Mean cost and cost-effectiveness ratios with censored data: a tutorial and SAS® macros

Because of the skewness of the distribution of medical costs, we consider modeling the median as well as other quantiles when establishing regression relationships to covariates. In many applications, the medical cost data are also right censored. In this article, we propose semiparametric procedures for estimating the parameters in median regression models based on weighted estimating equations when censoring is present. Numerical studies are conducted to show that our estimators perform well with small samples and the resulting inference is reliable in circumstances of practical importance. The methods are applied to a dataset for medical costs of patients with colorectal cancer.

Non-negative continuous outcomes with a substantial number of zero values and incomplete longitudinal follow-up are quite common in medical costs data. It is thus critical to incorporate the potential dependence of survival status and longitudinal medical costs in joint modeling, where censorship is death-related. Despite the wide use of conventional two-part joint models (CTJMs) to capture zero-inflation, they are limited to conditional interpretations of the regression coefficients in the model’s continuous part. In this paper, we propose a marginalized two-part joint model (MTJM) to jointly analyze semi-continuous longitudinal costs data and survival data. We compare it to the conventional two-part joint model (CTJM) for handling marginal inferences about covariate effects on average costs. We conducted a series of simulation studies to evaluate the superior performance of the proposed MTJM over the CTJM. To illustrate the applicability of the MTJM, we applied the model to a set of real electronic health record (EHR) data recently collected in Iran. We found that the MTJM yielded a smaller standard error, root-mean-square error of estimates, and AIC value, with unbiased parameter estimates. With this MTJM, we identified a significant positive correlation between costs and survival, which was consistent with the simulation results.

Medical economics and the assessment of value in cardiovascular medicine: Part I.

A flexible two-part random effects model for correlated medical costs

To compare clinical, health-related quality of life (HRQL), and medical cost outcomes in patients with symptomatic gastroesophageal reflux disease (GERD) receiving omeprazole sodium or ranitidine hydrochloride treatment. A multicenter, randomized, open-label, medical effectiveness trial conducted in 5 university-based family medicine clinics. Two hundred sixty-eight patients with GERD were recruited and randomly assigned to omeprazole sodium, 20 mg once daily, or ranitidine hydrochloride, 150 mg twice daily, for up to 6 months. Main outcome assessments included the Gastrointestinal Symptom Rating Scale (GSRS) Reflux score, Psychological General Well-Being Index, and Short-Form-36 Health Survey administered at baseline and 2, 4, 12, and 24 weeks. Medical resource use and cost data were collected. More omeprazole-treated patients reported improved heartburn resolution at 2 weeks (49.0% vs 33.3%; P=.007) and 4 weeks (58.6% vs 35.0%; P<.001) compared with ranitidine-treated patients. The GSRS Reflux scores across 3 months showed overall differences between omeprazole (mean, 2.67) and ranitidine (mean, 2.95) groups (P=.04). Mean total 6-month medical costs were $915 lower ($8371 vs $9286; P=.64), and no difference in mean outpatient medical costs ($1198 vs $1158; P=.76) were observed in the omeprazole group compared with the ranitidine group. A post hoc secondary analysis showed that, at 12 and 24 weeks, patients treated with omeprazole for 8 weeks or more reported greater heartburn resolution (ie, 24 [43%] of 56 patients at both intervals) than patients treated with ranitidine for 8 weeks or more (12 [24%] and 13 [26%] of 50 patients, respectively; P=.001). Ranitidine and omeprazole were both effective at improving heartburn symptoms; however, omeprazole provided greater resolution of heartburn symptoms at 2 and 4 weeks. Despite omeprazole's higher acquisition cost, there were no significant differences in total or outpatient costs between groups.

Analyses of Cost Data in Economic Evaluations Conducted Alongside Randomized Controlled Trials

Medical costs data with administratively censored observations often arise in cost-effectiveness studies of treatments for life-threatening diseases. Mean of medical costs incurred from the start of a treatment until death or a certain time point after the implementation of treatment is frequently of interest. In many situations, due to the skewed nature of the cost distribution and non-uniform rate of cost accumulation over time, the currently available normal approximation confidence interval has poor coverage accuracy. In this paper, we propose a bootstrap confidence interval for the mean of medical costs with censored observations. In simulation studies, we show that the proposed bootstrap confidence interval had much better coverage accuracy than the normal approximation one when medical costs had a skewed distribution. When there is light censoring on medical costs (< or =25 per cent), we found that the bootstrap confidence interval based on the simple weighted estimator is preferred due to its simplicity and good coverage accuracy. For heavily censored cost data (censoring rate > or =30 per cent) with larger sample sizes (n > or =200), the bootstrap confidence intervals based on the partitioned estimator has superior performance in terms of both efficiency and coverage accuracy. We also illustrate the use of our methods in a real example.

Stroke occurs concurrently with myocardial infarction (MI) in approximately 30 000 US patients each year. This number is expected to rise with the increasing use of thrombolytic therapy for MI. However, no data exist for the economic effect of stroke in the setting of acute MI (AMI). The purpose of this prospective study was to assess the effect of stroke on medical resource use and costs in AMI patients in the United States. Medical resource use and cost data were prospectively collected for 2566 randomly selected US GUSTO I patients (from 23 105 patients) and for the 321 US GUSTO I patients who developed non-bypass surgery-related stroke during the baseline hospitalization. Follow-up was for 1 year. All costs are expressed in 1993 US dollars. During the baseline hospitalization, stroke was associated with a reduction in cardiac procedure rates and an increase in length of stay, despite a hospital mortality rate of 37%. Together with stroke-related procedural costs of $2220 per patient, the baseline medical costs increased by 44% ($29 242 versus $20 301, P<0.0001). Follow-up medical costs were substantially higher for stroke survivors ($22 400 versus $5282, P<0.0001), dominated by the cost of institutional care. The main determinant for institutional care was discharge disability status. The cumulative 1-year medical costs for stroke patients were $15 092 higher than for no-stroke patients. Hemorrhagic stroke patients had a much higher hospital mortality rate than non-hemorrhagic stroke patients (53% versus 15%, P<0.001), which was associated with approximately $7200 lower mean baseline hospitalization cost. At discharge, hemorrhagic stroke patients were more likely to be disabled (68% versus 46%, P=0.002). In this first large prospective economic study of stroke in AMI patients, we found that strokes were associated with a 60% ($15 092) increase in cumulative 1-year medical costs. Baseline hospitalization costs were 44% higher because of longer mean lengths of stay. Stroke type was a key determinant of baseline cost. Follow-up costs were more than quadrupled for stroke survivors because of the need for institutional care. Disability level was the main determinant of institutional care and thus of follow-up costs.

Rotavirus is a major cause of gastroenteritis in children throughout Europe and the world. In addition to causing morbidity and mortality in children, rotavirus gastroenteritis (RVGE) creates a major economic burden on health care systems and families in Europe. The costs of hospital admissions for RVGE and nosocomial infections generate significant medical treatment costs throughout the region. Less information is available on the costs associated with less severe episodes and the costs borne by families, including lost time from work. The availability of rotavirus vaccines presents an effective opportunity to prevent RVGE and these associated economic costs, as well as providing protection to each child and hence benefiting the child's family. The adoption of rotavirus vaccine by health authorities in Europe will require a comparison of the costs and benefits. Economic evaluations that compare the costs of vaccination to the economic benefits of rotavirus vaccination will provide an estimate of its financial impact on health care systems and society. However, to provide a complete picture, economic evaluations of rotavirus vaccines will need to account for both the reduced costs and the reduced morbidity from prevented RVGE. Cost-effectiveness analyses based on quality-adjusted life years (QALYs) provide a systematic approach for assessing vaccination as a health investment, comparing the incremental costs associated with rotavirus vaccination and the reduced morbidity and mortality. QALYs provide a standardized approach for quantifying and comparing reductions in health-related quality of life and premature mortality. Although methodologic limitations exist in applying the QALY approach to childhood vaccines, their use in cost effectiveness analyses allows decision makers to consider the full health benefits of rotavirus and other vaccines.

Hospital use and medical care costs up to 5 years after triglyceride lowering among patients with severe hypertriglyceridemia

Epilepsy is a condition of the onset of attacks in the form of abnormal, irregular brain nerve cell movements, occurring repeatedly and causing temporary motor, sensory or mental function disorders. The treatment of epilepsy has costs that must be known, including direct medical costs, indirect medical costs, and indirect costs; this study aims to determine the cost of illness of epilepsy in one hospital in banyuasin regency with retrospective costing in outpatients. The research method used in this study is a cross-sectional study using patient medical record data and cost data taken from BPJS claims data and hospital rate patterns. This study uses the BPJS perspective and societal perspective, the cost data taken from the BPJS perspective is the result of BPJS claims according to the INACBGs. Package tariff and for the socital perspective the data taken is doctor consultation data, administrative costs, laboratory costs, drug costs and transportation costs and lost productivity costs carried out by interview method for 12 months. The results of this study indicate that the cost of epilepsy outpatients from a societal perspective is Rp.3,141,414 and for BPJS perspective is Rp.2,338,567.

Joint latent class model of survival and longitudinal data: An application to CPCRA study

In medical follow-up studies, longitudinal data and survival data are often accompanied and associated with each other, thus respective analysis of longitudinal and survival data might lead to biased results. Joint model can correct deviations, improve the efficiency of parameter estimation and provide effective inferences by simultaneously processing longitudinal and survival data. It is a popular method in medical research. Joint model has made much progress, whereas the literature about the joint model and its application is limited in China. This paper summarizes the main idea, basic framework, parameter estimation methods of random effect joint model and introduces the analysis on AIDS data set based on the R software package 'JM' to clarify the advantages of the joint model in processing medical follow-up data and promote the use of the joint model in clinical research.

Cost-Effectiveness of a Nonpharmacological Intervention in Pediatric Burn Care

Biomedical studies may collect longitudinal and survival data in follow-up studies. In randomised controlled trials for malaria treatment, longitudinal parasite count and hemoglobin level and survival outcomes, time to fever resolution or time to parasite clearance, are recorded. The longitudinal and survival data are analysed separately, yet longitudinal outcomes may be important predictors in the survival process. Standard survival analysis methods cannot handle such longitudinal outcomes. In such studies, survival competing risks are possible; thus analysis should consider survival, longitudinal and competing risks. In joint modelling, options for modelling dependence are a key issue as well as choice of random effects distribution. The example used in this work was from sub-Saharan Africa.Joint modelling framework, mixed-effects models and Cox-specific models for analysis of longitudinal and survival data were applied to malaria dataset from Malawi Liverpool Wellcome Trust. Longitudinal outcomes considered were hemoglobin level and parasite count, while survival outcomes were time to treatment failure due to severe malaria and time to withdrawal (due to adverse effects and protocol violation).Different survival outcomes observed were severe malaria (4.95%) and withdrawal (10.89%). The longitudinal outcomes were not associated with the risks of severe malaria and withdrawal in the Cox model. The true hemoglobin level and age were associated with the risk of withdrawal (p = 0.0111) and (p = 0.0305), respectively, in the joint model, and the separate models were opted to fit the data.When an association between longitudinal and survival outcomes is of interest, joint models can be considered over separate methods. However, where there is no association, separate models for survival and longitudinal data analysis can be used.KeywordsSurvival modelsLongitudinal dataCompeting risksJoint modelsSevere malariaRandomised controlled trialsEfficacyCox-specific modelHemoglobin levelParasite countWithdrawalMixed-effectsTimeBiomedical studyEventCensoringParameterRandom effectsEstimationBICProfileCovariatesFollow-upRelative riskTreatmentPackageErrorFrameworkDataResearchPredictingAssociationPatients