Explaining primary healthcare pharmacy expenditure using classification of medications for chronic conditions

Abstract

ElsevierVivas Consuelo, DJJ.; Guadalajara Olmeda, MN.; Barrachina Martínez, I.; Poza Plaza, EDL. (2011). Explaining primary health care pharmacy expenditure using classification of medications for chronic conditions. Health Policy. 103(1):9-15. doi:10.1016/j.healthpol.2011.08.014. 1Explaining primary healthcare pharmacy expenditure using classification of medications for chronic conditions. David Vivas*, Natividad Guadalajara*, Isabel Barrachina*, José-Luis Trillo**, Ruth Usó** and Elena de-la-Poza*. AbstractBackground: The Valencian Autonomous Community (Spain) has implemented a scheme of purchasing services with the participation of public and private providers. Five districts are managed using PublicPrivate Partnership. The financing model is capitation and inter-centre invoice. The pharmaceutical benefits are not included in the per capita assignment.Objectives: Modeling and explaining pharmacy expenditure using electronic prescriptions drug data.Methods: A database of electronic prescription corresponding to 625,246 patients between Nov 2008 and Oct 2009 was used to run four linear models that explain the pharmaceutical expenditures. We take as dependent variable the neperian log of total pharmacy annual cost per patient in the primary health setting. The independent variables used combine demographics with revised classification in 18 chronic conditions obtained from the anatomical therapeutic chemical classification index (ATC).Results: The retrospective model selected included: gender, pharmaceutical co-payment status and 8 dummy variables for the number of chronic conditions of each patient from 1 to 8 or more. The goodness-of-fit achieved is measured in R 2 of 57%.Conclusions: These models must be considered in the current capitation system for pharmaceutical budgeting in a primary care setting established at regional level, as is the case in the Valencian Autonomous Community. The use of diagnostics and information regarding hospital encounters appears to be a complementary option for refining models of capitation of pharmaceutical and total health expenditure.

Predictability of pharmaceutical spending in primary health services using Clinical Risk Groups

“…Previously, when a reliable EHR was not available, prescription data and WHO-ATC codes were used to establish the risk adjustment system [17]. However, although this system achieves a high explicative power for pharmaceutical expenditure, it is difficult to operate and has poor clinical use, as it is not connected with the EHR and a regular cross section calculation of weights is necessary.…”

“…We used an appropriate comparison system, described in a recent work [17], the ATC-model, a retrospective model that classifies patients according to the number of chronic conditions in 9 groups, from healthy to those with 8 chronic diseases or more and also includes gender.…”

“…Table 1 shows the ATC-code related with each chronic condition and the number of patients who have received at least 5 prescriptions per year. We use a classification of medicines validated by Lamers LM and van Vliet RC [4] and modified by Vivas D et al [17].…”

Gasto farmacéutico en diabetes mellitus en una región de España según el Clinical Risk Group, 2012

“…La implementación de estos sistemas de ajuste depende de la información de la cual se disponga, y esta puede hacer referencia al diagnóstico de los pacientes o al consumo de sustancias farmacéuticas (10).…”

Focus on primary care—A tribute to Barbara Starfield

“…The articles following provide good examples of important aspects of primary care such as predicting pharmaceutical expenditure, affiliation to and choice of general practitioners as well as the public-private mix in Spain [5], Australia [6], New Zealand [7] and Sweden [8]. Health Policy is continuously seeking to receiving -and publishing -short, full-length and review articles on primary care, which are both scientifically sound and politically relevant.…”