Shared longitudinal health records for clinical and population health

The ability of a health information exchange (HIE) to consolidate information, collected from multiple, disparate information systems, into a single, person-centric health record can provide a comprehensive and longitudinal representation of an individual's medical history. Shared, longitudinal health records can be leveraged to enhance the delivery of individual clinical care and provide opportunities to improve health outcomes at the population level. This chapter describes the clinical benefits imparted by the shared health record (SHR) component an HIE infrastructure. It also characterizes the potential public health benefits of the aggregate level, population health indicators calculated, stored, and distributed by a health management information system (HMIS) component. Tools for visualizing health indicators from the HMIS, including disease surveillance systems developed during the COVID-19 pandemic, are also described. Postpandemic components such as the SHR and HMIS will likely play critical roles in strengthening health information infrastructures in states and nations. © 2023 Elsevier Inc. All rights reserved.

Impact of COVID-19 on utilization of maternal and child health services in India: Health management information system data analysis.

Background/Objectives: Studies globally have documented the impact of COVID 19 on maternal and newborn health services. This study assesses the impact of COVID-19 on essential maternal and child health (MCH) services in India based on the national Health Management Information System (HMIS). Methods: Present retrospective study used secondary data analysis upon the routinely collected data accessed from Health Management Information System. Microdata on maternal and newborn indicators was extracted for all states between April and June during 2019, 2020 and 2021. Relative change for each indicator were taken into consideration for the year 2020 and 2021; with respect to the outcomes in 2019. Results: Compared to 2019, antenatal care registrations saw a decline in all states for both periods in 2020 and 2021 except for Sikkim, Telangana, Maharashtra and Andhra Pradesh. Similarly, the relative changes in 2019 pertaining to the proportion of pregnant women provided with emergency obstetric care for pregnancy complications registered a decline in all states except for Himachal Pradesh, Telangana and Arunachal Pradesh. There was a decreasing trend noted in institutional deliveries in 2020 and 2021 among all major states. However, an increasing trend was seen in the number of immunization sessions held among all major states. Conclusion: The study demonstrates a disruption in service delivery during the lockdown period in the first wave and the peak of the second wave. Further qualitative studies need to be undertaken to generate evidence for maintaining continuum of care during a pandemic situation.

Addressing missing values in routine health information system data: an evaluation of imputation methods using data from the Democratic Republic of the Congo during the COVID-19 pandemic.

BACKGROUND: Poor data quality is limiting the use of data sourced from routine health information systems (RHIS), especially in low- and middle-income countries. An important component of this data quality issue comes from missing values, where health facilities, for a variety of reasons, fail to report to the central system. METHODS: Using data from the health management information system in the Democratic Republic of the Congo and the advent of COVID-19 pandemic as an illustrative case study, we implemented seven commonly used imputation methods and evaluated their performance in terms of minimizing bias in imputed values and parameter estimates generated through subsequent analytical techniques, namely segmented regression, which is widely used in interrupted time series studies, and pre-post-comparisons through paired Wilcoxon rank-sum tests. We also examined the performance of these imputation methods under different missing mechanisms and tested their stability to changes in the data. RESULTS: For regression analyses, there were no substantial differences found in the coefficient estimates generated from all methods except mean imputation and exclusion and interpolation when the data contained less than 20% missing values. However, as the missing proportion grew, k-NN started to produce biased estimates. Machine learning algorithms, i.e. missForest and k-NN, were also found to lack robustness to small changes in the data or consecutive missingness. On the other hand, multiple imputation methods generated the overall most unbiased estimates and were the most robust to all changes in data. They also produced smaller standard errors than single imputations. For pre-post-comparisons, all methods produced p values less than 0.01, regardless of the amount of missingness introduced, suggesting low sensitivity of Wilcoxon rank-sum tests to the imputation method used. CONCLUSIONS: We recommend the use of multiple imputation in addressing missing values in RHIS datasets and appropriate handling of data structure to minimize imputation standard errors. In cases where necessary computing resources are unavailable for multiple imputation, one may consider seasonal decomposition as the next best method. Mean imputation and exclusion and interpolation, however, always produced biased and misleading results in the subsequent analyses, and thus, their use in the handling of missing values should be discouraged.

Routine Health Information Systems in the European Context: A Systematic Review of Systematic Reviews.

(1) Background: The aim of this study is to provide a better understanding of the requirements to improve routine health information systems (RHISs) for the management of health systems, including the identification of best practices, opportunities, and challenges in the 53 countries and territories of the WHO European region. (2) Methods: We conducted an overview of systematics reviews and searched the literature in the databases MEDLINE/PubMed, Cochrane, EMBASE, and Web of Science electronic databases. After a meticulous screening, we identified 20 that met the inclusion criteria, and RHIS evaluation results were presented according to the Performance of Routine Information System Management (PRISM) framework. (3) Results: The reviews were published between 2007 and 2020, focusing on the use of different systems or technologies and aimed to analyze interventions on professionals, centers, or patients' outcomes. All reviews examined showed variability in results in accordance with the variability of interventions and target populations. We have found different areas for improvement for RHISs according to the three determinants of the PRISM framework that influence the configuration of RHISs: technical, organizational, or behavioral elements. (4) Conclusions: RHIS interventions in the European region are promising. However, new global and international strategies and the development of tools and mechanisms should be promoted to highly integrate platforms among European countries.

Rapid assessment on the utilization of maternal and child health services during COVID-19 in Rwanda.

SETTING: All public health facilities in Rwanda, East Africa. OBJECTIVE: To assess the change in the utilization of maternal and child health (MCH) services during the COVID-19 outbreak. DESIGN: This was a cross-sectional quantitative study. RESULTS: During the COVID-19 outbreak in Rwanda, the utilization of 15 MCH services in all four categories-antenatal care (ANC), deliveries, postnatal care (PNC) and vaccinations-significantly declined. The Northern and Western Provinces were affected the most, with significant decrease in respectively nine and 12 services. The Eastern Province showed no statistically significant utilization changes. Kigali was the only province with significant increase in the fourth PNC visits for babies and mothers, while the Southern Province showed significant increase in utilization of measles + rubella (MR) 1 vaccination. CONCLUSION: Access and utilization of basic MCH services were considerably affected during the COVID-19 outbreak in Rwanda. This study highlighted the need for pre-emptive measures to avoid disruptions in MCH service delivery and routine health services during outbreaks. In order for the reductions in MCH service utilization to be reversed, targeted resources and active promotion of ANC, institutional deliveries and vaccinations need to be prioritized. Further studies on long-term impact and geographical variations are needed.

CONTEXTE: Toutes les structures de santé publique au Rwanda, Afrique de l'Est. OBJECTIF: Evaluer les modifications de l'utilisation des services de santé maternelle et infantile (MCH) pendant la flambée de COVID-19. SCHÉMA: Ceci est une étude quantitative transversale. RÉSULTATS: Pendant la flambée de COVID-19 au Rwanda, l'utilisation de 15 services de MCH des quatre catégories­soins prénataux (ANC), accouchements, soins post natals (PNC) et vaccinations­ont significativement décliné. Les provinces du Nord et de l'Ouest ont été les plus affectées, avec une diminution significative dans neuf et douze services respectivement. La province de l'Est n'a pas montré de modifications statistiquement significatives de l'utilisation. Kigali a été la seule province ayant eu une augmentation significative dans les soins postnataux (PNC 4) pour les bébés et les mères, tandis que la province du Sud a montré une augmentation significative de l'utilisation du premier vaccin rougeole et rubéole (MR). CONCLUSION: L'accès et l'utilisation des services de base de MCH ont été considérablement affectés pendant la flambée de COVID-19 au Rwanda. Cette étude a mis en lumière le besoin de mesures préventives pour éviter les perturbations de la fourniture de services de MCH et des services de santé de routine pendant les épidémies. Pour éviter les réductions de l'utilisation des services de MCH, des ressources ciblées et une promotion active des soins anténataux, des accouchements en institution et des vaccinations doivent avoir priorité. D'autres études sur l'impact à long terme et les variations géographiques sont requises.