RESUMEN
OBJETIVO: Determinar la mortalidad al año y los factores relacionados en pacientes crónicos complejos (PCC) de centros de salud rurales y zonas de necesidades de transformación social (ZNTS) de Atención Primaria (AP) de Andalucía. MATERIAL Y MÉTODO: Diseño: descriptivo longitudinal prospectivo abierto de un año. Ámbito: 40 centros de salud. Sujetos: PCC mayores de 18 años con criterios de pluripatología y consentimiento a participar. Muestra: 814 sujetos (intervalo de confianza del 95%; riesgo alfa 0,03; p 0,2; incremento del 20% por posibles pérdidas). Variables: Dependiente: Mortalidad al año. Independientes: sociodemográficas, sociofamiliares, clínicas, funcionales (índice de Barthel -IB-, índice de Lawton-Brody), cognitivas (test de Pfeiffer), fármacos prescritos, uso de recursos sociosanitarios y calidad de vida (EQ-5D). Recogida de datos: entrevista e historia clínica. RESULTADOS: 832 PCC fueron incluidos (48,8% mujeres). La mortalidad al año fue 17,8% (n=148). El modelo de regresión logística para mortalidad incluyó: edad mayor de 85 años, presencia de cuidador, hemoglobina menor de 10g/L, ingreso hospitalario en el último año, IB menor de 60 puntos y neoplasia activa. La calibración del modelo fue buena (p = 0,85 en el test de Hosmer-Lemeshow) con buen poder de discriminación (área bajo la curva ROC 0,72 [IC 95% 0,68 a 0,77]). CONCLUSIONES: La mortalidad al año en PCC atendidos en centros de salud rurales y ZNTS de AP fue del 17,8%. El conocimiento de los factores relacionados con la mortalidad en este grupo de pacientes contribuye al abordaje de necesidades y gestión de los recursos sociosanitarios
OBJECTIVE: To determine one-year mortality and associated factors in patients with complex chronic diseases (CCP) in rural health centres and social transformation needs areas (STNA) in Primary Health Care (PHC) in Andalusia. MATERIAL AND METHODS: Design: 1-Year longitudinal observational prospective open study. SETTING: 40 health centre. Subjects: consenting subjects over 18yr according multiple health condition criteria. Sample Size: 814 subjects (confidence interval 95%, alpha risk 0.03%, p=.2; 20% of sample increase due to possible losses). End-point: 1-year Mortality. Independent variables: socio-demographic, socio-familial, clinical, functional (Barthel Index -BI-, Lawton-Brody Index), cognitive (Pfeiffer Test), prescribed drugs, social healthcare resources consumption, and quality of life (EQ-5D). Data source: Interview and computerised clinical history. RESULTS: A total of 832 CCP were included (48.8% women). One-year mortality was 17.8% (n=148). Logistic regression model for mortality included: aged 85 and over, having a caregiver, haemoglobin level less 10g/L, hospital admission in last year, BI under 60 points, and active neoplasia. The calibration obtained from model was good (p=.85 in the Hosmer-Lemeshow goodness-of-fit test), and the discrimination power also good (AUC=0.772 [0.68-0.77] in ROC curve). CONCLUSIONS: 1-year mortality of CCP in rural centres and STNA in PHC was 17.8%. Knowledge of the factors related to the mortality of CCP helps to approach the needs and social-health resources management
Asunto(s)
Humanos , Masculino , Femenino , Persona de Mediana Edad , Anciano , Anciano de 80 o más Años , Enfermedad Crónica/mortalidad , Hospitalización/estadística & datos numéricos , Calidad de Vida , Población Rural/estadística & datos numéricos , Estudios Longitudinales , Primeros Auxilios , Estudios Prospectivos , EspañaRESUMEN
OBJECTIVE: To determine one-year mortality and associated factors in patients with complex chronic diseases (CCP) in rural health centres and social transformation needs areas (STNA) in Primary Health Care (PHC) in Andalusia. MATERIAL AND METHODS: Design: 1-Year longitudinal observational prospective open study. SETTING: 40 health centre. SUBJECTS: consenting subjects over 18yr according multiple health condition criteria. SAMPLE SIZE: 814 subjects (confidence interval 95%, alpha risk 0.03%, p=.2; 20% of sample increase due to possible losses). End-point: 1-year Mortality. INDEPENDENT VARIABLES: socio-demographic, socio-familial, clinical, functional (Barthel Index -BI-, Lawton-Brody Index), cognitive (Pfeiffer Test), prescribed drugs, social healthcare resources consumption, and quality of life (EQ-5D). DATA SOURCE: Interview and computerised clinical history Results: A total of 832 CCP were included (48.8% women). One-year mortality was 17.8% (n=148). Logistic regression model for mortality included: aged 85 and over, having a caregiver, haemoglobin level less 10g/L, hospital admission in last year, BI under 60 points, and active neoplasia. The calibration obtained from model was good (p=.85 in the Hosmer-Lemeshow goodness-of-fit test), and the discrimination power also good (AUC=0.772 [0.68-0.77] in ROC curve). CONCLUSIONS: 1-year mortality of CCP in rural centres and STNA in PHC was 17.8%. Knowledge of the factors related to the mortality of CCP helps to approach the needs and social-health resources management.
Asunto(s)
Enfermedad Crónica/mortalidad , Hospitalización/estadística & datos numéricos , Calidad de Vida , Población Rural/estadística & datos numéricos , Anciano , Anciano de 80 o más Años , Femenino , Humanos , Estudios Longitudinales , Masculino , Persona de Mediana Edad , Atención Primaria de Salud , Estudios Prospectivos , EspañaRESUMEN
OBJECTIVE: The aims of this study were to investigate whether general practitioners (GPs) who complied with quality prescribing indicators included in the pay-for-performance programmes also complied with quality prescribing indicators which are not linked to incentives and to compare the prescribing behaviour between those GPs who showed compliance with quality prescribing indicators linked to financial incentives and those who did not. DESIGN AND METHODOLOGY: This was a descriptive cross-sectional study which was conducted in 2007 in the Aljarafe Primary Care Area (Andalusia, Spain) and involved 37 Health Care Centres and 176 GPs. The main outcome was the results of a comparison of six quality prescribing indicators linked to incentives and 14 quality prescribing indicators not linked to incentives. The chi-square test was used to compare qualitative variables. Quantitative variables were tested using Student's t test upon confirmation of normality. RESULTS: Those GPs showing compliance with the indicators included in the pay-for performance programme showed low levels of compliance with quality prescribing indicators that were unincentivised. With respect to compliance with the indicators not linked to financial incentives, we found no statistical difference between GPs who showed compliance with incentivised indicators (n = 57) and those showing non-compliance (n = 112) in terms of drug selection, with the exception of the selection of second- and third-line antibiotics and antihistamines, nor in terms of the appropriate use of drugs linked to patient's clinical conditions. CONCLUSIONS: The compliance of GPs showing compliance with quality prescribing indicators included in pay-for-performance programmes was not better than that of those who showed no compliance with other relevant quality prescribing indicators not linked to financial incentives.