HEOR Competencies Framework

Through a collaboration between the ISPOR Institutional Council and Faculty Advisor Council, and leveraging the expertise and perspectives of ISPOR members, a set of competencies, organized into different domains, was developed to highlight areas for career growth while pointing professionals toward development opportunities for the future.

1.1 Business Acumen

2.1 Orientation Towards Solutions and Success

3.1 Drug Development Expertise

4.1 Cultural Awareness and Sensitivity

5.1 Burden of Illness Analysis

Burden of illness analyses involve combining epidemiological, economic, and often quality of life or utility analysis to estimate the overall impact of a disease.

• Measure healthcare costs, quality-adjusted life years lost, and value of work productivity losses using available data
• Understand when and be able to employ primary data analysis, literature review, or both
• Design and implement statistical analyses to quantify the burden of illness and to interpret study results and translate them for a general audience
  

5.2 Economic Analysis Alongside Clinical Trials

Economic analyses alongside clinical trials pertain to conducting an economic analysis of treatment based on the data for patients and outcomes within clinical trials.

• Understand all types of economic analyses that may be needed, including cost-effectiveness analysis, cost-utility analysis, cost-benefit analysis, cost-minimization analysis, and budget-impact analysis
• Understand the nature and operations of a health system with an emphasis on the finances and economics within it
• Identify and represent uncertainty in trial data using sensitivity analyses and modeling

5.3 Health Economic Models

Health economic models are used to develop an understanding of clinical and economic benefit and costs of products from clinical trial evidence as well as under various scenarios of different costs, health systems, and practice scenarios.

• Understand, and be able to conduct, model selection and the model development process, including the technical skills of designing and building a health economic model
• Understand how to include both models for evidence generation as well as the types and application of specific types of models (eg, decision analyses, Markov/population simulation models, budget impact models)
• Identify and analyze uncertainty using sensitivity analysis 

6.1 Epidemiology, Including Pharmacoepidemiology Studies

Epidemiology is a branch of medical science that deals with the distribution and determinants of disease or other health-related characteristics in human populations.

• Have a strong understanding of the availability and quality of the common sources of existing data at local, state, and national levels
• Understand epidemiological study designs (eg, case-control, cross-sectional studies, etc)
• Understand discerning cause and effects of health and disease conditions in defined populations with the ability to interpret different frequency measures and effect measures as well as the results from cross-sectional and noninferential analyses and treatment patterns
• Understand and interpret epidemiological frequency measures (eg, incidence and mortality) and effect measures (eg, relative risk [RR], hazard ratio [HR], standardized incidence ratio [SIR], standardized mortality ratio [SMR], and odds ratio [OR], etc)
  

6.2 Pharmacovigilance Analyses

Pharmacovigilance analyses refer to the theory and practice of detection, assessment, understanding, and prevention of adverse effects or any other drug-related problem after a product has been licensed for use, especially in order to identify and evaluate previously unreported adverse reactions.

• Have a solid background in epidemiology (as described in 6.1)
• Analyze and interpret all available safety information received to identify potential safety concerns
• Communicate results via product-specific “aggregate reports” submitted to regulatory authorities 

7.1 Health Policy and External Environment Expertise

Health policy and external environment expertise means to understand and engage in the design and implementation of a healthcare system regardless of scope (eg, community versus national policy).

• Understand the issues in various sectors of the healthcare system with a focus on public health and patient well-being
• Understand the issues and pressures in formulating and implementing policy
• Understand the success factors for implementing policy within a health system
  

7.2 Fundamentals of Health Insurance: Design, Coverage, and Pricing

Fundamentals of health insurance covers the basic principles of health insurance concepts, design, and implementation.

• Understand the fundamental terms and components of health insurance and its positive and negative effects on patients and the health systems
• Have and share insight into the complex issues and trade-offs that health insurance solutions may require
• Understand the ramifications of changes and compromise within health insurance design and administration, specifically, how the design and administration affect the financial feasibility and sustainability of healthcare systems, especially those that involve private-sector insurer contributions and risks
• Understand the ultimate value of a health insurance plan to the patients and payers

7.3 Regulatory Activity and Review

Regulatory activity and review refer to understanding and applying the various regulatory requirements and reviews that are part of the process of drug discovery and drug development.

• Understand what outcomes information (eg, patient-reported outcomes [PROs], label claims) is necessary or desired in the drug label for a new or existing drug when it undergoes regulatory review
• Demonstrate a firm understanding of the regulatory standards for approval and communication of evidence. Know the regulatory requirements and restrictions for communicating to practicing physicians to achieve their understanding of and support for the product
• Adhere to all regulatory and compliance guidelines and company policies in all aspects of scientific dissemination of information, including responses to unsolicited requests for medical information
• Maintain awareness of HEOR regulatory legislation and assess its impact on business and development programs
• Facilitate the interpretation and application of HEOR regulations 

8.1 Customer Interactions and Relationships

Customer interactions and relationships refers to the ability to understand customer needs and collaborate with them effectively.

• Represent the company at external meetings to present HEOR evidence
• Understand trends or issues critical to the customer base
• Consult with external customers to understand business needs and opportunities
• Collaborate and build relationships with customers on mutual solutions for the shared needs and opportunities
• Support the development, deployment, and appropriate use of educational programs or scientific tools and resources and deliver relevant communications to meet customer and business needs
  

8.2 Health System Expertise (Regional and Affiliate Level) at the Payer Level

Health system expertise at the payer level includes a detailed understanding of how payers make decisions on coverage and reimbursement in the major health systems (see “Global Understanding of Health Systems and HTA”).

• Influence product development and commercial strategy to ensure balanced consideration of market access and outcomes considerations
• Understand how healthcare reimbursement systems work for both medical and pharmaceutical management. It includes understanding methods used to manage cost (eg, prior authorization) and quality (eg, disease management)
• Understand how cost-effectiveness and other cost versus benefit decisions are determined

8.3 Program Evaluations

Program evaluation is a systematic way to improve health programs and procedures to ensure that they are useful, feasible, and achieving the desired impact.

• Understand evaluation design, development, and implementation of qualitative and/or quantitative measures and measurement strategy, analysis, reporting, and effective engagement of stakeholders relevant to the program
• Obtain training/experience in general system and procedural analysis for evaluating and improving existing programs
• Establish and maintain metrics and monitor programs for continuous improvements 

9.1 Global Understanding of Health Systems and HTA

Global understanding of health systems and health technology assessment (HTA) refers to a general understanding of the health systems within the major global health economies assessing the value and use of a product.

• Understand the nature and process for reimbursement and access in global markets as well as the design and fundamental workings of their healthcare systems
• Provide strategic insights and inputs to shape global HEOR strategies both while the product is in development and during the peri- and post-launch phases
• Understand how to conduct outcomes research in different geographic regions
• Use quantitative and qualitative methods to assess distribution of outcomes (socioeconomic status, gender, ethnicity, religion, etc)
• Provide a description and understand the context of particular groups that may be disproportionately affected with regards to outcomes or access by a decision
  

9.2 Health Technology Assessment (HTA) Evidence Requirements and Development

Health technology assessment (HTA) evidence requirements and development covers the technical understanding of evidence development for HTA bodies.

• Understand the processes of evidence appraisal and decision making used by the primary health systems
• Understand the value of the evidence for seeking access and reimbursement
• Follow the evidentiary requirements of the various HTA bodies as they evolve
• Demonstrate the technical knowledge that can produce the evidence that is required to achieve a successful HTA decision

9.3 Product Dossier (Global and Local)

Product dossier refers to the summary of the clinical, humanistic, and economic body of evidence for a health technology (ie, pharmaceutical or device) and relevant comparators. This competency addresses how to compile and present the evidence that is collected in support of the access and reimbursement for a product.

• Demonstrate knowledge of a dossier structure and content that represents the body of evidence needed to support pricing, reimbursement, and access at the time of product launch and subsequent life-cycle reviews
• Assist affiliates in building their local reimbursement or HTA dossiers
• Demonstrate the ability to develop product life-cycle and labeling strategies that will ensure a strong dossier to the relevant authorities

9.4 Decision Analysis

Decision analysis includes many procedures, methods, and tools for identifying, clearly representing, and formally assessing important aspects of a decision.

• Understand the various methods and facilitation techniques most commonly used in decision analysis and how it can be used to formulate a recommended course of action from a well-formed representation of the decision
• Translate the formal representation of a decision and its corresponding recommendation into insight for the decision maker and other stakeholders 

10.1 Data Strategy and Statistical Analysis Planning

Data strategy and statistical analysis planning provides the opportunity to identify key study measures, establish access to the relevant data sources, implement data cleaning protocols, as well as develop the analytic files and study documentation that will be needed to support the statistical analysis.

• Understand the aim of the project, identify relevant sources of data and inputs that will be needed to answer the research question
• Develop a statistical analysis plan that is sufficiently detailed to guide file creation and statistical analysis
• Understand the technical, clinical, legal, ethical, societal, and equity issues relating to the collection, production, and analysis of data
• Understand the limitations of the chosen modeling approach
  

10.2 Statistics and Analytics

Statistics and analytics refer to the ability to apply valid and defensible statistical reasoning and inference.

• Identify…
  • Appropriate biostatistical and econometric methods to conduct descriptive and inferential statistics
    • Frequentist and Bayesian approaches to statistical inference
    • Types of statistics (eg, ratio, probability, rate) or effects (eg, fixed, random, mixed, interaction, marginal)
    • Appropriate statistical software for data wrangling, statistical analysis, and all accompanying documentation to ensure transparency and reproducibility
• Understand…
  • Testable and maintained assumptions of statistical models
  • Study designs and the implications for the choice of statistical model
  • Sources of bias related to study design, measurement, and inference
  • Causal inference methods
• Apply…
  • Appropriate components of a model in addition to functional form
  • Appropriate missing data methods
  • Misspecification tests as needed to develop a statistically adequate model

10.3 Artificial Intelligence (AI) and Machine Learning (ML)

AI refers to the broader field of creating systems/services that can perform tasks that typically require human intelligence. ML is a subset of AI, representing a family of statistical methods that focus on data regression, classification, ranking, and prediction.

• Understand the possible types of machine learning modeling, their strengths and weaknesses, trade-offs, and context of use
• Understand the risks of algorithmic bias and validity and emerging methods to address it

10.4 Statistical Communication and Reports

Communication and reporting practices are designed to disseminate the result to a broader audience that includes HEOR professionals and various stakeholders (eg, regulators, payers, providers, patients, and families).

• Communicate data results effectively via tables and visualizations
• Utilize an appropriate reporting guideline to present and communicate results
• Utilize available social media platforms to communicate research findings 

11.1 Bioethics and Human Subjects Rights and Protections

Bioethics and human subjects rights and protections are critical topics in all research to include HEOR research. The competency has an important history that explains its development as both a discipline and practice.

• Understand the history and key elements of bioethics and ethical research
• Understand and apply ethically justified criteria for the design, conduct, and review of clinical investigation
• Understand the basics of informed consent and conditions warranting waiver of consent, confidentiality, privacy, privileged communication, and respect and responsibility are key elements of this competency
• Understand the obligations of researcher to all involved, particularly the human subjects 

12.1 Diversity, Equity, Inclusion (DEI)

Diversity, equity, and inclusion (DEI) is important in patient-centered research. Understanding DEI allows for better collaboration and empathy between patients, researchers, and clinicians. Patients must be included from diverse populations when conducting basic and clinical research to account for biological variabilities as well as considerations in trial clinical design (eg, access to clinical trials, patient engagement in the planning and execution of the trial design). DEI is not a single concept as diversity, equity, and inclusion have both overlapping and distinct goals to be supportive of different groups of individuals when conducting research as well as when hiring/ recruiting individuals into the HEOR workforce (eg, different races, ethnicities, religions, abilities, genders, and sexual orientations).

• Describe when conducting research how stratification (race, ethnicity, primary language, socioeconomic status, gender identity, sexual orientation, etc) can allow identification of healthcare disparities and health inequities
• Understand practices that promote inclusive and collaborative communication that help patients, families, and healthcare teams of all health literacy levels to understand and actively integrate healthcare information
• Demonstrate evidence of self-reflection and how one’s personal identities, biases, and lived experiences may influence one’s perspectives, clinical decision making, and research
• Demonstrate knowledge of the intersectionality of a patient’s multiple identities and how each identity may result in varied and multiple forms of oppression or privilege
• Evaluate equity-efficiency trade-offs between reducing health inequities and improving health (Is it worth funding an intervention that is not cost-effective but reduces health inequity?)
  

12.2 Patient-Reported Outcomes and Other Clinical Outcomes Assessments Development, Including Psychometrics

Patient-reported outcomes (PROs) are a type of clinical outcome assessment (COA) that measure, describe, or reflect how a patient feels, functions, or survives. Other types of COAs include clinical-reported outcome (ClinRO), observer-reported outcome (ObsRO), and performance outcome (PerfO) measures.

• PROs development, including psychometrics, covers the complete process in the development and approval of a PRO
• Understand the analysis of PRO data, development of PRO measures, psychometric evaluation, and survey research. This includes the ability to conduct expert and patient interviews and to develop questionnaires to collect PRO data
• Understand the advanced design and analysis techniques used in both qualitative and quantitative research
• Understand the regulatory requirements to have a PRO included in the product’s label language

12.3 Utility and Quality of Life Studies

Utility and quality of life (QOL) studies are used to evaluate the general well-being of individuals and societies.

• Apply the PRO competency
• Design, measure, analyze, and interpret the QOL measures and the corresponding effects of treatments
• Design, implement, and analyze the use of QOL methods (eg, time trade-offs and standard gambles)

12.4 Qualitative Research

Qualitative research involves designing a controlled experiment or data collection process to gain insight into the underlying reasons, opinions, and motivations from a targeted population.

• Understand how to formulate problem statements and hypotheses to answer them
• Formulate research questions and design and protocol development
• Formulate insights from the results to provide answers as well as develop ideas or hypotheses for further research 

13.1 Clinical Trial Design and Implementation

Clinical trial design and implementation includes an ethical and scientific process of developing clinical information following Good Clinical Practices (GCP).

• Understand the entire process of developing a specific trial for a molecule in the overall clinical development process including proficiency in study design, randomization or other methods of group assignment, sample size estimation, trial-related regulation and compliance, study management, and quality assurance monitoring
• Work with clinical development teams to identify appropriate trial endpoints and coordinate HEOR input
• Understand the practical application of the regulatory requirements for drug approval

13.2 Pragmatic Studies

Pragmatic studies refer to prospective medical research studies that employ randomization but have minimal interventional activities while maintaining routine care of the subjects. The goal of pragmatic trials is to provide comparative effectiveness evidence applicable to a broad range of patients and intended for healthcare decision makers to make informed healthcare decisions.

• Demonstrate a strong understanding of when pragmatic studies are most applicable (eg, to improve practice and inform clinical and policy decisions)
• Understand the advantages of pragmatic studies over traditional randomized trials in terms of relevance and applicability to everyday practice
• Understand how to design a pragmatic study based on the key differential factors that define the continuum between a randomized clinical trial and a pragmatic trial

13.3 Prospective and Retrospective Observational Studies (Real-World Evidence) Including Digital Health

Prospective and retrospective observational studies (real-world evidence) involve noninterventional research. The term noninterventional means that the healthcare provider’s decisions regarding the proper treatment and care of the patient are made in the course of normal clinical practice.

• Understand when observational research is most applicable
• Understand the advantages of observational research studies over traditional randomized trials in terms of relevance and applicability to everyday practice
• Identify differences between observational/descriptive and experimental studies in both prospective and retrospective settings
• Understand the role of bias in interpretation of study results and can identify sources of bias in a given study
• Investigate the ways in which the validity and reliability of digital therapeutics can be evaluated and applied
• Promote the effective use of digital technologies to measure and improve patient outcomes and efficiency of healthcare systems

13.4 Retrospective Claims Database Studies

Retrospective claims database studies refer to use of secondary administrative claims and enrollment data to examine patient characteristics, medical care, and pharmacy utilization and outcomes as they occur in routine clinical care.

• Understand available databases, including their strengths and weaknesses for the current application. These data sets often provide large study populations and longer observation periods, allowing for examination of specific subpopulations
• Design studies using retrospective claims data, which may or may not be linked with other types of data at various units of measurement (eg, patient-level, area-level, hospital-level, etc)
• Understand the skill set needed to analyze the data effectively and produce reports from it
• Understand the role of bias in interpretation of study results as well as the ability to identify sources of bias and adequately correct for them

13.5 Patient Registries, Including Risk Evaluation Monitoring Studies

Patient registries including risk evaluation monitoring studies are collections of secondary data related to patients with a specific diagnosis, condition, or procedure. They are a unique form of observational studies characterized by ongoing longitudinal data collection where the scientific questions will evolve and change over time.

• Demonstrate a strong understanding of the “Observational Methods” competencies
• Understand the role of multiple endpoints and important covariates to answer hypotheses and research questions in the therapeutic area of focus
• Demonstrate a strong understanding and application of data quality and monitoring to ensure the validity and reliability of the registry data

13.6 Systematic Literature Reviews

Systematic literature reviews (SLRs) can be defined as the application of strategies that limit bias in the assembly, critical appraisal, and synthesis of all relevant studies of a specific topic.

• Understand how systematic reviews are conducted in peer-reviewed publications dealing with a health problem
• Use rigorous, standardized methods for the selection and assessment of these publications
• Understand the various options for conducting systematic review:
  • Observational (case-control or cohort) studies as well as randomized, controlled trials
  • Studies performed at a single point in time or using technology platforms to monitor evidence on an ongoing basis
  • AI-supported SLRs

13.7 Meta-Analysis and Indirect Comparisons

Meta-analysis and indirect comparisons refer to the statistical synthesis of data from a set of comparable studies to create a quantitative summary of the pooled results.

• Understand how to aggregate the data and results from a set of studies that have used the same or similar methods and procedures to assess the same outcomes and/or interventions
• Understand how to reanalyze the data from all the combined studies to generate data sets with larger sample sizes to produce more stable results on the interventions and outcomes. This will allow subsequent statistical analysis and significance testing to produce more generalizable results than were available in any single study