Judith R. Lave
University of Pittsburgh
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Featured researches published by Judith R. Lave.
Medical Decision Making | 2005
Joseph T. King; Joel Tsevat; Judith R. Lave; Mark S. Roberts
Background . Health-state preferences can be combined with willingness-to-pay (WTP) data to calculate WTP per quality-adjusted life year (QALY). The WTP/QALY ratios provide insight into societal valuations of expenditures for medical interventions. Methods . The authors measured preferences for current health in 3 patient populations (N = 391) using standard gamble, time trade-off, visual analog scale, and WTP, then they calculated WTP/QALY ratios. The ratios were compared with several proposed cost/QALY cost-effectiveness ratio thresholds, the value-of-life literature, and with WTP/QALY ratios derived from published preference research. Results . Mean WTP/QALY ratios ranged from
The American Journal of Medicine | 1993
Michael J. Fine; Daniel E. Singer; Barbara H. Hanusa; Judith R. Lave; Wishwa N. Kapoor
12,500 to
The American Journal of Medicine | 2000
Michael J. Fine; Hugh M. Pratt; D. Scott Obrosky; Judith R. Lave; Laura J McIntosh; Daniel E. Singer; Christopher M. Coley; Wishwa N. Kapoor
32,200 (2003
Journal of General Internal Medicine | 1995
Michael J. Fine; Barbara H. Hanusa; Judith R. Lave; Daniel E. Singer; Roslyn A. Stone; Lisa A. Weissfeld; Christopher M. Coley; Thomas J. Marrie; Wishwa N. Kapoor
US). All values were below most published cost-effectiveness ratio thresholds, below the ratio from a prototypic medical treatment covered by Medicare (i.e., renal dialysis), and below ratios from the value-of-life literature. The WTP/QALY ratios were similar to those calculated from published preference data for patients with symptomatic meno-pause, dentofacial deformities, asthma, or dermatologic disorders. Conclusions . WTP/QALY ratios calculated using preference data collected from diverse populations are lower than most proposed thresholds for determining what is “cost-effective.” Current proposed cost-effectiveness ratio thresholds may overestimate the willingness of society to pay for medical interventions.
The New England Journal of Medicine | 2009
Yuting Zhang; Julie M. Donohue; Judith R. Lave; Joseph P. Newhouse
PURPOSE Our purpose was to validate a previously developed pneumonia-specific prognostic index in a large, multicenter population. PATIENTS AND METHODS We developed a pneumonia-specific prognostic index in a prospective, multicenter study of 346 patients with clinical and radiographic evidence of pneumonia admitted to 3 Pittsburgh hospitals (the derivation cohort), and validated the index in 14,199 patients with a principal ICD-9-CM diagnosis of pneumonia admitted to 78 hospitals in the 1989 MedisGroups Comparative Hospital Database (the validation cohort). The prognostic index classified patients into five ordered risk classes based on six predictors of mortality: age greater than 65 years, pleuritic chest pain, a vital sign abnormality, altered mental status, neoplastic disease, and high-risk pneumonia etiology. Each patient in the validation cohort was assigned to a risk class by obtaining values for the indexs six predictors in the MedisGroups population. The performance of the prognostic index in the derivation and validation cohorts was assessed by comparing hospital mortality rates within each of the indexs five prognostic risk classes. RESULTS The hospital mortality rate was 13.0% in the derivation cohort, and 11.1% in the validation cohort (p = 0.26). The agreement in the risk class-specific mortality rates was striking with the exception of class V: in class I, mortality was 0% in the derivation cohort versus 1% in the validation cohort; in class II, 0% versus 1.1%; class III, 10.9% versus 8.6%; class IV, 21.8% versus 26.2%; and class V, 73.7% versus 37.7%. There were no statistically significant differences in mortality rates within the first four risk classes, which represented the vast majority of patients in the derivation (94%) as well as the validation (98%) cohorts. CONCLUSIONS These data support the generalizability of a pneumonia-specific prognostic index. This index, which performs exceptionally well in classifying low-risk patients, may help physicians identify patients with community-acquired pneumonia who could safely be managed in the ambulatory setting, or if hospitalized, the patients that could be treated with abbreviated inpatient care.
American Journal of Psychiatry | 2011
Rachel L. Garfield; Samuel H. Zuvekas; Judith R. Lave; Julie M. Donohue
PURPOSE Patients with pneumonia often remain hospitalized after becoming clinically stable, without demonstrated benefits on outcome. The purposes of this study were to assess the relation between length of hospital stay and daily medical care costs and to estimate the potential cost savings associated with a reduced length of stay for patients with pneumonia. SUBJECTS AND METHODS As part of a prospective study of adults hospitalized with community-acquired pneumonia at a community hospital and two university teaching hospitals, daily medical care costs were estimated by multiplying individual charges by department-specific cost-to-charge ratios obtained from each hospitals Medicare cost reports. RESULTS The median total cost of hospitalization for all 982 inpatients was
Medical Care | 1994
Judith R. Lave; Chris L. Pashos; Gerard F. Anderson; David J. Brailer; Thomas A. Bubolz; Douglas A. Conrad; Deborah A. Freund; Steven Fox; Emmett B. Keeler; Joseph Lipscomb; S Harold S. Luft; George Provenzano
5, 942, with a median daily cost of
Critical Care Medicine | 2005
Henry E. Wang; Douglas F. Kupas; David Hostler; Robert Cooney; Donald M. Yealy; Judith R. Lave
836, including
The American Journal of Medicine | 1998
Kenneth Gilbert; Patrick P. Gleason; Daniel E. Singer; Thomas J. Marrie; Christopher M. Coley; D. Scott Obrosky; Judith R. Lave; Wishwa N. Kapoor; Michael J. Fine
491 (59%) for room and
American Journal of Respiratory and Critical Care Medicine | 2011
Amber E. Barnato; Steven M. Albert; Derek C. Angus; Judith R. Lave; Howard B. Degenholtz
345 (41%) for non-room costs. Average daily non-room costs were 282% greater on the first hospital day, 59% greater on the second day, and 19% greater on the third day than the average daily cost throughout the hospitalization (all P <0.05), and were 14% to 72% lower on the last 3 days of hospitalization. Average daily room costs remained relatively constant throughout the hospital stay, with the exception of the day of discharge. A projected mean savings of