A multiple regression analysis is used to determine the relationship or association between independent variables (IVs), also known as predictor variables, and a dependent variable (DV) (Sen & Srivastava, 2012). The purpose of the report is to summarize and analyze the Virginia Hospitals data from 2005 to determine run a multiple regression model against multiple predictor variables and determine statistical significance between the various hospital variables (i.e. independent variables) and the Total Operating Expense (TOE). A multiple linear regression was calculated to predict the DV (i.e.Total Operating Expense_05) based on the IVs (i.e. Staffed beds_05, Medicare Days_05, Medicaid Days_05, Total Surgeries_05, RN FTE_05, Occupancy, …show more content…
For the Staffed beds_05, the hypothesis is that the number of staffed beds has a positive association (β1 > 0) with TOE; staffed beds require regular care and maintenance, so an increase in staffed bed increases TOE (Villa & Kane, 2013). For the Medicare Days_05, the hypothesis is that Medicare days have a negative association (β2 < 0) with TOE; Medicare days affect the hospital 's revenue based on Medicare coverage, and so, an increase in Medicare days decreases TOE (Villa & Kane, 2013). For the Medicaid Days_05, the hypothesis is that Medicaid days have a negative association (β3 < 0) with TOE because Medicaid days increases the hospital 's expenses/bad debt; therefore an increase in Medicaid days decreases TOE (Villa & Kane, 2013). For the Total Surgeries_05, the hypothesis is that total surgeries have a positive association (β4 > 0) with TOE as surgical procedures incur costs with the use of specific/specialized drugs and equipment and post-operative care; therefore, as total surgeries increase, TOE increases (Fay, 2016). For the RN FTE_05, the hypothesis is that RN FTE has a positive association (β5 > 0) with TOE as increasing the level of nurse staffing, especially full-time (FTE) registered nurses (RN), increases TOE due to the salary payment (Investopedia, 2014). For the Occupancy, the hypothesis is that occupancy has a positive association (β6 > 0) with
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In the healthcare environment, the challenges that providers face are revenue shortfalls due to insufficient payments from the reduction of Medicare reimbursement rates (Shi and Singh, 2015. p238). Payers that have employment-based insurance are charged extra to cover the remaining balance. This process is called cost shifting. In some healthcare systems, the relationship between reimbursement reduction and cost shifting is correlated in an inversely proportional trend. As the decrease in reimbursement from public insurance such as Medicare and Medicaid, the method of cost shifting would increase.
Medicare payments to hospitals grew annually by 19 percent; the Medicare hospital deductible had expanded, placing a burden on beneficiaries; the solvency of the Medicare Trust Fund was endangered by escalating costs; expenditures for hospital inpatient care jeopardized Medicare's ability to fund other necessary health programs; Medicare's payments for comparable services were vastly different across hospitals nationwide; and the cost-based system imposed burdensome reporting requirements.
Since most specialty procedures are inpatient services, EMC’s inpatient occupancy rate suffers. The occupancy rate for Emanuel Medical Center – fifty percent – is far below that of its competitors and industry benchmarks. To accompany this, EMC (on average) receives a lower reimbursement for in-patient Medicare services per patient seen in comparison to its competitors. A result such as this is correlated with directly to the fewer amount of specialty services that EMC offers. In order for Emanuel Medical Center to be able to compete with other hospitals in its service area, it is imperative that EMC evaluates what services they currently offer and are capable to offer in the future to add value to the hospital, increase its revenue stream, and expand its patient mix. Currently, Emanuel Medical Center has not succumbed to its increasing financial pressurealthough EMC has had a negative operating income for five straight years. A negative operating income places EMC at a disadvantage because it limits the hospitals ability to renovate its aging building or hire new specialists to offer revenue enhancing procedures. EMC’s competitors, on the other hand, have large sources of revenue due to their mergers with large healthcare networks such as Catholic Healthcare West. Another competitor, Kaiser Permanente Modesto Medical Center, has extremely large financial resources due to the fact
Analyses used to collect the data were the profitability, break-even and utilization/volume. A dashboard analysis was also used. To analyze the profit of the organization over the next five years, profitability analysis was used with considering inflation rates for each item. Break-even analysis was used to compare the amount of additional visits per day if the clinic operated as-is to operating with the expansion of the new marketing program. The break-even analysis was also used to recognize the volume required to cover the costs of the marketing program. The dashboard analysis was then used to summarize all analyses used.
Through the Internet, massive amounts of information are just a click away. Healthcare professionals, media, and government agencies encourage people to make informed decisions pertaining to their health. Therefore, people may choose their hospitals through reported statistics. Governing organizations motivate hospitals by what they required to report. Hospitals are analyzing expenses to cut costs and improve the quality of care. Consequently, institutions inspire hospitals through financial awards or prestigious designations to move forward.
The cost of the health care industry has always been rising since the early 1980s. It has been a growing concern in both the industry and society. Massachusetts General Hospital (MGH) is no exception. Even though the average length of stay (LOS) for the patients in MGH has been declining (Exhibit 10), it is still the highest compared to their competitors (Exhibit 6). Besides the cost, there is no uniformity of process and standardization across different facilities and departments of the hospital. MGH lacks communication and coordination between the facilities.
For several decades health care has been tied to the economy and with the current downturn we see continued efforts to control and reduce over-head costs. Health care organizations in their effort to become more efficient and address changes in the industry have altered their strategic business plans. Lee & Alexander (1999) researched organizational change in hospitals and their survival, in this paper I hope to discuss their findings and add other examples to validate their conclusions.
The following pages present a brief analysis of sample data from one healthcare organization. Accompanying this written report are spreadsheets of the company's financial data its balance sheet and its statement of revenue and expenses that provide not only the figures from the audited reports of the hospital examined, but also show the change from year to year on each item as both a dollar amount and a percentage. Changes of more than five percent are considered worthy of discussion, and as these documents show much
“Hospitals can be non-profit, for-profit, and government-owned and/or operated” (Baker & Baker, 2006). There are different terms for each classification in how to report and handle the finances but the basics are the same for any type of business. Business finances require the following basic fundamentals: creating “budgets, understanding capital expenditure, loan acquisition, and financial fees” (Baker & Baker, 2006). Government owned and operated hospitals offer unprofitable services; which
The main GLM regression models included a hospital admission HHI where the total number of admissions in a hospital is measured as a proxy of the hospital’s market share. Another way to measure a hospital’s market share is to calculate the total inpatient day share of the hospital. Table 9 shows the GLM equations with the admission HHI vs. the inpatient days HHI for all samples. This sensitivity analysis results were consistent with the results from the main GLM regression.
In this case study three I used the information from the last two assignments to form a report for Sunrise Company that included a multiple regression model, an Interpretation of all the estimated regression coefficients, using the t-test or the p-value, analysis of residuals, and analysis coefficient of Determination (R2) and the F-test. In this scenario I am hired to be a statistical consultant to provide information from a sample of BMW data. In this part Sunrise is requiring a memo based on all the data that I have gathered. I will be gathering my data together to advise Sunrise on how they should market their cars to customers making them more knowledgeable and profitable.
Run the regression Report your answer in the format of equation 5.8 (Chapter 5, p. 152) in the textbook including and the standard error of the regression (SER). Interpret the estimated slope parameter for LOT. In the interpretation, please note that PRICE is measured in thousands of dollars and LOT is measured in acres.