5 resultados para Billing
em Digital Commons at Florida International University
Resumo:
In his discussion - Database As A Tool For Hospitality Management - William O'Brien, Assistant Professor, School of Hospitality Management at Florida International University, O’Brien offers at the outset, “Database systems offer sweeping possibilities for better management of information in the hospitality industry. The author discusses what such systems are capable of accomplishing.” The author opens with a bit of background on database system development, which also lends an impression as to the complexion of the rest of the article; uh, it’s a shade technical. “In early 1981, Ashton-Tate introduced dBase 11. It was the first microcomputer database management processor to offer relational capabilities and a user-friendly query system combined with a fast, convenient report writer,” O’Brien informs. “When 16-bit microcomputers such as the IBM PC series were introduced late the following year, more powerful database products followed: dBase 111, Friday!, and Framework. The effect on the entire business community, and the hospitality industry in particular, has been remarkable”, he further offers with his informed outlook. Professor O’Brien offers a few anecdotal situations to illustrate how much a comprehensive data-base system means to a hospitality operation, especially when billing is involved. Although attitudes about computer systems, as well as the systems themselves have changed since this article was written, there is pertinent, fundamental information to be gleaned. In regards to the digression of the personal touch when a customer is engaged with a computer system, O’Brien says, “A modern data processing system should not force an employee to treat valued customers as numbers…” He also cautions, “Any computer system that decreases the availability of the personal touch is simply unacceptable.” In a system’s ability to process information, O’Brien suggests that in the past businesses were so enamored with just having an automated system that they failed to take full advantage of its capabilities. O’Brien says that a lot of savings, in time and money, went un-noticed and/or under-appreciated. Today, everyone has an integrated system, and the wise business manager is the business manager who takes full advantage of all his resources. O’Brien invokes the 80/20 rule, and offers, “…the last 20 percent of results costs 80 percent of the effort. But times have changed. Everyone is automating data management, so that last 20 percent that could be ignored a short time ago represents a significant competitive differential.” The evolution of data systems takes center stage for much of the article; pitfalls also emerge.
Resumo:
In - Protecting Your Assets: A Well-Defined Credit Policy Is The Key – an essay by Steven V. Moll, Associate Professor, The School of Hospitality Management at Florida International University, Professor Moll observes at the outset: “Bad debts as a percentage of credit sales have climbed to record levels in the industry. The author offers suggestions on protecting assets and working with the law to better manage the business.” “Because of the nature of the hospitality industry and its traditional liberal credit policies, especially in hotels, bad debts as a percentage of credit sales have climbed to record levels,” our author says. “In 1977, hotels showing a net income maintained an average accounts receivable ratio to total sales of 3.4 percent. In 1983, the accounts receivable ratio to total sales increased to 4.1 percent in hotels showing a net income and 4.4 percent in hotels showing a net loss,” he further cites. As the professor implies, there are ways to mitigate the losses from bad credit or difficult to collect credit sales. In this article Professor Moll offers suggestions on how to do that. Moll would suggest that hotels and food & beverage operations initially tighten their credit extension policies, and on the following side, be more aggressive in their collection-of-debt pursuits. There is balance to consider here and bad credit in and of itself as a negative element is not the only reflection the profit/loss mirror would offer. “Credit managers must know what terms to offer in order to compete and afford the highest profit margin allowable,” Moll says. “They must know the risk involved with each guest account and be extremely alert to the rights and wrongs of good credit management,” he advocates. A sound profit policy can be the result of some marginal and additional credit risk on the part of the operation manager. “Reality has shown that high profits, not small credit losses, are the real indicator of good credit management,” the author reveals. “A low bad debt history may indicate that an establishment has an overly conservative credit management policy and is sacrificing potential sales and profits by turning away marginal accounts,” Moll would have you believe, and the science suggests there is no reason not to. Professor Moll does provide a fairly comprehensive list to illustrate when a manager would want to adopt a conservative credit policy. In the final analysis the design is to implement a policy which weighs an acceptable amount of credit risk against a potential profit ratio. In closing, Professor Moll does offer some collection strategies for loose credit accounts, with reference to computer and attorney participation, and brings cash and cash discounts into the discussion as well. Additionally, there is some very useful information about what debt collectors – can’t – do!
Resumo:
Intensive Care Units (ICUs) account for over 10 percent of all US hospital beds, have over 4.4 million patient admissions yearly, approximately 360,000 deaths, and account for close to 30% of acute care hospital costs. The need for critical care services has increased due to an aging population and medical advances that extend life. The result is efforts to improve patient outcomes, optimize financial performance, and implement models of ICU care that enhance quality of care and reduce health care costs. This retrospective chart review study examined the dose effect of APN Intensivists in a surgical intensive care unit (SICU) on differences in patient outcomes, healthcare charges, SICU length of stay, charges for APN intensivist services, and frequency of APNs special initiatives when the SICU was staffed by differing levels of APN Intensivist staffing over four time periods (T1-T4) between 2009 and 2011. The sample consisted of 816 randomly selected (204 per T1-T4) patient chart data. Study findings indicated reported ventilator associated pneumonia (VAP) rates, ventilator days, catheter days and catheter associated urinary tract infection (CAUTI) rates increased at T4 (when there was the lowest number of APN Intensivists), and there was increased pressure ulcer incidence in first two quarters of T4. There was no statistically significant difference in post-surgical glycemic control (M = 142.84, SD = 40.00), t (223) = 1.40, p = .17, and no statistically significant difference in the SICU length of stay among the time-periods (M = 3.27, SD = 3.32), t (202) = 1.02, p = .31. Charges for APN services increased over the 4 time periods from $11,268 at T1 to $51,727 at T4 when a system to capture APN billing was put into place. The number of new APN initiatives declined in T4 as the number of APN Intensivists declined. Study results suggest a dose effect of APN Intensivists on important patient health outcomes and on the number of APNs initiatives to prevent health complications in the SICU. ^
Resumo:
The purpose of this study was to analyze the network performance by observing the effect of varying network size and data link rate on one of the most commonly found network configurations. Computer networks have been growing explosively. Networking is used in every aspect of business, including advertising, production, shipping, planning, billing, and accounting. Communication takes place through networks that form the basis of transfer of information. The number and type of components may vary from network to network depending on several factors such as requirement and actual physical placement of the networks. There is no fixed size of the networks and they can be very small consisting of say five to six nodes or very large consisting of over two thousand nodes. The varying network sizes make it very important to study the network performance so as to be able to predict the functioning and the suitability of the network. The findings demonstrated that the network performance parameters such as global delay, load, router processor utilization, router processor delay, etc. are affected. The findings demonstrated that the network performance parameters such as global delay, load, router processor utilization, router processor delay, etc. are affected significantly due to the increase in the size of the network and that there exists a correlation between the various parameters and the size of the network. These variations are not only dependent on the magnitude of the change in the actual physical area of the network but also on the data link rate used to connect the various components of the network.
Resumo:
Intensive Care Units (ICUs) account for over 10 percent of all US hospital beds, have over 4.4 million patient admissions yearly, approximately 360,000 deaths, and account for close to 30% of acute care hospital costs. The need for critical care services has increased due to an aging population and medical advances that extend life. The result is efforts to improve patient outcomes, optimize financial performance, and implement models of ICU care that enhance quality of care and reduce health care costs. This retrospective chart review study examined the dose effect of APN Intensivists in a surgical intensive care unit (SICU) on differences in patient outcomes, healthcare charges, SICU length of stay, charges for APN intensivist services, and frequency of APNs special initiatives when the SICU was staffed by differing levels of APN Intensivist staffing over four time periods (T1-T4) between 2009 and 2011. The sample consisted of 816 randomly selected (204 per T1-T4) patient chart data. Study findings indicated reported ventilator associated pneumonia (VAP) rates, ventilator days, catheter days and catheter associated urinary tract infection (CAUTI) rates increased at T4 (when there was the lowest number of APN Intensivists), and there was increased pressure ulcer incidence in first two quarters of T4. There was no statistically significant difference in post-surgical glycemic control (M = 142.84, SD= 40.00), t (223) = 1.40, p = .17, and no statistically significant difference in the SICU length of stay among the time-periods (M= 3.27, SD = 3.32), t (202) = 1.02, p= .31. Charges for APN services increased over the 4 time periods from $11,268 at T1 to $51,727 at T4 when a system to capture APN billing was put into place. The number of new APN initiatives declined in T4 as the number of APN Intensivists declined. Study results suggest a dose effect of APN Intensivists on important patient health outcomes and on the number of APNs initiatives to prevent health complications in the SICU.