Epidemiological profile and temporal trend of exogenous intoxications in children and adolescents.

OBJECTIVE: To describe the epidemiological profile and to analyze the trend in the incidence rate of exogenous poisoning concerning children and adolescents (0-19 years old) in the city of Arapiraca, Alagoas, Brazil, in the period from 2007 to 2015. METHODS: Observational study with data extracted from the Notifiable Diseases Information System. The variables sex, age group, toxic agent, and circumstance were analyzed using descriptive statistics. For temporal analysis, cut-off rates of incidence/10,000 inhabitants were calculated and the inflection point regression model was used for analysis. RESULTS: There were 5,539 cases of exogenous intoxication in individuals aged 0-19 years in the city, of which 53.1% (n=2,944) occurred in girls and 61.5% (n=3,405) in children aged 0-9 years. Medicines consisted in the main agent responsible for intoxications (28.5%; n=1,580), mainly by accidental use (18.2%; n=1,010). There was a significant increase in the events during the study period (Average Annual Percent Change: 12.7; 95%CI 1.1-25.6; p<0.001), with rates increasing from 56.52/10,000 inhabitants in 2007 to 56.64/10,000 inhabitants in 2015. The incidence of cases in girls increased from 57.34/10,000 inhabitants in 2007 to 62.27/10,000 inhabitants in 2015. In boys, the incidence of cases was stationary: 55.69/10,000 inhabitants to 50.9 /10,000 inhabitants in the same period. CONCLUSIONS: The study showed a higher frequency of cases in girls aged 0 to 4 years and an increasing trend in the incidence rate during the study period. Implementation of actions and strategies, with emphasis on health education, is needed in order to prevent cases of exogenous intoxication.

Use of Immunization Information Systems in Ascertainment of COVID-19 Vaccinations for Claims-Based Vaccine Safety and Effectiveness Studies.

Importance: Safety and effectiveness studies of COVID-19 vaccines are being conducted using clinical data, including administrative claims. However, claims data only partially capture administered COVID-19 vaccine doses for numerous reasons, such as vaccination at sites that do not generate claims for reimbursement. Objective: To evaluate the extent to which Immunization Information Systems (IIS) data linked to claims data enhances claims-based COVID-19 vaccine capture for a commercially insured population and to estimate the magnitude of misclassification of vaccinated individuals as having unvaccinated status in the linked IIS and claims data. Design, Setting, and Participants: This cohort study used claims data from a commercial health insurance database and obtained vaccination data from IIS repositories in 11 US states. Participants were individuals younger than 65 years who resided in 1 of 11 states of interest and who were insured in health plans from December 1, 2020, through December 31, 2021. Main Outcomes and Measures: Estimated proportion of individuals with at least 1 dose of any COVID-19 vaccine and proportion of individuals with a completed vaccine series based on general population guidelines. Vaccination status estimates were calculated and compared using claims data alone and linked IIS and claims data. Remaining misclassification of vaccination status was assessed by comparing linked IIS and claims data estimates with estimates from external surveillance data sources (Centers for Disease Control and Prevention [CDC] and state Department of Health [DOH]) and capture-recapture analysis. Results: This cohort study included 5 112 722 individuals (mean [SD] age, 33.5 [17.6] years; 2 618 098 females [51.2%]) from 11 states. Characteristics of those who received at least 1 vaccine dose and those who completed a vaccine series were similar to the overall study population. The proportion with at least 1 vaccine dose increased from 32.8% using claims data alone to 48.1% when the data were supplemented with IIS vaccination records. Vaccination estimates using linked IIS and claims data varied widely by state. The percentage of individuals who completed a vaccine series increased from 24.4% to 41.9% after the addition of IIS vaccine records and varied across states. The percentages of underrecording using linked IIS and claims data were 12.1% to 47.1% lower than those using CDC data, 9.1% to 46.9% lower than the state DOH, and 9.2% to 50.9% lower than capture-recapture analysis. Conclusion and Relevance: Results of this study suggested that supplementing COVID-19 claims records with IIS vaccination records substantially increased the number of individuals who were identified as vaccinated, yet potential underrecording remained. Improvements in reporting vaccination data to IIS infrastructures could allow frequent updates of vaccination status for all individuals and all vaccines.

[Evaluation of data on deaths due to COVID-19 from the databases of the Civil Registry (RC-Arpen), SIVEP-Gripe, and SIM in Brazil in 2020]. / Avaliação dos dados de mortes por COVID-19 nas bases dos cartórios do RC-Arpen, SIVEP-Gripe e SIM no Brasil em 2020.

This study compares the death records due to COVID-19 in 2020 for Brazilian territory. Three distinct databases were used: Civil Registry (RC-Arpen), Brazilian Mortality Information System (SIM), and Influenza Epidemiological Surveillance Information System (SIVEP-Gripe). We identified differences between the numbers of deaths due to COVID-19 in these databases, varying in each federative unit. The RC database is updated faster than the other two databases (SIM and SIVEP-Gripe) and it is most suited for monitoring and for studies covering recent periods. Despite the slower update, Brazilian Health Informatics Department (DATASUS) databases present geographically similar numbers and disclose more detailed data on deaths. This detailed information improves the DATASUS databases for studies that require more information about the patient and treatment.

Este estudo compara os registros de óbitos por COVID-19 em 2020 para todo o território nacional. Utilizamos três bases distintas: Registro Civil (RC-Arpen), Sistema de Informação sobre Mortalidade (SIM) e Sistema de Informação da Vigilância Epidemiológica da Gripe (SIVEP-Gripe). Há discordâncias entre os números de mortes por COVID-19 divulgados pelas diversas bases e essas diferenças variam em cada Unidade da Federação. A base do RC-Arpen é atualizada mais rapidamente que as outras duas bases do Departamento de Informática do Sistema Único de Saúde - DATASUS (SIM e SIVEP-Gripe), além de ser mais indicada para monitoramentos e pesquisas que abrangem períodos mais recentes. Apesar da atualização mais lenta, as bases do DATASUS apresentam números geograficamente similares e divulgam dados mais detalhados sobre as mortes. Esse detalhamento das informações torna as bases do DATASUS mais adequadas para pesquisas que demandam mais informações sobre o paciente e o tratamento.

Este estudio compara los registros de defunciones por COVID-19 en 2020 para todo el territorio brasileño. Se utilizaron tres bases diferentes: Registro Civil (RC-Arpen), Sistema de Información de Mortalidad (SIM) y Sistema de Información de Vigilancia Epidemiológica de la Gripe (SIVEP-Gripe). Existen discrepancias entre las cifras de muertes por COVID-19 comunicadas por las distintas bases de datos y estas diferencias varían en cada Unidad Federal. La base de datos RC se actualiza más rápidamente que las otras dos bases de datos del Departamento de Informática del Sistema Único de Salud - DATASUS (SIM y SIVEP-Gripe) y es más adecuada para el seguimiento y las encuestas que abarcan periodos más recientes. A pesar de que la actualización es más lenta, las bases de datos del DATASUS presentan cifras geográficamente similares y revelan datos más detallados sobre las muertes. Este detalle de la información hace que las bases de datos del DATASUS sean más adecuadas para investigaciones que requieren más información sobre el paciente y el tratamiento.

"All Quiet on the Western Front" - Clinical Information Systems Research in the Year 2021.

OBJECTIVES: In this synopsis, we give an overview of recent research and propose a selection of best papers published in 2021 in the field of Clinical Information Systems (CIS). METHOD: As CIS section editors, we annually apply a systematic process to retrieve articles for the IMIA Yearbook of Medical Informatics. For eight years now, we use the same query to find relevant publications in the CIS field. Each year we retrieve more than 2,400 papers which we categorize in a multi-pass review to distill a preselection of up to 15 candidate papers. External reviewers and yearbook editors then assess the selected candidate papers. Based on the review results, the IMIA Yearbook editorial board chooses up to four best publications for the section at a selection meeting. To get a comprehensive overview of the content of the retrieved articles, we use text mining and term co-occurrence mapping techniques. RESULTS: We carried out the query in mid-January 2022 and retrieved a deduplicated result set of 2,688 articles from 1,062 different journals. This year, we nominated ten papers as candidates and finally selected two of them as the best papers in the CIS section. As in the previous years, the content analysis of the articles revealed the broad spectrum of topics covered by CIS research, but - on the other side - no real innovations or new upcoming research trends. However, the significant impact of COVID-19 on CIS research was observable also this year. CONCLUSIONS: The trends in CIS research, as seen in recent years, continue to be observable. The content analysis revealed nothing really new in the CIS domain. What was very visible was the impact of the COVID-19 pandemic, which still effects our lives and also CIS.

A Brazilian classified data set for prognosis of tuberculosis, between January 2001 and April 2020.

After COVID-19, tuberculosis (TB) is the leading cause of death by an infectious disease in the world. This work presents a data set based on data collected from the Brazilian Information System for Notifiable Diseases (SINAN) for the period from January 2001 to April 2020 relating to patients diagnosed with tuberculosis in Brazil. The data from SINAN was pre-processed to generate a new data set with two distinct treatment outcome classes: CURED and DIED. The data set comprises 37 categorical attributes (including socio-demographic, clinical, and laboratory data) as well as the target class. There are 927,909 records of patients classified as CURED and 36,190 classified as DIED, totaling 964,099 records.

Soft ordered double quantitative approximations based three-way decisions and their applications.

The classical theory of rough set was established by Pawlak, which mainly focusses on the approximation of sets characterized by a single equivalence relation over the universe. However, most of the current single granulation structure models cannot meet the user demand or the target of solving problems. Multigranulation rough sets approach can better deal with the problems, where data might be spread over various locations. In this article, we present the idea of soft preference and soft dominance relation for the development of soft dominance rough set in an incomplete information system. Subsequently, several important structural properties and results of the proposed model are carefully analyzed. After employing soft dominance based rough set approach to it for any times, we can only get six different sets at most in an incomplete information system. That is to say, every rough set in a universe can be approximated by only six sets, where the lower and upper approximations of each set in the six sets are still lying among these six sets. The relationships among these six sets are established. Based on soft dominance relation, we introduce logical disjunction/conjunction soft dominance optimistic/pessimistic multigranulation decision theoretic rough approximations in an incomplete information. Meanwhile, to measure the uncertainty of soft dominance optimistic/pessimistic multigranulation decision theoretic rough approximation and some of their interesting properties are examined. Thereafter, a novel multi attribute with multi decision making problem approach based on logical disjunction/conjunction soft dominance optimistic/pessimistic multigranulation decision theoretic rough sets approach are developed to solve the selection of medicine to treat the coronavirus disease (COVID-19). The basic principle and the detailed steps of the decision making model (algorithms) are presented in detail. To demonstrate the applicability and potentiality of the proposed model, we present a practical example of a medical diagnosis is given to validate the practicality of the technique.

The impact of the SARS COV-2 pandemic on pediatric accesses in ED: A Healthcare Emergency Information System analysis.

BACKGROUND: The Emergency Department (ED) services play a fundamental role in managing the accesses of potential Sars-Cov-2 cases. The aim of this study is to evaluate the impact of the SARS COV-2 pandemic on pediatric accesses in Emergency Department of Lazio Region. METHODS: The population includes all pediatric accesses (0-17 years) in the ED of Lazio Region during 2019 and 2020. Accesses were characterized by age, week and calendar period. Four periods were defined: pre-lockdown, lockdown, post-lockdown and the second wave. The trend of ED accesses (total or for specific cause) in 2020 (by period and week) were compared to them occurred in 2019. ED visits have been described by absolute frequency and percentage variation. Percentage variation of adult was also reported to compare the trend in adult and young population. The Chi-square test was used to compare characteristics of admissions in 2019 and 2020. RESULTS: There is a large decrease of pediatric accesses in 2020 compared to 2019 (-47%), especially for younger age-classes (1-2 years: -52.5% and 3-5 years: -50.5%). Pediatric visits to ED in 2020 decreased following the same trend of adults, but more drastically (-47% vs -30%). ED accesses for suspected COVID-19 pneumonia trend show different characteristics between children and adults: in adults there is an increase in 2020, especially during the 2nd wave period (+321%), in children there is a decrease starting from the lockdown period to the achievement of the lowest level in December 2020 (-98%). CONCLUSIONS: This descriptive study has identified a decrease of total pediatric accesses in ED in 2020 compared to 2019 and a different trend of accesses by adult and young population especially by cause. The monitoring of paediatric accesses could be a useful tool to analyse the trend of COVID-19 pandemic in Italy and to reprogramming of the healthcare offer according to criteria of clinical and organizational appropriateness.

Physicians' Perceptions as Predictors of the Future Use of the National Death Information System in Peru: Cross-sectional Study.

BACKGROUND: A computer application called the National Death Information System (SINADEF) was implemented in Peru so that physicians can prepare death certificates in electronic format and the information is available online. In 2018, only half of the estimated deaths in Peru were certified using SINADEF. When a death is certified in paper format, the probability being entered in the mortality database decreases. It is important to know, from the user's perspective, the factors that can influence the successful implementation of SINADEF. SINADEF can only be successfully implemented if it is known whether physicians believe that it is useful and easy to operate. OBJECTIVE: The aim of this study was to identify the perceptions of physicians and other factors as predictors of their behavioral intention to use SINADEF to certify a death. METHODS: This study had an observational, cross-sectional design. A survey was provided to physicians working in Peru, who used SINADEF to certify a death for a period of 12 months, starting in November 2019. A questionnaire was adapted based on the Technology Acceptance Model. The questions measured the dimensions of subjective norm, image, job relevance, output quality, demonstrability of results, perceived usefulness, perceived ease of use, and behavioral intention to use. Chi-square and logistic regression tests were used in the analysis, and a confidence level of 95% was chosen to support a significant association. RESULTS: In this study, 272 physicians responded to the survey; 184 (67.6%) were men and the average age was 45.3 (SD 10.1) years. The age range was 24 to 73 years. In the bivariate analysis, the intention to use SINADEF was found to be associated with (1) perceived usefulness, expressed as "using SINADEF avoids falsifying a death certificate" (P<.001), "using SINADEF reduces the risk of errors" (P<.001), and "using SINADEF allows for filling out a certificate in less time" (P<.001); and (2) perceived ease of use, expressed as "I think SINADEF is easy to use" (P<.001). In the logistic regression, perceived usefulness (odds ratio [OR] 8.5, 95% CI 2.2-32.3; P=.002), perceived ease of use (OR 10.1, 95% CI 2.4-41.8; P=.001), and training in filling out death certificates (OR 8.3, 95% CI 1.6-42.8; P=.01) were found to be predictors of the behavioral intention to use SINADEF. CONCLUSIONS: The behavioral intention to use SINADEF was related to the perception that it is an easy-to-use system, the belief that it improves the performance of physicians in carrying out the task at hand, and with training in filling out death certificates.

How ready was the US vaccination infrastructure and network of immunization information systems for COVID-19 vaccination campaigns: Recommendations to strengthen the routine vaccination program and prepare for the next pandemic.

Coronavirus disease 2019 (COVID-19) pandemic vaccination campaigns globally have been unlike any effort in history. In the United States, the success of these efforts, in part, has hinged on the timely capture and reporting of an unprecedented amount of data from a significantly greater number of administering providers than for routine vaccinations. The pandemic response has highlighted the need to explore the status and value of vaccination data as the critical glue that connects all aspects of the upstream US vaccine development and downstream vaccination delivery system. In this review, we examine immunization information systems and the role that data and staffing play in pandemic responses. We offer three strategic recommendations-regarding funding, expanded provider enrollment, and data reporting-informed by a literature review, a survey and focus group from a convenience sample of 22 immunization jurisdictions, and the vision for enhanced data flow to improve future pandemic responses and routine vaccination.

Increasing use of immunization information systems for routine vaccinations in independent community pharmacies: A randomized controlled trial.

BACKGROUND: Only 60% of adults nationwide and just 36.8% of adults in Alabama have immunization data recorded in an Immunization Information System (IIS). The objective of this study, which took place before the coronavirus disease 2019 (COVID-19) pandemic, was to evaluate the impact of an IIS training program on pharmacists' IIS enrollment, participation, awareness, knowledge, intention, and attitudes. METHODS: A randomized controlled trial was conducted in 2019 among Alabama pharmacists (N = 41) practicing in independently owned pharmacies and providing vaccination services but whose pharmacy was not enrolled in Alabama's IIS (Immunization Patient Registry with Integrated Technology [ImmPRINT]). Intervention pharmacists were offered a 2-hour IIS training program, including an online continuing pharmacy education article, demonstration videos, implementation guide, and informational flyer. Control pharmacies received the informational flyer only. Pharmacy-level outcomes, including enrollment and participation, were obtained from ImmPRINT administrative records. Pharmacist-level outcomes, including awareness, knowledge, intention, and attitudes, were self-reported using baseline, 1-month, and 3-month surveys. Two-way mixed analysis of variance, chi-square, and independent t tests were used to analyze differences in outcomes between and within groups. RESULTS: Enrollment in ImmPRINT was significantly greater among intervention pharmacists' pharmacies (P = 0.035). In particular, 59.1% of intervention pharmacies compared with 26.3% of control pharmacies were enrolled in ImmPRINT at 3 months. No statistically significant differences were found between groups in terms of participation in ImmPRINT. Intervention pharmacists' awareness of IIS was significantly greater than control pharmacists (P = 0.028) at 1 month (postintervention). Furthermore, the IIS training program significantly improved intervention pharmacists' knowledge (P = 0.030) and attitudes (P = 0.016) toward IIS over 3 months compared with the control group. CONCLUSIONS: This pharmacist-centered training program focused on practical strategies to integrate IIS into pharmacy workflow. Results show that pharmacists' enrollment, awareness, knowledge, and attitudes significantly improved as a result of this training. As pharmacists become more involved in immunization efforts, particularly in response to COVID-19, awareness of and participation in responsible immunization documentation are critical.

Acceleration of opioid-related EMS runs in the spring of 2020: The National Emergency Medical Services Information System data for 2018-2020.

BACKGROUND: State- and county-level reports suggest that the COVID-19 pandemic exacerbated the opioid crisis. We examined US national trends of nonfatal opioid overdose in 2020 in comparison to pre-COVID years 2018-2019. METHODS: We used National Emergency Medical Services Information System (NEMSIS) data to conduct a temporal analysis from 2018 to 2020. Opioid-related EMS run was defined using five scenarios of naloxone administration. To determine annual patterns and slope inflection points, we used the Prophet model of the time series analysis. Linear slopes and their 95% confidence intervals (CIs) were calculated for pre-stay-at-home (pre-SaH) and SaH periods in 2020 and compared to the slopes during the same time in 2018-2019. Three cut-points for SaH start were considered: March 19, 24, and 29. RESULTS: We identified 91,065, 144,802, and 242,904 opioid-related EMS runs in 2018-2020, respectively. In 2020, opioid-related runs increased in January-June, with a pronounced acceleration in March, which coincides with the stay-at-home (SaH) orders. In both 2018 and 2019, opioid-related runs increased in January-August without the spring acceleration. In 2020, weekly increases (95% CI) during SaH for all examined cut-points were significantly greater than in pre-SaH: 18.09 (16.03-20.16) vs. 6.44 (3.42-9.47) for March 19, 17.77 (15.57-19.98) vs. 4.85 (2.07-7.64) for March 24, 18.03 (15.68-20.39) vs. 4.97(2.4-7.54) for March 29. No significant difference was found between these periods in 2018-2019. CONCLUSIONS: The acceleration of opioid-related EMS runs during the SaH period of 2020 suggests that EMS data may serve as an early warning system for local health jurisdictions to deploy harm reduction/prevention resources.

Monitoring vaccine safety using the vaccine safety Datalink: Assessing capacity to integrate data from Immunization Information systems.

BACKGROUND: The Vaccine Safety Datalink (VSD) uses vaccination data from electronic health records (EHR) at eight integrated health systems to monitor vaccine safety. Accurate capture of data from vaccines administered outside of the health system is critical for vaccine safety research, especially for COVID-19 vaccines, where many are administered in non-traditional settings. However, timely access and inclusion of data from Immunization Information Systems (IIS) into VSD safety assessments is not well understood. METHODS: We surveyed the eight data-contributing VSD sites to assess: 1) status of sending data to IIS; 2) status of receiving data from IIS; and 3) integration of IIS data into the site EHR. Sites reported separately for COVID-19 vaccination to capture any differences in capacity to receive and integrate data on COVID-19 vaccines versus other vaccines. RESULTS: All VSD sites send data to and receive data from their state IIS. All eight sites (100%) routinely integrate IIS data for COVID-19 vaccines into VSD research studies. Six sites (75%) also routinely integrate all other vaccination data; two sites integrate data from IIS following a reconciliation process, which can result in delays to integration into VSD datasets. CONCLUSIONS: COVID-19 vaccines are being administered in a variety of non-traditional settings, where IIS are commonly used as centralized reporting systems. All eight VSD sites receive and integrate COVID-19 vaccine data from IIS, which positions the VSD well for conducting quality assessments of vaccine safety. Efforts to improve the timely receipt of all vaccination data will improve capacity to conduct vaccine safety assessments within the VSD.

Sustainable Program Assessment Practices: A Review of the ABET and NCAAA Computer Information Systems Accreditation Process.

Program outcome assessment is a complex process that demands careful planning and resources in order to accurately assess higher-order thinking skills. A well-defined assessment approach provides detailed insights into program weaknesses and leads to continuous improvement. Whereas a poor assessment approach does not reflect the underlying weaknesses and may result in a useless effort. Furthermore, each accreditation body may have a different recommended outcome measurement approach. As a result, academic institutions may make adhoc choices just to satisfy accreditation requirements rather than designing a sustainable measurement approach. On the other hand, the magnitude of huge tasks for satisfying multiple accreditation bodies results in fatigue and mental stress for academic staff. ABET is a well-known international program accreditation body, and NCAAA is a local accreditation body for academic programs in the Kingdom of Saudi Arabia. In this paper, we have documented that how a sustainable outcome measurement mechanism can be designed to satisfy both ABET and NCAAA requirements. The core contribution of this paper is relevant specifically for academic programs in the Kingdom striving to meet both ABET and NCAAA requirements and is also relevant for all education programs to design an appropriate program assessment approach to ensure a sustainable process to foster better learning among students.

Development of the COVID-19 Real-Time Information System for Preparedness and Epidemic Response (CRISPER), Australia.

Accurate and current information has been highlighted across the globe as a critical requirement for the COVID-19 pandemic response. To address this need, many interactive dashboards providing a range of different information about COVID-19 have been developed. A similar tool in Australia containing current information about COVID-19 could assist general practitioners and public health responders in their pandemic response efforts. The COVID-19 Real-time Information System for Preparedness and Epidemic Response (CRISPER) has been developed to provide accurate and spatially explicit real-time information for COVID-19 cases, deaths, testing and contact tracing locations in Australia. Developed based on feedback from key users and stakeholders, the system comprises three main components: (1) a data engine; (2) data visualization and interactive mapping tools; and (3) an automated alert system. This system provides integrated data from multiple sources in one platform which optimizes information sharing with public health responders, primary health care practitioners and the general public.

Lessons learned from urgent computing in Europe: Tackling the COVID-19 pandemic.

PRACE (Partnership for Advanced Computing in Europe), an international not-for-profit association that brings together the five largest European supercomputing centers and involves 26 European countries, has allocated more than half a billion core hours to computer simulations to fight the COVID-19 pandemic. Alongside experiments, these simulations are a pillar of research to assess the risks of different scenarios and investigate mitigation strategies. While the world deals with the subsequent waves of the pandemic, we present a reflection on the use of urgent supercomputing for global societal challenges and crisis management.

Toward an Agile System: Iranian Information System for Covid-19-Affected Patients Data Collection from Iranian Hospitals.

COVID-19's rapid spreads has caused a global pandemic. On 19th February 2020, Iran reported its first confirmed cases of infections in Qom City and the number of diagnosed cases and the death toll rose exponentially in March [1-3]. Managing the disease, which is considered a pandemic according to the World Health Organization (WHO) [4], requires definite approaches differing according to various factors in each country, which may also lead to (in)effective dealing with the disease. In addition, using international data and information, and WHO advice, especially in the crisis and therapeutic procedures, is one of the best crisis management strategies [5]. For every plan by governances, the first step is collecting information on epidemic distribution for the purpose of isolating provinces and cities at a national scale. Thus, Ministry of Health and Medical Education of Iran (MOHME) attempted to collect the minimum required data on the infection-affected patients based on medical records and epidemiological factors, such as demographic data (gender, age and national code), exposure history (close contact with the infected, suspect patients or even having traveled) and signs and symptoms (fever, cough, shortness or difficulties in breathing, fatigue, anorexia, hemoptysis, sputum production, dyspnea, Myalgia, Pharyngalgia, nausea, vomiting, Diarrhea, Headache, Abdominal pain, Dizziness, etc.). Therefore, to ensure accuracy and validity, and to speed up data collection in an area, Information Technology (IT) tools were required [6]. In this regard, developing an information system with a simple format and user-friendly interface in the shortest possible time was the aim. This study presents the local information system developed in March 2020, which has been registering hospitalized Covide-19-affected patients in Iranian hospitals up till now. In other words, this paper introduces features and procedures of one of the national systems as a health registry that includes clinical information on admitted Covid-19 patients in Iranian hospitals from admission to discharge or death. This system is supported by MOHME, and along with outpatient Point of Care Information Systems (POCS), feeds the national and international pandemic reports and decisions.

A Survey of implementation status of child nutrition surveillance systems, registry systems and information systems: a scoping literature review protocol.

Introduction: Child malnutrition in all forms is known globally as the leading cause of poor health. Planning and solving this challenge require sources that collect data accurately. Nutrition surveillance systems (NSS), nutrition registry systems (NRS) and nutrition information systems (NIS) collect and analyse data on nutrition status. Unfortunately, these systems only exist in a few countries. The methods that these systems use significantly differ and their effectiveness is also scarcely researched. This scoping literature review aimed to conduct a survey on NSS, NRS and NIS that collect data on children's nutrition at national and international levels, along with their attributes. Methods and analysis: The methods and analyses of this scoping review follow the Arksey and O'Malley's methodology. This scoping literature review will be conducted in five stages based on this method. (1) The main research question and subquestions are identified. (2) Relevant studies are extracted. In this step, we will search electronic databases including PubMed, Scopus and ISI Web of Science. A manual search will also be performed in Google Scholar, grey literature, and the websites of organisations such as WHO, UNICEF, Centers for Disease Control and Prevention, National Health Service, International Food Policy Research Institute, Food and Agriculture Organization, Food and Nutrition Technical Assistance, United Nations World Food Programme, and United Nations System Standing Committee on Nutrition. (3) Extracted studies are separately reviewed by two reviewers based on inclusion and exclusion criteria, and eligible studies are then selected. A third reviewer resolves disagreements. (4) A checklist is developed to extract the features. Data of included systems are separately extracted and entered into a checklist by two reviewers. A third reviewer then resolves any disagreement. (5) Data are summarised and analysed and are presented in tables and figures. Discussion: This scoping literature review provides strong evidence of the status of systems that collect data on the status of child nutrition. This evidence can help select best practices which can be applied to develop future systems. It can also be a positive step towards achieving an integrated system.

Clinical Information Systems Research in the Pandemic Year 2020.

OBJECTIVE: In this synopsis, we give an overview of recent research and propose a selection of best papers published in 2020 in the field of Clinical Information Systems (CIS). METHOD: As CIS section editors, we annually apply a systematic process to retrieve articles for the International Medical Informatics Association Yearbook of Medical Informatics. For seven years now, we use the same query to find relevant publications in the CIS field. Each year we retrieve more than 2,400 papers which we categorize in a multi-pass review to distill a preselection of 15 candidate papers. External reviewers and yearbook editors then assess the selected candidate papers. Based on the review results, the IMIA Yearbook editorial board chooses up to four best publications for the section at a selection meeting. To get an overview of the content of the retrieved articles, we use text mining and term co-occurrence mapping techniques. RESULTS: We carried out the query in mid-January 2021 and retrieved a deduplicated result set of 2,787 articles from 1,135 different journals. We nominated 15 papers as candidates and finally selected four of them as the best papers in the CIS section. As in the previous years, the content analysis of the articles revealed the broad spectrum of topics covered by CIS research. Thus, this year we could observe a significant impact of COVID-19 on CIS research. CONCLUSIONS: The trends in CIS research, as seen in recent years, continue to be observable. What was very visible was the impact of the Corona Virus Disease 2019 (COVID-19) pandemic, which has affected not only our lives but also CIS.

The Clinical Information Systems Response to the COVID-19 Pandemic.

OBJECTIVE: The year 2020 was predominated by the coronavirus disease 2019 (COVID-19) pandemic. The objective of this article is to review the areas in which clinical information systems (CIS) can be and have been utilized to support and enhance the response of healthcare systems to pandemics, focusing on COVID-19. METHODS: PubMed/MEDLINE, Google Scholar, the tables of contents of major informatics journals, and the bibliographies of articles were searched for studies pertaining to CIS, pandemics, and COVID-19 through October 2020. The most informative and detailed studies were highlighted, while many others were referenced. RESULTS: CIS were heavily relied upon by health systems and governmental agencies worldwide in response to COVID-19. Technology-based screening tools were developed to assist rapid case identification and appropriate triaging. Clinical care was supported by utilizing the electronic health record (EHR) to onboard frontline providers to new protocols, offer clinical decision support, and improve systems for diagnostic testing. Telehealth became the most rapidly adopted medical trend in recent history and an essential strategy for allowing safe and effective access to medical care. Artificial intelligence and machine learning algorithms were developed to enhance screening, diagnostic imaging, and predictive analytics - though evidence of improved outcomes remains limited. Geographic information systems and big data enabled real-time dashboards vital for epidemic monitoring, hospital preparedness strategies, and health policy decision making. Digital contact tracing systems were implemented to assist a labor-intensive task with the aim of curbing transmission. Large scale data sharing, effective health information exchange, and interoperability of EHRs remain challenges for the informatics community with immense clinical and academic potential. CIS must be used in combination with engaged stakeholders and operational change management in order to meaningfully improve patient outcomes. CONCLUSION: Managing a pandemic requires widespread, timely, and effective distribution of reliable information. In the past year, CIS and informaticists made prominent and influential contributions in the global response to the COVID-19 pandemic.