Use of RWD, SDOH and patient cartography to eliminate the dead angles from the patient’s journey

Although most diseases are well defined, the patent experience for those who have the same condition may differ considerably for a multitude of reasons. The physical and psychological impact on patients is significant. Comorbidities, genetics, financial situation, social life, ethnicity, life experiences, environmental factors also play a role. This is why clinicians and pharmaceutical companies must consider the real world data (RWD) for the development of drugs. Without this crucial information, clinicians and drug developers create “dead angles” which prevent them from fully understanding the condition and what is necessary for effective treatments. A recent webinar organized by Medcity News and Purlelab explored the importance of the results reported by patients as essential to repair these dead angles through the objective of non -small cell cancer (CNPNC).

RWDs are essential tools to identify and highlight significant risk factors that are often overlooked. These data, such as social determinants of health and socio-economic barriers, offer a more holistic vision and reveal these “dead angles” than traditional clinical trials, according to their design, simply cannot.

The main objective of clinical trials is to assess the effectiveness of a new treatment and its safety profile, generally compared to current treatments and best practices. Clinical trial protocols light up each aspect of a study, from diagnostic tests for biomarkers to the administration of treatment methods, such as surgery, chemotherapy, targeted therapies or immunotherapy.

Patient centered results

A challenge with clinical trials is that it can take up to a year to recruit participants. Professional and family commitments make potential obstacles to regular attendance in person. The clinical nature of a study means that data from the vital signs of participants often differ from their family environment. Variations in drug support, daily challenges and emotional assessment of life with chronic disease manifest themselves differently for each participant in the clinical trial and can have a significant impact on the results of clinical trials.

Although randomized clinical trials for people with NSCLC follow the tumor response and survival, there are many subtle nuances of the disease that have a significant impact on the quality of life of people with disease, but that clinical studies, in general, fail to capture. Pain and fatigue are the most common symptoms that can make an emotional assessment over an prolonged period of time. They lead to an inability to exercise, to make walking difficult, to contribute to restless sleep and to apply for work at work. However, this information is not systematically recorded or evaluated in clinical data.

Although clinical trials need a high level of patient membership to be effective, membership can be complex to unpack. Undilted side effects, comorbidities, such as depression, access to transport and requests for a career can shed light on a patient’s support.

Social determinants of health

Defined as non-medical factors that influence the duration and quality of life of a patient, the social determinants of health (SDOH) extend underlying the social, economic and environmental conditions facing individuals and their communities. SDOHs are particularly relevant to oncology and are increasingly considered as a critical factor having an impact on the results of health and quality of life. Some studies link SDOH factors to 75% of cancer occurrences. SDOHs are recognized as independent risk factors of lower health results, exacerbating inequalities in the continuum of cancer care.

Since CBNPC is a respiratory disease, it should not be surprising that the environment could play an important role in the CPNPR patient course, because Dr. Ben Freiberg, the main computer systems, lead with GCS computer catalysts from Genentech, stressed in the webinar.

“The ability to join other data to the data we have of the patient’s journey is important. I could say, “Look, there is [a higher number of people with asthma] in this city. But what I could also seek are pollution cards that show the types of pollution that exist across the country. Is it an environmental factor that weighs and potentially influences the development of asthma? The ability to join these other data sources in a significant way and really based on the population, as opposed to any individual patient, really allows for the search for these deeper ideas, in search of correlations which could be causality, depending on what you offer, why a certain disease tends to be more widespread in certain populations of people living in certain places. “”

Regional legislation can also dictate the types of screening available from one state to another.

Steven Emrick, Purlelab’s main vice-president of clinical IT solutions and Healthnexus®, noted that biomarker tests for lung cancer non-small cells for insurance regimes varied by the state varies. Sixteen states require this biomarker test.

“Purlelab actually did a study on this subject some time ago, and they examined the populations of patients who receive biomarkers for lung cancer not with small cells. They found that, per capita, per 100,000 people, the lung cancer rate between whites and African-Americans was very similar. This is a continuous problem in this country.

He added: “For me, the northern star of the real world proves that data to influence not only the way in which drug development, the development of therapy, diagnostic development accelerate, but also the strengthening of this information on regulators and decision -makers to modify health results.”

Cartography of the patients’ journey

One way of helping to visualize the complex experience of health care of an individual over time is the mapping of patients. The objective is to better understand the obstacles, support, interactions with the services and overall results of patients from the patient’s point of view. This approach helps to identify friction points and improvement opportunities in the continuum of care.

The rupture of the patient’s journey in distinct stages facilitates the complete cartography of patients. Among the common executives are:

• Pre-diagnosis: capturing initial symptoms, self-assessment, research and initial concerns
• Initial contact: the first direct interaction with the health system (for example, call center, visit in person)
• Diagnosis: the state confirmation process and its staging
• Treatment: active management of the disease, including therapies and continuous care
• Post-processing / Current care: follow-up, management of symptoms, life adjustments and long-term well-being

Take advantage of RWD sources:

Electronic health files (DSE): These provide clinical granular details, including diagnoses (for example, ICD-10 codes), procedures (for example, CPT codes), laboratory results (for example, biomarkers tests), prescriptions and doctor notes. Although rich in clinical depth, DSE can lack a complete view of the care provided outside a specific health system and often contain unstructured text which requires advanced treatment.

Administrative complaint data: This data captures the billing and reimbursement information of payers, offering a longitudinal view of meetings with patients between various suppliers and parameters. It is invaluable to understand the use of health care, costs and monitoring of patients flow over time.

Patient registers: These systematically collect specific information, often granular, on patients with a particular disease or receiving specific treatment. Registers may include data elements that are generally not found in DSE or complaints, such as detailed evaluations of biomarkers, behavioral factors (for example, smoking status) and the results reported by patients (pro).

Social media data: Publications and discussions on forums and platforms specific to lung cancer provide underect and real information on patient symptoms, side effects, treatment challenges and emotional impacts. This offers a raw and real -time understanding of the feeling and priorities of patients.

Results declared by patients: These are direct reports of patients on their state of health, their symptoms, their functional condition and their quality of life, captured without interpretation by a clinician. The advantages are crucial to understanding what really matters to patients, such as relief of symptoms, quality of life and satisfaction of treatment.

Analytical techniques: Qualitative data analysis (QDA) is used for publications on social networks and interviews transcriptions to identify themes and models. For more important DSE data and complaints, advanced analyzes, including AI and automatic learning, are used to identify trends and predict patient behavior. Retrospective and prospective observation studies are common conceptions for RWD analysis.

Take advantage of the immense various forms of RWD, facilitated by the digitization of patient data, revolutionizes the development of drugs. It advances a more personalized approach to health care and help clinicians meet patients where they are. This is the only way to follow to improve the recruitment and participation of clinical studies and will help us to develop more effective drugs that not only improve patient health for various patient populations, but also their quality of life. The reduction in side effects of treatment will also improve the observance of drugs and lead to a healthier and more robust health industry.