Generating evidence involves formulating the right research question(s), identifying and collecting fit-for-purpose data, applying suitable study designs, and conducting the appropriate analyses. Asking the right question is crucial as it is the stepping-stone to the development and conduct of a meaningful study.
Research: Articulating Questions, Generating Hypotheses, and Choosing Study Designs, Setting a research question, aim and objective (CJHP 2014;67(1):31-34) and Formulating Answerable Questions: Question Negotiation in Evidence-based Practice (JCHLA/JABSC 2013;34:55-60) suggest stepwise approaches to the generation of the research question.
In the first step, a flow of research ideas or topics is generated from clinical practice, patient experience, unmet medical need, pharmaceutical companies’ development plans, public health issues, or during regulatory and health technology assessment processes. It is recommended to include all relevant stakeholders in the process of ideation. A critical and thorough review of the literature forms the basis for the theoretical framework of the research question and should ideally be included in the background section of the study protocol. Such a review aims at evaluating the current evidence around the issue at hand and identifying gaps in knowledge that a study is intended to fill. The ideation process should allow the researcher(s) to ask relevant questions, select the best question(s) for research, and transform the question into a study objective, including a testable hypothesis (if the study involves hypothesis-testing). In Posing the research question: not so simple(Can J Anaesth. 2009;56(1):71-9), the FINER criteria (Feasible, Interesting, Novel, Ethical, and Relevant) are proposed to verify the desirable properties of an appropriate, meaningful and purposeful research idea.
Research questions relevant to regulatory authorities and health technology assessment bodies regarding the utilisation, safety, efficacy and impact of medicines are detailed in the European Public Assessment Report (EPAR) available for each centrally authorised product on the EMA website, with general pharmacovigilance-related aspects being described in Modules of the Good Pharmacovigilance Practices (GVP), and the European network of Health Technology Assessment (EUnetHTA)’s The criteria to select and prioritise health technologies for additional evidence generation document (2012).
In the second step, a research question is formulated through “a logical statement that progresses from what is known or believed to be true to that which is unknown and requires validation”, as described in Developing great research questions (Am J Health Syst Pharm. 2008;65(17):1667-70). A poorly defined research question can hinder the thought process, create confusion, jeopardize the development of a clear protocol. This can make the evaluation of the study results against the unclear question irrelevant and hamper the publication of the study. How to formulate research recommendations (BMJ. 2006;333(7572):804-6) proposes the EPICOT format with 5 core elements for research recommendations on the effects of treatments: Evidence (source of the current evidence), Population (population characterised by any diagnosis, disease stage, comorbidity, risk factor, sex, age, ethnic group, specific inclusion or exclusion criteria, clinical setting), Intervention (type, frequency, dose, duration, prognostic factor), Comparison (placebo, routine care, alternative treatment/management), Outcome (which clinical or patient related outcomes will the researcher need to measure, improve, influence or accomplish; which methods of measurement should be used), and Time stamp (date of literature search or recommendation). This format was adopted by EUnetHTA in its Position paper on how to formulate research recommendations (2015).
In a third step, the objectives of the studies are defined. They are more operational than the research question and can be further divided into primary, secondary and exploratory. The primary objective corresponds to the single most important objective of the study, which drives the study design, the calculation of the sample size and the methods that will lead to answer the research question. It can sometimes be a composite objective. Secondary objectives can be defined to provide additional details to support the primary objective, to add new knowledge or comparison, or to answer other questions that are relevant to the study. Objectives should be closely related to the research question, cover all aspects of the problem, and ordered in a logical sequence. The SMART criteria (Specific, Measurable, Appropriate (aligned with the research question), Realistic and Time specific) are often proposed to testify well formulated study objectives (There's a S.M.A.R.T. way to write management's goals and objectives, 1981).
Assessing the feasibility of the study could constitute a last step of this process and should be considered to ensure that sufficient information is available to apply the proposed study design, for example knowledge about the available information in the data sources. The aim is not to answer the research question directly, but to determine whether the proposed study design could allow for answering the research question with the expected statistical power and within the proposed timelines. A feasibility assessment can provide information on the number of people with a specific exposure or outcome, the availability of covariates and the follow up period needed. It can also provide insights into the potential difficulties which may be encountered in the conduct of the study or which may introduce bias. Importance of feasibility assessments before implementing non‐interventional pharmacoepidemiologic studies of vaccines: lessons learned and recommendations for future studies (Pharmacoepidemiol Drug Saf. 2016;25(12):1397-406) illustrates a vaccine manufacturer’s pragmatic approach for conducting feasibility assessments for post-authorisation studies required to address regulatory requests. This approach can be applied beyond vaccine research. The ISPE Good pharmacoepidemiology practice (GPP) explains how a data collection method or data source can answer a research question with justifications based on feasibility when relevant. Linking electronic health data in pharmacoepidemiology: Appropriateness and feasibility(Pharmacoepidemiol Drug Saf. 2020;29(1):18-29) provides guidance to assess the feasibility of data linkage based on key areas including the design of the research question for study objectives addressed using secondary data collection.
Further insights on formulating the research question and evaluating study feasibility are provided in Evaluating the Feasibility of Electronic Health Records and Claims Data Sources for Specific Research Purposes (Ther Innov Regul Sci. 2020;54(6):1296-1302).
It is to be noted that formulating a research question is an iterative process. For example, the feedback obtained from a feasibility assessment may reveal that the research question is not feasible and consequently lead to the change of the objectives or design of the study.