Public Health Analysis
Public health remains a fundamental practice area in realising sustainable health outcomes within the population. It plays a key role in disease prevention, increasing life expectancy and improving the quality of life led by individuals. At the heart of public health practice is policy formulation and implementation that addresses multiple areas in delivering healthcare services, including disease monitoring, prevention, and issues surrounding equitable access to healthcare services by all deserving individuals. Public health is concerned with applying programmes and conducting research to ensure disease incidences do not recur through public education, creating awareness, sensitisation, and advocacy for implementing certain policies. Public health analysis plays a pivotal part in the goals of public health systems as it provides the quantitative tools required to analyse and evaluate patterns in data while providing insights that are useful in the decision-making process.
In recent years, data has become a powerful tool for organisations to enhance their decision-making quality and outcomes. Public health analysts possess the necessary skills to extract value from existing healthcare data, provide recommendations that shape public health policies and practices, and adapt to ongoing changes.
Both traditional statistics conducted by humans and artificial analysis can handle statistical analysis. However, human input is crucial for public health decision-making, which significantly impacts the population's well-being.
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Course Overview
This course aims to equip public health professionals with the necessary knowledge and competencies to leverage the potential of data in informing organisational decision-making. Public health analysis courses prepare learners to be efficient in problem-solving and provide effective solutions based on evidence from data, thus improving the efficacy of public health programmes.
- Management of healthcare data
- Introduction to statistical thinking and data analysis
- Recap of the principles of epidemiology
- Biostatistics for public health
- Computational epidemiology
- Regression analysis and modelling techniques
- Machine learning for public health
- Introduction to statistical programming and different software for statistical data analysis.
- Data-informed decision making in public health practice
Course Aims
The course objective is to prepare participants with the necessary skills to analyse critically, develop predictors, suggest effective interventions, and recognise data's significance in the decision-making process. The data can be utilised to safeguard the community and enhance healthcare services. Thus, the course intends to instil a culture of evidence-based decision-making in the attendees, to impact policy formulation and the implementation of appropriate intervention. Additionally, the course stimulates the participants' critical thinking skills through practical scenarios that reflect real-life problems and solicit solutions and recommendations based on the data provided.
Target Audience
This course is designed for individuals or those who anticipate a role in management and supervisory positions and health professionals seeking to broaden their knowledge of the basics of public health analysis. They are responsible for high-level decisions based on presented cases and play a pivotal role in policy formulation. Individuals in these positions understand the concepts behind the reports presented for them to question the clarity of the recommendations better and make decisions from the point of information.
Course Learning Objectives
General Objectives
- Develop the ability to effectively use health indicators to enhance knowledge and generate evidence about population health.
- Demonstrate an understanding of the importance of data in the contemporary public health environment.
- Apply epidemiological methods in the analysis and interpretation of health data, enabling the identification of patterns and trends.
- Retrieve, analyse, and appraise evidence from diverse data sources to support decision-making in public health.
- Understand health impact assessment techniques and comprehend the HIA implications for public health decision-making.
- Present sufficient knowledge required for data-informed decision-making and an urge to explore the area of public health analysis further.
- Evaluate public health data, ensuring accuracy and relevance in decision-making, and identifying potential biases or limitations in the data.
- Promote evidence-based professional practice in public health, emphasising the importance of basing decisions on sound evidence.
Course Structure
The course incorporates modules on public health, statistical data analysis, and decision-making in a simple and accessible manner. Furthermore, the course has been devised to suit people from a public health education background who need more understanding of statistical data analysis. It will be delivered through interactive sessions, practical exercises, and homework assignments. Participants will have the opportunity to be part of the discussion and share their experiences to enhance peer learning.
The training will cover the following key areas:
- Introduction to Epidemiological Analysis
- Data Collection and Management
- Statistical Analysis in Public Health
- Health Impact Assessment Techniques
- Machine Learning for Public Health
- Data-informed Decision-making
- Program Planning and Evaluation
- Assessment of data quality
Competencies addressed by the Course.
Addresses the Essential Public Health Functions that aim to advance public health research to inform policy and practice:
- Uses health indicators effectively to increase knowledge and generate evidence about population health, including within at-risk and vulnerable groups. -
- Ability to apply epidemiological methods to analyse and interpret health data, identifying patterns and trends.
- Knows how to retrieve, analyse, and appraise evidence from all data sources to support decision-making.
- Competence in conducting health impact assessments and understanding their implications on public health.
- Acquire skills in using data for decision-making processes in public health, contributing to evidence-based policies, and involving relevant stakeholders in this process.
- Develops and implements standards, protocols and procedures that incorporate national and international best practices in the health system.
- Capability to critically evaluate public health data, ensuring accuracy and relevance in decision-making.
- Act on and promote evidence-based professional practice.
Assessment and Feedback
At the end of each training day, participants will be evaluated through tests and feedback provided. Participants will be requested to complete questionnaires and provide opinions on the sessions. At the end of the training period, participants will be evaluated on their ability to use essential features of the chosen statistical analysis, interpret, and analyse the data and its real-world application.
Certificates
The WHOCC Imperial College London will issue a certificate of competence upon completing all required assessments and active participation in the course activities. The course has been accredited with 14 CPD (Continuing Professional Development) hours.
Faculty
School of Public Health, Imperial College London
Public Health England
WHO EURO and EMRO
Participants
The proposed maximum number of participants will be 20, but this may change depending on the availability of facilitators and computing resources for the practical sessions. The limited number is to safeguard the quality of the learning experience due to the interactive nature of the training.
Dates
8th, 15th 22nd April 2024
Cost
£700 full price
20% discount for Imperial College & NHS Staff & Students!
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