Generating new evidence of the value of new drugs and interventions are the fundamentals of health economics and outcomes research (HEOR). HEOR is an essential pillar of life sciences and a fundamental part of any new health policy on its cost-effectiveness analysis.
HEOR measures the relationship between a treatment and the actual outcomes. The aim is to improve healthcare with extensive data analysis, data management, and statistical analyses used in clinical research. In short, HEOR provides real-world data and evidence that can improve patient care.
In order to analyze the HEOR evidence produced, we must make use of biostatistics.
What Are Biostatistics?
Biostatistics in HEOR leverages statistical inputs, methods, and models to facilitate decision-making. It can apply to a bioresearch or study, starting from its conception to the design, conduct, detailed analysis, and reporting, which is of high relevance in public health and medicine.
Biostatistical models play a major role in modern biological studies, and are vital when observing experimental results in the healthcare field. These models help develop economic models and statistics that can support HEOR, clinical trials, and health sciences projects.
A professional in this field, such as a biostatistician or a biometrician, can work for a clinical research organization, in health economics outcomes research, health services research, as a clinical data scientist, healthcare analyst, behavioral health research analyst, and in any other related field.
Biostatistics in HEOR: Research Planning
Answering a scientific question is the central pillar of research in life sciences. In order to obtain accurate results that can be used in health economics, questions need to be answered with high certainty. Making a decision is the direct result of understanding and researching a topic.
Research planning pertaining to biostatistics in HEOR must go through the following phases:
What are the Applications of Biostatistics in Public Health?
Biostatistics can aid in the study of areas such as:
- Environmental health
- Health services research
- Healthcare policy
The design and data analysis of clinical trials becomes highly important when assessing the severity state of a patient with a prognosis of an outcome of a disease.
New technologies and genetic knowledge are also a significant part of biostatistics since they are now used for systems medicine resulting in more personalized treatment with the integration of data from different sources, both conventional and technological.
The Demand for Professionals in Biostatistics in HEOR
If you wish to become an HEOR professional in biostatistics, a master’s degree or a Ph.D. in biostatistics can bring you closer to this objective.
Next, we will discuss the skills employers demand, the tasks you can perform, and the required experience and education for HEOR jobs.
HEOR Job Skills in Demand
Here are some of the most frequent skills an HEOR consultancy looks for:
HEOR Job Tasks
The following are some of the tasks you will perform as a HEOR professional:
- Lead the coordination and execution of analyses of registry data
- Produce outputs of high scientific quality
- Innovate scientifically
- Lead the communication of study findings promptly for conference presentations, publications, health technology assessment (HTA) submissions, and others.
- Communicate results of research to stakeholders.
- Inform and interface with external global regulatory and reimbursement decision makers.
- Work across all HEOR pillars to ensure research delivery.
- Work with cross-functional partners to understand medical and commercial strategies
- Generate comprehensive reports for patients
- Strategize solutions to analytic challenges
- Collaborate with data management and biometrics
- Contribute to the continuous improvement and development of HEOR with new initiatives and change management.
- Economic modeling
- Perform comparative effectiveness analyses
Experience and Education Needed in HEOR Jobs
Job positions in HEOR and biostatistics typically require extensive experience and education such as:
- Master’s degree in health economics, biostatistics, epidemiology, or another scientific discipline
- Doctoral degree in the same fields as above
- More than three years of technical work experience post Ph.D. or master’s degree in health decision-analytic modeling, like cost-effectiveness or utility analyses
- Experience with disease or product registries
- Experience with rare diseases
- Experience in observational research study management
- Experience in data analytics in the pharma or biotechnology industry