NI Finals

• Data management is the practice of collecting, keeping, and using data securely, efficiently, and cost-effectively.
• The goal of data management is to help people, organizations, and connected things optimize the use of data within the bounds of policy and regulation so that they can make decisions and take actions that maximize the benefit to the organization.
• data management process aim to make sure that the data in corporate systems is accurate, available and accessible.
• Health Data Management is the practice of making sense of collected data and managing it to the benefit of healthcare organizations, practitioners, and ultimately patient well being and health
• Health Information Management (HIM) - the systematic organization of health data in digital form.
• Electronic Medical Records (EMR) - generated as a result of doctor visits.
• EHR - Electronic Health Records
• Key Parts of Data Management Process:

  1. Data Architecture is designed and deployed
  2. Data Models are created
  3. Data is generated, processed, and stored
  4. Data are integrated from diff. sources (Data Warehouse/Lake)
  5. Data quality checks
  6. Data governance
• Database - most common platform used to hold data; collection of data to be accessed, updated, managed, and analyzed
• Data Architecture Development - An architecture provides a blueprint for the databases and other data platforms that will be deployed, including specific technologies to fit individual applications.
• Database administration is a core data management function.

  1. database design
  2. configuration
  3. installation and updates
  4. data security
  5. database backup and recovery
  6. application of software upgrades and security patches
• Data Modeling - which diagrams the relationships between data elements and how data flows through systems
• Data Integration - which combines data from different data sources for operational and analytical uses
• Data Governance - which sets policies and procedures to ensure data is consistent throughout an organization; and data quality management, which aims to fix data errors and inconsistencies
• Master Data Management (MDM) - which creates a common set of reference data on things like customers and products.
• Database Management System - The primary technology used to deploy and administer databases.
• Database Management System - software that acts as an interface between the databases it controls and the database administrators, end users and applications that access them.
• The most prevalent type of DBMS is the relational database management system
• Relational databases organize data into tables with rows and columns that contain database records
• Big Data Management - Analyzing large amount of data
• Data Warehouse - traditional; structured data; prepared for analysis; expensive; less agile;

  Data Lake - unstructured, raw data; low-cost; highly agile
• Disease surveillance is recognized as the cornerstone of public health decision-making and practice
• Surveillance data provide information which can be used for priority setting, policy decisions, planning, implementation, resource mobilization and allocation, prediction and early detection of epidemics.
• A surveillance system can also be used for monitoring, evaluation and improvement of disease prevention and control programs; it also generates data that is helpful to the Public Health Officials in understanding the existing and emerging infectious and non-infectious diseases
• Revised IRR of RA 11332 - Implementing Rules and Regulations of RA 11332 (Mandatory reporting of Notifiable Diseases and Health Events of Public Health Concern Act)
• Administrative Order 2021-0057 - Revised Guidelines on the Philippines Integrated Disease Surveillance and Response (PIDSR)
• Department Memorandum 2022-0006 - Implementation of Epidemic-prone Disease Case Surveillance (EDCS) Information System (IS) in Selected Hospital Sentinel Surveillance (HSS) Pilot Sites
• Department Memorandum 2022-0410 - Updating of the Cadence of Submission of Morbidity Week Reports to the Philippine Integrated Diseases Surveillance and Response - Epidemic-prone Disease Case Surveillance System and Advisory on the Use of the Epidemic-prone Disease Case Surveillance Information System
• Epidemic-prone Disease Case Surveillance (EDCS) - refers to a surveillance system to monitor trends, alert, and epidemic thresholds of diseases with epidemic potential as well as diseases for elimination and eradication.
• Event-based Surveillance and Response (ESR) - refers to the organized and rapid capture of information about events that are a potential risk to public health including events related to the occurrence of a disease in humans and events related to potential risk-exposures in humans.
• Framework of Public Health Surveillance and Action in the Philippines

  Support Activity:

  1. Communication
  2. Training
  3. Supervision
  4. Resource Provision

  Public Health Surveillance

  1. Detection
  2. Registration
  3. Reporting
  4. Confirmation
  5. Analysis
  6. Feedback

  Public Health Response

  1. Acute Response - Epidemic Type
  2. Planned Response - Management Type
• ESR Core Processes:

  1. Capture
  2. Verify
  3. Filter
  4. Assessment
  5. Response
  6. Feedback and Information Dissemination
• EDCS Core Process:

  1. Case Detection
  2. Case Registration
  3. Case Reporting
  4. Laboratory Analysis and Confirmation
  5. Data Management
  6. Analysis, Interpretation and Report Generation
  7. Feedback
  8. Epidemic Response
  9. Monitoring and Evaluation
• Goal of PIDSR:

  To support the health sector in reducing morbidity and mortality from diseases of public health importance through an institutionalized, functional integrated disease surveillance and response system.
• Objectives of PIDSR:

  1. To continually improve capacities at the national and regional levels to efficiently and effectively manage national and sub-national surveillance and response system.
  2. To mobilize and empower LGUs in the establishment and institutionalization of disease surveillance and response system.
  3. To support health sector capacity development for sustainable disease surveillance and response system.
  4. . To enhance utilization of disease surveillance data for decision making, policy development, program management, planning, monitoring and evaluation at all levels.
• PIDSR is integrated in terms of the use of standard case definitions, surveillance core activities, and resources.
• PIDSR has the capacity for early detection of epidemics.
• PIDSR utilizes case-based, laboratory-based and event-based surveillance approaches.
• PIDSR strengthens local capacity for surveillance and response.
• PIDSR provides for an integrated response to epidemics and other public health threats.