Predictability of drug expenditures: an application using morbidity data

García-Goñi, Manuel; Ibern, Pere

doi:10.1002/hec.1238

Cited by 22 publications

(16 citation statements)

References 11 publications

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“…To date, research in the European and Spanish contexts has focused on using diagnoses-based risk assessment variables [3,11]. However, our study, as well as others carried out within the Spanish National Health System [20], determined that the accuracy of the diagnostic codes allocated by primary health care physicians in their computerised medical records could be improved.…”

Section: Discussionmentioning

confidence: 83%

“…By taking into account the risk factors for a covered population, prospective risk adjustment methodologies--commonly referred to as "predictive models" (PMs)--can be helpful for health budget planning and case profiling [3]. These tools can also be used as population-based screens meant to identify enrolees who pose a relatively higher risk of generating large future pharmacy expenditures [4,5].…”

Section: Introductionmentioning

confidence: 99%

“…To date, health services research in the Spanish context has focused on using diagnoses-based risk assessment variables [3,11]. However, risk assessment models such as the ACG-PMs, which integrate routinely collected pharmacy data, may be more appropriate.…”

Section: Introductionmentioning

confidence: 99%

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Applying diagnosis and pharmacy-based risk models to predict pharmacy use in Aragon, Spain: The impact of a local calibration

Calderón‐Larrañaga

Abrams

Poblador‐Plou

et al. 2010

BMC Health Serv Res

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BackgroundIn the financing of a national health system, where pharmaceutical spending is one of the main cost containment targets, predicting pharmacy costs for individuals and populations is essential for budget planning and care management. Although most efforts have focused on risk adjustment applying diagnostic data, the reliability of this information source has been questioned in the primary care setting. We sought to assess the usefulness of incorporating pharmacy data into claims-based predictive models (PMs). Developed primarily for the U.S. health care setting, a secondary objective was to evaluate the benefit of a local calibration in order to adapt the PMs to the Spanish health care system.MethodsThe population was drawn from patients within the primary care setting of Aragon, Spain (n = 84,152). Diagnostic, medication and prior cost data were used to develop PMs based on the Johns Hopkins ACG methodology. Model performance was assessed through r-squared statistics and predictive ratios. The capacity to identify future high-cost patients was examined through c-statistic, sensitivity and specificity parameters.ResultsThe PMs based on pharmacy data had a higher capacity to predict future pharmacy expenses and to identify potential high-cost patients than the models based on diagnostic data alone and a capacity almost as high as that of the combined diagnosis-pharmacy-based PM. PMs provided considerably better predictions when calibrated to Spanish data.ConclusionUnderstandably, pharmacy spending is more predictable using pharmacy-based risk markers compared with diagnosis-based risk markers. Pharmacy-based PMs can assist plan administrators and medical directors in planning the health budget and identifying high-cost-risk patients amenable to care management programs.

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Section: Discussionmentioning

confidence: 83%

Section: Introductionmentioning

confidence: 99%

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Applying diagnosis and pharmacy-based risk models to predict pharmacy use in Aragon, Spain: The impact of a local calibration

Calderón‐Larrañaga

Abrams

Poblador‐Plou

et al. 2010

BMC Health Serv Res

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“…The study uses past pharmaceutical procurement expenditure data to identify variables explaining primary health care pharmaceutical expenditure. This is in contrast to other studies that have used diagnosis data, pharmacy claims data and individual patient morbidity data [7,11-15]. Such data is not readily available in the Ugandan context.…”

Section: Discussionmentioning

confidence: 87%

What variables should be considered in allocating Primary health care Pharmaceutical budgets to districts in Uganda?

Mujasi

Puig‐Junoy

2015

J of Pharm Policy and Pract

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ObjectivesA key policy question for the government of Uganda is how to equitably allocate primary health care pharmaceutical budgets to districts. This paper seeks to identify variables influencing current primary health care pharmaceutical expenditure and their usefulness in allocating prospective pharmaceutical budgets to districts.MethodsThis was a cross sectional, retrospective observational study using secondary administrative data. We collected data on the value of pharmaceuticals procured by primary health care facilities in each district from National Medical Stores for the financial year 2011/2012. The dependent variable was expressed as per capita district pharmaceutical expenditure. By reviewing literature we identified 26 potential explanatory variables. They include supply, need and demand, and health system organization variables that may influence the demand and supply of health services and the corresponding pharmaceutical expenditure. We collected secondary data for these variables for all the districts in Uganda (n = 112). We performed econometric analysis to estimate parameters of various regression models.ResultsThere is a significant correlation between per capita district pharmaceutical expenditure and total district population, rural poverty, access to drinking water and outpatient department (OPD) per capita utilisation.(P < 0.01). The percentage of health centre IIIs (HC III) among each district’s health facilities is significantly correlated with per capita pharmaceutical expenditure (P < 0.05). OPD per capita utilisation has a relatively strong correlation with per capita pharmaceutical expenditure (r = 0.498); all the other significant factors are weakly correlated with per capita pharmaceutical expenditure (r < 0.5).From several iterations of an initially developed model, the proposed final model for explaining per capita pharmaceutical expenditure explains about 53% of the variation in pharmaceutical expenditure among districts in Uganda (Adjusted R2 = 0.528). All variables in the model are significant (p < 0.01).ConclusionsFrom evaluation of the various models, proposed variables to consider in allocating prospective primary health care pharmaceutical budgets to districts in Uganda are: district outpatient department attendance per capita, total district population, total number of government health facilities in the district and the district human poverty index.

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“…A previous study fitted a set of different models to estimate drug consumption costs for the Baix Empordà population [32]. The authors used CRGs as a risk adjuster, obtaining a high predictive power compared to other models in the literature.…”

Section: Discussionmentioning

confidence: 99%

Analysing the Costs of Integrated Care: A Case on Model Selection for Chronic Care Purposes

Carreras

Sánchez-Pérez

Ibern

et al. 2016

International Journal of Integrated Care

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Background:The objective of this study is to investigate whether the algorithm proposed by Manning and Mullahy, a consolidated health economics procedure, can also be used to estimate individual costs for different groups of healthcare services in the context of integrated care.Methods:A cross-sectional study focused on the population of the Baix Empordà (Catalonia-Spain) for the year 2012 (N = 92,498 individuals). A set of individual cost models as a function of sex, age and morbidity burden were adjusted and individual healthcare costs were calculated using a retrospective full-costing system. The individual morbidity burden was inferred using the Clinical Risk Groups (CRG) patient classification system.Results:Depending on the characteristics of the data, and according to the algorithm criteria, the choice of model was a linear model on the log of costs or a generalized linear model with a log link. We checked for goodness of fit, accuracy, linear structure and heteroscedasticity for the models obtained.Conclusion:The proposed algorithm identified a set of suitable cost models for the distinct groups of services integrated care entails. The individual morbidity burden was found to be indispensable when allocating appropriate resources to targeted individuals.

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Predictability of drug expenditures: an application using morbidity data

Cited by 22 publications

References 11 publications

Applying diagnosis and pharmacy-based risk models to predict pharmacy use in Aragon, Spain: The impact of a local calibration

Applying diagnosis and pharmacy-based risk models to predict pharmacy use in Aragon, Spain: The impact of a local calibration

What variables should be considered in allocating Primary health care Pharmaceutical budgets to districts in Uganda?

Analysing the Costs of Integrated Care: A Case on Model Selection for Chronic Care Purposes

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