Chapter 4 How to Collect Clinical Data
4.2 Case Report Forms (CRFs)
In clinical research, case report forms (CRFs) are essential tools for collecting standardized data from study participants. Note that case report forms are any paper or form that will be filled in at the case or participant level. By that definition, even a consent form is a case report form! And each clinical study may utilize multiple CRFs (e.g., one for consent, another for medical history, another for reporting any adverse effects). CRFs are useful for several tasks already discussed within this chapter – specifically, tracking adverse events or outcomes (like those discussed in the Risk Prediction section) or tracking demographics and medical history for identifying cohorts (as discussed in the Cohort Identification section). CRFs are also useful for topics this chapter will discuss in later sections (e.g., Retrospective analyses).
Designing CRFs that are accessible and sensitive to the different needs of participants requires careful consideration. Questions within CRFs should be formulated to gather comprehensive and accurate clinical data while ensuring participants feel safe, respected, and comfortable. This section explores the types of questions that can be asked using CRFs with a focus on accessibility, sensitivity, specificity, and comfort for people
While within a study, CRFs help to ensure standardization in data collection, there may be a lack of standardization when comparing data between studies if each study did not use the same CRFs or comparable/subsets of questions within forms. This section will provide guidelines for types of questions that may be found within CRFs and writing these questions; however, there aren’t necessarily templates that have been used widely within the field. Further, your specific study needs may also require different or additional types of questions – the guidelines within this section are not exhaustive/all-encompassing of what may be encountered within the field.
Here, we explore the different categories of questions that may be included within case report forms:
- Demographic and Socioeconomic Questions
Capturing demographic and socioeconomic data is fundamental in clinical research to understand the background of study participants. However, these questions must be asked in a manner that respects privacy, avoids assumptions, and helps identify people with different life experiences. It’s also good practice in order to respect privacy to include an option allowing the participants to leave the question unanswered or respond with “prefer not to answer”.
- Sex and Gender: When asking about gender and sex include an option of “prefer to self-describe” to capture more information.
- Ethnicity and Race: Ethnicity and race questions should be specific and use respectful language, allowing participants to self-identify rather than selecting from a predefined list.
- Socioeconomic Status: Questions about employment, income, or education should be framed to capture social determinants of health without making participants feel judged. For example, asking, “What is your current employment status?” with choices that include full-time, part-time, unemployed, student, and unable to work can help gather relevant data without stigma.
It is essential to use neutral, non-judgmental language and to explain why these questions are being asked, ensuring participants understand the relevance of their responses.
- Health and Medial History Questions
Health and medical history questions provide critical information about baseline conditions and potential risk factors of participants. These questions should be framed clearly and respectfully to avoid any discomfort.
- Medical Conditions and History: Questions about past and present health conditions should use clear, accessible language. For example, “Have you ever been diagnosed with any of the following conditions? (Please check all that apply)” followed by a comprehensive list containing all necessary options.
- Medication Use: Questions about current and past medications should include over-the-counter and alternative therapies, and space should be provided for free-text responses to capture additional details.
- Disability and Functional Status: For many populations, it is important to use person-first language, such as “Do you have any physical, sensory, or cognitive impairments that you would like us to be aware of?” and provide space for participants to describe their specific needs. However, different populations have different preferences. The “Disability Language Style Guide” from the National Center on Disability and Journalism provides some basic guidelines, thorough discussion, and community specific advice on this topic (“Disability Language Style Guide” 2021).
Avoiding medical jargon and providing definitions or examples can help ensure that participants understand the questions, and confidentiality should be emphasized to encourage honest responses.
- Experience and Quality of Life Questions
Understanding how health conditions and treatments affect participants’ daily lives and well-being is essential, particularly for those from communities who experience health disparities and may also experience unique challenges.
- Daily Living and Social Functioning: Questions like “How often do your health conditions affect your ability to perform daily tasks (e.g., cooking, cleaning, working)?” can help assess the impact on daily life, with options ranging from “never” to “always.”
- Emotional and Psychological Well-Being: Including questions such as “In the past week, how often have you felt anxious or depressed?” using a scale from “not at all” to “very often” can provide insights into mental health needs.
- Support Systems and Social Networks: Asking about social support (e.g., “Do you have someone you can rely on for emotional support?”) can help identify participants’ needs for social and emotional resources.
Using sensitive language and providing mental health support resources where needed is crucial when discussing emotional well-being to avoid triggering emotional distress.
- Sexual and Reproductive Health Questions
Questions about sexual and reproductive health must be asked with sensitivity, as they can be deeply personal, particularly for groups who may face stigma.
- Sexual Orientation and Gender Identity (SOGI): Instead of just predefined categories, open-ended questions like “How would you describe your sexual orientation?” and “What is your gender identity?” allow participants to self-identify. Offering the option to skip these questions respects participants’ privacy. Options can be provided with a space or text box for the person to fill in their own descriptor, but having the categorical data will allow for easier analysis for those that select one rather than every response being from variable open text responses.
- Reproductive Health: Questions about menstrual health, contraception, or pregnancy should be framed neutrally. For example, “Are you currently using any form of contraception? If yes, please specify.”
- Sexual Activity and History: Questions should be direct but framed sensitively, such as “Are there any sexual health concerns you would like to discuss? Your answers will help us understand how to better support your care needs.”
These questions should always be optional, with confidentiality emphasized to encourage honest, comfortable participation.
- Treatment Preferences and Decision-Making Questions
Understanding participants’ preferences for treatment and decision-making is vital for providing patient-centered care, especially for certain groups of people.
- Decision-Making Preferences: Questions like “How involved would you like to be in decisions about your healthcare?” offer a range of choices from “I prefer to make decisions myself” to “I prefer my healthcare provider to make decisions,” allowing participants to express their autonomy.
- Cultural and Religious Considerations: Asking, “Are there any cultural, religious, or personal beliefs that we should consider when discussing treatment options with you?” ensures that care is respectful and culturally appropriate.
- Treatment Burden: Questions such as “What level of inconvenience or side effects would be acceptable to you when considering a treatment?” help to gauge participants’ preferences and comfort levels.
These questions should be framed to respect participants’ autonomy and encourage honest responses without fear of judgment.
- Accessibility and Accommodation Needs Questions
To ensure that all participants can fully engage with the study, it is essential to ask about accessibility and accommodation needs.
- Language and Communication Needs: “What is your preferred language for communication? Do you need an interpreter or translated materials?” These questions help ensure that participants can understand the materials.
- Physical Accessibility: Asking, “Do you require any specific accommodations to participate in this study (e.g., wheelchair access, hearing aids, visual aids)?” ensures physical accessibility.
- Format Preferences: “Would you prefer to complete this form online, on paper, or verbally with assistance?” helps accommodate different needs and preferences. Providing multiple options and allowing participants to request changes at any time is crucial to accommodate evolving needs.
Providing multiple options and allowing participants to request changes at any time is crucial to accommodate evolving needs.
- Cultural Sensitivity and Identity Questions
CRFs should respect different cultural backgrounds, values, and identities without perpetuating biases or assumptions.
- Cultural Identity and Practices: An open-ended question such as “Are there any cultural practices or beliefs that are important for us to be aware of in your care?” allows participants to share relevant information.
- Dietary Restrictions and Preferences: Asking, “Do you have any dietary restrictions or preferences that are culturally or religiously motivated?” ensures that these are respected.
- Community and Belonging: “Is there anything about your community or background that you would like us to know to provide better care?” encourages participants to share relevant aspects of their identity.
These questions should be open-ended, allowing participants to skip questions they find irrelevant or uncomfortable.
- Ensuring Comfort, Trust, and Privacy Questions
Fostering a sense of safety and trust is especially important for individuals who may have experienced discrimination in healthcare settings.
- Comfort and Confidentiality: Asking, “Do you feel comfortable with the way your information is being collected and stored? Are there any specific concerns you would like to address?” helps build trust.
- Feedback and Preferences: “Is there anything about this form or the study process that you find confusing, uncomfortable, or concerning?” invites participants to share their feedback.
- Consent and Voluntary Participation: Questions like, “Would you like to be contacted about the results of this study or for future research opportunities? Participation is entirely voluntary.” reinforce autonomy and respect.
Reminding participants of the confidentiality and voluntary nature of their involvement can help foster a trusting environment.
The guidelines above sometimes suggest use of open-ended questions where participants would provide free-text responses rather than selecting pre-defined categories. This will require researchers to process those free-text responses and may decrease the overall standardization.
Designing specific and sensitive CRFs for clinical studies requires a thoughtful approach that respects the different backgrounds, privacy, and comfort of all participants, especially those from communities that experience health disparities. By using accessible language, offering multiple options, respecting autonomy, and providing a safe space for participants to express themselves, researchers can gather meaningful and accurate data while ensuring participants feel valued and respected. These considerations are vital to fostering clinical research that captures enough information about a wide variety of individuals. Case report forms (CRFs) are often tailored to specific studies and may vary widely in structure and content, lacking standardization across different projects. Despite this, certain themes are commonly expected in CRFs, including sections on participant demographics, medical history, treatment outcomes, and adverse events, ensuring essential data collection across a variety of study designs. By thoughtfully addressing both unique study requirements and universally relevant data points, researchers can optimize CRFs for consistency across clinical studies.
4.3 Clinical Studies and Trials
Clinical data generated from clinical trials and observational studies form the backbone of evidence-based medicine. The ability to analyze and interpret this data enables researchers and clinicians to answer a variety of important questions that directly impact patient care, treatment decisions, and healthcare policies.
4.3.1 Clinical Trials
Clinical trials are tightly regulated studies, controlling patient recruitment and monitoring administration and impact of treatments or interventions (“What Are Clinical Trials and Studies?” 2023). The goals of clinical trials include assessing the safety and efficacy of new treatments or interventions, comparing different/existing treatment options, determining the optimal dosage and administration of interventions, and identifying potential side effects or adverse events.
Definition 4.1 The NIH’s definition of a clinical trial is “a research study in which one or more human subjects are prospectively assigned to one or more interventions (which may include placebo or other control) to evaluate the effects of those interventions on health-related biomedical or behavioral outcomes.”
The NIH provides 4 questions and additional clarifications to consider when identifying if a study is a clinical trial or just a clinical study (“NIH’s Definition of a Clinical Trial,” n.d.).
Definition 4.2 Prospectively assigned: Refers to a pre-defined process (e.g., randomization) specified in an approved protocol that stipulates the assignment of research subjects (individually or in clusters) to one or more arms (e.g., intervention, placebo, or other control) of a clinical trial (“NIH Clinical Trials,” n.d.).
4.3.2 Observational Studies
In observational studies, patients are monitored and outcomes are measured, but there is no intervention or assignment ((Overview of clinical study designs)[https://pmc.ncbi.nlm.nih.gov/articles/PMC11009715/]).
4.3.2.1 Case-control Studies
In case-control studies, a group of individuals who have a certain disease or condition are identified as cases, and are compared to a group of individuals without the disease or condition (these are the controls). Group level summaries of outcomes, such as medical events or other biological measurements, are compared between the case and control groups. In case-control studies, there is a risk of bias, in which the group of cases and group of controls are systematically different, beyond the disease or condition that is being studied. Therefore, it is important to match the groups in terms of individual characteristics as much as possible.
4.3.2.2 Cohort Studies
Cohort studies follow study participants over time. Participants are recruited into the cohort if they share a specific characteristic that is being studied. They are then followed over time, and monitored to see which participants develop a specific outcome. Cohort studies can be prospective (the cohort is identified and then monitored), or retrospective (the cohort is identified about a time period has passed and past data is obtained).
4.4 Retrospective Analyses
Does this belong in collecting data or acquiring data?
Retrospective analysis involves the examination of pre-existing clinical data to answer specific research questions, explore hypotheses, and identify patterns or trends. This method leverages historical data collected from medical records, administrative databases, registries, electronic health records (EHRs), or other sources of clinical information.
4.5 Research Design Considerations
Researchers need to intentionally use methods earlier in the research process than data analysis to manage data biases associated with clinical data, especially EHR.
One of the most important challenges in using EHR data in cancer research is that, as in many other fields, healthcare data are plagued with several types of biases that result from disparities in the delivery of healthcare. Overall, cancer research has historically relied on data from high resource academic medical centers, which disproportionately provide care to patients who are White, have high socioeconomic status, and live in urban areas. As a result, medical knowledge produced from these data have disproportionately benefited those patients. Different sources of bias are prevalent in EHR data. For example,
- Information representativeness bias occurs when certain groups are disproportionately less present in the EHR because they have no contact with the healthcare system.
- Information presence bias, on the other hand, occurs when certain groups may be represented in the EHR, but have disproportionately less comprehensive healthcare data due to issues such as overall lower access to and use of healthcare service, lack of a primary care provider, lack of access to specialty care, and lack of access to digital resources (e.g., patient portals, home sensors, telehealth) that can be used to provide healthcare data.
- Treatment biases happen when certain groups receive disproportionate access to more advanced treatments, which is often determined by social drivers such as insurance, distance, health literacy, and socioeconomic status.
- Algorithm bias further amplifies these previous sources of bias by leveraging biased EHR data to make predictions about diagnosis, treatment and prognosis that are used by clinicians to make potentially biased healthcare decisions, which are then documented in the EHR.
Recent advances in sophisticated and costly technology such as genetic testing, artificial intelligence, and digital health, which are disproportionately available in high resource healthcare systems further compound the problem. Therefore, cancer researchers increasingly need to use intentional methods to prevent, identify, and correct for biases in EHR data. For example, the National Institutes of Health Pragmatic Trials Collaboratory has made several recommendations to address EHR data biases in research (Andrew D. Boyd et al. 2023a; Andrew D. Boyd et al. 2023b):
- Include data from low resource healthcare settings such as community health centers that provide care for patients who have low socioeconomic status and live in rural areas.
- Engage with communities during study design and study conduct to ensure proper data collection, analysis, and representation.
- Use data collection methods for self-reported data that rely on more accessible technology such as text messaging, using accessible and culturally adapted communication.
- Include subgroup analysis by different demographic groups according to variables such as socioeconomic status, race, ethnicity, sex, geographical location, and social determinants of health.
With such approaches, cancer researchers while aiming to avoid exacerbating health disparities, in addition help to reduce disparities.