Predicting healthcare utilization using a pharmacy-based metric with the WHO's Anatomic Therapeutic Chemical algorithm

The influence of socio-economic status and multimorbidity patterns on healthcare costs: a six-year follow-up under a universal healthcare system

Introduction

Multimorbidity has been linked to elevated healthcare utilization and previous studies have found that socioeconomic status is an important factor associated with multimorbidity. Nonetheless, little is known regarding the impact of multimorbidity and socioeconomic status on healthcare costs and whether inequities in healthcare exist between socioeconomic classes within a universal healthcare system.

Methods

This longitudinal study employed the claims database of the National Health Insurance of Taiwan (959 990 enrolees), adopting medication-based Rx-defined morbidity groups (Rx-MG) as a measurement of multimorbidity. Mixed linear models were used to estimate the effects of multimorbidity and socioeconomic characteristics on annual healthcare costs between 2005 and 2010.

Results

The distribution of Rx-MGs and total costs presented statistically significant differences among gender, age groups, occupation, and income class (p < .001). Nearly 80% of the enrolees were classified as multimorbid and low income earners presented the highest prevalence of multimorbidity. After controlling for age and gender, increases in the number of Rx-MG assignments were associated with higher total healthcare costs. After controlling for the effects of Rx-MG assignment and demographic characteristics, physicians, paramedical personnel, and public servant were found to generate higher total costs than typical employees/self-employed enrolees, while low-income earners generated lower costs. High income levels were also found to be associated with lower total costs. It was also revealed that occupation and multimorbidity have a moderating effect on healthcare cost.

Conclusions

Increases in the prevalence of multimorbidity are associated with higher health care costs. This study determined that instances of multimorbidity varied according to socioeconomic class; likewise there were inequities in healthcare utilization among individuals of various occupations and income levels, even when demographic characteristics and multimorbidity were controlled for. This highlights the importance of socioeconomic status with regard to healthcare utilization. These results indicate that socioeconomic factors should not be discounted when discussing the utilization of healthcare by patients with multimorbidity.

Predictive risk modelling in the Spanish population: a cross-sectional study

BACKGROUND

An increase in chronic conditions is currently the greatest threat to human health and to the sustainability of health systems. Risk adjustment systems may enable population stratification programmes to be developed and become instrumental in implementing new models of care.The objectives of this study are to evaluate the capability of ACG-PM, DCG-HCC and CRG-based models to predict healthcare costs and identify patients that will be high consumers and to analyse changes to predictive capacity when socio-economic variables are added.

METHODS

This cross-sectional study used data of all Basque Country citizens over 14 years of age (n = 1,964,337) collected in a period of 2 years. Data from the first 12 months (age, sex, area deprivation index, diagnoses, procedures, prescriptions and previous cost) were used to construct the explanatory variables. The ability of models to predict healthcare costs in the following 12 months was assessed using the coefficient of determination and to identify the patients with highest costs by means of receiver operating characteristic (ROC) curve analysis.

RESULTS

The coefficients of determination ranged from 0.18 to 0.21 for diagnosis-based models, 0.17-0.18 for prescription-based and 0.21-0.24 for the combination of both. The observed area under the ROC curve was 0.78-0.86 (identifying patients with a cost higher than P-95) and 0.83-0.90 (P-99). The values of the DCG-HCC models are slightly higher and those of the CRG models are lower, although prescription information could not be used in the latter. On adding previous cost data, differences between the three systems decrease appreciably. Inclusion of the deprivation index led to only marginal improvements in explanatory power.

CONCLUSION

The case-mix systems developed in the USA can be useful in a publicly financed healthcare system with universal coverage to identify people at risk of high health resource consumption and whose situation is potentially preventable through proactive interventions.

Improved prediction of medical expenditures and health care utilization using an updated chronic disease score and claims data

OBJECTIVE

To predict future medical expenditures, health care utilization, and mortality in Switzerland using an updated chronic disease score (CDS), a chronic morbidity measure based on pharmacy data.

STUDY DESIGN AND SETTING

We performed a cohort study using medical claims data from insured persons enrolled in 2009 and 2010. Patient's characteristics, chronic conditions, and health care costs from baseline were used to calculate each patient's disease score. Two-part regression models were fit to predict health care expenditures, utilization, and mortality during the following year using the score's baseline values. We calculated the proportion of explained variation for each regression model to assess their performance.

RESULTS

The CDS model, controlled for sociodemographics and health insurance plan, showed a significant improvement in explained variance of health care costs, outpatient costs, and outpatient visits in 2010. Future outpatient visits were predicted best with an R(2) of 29.2% (age group: 18-65 years) and 22.9% (>65 years), and models predicted future mortality with a c-statistic of 0.8.

CONCLUSION

The CDS showed reasonable predictive validity of future health care utilization and medical expenditure based on pharmacy dispensing data, which may support health care decision makers in the planning delivery systems and resource allocation.

The poorer cancer survival among the unmarried in Norway: is much explained by comorbidities?

Studies from Norway and other countries have shown that the unmarried have poorer cancer survival than the married, given age, tumor site and stage at diagnosis. The objective of this investigation was to assess the importance of comorbidities for this difference, using disease indicators derived from the Norwegian Prescription Database (NorPD) and information on cancer and sociodemographic characteristics from various other registers, all of which cover the entire Norwegian population. Discrete-time hazard models for cancer mortality up to 2007 were estimated for all 22,925 men and 21,694 women diagnosed with 13 common types of cancer in 2005-7. There were 4898 cancer deaths among men and 4187 among women. Controlling for sociodemographic factors and tumor characteristics, the odds of dying from cancer among never-married men relative to the married was 1.56 (CI 1.41-1.74). The corresponding estimates for widowed and divorced were 1.16 (CI 1.05-1.28) and 1.27 (CI 1.15-1.40). For women, the odds ratios for these three groups were 1.47 (CI 1.29-1.67), 1.10 (CI 1.01-1.20) and 1.14 (CI 1.02-1.27). Several of the 24 indicators of diseases in the year before diagnosis were associated with cancer survival, but their inclusion reduced the excess mortality of the unmarried by only 1-5 percentage points, or about 10% as an overall relative figure. Similar results were found when the four most common cancers were analyzed separately, though there were some differences between them in the role played by the comorbidities. It is possible that important comorbidities are inadequately captured by the included indicators, and perhaps especially for the unmarried. Such concerns aside, the results suggest that the marital status differences in cancer survival to little extent are due to comorbidities (and the few disease risk factors that are also captured), but rather to various other "host factors" or to treatment or care.

Comorbidity in patients with branch retinal vein occlusion: case-control study

OBJECTIVES

To evaluate comorbidity before and after the diagnosis of branch retinal vein occlusion to determine whether it is a consequence of arterial thickening and therefore could serve as a diagnostic marker for other comorbidities and to evaluate the risk factors for the development of such occlusion.

DESIGN

Case-control study with prospective follow-up data from Danish national registries.

SETTING

Four secondary referral centres covering about 80% of the Danish population (4.4 million).

PARTICIPANTS

1168 patients with photographically verified branch retinal vein occlusion and 116,800 controls alive and aged ≥ 40 when the occlusion was diagnosed in the corresponding case.

MAIN OUTCOME MEASURES

The risk of comorbidity 10 years and 1 year before the diagnosis of branch retinal vein occlusion and the incident comorbidity in a mean period of seven years after the diagnosis, with odds ratios and incidence rate ratios adjusted for age, sex, and year of diagnosis.

RESULTS

Risk factors present 10 years and 1 year before the diagnosis of branch retinal vein occlusion included peripheral artery disease (odds ratio 1.83, 95% confidence interval 1.14 to 2.95), diabetes (1.74, 1.40 to 2.17) and arterial hypertension (2.16, 1.86 to 2.51). After the diagnosis, patients had an increased risk of developing arterial hypertension (incidence rate ratio 1.37, 95% confidence interval 1.15 to 1.57), diabetes (1.51, 1.17 to 2.04), congestive heart failure (1.41, 1.12 to 1.68), and cerebrovascular disease (1.49, 1.27 to 1.76).

CONCLUSION

Diabetes, hypertension, and peripheral artery disease are associated with an increased risk of developing branch retinal vein occlusion up to a decade later. Branch retinal vein occlusion was associated with an increased risk of subsequently developing hypertension, diabetes, congestive heart failure, and cerebrovascular disease, emphasising the importance of preventive initiatives. These results fit the assumption that branch retinal vein occlusion is a consequence of arterial thickening and that the arteriovenous crossing signs that precede it are hallmarks of arterial disease.