A cancer patient requires much care — regular, repetitive care, depending on the stage of the tumor. Perception indicates that patients who go to an academic medical center or top cancer research center for treatment and trials receive the best care. However, is that true?
Academic medical centers have the infrastructure to their advantage and can conduct more clinical trials than a community hospital. Yet, there is enough evidence to suggest that patients choose the community setting. 85% of oncology patients receive treatment in the rural or suburban community setting. At a recent webinar, we discussed the various technology barriers in serving community cancer patients. Our panelists pointed out a severe disconnect in the oncology trial ecosystem — cancer research centers have the capabilities to conduct numerous trials, while the bulk of candidates were at the community level.
The panel included Dr. Kashyap Patel, CEO, Carolina Blood and Cancer Care and VP, Community Oncology Alliance (DC); Dr. Harish Dave, CMO, AUM Biosciences; and TJ Bowen, CSO and Co-founder, Deep Lens. Dr. Kamala Maddali, VP, Strategic Alliances, Deep Lens, moderated the session.
Despite receiving better care in an academic setting, there are numerous reasons why patients would still choose the community hospital.
Dr. Patel noted, "There is a place for the academic center. They provide excellent early-stage studies. However," he quickly added, "I think patients prefer treatment closer to home."
Dr. Dave supported Dr. Patel’s point by putting himself in the shoes of a Maryland-based patient. He questioned, "Why would I want to drive into Washington DC, fight the traffic, pay $20 to park, and then wait for two hours to be seen for five minutes when I can go to a community oncologist who is two or three miles away from me, who has got much easier access? Park right in front of his door, and walk into the office. So, multiple soft factors impact this decision."
It is interesting to note that the problems faced by both – academic centers and community hospitals – are the same. There is too much data to analyze, too many sources of data, restrictive trial windows, limited training, manual screening, disconnected systems, and increasing frustration.
An integrative approach to data collection and interpretation can address these challenges. Research coordinators are currently filtering through stacks of unrelated data to find matches to trials or rely on doctor recommendations. Both pathways have limitations and don't result in excellent recruitment.
It is essential to engage the right technology to boost patient recruitment in oncology trials. Artificial intelligence can bridge these large gaps in the clinical trial ecosystem. VIPER uses artificial intelligence to establish a connection between disparate but essential patient data sources, right from pathology reports, EMR, LIS, and data from patient interviews. It can triage patients against inclusion and exclusion criteria and identify candidates suitable for various clinical trials. All this while reducing the burden on the recruitment staff.
Read how we helped a leading cancer care institute identify 150 previously unidentified patients for 16 different studies.
Watch the webinar titled — Technology barriers and breakthroughs to better serve community cancer patients.