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Biomedical subjects

C A Neslusan

Publications and source records attributed to C A Neslusan.

4 recordsLinked to original sources
PubMed2000

A national inpatient cost estimate of percutaneous endoscopic gastrostomy (PEG)-associated aspiration pneumonia.

OBJECTIVE: To present national estimates of the prevalence and costs of inpatient admissions for aspiration pneumonia (AP) associated with percutaneous endoscopic gastrostomies (PEGs) inserted before or during an admission. STUDY DESIGN: Retrospective analysis using medical claims. PATIENTS AND METHODS: National estimates of the prevalence of inpatient admissions associated with AP and mortality rates were developed, using data from the Nationwide Inpatient Sample of the Hospital Cost and Utilization Project (HCUP-3) Database. The MEDSTAT Group's MarketScan Private Pay Fee-for-Service (FFS) and Medicare FFS databases were used to calculate the percentage of admissions for AP that were preceded by a PEG or that entailed a PEG placement. Associated statistics, such as average length of stay and mean payments for these admissions, also were estimated. RESULTS: Approximately 300,000 inpatient admissions for AP took place in the United States in 1995, of which roughly 70,000 (23.9%) resulted in death. Approximately 10% of all AP admissions occurred after or entailed a PEG placement. After adjusting for differences in patients' age, gender, and health status, the total mean payments were estimated to be $26,618 per patient. This per-patient estimate translates into a national estimate of the cost of PEG-associated AP of approximately $808.2 million. CONCLUSION: The cost of PEG-associated AP is relatively high, as estimated in this study. The high inpatient mortality rates of AP imply that future efforts should be directed toward preventing AP.

Adolescent↗
PubMedDate not supplied

Controlling for systematic selection in retrospective analyses: an application to fluoxetine and sertraline prescribing in the United Kingdom.

BACKGROUND: Criticism has been made of observational studies in clinical practice because of their failure to control for unobserved factors that correlate with both initial treatment selection and observed outcomes. METHOD: A two-stage statistical model was applied to data obtained from a large general practitioner medical records database (DIN-LINK) to estimate the effect of initial antidepressant selection on the duration of antidepressant therapy and on the likelihood of being prescribed an average daily dose above the minimum recommended dose. The statistical model controlled for unobserved factors correlated with initial treatment selection and the observed outcomes as well as for observed confounders. RESULTS: Unobserved factors correlated with treatment selection were not a statistically significant determinant of the number of days of antidepressant therapy. However, unobserved factors correlated with treatment selection were a statistically significant determinant of the likelihood of receiving an average dose during therapy greater than the minimum recommended. After controlling for relevant confounders, those patients who began treatment with sertraline as opposed to fluoxetine had fewer days of antidepressant therapy and were more likely to receive average doses greater than the minimum recommended during therapy. CONCLUSION: Unobserved factors correlated with treatment selection can impact outcomes in observational studies and should be tested and controlled for whenever possible.

Journal Article↗
PubMedDate not supplied

Explaining drug spending trends: does perception match reality?

Several recent studies have made clear that drug expenditures are rising more rapidly than other health care spending. What has not been clear, however, is how much drug spending is driven by price rather than volume and whether volume increases are appropriate. This DataWatch takes a closer look at the components and drivers of drug spending using large claims databases from managed care and employer-sponsored health benefit plans. In both environments this study found volume, not price, to be the largest driver of drug spending for seven diseases studied. For four of the diseases, we review the clinical issues that may have influenced volume growth.

Centers for Medicare and Medicaid Services, U.S.↗