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Operating Margin (operating + margin)

Distribution by Scientific Domains

Medical Sciences	75%

Selected Abstracts

Form Follows Finance: Emergency Department Admissions and Hospital Operating Margins

ACADEMIC EMERGENCY MEDICINE, Issue 10 2008
Sandra M. Schneider MD
No abstract is available for this article. [source]

Factors Associated with Iowa Rural Hospitals' Decision to Convert to Critical Access Hospital Status

THE JOURNAL OF RURAL HEALTH, Issue 1 2009
Pengxiang Li PhD
ABSTRACT:,Context: The Balanced Budget Act (BBA) of 1997 allowed some rural hospitals meeting certain requirements to convert to Critical Access Hospitals (CAHs) and changed their Medicare reimbursement from prospective to cost-based. Some subsequent CAH-related laws reduced restrictions and increased payments, and the number of CAHs grew rapidly. Purpose: To examine factors related to hospitals' decisions to convert and time to CAH conversion. Methods: Eighty-nine rural hospitals in Iowa were characterized and observed from 1998 to 2005. Cox proportional hazards models were used to identify the determinants of time to CAH conversion. Findings: T-test and one-covariate Cox regression indicated that, in 1998, Iowa rural hospitals with more staffed beds, discharges, and acute inpatient days, higher operating margin, lower skilled swing bed days relative to acute days, and located in relatively high density counties were more likely to convert later or not convert before 2006. Multiple Cox regression with baseline covariates indicated that lower number of discharges and average length of stay (ALOS) were significant after controlling all other covariates. Conclusion: Iowa rural hospitals' decisions regarding CAH conversion were influenced by hospital size, financial condition, skilled swing bed days relative to acute days, length of stay, proportion of Medicare acute days, and geographic factors. Although financial concerns are often cited in surveys as the main reason for conversion, lower number of discharges and ALOS are the most prominent factors affecting rural hospitals' decision on when to convert. [source]

Hospital Costs and Revenue Are Similar for Resuscitated Out-of-hospital Cardiac Arrest and ST-segment Acute Myocardial Infarction Patients

ACADEMIC EMERGENCY MEDICINE, Issue 6 2010
Robert Swor DO
Abstract Objectives:, Care provided to patients who survive to hospital admission after out-of-hospital cardiac arrest (OOHCA) is sometimes viewed as expensive and a poor use of hospital resources. The objective was to describe financial parameters of care for patients resuscitated from OOHCA. Methods:, This was a retrospective review of OOHCA patients admitted to one academic teaching hospital from January 2004 to October 2007. Demographic data, length of stay (LOS), and discharge disposition were obtained for all patients. Financial parameters of patient care including total cost, net revenue, and operating margin were calculated by hospital cost accounting and reported as median and interquartile range (IQR). Groups were dichotomized by survival to discharge for subgroup analysis. To provide a reference group for context, similar financial data were obtained for ST-segment elevation myocardial infarction (STEMI) patients admitted during the same time period, reported with medians and IQRs. Results:, During the study period, there were 72 admitted OOCHA patients and 404 STEMI patients. OOCHA and STEMI groups were similar for age, sex, and insurance type. Overall, 27 (38.6%) OOHCA patients survived to hospital discharge. Median LOS for OOHCA patients was 4 days (IQR = 1,8 days), with most of those hospitalized for ,4 days (n = 34, 81.0% dying or discharged to hospice care). Median net revenue ($17,334 [IQR $7,015,$37,516] vs. $16,466 [IQR = $14,304,$23,678], p = 0.64) and operating margin ($7,019 [IQR = $1,875,$15,997] vs. $7,098 [IQR = $3,767,$11,138], p = 0.83) for all OOHCA patients were not different from STEMI patients. Net income for OOCHA patients was not different than for STEMI patients (,$322 vs. $114, p = 0.72). Conclusions:, Financial parameters for OOHCA patients are similar to those of STEMI patients. Financial issues should not be a negative incentive to providing care for these patients. ACADEMIC EMERGENCY MEDICINE 2010; 17:612,616 © 2010 by the Society for Academic Emergency Medicine [source]

Real Options: Meeting the Georgetown Challange

JOURNAL OF APPLIED CORPORATE FINANCE, Issue 2 2005
Thomas E. Copeland
In response to the demand for a single, generally accepted real options methodology, this article proposes a four-step process leading to a practical solution to most applications of real option analysis. The first step is familiar: calculate the standard net present value of the project assuming no managerial flexibility, which results in a value estimate (and a "branch" of a decision tree) for each year of the project's life. The second step estimates the volatility of the value of the project and produces a value tree designed to capture the main sources of uncertainty. Note that the authors focus on the uncertainty about overall project value, which is driven by uncertainty in revenue growth, operating margins, operating leverage, input costs, and technology. The key point here is that, in contrast to many real options approaches, none of these variables taken alone is assumed to be a reliable surrogate for the uncertainty of the project itself. For example, in assessing the option value of a proven oil reserve, the relevant measure of volatility is the volatility not of oil prices, but of the value of the operating entity,that is, the project value without leverage. The third step attempts to capture managerial flexibility using a decision "tree" that illustrates the decisions to be made, their possible outcomes, and their corresponding probabilities. The article illustrate various kinds of applications, including a phased investment in a chemical plant (which is treated as a compound option) and an investment in a peak-load power plant (a switching option with changing variance, which precludes the use of constant risk-neutral probabilities as in standard decision tree analysis). The fourth and final step uses a "no-arbitrage" approach to form a replicating portfolio with the same payouts as the real option. For most corporate investment projects, it is impossible to locate a "twin security" that trades in the market. In the absence of such a security, the conventional NPV of a project (again, without flexibility) is the best candidate for a perfectly correlated underlying asset because it represents management's best estimate of value based on the expected cash flows of the project. [source]