[Analysis of complaints in primary care using statistical process control]. / Análisis de las reclamaciones en atención primaria mediante el control estadístico de procesos.

OBJECTIVE: To analyze patient complaints in a Primary Health Care District (PHCD) using statistical process control methods compared to multivariate methods, as regards their results and feasibility of application in this context. MATERIAL AND METHOD: Descriptive study based on an aggregate analysis of administrative complaints. SETTING: Complaints received between January 2005 and August 2008 in the Customer Management Department in the 3rd PHCD Management Office, Madrid Health Services. Complaints are registered through Itrack, a computer software tool used throughout the whole Community of Madrid. MAIN VARIABLES: Total number of complaints, complaints sorted by Reason and Primary Health Care Team (PHCT), total number of patient visits (including visits on demand, appointment visits and home visits) and visits by PHCT and per month and year. STATISTICAL ANALYSIS: Multivariate analysis and control charts were used. RESULTS: 44-month time series with a mean of 76 complaints per month, an increasing trend in the first three years and decreasing during summer months. Poisson regression detected an excess of complaints in 8 out of the 44 months in the series. The control chart detected the same 8 months plus two additional ones. CONCLUSIONS: Statistical process control can be useful for detecting an excess of complaints in a PHCD and enables comparisons to be made between different PHC teams. As it is a simple technique, it can be used for ongoing monitoring of customer perceived quality.

Análisis de las reclamaciones en atención primaria mediante el control estadístico de procesos / Analysis of complaints in primary care using statistical process control

Objetivo: Analizar las reclamaciones de un área de atención primaria mediante técnicas de control estadístico de procesos, y compararlas con técnicas multivariables en cuanto a sus resultados y su factibilidad de aplicación en este medio. Material y método: Estudio descriptivo con análisis agregado de las reclamaciones administrativas. Período del estudio: reclamaciones recibidas desde enero de 2005 a agosto de 2008. Fuente de datos: la Unidad de Gestión de Usuarios de la Gerencia de Atención Primaria Área 3, Servicio Madrileño de Salud registra las reclamaciones en el programa track, utilizado en toda la Comunidad de Madrid. Mediciones principales: número total de reclamaciones, reclamaciones por motivo y por equipo de atención primaria, número de consultas totales (incluye consultas a demanda, concertadas y domicilio) y consultas por EAP, mes y año. Análisis estadístico: aplicación de técnicas multivariables y gráficos de control. Resultados: Serie temporal de 44 meses con una mediana de 76 reclamaciones/mes, una tendencia incremental en los primeros 3 años y descensos durante el verano. La regresión de Poisson permite detectar un exceso de reclamaciones en 8 de los 44 meses de la serie. El gráfico de control identifica los mismos puntos y 2 adicionales. Conclusiones: El control estadístico de procesos puede resultar útil para detectar excesos de reclamaciones en un área de salud y comparar entre unidades asistenciales. Su fácil aplicación permite realizar una monitorización continua de la calidad percibida por los usuarios (AU)

Objective: To analyze patient complaints in a Primary Health Care District (PHCD) using statistical process control methods compared to multivariate methods, as regards their results and feasibility of application in this context. Material and method: Descriptive study based on an aggregate analysis of administrative complaints. Setting: Complaints received between January 2005 and August 2008 in the Customer Management Department in the 3 rd PHCD Management Office, Madrid Health Services. Complaints are registered through track, a computer software tool used throughout the whole Community of Madrid. Main variables: Total number of complaints, complaints sorted by Reason and Primary Health Care Team (PHCT), total number of patient visits(including visits on demand, appointment visits and home visits) and visits by PHCT and per month and year. Statistical analysis: Multivariate analysis and control charts were used. Results: 44-month time series with a mean of 76 complaints per month, an increasing trend in the first three years and decreasing during summer months. Poisson regression detected an excess of complaints in 8 out of the 44 months in the series. The control chart detected the same 8 months plus two additional ones. Conclusions: Statistical process control can be useful for detecting an excess of complaints in a PHCD and enables comparisons to be made between different PHC teams. As it is a simple technique, it can be used for ongoing monitoring of customer perceived quality (AU)