[Adjusted clinical groups use at a Spanish primary care center: a retrospective, population-based study]. / Utilización de los grupos clínicos ajustados en un centro de atención primaria español: estudio retrospectivo de base poblacional.

OBJECTIVES: To evaluate the results of implementing a classification system based on adjusted clinical groups (ACG) at a primary health care (PHC) in a Spanish population. METHODS: A retrospective, cross-sectional study based on the computerized medical records of outpatients seen in 2007 by the La Roca clinic, administered by a health services management company in La Roca del Vallès, Barcelona, Spain. The ACGs were formed according to the International Classification of Diseases, 9th Revision, Clinical Modification. The relative weight of each ACG's total average cost was calculated (in U.S. dollars) and based on these, the resources usage levels were established. The risk index (RI) and efficiency index (EI) for 2006 and the classification's explanatory power were determined. RESULTS: A total of 8 294 patients were studied (82.7% coverage), with an average of 4.1 incidents per patient, 6.9 visits per patient, and 5.7 visits per person per year. Seven GCAs accounted for 51.0% of patients seen. The RI was 1.015, the EI was 0.975 visits, and the explanatory power of the ACG classification was 53.4% for visits and 74.8% for incidents. CONCLUSIONS: The ACG system allowed this patient population to be grouped by clinical status, which can help to, among other things, allocate resources and evaluate PHC team efficiency.

Utilización de los grupos clínicos ajustados en un centro de atención primaria español: estudio retrospectivo de base poblacional / Adjusted clinical groups use at a Spanish primary care center: a retrospective, population-based study

OBJETIVOS: Evaluar los resultados de la aplicación del sistema de clasificación mediante grupos clínicos ajustados (GCA) en un centro de atención primaria de salud (APS) de una población española. MÉTODOS: Estudio transversal retrospectivo a partir de los registros médicos informatizados de los pacientes atendidos ambulatoriamente durante 2007 en el centro de salud La Roca, administrado por una empresa de gestión de servicios de salud en La Roca del Vallès, Barcelona, España. Los GCA se conformaron según la Clasificación Internacional de Enfermedades, 9.ª revisión, modificación clínica. Se calcularon los pesos relativos medios en dólares estadounidenses de cada GCA respecto al costo medio total y, a partir de ellos, se crearon las bandas de utilización de recursos. Se determinaron los índices de riesgo (IR) y eficiencia (IE) con respecto a 2006 y se estimó el poder explicativo de la clasificación empleada. RESULTADOS: Se estudiaron 8 294 pacientes, para una cobertura de 82,7 por ciento, con una media de 4,1 episodios por paciente, 6,9 visitas por paciente y 5,7 visitas por habitante al año. A siete GCA correspondió 51,0 por ciento de los pacientes atendidos. El IR fue de 1,015, el IE en las visitas de 0,975 y el poder explicativo de la clasificación en GCA fue de 53,4 por ciento para las visitas y de 74,8 por ciento para los episodios. CONCLUSIONES: El sistema de GCA permitió agrupar a los pacientes de una población según su estado clínico y puede ayudar, entre otros aspectos, en la asignación de recursos y la evaluación de la eficiencia de los equipos de APS.

OBJECTIVES: To evaluate the results of implementing a classification system based on adjusted clinical groups (ACG) at a primary health care (PHC) in a Spanish population. METHODS: A retrospective, cross-sectional study based on the computerized medical records of outpatients seen in 2007 by the La Roca clinic, administered by a health services management company in La Roca del Vallès, Barcelona, Spain. The ACGs were formed according to the International Classification of Diseases, 9th Revision, Clinical Modification. The relative weight of each ACG's total average cost was calculated (in U.S. dollars) and based on these, the resources usage levels were established. The risk index (RI) and efficiency index (EI) for 2006 and the classification's explanatory power were determined. RESULTS: A total of 8 294 patients were studied (82.7 percent coverage), with an average of 4.1 incidents per patient, 6.9 visits per patient, and 5.7 visits per person per year. Seven GCAs accounted for 51.0 percent of patients seen. The RI was 1.015, the EI was 0.975 visits, and the explanatory power of the ACG classification was 53.4 percent for visits and 74.8 percent for incidents. CONCLUSIONS: The ACG system allowed this patient population to be grouped by clinical status, which can help to, among other things, allocate resources and evaluate PHC team efficiency.

Identificación de pacientes hiperconsumidores de farmacia en atención primaria / Identification of pharmacy cost outliers in primary care

ObjetivoIdentificar pacientes hiperconsumidores de farmacia en atención primaria, describir las diferencias epidemiológicas entre pacientes normoconsumidores e hiperconsumidores e investigar la capacidad explicativa del sistema de ajuste de riesgos ACG (Adjusted Clinical Groups) sobre la variabilidad del gasto farmacéutico para ambos grupos de pacientes.DiseñoEstudio observacional retrospectivo.Emplazamiento23 centros de salud de Aragón, Baleares y Cataluña.ParticipantesSe incluyeron 286.450 pacientes atendidos al menos una vez en 2005.MedicionesSe analizaron variables demográficas, de consumo farmacéutico y de casuística (ACG® 7.1). Se identificaron pacientes hiperconsumidores a partir del rango intercuartílico. Se construyó un modelo de regresión lineal, para conocer la capacidad explicativa del ACG sobre el consumo farmacéutico. El mismo modelo se aplicó para la estratificación según variables del profesional, centro de salud y comunidad autónoma.ResultadosUno de cada 10 pacientes se clasificó como hiperconsumidor. Este grupo fue el causante del 60% del gasto farmacéutico. Se trata de pacientes con 26,3 años más y con mayor comorbilidad que los pacientes normoconsumidores. La capacidad explicativa del ACG sobre el gasto farmacéutico fue llamativamente inferior para el grupo de hiperconsumidores (3 frente a 26% en pacientes normoconsumidores).ConclusionesHan de investigarse las causas que provocan la falta de adaptación de los ACG al grupo de pacientes hiperconsumidores. Puede que haya circunstancias sociales que influyen sobre la situación clínica de estos pacientes. O, más probablemente, el método utilizado para detectar el hiperconsumo no permita diferenciar adecuadamente, de entre todos los pacientes hiperconsumidores, a aquéllos en los que la enfermedad justifica el gasto realizado(AU)

ObjectiveTo identify pharmacy cost outlier patients in Primary Care, describing epidemiological differences between normal users and outliers; and to study the explanatory power of risk adjustment tools based on Adjusted Clinical Groups (ACG) as regards the variability of pharmacy expenditure for both groups of patients.DesignObservational, retrospective study.Setting23 health centres located in the regions of Aragon, Catalonia and the Balearic Islands.ParticipantsThe study sample consisted of 286,450 patients who were seen at least once in 2005.MeasurementsVariables related to demographic features, pharmacy cost, and case-mix (ACG® 7.1) were collected. Pharmacy cost outliers were selected according to the inter-quartile range method. A linear regression model was developed to measure the explanatory power of ACG. This same model was applied stratifying the population by variables of the physician, the health centre and the region.ResultsOne out of ten patients was classified as an outlier. This group was responsible for 60% of the total pharmacy expenditure. These outlier patients were 26.3 years older than normal users and had a higher comorbidity. The explanatory power of the ACG classification system was markedly lower −3% vs. 26.4% for normal users-.ConclusionsFurther research should be done on factors causing a lack of adequacy of ACG among pharmacy outlier patients. Although it could be thought that social circumstances might play a role in the clinical state of patients, it is more likely that the applied trimming method does not allow outliers with justifiable clinical reasons for higher costs to be distinguished from those without them(AU)

[Identification of pharmacy cost outliers in primary care]. / Identificación de pacientes hiperconsumidores de farmacia en atención primaria.

OBJECTIVE: To identify pharmacy cost outlier patients in Primary Care, describing epidemiological differences between normal users and outliers; and to study the explanatory power of risk adjustment tools based on Adjusted Clinical Groups (ACG) as regards the variability of pharmacy expenditure for both groups of patients. DESIGN: Observational, retrospective study. SETTING: 23 health centres located in the regions of Aragon, Catalonia and the Balearic Islands. PARTICIPANTS: The study sample consisted of 286,450 patients who were seen at least once in 2005. MEASUREMENTS: Variables related to demographic features, pharmacy cost, and case-mix (ACG 7.1) were collected. Pharmacy cost outliers were selected according to the inter-quartile range method. A linear regression model was developed to measure the explanatory power of ACG. This same model was applied stratifying the population by variables of the physician, the health centre and the region. RESULTS: One out of ten patients was classified as an outlier. This group was responsible for 60% of the total pharmacy expenditure. These outlier patients were 26.3 years older than normal users and had a higher comorbidity. The explanatory power of the ACG classification system was markedly lower -3% vs. 26.4% for normal users-. CONCLUSIONS: Further research should be done on factors causing a lack of adequacy of ACG among pharmacy outlier patients. Although it could be thought that social circumstances might play a role in the clinical state of patients, it is more likely that the applied trimming method does not allow outliers with justifiable clinical reasons for higher costs to be distinguished from those without them.

The relationship between effectiveness and costs measured by a risk-adjusted case-mix system: multicentre study of Catalonian population data bases.

BACKGROUND: The main objective of this study is to measure the relationship between morbidity, direct health care costs and the degree of clinical effectiveness (resolution) of health centres and health professionals by the retrospective application of Adjusted Clinical Groups in a Spanish population setting. The secondary objectives are to determine the factors determining inadequate correlations and the opinion of health professionals on these instruments. METHODS/DESIGN: We will carry out a multi-centre, retrospective study using patient records from 15 primary health care centres and population data bases. The main measurements will be: general variables (age and sex, centre, service [family medicine, paediatrics], and medical unit), dependent variables (mean number of visits, episodes and direct costs), co-morbidity (Johns Hopkins University Adjusted Clinical Groups Case-Mix System) and effectiveness.The totality of centres/patients will be considered as the standard for comparison. The efficiency index for visits, tests (laboratory, radiology, others), referrals, pharmaceutical prescriptions and total will be calculated as the ratio: observed variables/variables expected by indirect standardization.The model of cost/patient/year will differentiate fixed/semi-fixed (visits) costs of the variables for each patient attended/year (N = 350,000 inhabitants). The mean relative weights of the cost of care will be obtained. The effectiveness will be measured using a set of 50 indicators of process, efficiency and/or health results, and an adjusted synthetic index will be constructed (method: percentile 50).The correlation between the efficiency (relative-weights) and synthetic (by centre and physician) indices will be established using the coefficient of determination. The opinion/degree of acceptance of physicians (N = 1,000) will be measured using a structured questionnaire including various dimensions. STATISTICAL ANALYSIS: multiple regression analysis (procedure: enter), ANCOVA (method: Bonferroni's adjustment) and multilevel analysis will be carried out to correct models. The level of statistical significance will be p < 0.05.