and trait identified by universal programme varied. CONCLUSIONS: IEF and HPLC are very similar in terms of average cost per test. At 16 traits/1000 and 0.5 SCD/1000 there was no significant identification cost difference between universal and targeted programmes. Below this prevalence, a targeted programme is cheaper but likely to miss cases of SCD. If targeted programmes were 90-99% effective, universal programmes would cease to be good value except at very high prevalence. Greater use of prenatal diagnosis, resulting in termination, and therefore fewer affected births, reduces the cost effectiveness of universal screening. Screening services should aim to cover a screened population which will generate a workload over 25,000 births a year, and preferably over 40,000. (+info)
Surgical subspecialty block utilization and capacity planning: a minimal cost analysis model.
(21/3118)
BACKGROUND: Operational inefficiencies in the use of operating rooms (ORs) are hidden by traditional measures of OR utilization. To better detect these inefficiencies, the authors defined two new terms, underutilization and overutilization, and illustrated how these measures might be used to evaluate the use of surgical subspecialty ORs. The authors also described capacity planning (optimizing surgical subspecialty block time allotments) using a minimal cost analysis (MCA) model. METHODS: The authors evaluated post hoc all surgeries performed over 6 yr at a large teaching hospital. To prepare utilization estimates, surgical records were categorized relative to budgeted OR block time for each subspecialty. Surgical cases beginning and ending during budgeted OR block time were categorized as budgeted utilization, budgeted time not used for surgery was underutilization, and cases beginning before/after budgeted block time were classified as overutilization. Cases that overlapped budgeted and nonbudgeted OR block time were parsed and the portions were assigned appropriately. Probability distributions were fitted to the historical patterns of surgical demand, and MCA block time budgets were estimated that minimized the costs of underutilization and overutilization for each subspecialty. To illustrate the potential savings if these MCA budgets were implemented, the authors compared actual operational costs to the estimated MCA budget costs and expressed the savings as a percentage of actual costs. RESULTS: The authors analyzed data from 58,251 surgical cases and 10 surgical subspecialty blocks. Classic utilization for each block-day by surgical subspecialty ranged from 44-113%. Average daily block-specific underutilization ranged from 16 to 60%, whereas overutilization ranged from 4 to 49%. CONCLUSIONS: Underutilization and overutilization are important measures because they may be used to evaluate the quality of OR schedules and the efficiency of OR utilization. Overutilization and underutilization also allow capacity planning using an MCA model This study indicated that the potential savings, if the MCA budgets were to be implemented, would be significant. (+info)
Clinical economics in clinical trials: the measurement of cost and outcomes in the assessment of clinical services through clinical trials.
(22/3118)
As the population ages and more expensive high-technology services become available, health care costs continue to spiral upward. Because the financial resources for health care are limited, economic analysis can help to evaluate expenditures and set priorities. Economic analysis of medical technology or medical care evaluates a medical service by comparing its dollar cost with its dollar benefit (cost-benefit), by measuring its dollar cost in relation to its outcomes (cost-effectiveness) as well as in relation to its utility or quality-adjusted outcomes (cost-utility), or simply by tabulating the costs involved (cost-identification). Direct costs are generated as services are provided. In addition, patients' productivity is affected, and these costs can be considered, especially in determining the benefit of a service that decreases morbidity or mortality. Intangible costs are those of pain, suffering, and grief. The point of view, or perspective, of the study determines the costs and benefits that will be measured in the analysis. Sensitivity analysis, which can evaluate the stability of the conclusions to the data used, is an important assessment within economic analysis. Economic analysis of new pharmaceutical therapies is increasingly being incorporated into clinical trials. Although there are some limitations of pharmacoeconomic information in clinical studies of drug safety and efficacy, these trials are often the only opportunity for economic data collection before adoption and reimbursement decisions are made. Validation after the drug has been introduced should complement economic information developed from clinical trials. (+info)
Y2K: the moment of truth.
(23/3118)
It remains to be seen whether the world will move in time to fix the Y2K bug, or whether computers around the world will shut down when the clock strikes midnight on 31 December 1999. Y2K could have a serious impact on environmental facilities, particularly given the extent to which computer software and microchips are now involved in pollution control and environmental monitoring and protection systems. (+info)
A model for analysing the cost of autologous peripheral blood progenitor cell (PBPC) transplantation.
(24/3118)
Data from autologous peripheral blood progenitor cell (PBPC) transplant recipients were used for cost analysis and modelling so as to link the main intervention procedures and clinical events to resource use and costs. This cohort consisted of 64 patients from 4 to 62 years old at transplantation (mean, 36.9 years) who underwent a first transplant between August 1994 and May 1997. The main indications for transplantation were non-Hodgkin's lymphomas (47%), multiple myeloma (30%) and Hodgkin's lymphomas (15%). The course of a patient during the whole transplant procedure was modelled using a Markov chain of six states of health: (1) mobilisation and recovery of PBPC; (2) post-mobilisation phase; (3) conditioning and transplant; (4) critical haematological reconstitution; (5) non-critical haematological reconstitution; (6) death. The probability of transition between the different health states, together with the estimated costs, were the input for the Markov model. The model also managed transition probabilities depending both on the current health state and on various demographic, clinical and procedure-related covariates unique to the patient. The expected time spent in each clinical state and the expected total cost were, therefore, estimated. This analysis gave an actual total cost per transplanted patient of $26,600 (95% range: $24,700 to $43,500) while mean duration was 197 days. The expenses for in-hospital stay accounted for 80% of the costs. Both the probability of staying in the different states, and the consequent cost were dependent on the number of CD34-positive cells collected, the phase and the type of the disease, the subset of patients (either children or adults), and the post-transplant G-CSF prophylaxis. The sensitivity of the estimates to alternative assumptions was studied, and the method of comparing alternative future scenarios by the model was explored. (+info)