scholarly journals A Comparison of Tourist Arrivals Among Franchised Versus Independent Hotels

Tourism ◽  
2021 ◽  
Vol 69 (3) ◽  
pp. 406-417
Author(s):  
Andrea Kavarić ◽  
Silvana Đurašević
Keyword(s):  
Time Series ◽  
Length Of Stay ◽  
Decision Makers ◽  
Action Plans ◽  
Independent Hotels

The purpose of this article is to review the different influences of franchised hotels and independent hotels on tourist arrivals, length of stay, overnights, and generating markets of tourists to highlight differences between these two business concepts. The data for this study were obtained by MONSTAT, the Montenegrin statistical office, and combined with author calculations. Data are arranged in time series from 2009 to 2018. The analysis reveals significant differences between the influence of franchised hotels and independent hotels in terms of increased tourist arrivals, generating markets, length of stay, and consequently overnights. The findings of this study may support decision-makers in tourism to develop better strategies and action plans that are specifically important in small markets where a lack of space is evident.

scholarly journals Bending the cost curve: time series analysis of a value transformation programme at an academic medical centre

2019 ◽  
Vol 28 (6) ◽  
pp. 449-458 ◽  
Author(s):  
Steven C Chatfield ◽  
Frank M Volpicelli ◽  
Nicole M Adler ◽  
Kunhee Lucy Kim ◽  
Simon A Jones ◽  
...  
Keyword(s):  
Time Series ◽  
Length Of Stay ◽  
Time Series Analysis ◽  
Hospital Mortality ◽  
Cost Of Care ◽  
Medical Centre ◽  
Academic Medical Centre ◽  
Series Analysis ◽  
Academic Medical ◽  
The Cost

BackgroundReducing costs while increasing or maintaining quality is crucial to delivering high value care.ObjectiveTo assess the impact of a hospital value-based management programme on cost and quality.DesignTime series analysis of non-psychiatric, non-rehabilitation, non-newborn patients discharged between 1 September 2011 and 31 December 2017 from a US urban, academic medical centre.InterventionNYU Langone Health instituted an institution-wide programme in April 2014 to increase value of healthcare, defined as health outcomes achieved per dollar spent. Key features included joint clinical and operational leadership; granular and transparent cost accounting; dedicated project support staff; information technology support; and a departmental shared savings programme.MeasurementsChange in variable direct costs; secondary outcomes included changes in length of stay, readmission and in-hospital mortality.ResultsThe programme chartered 74 projects targeting opportunities in supply chain management (eg, surgical trays), operational efficiency (eg, discharge optimisation), care of outlier patients (eg, those at end of life) and resource utilisation (eg, blood management). The study cohort included 160 434 hospitalisations. Adjusted variable costs decreased 7.7% over the study period. Admissions with medical diagnosis related groups (DRG) declined an average 0.20% per month relative to baseline. Admissions with surgical DRGs had an early increase in costs of 2.7% followed by 0.37% decrease in costs per month. Mean expense per hospitalisation improved from 13% above median for teaching hospitals to 2% above median. Length of stay decreased by 0.25% per month relative to prior trends (95% CI −0.34 to 0.17): approximately half a day by the end of the study period. There were no significant changes in 30-day same-hospital readmission or in-hospital mortality. Estimated institutional savings after intervention costs were approximately $53.9 million.LimitationsObservational analysis.ConclusionA systematic programme to increase healthcare value by lowering the cost of care without compromising quality is achievable and sustainable over several years.

scholarly journals Segmented Linear Regression Models for Assessing Change in Retrospective Studies in Healthcare

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Epaminondas Markos Valsamis ◽  
David Ricketts ◽  
Henry Husband ◽  
Benedict Aristotle Rogers
Keyword(s):  
Time Series ◽  
Hip Fracture ◽  
Linear Regression ◽  
Length Of Stay ◽  
Regression Models ◽  
Retrospective Studies ◽  
Linear Regression Models ◽  
Time To Surgery ◽  
Before And After ◽  
Group Comparisons

Introduction. In retrospective studies, the effect of a given intervention is usually evaluated by using statistical tests to compare data from before and after the intervention. A problem with this approach is that the presence of underlying trends can lead to incorrect conclusions. This study aimed to develop a rigorous mathematical method to analyse temporal variation and overcome these limitations. Methods. We evaluated hip fracture outcomes (time to surgery, length of stay, and mortality) from a total of 2777 patients between April 2011 and September 2016, before and after the introduction of a dedicated hip fracture unit (HFU). We developed a novel modelling method that fits progressively more complex linear sections to the time series using least squares regression. The method was used to model the periods before implementation, after implementation, and of the whole study period, comparing goodness of fit using F-tests. Results. The proposed method offered reliable descriptions of the temporal evolution of the time series and augmented conclusions that were reached by mere group comparisons. Reductions in time to surgery, length of stay, and mortality rates that group comparisons would have credited to the hip fracture unit appeared to be due to unrelated underlying trends. Conclusion. Temporal analysis using segmented linear regression models can reveal secular trends and is a valuable tool to evaluate interventions in retrospective studies.

scholarly journals Cohort study of a specialist social worker intervention on hospital use for patients at risk of long stay

BMJ Open ◽  
2018 ◽  
Vol 8 (12) ◽  
pp. e023127 ◽  
Author(s):  
Sonya Osborne ◽  
Gai Harrison ◽  
Angela O’Malia ◽  
Adrian Gerard Barnett ◽  
Hannah E Carter ◽  
...  
Keyword(s):  
Cohort Study ◽  
Length Of Stay ◽  
Willingness To Pay ◽  
Social Worker ◽  
Decision Makers ◽  
Psychosocial Needs ◽  
Model Of Care ◽  
Hospital Resources ◽  
Bed Days ◽  
The Cost

BackgroundLong-stay patients in acute hospitals commonly present with complex psychosocial needs and use high levels of hospital resources.ObjectiveTo determine whether a specialist social worker-led model of care was associated with a reduction in length of stay for medically stable patients with complex psychosocial needs who were at risk of long stay, and to determine the economic value of this model relative to the decision makers’ willingness to pay for bed days released.DesignA prospective, matched cohort study with historical controls.SettingA large, tertiary teaching and referral hospital in metropolitan Southeast Queensland, Australia.MethodsLength of hospital stay for a cohort of patients seen under the specialist social worker-led model of care was compared with a matched control group of patients admitted to the hospital prior to the introduction of the new model of care using a multistate model with the social worker model of care as an intermediate event. Costs associated with the model of care were calculated and an estimate of the ‘cost per bed day’ was produced.ResultsThe model of care reduced mean length of stay by 33 days. This translated to 9999 bed days released over 12 months. The cost to achieve this was estimated to be $A229 000 over 12 months. The cost per bed day released was $23, which is below estimates of hospital decision makers’ willingness to pay for a bed day to be released for an alternate use.ConclusionsThe specialist social worker-led model of care was associated with a reduced length of stay at a relatively low cost. This is likely to represent a cost-effective use of hospital resources. The limitations of our historic control cohort selection mean that results should be interpreted with caution. Further research is needed to confirm these findings.

scholarly journals Scaling-up implementation in community hospitals: a multisite interrupted time series design of the Mobilization of Vulnerable Elders (MOVE) program in Alberta

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Jayna Holroyd-Leduc ◽  
◽  
Charmalee Harris ◽  
Jemila S. Hamid ◽  
Joycelyne E. Ewusie ◽  
...  
Keyword(s):  
Time Series ◽  
Length Of Stay ◽  
Interrupted Time Series ◽  
Hospitalized Patients ◽  
Intervention Period ◽  
Community Hospitals ◽  
Series Design ◽  
Time Series Design ◽  
The Impact ◽  
Interrupted Time Series Design

Abstract Background As the population ages, older hospitalized patients are at increased risk for hospital-acquired morbidity. The Mobilization of Vulnerable Elders (MOVE) program is an evidence-informed early mobilization intervention that was previously evaluated in Ontario, Canada. The program was effective at improving mobilization rates and decreasing length of stay in academic hospitals. The aim of this study was to scale-up the program and conduct a replication study evaluating the impact of the evidence-informed mobilization intervention on various units in community hospitals within a different Canadian province. Methods The MOVE program was tailored to the local context at four community hospitals in Alberta, Canada. The study population was patients aged 65 years and older who were admitted to medicine, surgery, rehabilitation and intensive care units between July 2015 and July 2016. The primary outcome was patient mobilization measured by conducting visual audits twice a week, three times a day. The secondary outcomes included hospital length of stay obtained from hospital administrative data, and perceptions of the intervention assessed through a qualitative assessment. Using an interrupted time series design, the intervention was evaluated over three time periods (pre-intervention, during, and post-intervention). Results A total of 3601 patients [mean age 80.1 years (SD = 8.4 years)] were included in the overall analysis. There was a significant increase in mobilization at the end of the intervention period compared to pre-intervention, with 6% more patients out of bed (95% confidence interval (CI) 1, 11; p-value = 0.0173). A decreasing trend in median length of stay was observed, where patients on average stayed an estimated 3.59 fewer days (95%CI -15.06, 7.88) during the intervention compared to pre-intervention period. Conclusions MOVE is a low-cost, effective and adaptable intervention that improves mobilization in older hospitalized patients. This intervention has been replicated and scaled up across various units and hospital settings.

Length of Stay, Leave and Re-Offending by Patients from a Queensland Security Patients Hospital

1998 ◽  
Vol 32 (6) ◽  
pp. 839-847 ◽  
Author(s):  
Bob Green ◽  
Anthony J. Baglioni
Keyword(s):  
Survival Analysis ◽  
Length Of Stay ◽  
Empirical Data ◽  
International Research ◽  
Decision Makers ◽  
International Studies ◽  
Lower Range ◽  
Public Controversy ◽  
The Media ◽  
The Subject

Objective: The release of patients from a security patients hospital has been the subject of public controversy. The present study uses empirical data to examine the length of stay, leave, and re-offending of patients from a security hospital. Methods: Survival analysis was used to examine factors that may be predictive of length of stay and time under restriction, as well as time to first overnight leave. Data on re-offending were obtained from a variety of sources and were compared with seriousness of index offences. Results: Consistent with international research, patients with more serious offences had longer hospitalisations. Patients with more serious offences were also hospitalised for longer periods before leave was granted. Compared with international studies, re-offending was in the lower range. Conclusions: Despite concerns raised in the media regarding patient ‘dangerousness’, time spent in hospital and the granting of leave, patients with serious offences were more likely to be hospitalised longer, which suggests decision makers do take into account public safety.

scholarly journals Applying the ARIMA Model to the Process of Forecasting GDP and CPI in the Jordanian Economy

2021 ◽  
Vol 12 (3) ◽  
pp. 70
Author(s):  
Abdullah Ghazo
Keyword(s):  
Time Series ◽  
Economic Policy ◽  
Gross Domestic Product ◽  
Economic Activity ◽  
Price Index ◽  
Arima Model ◽  
Consumer Price Index ◽  
Decision Makers ◽  
Domestic Product

Gross Domestic Product (GDP) and consumer price index (CPI) are significant indicators to describe and evaluate economic activity and levels of development. They are also often used by decision makers so as to plan economic policy. This paper aims at modeling and predicting GDP and CPI in Jordan. In order to achieve this goal, the study applied the Box- Jenkins (JB) methodology for the period 1976-2019. Based on the results, ARIMA (3,1,1) found to be the best model for the GDP. In addition, ARIMA (1,1,0) was the best model for forecasting the CPI. The results were supported with the findings of the stationarity and identification rules test of time series under using AIC and SIC criterion. The forecasted values of the GDP and the CPI for the next three years (2020-2022) were (29342.12, 32095.10, 35106.36 million JD) and (128.31, 133.28, 139.28) respectively. Compared with 2019, the GDP is forecasted to decrease in 2020, while the CPI is forecasted to increase in 2020. This implies that the Jordanian economy is tending toward stagflation. After 2020, both GDP and CPI increased, which indicates that Jordanian economy is tending toward cost-push inflation.

scholarly journals What Determines Price-to-Earnings Ratios: An Empirical Evidence from Banking Sector of Pakistan

2021 ◽  
Vol 3 (1) ◽  
pp. 13-21
Author(s):  
SAFDAR HUSSAIN TAHIR ◽  
MUHAMMAD RIZWAN ULLAH ◽  
DR. SAID SHAH
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Banking Sector ◽  
Panel Data Analysis ◽  
Investment Decision ◽  
Decision Makers ◽  
Individual Investors ◽  
Significant Determinant ◽  
Fund Managers ◽  
Investment Opportunities

It is of greater importance to understand the factors influencing P/E ratio for the fund managers, decision makers, market analysts and individual investors. Variability in shares prices and investment opportunities in Pakistani listed banking firms motivate to examine the determinants of P/E ratio using time-series as well as panel data analysis for the period of 2007 to 2014. The findings of panel data indicate significant variation in P/E ratio due to MktRtrn, VMP and SIZE. DP ratio is found to be the most influential determinant of P/E ratio indicating the willingness of investors to invest more funds in those banking firms paying greater dividends. Empirical outcomes of time-series analysis for banking industry represent that DP ratio is the super most imperative determinant of P/E ratio. Findings also indicate that P/E ratio vary across years and influence the investor’s investment decision. The findings of the study facilitate the decision makers by investigating the most significant determinant of P/E ratio of banking firms in order to attract attention of investors and increase their confidence to choose these firms in their portfolios.

scholarly journals Forecasting future performance of irrigation schemes: The case of Bergama

2021 ◽  
Vol 9 (4) ◽  
pp. 769-774
Author(s):  
Sinan Kartal
Keyword(s):  
Time Series ◽  
Water Supply ◽  
Performance Assessment ◽  
Irrigation Water ◽  
Agricultural Practices ◽  
Decision Makers ◽  
Command Area ◽  
Total Expenditure ◽  
Future Performance ◽  
Use Of Data

Potential outputs of irrigation should be put forth to improve the yields in agricultural practices. Available water resources should efficiently be used to improve yields and inputs should be minimized. Performance assessment of irrigation schemes is an importance issue for improved yields and to take relevant measured. Statistical methods are used for performance assessment of irrigation schemes with the use of various indicators. Forecasts for future performance of irrigation shames will facilitate the steps to be taken by decision-makers to improve performance. In this study, time series – ARIMA method was used to forecast future performance of Bergama irrigation scheme for 2017-2021 period. The indicator values of annual irrigation water supply per unit command area, output per unit command area and total expenditure per unit command area for 2006-2017 period were used to estimate performance indicators for 2017-2021 period. In 2021, at 95% probability, the lowest annual irrigation water supply per unit-command area was calculated as 4365.10 m3 ha-1 and the highest as 16835.69 m3 ha-1; the lowest output per unit command area was calculated as -5076.10 € ha-1 and the highest as 10401.2 € ha-1; the lowest total expenditure per unit command area was calculated as -2200.41 € ha-1 and the highest as 1866.31 € ha-1. Present forecasts of time series -ARIMA method with the use of data of 2006-2016 period revealed that annual irrigation water supply per unit-command area and output per unit command area will increase and total expenditure per unit command area will decrease in years.

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