An evaluation of lycra garments in the lower limb using 3-D gait analysis and functional assessment (PEDI).

Whole body lycra garments were assessed in eight children using gait analysis, the paediatric evaluation of disability index (PEDI), and a questionnaire of parental acceptance. Seven of the children had cerebral palsy and one Duchennes muscular dystrophy. After initial assessment and fitting of the garment, there was a 2-week introduction period followed by 6 weeks of wearing the garment for at least 6 h everyday, following which they were re-assessed. The root mean square error (RMSE) was used as a measure of variability over three separate passes through the gait laboratory and was a reference figure for gait stability. Proximal stability around the pelvis improved for five children and distal stability improved for three. Five children improved in at least one aspect of the PEDI scale. Although the parents and children detected these improvements, they did not outweigh the disadvantages of wearing the suit and as a consequence only one out of eight families considered continuing with the lycra garment.

Selective referral to high-volume hospitals: estimating potentially avoidable deaths.

CONTEXT: Evidence exists that high-volume hospitals (HVHs) have lower mortality rates than low-volume hospitals (LVHs) for certain conditions. However, few employers, health plans, or government programs have attempted to increase the number of patients referred to HVHs. OBJECTIVES: To determine the difference in hospital mortality between HVHs and LVHs for conditions for which good quality data exist and to estimate how many deaths potentially would be avoided in California by referral to HVHs. DESIGN, SETTING, AND PATIENTS: Literature in MEDLINE, Current Contents, and First-Search Social Abstracts databases from January 1, 1983, to December 31, 1998, was searched using the key words hospital, outcome, mortality, volume, risk, and quality. The highest-quality study assessing the mortality-volume relationship for each given condition was identified and used to calculate odds ratios (ORs) for in-hospital mortality for LVHs vs HVHs. These ORs were then applied to the 1997 California database of hospital discharges maintained by the California Office of Statewide Health Planning and Development to estimate potentially avoidable deaths. MAIN OUTCOME MEASURES: Deaths that potentially could be avoided if patients with conditions for which a mortality-volume relationship had been treated at an HVH vs LVH. RESULTS: The articles identified in the literature search were grouped by condition, and predetermined criteria were applied to choose the best article for each condition. Mortality was significantly lower at HVHs for elective abdominal aortic aneurysm repair, carotid endarterectomy, lower extremity arterial bypass surgery, coronary artery bypass surgery, coronary angioplasty, heart transplantation, pediatric cardiac surgery, pancreatic cancer surgery, esophageal cancer surgery, cerebral aneurysm surgery, and treatment of human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS). A total of 58,306 of 121,609 patients with these conditions were admitted to LVHs in California in 1997. After applying the calculated ORs to these patient populations, we estimated that 602 deaths (95% confidence interval, 304-830) at LVHs could be attributed to their low volume. Additional analyses were performed to take into account emergent admissions and distance traveled, but the impact of loss of continuity of care for some patients and reduction in the availability of specialists for patients remaining at LVHs could not be assessed. CONCLUSIONS: Initiatives to facilitate referral of patients to HVHs have the potential to reduce overall hospital mortality in California for the conditions identified. Additional study is needed to determine the extent to which selective referral is feasible and to examine the potential consequences of such initiatives.

Population choice and variable selection in the estimation and application of risk models.

This paper shows that risk adjustment models based on demographic and employment variables are not easily transferable from one population to the next, and that administrative variables are not useful in predicting medical expenditures. We found statistically significant differences between models built on populations of employees from a single employer enrolled in two different health plans, and between models built on populations of enrollees from a single health plan employed at two different companies. Employment-based variables (e.g., length of employment) had little predictive power in any of these risk models. We conclude that policymakers should be careful in applying risk models across populations, and that future versions of risk models for use within large employers need not include employment-based variables.

Choice of hospital for delivery: a comparison of high-risk and low-risk women.

OBJECTIVE: This article tests whether or not the factors that affect hospital choice differ for selected subgroups of the population. DATA SOURCES: 1985 California Office of Statewide Health Planning and Development (OSHPD) discharge abstracts and hospital financial data were used. STUDY DESIGN: Models for hospital choice were estimated using McFadden's conditional logit model. Separate models were estimated for high-risk and low-risk patients, and for high-risk and low-risk women covered either by private insurance or by California Medicaid. The model included independent variables to control for quality, price, ownership, and distance to the hospital. DATA EXTRACTION: Data covered all maternal deliveries in the San Francisco Bay Area in 1985 (N = 61,436). ICD-9 codes were used to classify patients as high-risk or low-risk. The expected payment code on the discharge abstract was used to identify insurance status. PRINCIPAL FINDINGS: The results strongly reject the hypothesis that high-risk and low-risk women have the same choice process. Hospital quality tended to be more important for high-risk than low-risk women. These results also reject the hypothesis that factors influencing choice of hospital are the same for women covered by private insurance as for those covered by Medicaid. Further, high-risk women covered by Medicaid were less likely than high-risk women covered by private insurance to deliver in hospitals with newborn intensive care units. CONCLUSIONS: The results show that the choice factors vary across several broadly defined subgroups of patients with a specific condition. Thus, estimates aggregating all patients may be misleading. Specifically, such estimates will understate actual patient response to quality of care indicators, since patient sensitivity to quality of care varies with the patients' risk status.