scholarly journals Length of Stay of Psychiatric Admissions in a Tertiary Care Hospital

2018 ◽  
Vol 56 (210) ◽  
pp. 593-597
Author(s):  
Madhur Basnet ◽  
Nidesh Sapkota ◽  
Suren Limbu ◽  
Dharanidhar Baral
Keyword(s):  
Logistic Regression ◽  
Length Of Stay ◽  
Average Length ◽  
Tertiary Care ◽  
Psychiatric Ward ◽  
Care Hospital ◽  
Factors Affecting ◽  
Factors Associated ◽  
Psychiatric Admissions ◽  
Co Morbidity

Introduction: The length of stay among psychiatric in-patients is usually longer than that of others. In-patient management is costly and longer length of stay can lead to catastrophic costs. We conducted this study to explore about the length of stay of psychiatric admissions and factors affecting it.Methods: We collected the data of all the patients admitted to the psychiatric ward of B. P. Koirala Institute of Health Sciences from 1st January 2007 to 31st December 2016 from the database of the medical records section after ethical approval. The sociodemographic and clinical variables were analyzed using SPSS 20.0 version. Length of stay more than 3 weeks was considered as long stay. Bivariate and multivariable logistic regression analyses were conducted to identify factors associated with length of stay.Results: There were 3687 admissions during the study period. The average length of stay was 19.36 (±13.14) days. On logistic regression, the factors associated with shorter length of stay were: male gender (aOR= 0.79, 95%CI: 0.68-0.93), being self employed (aOR= 0.17, 95%CI: 0.12-0.22), homemakers (aOR= 0.18, 95%CI: 0.14-0.24), farmers (aOR= 0.20, 95%CI: 0.15-0.27) and students (aOR= 0.23, 95%CI:0.17-0.32). Similarly, factors associated with longer length of stay were: being from other Eastern Terai districts(aOR=1.37, 95%CI: 1.11-1.70), other Eastern Hill districts (aOR= 1.68; 95%CI: 1.29-2.20), diagnosis of schizophrenia and related disorders (aOR=4.01, 95%CI: 1.34-12.0), having medical co-morbidity (aOR= 3.47; 95%CI: 2.49-4.84) and being readmitted (aOR= 1.23, 95%CI: 1.03-1.47).Conclusions: There was significant association of length of stay with gender, age, address, occupation, diagnosis and readmission

scholarly journals Percent Bed occupancy rate in a selected specialized tertiary care hospital in Dhaka city

1970 ◽  
Vol 11 (1) ◽  
pp. 18-24 ◽  
Author(s):  
H Rahman ◽  
SME Haque ◽  
MA Hafiz
Keyword(s):  
Length Of Stay ◽  
Tertiary Care Hospital ◽  
Average Length ◽  
Tertiary Care ◽  
Calculated Data ◽  
Care Hospital ◽  
Dhaka City ◽  
Occupancy Rate ◽  
Bed Occupancy ◽  
Average Length Of Stay

Background and Aims: Providing a necessary care for a sick person outside home 'in hospes or hospital' dates back to nearly 300 century BC. In the present day hospital care facilities has been taken an institutional shape both in public and private sector. A hospital bed is both a scarce and expensive commodity in healthcare. Administrators running hospitals are in a dire need of objective measures and methods for efficient management of their limited financial resources. Bed utilization rates can be of immense help in realistic and effective decision making. The present study was undertaken to explore utilization of bed in a specialized tertiary care hospital in the Dhaka city. Methods: Hospital records of the year were reviewed- age, gender, disease profile, duration of hospital stay, outcome of treatment were recorded and bed occupancy rate was calculated. Data were presented as number, percentage and/ or mean SD, as appropriate. The dada were managed by Statistical Package for Social Science (SPSS) for Windows Version 10. Results: The results showed in the year 2001 total number of admissions were 13,305 of which 9953 (74.8%) were male and 3352 (25.2%) female. Average monthly admission was 1109. Maximum number of admissions (1304) was observed in the month of September of that year. Male admission rate was higher than female admission throughout the year. Among all the admission 27.2% were of road traffic accident cases. Among the admitted patients there was 57.3% discharge with advice, 1.9% death, 14.6% discharge on request bond, 12.7% discharge on request. Of all the admission there 12.5% found to be absconded. Bed occupancy rate was 79.75% and average length of stay in the hospital 18.47 days. Conclusions: The present data suggest that (i) in terms of bed occupancy rate the NITOR found to run in optimal capacity which, however, might be attributed to the relative high rate of ascendance and discharges on requests; (ii) average length of stay of patients appeared to be relatively longer and (iii) the management need to look into the issue and take appropriate measures to reduce patients unwanted long duration of stay and make the tertiary care hospital improve the quality of services. DOI: http://dx.doi.org/10.3329/bjms.v11i1.9817 BJMS 2012; 11(1): 18-24

scholarly journals Distance from referral hospital as a risk factor for mortality and length of stay of neonates admitted in a tertiary care hospital

2019 ◽  
Vol 6 (11) ◽  
pp. 4912
Author(s):  
Kawal Krishen Pandita
Keyword(s):  
Risk Factor ◽  
Length Of Stay ◽  
Average Length ◽  
Tertiary Care ◽  
Newborn Care ◽  
Referral Hospital ◽  
Care Hospital ◽  
Prolonged Stay ◽  
Neonatal Deaths ◽  
District Hospitals

Background: Around 66% of infant and over 50% of under-five mortality occurs in newborn period. 99% of neonatal deaths occur in low and middle income countries. Most of these deaths can be prevented by suitable interventions at various levels. The premise of the study is that the neonates who require long transportation (>1 hour) have higher chances of mortality or prolonged stay in the hospital.Methods: A retrospective retrieval of data and prospective interview was conducted in G.B Pant children’s hospital Srinagar, an associated hospital of Govt. Medical College Srinagar in North India.Results: During the period of study 1431 neonates from twelve districts of the state were referred to the hospital for treatment, out of whom, 102 (7.13%) could not be saved. Neonatal death rate was found highest (11.11%) in neonates referred from districts of category-III (>100 kms from the referral hospital), followed by category-II (50-100 kms from the referral hospital) and category-I (>50 kms from the referral hospital). Average length of stay was observed longest for the neonates referred from districts of category-III followed by category-II and category-I.Conclusions: Several other studies found that transfer of sick neonates from another health facility were associated with relatively higher probability of morbidity and mortality after controlling for other predictors. Distance no doubt is a risk factor for neonatal outcome of referred neonates as we have observed in our study. To minimize neonatal deaths it is necessary to strengthen the perinatal services sick newborn care unit {(SNCUs) in district Hospitals)}.

scholarly journals Patient-Associated Risk Factors for Acquisition of Methicillin-Resistant Staphylococcus aureus in a Tertiary Care Hospital

2010 ◽  
Vol 31 (11) ◽  
pp. 1139-1147 ◽  
Author(s):  
Jo-anne M. Salangsang ◽  
Lee H. Harrison ◽  
Maria M. Brooks ◽  
Kathleen A. Shutt ◽  
Melissa I. Saul ◽  
...  
Keyword(s):  
Risk Factors ◽  
Staphylococcus Aureus ◽  
Logistic Regression ◽  
Tertiary Care Hospital ◽  
Conditional Logistic Regression ◽  
Tertiary Care ◽  
Care Hospital ◽  
Factors Associated ◽  
Target Unit ◽  
Associated Risk Factors

Background.Determining risk factors for acquisition of methicillin-resistant Staphylococcus aureus (MRSA) in hospitals is important for defining infection-control measures that may lead to fewer hospital-acquired infections.Objective.To determine patient-associated risk factors for acquisition of MRSA in a tertiary care hospital with the goal of identifying modifiable risk factors.Methods.A retrospective matched case-control study was performed. Case patients who acquired MRSA during hospitalization and 2 matched control patients were selected among inpatients admitted to target units during the period from 2001 through 2008. The odds of exposure to potential risk factors were compared between case patients and control patients, using matched univariate conditional logistic regression. A single multivariate conditional logistic regression model identifying independent patient-specific risk factors was generated.Results.A total of 451 case patients and 866 control patients were analyzed. Factors positively associated with MRSA acquisition were as follows: target unit stay before index culture; primary diagnosis of respiratory disease, digestive tract disease, injury or trauma, or other diagnosis compared with cardiocirculatory disease; peripheral vascular disease; mechanical ventilation with pneumonia; ventricular shunting or ventriculostomy; and ciprofloxacin use. Factors associated with decreased risk were receipt of a solid-organ transplant and use of penicillins, cephalosporins, rifamycins, daptomycin or linezolid, and proton pump inhibitors.Conclusion.Among the factors associated with increased risk, few are modifiable. Patients with at-risk conditions could be targeted for intensive surveillance to detect acquisition sooner. The association of MRSA acquisition with target unit exposure argues for rigorous application of hand hygiene, appropriate barriers, environmental control, and strict aseptic technique for all procedures performed on such Patients. Our findings support focusing efforts to prevent MRSA transmission and restriction of ciprofloxacin use.

Clinico-microbiological profile of health-care associated infections in a paediatric intensive care unit of tertiary care hospital

2017 ◽  
Vol 4 (2) ◽  
pp. 577
Author(s):  
Priyanka Udawat ◽  
Shalu Gupta ◽  
Vikas Manchanda ◽  
Diganta Saikia
Keyword(s):  
Health Care ◽  
Length Of Stay ◽  
Tertiary Care Hospital ◽  
Average Length ◽  
Tertiary Care ◽  
Developed Countries ◽  
Incidence Rates ◽  
Care Hospital ◽  
Microbiological Profile ◽  
Health Care Associated Infections

Background: The study was undertaken to determine the total burden of health-care associated infections, microbiological profile and their impact on length of stay and mortality in a PICU of a tertiary care Hospital by prospective surveillance.Methods: All children ≥ one month and ≤ twelve years of age admitted in PICU for more than 48 hours from December 2009 to November 2010 were followed according to CDC/NHSN surveillance definitions of HCAI. Incidence rates, incidence densities and device utilization ratio were measured for different HCAI. Length of stay and mortality of HCAI were compared with non-HCAI patients. Antibiotic susceptibility pattern of isolated micro-organism was analyzed. Results: Out of total 618 patients admitted in PICU during study period 324 fulfilled study criteria. In those 324 patients 58 patients developed 68 episodes of HCAI. The CIR and IDs’of HCAI were17.9/100 patients and 22.14/1,000 patient-days, respectively. Of the 68 episodes of HCAI, there were 36 VAP, 17 BSI, 8 UTI, 2 pneumonia, 2 LRI-LUNG and 1each of SSI-MED, SST-Skin and GI-IAB. The most common microorganism isolated was Acinetobacter spp. followed by Pseudomonas spp. HCAI increased the average length of PICU stay (20 days versus 5 days, P<0.01) and Hospital stay (28 days versus 12 days, P<0.01). Overall mortality was significantly higher in patients who developed HCAI than non-HCAI (50.9% versus 21.3%, P<0.01).Conclusions: HCAI rates were higher than developed countries. VAP was the most common HCAI followed by BSI. HCAI increased the length of stay and mortality (P<0.01). Organisms isolated in HCAI were more resistant than non-HCAI isolates.

scholarly journals Average length of stay in Level III and IV Care of Accident and Emergency Department of Tertiary care Hospital

JMS SKIMS ◽  
2011 ◽  
Vol 14 (2) ◽  
pp. 61-62
Author(s):  
Reyaz A Rangrez ◽  
Sheikh Mushtaq ◽  
Shafa Deva ◽  
Tanveer A Rather ◽  
Sameena Mufti ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Average Length ◽  
Tertiary Care ◽  
Care Hospital ◽  
Emergency Admissions ◽  
Prolonged Length ◽  
Average Length Of Stay ◽  
Accident And Emergency ◽  
Time Gap

BACKGROUND: The scope of Accident and Emergency (A&E) Department is gradually broadening and in fact these are now becoming“mini hospitals within hospitals”.OBJECTIVE:To determine the average length of stay (LOS) in level III and level IV care and factors leading to prolonged length of stay.METHODS:A Hospital based study with follow up of patients received in level III and level IV of A&E Department and the patients were followed till transfer out to respective specialty wards,discharge or death.RESULTS: Emergency beds occupied 9.3% of the total hospital bed strength. Of the total emergency admissions studied, 71.1 % comprised of neurosurgical admissions followed by CVTS (21.4%), neurological (6.8%) and other admissions(1.2%). The average Length of Stay was greatest in CVTS followed by General Surgery i.e. 5.4 days and 4.6 days respectively. The time gap between investigations ordered and reports received was 1.04 days. 67% of the patients who attended A&E Department were of rural background and out of it 54% have read upto high school.CONCLUSIONS: Average Length of stay is 4.3 days which needs to be brought down to 24 hours as per international norms to provide equitable emergency care to wider population. Co-ordination between administration and cliniciansis needed to expedite theproblem.JMS2011;14(2):61-62

scholarly journals Medication Adherence among Hypertensive Patients Attending a Tertiary Care Hospital in Nepal

2020 ◽  
Vol 17 (4) ◽  
pp. 521-527
Author(s):  
Tara Roka ◽  
Melina Ghimire
Keyword(s):  
Medication Adherence ◽  
Odds Ratio ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Care Hospital ◽  
Hypertensive Patients ◽  
Targeted Interventions ◽  
Factors Associated ◽  
Adherence To Medication ◽  
Co Morbidity

Background: Drug therapy and adherence to the medication is critical to prevent complications of hypertension and more importantly in countries like Nepal where more than one quarter adults suffer from it. Primary aim was to measure adherence to anti-hypertensive medication and factors associated with low adherence.Methods: Morisky Medication Adherence Scale was used for measuring medication adherence and a structured questionnaire for measuring background and illness related factors in a cross-sectional study among 216 hypertensive patients in a tertiary care hospital selected through sequential sampling. Data was analysed using descriptive and inferential statistics and results presented with proportion or odds ratio with 95% CI.Results: It was found that 72% of the patients had low adherence to anti-hypertensive medication, with sub-group differences notably higher among females (77%); among those with co-morbidity (80%); and among those getting medicines free of cost (76%). Post multivariate logistic regression, it was found that patients with co-morbidity had higher odds of having low adherence (Adjusted Odds Ratio – AOR: 2.50; 95%CI:1.28-4.89) than those without; and those who get medicine free of cost had higher odds of having low adherence (AOR: 3.01; 95%CI:1.32-6.86) than those who pay for medicine.Conclusions: A substantial proportion of hypertensive patients had low adherence to medication. Presence of co-morbidity, getting medicine free of cost, and not having regular follow up were the major factors associated with low adherence to anti-hypertensive medication. Targeted interventions in hospitals and health care centers in Nepal would improve medication adherence. Keywords: Adherence; hypertension; hypertensive patients; medication; Nepal.  

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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