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.

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.

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.

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.

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.

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.

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.

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.

[Evaluation of the impact of the implementation of the new primary health care information system on records of patient care and home visits in Brazil]. / Avaliação do impacto da implantação do novo sistema de informações da atenção primária à saúde nos registros de atendimentos e visitas domiciliares no Brasil.

The replacement of the Primary Care Information System (SIAB, 1998-2015), as of January 2016, by the new Health Information System for Primary Care (SISAB) determined new forms of collecting, processing, and using information, with a possible impact on the records of activities carried out in primary health care in Brazil. This study aimed to evaluate the implementation impact of the new information system on records of physicians' and nurses' patient care and home visits of community health workers (CHW) in Brazil from 2007 to 2019. To this end, a Bayesian structural time-series model approach was used, based on a diffuse state-space regression. From 2016 to 2019, 463.47 million physician care, 210.61 million nursing care, and 1.28 billion CHW visits were recorded. Following the trend recorded before the implementation, 598.86 million, 430.46 million, and 1.5 billion physician and nursing appointments and CHW visits would be expected, respectively. In relative terms, there was a decrease of 25% in physician care, 51% in nursing care, and 15% in CHW visits when compared to the value expected by the Bayesian method. The negative impact on the records of patient care and home visits identified in this study, whether due to difficulties in adapting to the new system or a reduction in improper records, must be investigated so that the challenge of improving the primary care information system can be understood and overcome in a planned way.

A substituição do Sistema de Informação da Atenção Básica (SIAB, 1998-2015), a partir de janeiro de 2016, pelo novo Sistema de Informação em Saúde para a Atenção Básica (SISAB) determinou novas formas de coleta, processamento e uso das informações, com possível impacto nos registros das atividades desenvolvidas na atenção primária à saúde no Brasil. O objetivo deste estudo foi avaliar o impacto da implantação do novo sistema de informação sobre registros de atendimentos de médicos e enfermeiros, e de visitas domiciliares de agentes comunitários de saúde (ACS) brasileiros entre 2007 e 2019. Para tal, utilizou-se uma abordagem bayesiana de modelo estrutural para séries temporais, com base em uma regressão difusa de espaço-estado. Ao longo do período de 2016 a 2019, foram registrados 463,47 milhões de atendimentos médicos, 210,61 milhões de atendimentos de enfermagem e 1,28 bilhão de visitas de ACS. Seguindo a tendência registrada antes da implantação, seriam esperados 598,86 milhões, 430,46 milhões e 1,5 bilhão de atendimentos de médicos, enfermeiros e visitas de ACS, respectivamente. Em termos relativos, houve um decréscimo de 25% nos atendimentos médicos, 51% nos atendimentos de enfermagem e 15% nas visitas de ACS quando comparado com o valor esperado pelo método bayesiano. O impacto negativo no registro de atendimentos e de visitas domiciliares identificado neste estudo, seja por dificuldade de adaptação ao novo sistema, seja por diminuição de registros indevidos, merece ser alvo de investigação para que se possa, de forma planejada, compreender e superar o desafio da melhoria do sistema de informação da atenção primária.

La sustitución del Sistema de Información de la Atención Básica (SIAB, 1998-2015), desde enero de 2016, por el nuevo Sistema de Información en Salud para la Atención Básica (SISAB) estableció nuevas maneras para recolectar, procesar y utilizar las informaciones, con posibles impactos en los registros de las actividades desarrolladas en la atención primaria de salud en Brasil. El objetivo de este estudio fue evaluar el impacto de la implantación del nuevo sistema de información sobre los registros de atención de médicos y enfermeros y de visitas domiciliarias de agentes comunitarios de salud (ACS) en Brasil entre 2007 y 2019. Para eso, se utilizó un enfoque bayesiano de modelo estructural para series temporales basadas en una regresión difusa de espacio de estado. Entre los años 2016 y 2019, se registraron 463,47 millones de consultas médicas, 210,61 millones de consultas de enfermería y 1,28 mil millones de visitas de ACS. Siguiendo la tendencia registrada antes de la implantación, se esperarían 598,86 millones, 430,46 millones y 1,5 mil millones de consultas médicas y de enfermería y visitas de ACS respectivamente. En términos relativos, hubo una disminución del 25% en las consultas médicas, del 51% en las consultas de enfermería y del 15% en las visitas de ACS en comparación con el valor esperado por el método bayesiano. El impacto negativo en el registro de consultas y visitas domiciliarias identificado en este estudio, ya sea por dificultades en la adaptación al nuevo sistema o por la disminución de los registros indebidos, merece ser objeto de investigación para que se pueda, de manera planificada, comprender y superar el desafío continuo de mejorar el sistema de información de la atención primaria.

Enhancing quality of life and medication adherence for people living with HIV: the impact of an information system.

BACKGROUND: The widespread availability of antiretroviral therapy has led to improvements in life expectancy and thus an increase in the number of people living with HIV/AIDS (PLWHA) worldwide. However, a similar increase in the number of newly-diagnosed patients in Cyprus suggests the need for solutions designed to improve monitoring, planning, and patient communication. In this study, we aimed to determine whether the use of an information system to manage PLWHA might contribute to improved quality of life and critical adherence to prescribed drug regimens and ongoing medical care. METHODS: A randomized controlled trial study was conducted in Cyprus based on information that we collected using the highly valid and reliable Greek translation of the World Health Organization (WHO) Quality of Life (QOL) HIV-BREF questionnaire to assess sociodemographic variables and patient compliance. We distributed 200 questionnaires before implementing a Health Medical Care (HMC) information system at our clinic. Six months after implementing this system, 68 of the completed questionnaires were selected, including two groups of 34 participants who had been assigned at random to the intervention or the control group. Participants included PLWHA aged ≥ 18 years who had been receiving antiretroviral therapy for more than 12 months between July 15, 2020, and July 15, 2022. RESULTS: The changes in baseline to six-month scores reported for the intervention group were significantly higher than in the control group in all six subscales assessed with the WHOQOL-HIV-BREF questionnaire, as well as in the assessment of compliance. Furthermore, compliance with treatment was associated with higher scores in the questionnaire subscales, including physical health, psychological health, degree of autonomy, social relationships, life circumstances, and spirituality/religious/personal beliefs. We also identified specific demographic factors and behaviors that were associated with better compliance with scheduled medical care and the prescribed drug regimen. Specifically, men exhibited better compliance than women and younger PLWHA exhibited better compliance than the elderly as did individuals who reported a higher level of educational attainment. Additionally, individuals who did not use addictive substances, consumed less alcohol, and were managed using the monitoring information system all exhibited better compliance compared to those in the control group. CONCLUSION: The results of this study suggest that management of PLWHA via the use of an information system can contribute to improved QOL and drug compliance.

This study was conducted to find ways to improve the lives of people living with HIV/AIDS (PLWHA) in Cyprus. With more PLWHA receiving treatment and care, it's crucial to ensure they have a good quality of life and follow their treatment plans. The main question we wanted to answer was whether using a special computer system to manage PLWHA could make their lives better and help them stick to their treatment. We found that using this computer system indeed made a positive difference. People who used it reported better physical and mental health, more independence, better relationships, and overall improved life circumstances. The study showed that managing PLWHA with a computer system can lead to better quality of life and treatment adherence. Some groups, like men, younger individuals, and those with more education, did even better. Also, people who didn't use addictive substances or consume much alcohol had better results. In summary, using technology in healthcare can greatly benefit PLWHA in Cyprus. This study highlights the importance of innovative solutions in healthcare to enhance the well-being of people living with HIV/AIDS and ensure they receive the best possible care.

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.

Reviewing Challenges in Specifying Interoperability Requirement in Procurement of Health Information Systems.

Procurement of health information systems (HIS) is a complex and critical task that requires early identification of interoperability requirements. However, specifying adequate requirements is often associated with several challenges. We examined relevant peer-reviewed literature and public documents (policy documents, annual reports, and newspapers) to summarize existing challenges in specifying interoperability requirement during procurement of HISs. In this study, 32 public documents and 2343 peer-reviewed articles were found using Google search engine, Springer, PubMed and ScienceDirect. Collected data were analyzed using a thematic coding schema. Our result shows that challenges related to describing the needs properly, conflicting needs and knowledge gaps are shared between most articles. Further research in the direction of developing a model that can bridge knowledge gaps, facilitate interdisciplinary collaboration, and help to avoid fuzzy requirements is needed.

Open Source Software in Healthcare: International Case Series from the IMIA Open Source Working Group.

In this case series, we demonstrate how open-source software has been widely adopted as the primary health information system in many low- and middle-income countries, and for government-developed applications in high-income settings. We discuss the concept of Digital Global Goods and how the general approach of releasing software developed through public funding under open-source licences could improve the delivery of healthcare in all settings through increased transparency and collaboration as well as financial efficiency.

Coding undiagnosed rare disease patients in health information systems: recommendations from the RD-CODE project.

BACKGROUND: In European Union countries, any disease affecting less than 5 people in 10,000 is considered rare. As expertise is scarce and rare diseases (RD) are complex, RD patients can remain undiagnosed for many years. The period of searching for a diagnosis, called diagnostic delay, sometimes leads to a diagnostic dead end when the patient's disease is impossible to diagnose after undergoing all available investigations. In recent years, extensive efforts have been made to support the implementation of ORPHA nomenclature in health information systems (HIS) so as to allow RD coding. Until recently, the nomenclature only encompassed codes for specific RD. Persons suffering from a suspected RD who could not be diagnosed even after full investigation, could not be coded with ORPHAcodes. The recognition of the RD status is necessary for patients, even if they do not have a precise diagnosis. It can facilitate reimbursement of care, be socially and psychologically empowering, and grant them access to scientific advances. RESULTS: The RD-CODE project aimed at making those patients identifiable in HIS in order to produce crucial epidemiological data. Undiagnosed patients were defined as patients for whom no clinically-known disorder could be confirmed by an expert center after all reasonable efforts to obtain a diagnosis according to the state-of-the-art and diagnostic capabilities available. Three recommendations for the coding of undiagnosed RD patients were produced by a multi-stakeholder panel of experts: 1/ Capture the diagnostic ascertainment for all rare disease cases; 2/ Use the newly created ORPHAcode (ORPHA:616874 "Rare disorder without a determined diagnosis after full investigation"), available in the Orphanet nomenclature: as the code is new, guidelines are essential to ensure its correct and homogeneous use for undiagnosed patients' identification in Europe and beyond; 3/ Use additional descriptors in registries. CONCLUSIONS: The recommendations can now be implemented in HIS (electronic health records and/or registries) and could be a game-changer for patients, clinicians and researchers in the field, enabling assessment of the RD population, including undiagnosed patients, adaptation of policy measures including financing for care and research programs, and to improved access of undiagnosed patients to research programs.

Trends in sedation-analgesia practices in pediatric liver transplant patients admitted postoperatively to the pediatric intensive care unit: An analysis of data from the pediatric health information system (PHIS) database.

BACKGROUND: Children admitted to the pediatric intensive care unit (PICU), after liver transplantation, frequently require analgesia and sedation in the immediate postoperative period. Our objective was to assess trends and variations in sedation and analgesia used in this cohort. METHODS: Multicenter retrospective cohort study using the Pediatric Health Information System from 2012 to 2022. RESULTS: During the study period, 3963 patients with liver transplantation were admitted to the PICU from 32 US children's hospitals with a median age of 2 years [IQR: 0.00, 10.00]. 54 percent of patients received mechanical ventilation (MV). Compared with patients without MV, those with MV were more likely to receive morphine (57% vs 49%, p < .001), fentanyl (57% vs 44%), midazolam (45% vs 31%), lorazepam (39% vs. 24%), dexmedetomidine (38% vs 30%), and ketamine (25% vs 12%), all p < .001. Vasopressor usage was also higher in MV patients (22% vs. 35%, p < .001). During the study period, there was an increasing trend in the utilization of dexmedetomidine and ketamine, but the use of benzodiazepine decreased (p < .001). CONCLUSION: About 50% of patients who undergo liver transplant are placed on MV in the PICU postoperatively and receive a greater amount of benzodiazepines in comparison with those without MV. The overall utilization of dexmedetomidine and ketamine was more frequent, whereas the administration of benzodiazepines was less during the study period. Pediatric intensivists have a distinctive opportunity to collaborate with the liver transplant team to develop comprehensive guidelines for sedation and analgesia, aimed at enhancing the quality of care provided to these patients.

National experience with pediatric surgical aortic valve repair: A Pediatric Health Information System analysis.

OBJECTIVE: To characterize national experience with surgical aortic valve repair in pediatric patients. METHODS: Patients in the Pediatric Health Information System database aged 17 years or younger with International Statistical Classification of Diseases and Related Health Problems codes for open aortic valve repair from 2003 to 2022 were included (n = 5582). Outcomes of reintervention during index admission (repeat repair, n = 54; replacement, n = 48; and endovascular intervention, n = 1), readmission (n = 2176), and in-hospital mortality (n = 178) were compared. A logistic regression was performed for in-hospital mortality. RESULTS: One-quarter (26%) of patients were infants. The majority (61%) were boys. Heart failure was present in 16% of patients, congenital heart disease in 73%, and rheumatic disease in 4%. Valve disease was insufficiency in 22% of patients, stenosis in 29%, and mixed in 15%. The highest quartile of centers by volume (median, 101 cases; interquartile range, 55-155 cases) performed half (n = 2768) of cases. Infants had the highest prevalence of reintervention (3%; P < .001), readmission (53%; P < .001), and in-hospital mortality (10%; P < .001). Previously hospitalized patients (median, 6 days; interquartile range, 4-13 days) were at higher risk for reintervention (4%; P < .001), readmission (55%; P < .001), and in-hospital mortality (11%; P < .001), as were patients with heart failure (reintervention [6%; P < .001], readmission [42%; P = .050], and in-hospital mortality [10%; P < .001]). Stenosis was associated with reduced reintervention (1%; P < .001) and readmission (35%; P = .002). The median number of readmissions was 1 (range, 0-6) and time to readmission was 28 days (interquartile range, 7-125 days). A regression of in-hospital mortality identified heart failure (odds ratio, 3.05; 95% CI, 1.59-5.49), inpatient status (odds ratio, 2.40; 95% CI, 1.19-4.82), and infancy (odds ratio, 5.70; 95% CI, 2.60-12.46) as significant. CONCLUSIONS: The Pediatric Health Information System cohort demonstrated success with aortic valve repair; however, early mortality remains high in infants, hospitalized patients, and patients with heart failure.

Critical Care Utilization in Children With Cancer: U.S. Pediatric Health Information System Database Cohort 2012-2021.

OBJECTIVES: To determine changes in pediatric oncology hospitalizations requiring intensive care over the period 2012-2021. DESIGN: Retrospective study of hospital admission. SETTING: Registry data from 36 children's hospitals in the U.S. Pediatric Health Information Systems database. PATIENTS: Children 18 years or younger admitted to any of 36 hospitals with an oncology diagnosis. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: There were a total of 55,827 unique patients accounted for 281,221 pediatric oncology hospitalizations over the 10-year period, and 16.6% of hospitalizations included admission to the PICU. Hospitalizations and PICU admissions steadily increased over this decade. Between 2012 and 2016, 15.1% of oncology hospitalizations were admitted to the PICU compared with 18.0% from 2017 to 2021 (difference 2.9% [95% CI, 2.6-3.2%] p ≤ 0.0001). Support with invasive mechanical ventilation also increased over time with 3.7% during 2012-2016 compared with 4.1% from 2017 to 2021 (difference 0.4% [95% CI, 0.2-0.5%] p ≤ 0.0001). Similar results were seen with cardiorespiratory life support using extracorporeal membrane oxygenation (difference 0.05% [95% CI, 0.02-0.07%] p = 0.0002), multiple vasoactive agent use (difference 0.3% [95% CI, 0.2-0.4%] p < 0.0001), central line placement (difference 5.3% [95% CI, 5.1-5.6%], p < 0.001), and arterial line placement (difference 0.4% [95% CI, 0.3-0.4%], p < 0.001). Year-on-year case fatality rate was unchanged over time (1.3%), but admission to the PICU during the second 5 years, compared with the first 5 years, was associated with lower odds of mortality (difference 0.7% [95% CI, 0.3-1.1%]) (odds ratio 0.82 [95% CI, 0.75-0.90%] p < 0.001). CONCLUSIONS: The percentage of pediatric oncology hospitalizations resulting in PICU admission has increased over the past 10 years. Despite the increasing use of PICU admission and markers of acuity, and on comparing 2017-2021 with 2012-2016, there are lower odds of mortality.