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Conteúdo (article):

DISTRIBUIÇÃO ESPACIAL DAS NOTIFICAÇÕES DE ERROS DE IMUNIZAÇÃO NO ESTADO DE MINAS GERAIS
SPATIAL DISTRIBUTION OF IMMUNIZATION ERROR NOTIFICATION IN MINAS GERAIS STATE
DISTRIBUCIÓN ESPACIAL DE LAS NOTIFICACIONES DE ERRORES DE INMUNIZACIÓN EN EL ESTADO DE MINAS GERAIS
1Wiara Viana Ferreira, Universidade Federal de São João del-Rei, e-mail: wiaravianaenf@gmail.com, ORCID: 0000-0003-3524-135X
2Luiz Henrique Arroyo, Escola de Enfermagem de Ribeirão Preto da Universidade de São Paulo, e-mail: luiz.arroyo@hotmail.com, ORCID: 0000-0003-3302-0502
3Rillary Carvalho dos Santos, Universidade Federal de São João del-Rei, e-mail:
rillarycarvalho24@outlook.com, ORCID: 0009-0008-5955-8005
4Thayane Ingrid Xavier de Andrade, Universidade Federal de São João del-Rei, e-mail: thatha.red@gmail.com, ORCID: 0000-0002-6561-7509
5Eliete Albano de Azevedo Guimarães, Universidade Federal de São João del-Rei, e-mail: elietealbano@ufsj.edu.br, ORCID: 0000-0001-9236-8643
6Valéria Conceição de Oliveira, Universidade Federal de São João del-Rei, e-mail: valeriaoliveira@ufsj.edu.br, ORCID: 000-0003-2606-9754

RESUMO
A vacinação é uma intervenção essencial, embora sujeita a erros, o que torna fundamental a notificação desses casos para garantir a segurança durante o processo de imunização. O objetivo foi identificar aglomerados espaciais de notificações de erro de imunização no estado de Minas Gerais e fatores associados. Trata-se de um estudo ecológico conduzido com base nas recomendações do STROBE nos 853 municípios de Minas Gerais, a partir das notificações de erros de imunização no período de 2015 a 2019. Realizou-se estatística de varredura para identificar agrupamentos espaciais e modelo generalizado para fatores associados. A análise espacial revelou aglomerados com baixa notificação de erro de imunização, em todas as macrorregiões do Estado. Identificou-se uma associação positiva entre a notificação de erro de imunização e a população menor de um ano, com Risco Relativo de 1,004 (IC95% = 1,002 a 1,006). Assim, um aumento de cinco crianças menores de um ano em um município mineiro, está associado a 1,84% (aproximadamente 2%) mais chance de ser notificado de um erro de imunização. Este estudo poderá subsidiar medidas prioritárias para estratégias adaptadas a cada macrorregião, garantindo vigilância mais eficiente e pontual nessas localidades.
Palavras-chave: Erros de Medicação; Imunização; Segurança do Paciente; Análise espacial, Eventos Adverso
ABSTRACT
Vaccination is an essential intervention, although subject to errors, which makes it essential to report these cases to ensure safety during the immunization process. The objective was to identify spatial clusters of immunization error notifications and associated factors in Minas Gerais State. This is an ecological study based on the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) recommendations in the 853 municipalities of Minas Gerais, considering the immunization error notifications from 2015 to 2019. Scan statistics were utilized to identify spatial clusters and a generalized model for associated factors. The spatial analysis revealed clusters with low immunization error notification in all of the state\'s macroregions. A positive association was found between the notification of immunization errors and the population under one year old, with a Relative Risk of 1.004 (95%CI = 1.002 to 1.006). Thus, an increase of five children under the age of one in a municipality in Minas Gerais was associated with a 1.84% (approximately 2%) greater chance of being notified as an immunization error. This study could support priority measures for strategies adapted to each macroregion, ensuring more efficient, timely surveillance in these locations.
Keywords: Medication Errors; Immunization; Patient Safety; Spatial Analysis, Adverse Events.
RESUMEN
La vacunación es una intervención esencial, aunque sujeta a errores, lo que hace imprescindible la notificación de estos casos para garantizar la seguridad durante el proceso de inmunización. El objetivo fue identificar clusters espaciales de notificación de errores de inmunización en el estado de Minas Gerais y factores asociados. Se trata de un estudio ecológico basado en las recomendaciones STROBE en los 853 municipios de Minas Gerais, a partir de las notificaciones de errores de inmunización de 2015 a 2019. Se utilizaron estadísticas de exploración para identificar clústeres espaciales y un modelo generalizado para los factores asociados. El análisis espacial reveló clústeres con baja notificación de errores de inmunización en todas las macrorregiones del estado. Se identificó una asociación positiva entre la notificación de errores de inmunización y la población menor de un año, con un Riesgo Relativo de 1,004 (IC 95% = 1,002 a 1,006). Así, un aumento de cinco niños menores de un año en un municipio de Minas Gerais se asocia con una probabilidad 1,84% (aproximadamente 2%) mayor de ser notificado de un error de inmunización. Este estudio podría subsidiar medidas prioritarias para estrategias adaptadas a cada macrorregión, garantizando una vigilancia más eficiente y oportuna en estas localidades.
Palabras clave: Errores de Medicación; Inmunización; Seguridad del Paciente; Análisis Espacial, Eventos Adversos
Introduction
Vaccination plays an essential role and is one of the most effective measures in the prevention of immunopreventable disease1, but is not free of errors2. Errors are inevitable due to human nature3. In this sense, the notification of immunization errors emerges as a fundamental element to ensure safety during the vaccination process4,5.
Since 1991, the National Immunization Program (PNI) has invested in the creation of a National Surveillance System of Adverse Post-Vaccination Events, recognizing the possibility of immunization errors and events associated with vaccination or immunization (ESAVI) 6 This system allows notification, investigation and monitoring of conduct patterns in the face of such occurrences6.
Globally, health professionals have an obligation to notify ESAVI of errors, and most agree this practice is critical to increasing patient safety7. However, fear of punishment can lead to undernotification of these events8.
An integrative review found that in most of the studies included (87.5%), the professionals participating recognized the undernotification of events or errors as a reality in the health services where they worked. Notification plays a crucial role in assessing patient safety culture in the health system, it being an essential tool to promote continuous monitoring of safety and quality of care provided7.
In recent years, with technological and methodological advances, spatial analysis has gained prominence in epidemiological studies. This approach allows identification of spatial patterns in various situations, including health and epidemiological aspects9,10. Georeferencing techniques utilized in these studies integrate socioeconomic, environmental and structural health data with the geographic component, establishing the likelihood of relationships between locations. Thus, these data enable the planning of promotion and intervention strategies directed to the same geographic sphere7,11.
Considering the importance of immunization error, notification and the fundamental role of spatial analysis in the identification of geographic patterns, this study sought to answer the following question: What is the spatial pattern of immunization error notification in Minas Gerais?
This study aimed to identify spatial clusters of immunization error notifications and associated factors in Minas Gerais State .
Method
Type of study
This is an ecological study conducted based on STROBE\'s recommendations12.
Study Scenario
The study was conducted in Minas Gerais State, the second most populous state in Brazil. With an estimated population of 20,539,989, it has an urbanization level of 85.29% and an estimated area of 586,528,293 km2. Its territory is divided into 14 macroregions: Sul (3101), Centro Sul (3102), Centro (3103), Jequitinhonha (3104), Oeste (3105), Leste (3106), Sudeste (3107), Norte (3108), Noroeste (3109), Leste do Sul (3110), Nordeste (3111), Triângulo do Sul (3112), Triângulo do Norte (3113) and Vale do Aço (3114) (Figure 1), covering 853 municipalities, the territorial units of analysis in this study13,14.
Figure 1

Data Origin
In Minas Gerais State, between 2015 and 2019, 57,289,277 vaccine doses (PNI.datasus.gov.br, accessed 19/06/2023) were administered, and the immunization error notifications recorded in this same period were analyzed in the Adverse Post-vaccination Event Information System of the National Immunization Program (SI-EAPV), generating a total of 3,643 notifications.
The outcome variable was the immunization error notification. Encountering an immunization error, it is the professional\'s responsibility to contribute to the national notification systems. This notification not only identifies problems and risks, but also guides strategies to ensure the safety and quality of care6,8. However, it is important to recognize that undernotification is a frequent reality, resulting in the absence of notification of many errors9,15.
To identify the factors associated with immunization error notification, explanatory variables were selected from the databases of the National Register of Health Establishments in Brazil (CNES)16,17 and the João Pinheiro Foundation13,18 (Chart 1).
Chart 1

Data processing and analysis
Immunization error notification data were initially stored in Microsoft Excel (2016) to verify their consistency and quality. The spatial analysis technique, called scan statistics proposed by Kulldorff and Nagarwalla (1995)19, was utilized to identify and evaluate clusters of these notifications. This study defined the analysis window as circular, with a radius limited to 50% of the target population vaccinated in Minas Gerais, allowing high flexibility in the location and size of the clusters. A discreet Poisson probability model was employed, processed by Satscan 9.620 software, with analysis of significance based on 999 Monte Carlo simulations.
Cluster analysis considered relative risk (RR) to compare the probability of notifications in different areas, with RR values greater than 1, indicating a greater chance of notification. Besides this, Moran Bivariate Spatial Analysis was performed to identify notifications related to spatial determinants utilizing Geoda 1.1221 software to calculate spatial self-relation and spatial correlation between adjacent municipalities.
To identify factors associated with notifications, GAMLSS (Generalized Additive Models for Location, Scale, and Shape) models were applied with a Yule distribution suitable for dependent variables of the countable type, similar to Poisson, but with specific characteristics such as super dispersion and asymmetry. The choice of Yule distribution was based on the data adjustment observed, considering that more common models, such as Poisson or Negative Binomial, did not properly capture the data characteristics. GAMLSS models were developed to deal with a larger variety of probability distributions for the data, allowing not only the mean (location), but also dispersion (scale) and distribution shape (e.g. asymmetry and kurtosis) to be modeled as covariable functions22,23.
All variables utilized in the Moran Bivariate were considered in the GAMLSS regression model. The criterion adopted for the explanatory model was the lowest value of the Akaike Information Criterion (AIC), utilizing the Stepwise variable selection technique for inclusion in the final statistical model. The AIC is an important metric for evaluating the quality of the statistical model, where the lower the value, the better the model. It is noteworthy that not all the variables presented in Chart 1 were included, as the process of selection and elimination of variables was aimed at reaching the lowest possible AIC value, resulting in the inclusion of the variable, population under one year (Table 2)24. The adequacy of the model was verified by Quantil-Quantil (QQplot) graphs, utilizing the R program version 4.1.1. It is noteworthy that the model\'s regression coefficients exponentially generated RR values and their respective 95% confidence intervals (IC95%). Coroplethic maps were devised with the results of the analyses, utilizing the Minas Gerais cartographic base available on the IBGE website, and processed by ArcGIS 10.825 software.
The study is part of the project, "Evaluation of Immunization Errors and Intervention Proposal", approved by the Ethics Committee in 2020 (Opinion No. 3,817.007).
Results
In the spatial scan analysis, the State’s macroregions were classified in areas with occurrence of high and low immunization errors (IE) among the 853 municipalities. Figure 2 reveals a heterogeneous distribution of low notification clusters, called cold areas in all the macroregions. Notably, there was an extensive low occurrence cluster in the Northwest region, while small areas with high occurrence, called hot areas, occasionally appeared, forming "islands" around various cold areas, spanning across the macroregions, Noroeste, Norte, Centro, and Triângulos do Sul e do Norte.
Figure 2

Analyzing the spatial correlation for immunization error notification, when index I of the Moran Global Bivariate was applied, the spatial correlation with socioeconomic factors and health service supply of the Minas Gerais municipalities was found (Table 1).
The variables: Population under one year, third dose of the DTPW+HB+Hib+HIB vaccine for coverage of the ESF and Basic| Care presented positive spatial correlation. On the other hand, the IDHM and the number of nurses per inhabitant showed inverse spatial correlation.
Table 1

Considering the GAMLSS regression model, a positive association between the notification of immunization error and the population under one year in the municipalities was identified. RR 1.004 (CI95% 1.002 to 1.006) indicated that, as the number of children under one year increased in the Minas Gerais municipalities, immunization error notifications also tended to increase. In this sense, considering the RR reported from the regression model, an increase of five times in the number of those aged less than one year in a particular municipality of the state resulted in 1.84% more risk of an immunization error.
Table 2

Considering the Kolmogorov-Smirnov test and the Q-Q plot, it is possible to confirm that the final model fulfills the presumptions of the analysis related to the residues, following a normal distribution, with a zero mean and constant variance.
Discussion
The results revealed heterogeneous behavior of purely spatial clusters with a low rate of IE notifications, distributed across all Minas Gerais macroregions. Clusters with low notification rates did not necessarily indicate that there was no occurrence of IE, but rather the possibility of undernotification of them.
Human error can be committed through personal or systemic approaches3. This type of personal approach to IE can lead to undernotification, understood as a lack of official registration or notification of cases that actually happened, resulting in underestimation of the real incidence figures or prevalence of a disease and/or event26.
Notably, in the health area, it is common to observe a predominance of a personal approach, both in investigation and in decision-making in the face of failure27. In this approach, the responsibility for error is almost always placed on the person who made it, and corrective measures often translate into negative disciplinary action, such as dismissal, sector reorganization administrative processes28,29.
Even though it is an important issue, the literature points out undernotification of immunization errors that are often not measured by the health services9,15,30,31.
A study conducted in Minas Gerais with the objective of investigating the IE undernotification found in children\'s vaccination record booklets, identified that all the errors were undernotified by the health services in the municipalities that participated9. In the USA, a study estimated that the annual error undernotification ranged from 50% to 60% 32.
By establishing a non-punitive atmosphere, the in-depth approach to underlying systems and processes is highlighted without concentrating exclusively on the individual12. This approach not only strengthens collective responsibility, but also contributes to a more comprehensive approach to the identification and correction of systemic issues11,12, which is most evident in environments that work with a positive safety culture, where the reported error is viewed as an opportunity for growth and improvement, which, in turn, promotes a culture of learning and continuous improvement throughout the organization, thus increasing the likelihood of error notification12,26.
IE notification plays a crucial role for the administration to recognize that there is scope for failure, providing a solid basis for analysis and implementation of strategic, systematic changes8. It is perceived as a fundamental part of the patient\'s safety due to its power to minimize damage and strengthen the learning of the professionals5.
The results of scan analysis draw attention to the presence of clusters in some regions with high rates of IE notification. However, it was observed that in the same region there were also clusters with low notification rates. This finding presupposes that there may be silent municipalities throughout the state.
The heterogeneous distribution of the low IE notification rates in macroregions of Minas Gerais, pointed out by this study, may be associated with regional disparities in investment in the health sector, such as human, technological and structural resources27, inputs, staff safety 15, among others. Consequently these discrepancies can directly influence the quality of care provided28.
In this sense, a survey conducted in Ghana points out that investments in health are related to patient safety at any level of care, this being an important factor for notifying an event11.
Minas Gerais, with its vast territorial extension, has regions with different levels of socioeconomic development29. The Centro, Norte, Noroeste and Triângulo do Norte macroregions recorded the highest IE notification rates. Although most of these regions have higher socioeconomi mean per capita income and higher social vulnerability, which puts it at a disadvantage in comparison with other areas of the state29,30.
A study conducted in Brazil that evaluated the notifications of events allegedly attributable to vaccination or immunization (ESAVI), also found heterogeneous distribution of notifications with higher incidences in regions with development regarded as high, such as the Sul and Sudeste regions31.
It is presumed that other contextual factors are related to notification, such as a lack of vaccination screening, deficiencies in the continuous education of professionals, absence of nursing supervision, work overload, demotivation, slow notification systems, and ignorance of the importance of filling out error notification forms5,30,31.
All the factors associated with immunization error notifications pointed out in this study presented spatial correlation. However, in regression analysis, only the population under one year of age was confirmed.
National and international studies have observed a higher prevalence of error in children aged under one year9,36.37. This fact may be due to this age group’s greater vaccination exposure, considering that most vaccines that make up the calendar are indicated for children of this age17. Another factor that may be related is the diversity of vaccines that this age group receives, and the similarity among them38, in addition to the concern of this public at the time of the administration of the vaccine, the low level ability of some professionals, and greater user frequency in health facilities, which provide opportunities for occurrence of such errors39.
The utilization of secondary data presents intrinsic limitations to the nature of information collection, which made it impossible to control them in this study to ensure the desired accuracy. In addition, immunization error undernotification can lead to underestimation of the true incidence in certain regions, thereby distancing the results from the reality of the event under study.
Despite the inherent limitations, this study presents valuable originality in addressing a reality faced by health systems and, specifically, nursing, which is the issue of notification/undernotification. The utilization of spatial analysis on this theme confers an innovative approach, providing important insights for planning future, more assertive intervention. The consideration of the localities, based on spatial analysis, broadens effective response capacity in the face of challenges related to immunization errors, thus contributing to improvement of the quality of care provided.



Conclusion
Minas Gerais presents significant variation in immunization error notifications, with areas showing low notification rates. The population under one year is associated with these rates.
To face this problem, action is needed to increase awareness of the importance of notifying immunization errors. These notifications provide valuable data to health administrators, allowing creation of prevention strategies and promotion of patient safety.
The results suggest implementation of strategies adapted to the specific needs of each macroregion in order to improve surveillance.
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