BackgroundThe 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.MethodsCross-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.ResultsThe 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€.ConclusionsDiabetes 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.

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. MethodsThe 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 or 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. ResultsModels 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 R 2 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. ConclusionsThe expenditure models allowed improved budget allocations between health districts by taking into account morbidity, as opposed to budgeting based solely on population size.

In Spain, the COVID-19 pandemic has impacted the various regions of the country differently. The availability of reliable and up-to-date information has proved to be fundamental for the management of this health crisis. However, especially during the first wave of the pandemic (February–August 2020), the disparity in the recording criteria and in the timing of providing these figures to the central government created controversy and confusion regarding the real dimension of the pandemic. It is therefore necessary to have objective and homogeneous criteria at the national level to guide health managers in the correct recording and evaluation of the magnitude of the pandemic. Within this context, we propose using Benford’s Law as an auditing tool to monitor the reliability of the number of daily COVID-related deaths to identify possible deviations from the expected trend.

p< 0.0001) and total costs ($6,958 vs. $1,618, p< 0.0001) than the comparison cohort. ConClusions: Study results suggest that patients diagnosed with T2DM utilized more health resources and incurred four times higher costs compared to those without a T2DM diagnosis.

<p>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.</p>