Arquitetura de saúde pública

Um dos oito princípios orientadores da transformação digital no setor de saúde promovidos pela Organização Pan-Americana de Saúde é a arquitetura de saúde pública. Esta sinopse de políticas apresenta conceitos-chave, linhas de ação recomendadas e indicadores para monitoramento, com o objetivo de avançar nesse domínio.

Mortality Associated with Priority Diseases in Flood-Affected Areas Using District Health Information System (DHIS2) During September-December 2022: Pakistan Experience.

OBJECTIVES: To quantify the burden of communicable diseases and characterize the most reported infections during public health emergency of floods in Pakistan. METHODS: The study's design is a descriptive trend analysis. The study utilized the disease data reported to District Health Information System (DHIS2) for the 12 most frequently reported priority diseases under the Integrated Disease Surveillance and Response (IDSR) system in Pakistan. RESULTS: In total, there were 1,532,963 suspected cases during August to December 2022 in flood-affected districts (n = 75) across Pakistan; Sindh Province reported the highest number of cases (n = 692,673) from 23 districts, followed by Khyber Pakhtunkhwa (KP) (n = 568,682) from 17 districts, Balochistan (n = 167,215) from 32 districts, and Punjab (n = 104,393) from 3 districts. High positivity was reported for malaria (79,622/201,901; 39.4%), followed by acute diarrhea (non-cholera) (23/62; 37.1%), hepatitis A and E (47/252; 18.7%), and dengue (603/3245; 18.6%). The crude mortality rate was 11.9 per 10 000 population (1824/1,532,963 [deaths/cases]). CONCLUSION: The study identified acute respiratory infection, acute diarrhea, malaria, and skin diseases as the most prevalent diseases. This suggests that preparedness efforts and interventions targeting these diseases should be prioritized in future flood response plans. The study highlights the importance of strengthening the IDSR as a Disease Early Warning System through the implementation of the DHIS2.

Building consensus on common features and interoperability use cases for community health information systems: a Delphi study.

INTRODUCTION: Information systems for community health have become increasingly sophisticated and evidence-based in the last decade and they are now the most widely used health information systems in many low-income and middle-income countries. This study aimed to establish consensus regarding key features and interoperability priorities for community health information systems (CHISs). METHODS: A Delphi study was conducted among a systematically selected panel of CHIS experts. This impressive pool of experts represented a range of leading global health institutions, with gender and regional balance as well as diversity in their areas of expertise. Through five rounds of iterative surveys and follow-up interviews, the experts established a high degree of consensus. We supplemented the Delphi study findings with a series of focus group discussions with 10 community health worker (CHW) leaders. RESULTS: CHISs today are expected to adapt to a wide range of local contextual requirements and to support and improve care delivery. While once associated with a single role type (CHWs), these systems are now expected to engage other end users, including patients, supervisors, clinicians and data managers. Of 30 WHO-classified digital health interventions for care providers, experts identified 23 (77%) as being important for CHISs. Case management and care coordination features accounted for more than one-third (14 of 37, 38%) of the core features expected of CHISs today, a higher proportion than any other category. The highest priority use cases for interoperability include CHIS to health management information system monthly reporting and CHIS to electronic medical record referrals. CONCLUSION: CHISs today are expected to be feature-rich, to support a range of user roles in community health systems, and to be highly adaptable to local contextual requirements. Future interoperability efforts, such as CHISs in general, are expected not only to move data efficiently but to strengthen community health systems in ways that measurably improve care.

Assessing intersectional gender analysis in Nepal's health management information system: a case study on tuberculosis for inclusive health systems.

BACKGROUND: Tuberculosis (TB) remains a major public health problem in Nepal, high in settings marked by prevalent gender and social inequities. Various social stratifiers intersect, either privileging or oppressing individuals based on their characteristics and contexts, thereby increasing risks, vulnerabilities and marganilisation associated with TB. This study aimed to assess the inclusiveness of gender and other social stratifiers in key health related national policies and the Health Management Information System (HMIS) of National Tuberculosis Programme (NTP) by conducting an intersectional analysis of TB cases recorded via HMIS. METHODS: A desk review of key policies and the NTP's HMIS was conducted. Retrospective intersectional analysis utilized two secondary data sources: annual NTP report (2017-2021) and records of 628 TB cases via HMIS 6.5 from two TB centres (2017/18-2018/19). Chi-square test and multi-variate analysis was used to assess the association between social stratifers and types of TB, registration category and treatment outcome. RESULTS: Gender, social inclusion and concept of intersectionality are incorporated into various health policies and strategies but lack effective implementation. NTP has initiated the collection of age, sex, ethnicity and location data since 2014/15 through the HMIS. However, only age and sex disaggregated data are routinely reported, leaving recorded social stratifiers of TB patients static without analysis and dissemination. Furthermore, findings from the intersectional analysis using TB secondary data, showed that male more than 25 years exhibited higher odds [adjusted odds ratio (aOR) = 4.95, 95% confidence interval (CI): 1.60-19.06, P = 0.01)] of successful outcome compared to male TB patients less than 25 years. Similarly, sex was significantly associated with types of TB (P < 0.05) whereas both age (P < 0.05) and sex (P < 0.05) were significantly associated with patient registration category (old/new cases). CONCLUSIONS: The results highlight inadequacy in the availability of social stratifiers in the routine HMIS. This limitation hampers the NTP's ability to conduct intersectional analyses, crucial for unveiling the roles of other social determinants of TB. Such limitation underscores the need for more disaggregated data in routine NTP to better inform policies and plans contributing to the development of a more responsive and equitable TB programme and effectively addressing disparities.

How Can Community Data Be Leveraged to Advance Primary Health Care? A Scoping Review of Community-Based Health Information Systems.

BACKGROUND: Community-based health information systems (CBISs) can provide critical insights into how community health systems function, and digitized CBISs may improve the quality of community-level data and facilitate integration and use of CBISs within the broader health system. This scoping review aims to understand how CBISs have been implemented, integrated, and used to support community health outcomes in low- and middle-income countries (LMICs). METHODS: Both peer-reviewed and gray literature were included; relevant articles were identified using key terms and controlled vocabulary related to community/primary health care, health information systems, digital health, and LMICs. A total of 11,611 total records were identified from 5 databases and the gray literature. After deduplication, 6,985 peer-reviewed/gray literature were screened, and 95 articles/reports were included, reporting on 105 CBIS implementations across 38 countries. RESULTS: Findings show that 55% of CBISs included some level of digitization, with just 28% being fully digitized (for data collection and reporting). Data flow from the community level into the health system varied, with digitized CBISs more likely to reach national-level integration. National-level integration was primarily seen among vertical CBISs. Data quality challenges were present in both paper-based and digitized CBISs, exacerbated by fragmentation of the community health landscape with often parallel reporting systems. CBIS data use was constrained to mostly vertical and digitized (partially or fully) CBISs at national/subnational levels. CONCLUSION: Digitization can play a pivotal role in strengthening CBIS use, but findings demonstrate that CBISs are only as effective as the community health systems they are embedded within. Community-level data are often not being integrated into national/subnational health information systems, undermining the ability to understand what the community health needs are. Furthermore, stronger investments within community health systems need to be in place broadly to reduce fragmentation and provide stronger infrastructural and systemic support to the community health workforce.

Proporção de casos nosocomiais de COVID-19 no Brasil: análise de seus fatores associados em 1.631.47 registros de 2020 a 2022 / Proporción de casos nosocomiales de COVID-19 en Brasil: análisis de sus factores asociados en 1.631.47 registros de 2020 a 2022 / Proportionof nosocomial cases of COVID-19 in Brazil: analysisof1.631.47 case records from 2020 to 2022

Introdução: Infecções nosocomiais, adquiridas após a internação hospitalar, são o evento adverso mais comum que ameaça a saúde dos pacientes hospitalizados, sendo a pneumonia, incluindo a causada pelo SARS-Cov-2, responsável por mais de 80% das infecções nosocomiais. A pandemia declarada pela OMS em março de 2020 reflete o rápido aumento de casos, impulsionado pela disseminação do vírus através de gotículas e aerossóis. A transmissão nosocomial do SARS-Cov-2 foi observada desde o início do surto em Wuhan, representando um desafio adicional na qualidade de vida dos pacientes. Estudos internacionais em hospitais reportam incidências de infecção nosocomial por COVID-19 entre 11% e 44%.Objetivo: Identificar a proporção de infecção nosocomial por SARS-COV-2 no Brasil entre março de 2020 até dezembro de 2022.Metodologia:Trata-se de um estudo analítico, retrospectivo, de corte transversal, sobre a proporção de infecção nosocomial por Sars-Cov-2 no Brasil, através de dados secundários oriundos do Sistema de Informação da Vigilância Epidemiológica da Gripe. No presente estudo a variável dependente analisada foi a proporção de infecção nosocomial por Sars-cov-2. Como variáveis independentes exploratórias foram utilizadas: faixa etária, sexo, comorbidades e macrorregião de residência. Resultados: O estudo identificou uma proporção de casos nosocomiais de 2,58%, sendo maior no terceiro ano da pandemia 2022 (5,5%) na região Norte (7,57%), entre os indivíduos de 18-59 anos de idade (6,93%)Conclusões: Este estudo sobre casos nosocomiais de COVID-19 no Brasil revela uma proporção de 2,58% entre 2020 e 2022, com associações identificadas em relação à região, idade e comorbidades. Diferenças em relação a estudos internacionais sugerem questões metodológicas específicas. Essa pesquisa é de importância crítica, visto ser de abrangência nacional com grande amplitude, e estabelece uma base sólida para futuros estudos epidemiológicos (AU).

Introduction: Nosocomial infections, acquired after hospital admission, are the most common adverse events threatening patient health, with pneumonia, including that caused by SARS-CoV-2, responsible for over 80% of nosocomial infections. The pandemic declared by the WHO in March 2020 reflects the rapid rise in cases driven by the virus's spread through droplets and aerosols. Nosocomial transmission of SARS-CoV-2 has been observed since the outbreak's onset in Wuhan, posing an additional challenge to patient quality of life. International hospital studies report nosocomial COVID-19 infection rates between 11% and 44%. Objective: Identifying the proportion of nosocomial SARS-CoV-2 infection in Brazil between March 2020 and December 2022.Methodology:This is an analytical, retrospective, cross-sectional study on the proportion of nosocomial SARS-CoV-2 infection in Brazil, using secondary data from the Influenza Epidemiological Surveillance Information System. In this study, the analyzed dependent variable was the proportionof nosocomial SARS-CoV-2 infection. The exploratory independent variables included: age group, gender, comorbidities, and macro-region of residence.Results:The study identified a proportion of nosocomial cases of 2.58%, with a higher proportion in the third year of the pandemic, 2022 (5.5%) in the North region (7.57%), among individuals aged 18-59 years (6.93%). Conclusions: This study on nosocomial cases of COVID-19 in Brazil reveals a proportion of 2.58% between 2020 and 2022, with associations identified regarding region, age, and comorbidities. Differences compared to international studies suggest specific methodological issues. This research is of critical importance, given its national scope and broad coverage, and establishes a solid foundation for future epidemiological studies (AU).

Introducción: Las infecciones nosocomiales, adquiridas tras la hospitalización, son el evento adverso más común que amenaza la salud de los pacientes hospitalizados, siendo la neumonía, incluida la causada por el SARS-Cov-2, la responsable de más del 80% de las infecciones. La pandemia declarada por la OMS en marzo de 2020 refleja el rápido aumento de casos, impulsado por la propagación del virus a través de gotitas y aerosoles. La transmisión nosocomial del SRAS-Cov-2 se ha observado desde el inicio del brote en Wuhan, lo que supone un reto adicional para la calidad de vida de los pacientes. Estudios internacionales realizados en hospitales informan de incidencias de infecciones nosocomiales por COVID-19 de entre el 11% y el 44%. Objetivo: Identificar la proporción de infección nosocomial por SARS-CoV-2 en Brasil entre marzo de 2020 y diciembre de 2022. Metodología: Se trata de un estudio analítico, retrospectivo y transversal sobre la proporción de infección nosocomial por SARS-CoV -2 en Brasil, utilizando datos secundarios del Sistema de Información de Vigilancia Epidemiológica de Influenza. La variable dependiente analizada fue la proporción de infección nosocomial por SARS-CoV-2. Como variables independientes exploratorias se utilizaron: grupo de edad, sexo, comorbilidades y macrorregión de residencia. Resultados:El estudio identificó una proporción de casos nosocomiales del 2,58%, siendo mayor en el tercer año de la pandemia de 2022 (5,5%) en la región Norte (7,57%), entre individuos de 18 a 59 años (6,93%). Conclusiones:Este estudio de casos de COVID-19 hospitalizados en Brasil revela una proporción de 2,58% entre 2020 y 2022, con asociaciones identificadas en relación a la región, edad y comorbilidades. Las disparidades en relación a estudios internacionales sugieren la presencia de cuestiones metodológicas específicas. Esta investigación es de extrema importancia para orientar estrategias preventivas y mejorar el control de las infecciones hospitalarias (AU).

Mortalidade por violência autoprovocada em mulheres em idade fértil no Rio Grande do Norte / Mortalidad por violencia autoprovocada en mujeres en edad fértil en Rio Grande do Norte / Mortality by self-inflicted injury in fertile women of Rio Grande to Norte state

Introdução:A violência autoprovocada é um importante problema de saúde pública. Esse agravo produz impactos no campo da saúde do indivíduo, da família eda coletividade com desdobramentos sociais e econômicos. Objetivo:Analisar a mortalidade por violência autoprovocada em mulheres em idade fértil no estado do Rio Grande do Norte, Brasil, entre os anos de 2012 e 2021. Metodologia:Trata-se de um estudo ecológico com abordagem quantitativa e utiliza-se como base o estado do Rio Grande do Norte. Os dados foram coletados do Departamento de Informática do Sistema Único de Saúde, por meio das Informações em Saúde,nas seções de estatísticas vitais e população residente com a seleção sexo feminino e faixa etária de 10 a 49 anos.Resultados:Entre os anos de 2012 a 2021, no estado do Rio Grande do Norte,foram registrados 213 óbitos de mulheres em idade fértil por lesões autoprovocadas. Considerando o início e o final desse período, é possível destacar que a faixa etária de maior ocorrência de suicídio foi de 30 a 39 anos em 2012 e de 40 a 49 anos em 2021. Observou-se, nos anos avaliados, que as mulheres eram em sua maioria solteiras, de raça parda/preta e que a própria residência da vítima foi o local predominante para o desfecho da lesão autoprovocada. No que se refere à escolaridade e à relação do óbito com período de gravidez ou puerpério é preciso ressaltar o alto índice de "Não informada" e "Ignorada" nos registros.A taxa média de mortalidade por lesões autoprovocadas em mulheres em idade fértil entre 2012 e 2021 foi de 2,0 óbitos por cada 100.000 habitantes. Conclusões:Assim, conclui-se que o cenário da mortalidade por violência autoprovocada em mulheres em idade fértil no Rio Grande do Norte necessita de estratégias para prevenção do suicídio nessa faixa etária (AU).

Introduction: Self-inflicted injury is a major public health problem that impacts the health, social, and economic areas of individuals, their families, and society. Aim: To analyze mortality by self-inflicted injury in fertile women from the Rio Grande do Norte state between 2012 and 2021.Methodology: This ecologic and quantitative study collected vital statistics of women aged between 10 and 49 years. Data were obtained from the Health Information Systems of the Brazilian Health Informatics Department.Results: A total of 213 deaths of fertile women by self-inflicted injury were registered between 2012 and 2021. Considering the age groups, most deaths occurred between 30 and 39 years in 2012 and between 40 and 49 years in 2021. In addition, women were mostly single andwith brown or black skin color, and most of the self-inflicted injuries happened at their houses. Regarding education level and the relationship of death with pregnancy or postpartum, most registries presented a high incidence of "Not informed" or "Ignored" answers. Last, the mean mortality by self-inflicted injury in this population was 2.0 per 100,000 inhabitants between 2012 and 2021.Conclusions: Strategies must be implemented to reduce the mortality by self-inflicted injury of fertile women from the Rio Grande do Norte state (AU).

Introducción: La violencia autoinfligida es un importante problema de salud pública. Este problema tiene impactos en la salud del individuo, la familia y la comunidad con consecuencias sociales y económicas.Objetivo: Analizar la mortalidad por violencia autoinfligida en mujeres en edad fértil en el estado de Rio Grande do Norte, Brasil, entre los años 2012 y 2021.Metodología: Se trata de un estudio ecológico con enfoque cuantitativo y utiliza como base el estado de Rio Grande do Norte. Los datos fueron recolectados del Departamento de Tecnologías de la Información del Sistema Único de Salud, a través de Información en Salud, en las secciones de estadísticas vitales y población residente con la selección del género femenino y rango de edad de 10 a 49 años. Resultados: Entre los años 2012 y 2021, en el estado de Rio Grande do Norte, se registraron 213 muertes de mujeres en edad fértil por lesiones autoinfligidas. Considerando el inicio y final de este periodo, es posible resaltar que el grupo etario con mayor incidencia de suicidio fue el de 30 a 39 años en 2012 y el de 40 a 49 años en 2021. Se observó, en los años evaluados, que las mujeres eran en su mayoría solteras, de raza mestiza/negra y la propia residencia de la víctima era el lugar predominante para la autolesión. En lo que respecta a la educación y la relación entre muerte y embarazo o puerperio, es necesario resaltar el alto índice de "No informados" e "Ignorados" en los registros. La tasa media de mortalidad por autolesiones en mujeres en edad fértil entre 2012 y 2021 fue de 2,0 muertes por 100.000 habitantes. Conclusiones: Así, se concluye que el escenario de mortalidad por violencia autoinfligida en mujeres en edad fértil en Rio Grande do Norte requiere estrategias para prevenir el suicidio en este rango de edad (AU).

Intention to Use an Electronic Community Health Information System Among Health Extension Workers in Rural Northwest Ethiopia: Cross-Sectional Study Using the Unified Theory of Acceptance and Use of Technology 2 Model.

BACKGROUND: IT has brought remarkable change in bridging the digital gap in resource-constrained regions and advancing the health care system worldwide. Community-based information systems and mobile apps have been extensively developed and deployed to quantify and support health services delivered by community health workers. The success and failure of a digital health information system depends on whether and how it is used. Ethiopia is scaling up its electronic community health information system (eCHIS) to support the work of health extension workers (HEWs). For successful implementation, more evidence was required about the factors that may affect the willingness of HEWs to use the eCHIS. OBJECTIVE: This study aimed to assess HEWs' intentions to use the eCHIS for health data management and service provision. METHODS: A cross-sectional study design was conducted among 456 HEWs in 6 pilot districts of the Central Gondar zone, Northwest Ethiopia. A Unified Theory of Acceptance and Use of Technology model was used to investigate HEWs' intention to use the eCHIS. Data were cleaned, entered into Epi-data (version 4.02; EpiData Association), and exported to SPSS (version 26; IBM Corp) for analysis using the AMOS 23 Structural Equation Model. The statistical significance of dependent and independent variables in the model was reported using a 95% CI with a corresponding P value of <.05. RESULTS: A total of 456 HEWs participated in the study, with a response rate of 99%. The mean age of the study participants was 28 (SD 4.8) years. Our study revealed that about 179 (39.3%; 95% CI 34.7%-43.9%) participants intended to use the eCHIS for community health data generation, use, and service provision. Effort expectancy (ß=0.256; P=.007), self-expectancy (ß=0.096; P=.04), social influence (ß=0.203; P=.02), and hedonic motivation (ß=0.217; P=.03) were significantly associated with HEWs' intention to use the eCHIS. CONCLUSIONS: HEWs need to be computer literate and understand their role with the eCHIS. Ensuring that the system is easy and enjoyable for them to use is important for implementation and effective health data management.

Incomplete recording of race/colour in health information systems in Brazil: time trend, 2009-2018. / Tendência temporal da incompletude do registro da raça/cor nos sistemas de informação em saúde do Brasil, 2009-2018.

This ecological study of time trends and multiple groups evaluated incompleteness in the race/colour field of Brazilian health information system records and the related time trend, 2009-2018, for the diseases and disorders most prevalent in the black population. The Romero and Cunha (2006) classification was applied in order to examine incompleteness using secondary data from Brazil's National Notifiable Diseases System, Hospital Information System and Mortality Information System, by administrative regions of Brazil, while percentage underreporting and time trend were calculated using simple linear regression models with Prais-Winsten correction (p-value<0.05). All records scored poorly except those for mortality from external causes (excellent), tuberculosis (good) and infant mortality (fair). An overall downward trend was observed in percentage incompleteness. Analysis by region found highest mean incompleteness in the North (30.5%), Northeast (33.3%) and Midwest (33.0%) regions. The Southeast and Northeast regions showed the strongest downward trends. The findings intended to increase visibility on the implications of the race/color field for health equity.

Propõe-se avaliar a incompletude e a tendência temporal do preenchimento do campo raça/cor das doenças e agravos mais prevalentes na população negra nos Sistemas de Informação em Saúde do Brasil, 2009-2018. Trata-se de estudo ecológico de tendência temporal e múltiplos grupos. Foi adotada a classificação de Romero e Cunha (2006) para análise da incompletude e utilizados dados secundários do Sistema Nacional de Agravos de Notificação, Sistema de Informações Hospitalares e Sistema de Informações sobre Mortalidade do Brasil e regiões brasileiras, calculada a proporção de subnotificação e a tendência temporal, utilizando o modelo de regressão linear simples, com correção Prais-Winsten (p-valor<0,05). Excetuando-se os registros de mortalidade por causas externas (excelente), tuberculose (bom) e mortalidade infantil (regular), todos os registros apresentaram escore ruim. Observou-se tendência decrescente da proporção de incompletude. A análise por região mostrou que as maiores médias de incompletude foram registradas na região Norte (30,5%), Nordeste (33,3%) e Centro-Oeste (33,0%). As regiões Sudeste e Nordeste foram as que mais apresentaram tendência decrescente. Os resultados visam ampliar a visibilidade acerca das implicações do preenchimento do campo raça/cor para a equidade em saúde.

Searchable Blockchain-Based Healthcare Information Exchange System to Enhance Privacy Preserving and Data Usability.

Ensuring the security and usability of electronic health records (EHRs) is important in health information exchange (HIE) systems that handle healthcare records. This study addressed the need to balance privacy preserving and data usability in blockchain-based HIE systems. We propose a searchable blockchain-based HIE system that enhances privacy preserving while improving data usability. The proposed methodology includes users collecting healthcare information (HI) from various Internet of Medical Things (IoMT) devices and compiling this information into EHR blocks for sharing on a blockchain network. This approach allows participants to search and utilize specific health data within the blockchain effectively. The results demonstrate that the proposed system mitigates the issues of traditional HIE systems by providing secure and user-friendly access to EHRs. The proposed searchable blockchain-based HIE system resolves the trade-off dilemma in HIE by achieving a balance between security and the data usability of EHRs.

EHR-BERT: A BERT-based model for effective anomaly detection in electronic health records.

OBJECTIVE: Physicians and clinicians rely on data contained in electronic health records (EHRs), as recorded by health information technology (HIT), to make informed decisions about their patients. The reliability of HIT systems in this regard is critical to patient safety. Consequently, better tools are needed to monitor the performance of HIT systems for potential hazards that could compromise the collected EHRs, which in turn could affect patient safety. In this paper, we propose a new framework for detecting anomalies in EHRs using sequence of clinical events. This new framework, EHR-Bidirectional Encoder Representations from Transformers (BERT), is motivated by the gaps in the existing deep-learning related methods, including high false negatives, sub-optimal accuracy, higher computational cost, and the risk of information loss. EHR-BERT is an innovative framework rooted in the BERT architecture, meticulously tailored to navigate the hurdles in the contemporary BERT method; thus, enhancing anomaly detection in EHRs for healthcare applications. METHODS: The EHR-BERT framework was designed using the Sequential Masked Token Prediction (SMTP) method. This approach treats EHRs as natural language sentences and iteratively masks input tokens during both training and prediction stages. This method facilitates the learning of EHR sequence patterns in both directions for each event and identifies anomalies based on deviations from the normal execution models trained on EHR sequences. RESULTS: Extensive experiments on large EHR datasets across various medical domains demonstrate that EHR-BERT markedly improves upon existing models. It significantly reduces the number of false positives and enhances the detection rate, thus bolstering the reliability of anomaly detection in electronic health records. This improvement is attributed to the model's ability to minimize information loss and maximize data utilization effectively. CONCLUSION: EHR-BERT showcases immense potential in decreasing medical errors related to anomalous clinical events, positioning itself as an indispensable asset for enhancing patient safety and the overall standard of healthcare services. The framework effectively overcomes the drawbacks of earlier models, making it a promising solution for healthcare professionals to ensure the reliability and quality of health data.

Oncology Nurses' Experiences of Using Health Information Systems in the Delivery of Cancer Care in a Range of Care Settings: A Systematic Integrative Review.

OBJECTIVES: This systematic review aimed to identify oncology nurses' experiences of using health information systems (HIS) in the delivery of cancer care. DATA SOURCES: The electronic databases searched included CINAHL, MEDLINE (EBSCO host), SCOPUS, Web of Science Core Collection, Google Scholar, OVID, and ProQuest Central (using advanced search strategy) and hand searching of reference lists of the included articles and relevant systematic reviews. Studies published in English language were examined. CONCLUSION: Twenty-six studies were included. Three themes emerged: (1) the transparency and application of the nursing process within HIS, (2) HIS enhancing and facilitating communication between nurses and patients, and (3) the impact of HIS on the elements of person-centered care. Nurses' experiences with HIS were overall positive. However, digital systems do not fully capture all elements of the nursing processes; this was confirmed in this review, through the nurses' lens. Most studies used HIS for symptom reporting and monitoring within non-inpatient settings and largely biomedical and lack insight into the person-centeredness and overall holistic care. IMPLICATIONS FOR NURSING PRACTICE: There are evidently varied views of HIS adoption across the globe. HIS can improve health-related quality of life and symptom burden, including self-reporting of symptoms among patients. However, there is a need for ongoing high-quality research, and clearer reporting than is evident in the current 26 studies, to fully understand the impact of HIS within the nursing processes and patient outcomes across all specialty cancer fields.

Securing the future of IoT-healthcare systems: A meta-synthesis of mandatory security requirements.

INTRODUCTION: Healthcare-based Internet of Things (Healthcare-IoT) is a turning point in the development of health information systems. This emerging trend significantly contributes to enhancing users' awareness of their health, ultimately leading to an extension in life expectancy. Security and privacy are among the greatest challenges for H-IoT systems. To establish complete safety and security in these systems, the implementation of mandatory security requirements is imperative. For this reason, this study identifies the necessary security requirements for H-IoT systems using a Meta-Synthesis approach. METHODS: Initially, following the Seven-Stage Sandelowski & Barroso approach, the existing literature was searched in the Scopus and Web of Science databases. Among the 844 extracted articles from the period of 2010 to 2020, 78 final articles were reviewed and analyzed, leading to the identification of 51 security requirements. Subsequently, to assess the quality of the identified requirements and their overlap, interviews were conducted with two experts. RESULTS: Finally, 14 security requirements, predominantly with technical and quantitative aspects, were identified for designing a Healthcare-IoT system and implementing security mechanisms. CONCLUSION: The findings of this study emphasize that addressing the identified 14 security requirements is crucial for safeguarding Healthcare-IoT systems and ensuring their robustness in the evolving health information landscape.

Data-driven decision-making for district health management: a cluster-randomised study in 24 districts of Ethiopia.

BACKGROUND: Use of local data for health system planning and decision-making in maternal, newborn and child health services is limited in low-income and middle-income countries, despite decentralisation and advances in data gathering. An improved culture of data-sharing and collaborative planning is needed. The Data-Informed Platform for Health is a system-strengthening strategy which promotes structured decision-making by district health officials using local data. Here, we describe implementation including process evaluation at district level in Ethiopia, and evaluation through a cluster-randomised trial. METHODS: We supported district health teams in 4-month cycles of data-driven decision-making by: (a) defining problems using a health system framework; (b) reviewing data; (c) considering possible solutions; (d) value-based prioritising; and (e) a consultative process to develop, commit to and follow up on action plans. 12 districts were randomly selected from 24 in the North Shewa zone of Ethiopia between October 2020 and June 2022. The remaining districts formed the trial's comparison arm. Outcomes included health information system performance and governance of data-driven decision-making. Analysis was conducted using difference-in-differences. RESULTS: 58 4-month cycles were implemented, four or five in each district. Each focused on a health service delivery challenge at district level. Administrators' practice of, and competence in, data-driven decision-making showed a net increase of 77% (95% CI: 40%, 114%) in the regularity of monthly reviews of service performance, and 48% (95% CI: 9%, 87%) in data-based feedback to health facilities. Statistically significant improvement was also found in administrators' use of information to appraise services. Qualitative findings also suggested that district health staff reported enhanced data use and collaborative decision-making. CONCLUSIONS: This study generated robust evidence that 20 months' implementation of the Data-Informed Platform for Health strengthened health management through better data use and appraisal practices, systemised problem analysis to follow up on action points and improved stakeholder engagement. TRIAL REGISTRATION NUMBER: NCT05310682.

Differences in antibiotic use between COPD and non-COPD residents based on the health information system.

OBJECTIVES: To compare the differences in antibiotic use between COPD and non-COPD residents, and to explore the effect of COPD on antibiotic use. METHODS: Participants aged 40 years old or over from the Songjiang Adult Cohort were included. Information on prescription and baseline survey was collected based on the health information system. A logit-negative binomial Hurdle model was used to explore correlations between COPD and percentage of antibiotic use and average rate of antibiotic prescribing of different types of antibiotic. Multinomial logistic regression was used to assess the association between COPD and antimicrobial combination therapy and routes of administration. RESULTS: A total of 34576 individuals were included and 1594 (4.6%) were COPD patients. During the 6 years' follow-up, the percentage of antibiotic use for COPD patients was 98.4%, which was 7.88 (95%CI: 5.24-11.85) times of that for non-COPD patients after adjusting for potential confounders. The prescribing rate was 3220 prescriptions (95%CI: 3063.6-3385.2) per 1000 person-years for COPD patients, which was 1.96 (95%CI: 1.87-2.06) times of that for non-COPD patients. Other beta-lactam antibacterials, Macrolides, lincosamides and streptogramins, and quinolone antibacterials were the most commonly used types of antibiotic. Except for aminoglycoside antibacterials, both percentage of antibiotic use and rate of antibiotic prescription were increased in COPD patients. COPD patients were more likely to be prescribed a maximum of two antibiotics (OR=1.34, 95%CI: 1.20-1.50); and were more likely to use antibiotics intravenously (OR=2.77, 95%CI: 2.47-3.11). CONCLUSION: COPD patients were more likely to have increased antibiotic use in a large-scale population-based adult cohort, suggesting COPD patients are a high-priority group for the management of antibiotic use in communities.

Usability and Evaluation of a Health Information System in the Emergency Department: Mixed Methods Study.

BACKGROUND: A lack of information during an emergency visit leads to the experience of powerlessness for patients and their family members, who may also feel unprepared to cope with acute symptoms. The ever-changing nature and fast-paced workflow in the emergency department (ED) often affect how health care professionals can tailor information and communication to the needs of the patient. OBJECTIVE: This study aimed to evaluate the usability and experience of a newly developed information system. The system was developed together with patients and their family members to help provide the information needed in the ED. METHODS: We conducted a mixed methods study consisting of quantitative data obtained from the System Usability Scale questionnaire and qualitative interview data obtained from purposively selected participants included in the quantitative part of the study. RESULTS: A total of 106 patients and 14 family members (N=120) answered the questionnaire. A total of 10 patients and 3 family members participated in the interviews. Based on the System Usability Scale score, the information system was rated close to excellent, with a mean score of 83.6 (SD 12.8). Most of the participants found the information system easy to use and would like to use it again. The participants reported that the system helped them feel in control, and the information was useful. Simplifications were needed to improve the user experience for the older individuals. CONCLUSIONS: This study demonstrates that the usability of the information system is rated close to excellent. It was perceived to be useful as it enabled understanding and predictability of the patient's trajectory in the ED. Areas for improvement include making the system more usable by older individuals. The study provides an example of how a technological solution can be used to diminish the information gap in an ED context.

Effect of patient factors, center, and era on Fontan timing: An observational study using the Pediatric Health Information Systems Database.

BACKGROUND: There are no consensus guidelines defining optimal timing for the Fontan operation, the last planned surgery in staged palliation for single-ventricle heart disease. OBJECTIVES: Identify patient-level characteristics, center-level variation, and secular trends driving Fontan timing. METHODS: A retrospective observational study of subjects who underwent Fontan from 2007 to 2021 at centers in the Pediatric Health Information Systems database was performed using linear mixed-effects modeling in which age at Fontan was regressed on patient characteristics and date of operation with center as random effect. RESULTS: We included 10,305 subjects (40.4% female, 44% non-white) at 47 centers. Median age at Fontan was 3.4 years (IQR 2.6-4.4). Hypoplastic left heart syndrome (-4.4 months, 95%CI -5.5 to -3.3) and concomitant conditions (-2.6 months, 95%CI -4.1 to -1.1) were associated with younger age at Fontan. Subjects with technology-dependence (+4.6 months, 95%CI 3.1-6.1) were older at Fontan. Black (+4.1 months, 95%CI 2.5-5.7) and Asian (+8.3 months, 95%CI 5.4-11.2) race were associated with older age at Fontan. There was significant variation in Fontan timing between centers. Center accounted for 10% of variation (ICC 0.10, 95%CI 0.07-0.14). Center surgical volume was not associated with Fontan timing (P = .21). Operation year was associated with age at Fontan, with a 3.1 month increase in age for every 5 years (+0.61 months, 95%CI 0.48-0.75). CONCLUSIONS: After adjusting for patient-level characteristics there remains significant inter-center variation in Fontan timing. Age at Fontan has increased. Future studies addressing optimal Fontan timing are warranted.

Evaluation of the malaria case surveillance system in KwaZulu-Natal Province, South Africa, 2022: a focus on DHIS2.

BACKGROUND: South Africa set a target to eliminate malaria by 2023, with KwaZulu-Natal (KZN) Province the malaria-endemic province closest to achieving this goal. Objective two of the National Malaria Elimination Strategic Plan (NMESP) focused on strengthening surveillance systems to support the country's elimination efforts. Regular evaluations of the malaria surveillance systems against the targets of the NMESP objective are crucial in improving their performance and impact. This study aimed to assess whether the malaria surveillance system in KwaZulu-Natal Province meets the NMESP surveillance objective and goals. METHODS: A mixed-methods cross-sectional study design was used to evaluate the malaria surveillance system, focusing on the District Health Information System 2 (DHIS2). The study assessed the data quality, timeliness, simplicity, and acceptability of the system. Key personnel from KZN's Provincial malaria control programme were interviewed using self-administered questionnaires to evaluate their perception of the system's simplicity and acceptability. Malaria case data from January 2016 to December 2020 were extracted from the DHIS2 and evaluated for data quality and timeliness. RESULTS: The survey respondents generally found the DHIS2-based surveillance system acceptable (79%, 11/14) and easy to use (71%, 10/14), stating that they could readily find, extract, and share data (64%, 9/14). Overall data quality was good (88.9%), although some variables needed for case classification had low completeness and data availability. However, case notifications were not timely, with only 61% (2 622/4 329) of cases notified within 24 h of diagnosis. During the 5-year study period, the DHIS2 captured 4 333 malaria cases. The majority of cases (81%, 3 489/4 330) were categorized as imported, and predominately in males (67%, 2 914/4 333). CONCLUSION: While the malaria surveillance system in KZN Province largely met the NMESP surveillance strategic goals, it failed to achieve the overarching surveillance objective of 100% notification of cases within 24 h of diagnosis. The majority of reported cases in KZN Province were classified as imported, emphasizing the importance of complete data for accurate case classification. Engaging with healthcare professionals responsible for case notification and disseminating aggregated data back to them is needed to encourage and improve notification timeliness.

MoCab: A Model Management System Based on FHIR for Clinical Decision Support.

MoCab is a framework that deploys high-accuracy medical models across various health information systems (HISs) using fast healthcare interoperability resources (FHIR). MoCab simplifies the process by importing and configuring stored models and retrieving data for prediction. Two case studies illustrate how MoCab can be used to support decision-making. The proposed framework increases model reusability across EHRs and improves the clinical decision-making process.