An evaluation of the risk factors associated with implementing projects of health information technology by fuzzy combined ANP-DEMATEL.

BACKGROUND: Application of a Clinical Information System (CIS) like Electronic Patient Record (EPR), PACS system and CPOE has turned into one of the most important criteria of priorities of health care systems. The aims of the clinical information system include improving the physicians' efficiency level, integrating the caring process, and expanding the fuzzy quality of the services offered to patients. Achievement of these benefits in reality is not an easy task, and there are lots of plans in this field which are doomed to failure. About 50% of the implementation plans of clinical information systems in health care organizations have failed, and this trend is significantly affecting industrial countries. Proper implementation of hospital information systems lies in identifying and assessing the relationships among the most important risk factors of fuzzy. The present study aimed to provide an applicable model for identifying, ranking and evaluating the risk factors associated with projects of clinical information technology in hospitals of Shiraz University of Medical Sciences. METHOD: This is an applied study which evaluates the risk factors associated with implementation of clinical information technology projects in hospitals of Shiraz Medical Sciences University. The participants consisted of professionals and senior experts of clinical information technology. Fuzzy logic was used in this study. We also applied ANP-DEMATEL combined model with fuzzy procedure to provide the analytic model of the study. RESULTS: According to the study findings, lack of top-executive supports, and unstable organizational environment were the two most important risk factors, while the main organizational factors and technology were also highly important. In addition, the factors associated with technology had the highest influence on the other studied risk factors. CONCLUSION: Hospital authorities can benefit from this proposed model to reduce the risk of implementing the projects of clinical information technology and improve the success coefficient of the risk of such projects.

Usefulness of the Hospital Information System for maternal mortality surveillance in Brazil. / Utilidade do Sistema de Informação Hospitalar na vigilância da mortalidade materna no Brasil.

OBJECTIVE: To evaluate the capability of hospital records in the Hospital Information System (SIH) to add valuable and complementary information to the Mortality Information System (SIM) in studies on maternal mortality. We calculated and compared the maternal mortality ratio from the SIH and SIM databases, by age group and region, to highlight differences between groups and assess the coverage of maternal deaths using SIH compared with SIM. METHODS: Obstetric hospitalizations were defined based on three sources (codes ICD-10 in diagnoses; procedures; billing information). Hospital and SIM mortality ratios were calculated by dividing maternal deaths in hospitals affiliated to the Unified Brazilian Health System (SUS) per live births (SINASC) in the same hospitals. RESULTS: In 2019, we identified 2,497,957 obstetric admissions, 0.04% (946) with in-hospital mortality as outcome. The presence of three criteria identified 98% of obstetric hospitalizations and 83% of obstetric hospitalizations with death as outcome. The comparison of mortality ratios between SIH (45.5 MMR; 95%CI 42.7 - 48.5) and SIM (49.7 MMR; 95%CI 46.7 - 52.8) was not statistically significant (p-value: 0.053). CONCLUSION: The analysis of SIH was able to provide additional information for the monitoring and surveillance of maternal health in Brazil. Although there are differences between the mortality rates, the SIH, as a complementary information system to the SIM, may be valid in studies on maternal mortality and morbidity.

OBJETIVO: Avaliar a capacidade dos registros hospitalares (SIH) em adicionar informações úteis e complementares ao Sistema de Informações sobre Mortalidade (SIM) no entendimento da mortalidade materna. Calcular e comparar a Razão de Mortalidade Materna (RMM) hospitalar e a RMM do SIM dos óbitos maternos ocorridos em hospitais, por faixa etária e por região, para demonstrar diferenças entre os grupos e avaliar a cobertura de óbitos maternos do SIM em relação ao SIH. MÉTODOS: As internações obstétricas foram definidas com base em três critérios (códigos da 10a Revisão da Classificação Estatística Internacional de Doenças e Problemas Relacionados à Saúde ­ CID-10 nos diagnósticos; procedimentos; cobrança de parto). As RMM hospitalar e do SIM foram calculadas dividindo-se os óbitos maternos ocorridos nos hospitais conveniados ao Sistema Único de Saúde (SUS) pelos nascidos vivos (Sistema de Informação sobre Nascidos Vivos ­ SINASC) desses estabelecimentos. RESULTADOS: Em 2019, identificamos 2.497.957 registros de internações obstétricas, 0,04% (946) com óbito hospitalar. Os três critérios localizaram 98% das internações obstétricas e 83% das internações com óbitos, revelando inconsistências entre diagnósticos e procedimentos. A comparação entre a RMM do SIH (45,5, intervalo de confiança ­ IC95%, 42,7­48,5) e a do SIM (49,7, IC95%, 46,7­52,8) não foi estatisticamente significante (p-valor 0,053). CONCLUSÃO: A análise do SIH foi capaz de prover informações adicionais ao monitoramento e vigilância da saúde materna no Brasil. Embora haja diferenças entre as RMM, o SIH como sistema de informação complementar ao SIM pode ser válido nos estudos sobre mortalidade e morbidade materna.

Deaths and hospitalizations of victims of non-drug toxicological events in Brazil, 2009 to 2018. / Óbitos e internações de vítimas de eventos toxicológicos não medicamentosos no Brasil, 2009 a 2018.

OBJECTIVE: to determine the rate of hospitalizations due to acute non-drug poisoning (NDP) events and to analyze mortality arising from these health conditions in Brazil from 2009 to 2018. METHODS: this was a time-series study using Prais-Winsten regression to analyze records of hospitalizations for "treatment of intoxication or poisoning due to exposure to non-drug substances" held on the Hospital Information System. RESULTS: there were 125,570 hospitalizations due to NDP. The average hospitalization rate was 6.3/100,000 inhabitants, although it was higher in males (8.0/100,000 inhab.) compared to females (4.6/100,000 inhab.). The hospitalization rate and the overall mortality rate due NDP to fell from 9.4 to 4.5/100,000 inhab. and from 2.5 to 1.6/1 million inhab., respectively. CONCLUSIONS: there was a reduction in the NDP hospitalization rate and in mortality due to NDP during the decade analyzed.

Drug closed-loop management system using mobile technology.

BACKGROUND: Drug closed-loop management reflects the level of hospital management and pharmacist service. It is a challenge for hospital pharmacists to realize the whole-process closed-loop management of drugs in hospital pharmacies. Therefore, this study aimed to evaluate the operational effect of using mobile technology to build a closed-loop drug management system. METHODS: Using mobile technology, replacing the traditional paper dispensing model and constructing a multinode information collection system according to the Healthcare Information and Management Systems Society Standard, we reformed the hospital information system and inpatient pharmacy workflow and then evaluated the new approach using statistical methods. RESULTS: After the transformation, the entire process of drug data can be traced. Closed-loop management, as well as real-time data verification and control, thereby improves the work efficiency and reduces the drug dispensing time. By reducing the work error rate, the number of dispensing errors decreased from 5 to 1 case/month. The comprehensive dispensing process can achieve the whole workflow of paperless operation and reduce the use of paper A4 by 180,000 pieces per year. CONCLUSIONS: Mobile technology can improve the service level of pharmacies, enhance the level of drug management and hospital quality management, ensure the safety of medication for inpatients, and significantly reduce the amount of paper used.

Protocolo devigilância de Enfermagem na Unidade de Cuidados Pós-Anestésicos: atualização e validação / Desenvolvimento de Competências em Enfermagem à Pessoa em Situação Crítica ­ "Protocolo devigilância de Enfermagem na Unidade de Cuidados Pós-Anestésicos: atualização e validação" / Nursing Surveillance Protocol in the Post-anaesthesia Care Unit: updating and validation

Os cuidados especializados de Enfermagem têm como pilar a Enfermagem Avançada. Verificou-se que a Enfermagem Avançada tem como base a investigação, a conceptualização dos cuidados, o processo de enfermagem, o desenvolvimento profissional e a gestão de serviços/instituições. Este relatório de estágio tem como objetivo demonstrar as competências adquiridas como Enfermeira Mestre e Especialista em Enfermagem Médico-Cirúrgica na Área da Pessoa em Situação Crítica, e apresentar o trabalho de investigação desenvolvido. A análise refletiva das competências especializadas adquiridas tem por base os três ensinos clínicos realizados junto do utente em situação crítica. A componente de investigação prende-se com a atualização e validação do protocolo de vigilância de Enfermagem na Unidade de Cuidados Pós-Anestésicos (UCPA). O conteúdo e a estrutura do protocolo foram validados através de um painel de Delphi e foi avaliada a utilidade e usabilidade do protocolo, na perspetiva dos enfermeiros da UCPA. A amostra para o painel de Delphi é composta por 12 enfermeiros especialistas em Enfermagem Médico-Cirúrgica na Área de Enfermagem Perioperatória e a que avalia a utilidade e usabilidade do protocolo por 44 enfermeiros que prestam cuidados de enfermagem na UCPA de um Centro Hospitalar da região de Lisboa e Vale do Tejo. Considera-se que foram adquiridas as competências comuns e específicas na área da Pessoa em Situação Crítica enquanto Enfermeira Mestre e Especialista através da análise critico-refletiva das situações vivenciadas nos contextos clínicos. De igual modo, considera-se que o estudo desenvolvido é um projeto de melhoria contínua da qualidade dos cuidados de Enfermagem na UCPA. Após duas rondas da técnica de Delphi, atingiu-se o consenso dos peritos à altura de 96,1% relativamente à estrutura, ao conteúdo, à relevância e à pertinência do protocolo de vigilância de enfermagem na UCPA. Os resultados do questionário dos enfermeiros da UCPA foram excelentes com concordância superior a 85% em todas as perguntas. De um modo geral, a quase totalidade dos enfermeiros (97,7%) concorda com a atualização do protocolo de vigilância de enfermagem na UCPA, afirmando ser útil.

Specialised nursing care uses advanced nursing as one of its pillars. It was acknowledged that advanced nursed is based on investigation, care conceptualisation, nursing process, professional development and dealing with services / facilities. The objective of the following internship report is to demonstrate the skills acquired as Nurse Practitioner and Nurse Specialist in medical-surgical nursing in the field of the patient in critical condition and show the investigative work that was developed. The reflective analysis of the acquired specialised skills is based on the three clinical internships which took place next to the patient in critical condition. The investigative part is linked to the updating and validation of the vigilance protocol of nursing of postanesthesic care unit (PACU). The content and the structure of the protocol were validated by a Delphi technique and its usefulness and usability was assessed according to the PACU nurses. The sample for the Delphi method is composed of 12 nurse specialists in medical-surgical nursing in the perioperative care, as far as the sample used to assess the usefulness and usability is concerned, it is composed of 44 nurses who work in the PACU of a hospital in the region of Lisbon and Vale do Tejo. It is considered that the common and specific skills in the field of the patient in critical condition were acquired as Nurse Practitioner and Nurse Specialist through the critical reflexive analysis of the cases that were examined in the clinical contexts. Similarly, it is considered that the study developed here is a project to continually improve the quality of nursing care in the PACU. After two rounds of the Delphi method, a consensus among experts reached 96,1% related to the structure, content, relevance, and pertinence of the vigilance protocol of nursing in the PACU. The results of the questionnaire of the PACU nurses were excellent, more than 85% of them agreed in all answers. More generally, almost all of them (97,7%) agreed and claimed that an updating of the vigilance protocol of nursing in the PACU was useful.

Profile of hospitalization in the health unic system in the municipality of São Paulo for acute myocardial infarction in the year 2021

INTRODUCTION: Despite significant scientific advances and public prevention policies, acute myocardial infarction corresponds to a high rate of hospitalizations and morbidity and mortality. OBJECTIVE: To analyze and describe the profile of patients who are hospitalized in the city of São Paulo for Acute Myocardial Infarction in the year 2021. METHODOLOGY: It consists of a descriptive, retrospective, longitudinal epidemiological study, based on the analysis of a secondary source of data, with the aim of the studies being hospital admissions in the Unified Health System of the city of São Paulo, in the year 2021, for causes related to diseases. hypertensive As inclusion criteria, all hospital admissions were selected through the Hospital Information System (SIH), through DATASUS. The period studied was the year 2021. The morbidities were separated and selected according to the main hospitalization diagnosis and classified according to the International Disease Code 10 (ICD10), the following being selected: I10 -Essential hypertension, I11 - Hypertensive heart disease , I12 - Hypertensive kidney disease, I13 - Hypertensive heart and kidney disease, I15 - Secondary hypertension. Gender, race/color and age group were also taken into account. RESULTS: During the study period, 2219 hospitalizations were performed for hypertensive diseases, of which 49.2% were male and 50.8% female. Among the target audience of the study, when considering race/color, 35.8% of patients consider themselves white, 8% black, 29.5% brown and 0.2% yellow. 26.5% of the registered admissions had no description of race/color. Regarding the age groups studied, there is a gradual increase in the number of hospitalizations as the observed age group also increases, with the group of patients over 80 years of age having the highest number of hospitalizations, corresponding to 14% of all the hospitalizations. CONCLUSION: Hospitalizations in the city of São Paulo due to hypertensive syndromes were slightly higher in males, most of whom were white and aged over 80 years.

Construction of Hospital Human Resource Information Management System under the Background of Artificial Intelligence.

Under the background of artificial intelligence (AI), a human resource information management system was designed to facilitate hospital human resource management and improve hospital management efficiency. Based on AI, SOA was constructed and Java2 platform enterprise edition (J2EE) was combined with Java to design and research hospital human resource information management system. In addition, the function and performance required by the system were tested. The results showed that the designed system showed high safety in requirement analysis and performance. The function focused mainly on the systematic analysis of personnel management, recruitment management, organization and personnel management, and patient medical information. The constructed system could work normally and achieve the efficiency of hospital human resource management. The evaluation response time of system home page access was less than 1 second when 300 users were concurrent, and the utilization rate of service CPU was lower than 50% without abnormal memory fluctuation. The concurrent response time of all 20 managers online was less than 5 seconds, and the utilization rate of the service was lower than 70%. When the information of 100 employees in the system was queried concurrently, the average CPU utilization of the database server exceeded 90%. After performance optimization, the test result showed that the transaction response time was reduced to 0.23 seconds, which met the target requirement. In conclusion, the proposed intelligent human resource management system could reduce hospital management cost and the high sharing of human resource information provided a reference for the decision-making system of hospital leaders.

Network Security Problems and Countermeasures of Hospital Information System after Going to the Cloud.

In the current social context, information technology, network technology, and cloud computing have been widely used in all walks of life. The analysis of the specific application results of progressive technology shows that the use of technology has changed the working state of various industries and improved the work efficiency and quality of the industry. It should be noted that although the application of some technologies will bring many positive belongings, the potential risks brought by them cannot be ignored. As far as the hospital is concerned, the information system using cloud computing technology can make better use of the hospital's information data, but after the information system is on the cloud, new problems will appear in network security, resulting in the leakage of hospital patient information or research information. Based on this, in practice, it is necessary to analyze the network security problems after the hospital information system goes to the cloud and build and implement the corresponding strategies. The author analyzes and discusses the corresponding contents through work practice and combined with previous articles, in order to provide guidance and help for peers.

Type and Number of Errors of the Iranian Electronic Health Record (SEPAS) in Hospitals Affiliated with Mashhad University of Medical Sciences.

This study aims to identify the type and number of errors in the Iranian Electronic Health Record System (SEPAS) in hospitals affiliated with Mashhad University of Medical Sciences (MUMS). A cross-sectional analytical study was conducted to specify the errors done by SEPAS in the first half of 2019, based on the type and number of errors in 26 hospitals affiliated with MUMS that were connected to the SEPAS system. SEPAS system errors were classified into four categories: identity errors, clinical errors, administrative-financial and technical errors. The most important errors that occurred in the SEPAS system included non-authentication errors in Hospital Information System (HIS), non-service records, and invalid national code, respectively. Therefore, hospital administrators and information system developers must make an effort to prevent such errors.

Coverage of Clinical Research Data Retrieved from Standardized Structured Medical Information eXchange Storage.

Clinical researchers hold high expectations for the utility of health data sourced from hospital information systems. In Japan, the standardized structured medical information eXchange version 2 (SS-MIX2) storage is a common resource for obtaining clinical data from different medical databases. However, little is known about the coverage of the data types derived from the SS-MIX2 storage. In this regard, we calculated the proportions of a dataset that could be extracted via SS-MIX2 for various clinical study categories listed in various articles published in the New England Journal of Medicine. In the 95 articles reviewed, the proportions varied from 13.3% ± 13.3% (mean ± SD) for dementia to 61.8% ± 13.7% for diabetes. For cardiology, the proportion of data accessed in a unique format (SEAMAT) increased significantly. We further noted that there was room for improvement in the coverage of SS-MIX2 data.

Design and Implementation of a Unique Patient Identification Model in Information Systems in Burkina Faso.

The implementation of a reliable identity process is the basis of any secure patient information sharing system. Indeed, each individual is unique and should be identified by a unique number (identifier). It is with these issues in mind that we have designed and implemented a unique patient identification method adapted to the context of Burkina Faso. The recommended method is inspired by the French method based on the work of the Group for the Modernization of the Hospital Information System (GMSIH) [1]. The developed model allows to assign a "Unique Identifier" (PatientID) to each patient from his profile of identification features (name, date of birth, gender,…). The patient ID is a sequence of 20 characters plus a security "key" of 2 characters. A reliability test of the model has been performed to take into account identity anomalies (duplicate, collision).

Application of a Machine Learning-Based Decision Support Tool to Improve an Injury Surveillance System Workflow.

BACKGROUND: Emergency department (ED)-based injury surveillance systems across many countries face resourcing challenges related to manual validation and coding of data. OBJECTIVE: This study describes the evaluation of a machine learning (ML)-based decision support tool (DST) to assist injury surveillance departments in the validation, coding, and use of their data, comparing outcomes in coding time, and accuracy pre- and postimplementations. METHODS: Manually coded injury surveillance data have been used to develop, train, and iteratively refine a ML-based classifier to enable semiautomated coding of injury narrative data. This paper describes a trial implementation of the ML-based DST in the Queensland Injury Surveillance Unit (QISU) workflow using a major pediatric hospital's ED data comparing outcomes in coding time and pre- and postimplementation accuracies. RESULTS: The study found a 10% reduction in manual coding time after the DST was introduced. The Kappa statistics analysis in both DST-assisted and -unassisted data shows increase in accuracy across three data fields, that is, injury intent (85.4% unassisted vs. 94.5% assisted), external cause (88.8% unassisted vs. 91.8% assisted), and injury factor (89.3% unassisted vs. 92.9% assisted). The classifier was also used to produce a timely report monitoring injury patterns during the novel coronavirus disease 2019 (COVID-19) pandemic. Hence, it has the potential for near real-time surveillance of emerging hazards to inform public health responses. CONCLUSION: The integration of the DST into the injury surveillance workflow shows benefits as it facilitates timely reporting and acts as a DST in the manual coding process.

[Exploration and Application of ESB High-availability Architecture Construction Based on Hospital Information System].

OBJECTIVE: To solve the ESB bus performance and safety problems caused by the explosive growth of the hospital's business, and to ensure the stable interaction of the hospital's business system. METHODS: Taking the construction of our hospital's information system as an example, we used AlwaysOn, load balancing and other technologies to optimize the ESB bus architecture to achieve high availability and scalability of the hospital's ESB bus. RESULTS: The ESB bus high-availability architecture effectively eliminates multiple points of failure. Compared with the traditional dual-machine Cluster solution, the security is significantly improved. The nodes based on load balancing can be scaled horizontally according to the growth of the hospital's business volume. CONCLUSIONS: The construction of the ESB bus high-availability architecture effectively solves the performance and security issues caused by business growth, and provides practical experience for medical information colleagues. It has certain guiding significance for the development of regional medical information.

Comparison of usability evaluation methods for a health information system: heuristic evaluation versus cognitive walkthrough method.

BACKGROUND: There are differences of opinion regarding the selection of the most practical usability evaluation method among different methods. The present study aimed to compare two expert-based evaluation methods in order to assess a nursing module as the most widely used module of a Hospital Information System (HIS). METHODS: Five independent evaluators used the Heuristic Evaluation (HE) and Cognitive Walkthrough (CW) methods to evaluate the nursing module of Shafa HIS. In this regard, the number and severity of the recognized problems according to the usability attributes were compared using two evaluation methods. RESULTS: The HE and CW evaluation methods resulted in the identification of 104 and 24 unique problems, respectively, of which 33.3% of recognized problems in the CW evaluation method overlapped with the HE method. The average severity of the recognized problems was considered to be minor (2.34) in the HE method and major (2.77) in the CW evaluation method. There was a significant difference in terms of the total number and average severity of the recognized problems by these methods (P < 0.001). Based on the usability attribute, the HE method identified a larger number of problems concerning all usability attributes, and a significant difference was observed in terms of the number of recognized problems in both methods for all attributes except 'memorability'. Also, there was a significant difference between the two methods based on the average severity of recognized problems only in terms of 'learnability'. CONCLUSION: The HE method identified more problems with lower average severity while the CW was able to recognize fewer problems with higher average severity. Regarding the evaluation goal, the HE method was able to be used to improve the effectiveness and satisfaction of the HIS. Furthermore, the CW evaluation method is recommended to identify usability problems with the highest average severity, especially in terms of 'learnability'.

Predictive Analysis of Hospital HIS System Usage Satisfaction Based on Machine Learning.

Hospital information system (HIS) can provide a full range of information support for various hospital business activities and information collection, processing, and transmission, helping medical service providers. And HIS can reduce medical service costs and improve work efficiency, greatly reducing errors in diagnosis and treatment. Although the advantages of using the HIS are obvious, there are still some challenges in its use, the most prominent being how to make the medical staff use HIS effectively. Based on this background, this paper uses machine learning (ML) technology to predict and analyze the satisfaction of HIS use in hospitals and completes the following work: firstly, introduce the situation and development trend of HIS construction at home and abroad and provide theoretical basis for model design. The related development technologies are discussed and studied in detail. Second, the ML algorithm is used to provide a prediction strategy. The support vector machine (SVM) can handle small data sets well, and this study applies the AdaBoost technique to improve the model's generalization ability and accuracy. Lastly, a diversity metric is included to guarantee that the basic learner has good variety in order to increase the algorithm's performance. Accuracy rates may reach more than 95% in the case of tiny data sets, according to the self-built data set used for testing. This proves the superiority of the model proposed in this paper.

Electronic Phenotyping to Identify Patients with Arrythmia Disease from a Hospital Information System.

Electronic phenotyping is an important method to identify a disease group by collecting clinical data from hospital information systems. This study aimed to extract accurate cases of supraventricular arrythmia, ventricular arrythmia, and bradycardia from clinical data of a hospital information system. The electronic phenotyping algorithm was improved using the machine learning method. Subsequently, it showed a higher area under the curve for prediction and higher specificity. However, the algorithm needs further improvement to classify each arrythmia disease accurately. In conclusion, phenotyping using clinical data from hospital information systems has some affinities and issues depending on the disease.

Goupile: A New Paradigm for the Development and Implementation of Clinical Report Forms.

Despite the increasing computerization of hospital information systems, segments of patient care are still in paper format. Data extracted automatically from the hospital databases for one specific project are thus supplemented by data collected manually. Data collection tools are usually developed entirely, which requires computer knowledge and is tedious, or automatically from metadata or drag and drop controls, which is limiting in terms of functionality. To facilitate this manual collection, we developed a free and open-source tool for creating forms that does not require advanced computer skills, offers rich features, and is quickly implemented, tested and deployed. It was implemented for 15 projects and supported thousands of daily users for a complex interactive study at the national level.

Costs of hospital admission authorizations due to falls among older people in the Brazilian National Health System, Brazil, 2000-2020: a descriptive study. / Custos das autorizações de internação hospitalar por quedas de idosos no Sistema Único de Saúde, Brasil, 2000-2020: um estudo descritivo.

OBJECTIVE: To describe the costs of hospital admission authorizations (AIHs) due to falls among older people within the Brazilian National Health System (SUS). METHODS: This was a descriptive cost analysis study, based on data from the SUS's Hospital Information System, related to AIH due to falls among older people (60 years and older), between 2000 to 2020. A descriptive analysis was performed and cost measurement was based on a macro-costing method. RESULTS: 1,746,097 AIHs due to falls among older people were recorded, and the total cost was found to be BRL 2,315,395,702.75. The proportion of hospitalization costs was higher among those aged 80 years and older (36.9%), female (60.4%) and the Southeast region of the country (57.3%). The average length of stay in hospital ranged from 5.2 to 7.5 days. CONCLUSION: The high costs identified showed the need for investments in more effective measures in order to prevent and mitigate the damage caused by falls among older people.

Atenciones HIS

Analysis of trends in sepsis mortality in Brazil and by regions from 2010 to 2019.

OBJECTIVE: To characterize the profile of inpatients and trend of sepsis mortality in the Brazilian Unified Health System (SUS), throughout Brazil, and in its regions separately, from 2010 to 2019. METHODS: Observational, analytical and retrospective study of secondary data obtained through consultation to the Sistema de Informação Hospitalar (Hospital Information System). All incoming septicemia notifications from January 1, 2010 to December 31, 2019 were included. The following sociodemographic variables were used: sex, age, race, region and federative unit of residence. For data analysis, we used mortality and hospitalization coefficient, relative risk and Joinpoint regression. RESULTS: There were a total of 1,044,227 cases of sepsis in Brazil, yielding a mean prevalence coefficient of 51.3/100 thousand inhabitants. There were 463,000 deaths from sepsis recorded, with a mean prevalence coefficient of 22.8 deaths/100,000 inhabitants. The highest rates occurred among the elderly, of brown race, and there was no significant difference between genders. The Southeast region accounted for the highest rates of hospitalization and deaths. A general trend toward increased mortality was observed in the period studied. CONCLUSION: The heterogeneity of Brazil should be considered regarding socioeconomic and demographic characteristics, and differences in health investment and underreporting between regions, in order to understand the disease's epidemiological course. Finally, these findings should be correlated with other studies, in an effort to understand the behavior of the disease, and provide inputs for public and private policies in order to reduce the expressiveness of cases and deaths from sepsis in Brazil.