Validating a Framework for Coding Patient-Reported Health Information to the Medical Dictionary for Regulatory Activities Terminology: An Evaluative Study.

BACKGROUND: The availability of and interest in patient-generated health data (PGHD) have grown steadily. Patients describe medical experiences differently compared with how clinicians or researchers would describe their observations of those same experiences. Patients may find nonserious, known adverse drug events (ADEs) to be an ongoing concern, which impacts the tolerability and adherence. Clinicians must be vigilant for medically serious, potentially fatal ADEs. Having both perspectives provides patients and clinicians with a complete picture of what to expect from drug therapies. Multiple initiatives seek to incorporate patients' perspectives into drug development, including PGHD exploration for pharmacovigilance. The Food and Drug Administration (FDA) Adverse Event Reporting System contains case reports of postmarketing ADEs. To facilitate the analysis of these case reports, case details are coded using the Medical Dictionary for Regulatory Activities (MedDRA). PatientsLikeMe is a Web-based network where patients report, track, share, and discuss their health information. PatientsLikeMe captures PGHD through free-text and structured data fields. PatientsLikeMe structured data are coded to multiple medical terminologies, including MedDRA. The standardization of PatientsLikeMe PGHD enables electronic accessibility and enhances patient engagement. OBJECTIVE: The aim of this study is to retrospectively review PGHD for symptoms and ADEs entered by patients on PatientsLikeMe and coded by PatientsLikeMe to MedDRA terminology for concordance with regulatory-focused coding practices. METHODS: An FDA MedDRA coding expert retrospectively reviewed a data file containing verbatim patient-reported symptoms and ADEs and PatientsLikeMe-assigned MedDRA terms to determine the medical accuracy and appropriateness of the selected MedDRA terms, applying the International Council for Harmonisation MedDRA Term Selection: Points to Consider (MTS:PTC) guides. RESULTS: The FDA MedDRA coding expert reviewed 3234 PatientsLikeMe-assigned MedDRA codes and patient-reported verbatim text. The FDA and PatientsLikeMe were concordant at 97.09% (3140/3234) of the PatientsLikeMe-assigned MedDRA codes. The 2.91% (94/3234) discordant subset was analyzed to identify reasons for differences. Coding differences were attributed to several reasons but mostly driven by PatientsLikeMe's approach of assigning a more general MedDRA term to enable patient-to-patient engagement, while the FDA assigned a more specific medically relevant term. CONCLUSIONS: PatientsLikeMe MedDRA coding of PGHD was generally comparable to how the FDA would code similar data, applying the MTS:PTC principles. Discordant coding resulted from several reasons but mostly reflected a difference in purpose. The MTS:PTC coding principles aim to capture the most specific reported information about an ADE, whereas PatientsLikeMe may code patient-reported symptoms and ADEs to more general MedDRA terms to support patient engagement among a larger group of patients. This study demonstrates that most verbatim reports of symptoms and ADEs collected by a PGHD source, such as the PatientsLikeMe platform, could be reliably coded to MedDRA terminology by applying the MTS:PTC guide. Regarding all secondary use of novel data, understanding coding and standardization principles applied to these data types are important.

Increasing Patient Involvement in Drug Development.

BACKGROUND: To ensure the creation of treatments that maximize value at the lowest cost, all aspects of the health care system need to align with patient needs and preferences. Despite growing efforts to engage patients in research and regulatory activities, the pharmaceutical industry has yet to maximize patient involvement in the drug development process. OBJECTIVE: To gain a better understanding of the present state of patient involvement in drug development. METHODS: Through a semistructured interview methodology, we sought to identify opportunities, barriers, and examples of patient involvement in the drug development process. Telephone interviews were conducted with six senior leaders of evidence generation within the pharmaceutical industry and four patients. These interviews were supplemented with interviews with a research funder, a regulator, a patient advocacy group, and a caregiver. RESULTS: Although our interviewees spoke of the potential benefits of aligning research around the needs of patients, there were few examples they could share to suggest this was occurring at scale. A number of barriers were identified including the added burden associated with adverse event reporting, concerns about patient representativeness or their ability to participate in drug development conversations, and the costs in time and resources involved relative to returns on investment. CONCLUSIONS: As health care systems continue to evolve and establish patients as the primary stakeholder in their health care decision making, the pharmaceutical industry will need to be innovative to demonstrate the value of their products relative to the outcomes experienced by patients. Pharmaceutical companies should recognize the value of involving patients across the entire product life cycle and work to transform present perceptions and practices throughout their organizations.