Analysis of hospital costs by morbidity group for patients with severe mental illness.

OBJECTIVES: The goal of this study is to analyse hospital costs and length of stay of patients admitted to psychiatric units in hospitals in a European region of the Mediterranean Arc. The aim is to identify the effects of comorbidities and other variables in order to create an explanatory cost model. METHODS: In order to carry out the study, the Ministry of Health was asked to provide data on access to the mental health facilities of all hospitals in the region. Among other questions, this database identifies the most important diagnostic variables related to admission, like comorbidities, age and gender. The method used, based on the Manning-Mullahy algorithm, was linear regression. The results were measured by the statistical significance of the independent variables to determine which of them were valid to explain the cost of hospitalization. RESULTS: Psychiatric inpatients can be divided into three main groups (psychotic, organic and neurotic), which have statistically significant differences in costs. The independent variables that were statistically significant (p <.05) and their respective beta and confidence intervals were: psychotic group (19,833.0 ± 317.3), organic group (9,878.4 ± 276.6), neurotic group (11,060.1 ± 287.6), circulatory system diseases (19,170 ± 517.6), injuries and poisoning (21,101.6 ± 738.7), substance abuse (20,580.6 ± 514, 6) and readmission (19,150.9 ± 555.4). CONCLUSIONS: Unlike most health services, access to psychiatric facilities does not correlate with comorbidities due to the specific nature of this specialization. Patients admitted to psychosis had higher costs and a higher number of average staysKEY MESSAGESThe highest average hospital expenditure occurred in patients admitted for psychotic disorders.Due to the particularities of psychiatry units and unlike other medical specialties, the number of comorbidities did not influence the number of hospital stays or hospital expenditure.Apart from the main diagnostic group, the variables that were useful to explain hospital expenditure were the presence of poisoning and injuries as comorbidity, diseases of circulatory system as comorbidity, history of substance abuse and readmission.

Predicting healthcare expenditure by multimorbidity groups.

OBJECTIVES: This article has two main purposes. Firstly, to model the integrated healthcare expenditure for the entire population of a health district in Spain, according to multimorbidity, using Clinical Risk Groups (CRG). Secondly, to show how the predictive model is applied to the allocation of health budgets. METHODS: The database used contains the information of 156,811 inhabitants in a Valencian Community health district in 2013. The variables were: age, sex, CRG's main health statuses, severity level, and healthcare expenditure. The two-part models were used for predicting healthcare expenditure. From the coefficients of the selected model, the relative weights of each group were calculated to set a case-mix in each health district. RESULTS: Models based on multimorbidity-related variables better explained integrated healthcare expenditure. In the first part of the two-part models, a logit model was used, while the positive costs were modelled with a log-linear OLS regression. An adjusted R2 of 46-49% between actual and predicted values was obtained. With the weights obtained by CRG, the differences found with the case-mix of each health district proved most useful for budgetary purposes. CONCLUSIONS: The expenditure models allowed improved budget allocations between health districts by taking into account morbidity, as opposed to budgeting based solely on population size.

Pharmaceutical cost and multimorbidity with type 2 diabetes mellitus using electronic health record data.

BACKGROUND: The objective of the study is to estimate the frequency of multimorbidity in type 2 diabetes patients classified by health statuses in a European region and to determine the impact on pharmaceutical expenditure. METHODS: Cross-sectional study of the inhabitants of a southeastern European region with a population of 5,150,054, using data extracted from Electronic Health Records for 2012. 491,854 diabetic individuals were identified and selected through clinical codes, Clinical Risk Groups and diabetes treatment and/or blood glucose reagent strips. Patients with type 1 diabetes and gestational diabetes were excluded. All measurements were obtained at individual level. The prevalence of common chronic diseases and co-occurrence of diseases was established using factorial analysis. RESULTS: The estimated prevalence of diabetes was 9.6 %, with nearly 70 % of diabetic patients suffering from more than two comorbidities. The most frequent of these was hypertension, which for the groups of patients in Clinical Risk Groups (CRG) 6 and 7 was 84.3 % and 97.1 % respectively. Regarding age, elderly patients have more probability of suffering complications than younger people. Moreover, women suffer complications more frequently than men, except for retinopathy, which is more common in males. The highest use of insulins, oral antidiabetics (OAD) and combinations was found in diabetic patients who also suffered cardiovascular disease and neoplasms. The average cost for insulin was 153€ and that of OADs 306€. Regarding total pharmaceutical cost, the greatest consumers were patients with comorbidities of respiratory illness and neoplasms, with respective average costs of 2,034.2€ and 1,886.9€. CONCLUSIONS: Diabetes is characterized by the co-occurrence of other diseases, which has implications for disease management and leads to a considerable increase in consumption of medicines for this pathology and, as such, pharmaceutical expenditure.

[Impact of Morbidity on Health Care Costs of a Department of Health through Clinical Risk Groups. Valencian Community, Spain]. / Impacto de la morbilidad en los costes asistenciales de un Departamento de Salud de la Comunidad Valenciana a través de estudio de Grupos Clínicos de Riesgo.

BACKGROUND: Risk adjustment systems based on diagnosis stratify the population according to the observed morbidity. The aim of this study was to analyze the total health expenditure in a health area, relating to age, gender and morbidity observed in the population. METHODS: Observational cross-sectional study of population and area of health care costs in the Health District of Denia-Marina Salud (Alicante) in 2013. Population (N=156,811) were stratified by Clinical Risk Groups into 9 states of health, state 1 being healthy, and state 9 the highest disease burden. Each inhabitant was charged with the hospital costs, primary care and outpatient pharmacy to obtain the total costs. Health status and severity by age and gender, as well as the costs of each group were analysed. The statistical tests, student t and χ2 were applied to verify the existence of significant differences between and intra groups. RESULTS: The average cost per inhabitant was 983 euros which increased from 240 euros to 42,881 at the state 9 and severity level 6. Patients of health states 5 and 6 caused the largest expenditure by concentration of the population, but health states 8 and 9 had the highest average expenditure, with 80% of hospitalised cost. CONCLUSIONS: A different composition of health expenditure per individual morbidity was corroborated, with an exponential growth in hospital spending.

OBJETIVO: Los sistemas de ajuste de riesgo basados en diagnóstico estratifican la población según la morbilidad observada. El objetivo de este trabajo fue analizar el gasto sanitario total en un área de salud en función de la edad, el sexo y la morbilidad observada en la población. METODOS: Estudio observacional de corte transversal y de ámbito poblacional de los costes de atención sanitaria en el Departamento de salud Dénia-Marina Salud (Alicante) durante el año 2013. Se estratificó a la población (N=156.811) según Grupos de Riesgo Clínico en 9 estados de salud, siendo sano el estado 1 y el 9 el de mayor carga de morbilidad. A cada habitante se le imputaron los costes hospitalarios, de atención primaria y de farmacia ambulatoria para obtener los costes totales. Se analizaron los estados de salud y gravedad por edad y sexo así como los costes de cada grupo. Se aplicaron las pruebas estadísticas t de student y χ2 para verificar la existencia de diferencias significativas entre e intra grupos. RESULTADOS: El coste medio por habitante fue de 983 euros oscilando desde 240 hasta 42.881 en el estado 9 y nivel de gravedad 6. Los pacientes de los estados de salud 5 y 6 realizaron el mayor gasto, pero los estados de salud 8 y 9 tuvieron el mayor gasto medio, siendo el 80% hospitalario. CONCLUSIONES: Se corrobora una diferente composición del gasto sanitario por morbilidad individual, con un crecimiento exponencial del gasto hospitalario.

Gasto farmacéutico en diabetes mellitus en una región de España según el Clinical Risk Group, 2012 / Pharmaceutical Expenditure for Diabetes Mellitus in a Region of Spain as Clinical Risk Group, 2012 / Despesa com medicamentos em pacientes com diabetes mellitus em uma região da Espanha como o Grupo de Risco Clínico de 2012

Se pretende estimar la multimorbilidad asociada con diabetes mellitus tipo 2 y su relación con el gasto farmacéutico, para lo cual se realizó un estudio de corte transversal durante el año 2012. Se identificó a 350 015 individuos diabéticos, a través de códigos clínicos, usando la Clasificación Internacional de Enfermedades y el software 3M Clinical Risk Groups. Todos los pacientes fueron clasificados en cuatro grupos de morbilidad. El primer grupo corresponde al estadio inicial, el segundo grupo incluye el núcleo de multimorbilidad de pacientes en fases intermedia y avanzada, el tercer grupo incluye pacientes con diabetes y enfermedades malignas, y el último grupo es de pacientes en estado catastrófico, principalmente enfermos renales crónicos. La prevalencia bruta de diabetes fue de 6,7%. El gasto promedio total fue de ¬ 1257,1. La diabetes se caracteriza por una fuerte presencia de otras condiciones crónicas y tiene un gran impacto en el gasto farmacéutico.

Estimations of multimorbidity associated with Type 2 Diabetes Mellitus and its relationship to pharmaceutical expenditure. Cross-sectional study during 2012. 350,015 diabetic individuals, identified through clinical codes using the International Statistical Classification of Diseases and Related Health Problem and the 3M Clinical Risk Groups software. The raw prevalence of diabetes was 6.7%. All patients were stratified into four morbidity groups. The first group corresponds to the initial state; the second group includes the core multimorbidity patients in the intermediate and advanced stages; the third group includes patients with diabetes and malignancies; the last group patients with catastrophic statuses, manly chronic renal patients. The raw prevalence of diabetes was 6.7%. The average total cost was ¬ 1257.1. Diabetes is characterized by a strong presence of other chronic conditions have a great impact on pharmaceutical spending.

As estimativas de vários morbidade associada com diabetes mellitus tipo 2 e sua relação com a despesa farmacêutica, para o qual um estudo transversal foi realizado em 2012. Ele foi identificado em 350 015 indivíduos diabéticos, foram identificados através códigos clínicos, utilizando a Classificação Internacional de Doenças e Risco clínica software Grupos 3M. Todos os pacientes foram classificados em quatro grupos de doença 4. O primeiro grupo corresponde à fase inicial (CRG 1-4); O segundo grupo inclui pacientes multimorbid principais fases intermediárias e avançadas, o terceiro grupo inclui pacientes com diabetes e doenças malignas, eo último grupo de pacientes em estado catastrófico, pacientes renais crónicos, principalmente. A prevalência global de diabetes foi de 6,7%. A despesa média total foi de ¬ 1257,1. Diabetes que se caracteriza por uma forte presença de outras condições crónicas e tieniendo um grande impacto sobre os gastos farmacêutica.

Impacto de la morbilidad en los costes asistenciales de un departamento de salud de la Comunidad Valenciana a través de los grupo de riesgo clínico / Impact of morbidity on health care costs of a department of health through clinic

Fundamentos: Los sistemas de ajuste de riesgo basados en diagnóstico estratifican la población según la morbilidad observada. El objetivo de este trabajo fue analizar el gasto sanitario total en un área de salud en función de la edad, el sexo y la morbilidad observada en la población. Métodos: Estudio observacional de corte transversal y de ámbito poblacional de los costes de atención sanitaria en el Departamento de salud Dénia-Marina Salud (Alicante) durante el año 2013. Se estratificó a la población (N=156.811) según Grupos de Riesgo Clínico en 9 estados de salud, siendo sano el estado 1 y el 9 el de mayor carga de morbilidad. A cada habitante se le imputaron los costes hospitalarios, de atención primaria y de farmacia ambulatoria para obtener los costes totales. Se analizaron los estados de salud y gravedad por edad y sexo así como los costes de cada grupo. Se aplicaron las pruebas estadísticas t de student y χ2 para verificar la existencia de diferencias significativas entre e intra grupos. Resultados: El coste medio por habitante fue de 983 euros oscilando desde 240 hasta 42.881 en el estado 9 y nivel de gravedad 6. Los pacientes de los estados de salud 5 y 6 realizaron el mayor gasto, pero los estados de salud 8 y 9 tuvieron el mayor gasto medio, siendo el 80% hospitalario. Conclusiones: Se corrobora una diferente composición del gasto sanitario por morbilidad individual, con un crecimiento exponencial del gasto hospitalario (AU)

Background: Risk adjustment systems based on diagnosis stratify the population according to the observed morbidity. The aim of this study was to analyze the total health expenditure in a health area, relating to age, gender and morbidity observed in the population. Methods: Observational cross-sectional study of population and area of health care costs in the Health District of Denia-Marina Salud (Alicante) in 2013. Population (N=156,811) were stratified by Clinical Risk Groups into 9 states of health, state 1 being healthy, and state 9 the highest disease burden. Each inhabitant was charged with the hospital costs, primary care and outpatient pharmacy to obtain the total costs. Health status and severity by age and gender, as well as the costs of each group were analysed. The statistical tests, student t and χ2 were applied to verify the existence of significant differences between and intra groups. Results: The average cost per inhabitant was 983 euros which increased from 240 euros to 42,881 at the state 9 and severity level 6. Patients of health states 5 and 6 caused the largest expenditure by concentration of the population, but health states 8 and 9 had the highest average expenditure, with 80% of hospitalised cost. Conclusions: A different composition of health expenditure per individual morbidity was corroborated, with an exponential growth in hospital spending (AU)