The Problem of Capacity Management in Greek Public Hospitals

2017 ◽  
Vol 1 (2) ◽  
pp. 414
Author(s):  
Christos Tsitsakis ◽  
Persefoni Polychronidou ◽  
Anastasios Karasavvoglou
Keyword(s):  
Length Of Stay ◽  
Average Length ◽  
National Health System ◽  
Healthcare Services ◽  
Capacity Management ◽  
Point Of View ◽  
Public Hospitals ◽  
Theory Of Constraints ◽  
Healthcare Organizations ◽  
Average Length Of Stay

<p class="AbstractText">One of the most important problems that the users of Greek National Health System face, is the long waiting lists. Αrather superficial explanationof this phenomenon is usually refer the increasing demand for healthcare services, ignoring that the problem is mainly a problem of capacity management, which is associated with the occupancy rate of specific wards of a hospital, and the average length of stay.</p><p class="AbstractText">The theory of constraints can apply successfully to healthcare organizations, to solve problems of capacity management, reducing the inpatient length of stay and increasing the satisfaction from the offering services as has been proved by international research.</p><p class="AbstractText">In this paper, we study the problem from this point of view. Our qualitative research revealed that there is a bottle-neck in the normal flow of patients, because of the delays in the imaging departments of the hospitals.</p>The increase of the capacity of the imaging departments would offer a feasible solution to the problem.

The Health Sector Evolution Plan and the Technical Efficiency of Public Hospitals in IranBackground: Iranian public hospitals have been excessively changing during the healthcare reform since 2014. This study aimed to examine the technical efficiency of p

2020 ◽  
Author(s):  
Edris KAKEMAM ◽  
Hossein DARGAHI
Keyword(s):  
Length Of Stay ◽  
Technical Efficiency ◽  
Healthcare Reform ◽  
Average Length ◽  
Health Sector ◽  
Public Hospitals ◽  
Occupancy Rate ◽  
Bed Occupancy ◽  
Tobit Regression ◽  
Average Length Of Stay

Background: Iranian public hospitals have been excessively changing during the healthcare reform since 2014. This study aimed to examine the technical efficiency of public hospitals during before and after the implementation of Health Sector Evolution Plan (HSEP) and to determine whether, and how, efficiency is affected by various factors. Methods: Forty-two public hospitals were selected in Tehran, Iran, from 2012 to 2016. Data envelopment analysis was employed to estimate the technical and scale efficiency sample hospitals. Tobit regression was used to relate the technical efficiency scores to seven explanatory variables in 2016, the last year. Results: Overall, 24 (57.1%), 26 (61.9%), 26 (61.9%), 24 (57.1%) and 21 (50%) of the 42 sample hospitals ran inefficiently in 2012 to 2016, with average technical efficiency of 0.859, 0.836, 0.845, 0.905 and 0.934, respectively. The average pure technical efficiency in sample hospitals increased from 0.860 in 2010 (before the HSEP) to 0.944 in 2012 (after the HSEP). Tobit regression showed that average length of stay had a negative impact on technical efficiency of hospitals. In addition, bed occupancy rate, ratio of beds to nurses and ratio of nurses to physicians assumed a positive sign with technical efficiency. Conclusion: Despite government support, public hospitals operated relatively inefficien. Managers can enhance technical efficiency by increasing bed occupancy rate through shortening the average length of stay, proportioning the number of doctors, nurses, and beds along with service quality assurance.

scholarly journals The Factors Influencing Economic Efficiency of the Hospital Bed Care in Terms of the Regional Allowance Organizations

2014 ◽  
Vol 14 (3) ◽  
pp. 233-248 ◽  
Author(s):  
Ivana Vaňková ◽  
Iveta Vrabková
Keyword(s):  
Czech Republic ◽  
Length Of Stay ◽  
Technical Efficiency ◽  
Average Length ◽  
Allocative Efficiency ◽  
Hospitalized Patients ◽  
Point Of View ◽  
The Czech Republic ◽  
Average Length Of Stay ◽  
Hospital Bed

Abstract This paper aims to provide an efficiency evaluation of selected hospital bed care providers during years 2010 -2012 with respect to selected factors: The size of the hospital establishment according to number of beds, number of hospitalized patients, the average length of stay per a patient in care, total staff cost calculated per bed, total revenues calculated per bed, and total costs calculated per bed. For this purpose, hospitals providing primarily acute bed care were chosen. From the legal point of view, they are allowance organizations of a particular region. The evaluation concerns both allocative efficiency and technical efficiency. The allocative efficiency is treated from the proper algorithm point of view and it compares total costs calculated per bed with total revenues calculated per bed. A method denominated Data Envelopment Analysis was applied for the calculation of the technical efficiency of units. To be more specific, it was input-oriented model with constant returns to scale (CCR). The input parameters involve the number of beds, the average length of stay and costs per day of stay. Output parameters were as follows: Bed occupancy in days and the number of hospitalized patients. The data published by the Institute of Health Information and Statistic of the Czech Republic and by ÚFIS system (the Data Base of Ministry of Finance of the Czech Republic) were used as the source of data. The evaluation implies that only three hospitals were economically-effective: Silesian Hospital in Opava, Hospital Jihlava, and TGM Hospital Hodonín. The most significant factor influencing the efficiency was determined - the average length of stay.

scholarly journals Overcoming gaps: Regional collaborative to optimize capacity management and predict length of stay of patients admitted with COVID-19

JAMIA Open ◽  
2021 ◽  
Author(s):  
Michael G Usher ◽  
Roshan Tourani ◽  
Gyorgy Simon ◽  
Christopher Tignanelli ◽  
Bryan Jarabek ◽  
...  
Keyword(s):  
Weight Loss ◽  
Length Of Stay ◽  
Average Length ◽  
Capacity Management ◽  
Patient Data ◽  
Regional Level ◽  
System Level ◽  
Nursing Home Admission ◽  
Average Length Of Stay ◽  
Hospital Systems

Abstract Objective Ensuring an efficient response to COVID-19 requires a degree of inter-system coordination and capacity management coupled with an accurate assessment of hospital utilization including length of stay (LOS). We aimed to establish optimal practices in inter-system data sharing and LOS modeling to support patient care and regional hospital operations. Methods We completed a retrospective observational study of patients admitted with COVID-19 followed by 12-week prospective validation, involving 36 hospitals covering the upper Midwest. We developed a method for sharing de-identified patient data across systems for analysis. From this we compared three approaches, generalized linear model (GLM) and random forest (RF), and aggregated system level averages to identify features associated with LOS. We compared model performance by area under the ROC curve (AUROC). Results A total of 2068 patients were included and used for model derivation and 597 patients for validation. LOS overall had a median of 5.0 days and mean of 8.2 days. Consistent predictors of LOS included age, critical illness, oxygen requirement, weight loss, and nursing home admission. In the validation cohort, the RF model (AUROC-0.890) and GLM model (AUROC-0.864) achieved good to excellent prediction of LOS, but only marginally better than system averages in practice. Conclusion Regional sharing of patient data allowed for effective prediction of LOS across systems; however, this only provided marginal improvement over hospital averages at the aggregate level. A federated approach of sharing aggregated system capacity and average length of stay will likely allow for effective capacity management at the regional level. Lay Summary Regional planning for a surge in hospitalizations related to the COVID-19 pandemic requires three components: a prediction of new cases, prediction of how long COVID-19 patients will require hospitalization, and an ability to share that information across hospital systems that support that region. While prediction of new cases is well studied, hospital length of stay, and methods to share this information is less well established. In this study, we developed an approach to share information across hospital systems and explore approaches to predict length of stay. We find that length of stay can be accurately predicted using patient factors including age, low oxygen, and chronic conditions such as weight loss. However, in hospital planning at the regional level, the simplest solution: sharing raw case counts and average length of stay for each hospital is likely best.

scholarly journals Australian hospital services: An overview

2002 ◽  
Vol 25 (1) ◽  
pp. 2 ◽  
Author(s):  
S.J. Duckett
Keyword(s):  
Length Of Stay ◽  
Private Health Insurance ◽  
Average Length ◽  
Admission Rate ◽  
Public Hospitals ◽  
State Governments ◽  
Hospital Services ◽  
Private Hospitals ◽  
Average Length Of Stay ◽  
Australian Hospital

Hospital services in Australia are provided by public hospitals (about 75% of hospitals, two-thirds of separations) and private hospitals (the balance). Australians use about one bed day per person per year, with an admission rate of about300 admissions per thousand population per annum. Provision rates for public hospitals have declined significantly (by 40%) over the last 20 years but separation rates have increased. Average length of stay for overnight patients has been stable but, because the proportion of same day patients has increased dramatically, overall length of stay has declined from around seven days in the mid 1980s to around four days in the late 1990s. Overall, the Commonwealth and state governments each meet about half the costs of public hospital care, private health insurance meets about two-thirds of the costs of private hospitals.

scholarly journals Length of stay comparisons for private and public hospitals

2000 ◽  
Vol 23 (3) ◽  
pp. 162 ◽  
Author(s):  
Jennifer Badham ◽  
Jason Brandrup
Keyword(s):  
Length Of Stay ◽  
Public Hospital ◽  
Average Length ◽  
Public Hospitals ◽  
Private Hospitals ◽  
The Public ◽  
Average Length Of Stay ◽  
Private And Public

This analysis uses average length of stay as a proxy for efficiency, to compare the Australian private and public hospitalsectors. We conclude that private hospitals are more efficient than public hospitals in providing the range of care providedby private hospitals. However, public hospitals are more efficient in handling the casemix of the public hospital sector.The picture is more complicated when particular types of care (such as obstetric and psychiatric) are excluded.

scholarly journals HOSPITALIZATIONS FOR CHOLECYSTITIS AND CHOLELITHIASIS IN THE STATE OF RIO GRANDE DO SUL, BRAZIL

2016 ◽  
Vol 29 (2) ◽  
pp. 77-80 ◽  
Author(s):  
Emeline Caldana NUNES ◽  
Roger dos Santos ROSA ◽  
Ronaldo BORDIN
Keyword(s):  
Length Of Stay ◽  
Health System ◽  
National Health ◽  
Average Length ◽  
National Health System ◽  
Rio Grande ◽  
The State ◽  
Hospital Services ◽  
Rio Grande Do Sul ◽  
Average Length Of Stay

ABSTRACT Background: The cholelithiasis is disease of surgical resolution with about 60,000 hospitalizations per year in the Sistema Único de Saúde (SUS - Brazilian National Health System) of the Rio Grande do Sul state. Aim: To describe the profile of hospitalizations for cholecystitis and cholelithiasis performed by the SUS of Rio Grande do Sul state, 2011-2013. Methods: Hospital Information System data from the National Health System through morbidity list for cholelithiasis and cholecystitis (ICD-10 K80-K81). Variables studied were sex, age, number of hospitalizations and approved Hospitalization Authorizations (AIH), total amount and value of hospital services generated, days and average length of stay, mortality, mortality and case fatality ratio, from health regions of the Rio Grande do Sul. Results: During 2011-2013 there were 60,517 hospitalizations for cholecystitis and cholelithiasis, representing 18.86 hospitalizations per 10,000 inhabitants/year, most often in the age group from 60 to 69 years (41.34 admissions per 10,000 inhabitants/year) and female (27.72 hospitalizations per 10,000 inhabitants/year). The fatality rate presented an inverse characteristic: 13.52 deaths per 1,000 admissions/year for males, compared with 7.12 deaths per 1,000 admissions/year in females. The state had an average total amount spent and value of hospital services of R$ 16,244,050.60 and R$ 10,890,461.31, respectively. The health region "Capital/Gravataí Valley" exhibit the highest total expenditure and hospital services, and the largest number of deaths, and average length of stay. Conclusion: The hospitalization and lethality coefficients, the deaths, the length of stay and spending related to admissions increased from 50 years old. Females had a higher frequency and higher values spent on hospitalization, while the male higher coefficient of mortality and mean hospital stay.

scholarly journals Path Analysis of Hospitalization Expenses of 2,164 Appendicitis Patients at County-Level Public Hospitals in Anhui Province, China

2020 ◽  
Author(s):  
Junjun Xue ◽  
Heng Wang ◽  
Niannian Li ◽  
Yuhuan Ling ◽  
Chen Qian ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Path Analysis ◽  
Average Length ◽  
Anhui Province ◽  
Public Hospitals ◽  
County Level ◽  
Operative Duration ◽  
Average Length Of Stay ◽  
Factors Influencing ◽  
Controllable Factors

Abstract Background and objective Appendicitis resection is one of the most common surgical procedures. Hospitalization expenses are a major determinant of appendicitis treatment. This study explored the factors influencing hospitalization expenses of appendicitis patients in Anhui province and provided a scientific basis for reasonably controlling medical expenses. Methods A multi-stage random cluster sampling method was used to collect case information on 2,164 patients who underwent appendicitis surgery at 6 county-level public hospitals in Anhui province, China. Path analysis was used to study the factors influencing hospitalization expenses of appendicitis patients. Results The average length of stay was 5.62 ± 2.64 days, with a median of 5 days; the average hospitalization expenses were 6,109.60 ± 2,109.44 CNY, with a median of 5,511.93 CNY. The direct effect of length of stay was 0.535. Surgical grades, surgical methods, and chronic appendicitis directly affected hospitalization expenses, with direct effects of 0.149, 0.081, and -0.037; surgical costs, anesthesia costs, disease outcomes, age, acute simple appendicitis, and operative duration not only directly affected hospitalization expenses, but also indirectly affected hospitalization expenses, the total effects were 0.283, 0.045, 0.200, 0.202, -0.162, and 0.062, respectively. The total number of surgeons and assistants only indirectly affected hospitalization expenses, with indirect effect of 0.020. Conclusions The length of stay is the most important factor affecting hospitalization expenses. Based on controlling the average length of stay, combined with shortening operative duration, conducting health education, strengthening controllable factors, and other comprehensive measures can effectively reduce the economic burden of patients and hospitals.

scholarly journals Evaluation of Selected Ken-Drgs in Greek Public Hospitals: The Degree to Which they Reflect Actual Expenditure and Average Length of Stay

2014 ◽  
Vol 17 (7) ◽  
pp. A602
Author(s):  
O. Siskou ◽  
P. Galanis ◽  
D. Kaitelidou ◽  
M. Kalogeropoulou ◽  
E. Kouli ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Average Length ◽  
Public Hospitals ◽  
Average Length Of Stay

scholarly journals Colonization and Infection With MRSA and CRKP and Its Result in an Increased Mortality Rate Within the Intensive Care and High-Dependency Units in Barbados

2020 ◽  
Vol 41 (S1) ◽  
pp. s173-s174
Author(s):  
Keisha Gustave
Keyword(s):  
Intensive Care ◽  
Length Of Stay ◽  
High Mortality ◽  
Average Length ◽  
Cohort Analysis ◽  
Health Concern ◽  
Queen Elizabeth Hospital ◽  
Surveillance Program ◽  
Average Length Of Stay ◽  
High Dependency

Background: Methicillin-resistant Staphylococcus aureus(MRSA) and carbapenem-resistant Klebsiella pneumoniae (CRKP) are a growing public health concern in Barbados. Intensive care and critically ill patients are at a higher risk for MRSA and CRKP colonization and infection. MRSA and CRKP colonization and infection are associated with a high mortality and morbidly rate in the intensive care units (ICUs) and high-dependency units (HDUs). There is no concrete evidence in the literature regarding MRSA and CRKP colonization and infection in Barbados or the Caribbean. Objectives: We investigated the prevalence of MRSA and CRKP colonization and infection in the patients of the ICU and HDU units at the Queen Elizabeth Hospital from 2013 to 2017. Methods: We conducted a retrospective cohort analysis of patients admitted to the MICU, SICU, and HDU from January 2013 through December 2017. Data were collected as part of the surveillance program instituted by the IPC department. Admissions and weekly swabs for rectal, nasal, groin, and axilla were performed to screen for colonization with MRSA and CRKP. Follow-up was performed for positive cultures from sterile isolates, indicating infection. Positive MRSA and CRKP colonization or infection were identified, and patient notes were collected. Our exclusion criteria included patients with a of stay of <48 hours and patients with MRSA or CRKP before admission. Results: Of 3,641 of persons admitted 2,801 cases fit the study criteria. Overall, 161 (5.3%) were colonized or infected with MRSA alone, 215 (7.67%) were colonized or infected with CRKP alone, and 15 (0.53%) were colonized or infected with both MRSA and CRKP. In addition, 10 (66.6%) of patients colonized or infected with MRSA and CRKP died. Average length of stay of patients who died was 50 days. Conclusions: The results of this study demonstrate that MRSA and CRKP cocolonization and coinfection is associated with high mortality in patients within the ICU and HDU units. Patients admitted to the ICU and HDU with an average length of stay of 50 days are at a higher risk for cocolonization and coinfection with MRSA and CRKP. Stronger IPC measures must be implemented to reduce the spread and occurrence of MRSA and CRKP.Funding: NoneDisclosures: None

scholarly journals Temporal Changes in Central-Line–Associated Bloodstream Infection Time Between Events, 2017–2018 Versus 2015–2016

2020 ◽  
Vol 41 (S1) ◽  
pp. s403-s404
Author(s):  
Jonathan Edwards ◽  
Katherine Allen-Bridson ◽  
Daniel Pollock
Keyword(s):  
Length Of Stay ◽  
Patient Care ◽  
Average Length ◽  
Bloodstream Infections ◽  
Central Line ◽  
Significant Shift ◽  
Care Hospital ◽  
Average Length Of Stay ◽  
Period 2 ◽  
Hospital Bed

Background: The CDC NHSN surveillance coverage includes central-line–associated bloodstream infections (CLABSIs) in acute-care hospital intensive care units (ICUs) and select patient-care wards across all 50 states. This surveillance enables the use of CLABSI data to measure time between events (TBE) as a potential metric to complement traditional incidence measures such as the standardized infection ratio and prevention progress. Methods: The TBEs were calculated using 37,705 CLABSI events reported to the NHSN during 2015–2018 from medical, medical-surgical, and surgical ICUs as well as patient-care wards. The CLABSI TBE data were combined into 2 separate pairs of consecutive years of data for comparison, namely, 2015–2016 (period 1) and 2017–2018 (period 2). To reduce the length bias, CLABSI TBEs were truncated for period 2 at the maximum for period 1; thereby, 1,292 CLABSI events were excluded. The medians of the CLABSI TBE distributions were compared over the 2 periods for each patient care location. Quantile regression models stratified by location were used to account for factors independently associated with CLABSI TBE, such as hospital bed size and average length of stay, and were used to measure the adjusted shift in median CLABSI TBE. Results: The unadjusted median CLABSI TBE shifted significantly from period 1 to period 2 for the patient care locations studied. The shift ranged from 20 to 75.5 days, all with 95% CIs ranging from 10.2 to 32.8, respectively, and P < .0001 (Fig. 1). Accounting for independent associations of CLABSI TBE with hospital bed size and average length of stay, the adjusted shift in median CLABSI TBE remained significant for each patient care location that was reduced by ∼15% (Table 1). Conclusions: Differences in the unadjusted median CLABSI TBE between period 1 and period 2 for all patient care locations demonstrate the feasibility of using TBE for setting benchmarks and tracking prevention progress. Furthermore, after adjusting for hospital bed size and average length of stay, a significant shift in the median CLABSI TBE persisted among all patient care locations, indicating that differences in patient populations alone likely do not account for differences in TBE. These findings regarding CLABSI TBEs warrant further exploration of potential shifts at additional quantiles, which would provide additional evidence that TBE is a metric that can be used for setting benchmarks and can serve as a signal of CLABSI prevention progress.Funding: NoneDisclosures: None

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