As the UNM Cancer Center’s primary site for clinical and translational research, the UNM Cancer Treatment and Clinical Research Facility serves as the hub of the Center’s Statewide Cancer Care Network.
The Cancer Care Network is a series of partnerships with community health systems
The UNM Cancer Center is also developing partnerships in Alamogordo and in the Roswell/Carlsbad area.
Linked by telemedicine and virtual web, each outreach site provides a critical foothold to not only deliver improved cancer care, but also community-based cancer education and participatory research and access for patients and community oncologists to the UNM Cancer Center’s cancer clinical trials program.
Funded in part by the Center’s Minority-Based Community Clinical Oncology Program Grant (U01CA086780), these outreach sites participate in the UNM Cancer Center’s statewide cancer clinical trials network, The New Mexico Cancer Care Alliance.
The UNMCCC Clinical Research Office (CRO) and NMCCA employ
The goals of the CRO staff are to:
The CRO will provide study support to all of the Affiliate sites: consenting, sample collection, sample processing, study coordination, data entry, regulatory coordination etc. for the Participant Engagement Unit (PEU), Genome Characterization Unit (GCU) and Engagement Optimization Unit (EOU).
The CRO staff will work with the Participant Engagement Unit throughout the study to ensure cultural sensitivity.
One of the major goals for UNMCCC in the next five years is to build an integrated data warehouse. This data warehouse will automatically pull data from disparate sources and integrate it in a flexible, central repository. The data warehouse will act as the foundation of the overarching integrated informatics system and provide comprehensive access to patient information, including clinical, pathological, molecular, billing, demographic, genomic, psychological, behavioral, and socioeconomic data. RS21, an experienced local informatics company is tasked to build this warehouse. The data generated from this proposal will be hosted within this data warehouse for sharing with UNMCCC researchers under strict IRB supervision. Researchers, clinicians, and even patients, each with personalized credentials granting them specific access to the data, will be able to interact with the warehouse via an intuitive dashboard that displays information at both a population- and patient-level.
Using the cancer informatics platforms developed by RS21, UNMCCC researchers will analyze data from different sources to deliver insights that enable healthcare providers and systems to forecast challenges, decrease costs, and improve care. In addition, they will evaluate the social, economic, behavioral and geographic determinants of health. This data warehouse will further elevate patient care and illuminate patterns and possibilities within data to better match patients with clinical trials, catalyze novel research efforts, and improve community engagement and preventative testing. It will collect, integrate, and mobilize disparate data and employ cutting-edge computing and machine learning technologies to revolutionize patient care and cancer research.
At the patient-level, a person will access and engage with their personal information in the privacy of their home. In addition to connecting patients with their data, the patient portal can be used to communicate goals and value of genomic characterization, along with information about the research program, ongoing studies, publications, etc. This library of self-serve information provides patients with the information many of them seek independently on the web preceding a procedure/upon receiving test results or a diagnosis. Our patient portal will also provide a medium by which information can be collected from our patients, such as patient intake information and informed consent forms. The patient-level view will also be useful for clinicians and case managers who can use it to flag a patient for follow up with someone on a patient’s care team.
At the population-level, clinicians and researchers can investigate patterns and trends across vast amounts of data in a way that has never before been possible at this scale. By centralizing all of our data and employing machine learning and AI technologies, we will be able to match patients and clinical trials with unprecedented speed and precision. Through a geospatial tool within the population-level dashboard, combinations of data can be viewed such that signals emerge indicating why some individuals develop certain cancers, the confounding factors that determine survival rates, and the quality of life for patients with cancer. The tool will also be used to conduct targeted outreach to patient populations that have a greater risk for developing a certain cancer. By conducting targeted outreach, individuals are alerted to those preventative behaviors or screenings that have the greatest likelihood to improving their long-term health