Dataset Information

Accounting for the relationship between per diem cost and LOS when estimating hospitalization costs.

ABSTRACT:

Background

Hospitalization costs in clinical trials are typically derived by multiplying the length of stay (LOS) by an average per-diem (PD) cost from external sources. This assumes that PD costs are independent of LOS. Resource utilization in early days of the stay is usually more intense, however, and thus, the PD cost for a short hospitalization may be higher than for longer stays. The shape of this relationship is unlikely to be linear, as PD costs would be expected to gradually plateau. This paper describes how to model the relationship between PD cost and LOS using flexible statistical modelling techniques.

Methods

An example based on a clinical study of clevidipine for the treatment of peri-operative hypertension during hospitalizations for cardiac surgery is used to illustrate how inferences about cost-savings associated with good blood pressure (BP) control during the stay can be affected by the approach used to derive hospitalization costs.Data on the cost and LOS of hospitalizations for coronary artery bypass grafting (CABG) from the Massachusetts Acute Hospital Case Mix Database (the MA Case Mix Database) were analyzed to link LOS to PD cost, factoring in complications that may have occurred during the hospitalization or post-discharge. The shape of the relationship between LOS and PD costs in the MA Case Mix was explored graphically in a regression framework. A series of statistical models including those based on simple logarithmic transformation of LOS to more flexible models using LOcally wEighted Scatterplot Smoothing (LOESS) techniques were considered. A final model was selected, using simplicity and parsimony as guiding principles in addition traditional fit statistics (like Akaike's Information Criterion, or AIC). This mapping was applied in ECLIPSE to predict an LOS-specific PD cost, and then a total cost of hospitalization. These were then compared for patients who had good vs. poor peri-operative blood-pressure control.

Results

The MA Case Mix dataset included data from over 10,000 patients. Visual inspection of PD vs. LOS revealed a non-linear relationship. A logarithmic model and a series of LOESS and piecewise-linear models with varying connection points were tested. The logarithmic model was ultimately favoured for its fit and simplicity. Using this mapping in the ECLIPSE trials, we found that good peri-operative BP control was associated with a cost savings of $5,366 when costs were derived using the mapping, compared with savings of $7,666 obtained using the traditional approach of calculating the cost.

Conclusions

PD costs vary systematically with LOS, with short stays being associated with high PD costs that drop gradually and level off. The shape of the relationship may differ in other settings. It is important to assess this and model the observed pattern, as this may have an impact on conclusions based on derived hospitalization costs.

SUBMITTER: Ishak KJ

PROVIDER: S-EPMC3522016 | biostudies-literature | 2012 Dec

REPOSITORIES: biostudies-literature

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Publications

Accounting for the relationship between per diem cost and LOS when estimating hospitalization costs.

Ishak K Jack KJ Stolar Marilyn M Hu Ming-yi MY Alvarez Piedad P Wang Yamei Y Getsios Denis D Williams Gregory C GC

BMC health services research 20121201

<h4>Background</h4>Hospitalization costs in clinical trials are typically derived by multiplying the length of stay (LOS) by an average per-diem (PD) cost from external sources. This assumes that PD costs are independent of LOS. Resource utilization in early days of the stay is usually more intense, however, and thus, the PD cost for a short hospitalization may be higher than for longer stays. The shape of this relationship is unlikely to be linear, as PD costs would be expected to gradually pla ...[more]

PMID: 23198908

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Project description:BackgroundMalaria causes significant mortality and morbidity in sub-Saharan Africa, especially among children under five years of age and places a huge economic burden on individuals and health systems. While this burden has been assessed previously, few studies have explored how malaria comorbidities affect inpatient costs. This study in a malaria endemic area in Western Kenya, assessed the total treatment costs per malaria episode including comorbidities in children and adults.MethodsTotal economic costs of malaria hospitalizations were calculated from a health system and societal perspective. Patient-level data were collected from patients admitted with a malaria diagnosis to a county-level hospital between June 2016 and May 2017. All treatment documented in medical records were included as health system costs. Patient and household costs included direct medical and non-medical expenses, and indirect costs due to productivity losses.ResultsOf the 746 patients admitted with a malaria diagnosis, 64% were female and 36% were male. The mean age was 14 years (median 7 years). The mean length of stay was three days. The mean health system cost per patient was Kenyan Shilling (KSh) 4288 (USD 42.0) (95% confidence interval (CI) 95% CI KSh 4046-4531). The total household cost per patient was KSh 1676 (USD 16.4) (95% CI KSh 1488-1864) and consisted of: KSh 161 (USD1.6) medical costs; KSh 728 (USD 7.1) non-medical costs; and KSh 787 (USD 7.7) indirect costs. The total societal cost (health system and household costs) per patient was KSh 5964 (USD 58.4) (95% CI KSh 5534-6394). Almost a quarter of patients (24%) had a reported comorbidity. The most common malaria comorbidities were chest infections, diarrhoea, and anaemia. The inclusion of comorbidities compared to patients with-out comorbidities led to a 46% increase in societal costs (health system costs increased by 43% and patient and household costs increased by 54%).ConclusionsThe economic burden of malaria is increased by comorbidities which are associated with longer hospital stays and higher medical costs to patients and the health system. Understanding the full economic burden of malaria is critical if future malaria control interventions are to protect access to care, especially by the poor.

Project description:BackgroundThe potential economic benefit in terms of reduced healthcare costs when patients quit smoking after hospital discharge has not been directly measured. The aim of this study was to compare the costs for hospital admission and six-month follow-up for a cohort of patients who self-reported abstinence from cigarettes at 6 months after hospital discharge and a matched group of patients who reported continued smoking.Materials and methodsThis was a secondary analysis of a recent population-based clinical trial cohort (ClinicalTrials.gov ID: NCT01575145), with cohort membership determined by self-reported 7 day point prevalence abstinence at 6 months after the index hospital discharge. Participants were admitted to Mayo Clinic Hospital, Rochester, MN, between May 5, 2012 and August 10, 2014 for any indication and lived in the areas covered by postal codes included in Olmsted County, MN. Propensity score matching was used to control for differences between groups other than smoking status, and any residual imbalance was adjusted through generalized linear model with gamma distribution for cost and log-link transformation.ResultsOf 600 patients enrolled in the clinical trial, 144 could be contacted and self-reported 7 day point prevalence abstinence at 6 months after hospital discharge. Of these patients, 99 were successfully matched for this analysis. The cost for the index hospitalization was significantly greater in patients who abstained compared to those that did not abstain (mean difference of $3042, higher for abstainers, 95% CI $170 to $5913, P = 0.038). However, there was no difference between mean 6-month follow-up costs, number of inpatient hospitalizations, or number of emergency room visits for abstainers versus non-abstainers.ConclusionThere was no evidence to support the hypothesis that abstinence at 6 months after hospital discharge is associated with a decrease in health care costs or utilization over the first 6 months after hospital discharge.

Dataset Information

Accounting for the relationship between per diem cost and LOS when estimating hospitalization costs.

Background

Methods

Results

Conclusions

Publications

Accounting for the relationship between per diem cost and LOS when estimating hospitalization costs.

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