Haroldo lopes datasus - Informações em Saúde: história, uso e desafios

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The document summarizes the history and development of Brazil's national health information system. It outlines key events like the creation of the Unified Health System (SUS) in 1990 and the Department of Information Technology of SUS (DATASUS) in 1994. A timeline shows major health databases and systems being established over time from the 1970s to the present. The document also describes how different groups like health managers and educational institutions use information for purposes like strategic planning, epidemiological surveillance, and analyzing health status. It outlines the various health information systems and tools that provide data to support management and decision making in Brazil's public health system.

1st Symposium on Big Data and Public Health

Health Information: history, uses e challenges!

DATASUS – Departamento de Informática do SUS

Coordenação-Geral de Disseminação de Informações em Saúde
SGEP – Secretaria de Gestão Estratégica e Participativa / MS
Rio de Janeiro – 24 de outubro de 2013

2

The first national
health information
system:
mortality

Creation of DATASUS
The IT department of SUS

CD
BBS

........................................

2011
2012
2013

.......................

2003

.....

1998

1996

.....

Creation of
RIPSA
Inter-agency
Health
Information
Network

Creation of SUS –
The brazilian national
health system

Incorporation of Social
Security Database

...........

1994

......................................................................

1990
1991

1976

TIMELINE– Organization of Health Information

PNIIS
National IT Health
Policy

(review)

Federal Law
7508/2011:
COAP
Health Maps

INTERNET

IDSUS

Begining of
National
Health Card
Project

PNIIS

1st Symposium on
Big Data and Public
Health
Restructuring of
National Health
Card Project

3

TIMELINE – Availabilty of Health Databases

Health Indicators - RIPSA
Health facility
Health professionals
Health Supplementary
Disease Notification
Morbidity
Primary healthcare
Outpatient
Immunizations
Hospitalizations
Births

data individually
identified

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1996

1995

1994

1993

1992

1991

1990

1989

1988

1987

1986

1986

1985

1984

1983

1982

1982

1981

1980

1979

Deaths

4

Use of Health Information – by whom and how they are used

Health Manager
Strategic Planning
Sectoral Planning
Control
Evaluation
Auditing
Epidemiological
Surveillance
Monitoring
Academical use
Management of Health
Facilities
Analysis of health status

Educational
Institutions &
Research

Social Control

5

Use of Health Information - Indicator Matrix

IDB/RIPSA e
IDT/
Environmental
Planning
Monitoring, Control,
Evaluation and Audit
Epidemiological and
Environmental
Surveillance
Analysis of health status

COAP

Indicators for
Hospital
Management

IDSUS

6

Use of Health Information – Data Sources
Health Information Systems

Hospital Admission - SIH-SUS
Outpatient Care - SIA-SUS
Highly Complex Procedures - APAC

SISRCA

Diseases which require Notification - SINAN
Mortality System - SIM
Live Births System - SINASC
Vaccination System - SISPNI
Regulation of Health Services - SISREG
Urgency and Emergency – SAMU
e-Health Hospital - eSUSHospitalar
e-Health Primary Care – SUS/AB
General Budget - SIOPS

Popular Pharmacy - Farmácia Popular
Pharmacy System - Hórus
Breast Cancer - SISMAMA
Cervix Cancer - SISCOLO

..........

SISCAN

Management
and Planning

Analysis of
health status

Management of
health facilities

Epidemiological
Surveillance

7

Use of Health Information – Tools for information retrieval in SUS

Local

Datamining

WEB

Big
Data

Business
Intelligence
TABNET

TABWIN

Datawarehouse
and
Datamart
(DW)

TABDOS
FORMSUS
20th century

21th century

THANK YOU!
Haroldo Lopes dos Santos (haroldo@datasus.gov.br)
Coordenador Geral de Disseminação de Informações em
Saúde
DATASUS/SGEP/MS

1. The study examined how biodiversity may prevent malaria outbreaks in tropical forests through two mechanisms: the dilution effect of wild animals acting as dead-end hosts for Plasmodium parasites, and diffuse competition among mosquito vectors and non-vectors for blood meals. 2. Models based on the Ross-Macdonald framework and incorporating biodiversity factors were developed and parameterized using field and literature data from a Brazilian forest where the main malaria vector is present but no cases have been reported since 1980. 3. The standard Ross-Macdonald model predicted malaria outbreaks should occur (R0 > 1), but the biodiversity-incorporated model matched the observed absence of transmission (R0 < 1),

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1) Access to public information in Brazil is a constitutional right and includes all information produced by the government or under government custody. The main attributes of public information are availability, authenticity, and integrity. 2) Federal Law no 12.527/2011 regulates the right of access to public information and provides that the government must efficiently manage documents and make knowledge and consultation available to all, with only secret or personal information being restricted. 3) Resolution no 466/2012 regulates research involving human subjects and reaffirms the confidentiality of personal data, only exceptionally authorizing access without consent after review by an ethics committee.

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This document summarizes a project to mine and analyze over 1.3 million legal texts from the Brazilian Supreme Court. It involved web scraping the documents, parsing the HTML, storing the data in MySQL and MongoDB databases, applying natural language processing and pattern matching techniques, and visualizing the results using tools like Matplotlib, Ubigraph and Gource. The goal was to better understand the information and relationships within the large corpus of legal texts.

Causal Bayesian Networks

Flávio Codeço Coelho

This document discusses causal Bayesian networks. It begins by introducing basic graph theory concepts like vertices, edges, directed and undirected graphs. It then explains that Bayesian networks are a type of directed acyclic graph that can be used to represent conditional independence relationships between variables. The document outlines some key properties and theorems regarding causal Bayesian networks, such as d-separation and the Markov condition. It also discusses how causal Bayesian networks can be used for inference and representing the effects of interventions.

In trodução ao Epigrass

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1. O documento introduz o Epigrass, uma plataforma de modelagem orientada a objetos para modelar dinamicamente populações espacialmente estruturadas. 2. O Epigrass permite aumentar a complexidade dos modelos sem um aumento exponencial do esforço, incorporando conceitos de teoria de grafos e redes. 3. O documento descreve as características e funcionalidades atuais do Epigrass, como a especificação e parametrização de modelos, visualização de resultados e futuras melhorias planejadas.

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1. 1st Symposium on Big Data and Public Health Health Information: history, uses e challenges! DATASUS – Departamento de Informática do SUS Coordenação-Geral de Disseminação de Informações em Saúde SGEP – Secretaria de Gestão Estratégica e Participativa / MS Rio de Janeiro – 24 de outubro de 2013

2. 2 The first national health information system: mortality Creation of DATASUS The IT department of SUS CD BBS ........................................ 2011 2012 2013 ....................... 2003 ..... 1998 1996 ..... Creation of RIPSA Inter-agency Health Information Network Creation of SUS – The brazilian national health system Incorporation of Social Security Database ........... 1994 ...................................................................... 1990 1991 1976 TIMELINE– Organization of Health Information PNIIS National IT Health Policy (review) Federal Law 7508/2011: COAP Health Maps INTERNET IDSUS Begining of National Health Card Project PNIIS 1st Symposium on Big Data and Public Health Restructuring of National Health Card Project

3. 3 TIMELINE – Availabilty of Health Databases Health Indicators - RIPSA Health facility Health professionals Health Supplementary Disease Notification Morbidity Primary healthcare Outpatient Immunizations Hospitalizations Births data individually identified 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1986 1985 1984 1983 1982 1982 1981 1980 1979 Deaths

4. 4 Use of Health Information – by whom and how they are used Health Manager Strategic Planning Sectoral Planning Control Evaluation Auditing Epidemiological Surveillance Monitoring Academical use Management of Health Facilities Analysis of health status Educational Institutions & Research Social Control

5. 5 Use of Health Information - Indicator Matrix IDB/RIPSA e IDT/ Environmental Planning Monitoring, Control, Evaluation and Audit Epidemiological and Environmental Surveillance Analysis of health status COAP Indicators for Hospital Management IDSUS

6. 6 Use of Health Information – Data Sources Health Information Systems Hospital Admission - SIH-SUS Outpatient Care - SIA-SUS Highly Complex Procedures - APAC SISRCA Diseases which require Notification - SINAN Mortality System - SIM Live Births System - SINASC Vaccination System - SISPNI Regulation of Health Services - SISREG Urgency and Emergency – SAMU e-Health Hospital - eSUSHospitalar e-Health Primary Care – SUS/AB General Budget - SIOPS Popular Pharmacy - Farmácia Popular Pharmacy System - Hórus Breast Cancer - SISMAMA Cervix Cancer - SISCOLO .......... SISCAN Management and Planning Analysis of health status Management of health facilities Epidemiological Surveillance

7. 7 Use of Health Information – Tools for information retrieval in SUS Local Datamining WEB Big Data Business Intelligence TABNET TABWIN Datawarehouse and Datamart (DW) TABDOS FORMSUS 20th century 21th century

8. THANK YOU! Haroldo Lopes dos Santos (haroldo@datasus.gov.br) Coordenador Geral de Disseminação de Informações em Saúde DATASUS/SGEP/MS

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