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Variability in costs across hospital wards. A study of Chinese hospitals.

ABSTRACT: Analysts estimating the costs or cost-effectiveness of health interventions requiring hospitalization often cut corners because they lack data and the costs of undertaking full step-down costing studies are high. They sometimes use the costs taken from a single hospital, sometimes use simple rules of thumb for allocating total hospital costs between general inpatient care and the outpatient department, and sometimes use the average cost of an inpatient bed-day instead of a ward-specific cost.In this paper we explore for the first time the extent and the causes of variation in ward-specific costs across hospitals, using data from China. We then use the resulting model to show how ward-specific costs for hospitals outside the data set could be estimated using information on the determinants identified in the paper.Ward-specific costs estimated using step-down costing methods from 41 hospitals in 12 provinces of China were used. We used seemingly unrelated regressions to identify the determinants of variability in the ratio of the costs of specific wards to that of the outpatient department, and explain how this can be used to generate ward-specific unit costs.Ward-specific unit costs varied considerably across hospitals, ranging from 1 to 24 times the unit cost in the outpatient department--average unit costs are not a good proxy for costs at specialty wards in general. The most important sources of variability were the number of staff and the level of capacity utilization.More careful hospital costing studies are clearly needed. In the meantime, we have shown that in China it is possible to estimate ward-specific unit costs taking into account key determinants of variability in costs across wards. This might well be a better alternative than using simple rules of thumb or using estimates from a single study.

SUBMITTER: Adam T

PROVIDER: S-EPMC4038551 | biostudies-other | 2014

REPOSITORIES: biostudies-other

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Variability in costs across hospital wards. A study of Chinese hospitals.

Adam Taghreed T Evans David B DB Ying Bian B Murray Christopher J L CJ

PloS one 20140529 5

<h4>Introduction</h4>Analysts estimating the costs or cost-effectiveness of health interventions requiring hospitalization often cut corners because they lack data and the costs of undertaking full step-down costing studies are high. They sometimes use the costs taken from a single hospital, sometimes use simple rules of thumb for allocating total hospital costs between general inpatient care and the outpatient department, and sometimes use the average cost of an inpatient bed-day instead of a w ...[more]

PMID: 24874566

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Project description:BackgroundHospitalized patients are designated alternate level of care (ALC) when they no longer require hospitalization but discharge is delayed while they await alternate disposition or living arrangements. We assessed hospital costs and complications for general internal medicine (GIM) inpatients who had delayed discharge. In addition, we developed a clinical prediction rule to identify patients at risk for delayed discharge.MethodsWe conducted a retrospective cohort study of consecutive GIM patients admitted between 1 January 2015 and 1 January 2016 at a large tertiary care hospital in Canada. We compared hospital costs and complications between ALC and non-ALC patients. We derived a clinical prediction rule for ALC designation using a logistic regression model and validated its diagnostic properties.ResultsOf 4311 GIM admissions, 255 (6%) patients were designated ALC. Compared to non-ALC patients, ALC patients had longer median length of stay (30.85 vs. 3.95 days p < 0.0001), higher median hospital costs ($22,459 vs. $5003 p < 0.0001) and more complications in hospital (25.5% vs. 5.3% p < 0.0001) especially nosocomial infections (14.1% vs. 1.9% p < 0.0001). Sensitivity analyses using propensity score and pair matching yielded similar results. In a derivation cohort, seven significant risk factors for ALC were identified including age > =80 years, female sex, dementia, diabetes with complications as well as referrals to physiotherapy, occupational therapy and speech language pathology. A clinical prediction rule that assigned each of these predictors 1 point had likelihood ratios for ALC designation of 0.07, 0.25, 0.66, 1.48, 6.07, 17.13 and 21.85 for patients with 0, 1, 2, 3, 4, 5, and 6 points respectively in the validation cohort.ConclusionsDelayed discharge is associated with higher hospital costs and complication rates especially nosocomial infections. A clinical prediction rule can identify patients at risk for delayed discharge.

Project description:IntroductionHospital based delivery has been an expensive experience for poor households because of hidden costs which are usually unaccounted in hospital costs. The main aim of this study was to estimate the hidden costs of hospital based delivery and determine the factors associated with the hidden costs.MethodsA hospital based cross-sectional study was conducted among 384 post-partum mothers with their husbands/house heads during the discharge time in Manipal Teaching Hospital and Western Regional Hospital, Pokhara, Nepal. A face to face interview with each respondent was conducted using a structured questionnaire. Hidden costs were calculated based on the price rate of the market during the time of the study.ResultsThe total hidden costs for normal delivery and C-section delivery were 243.4 USD (US Dollar) and 321.6 USD respectively. Of the total maternity care expenditures; higher mean expenditures were found for food & drinking (53.07%), clothes (9.8%) and transport (7.3%). For postpartum women with their husband or house head, the total mean opportunity cost of "days of work loss" were 84.1 USD and 81.9 USD for normal delivery and C-section respectively. Factors such as literate mother (p = 0.007), employed house head (p = 0.011), monthly family income more than 25,000 NRs (Nepalese Rupees) (p = 0.014), private hospital as a place of delivery (p = 0.0001), C-section as a mode of delivery (p = 0.0001), longer duration (>5days) of stay in hospital (p = 0.0001), longer distance (>15km) from house to hospital (p = 0.0001) and longer travel time (>240 minutes) from house to hospital (p = 0.007) showed a significant association with the higher hidden costs (>25000 NRs).ConclusionExperiences of hidden costs on hospital based delivery and opportunity costs of days of work loss were found high. Several socio-demographic factors, delivery related factors (place and mode of delivery, length of stay, distance from hospital and travel time) were associated with hidden costs. Hidden costs can be a critical factor for many poor and remote households who attend the hospital for delivery. Current remuneration (10-15 USD for normal delivery, 30 USD for complicated delivery and 70 USD for caesarean section delivery) for maternity incentive needs to account the hidden costs by increasing it to 250 USD for normal delivery and 350 USD for C-section. Decentralization of the obstetric care to remote and under-privileged population might reduce the economic burden of pregnant women and can facilitate their attendance at the health care centers.

Project description:Balancing the number of nursing staff in relation to the number of patients is important for hospitals to remain efficient and optimizing the use of resources. One way to do this is to work with a workload management method. Many workload management methods use a time study to determine how nurses spend their time and to relate this to patient characteristics in order to predict nurse workload.In our study, we aim to determine how nurses spend their working day and we will attempt to explain differences between specialized surgical wards.The research took place in an academic hospital in the Netherlands. Six surgical wards were included, capacity 15 to 30 beds.We have used a work sampling methodology where trained observers registered activities of nurses and patient details every ten minutes during the day shift for a time period of three weeks.The work sampling showed that nurses spend between 40.1% and 55.8% of their time on direct patient care. In addition to this, nurses spend between 11.0% and 14.1% on collective patient care. In total, between 52.1% and 68% of time spent on tasks is directly patient related. We found significant differences between wards for 10 of the 21 activity groups. We also found that nurses spend on average 31% with the patient (bedside), which is lower than in another study (37%). However, we noticed a difference between departments. For regular surgical departments in our study this was on average 34% and for two departments that have additional responsibilities in training and education of nursing students, this was on average 25%.We found a relatively low percentage of time spent on direct plus indirect care, and a lower percentage of time spent with the patient. We suspect that this is due to the academic setting of the study; in our hospital, there are more tasks related to education than in hospitals in other study settings. We also found differences between the wards in our study, which are mostly explained by differences in the patient mix, nurse staffing (proportion of nursing students), type of surgery and region of the body where the surgery was performed. However, we could not explain all differences. We made a first attempt in identifying and explaining differences in nurses' activities between wards, however this domain needs more research in order to better explain the differences.

Project description:BackgroundA maternal near-miss (MNM) refers to when a gravely ill woman survives a complication as a result of the standard of care she receives or by chance during gestation, childbirth, or within 42 days of the termination of pregnancy. Rescuers of near-miss events share several features with mothers who have died and identifying MNM determinants will aid in improving the capacity of the health system to reduce severe maternal morbidity and mortality. Ethiopia is one of the countries in sub-Saharan Africa with high maternal mortality and morbidity, but there is little evidence on determinants of a MNM based on a WHO criteria. Hence, this study aimed at identifying determinants of MNM among women admitted to tertiary hospitals in southern Ethiopia, 2020.MethodsA facilities-based unmatched case-control study was conducted in five selected tertiary hospitals found in central southern Ethiopia from February 1 to June 1, 2020. A total of 322 (81 cases and 241 controls) study participants were included in the study. At the time of their discharge, cases were recruited consecutively, while controls were selected using a systematic sampling method. The cases were women admitted to hospitals during pregnancy, childbirth, or 42 days following termination of pregnancy who met at least one of the WHO near-miss criteria. Whereas the controls comprised of women who were admitted during pregnancy, childbirth, or 42 days following termination of pregnancy and discharged without severe obstetric complications. Data collection was conducted using the interviewer-administered structured questionnaire and data abstraction tool. The data was coded and entered into Epi-Data version 3.1 and exported to SPSS version 23 for analysis. Multivariable logistic regression analysis was conducted and determinants of MNM were established at p-value<0.05.ResultsSevere postpartum hemorrhage (50.6%) and sepsis (23.4%) were the most common reasons for admission of cases. Lack of ANC [AOR = 3.25; 95%CI: 2.21,7.69], prior history of Cesarean section [AOR = 3.53; 95%CI:1.79,6.98], delaying more than 60 minute to access final place of care [AOR = 3.21; 95%CI:1.61,6.39], poor practice of Birth preparedness and complication readiness (BPCR) [AOR = 3.31; 95%CI:1.50,7.29], and history of preexisting medical disorders [AOR = 2.79; 95%CI:1.45,5.37] were identified as significantly determinants of maternal near miss.Conclusion and recommendationStakeholders need to enhance their efforts for improving access to roads and transportations. Besides, women who have a prior history of Caesarean section, chronic medical conditions, and no ANC need special attention from their families and health care providers to proactively mitigate the occurrence of serious obstetric complications. More attention has to be paid to birth preparedness and complication readiness activities.

Project description:ObjectiveTo quantify the consumption of chocolates in a hospital ward environment.DesignMulticentre, prospective, covert observational study.SettingFour wards at three hospitals (where the authors worked) within the United Kingdom.ParticipantsBoxes of Quality Street (Nestlé) and Roses (Cadbury) on the ward and anyone eating these chocolates.InterventionObservers covertly placed two 350 g boxes of Quality Street and Roses chocolates on each ward (eight boxes were used in the study containing a total of 258 individual chocolates). These boxes were kept under continuous covert surveillance, with the time recorded when each chocolate was eaten.Main outcome measureMedian survival time of a chocolate.Results191 out of 258 (74%) chocolates were observed being eaten. The mean total observation period was 254 minutes (95% confidence interval 179 to 329). The median survival time of a chocolate was 51 minutes (39 to 63). The model of chocolate consumption was non-linear, with an initial rapid rate of consumption that slowed with time. An exponential decay model best fitted these findings (model R(2)=0.844, P<0.001), with a survival half life (time taken for 50% of the chocolates to be eaten) of 99 minutes. The mean time taken to open a box of chocolates from first appearance on the ward was 12 minutes (95% confidence interval 0 to 24). Quality Street chocolates survived longer than Roses chocolates (hazard ratio for survival of Roses v Quality Street 0.70, 95% confidence interval 0.53 to 0.93, P=0.014). The highest percentages of chocolates were consumed by healthcare assistants (28%) and nurses (28%), followed by doctors (15%).ConclusionsFrom our observational study, chocolate survival in a hospital ward was relatively short, and was modelled well by an exponential decay model. Roses chocolates were preferentially consumed to Quality Street chocolates in a ward setting. Chocolates were consumed primarily by healthcare assistants and nurses, followed by doctors. Further practical studies are needed.

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Variability in costs across hospital wards. A study of Chinese hospitals.

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Variability in costs across hospital wards. A study of Chinese hospitals.

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