RESUMEN
BACKGROUND: Accurate and timely cause of death (COD) data are essential for informed public health policymaking. Medical certification of COD generally provides the majority of COD data in a population and is an essential component of civil registration and vital statistics (CRVS) systems. Accurate completion of the medical certificate of cause of death (MCCOD) should be a relatively straightforward procedure for physicians, but mistakes are common. Here, we present three training strategies implemented in five countries supported by the Bloomberg Philanthropies Data for Health (D4H) Initiative at the University of Melbourne (UoM) and evaluate the impact on the quality of certification. METHODS: The three training strategies evaluated were (1) training of trainers (TOT) in the Philippines, Myanmar, and Sri Lanka; (2) direct training of physicians by the UoM D4H in Papua New Guinea (PNG); and (3) the implementation of an online and basic training strategy in Peru. The evaluation involved an assessment of MCCODs before and after training using an assessment tool developed by the University of Melbourne. RESULTS: The TOT strategy led to reductions in incorrectly completed certificates of between 28% in Sri Lanka and 40% in the Philippines. Following direct training of physicians in PNG, the reduction in incorrectly completed certificates was 30%. In Peru, the reduction in incorrect certificates was 30% after implementation and training on an online system only and 43% after training on both the online system and basic medical certification principles. CONCLUSIONS: The results of this study indicate that a variety of training strategies can produce benefits in the quality of certification, but further improvements are possible. The experiences of D4H suggest several aspects of the strategies that should be further developed to improve outcomes, particularly key stakeholder engagement from early in the intervention and local committees to oversee activities and support an improved culture in hospitals to support better diagnostic skills and practices.
Asunto(s)
Causas de Muerte , Certificado de Defunción , Estadísticas Vitales , Exactitud de los Datos , Educación Médica , Humanos , Mianmar , Papúa Nueva Guinea , Perú , Filipinas , Sri LankaRESUMEN
BACKGROUND: Mortality statistics derived from cause of death data are an important source of information for population health monitoring, priority setting and planning. In Perú, almost all death certificates are issued by doctors because it is a legal requirement. However, the quality of cause of death data is poor. In August 2016, the Ministry of Health of Perú decided to make two specific interventions to improve cause of death data: to introduce an online death certification system and to train doctors in standard death certification practices. METHODS: The study comprised a random sample of 300 pre-intervention death certificates, 900 death certificates that were part of the online intervention, and 900 death certificates that were part of both the online and training interventions. All the deaths had occurred between January and September 2017. We used the Assessing the quality of death certification tool from the University of Melbourne for the assessment. We examined the frequency of common errors in death certificates, the frequency of any error and the average error score for each category of: age group, sex, doctor's seniority, doctor's speciality, level of health facility and broad cause of death. RESULTS: The average error score declined by 38% due to the online intervention and by a further 26% due to the training intervention. Improved certification practices remained after controlling for potentially confounding factors. Main improvements were reductions in the absence of a time interval (66% of certificates), incorrect sequence of causes (22%), and ill-defined conditions (13%). CONCLUSIONS: This study demonstrates how the two interventions introduced by the Ministry of Health in Perú improved the correctness of death certificates. The study also provides evidence on necessary changes to the training program to address the poor certification practices that have remained after implementation of the online system.
Asunto(s)
Causas de Muerte , Exactitud de los Datos , Certificado de Defunción , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Niño , Preescolar , Educación , Femenino , Humanos , Lactante , Recién Nacido , Masculino , Persona de Mediana Edad , Sistemas en Línea , Perú/epidemiología , Médicos , Evaluación de Programas y Proyectos de Salud , Adulto JovenRESUMEN
MAIN RESULTS: It could be seen good performance of the software for the automatic selection of the underlying cause of death, increasing from 69.6% in 2016 to 78.8% in 2019. There was a correlation between this result and the use of online death certificates by physicians. IMPLICATIONS FOR SERVICES: Automatic coding and selection of causes of death improve productivity and timeliness of information, contributing to the quality of the country's information system. PERSPECTIVES: It is necessary to analyze the agreement between the medical terms in the software dictionaries used in South American countries in order to improve standardization and comparability of information on causes of death. OBJECTIVE: to describe software performance in the automatic selection of the underlying cause of death in Peru, between 2016 and 2019. METHODS: this was a descriptive study on the software performance in the automated selection of the underlying cause of death over the years (chi-square test for trend) and the correlation between the type of death certificate and software performance (correlation coefficient and coefficient of determination). RESULTS: a total of 446,217 death certificates were analyzed; the proportion of death certificates with the underlying cause of death increased from 69.6% in 2016 to 78.8% in 2019 (p-value < 0.001); it could be seen a direct linear correlation between electronic death certificates and software performance (correlation coefficient = 0.95; R2 = 0.89). CONCLUSION: the software showed good performance in the automatic selection of the underlying cause of death, with a significant increase between 2016 and 2019.
Asunto(s)
Médicos , Humanos , Perú , Causas de Muerte , Brasil , Programas InformáticosRESUMEN
Objectives: We aimed to understand the information architecture and degree of integration of mortality surveillance systems in Ghana and Peru. Methods: We conducted a cross-sectional study using a combination of document review and unstructured interviews to describe and analyse the sub-systems collecting mortality data. Results: We identified 18 and 16 information subsystems with independent databases capturing death events in Peru and Ghana respectively. The mortality information architecture was highly fragmented with a multiplicity of unconnected data silos and with formal and informal data collection systems. Conclusion: Reliable and timely information about who dies where and from what underlying cause is essential to reporting progress on Sustainable Development Goals, ensuring policies are responding to population health dynamics, and understanding the impact of threats and events like the COVID-19 pandemic. Integrating systems hosted in different parts of government remains a challenge for countries and limits the ability of statistics systems to produce accurate and timely information. Our study exposes multiple opportunities to improve the design of mortality surveillance systems by integrating existing subsystems currently operating in silos.
Asunto(s)
COVID-19 , Estadísticas Vitales , Humanos , Ghana/epidemiología , Perú/epidemiología , Estudios Transversales , PandemiasRESUMEN
Objective: to describe software performance in the automatic selection of the underlying cause of death in Peru, between 2016 and 2019. Methods: this was a descriptive study on the software performance in the automated selection of the underlying cause of death over the years (chi-square test for trend) and the correlation between the type of death certificate and software performance (correlation coefficient and coefficient of determination). Results: a total of 446,217 death certificates were analyzed; the proportion of death certificates with the underlying cause of death increased from 69.6% in 2016 to 78.8% in 2019 (p-value < 0.001); it could be seen a direct linear correlation between electronic death certificates and software performance (correlation coefficient = 0.95; R2 = 0.89). Conclusion: the software showed good performance in the automatic selection of the underlying cause of death, with a significant increase between 2016 and 2019.
Objetivo: describir el desempeño de un software en la selección automática de la causa básica de muerte en Perú, entre 2016 y 2019. Métodos: estudio descriptivo de la tendencia del desempeño de un software para seleccionar la causa básica de muerte a través de los años (chi cuadrado de tendencia) y la correlación entre los certificados de defunción electrónicos y el desempeño del software (coeficientes de correlación y determinación). Resultados: se analizaron 446.217 certificados; la proporción de certificados con causa básica de muerte aumentó de 69,6% en 2016 a 78,8% en 2019 (p-valor < 0,001); se observó una correlación lineal directa entre certificados electrónicos y el desempeño del software (coeficiente de correlación = 0,95; R2 = 0,89). Conclusión: el software presentó un buen desempeño en la selección de la causa básica de muerte y aumentó significativamente entre 2016 y 2019.
Objetivo: descrever o desempenho de um software na seleção automática da causa básica de morte no Peru, entre 2016 e 2019. Métodos: estudo descritivo do desempenho de um software na seleção automatizada da causa básica de morte ao longo dos anos (teste qui-quadrado de tendência) e da correlação entre a forma de declaração de óbito e o desempenho do software (coeficientes de correlação e determinação). Resultados: foram analisadas 446.217 declarações de óbito; a proporção de declarações com causa básica de morte aumentou de 69,6%, em 2016, para 78,8%, em 2019 (p-valor < 0,001); observou-se correlação linear direta entre as declarações eletrônicas de óbito e o desempenho do software (coeficiente de correlação = 0,95; R2 = 0,89). Conclusão: o software apresentou bom desempenho na seleção automática da causa básica de morte, com aumento significativo entre 2016 e 2019.