Bed Occupancy Rate Research Articles

FOOD DISTRIBUTION BEFORE AND DURING THE COVID-19 PANDEMIC AT THE NUTRITION INSTALLATION OF THE TUGUREJO REGIONAL GENERAL HOSPITAL SEMARANG: A DESCRIPTIVE STUDY

The COVID-19 pandemic has made some of the activities carried out differently than before the pandemic. The handling and treatment of COVID-19 are inseparable from the contribution of healthcare facilities and hospitals. The physical distancing recommendation to prevent the transmission of the COVID-19 virus that supports patient care has made the food service management in hospitals – especially food distribution – undergo several modifications. The purpose of this study was to analyze the differences in the food distribution process at the Nutrition Installation of Tugurejo Regional General Hospital Semarang before and during the COVID-19 pandemic. This descriptive study used observational methods and online interviews using structured questions. Data related to the food distribution process before and during the pandemic was acquired through interviews with the Head of Research and Development of the Nutrition Installation of Tugurejo Regional General Hospital Semarang, while observation was only done during the pandemic. There were differences in the food distribution system before and after the pandemic at the Nutrition Installation of Tugurejo Regional General Hospital Semarang related to the Bed Occupancy Rate (BOR), nutritional service classes, distribution processes, food distribution time, places to eat (food serving media), hygiene and sanitation, as well as measuring food acceptance. The food service management focused on providing the best services of patient care before the pandemic; and highlighted the importance of physical distancing, sanitation, and hygiene during the pandemic. Understanding the changes needed in food distribution services at the hospital during the COVID-19 pandemic will give insights into the approach to improve patient care and prevent the transmission of the COVID-19 virus.

The burden of non-SARS-CoV2 viral lower respiratory tract infections in hospitalized children in Barcelona (Spain): A long-term, clinical, epidemiologic and economic study.

Viral lower respiratory tract infections (LRTI) are the leading cause of hospitalization in children. In Catalonia (Spain), information is scarce about the burden of viral LRTIs in paediatric hospitalizations. The aim of this study is to describe epidemiological, clinical, virological and economic features of paediatric hospitalizations due to viral LRTI. From October 2012 to December 2020, children aged <16 years admitted to a tertiary paediatric hospital in Catalonia (Spain) with confirmed viral LRTI were included in the study. Virus seasonality, prevalence, age and sex distribution, clinical characteristics, hospital costs and bed occupancy rates were determined. A total of 3,325 children were included (57.17% male, 9.44% with comorbidities) accounting for 4056 hospitalizations (32.47% ≤ 12 months): 53.87% with wheezing/asthma, 37.85% with bronchiolitis and 8.28% with pneumonia. The most common virus was respiratory syncytial virus (RSV) (52.59%). Influenza A was associated with pneumonia (odds ratio [OR] 7.75) and caused longer hospitalizations (7 ± 31.58 days), while RSV was associated with bronchiolitis (OR 6.62) and was the most frequent reason for admission to the paediatric intensive care unit (PICU) (11.23%) and for respiratory support (78.76%). Male sex, age ≤12 months, chronic conditions and bronchiolitis significantly increased the odds of PICU admission. From October to May, viral LRTIs accounted for 12.36% of overall hospital bed days. The total hospitalization cost during the study period was €16,603,415. Viral LRTIs are an important cause of morbidity, hospitalization and PICU admission in children. The clinical burden is associated with significant bed occupancy and health-care costs, especially during seasonal periods.

The effect of time-varying capacity utilization on 14-day in-hospital mortality: a retrospective longitudinal study in Swiss general hospitals

BackgroundHigh bed-occupancy (capacity utilization) rates are commonly thought to increase in-hospital mortality; however, little evidence supports a causal relationship between the two. This observational study aimed to assess three time-varying covariates—capacity utilization, patient turnover and clinical complexity level— and to estimate causal effect of time-varying high capacity utilization on 14 day in-hospital mortality.MethodsThis retrospective population-based analysis was based on routine administrative data (n = 1,152,506 inpatient cases) of 102 Swiss general hospitals. Considering the longitudinal nature of the problem from available literature and expert knowledge, we represented the underlying data generating mechanism as a directed acyclic graph. To adjust for patient turnover and patient clinical complexity levels as time-varying confounders, we fitted a marginal structure model (MSM) that used inverse probability of treatment weights (IPTWs) for high and low capacity utilization. We also adjusted for patient age and sex, weekdays-vs-weekend, comorbidity weight, and hospital type.ResultsFor each participating hospital, our analyses evaluated the ≥85th percentile as a threshold for high capacity utilization for the higher risk of mortality. The mean bed-occupancy threshold was 83.1% (SD 8.6) across hospitals and ranged from 42.1 to 95.9% between hospitals. For each additional day of exposure to high capacity utilization, our MSM incorporating IPTWs showed a 2% increase in the odds of 14-day in-hospital mortality (OR 1.02, 95% CI: 1.01 to 1.03).ConclusionsExposure to high capacity utilization increases the mortality risk of inpatients. Accurate monitoring of capacity utilization and flexible human resource planning are key strategies for hospitals to lower the exposure to high capacity utilization.

Queuing management study at the Multidisciplinary Anesthesia and Intensive Care Clinic of CNHU-HKM in April 2022

Objective: Constant availability of inpatient beds in an intensive care unit (ICU) is part of the resilience of health systems, especially in an emergency context, namely in public health. This study aims to appraise the management of inpatient waiting lines in the ICU of Hubert Koutoukou Maga National Hospital and University Center (CNHU-HKM) in Benin, in March-April 2022.Methods: This was an analytic cross-sectional study of inpatients or their relatives and staff, selected by convenience and reasoned choice, respectively, carried out from March 21 to April 15, 2022. Logistic regression was used to identify associated factors with queues management.Results: Altogether 55 patients were surveyed. On a daily basis, 13 ± 1 patients were hospitalized in 18 functional beds for 3 ± 1 admissions and 3 ± 1 discharges. The average bed occupancy rate was 89.8% ± 3.8%; the average waiting time before patient care was 3.6 ± 1.2 minutes and the traffic intensity were 0.03. Per hour, the odds of having a patient were 33.29%, with a 97% chance of a bed being occupied. The probability that an admitted patient would spend a whole week there was 37%. Only patient arrival flow was significantly associated with insufficient queuing management. There was also a lack of inpatient beds and technical boards. The construction of two wards and the installation of seven additional beds could improve queues management.Conclusions: The management of AF in our study site depends mainly on the daily flow of arriving patients, but also on the number of available hospital beds, the working organization and the existing technical and structural measures. Addressing these parameters will significantly improve the situation.

Analisis Kualitas Pengelolaan Mutu Pelayanan Pendaftaran Pasien di Instalasi Rawat Inap Rumah Sakit Santa Elisabeth Medan

Inpatient services are non-structural service units that provide facilities and organize individual health service activities which include observation, diagnosis, treatment, nursing and medical rehabilitation. Inpatient registration (TPPRI) is the responsible part of the data and information of patients to be hospitalized. Hospitalization is the maintenance of hospital health where the patient stays for at least one day based on referrals from the implementation of other health services. This study aims to find out how the flow of processing the quality of patient registration services at the Inpatient Installation at Santa Elisabeth Hospital Medan. This study aims to find out how the flow of processing the quality of patient registration services at the Inpatient Installation at Santa Elisabeth Hospital Medan. This study is a qualitative descriptive study using purposive sampling, and collected 17 informants, namely 10 inpatients, 3 medical record services, 4 inpatient registration officer service staff at Santa Elisabeth Hospital Medan. Inpatient installation is one of the clinical services that serves patients who have to be treated for one day or more. The assessment of the success rate of services in health services is usually seen from various aspects, namely the level of utilization of facilities, quality and level of service efficiency. Some standard indicators related to health services that are monitored include bed utilization (Bed Occupancy Rate / BOR), average length of stay (LOS), average bed turn over (BTO), and percentage of discharged patients who died ≥ 48 hours of treatment (Net Death Rate/ NDR).

Pelaksanaan Sensus Harian Rawat Inap di Rumah Sakit Elisabeth Medan

Processing of the daily inpatient census starts from filling out the daily inpatient census by the head of the room or the person in charge and the daily inpatient census is sent to the medical record room every working day at 08.00 am. Information generated from daily inpatient census data in the form of inpatient management indicators consisting of BOR (Bed Occupancy Rate), TOI (Turn Over Interval), LOS (Length Of Stay), BTO (Bed Turn Over) to monitor activities in hospitalization and GDR (Gross Death Rate), NDR (Net Death Rate) to assess the quality of inpatient services. Implementation of the Daily Inpatient Census At Elisabeth Hospital Medan, it was found that the preparation of the daily inpatient census was guided by the technical instructions for filling out the daily inpatient census, but because the technical instructions in each ward were no longer available, there was no need to make the daily inpatient census. . Data collection methods used in this study were interviews and active participation observations using research instruments in the form of interview guidelines. The results showed that the standard procedure at RSE Medan in making the daily inpatient census had not been fully implemented when sending the daily inpatient census from the ward to the medical records department. The source of data in making the daily inpatient census is the inpatient service register book. The method of making a daily inpatient census at RSE Medan is not in accordance with the Ministry of Health of the Republic of Indonesia (2006).

Assessment of Health Performance and Outcome with Disease Profile among Paediatrics Population of a Non COVID Tertiary Care Hospital in Bangladesh in COVID Era

Background: Hospital based data of diseases profile are reflection of community at large. Being in COVID pandemic era, knowledge of disease pattern and outcome in children is crucial for proper resource allocation and health care planning. Performance evaluation of each hospital has become central to the concept of quality improvement. Objective: to evaluate disease pattern and outcome of a non COVID hospital in COVID era. Methodology: This retrospective descriptive study was conducted in pediatric unit (1 months to 14 year) of Sir Salimullah Medical College Mitford Hospital from January, 2021 to December, 2021. Medical records were reviewed and analyzed for age, gender, disease, duration of hospital stay, bed occupancy rate and outcome. Results: Total 4346 patients were admitted of which male is 68%. Most admission was in between 1 month to 12 months of age which is 48.5%. Bronchopneumonia, Dengue and Bronchiolitis became the top 3 cause of admission. 70% patients stayed less than 7 days. 2% patients were referred of which maximum were later diagnosed as COVID-19 patients. Bed Occupancy rate was 138% and Bed Turn Over rate was 72.4 patients/bed/year. Mortality rate was 1.6%. Conclusion: To achieve SDG 3 goal by 2030, assessment of hospital performance as well as disease profile of each hospital is needed for proper resource allocation and community improvement. Sir Salimullah Med Coll J 2022; 30: 168-174

Evaluating the Impact of Introducing Modified Early Warning Score to Identify Deteriorating Patients in the Wards at a Tertiary University Hospital - A before-after Study

BACKGROUND&#x0D; Modified early warning score (MEWS) is a scoring system being used in hospitals for the identification of patients who may deteriorate into medical emergencies or cardiac arrest. However, the mortality benefit of MEWS hasn’t been established. Also, there is limited data about the experience of MEWS being implemented in low-income countries. Hence, we conducted a before-after prospective observational study to evaluate the impact on ICU mortality post-introduction of the MEWS chart.&#x0D; METHODS&#x0D; MEWS before-after study is a single-centre prospective observational study in a tertiary university hospital conducted in the ICU at Kasturba Hospital, Manipal University, India. We trained ward nurses on MEWS and introduced the MEWS chart and compared the change in outcomes from two months prior (i.e. February-March 2018) to the subsequent two months (i.e. April-May 2018). The primary outcome measured was the ICU mortality between the samples. Our secondary outcomes were the length of stay (LOS) and hospital mortality. Student t-test was used to estimate the total sample size and we used the chi-square test for statistical analyses.&#x0D; RESULTS&#x0D; We enrolled 161 patients into each group and the patient demographics between groups did not show any statistically significant difference. The ICU mortality data did not show any statistically significant difference before the introduction of MEWS after using the chi-square test with a p-value of 0.33. There was no statistically significant difference in ICU LOS, ICU re-admission rates, hospital LOS, hospital mortality, bed occupancy rates, or incidence of CPR between the two periods.&#x0D; CONCLUSIONS&#x0D; Our study did not show a significant difference in the mortality after introduction of MEWS scoring charts to our wards. The introduction of critical care outreach services may improve the outcomes.

Peak Health Care Burden During the First Three COVID-19 Waves in the Republic of Croatia

Introduction: One of the main concerns during the COVID-19 pandemic was the overload of health care sector capacities. The objective of this paper was to show peak numbers of selected indicators during the three COVID-19 waves in Croatia and ensure information that will enable revision of preparedness plan and potential hospitals` (re)organization. Methods: Retrospective analysis of COVID-19 testing, infections, hospitalizations, ICU admissions, mechanical ventilation support and deceased data collected via capacity surveillance in the Republic of Croatia during the first three waves. Results: Peak hospital bed occupancy rates observed in the 2nd and 3rd waves were 70.19% and 54.60%, compared to maximum capacity during the COVID-19 wave, and 168.90% and 131.38%, compared to maximum capacity between waves, while ICU beds occupancy rates were 75.51% and 70.73%, and 170.51% and 160.37%, respectively. Peak daily numbers were as follows (first/ second/third wave); positive persons: 53/4827/3198; tested persons: 1984/13325/11622; total hospitalized persons: 372/2976/2315; total mechanical ventilation needed: 31/306/278; total ICU hospitalized: unknown/370/348; deceased: 8/92/52. Conclusion: During pandemic waves, the requirements for hospital and ICU beds significantly exceeded standard available health sector capacities. The system has acutely adjusted by increasing the number of beds available for COVID-19 patients. However, given the peaks observed so far, a permanent additional increase or reorganization of hospital capacity is needed to ensure that during the upcoming waves non-COVID-19 and COVID-19 patients won’t be endangered or part of the staff overloaded.

Comparing the Bed Occupancy Rate for January 2022 of Various Departments at Holy Family Hospital Rawalpindi Pakistan

Objective: To compare the bed occupancy rates of various departments of Holy Family Hospital during January 2022. Materials &amp; Methods: A cross-sectional descriptive study was done to determine and compare the Bed Occupancy Rates (BOR) of January 2022 from numerous departments of Holy Family Hospital Rawalpindi. Medicine &amp; Allied departments in our study were those of Medicine, Nephrology and Paediatrics. Surgery and Allied departments were comprised of General Surgery, Plastic Surgery, Pediatric Surgery, Gynecology, Obstetrics, ENT, Ophthalmology and Neurosurgery. No. of beds for Medicine and Surgery &amp; Allied departments are denoted by “n”. Data was analysed by Microsoft Excel 2010. Data was also gathered from intensive care units of the hospital. BOR% of each department and mean BOR were calculated. Difference between Mean BOR ± SD of Medicine &amp; Allied and Surgery &amp; Allied was statistically confirmed by applying independent sample t-test. P ≤ 0.05 was taken as significant. 95% CI Results: Mean BOR of hospital wards was 97.6%. The greatest BOR was reported from Plastic Surgery department (154%) followed by that from Paediatrics (128%). Nephrology and Obstetrics with same BOR (121%) were ranked third. Mean BOR of Medicine &amp; Allied departments was 108.7 ± 27.59 while that of Surgery &amp; Allied was 93.4 ± 35.79. This difference of mean BOR was statistically significant (P = 0.000; 95% CI, 9.4 – 21.2). The crowning of BOR from Pediatric and Neonatal ICU was acknowledged with 247% and 223.10% respectively. The female patients in both medical and surgical departments were greater in magnitude than males. Conclusion: BOR of public sector teaching hospital is quite enormous that needs attention of policy makers for diminution.

Comparing the Bed Occupancy Rate for January 2022 of Various Departments at Holy Family Hospital Rawalpindi Pakistan

Objective: To compare the bed occupancy rates of various departments of Holy Family Hospital during January 2022. Materials &amp; Methods: A cross-sectional descriptive study was done to determine and compare the Bed Occupancy Rates (BOR) of January 2022 from numerous departments of Holy Family Hospital Rawalpindi. Medicine &amp; Allied departments in our study were those of Medicine, Nephrology and Paediatrics. Surgery and Allied departments were comprised of General Surgery, Plastic Surgery, Pediatric Surgery, Gynecology, Obstetrics, ENT, Ophthalmology and Neurosurgery. No. of beds for Medicine and Surgery &amp; Allied departments are denoted by “n”. Data was analysed by Microsoft Excel 2010. Data was also gathered from intensive care units of the hospital. BOR% of each department and mean BOR were calculated. Difference between Mean BOR ± SD of Medicine &amp; Allied and Surgery &amp; Allied was statistically confirmed by applying independent sample t-test. P ≤ 0.05 was taken as significant. 95% CI Results: Mean BOR of hospital wards was 97.6%. The greatest BOR was reported from Plastic Surgery department (154%) followed by that from Paediatrics (128%). Nephrology and Obstetrics with same BOR (121%) were ranked third. Mean BOR of Medicine &amp; Allied departments was 108.7 ± 27.59 while that of Surgery &amp; Allied was 93.4 ± 35.79. This difference of mean BOR was statistically significant (P = 0.000; 95% CI, 9.4 – 21.2). The crowning of BOR from Pediatric and Neonatal ICU was acknowledged with 247% and 223.10% respectively. The female patients in both medical and surgical departments were greater in magnitude than males. Conclusion: BOR of public sector teaching hospital is quite enormous that needs attention of policy makers for diminution.

COVID-19 Pandemic and Hospital Efficiency in Iran: Insight from an Interrupted Time Series Analysis and Pabon Lasso Model.

Limited evidence exists on the impact of the Coronavirus Disease 2019 (COVID-19) pandemic on hospital efficiency worldwide. This study aimed to investigate the impact of the COVID-19 pandemic on public hospitals in Iran. In this quasi-experimental study, monthly data on the average length of stay (ALoS), bed occupancy rate (BOR), bed turnover rate (BTR) and bed turnover interval (BTI) were collected for 58 months (36 months before and 22 months after the COVID-19 outbreak in Iran) from the health information systems of all 18 public hospitals affiliated with Kermanshah University of Medical Sciences in Kermanshah province, Iran. We used interrupted time series analysis and the Pabon Lasso model to investigate the impact of the COVID-19 pandemic on hospital efficiency. The monthly average ALoS, BOR, BTR and BTI before (after) the COVID-19 pandemic was 3.30 (3.48) days, 70.14% (49.37), 6.78 (4.81) patients per bed and 1.15 (2.88) days, respectively. The study indicated that a statistically significant decrease in ALoS of 0.29 and BOR of 25.09 in the first month following the COVID-19 pandemic. Compared with the before pandemic period, we observed a significant increase in the monthly trend of ALoS (coefficient = 0.021; p = 0.015), BOR (coefficient = 1.30; p = 0.002), and BTR (coefficient = 0.08, p = 0.012). We found a significant decrease in the monthly trend in BTI (coefficient = -0.11, p = 0.009) after the COVID-19 pandemic when compared with before the pandemic. Based on the Pabon Lasso model, before (after) the pandemic, 29.4% (29.4%) of the hospitals were located in zone 1 as an inefficient area, and 17.6% (35.3%) of hospitals were located in zone 3 as an efficient area. The study demonstrated that the BOR and BTR decreased substantially after the outbreak of COVID-19. In contrast, the ALoS and BTI have significantly increased following the COVID-19 pandemic. We also found that hospitals' performance in both periods was poor, and only 30% of hospitals were located in the efficient zone (zone three) based on the Pabon Lasso model. Further studies aimed at identifying the main factors affecting lower efficiency among hospitals in Iran are recommended.

Identification and prioritization of indicators of hospital bed allocation in Iran

AbstractThe distribution of hospital beds can be used as an indicator to assess the distribution of health services. This study aimed to determine and prioritize indicators of hospital bed allocation in Iran. In the first phase of the study, we used a scoping review to identify criteria affecting hospital bed allocation. Then, we applied an expert panel and the Delphi method to localize the criteria. Finally, we carried out Analytic Network Process method based on Decision Making Trial and Evaluation Laboratory technique (DANP), to determine the weight and importance of indicators and to evaluate the causal relationship between them. Based on the scoping review, we identified 75 criteria that influence bed allocation. In 2 Delphi cycles, 28 criteria were selected and included in the DANP phase. The population, the presence of a reference hospital in the region, the type of hospital, the common diseases in the region, and the presence of home care services were the variables that had the most interaction with other variables. The variable of home care services was at the highest level of the causal chain. Bed occupancy rate, average length of stay, waiting list, as well as type and level of the hospital had the highest priority in the allocation of hospital beds. Furthermore, given the importance of home care services, policies should be adopted to expand these services nationwide. The indicators identified in this study will be useful for the development of policies aimed at an equitable allocation of hospital beds.

International Accreditation Standards and the Benefits to Hospitals Attracting Medical Tourists

There are several studies showing international hospital accreditation does have some impact on clinical standards and even bed occupancy rates. However, little is known about the impact on attracting more international medical tourists to hospitals that have received this distinction. It was expected, prior to the study, that participating in international accreditation might increase operational expenses and greater amounts of international patients would also boost patient volumes and profitability. However, this research found that the investment in accreditation led to insignificant changes (pre-accreditation versus post-accreditation) in operating profit margins (OPM), net profit margins (NPM), and the debt-to-equity (D/E) ratio. This suggests that international hospital accreditation has little impact on the financial aspects of the hospital's operations. It appears to be more of a signaling strategy than a recipe for growth. However, there may be some other tangible benefits of international accreditation (e.g., better medical/clinical outcomes).

A Model to Compare International Hospital Bed Numbers, including a Case Study on the Role of Indigenous People on Acute 'Occupied' Bed Demand in Australian States.

Comparing international or regional hospital bed numbers is not an easy matter, and a pragmatic method has been proposed that plots the number of beds per 1000 deaths versus the log of deaths per 1000 population. This method relies on the fact that 55% of a person’s lifetime hospital bed utilization occurs in the last year of life—irrespective of the age at death. This is called the nearness to death effect. The slope and intercept of the logarithmic relationship between the two are highly correlated. This study demonstrates how lines of equivalent bed provision can be constructed based on the value of the intercept. Sweden looks to be the most bed-efficient country due to long-term investment in integrated care. The potential limitations of the method are illustrated using data from English Clinical Commissioning Groups. The main limitation is that maternity, paediatric, and mental health care do not conform to the nearness to death effect, and hence, the method mainly applies to adult acute care, especially medical and critical care bed numbers. It is also suggested that sensible comparison can only be made by comparing levels of occupied beds rather than available beds. Occupied beds measure the expressed bed demand (although often constrained by access to care issues), while available beds measure supply. The issue of bed supply is made complex by the role of hospital size on the average occupancy margin. Smaller hospitals are forced to operate at a lower average occupancy; hence, countries with many smaller hospitals such as Germany and the USA appear to have very high numbers of available beds. The so-called 85% occupancy rule is an “urban myth” and has no fundamental basis whatsoever. The very high number of “hospital” beds in Japan is simply an artefact arising from “nursing home” beds being counted as a “hospital” bed in this country. Finally, the new method is applied to the expressed demand for occupied acute beds in Australian states. Using data specific to acute care, i.e., excluding mental health and maternity, a long-standing deficit of beds was identified in Tasmania, while an unusually high level of occupied beds in the Northern Territory (NT) was revealed. The high level of demand for beds in the NT appears due to an exceptionally large population of indigenous people in this state, who are recognized to have elevated health care needs relative to non-indigenous Australians. In this respect, indigenous Australians use 3.5 times more occupied bed days per 1000 deaths (1509 versus 429 beds per 1000 deaths) and 6 times more occupied bed days per 1000 population (90 versus 15 beds per 1000 population) than their non-indigenous counterparts. The figure of 1509 beds per 1000 deaths (or 4.13 occupied beds per 1000 deaths) for indigenous Australians is indicative of a high level of “acute” nursing care in the last months of life, probably because nursing home care is not readily available due to remoteness. A lack of acute beds in the NT then results in an extremely high average bed occupancy rate with contingent efficiency and delayed access implications.

IMPLEMENTASI BUSINESS INTELLIGENCE UNTUK PENILAIAN MUTU PELAYANAN DI RUMAH SAKIT UMUM DAERAH TULANG BAWANG BARAT

KMK number 340 about the classification of hospitals, hospitals must have the ability to serve at least general medical services, emergency services, nursing services, outpatient care, inpatient care, surgery, basic specialist medical services, medical support, pharmacy, nutrition, sterilization, medical records, administrative and management services, public health counseling, relocation of corpses, laundry, and ambulances, maintenance of hospital facilities, and waste treatment. Business Intelligence is one solution so that hospital management gets information about service quality assessments that can help make decisions. The application used to implement Business Intelligence is Google Data Studio. This study uses six indicators of hospital quality service standards (SPM), namely Bed Occupancy Rate (BOR), Turn Over Interval (TOI), Average Length of Stay (ALOS), Bed Turn Over (BTO), Net Death Rate (NDR), and Gross Death Rate (GDR). The data variables that need indicator values are time, number of patients, number of patients discharged, number of patients dying &gt;48 hours, number of dead patients, number of days of treatment, number of lengths of stay and number of beds. The data is processed by the Extract, Transform, Load (ETL) process to form a data warehouse. The data contained in the data warehouse will be visualized on Google Data Studio.

Effect of COVID-19 Patients Flow Rate from ER to LPD on COVID-19 Patients Healing Rates at RSUP DR. Sardjito’s ER

COVID-19 or Coronavirus Disease-19 which first appeared in December 2019 has spread around the world, one of which is Indonesia. The spread of the COVID-19 has affected all areas of human life and the most affected area is health. It can be known from the number of COVID-19 patients in numerous national referral hospitals, one of which is RSUP Dr. Sardjito. This large number of COVID-19 patients often causes a high number of bed occupancy rates and has an impact on special rooms, the room for COVID-19 patients who come to the hospital for the first time or the Emergency Room (ER) and the room for COVID-19 patients from the ER who was declared seriously ill or inpatient. Furthermore, imbalance between the number of ER and Long-stay Patient Department (LPD) and the number of COVID-19 patients result in a decrease in the flow rate of COVID-19 patients from the ER to the long stay patient department. To find out the impact of that flow rate, this research was conducted using Richard's Curve and Kaplan-Meier Estimator. The results of this research show effect of flow rate which can be observed from the probability of COVID-19 patients who recovered or died in each special room. The probability of a COVID-19 patient in the ER recovered is greater than the probability of a patient died. Meanwhile, the probability of a COVID-19 patient in the long stay patient department recovered is smaller than the probability of a patient died.

The Impact of COVID-19 on Pediatric Healthcare Utilization and Disease Dynamics: An Observational Study From Western Odisha.

IntroductionChildren were affected by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus during the first and second waves of the coronavirus disease 2019 (COVID-19 pandemic. Although the severity was less in children, the fear of contracting SARS-CoV-2 at the hospital might have led to a delayed health-seeking attitude. The objective of the study was tailored around emergency health care utilization affecting outcomes. The study was done to compare the trend concerning the utilization of pediatric healthcare and immunization services, changes in the profile of diseases, and the outcomes between the pre-COVID-19 period and the COVID-19 period in a tertiary care hospital.MethodsThis retrospective observational study was conducted in a tertiary care hospital in western Odisha. Data were collected retrospectively from different hospital registers (outpatient register, inpatient register, and immunization records) and analyzed between the pre-COVID-19 period (April 2019 to March 2020) and the COVID-19 period (April 2020 to March 2021) with appropriate statistical procedures.ResultsThere was a 60%, 49.8%, 51.1%, and 25.5% reduction in outpatient attendance, indoor pediatric admissions, nutritional rehabilitation centre admissions, and newborn admissions, respectively in COVID-19 period as compared to the pre-COVID-19 period. The pediatric bed occupancy rate was reduced by 54.5%. Unfavourable outcomes (death, left against medical advice, and referral) were significantly high in hospitalized children (24% vs. 18.1%, p < 0.001). The reduction in hospitalization due to common conditions like acute respiratory tract infections, bronchiolitis and asthma, and acute gastroenteritis during COVID-19 was 76.5%, 86.2%, and 39.5%, respectively. A higher percentage of low birth weight and preterm (<34 weeks) babies were admitted to special neonatal care unit (SNCU) during the pandemic (61.8% vs. 58%, p < 0.05; 18.9% vs. 15.8%; p < 0.05 respectively).ConclusionThe COVID-19 pandemic and the associated lockdown led to a significant decrease in pediatric and neonatal healthcare utilization. The impact of lower care-seeking and attendance resulting in poor patient-related outcomes (malnutrition, upsurge of vaccine-preventable diseases, disease-specific hospitalization, and mortality) post-pandemic is a real threat.

Why Do Inpatient Visits Decrease during the Covid-19 Pandemic? A Case Study in Hospital, Malang Regency

The Covid-19 pandemic has caused a decreasing number of non-Covid-19 inpatient visits in almost all hospitals, including the hospital where the study was conducted, which experienced decreasing Bed Occupancy Rate (BOR) up to 35.5%. This study aimed to identify the factors causing the decrease in the number of inpatients at the hospital. The research was conducted using a case study approach at a type D hospital in Malang Regency. Data was collected through a Focus Group Discussion (FGD) analyzed using a Fishbone Diagram combined with 5 whys and triangulation using secondary data and surveys. FGD respondents determined were eight respondents consisting of the Head of Inpatient Room, the Coordinator of Inpatient Room, the Coordinator of Outpatient, the Head of the Public Relations and Marketing Unit, and the Coordinator of the Admission Department. The results show that the causes can originate from human, method, market, and environmental aspects. Distrust in hospitals is caused by negative stigmatization and instructions to delay hospital services and communication barriers due to media as a consequence of implementing health protocols.

Assessing the Performance of a Private Hospital in Nepal: Evidence from Pabon Lasso and Regression Models

There is limited empirical evidence on the relationship between management and performance of private hospitals in Nepal. We address this gap using de-identified inpatient data from a private hospital in Kathmandu between 2013 and 2017. We consider foreign-born and native-born patients separately, in addition to the full sample. Using a Pabon Lasso model, we assess relationship between hospital management and: (a) bed occupancy rate; (b) bed turnover rate; and (c) average length of stay. To complement the Pabon Lasso model, we use a regression analysis to assess the relationship between hospital management and length of stay in a multivariate framework. Our results indicate that separation between the chief executive officer (CEO) and board may promote better performance, versus CEO duality. However, there are important differences by performance indicator, patient type (i.e., native-born versus foreign-born) and analytical approach. These results comprise new evidence on the relationship between management and performance of private hospitals in a developing context.