Efficiency indicators of the round-the-clock hospital beds of the oncologic profile in the Russian Federation

2020 ◽  
pp. 12-18
Author(s):  
V. A. Evdakov ◽  
◽  
M. N. Banteva ◽  
E. M. Manoshkina ◽  
Y. Y. Melnikov ◽  
...  
Keyword(s):  
Health Care ◽  
Length Of Stay ◽  
Russian Federation ◽  
Average Length ◽  
Hospitalization Rate ◽  
Bed Occupancy ◽  
Average Length Of Stay ◽  
Hospital Beds ◽  
Federal Districts ◽  
The Russian Federation

The steady growth trend of oncological diseases in Russia in recent years requires a response from the health care system: development of prevention aimed at early detection of diseases; improvement of methods of diagnostics and treatment of oncopathology; improving the quality and effectiveness of medical care. A i m : to identify trends in changes of the neoplasms incidence and performance indicators of oncological beds for round-the-clock stay of the state health care system in the Russian Federation, federal districts and regions of the Russian Federation in dynamics for 2010–2019. M a t e r i a l s a n d m e t h o d s . Using the data of federal statistical observation (forms NoNo. 12, 30) by the method of descriptive statistics, the main indicators of the neoplasms incidence in the population are analyzed, as well as the work of round-the-clock oncological beds in the Russian Federation, federal districts and regions of the Russian Federation in dynamics for 2010–2019. R e s u l t s . On the background of an increase in the neoplasms incidence in the population (by 24.9%), including malignant (1.5 times), for the period 2010–2019 in the Russian Federation increased: the absolute number of oncology beds of round-the-clock stay from 30,970 to 36,186 (+ 16.8%), the provision with these beds from 2.17 to 2.47 per 10,000 population (+ 13.8%), hospitalization rate from 6.1 to 9.6 per 1000 population (+ 57.4%), and decreased: the average length of stay in an oncological bed (from 12.1 days to 8.4 – by 30.6%), as well as the average bed occupancy per year (from 345 to 330 days – by 4.3%). The extreme values of the indicators of the hospitalization rate for round-the-clock oncological beds in the regions of the Russian Federation in 2019 differ 12.8 times, the provision of these beds – 9.2 times, the average bed occupancy per year – 1.5 times, the average length of stay in a bed – 2.4 times. Mortality in oncological hospital beds increased from 0.76% in 2010 to 0.95% in 2019 (by 25%). C o n c l u s i o n . The 24-hour oncological bed capacity, against the background of the growth of oncological morbidity, has naturally increased, but at the same time it is characterized by an extreme disproportionality of development in the Federal Districts and the regions of the Russian Federation. Optimization of the bed fund should be carried out based on the objective needs of a particular region, taking into account its characteristics and with the simultaneous development of alternative medical services.

DYNAMICS OF THE MAIN INDICATORS OF HOSPITAL BEDS CARDIOLOGICAL HOUR AND DAY OF STAY IN THE RUSSIAN FEDERATION

2020 ◽  
Vol 5 (4) ◽  
pp. 43-49
Author(s):  
E. Manoshkina ◽  
M. Bant'eva ◽  
V. Kuznecova
Keyword(s):  
Length Of Stay ◽  
Medical Care ◽  
Russian Federation ◽  
Average Length ◽  
Health Resources ◽  
Average Length Of Stay ◽  
Hospital Beds ◽  
The Russian Federation ◽  
Day Hospitals ◽  
Observation Period

. For the period 2010-2018, the number of cardiac macroglobulinov stay in the Russian Federation decreased from 55477 before 49578 (10.6%),polysilazane hospitalizations for cardiac beds (from 9.3 to 10.8 per 1,000 population – 16.1%),decreased provision of cardiological beds (from 3.88 to 3.38 per 1000 population – by 12.9%), the average length of stay for cardiac bed (from 13.1 to 9.1 tnado – by 26.0%) and average employment cardiology bed per year (from 340 to 327 days – 3.8%). Mortality in cardiac beds in the Russian Federation decreased from 1.96% in 2010 to 1.89% in 2018 (by 3.6%).The provision of places for the Russian population in day hospitals of cardiological profile of organizations providing medical care in inpatient conditions increased by 19.6% (from 0.12 per 10,000 population in 2010 to 0.14 in 2018), and in day hospitals of organizations providing medical care in outpatient conditions decreased by 11.5% (from 0.15 per 10,000 population in 2014 up to 0.14 in 2018).In the Russian Federation, during the observation period, the level of hospitalizations in day hospitals of organizations providing medical care in inpatient conditions increased by 43.6%, and the GVA of the cardiological profile of organizations providing medical care in outpatient conditions increased by 5.2%. The dynamics of indicators of the bed Fund of cardiology profile in recent years indicates the process of inpatient replacement, which is undoubtedly one of the ways to improve the efficiency of using health resources.

scholarly journals Psychiatric inpatient care: where do we go from here?

2015 ◽  
Vol 24 (5) ◽  
pp. 371-375 ◽  
Author(s):  
C. Samele ◽  
N. Urquía
Keyword(s):  
Length Of Stay ◽  
Inpatient Care ◽  
Average Length ◽  
Psychiatric Inpatient ◽  
Significant Decline ◽  
Eu Member States ◽  
Average Length Of Stay ◽  
Level Data ◽  
Hospital Beds ◽  
The Uk

The significant decline in the number of psychiatric hospital beds for more than two decades across Europe has changed the landscape of mental health services. This has rekindled debates about bed shortages and the reasons for variations in the number of inpatient beds, admissions to hospital and length of stay. Analysis of European Union (EU) level data shows that the UK has a relatively low number of admissions to hospital, yet a much higher than average length of stay compared with 12 other EU Member States. Understanding this is difficult, but recent studies shed some further light on the patterns and predictors of admissions and 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

scholarly journals Biased and unbiased estimation of the average length of stay in intensive care units in the Covid-19 pandemic

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Nathanael Lapidus ◽  
Xianlong Zhou ◽  
Fabrice Carrat ◽  
Bruno Riou ◽  
Yan Zhao ◽  
...  
Keyword(s):  
Intensive Care ◽  
Length Of Stay ◽  
Average Length ◽  
Parametric Method ◽  
Estimation Methods ◽  
Unbiased Estimation ◽  
Bed Occupancy ◽  
Average Length Of Stay ◽  
Discharged Patients ◽  
First Admission

Abstract Background The average length of stay (LOS) in the intensive care unit (ICU_ALOS) is a helpful parameter summarizing critical bed occupancy. During the outbreak of a novel virus, estimating early a reliable ICU_ALOS estimate of infected patients is critical to accurately parameterize models examining mitigation and preparedness scenarios. Methods Two estimation methods of ICU_ALOS were compared: the average LOS of already discharged patients at the date of estimation (DPE), and a standard parametric method used for analyzing time-to-event data which fits a given distribution to observed data and includes the censored stays of patients still treated in the ICU at the date of estimation (CPE). Methods were compared on a series of all COVID-19 consecutive cases (n = 59) admitted in an ICU devoted to such patients. At the last follow-up date, 99 days after the first admission, all patients but one had been discharged. A simulation study investigated the generalizability of the methods' patterns. CPE and DPE estimates were also compared to COVID-19 estimates reported to date. Results LOS ≥ 30 days concerned 14 out of the 59 patients (24%), including 8 of the 21 deaths observed. Two months after the first admission, 38 (64%) patients had been discharged, with corresponding DPE and CPE estimates of ICU_ALOS (95% CI) at 13.0 days (10.4–15.6) and 23.1 days (18.1–29.7), respectively. Series' true ICU_ALOS was greater than 21 days, well above reported estimates to date. Conclusions Discharges of short stays are more likely observed earlier during the course of an outbreak. Cautious unbiased ICU_ALOS estimates suggest parameterizing a higher burden of ICU bed occupancy than that adopted to date in COVID-19 forecasting models. Funding Support by the National Natural Science Foundation of China (81900097 to Dr. Zhou) and the Emergency Response Project of Hubei Science and Technology Department (2020FCA023 to Pr. Zhao).

scholarly journals Times of change in complex environments - Evaluating hospital co-payments in Palestine refugee camps

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
S V Valente de Almeida ◽  
H Ghattas ◽  
G Paolucci ◽  
A Seita
Keyword(s):  
Length Of Stay ◽  
Policy Change ◽  
Negative Binomial ◽  
Negative Impact ◽  
Average Length ◽  
Lessons Learned ◽  
Policy Impact ◽  
Average Length Of Stay ◽  
Ex Post ◽  
The Impact

Abstract We measure the impact introducing a of 10% co-payment component on hospitalisation costs for Palestine refugees from Lebanon in public and private hospitals. This ex-post analysis provides a detailed insight on the direction and magnitude of the policy impact in terms of demand and supply for healthcare. The data was collected by the United Nations Relief and Works Agency for Palestine Refugees in the Near East and include episode level information from all public, private and Red Crescent Hospitals in Lebanon, between April 2016 and October 2017. This is a complete population episode level dataset with information from before and after the policy change. We use multinomial logit, negative binomial and linear models to estimate the policy impact on demand by type of hospital, average length of stay and treatment costs for the patient and the provider. After the new policy was implemented patients were 18% more likely to choose a (free-of-charge) PRCS hospital for secondary care, instead of a Private or Public hospital, where the co-payment was introduced. This impact was stronger for episodes with longer stays, which are also the more severe and more expensive cases. Average length of stay decreased in general for all hospitals and we could not find a statistically significant impact on costs for the provider nor the patient. We find evidence that the introduction of co-payments is hospital costs led to a shift in demand, but it is not clear to what extent the hospitals receiving this demand shift were prepared for having more patients than before, also because these are typically of less quality then the others. Regarding costs, there is no evidence that the provider managed to contain costs with the new policy, as the demand adapted to the changes. Our findings provide important information on hospitalisation expenses and the consequences of a policy change from a lessons learned perspective that should be taken into account for future policy decision making. Key messages We show that in a context of poverty, the introduction of payment for specific hospital types can be efficient for shifting demand, but has doubtable impact on costs containment for the provider. The co-payment policy can have a negative impact on patients' health since after its implementation demand increased at free-of-charge hospitals, which typically have less resources to treat patients.

scholarly journals P17 An audit of Trakcare discharge times for Laparoscopic Cholecystectomy

BJS Open ◽  
2021 ◽  
Vol 5 (Supplement_1) ◽  
Author(s):  
Jacob Rapier ◽  
Steven Hornby ◽  
Jacob Rapier
Keyword(s):  
Laparoscopic Cholecystectomy ◽  
Length Of Stay ◽  
Initial Data ◽  
Best Practice ◽  
Average Length ◽  
Accurate Data ◽  
Day Case ◽  
Average Length Of Stay ◽  
Number Of Patients ◽  
Elective Laparoscopic Cholecystectomy

Abstract Introduction Nationally 61,220 Laparoscopic Cholecystectomies are carried out annually. Those carried out as day-cases reduce providers’ costs and increase income through the best practice tariff. The system in our trust to record discharges is ‘Trakcare’. The aim of this audit was to accurately measure the discharge times of patients undergoing elective Laparoscopic Cholecystectomies, to try and reduce the number of patients recorded as having an overnight stay by accurate data collection. Methods Initial data was collected for all elective Laparoscopic Cholecystectomy discharge times on Trakcare, over a 1 month period. This data was then re-audited prospectively both from Trakcare and discharges reported by nurses/patients. A comparison was then made of Trakcare against reported discharge times. Results Initially 54 operations were recorded, with 30 completed as day cases (55.6%). The re-audited data (on Trakcare) recorded 47 operations, with 15 completed as day cases (37.91%). Of these discharges we were able to capture 26 (55.32%) manually, and 11 were completed as day cases (42.31%). Measuring these 26 with the same operations on Trakcare we were unable to show a difference in the number of cases completed as a day case (11 vs 11), with only a 33 minute decrease in the average length of stay. Conclusion Trakcare is a reliable tool for measuring the date of discharge for patients. The recommendations in are: scheduling surgery for a time pre-13:00 shows a higher proportion of patients discharged the same day, and continue to use Trakcare to record discharge times.

Total Population Estimate of Newborn Special-Care Bed Needs

PEDIATRICS ◽  
1985 ◽  
Vol 75 (6) ◽  
pp. 993-996
Author(s):  
August L. Jung ◽  
Nan Sherman Streeter
Keyword(s):  
Length Of Stay ◽  
Total Population ◽  
Average Length ◽  
Special Care ◽  
Care Hospital ◽  
Total Hospital ◽  
Live Births ◽  
Average Length Of Stay ◽  
Study Results ◽  
Hospital Days

In 1977, 7% of the 38,855 infants born in Utah were estimated to have required a total of 27,439 special-care hospital days. About half (53%) were mildly ill; their average length of stay was 4.6 days, or 24% of the total hospital-days. Another 20% of the infants had intermediate illness, with a 12-day average stay, or 23% of the total hospital-days. The remaining 27% of the infants required intensive care and used 53% of the total hospital-days; their average length of stay was 20 days. As a total population, the state's 38,855 births generated a need for two beds per 1,000 annual live births in special-care facilities. The estimated bed need was: mild illness (Level I), 0.5 beds per 1,000 annual live births; intermediate illness (Level II), 0.5 beds per 1,000 annual live births; and intense illness (Level III), one bed per 1,000 annual live births. Results are based on the assumption that nonstudy births, 30% of the total, have needs proportionate to study births. The following considerations are necessary to extrapolate these bed needs to other populations: (1) convalescence of intensely ill babies may require that up to 50% of their bed needs may be shifted to intermediate care; (2) compliance with criteria for transport to the next level of care may not be 100% as assumed in the study, thus redistributing bed needs; (3) census characteristically fluctuates in special-care nurseries (study results are reported for an unchanging daily census); and (4) the low birth rate of a population is intimately related to the bed needs.

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