Regionalização e Rede de Atenção à Saúde em Mato Grosso

Este estudo analisa a estruturação da Rede de Atenção à Saúde nas regiões de saúde do estado de Mato Grosso, considerando as ações planejadas nos instrumentos de gestão do governo do estado e da Secretaria de Estado de Saúde (SES), nos anos de 2012 a 2017, em conformidade com as diretrizes da Portaria MS/GM nº 4.279, de 30 de dezembro de 2010, que orienta o processo de conformação das redes de atenção à saúde no âmbito do Sistema Único de Saúde (SUS). Trata-se de estudo qualitativo, de natureza exploratório-descritiva, do tipo documental, que analisou os documentos públicos referentes ao planejamento do governo na especificidade do setor de saúde, o que inclui o Plano Plurianual, o Plano Estadual de Saúde e o Plano Estratégico da SES. Os achados do estudo mostram que, embora algumas ações/atividades relacionadas às diretrizes da portaria estivessem contempladas nos documentos pesquisados, ainda não foram suficientes para o estabelecimento de uma rede de atenção regionalizada de qualidade e para o fortalecimento da Atenção Primária à Saúde (APS) com capacidade de ser coordenadora do cuidado e ordenadora da rede no estado de Mato Grosso.This study analyzes the structuring of the Health Care Network in the health regions of the state of Mato Grosso, considering the actions planned in the management instruments of the State government and the State Department of Health (SES), in the years of 2012 to 2017, in accordance with the guidelines of Ordinance MS/GM No 4.279, of December 30, 2010, which guides the process of conformation of Health Care Networks within the scope of the Brazilian National Health System (SUS). This is a qualitative, exploratory-descriptive study, of documentary type, which analyzed the public documents related to government planning on the specificity of the health sector, which includes the Pluriannual Plan, the State Health Plan and the Strategic Plan of the SES. The findings of the study show that, although some actions/activities related to the guidelines of the Ordinance were included in the researched documents, they were not yet sufficient for establishing a quality regionalized care network and for strengthening the Primary Health Care (PHC) with the capacity to coordinate care and order the network in the state of Mato Grosso

Analysis of the structuring of the Health Care Network in the State of Mato Grosso, Brazil, within the context of Regionalization

Abstract The article analyzes aspects of the structuring of the health care network in the regions of the State of Mato Grosso, and the narrative about them, by institutional actors representing management, service providers and society. It is based on research on governance and regionalization of the SUS in this state, with a quantitative and qualitative approach, the empirical basis of which included secondary data, institutional documents and interviews with key actors representing management, service providers and society. In this research, the focus was on coverage of the Family Health Strategy; availability of health services; workforce; expenses on health. Between 2010 and 2018, despite the improvement of several indicators examined: the supply and distribution of services and professionals reveal regional inequalities; there are financial limitations and a lack of services and professionals. The Health Care Network (HCN) is not structured as regulated, but rather as each region - and its municipalities - interprets and adapts it, according to its installed capacity. The PHC network has promoted advances, but it has not been able to be effective and resolute in terms of health needs, not providing care properly nor coordinating the HCN.</p

Global variation in postoperative mortality and complications after cancer surgery: a multicentre, prospective cohort study in 82 countries

© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 licenseBackground: 80% of individuals with cancer will require a surgical procedure, yet little comparative data exist on early outcomes in low-income and middle-income countries (LMICs). We compared postoperative outcomes in breast, colorectal, and gastric cancer surgery in hospitals worldwide, focusing on the effect of disease stage and complications on postoperative mortality. Methods: This was a multicentre, international prospective cohort study of consecutive adult patients undergoing surgery for primary breast, colorectal, or gastric cancer requiring a skin incision done under general or neuraxial anaesthesia. The primary outcome was death or major complication within 30 days of surgery. Multilevel logistic regression determined relationships within three-level nested models of patients within hospitals and countries. Hospital-level infrastructure effects were explored with three-way mediation analyses. This study was registered with ClinicalTrials.gov, NCT03471494. Findings: Between April 1, 2018, and Jan 31, 2019, we enrolled 15 958 patients from 428 hospitals in 82 countries (high income 9106 patients, 31 countries; upper-middle income 2721 patients, 23 countries; or lower-middle income 4131 patients, 28 countries). Patients in LMICs presented with more advanced disease compared with patients in high-income countries. 30-day mortality was higher for gastric cancer in low-income or lower-middle-income countries (adjusted odds ratio 3·72, 95% CI 1·70–8·16) and for colorectal cancer in low-income or lower-middle-income countries (4·59, 2·39–8·80) and upper-middle-income countries (2·06, 1·11–3·83). No difference in 30-day mortality was seen in breast cancer. The proportion of patients who died after a major complication was greatest in low-income or lower-middle-income countries (6·15, 3·26–11·59) and upper-middle-income countries (3·89, 2·08–7·29). Postoperative death after complications was partly explained by patient factors (60%) and partly by hospital or country (40%). The absence of consistently available postoperative care facilities was associated with seven to 10 more deaths per 100 major complications in LMICs. Cancer stage alone explained little of the early variation in mortality or postoperative complications. Interpretation: Higher levels of mortality after cancer surgery in LMICs was not fully explained by later presentation of disease. The capacity to rescue patients from surgical complications is a tangible opportunity for meaningful intervention. Early death after cancer surgery might be reduced by policies focusing on strengthening perioperative care systems to detect and intervene in common complications. Funding: National Institute for Health Research Global Health Research Unit

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseBackground: Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide. Methods: A multimethods analysis was performed as part of the GlobalSurg 3 study—a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital. Findings: Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3·85 [95% CI 2·58–5·75]; p<0·0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63·0% vs 82·7%; OR 0·35 [0·23–0·53]; p<0·0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer. Interpretation: Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised. Funding: National Institute for Health and Care Research

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use