Leveraging Data to Enhance Patient Care: Addressing Social Determinants of Health in Oncology Care

US Oncology Network Senior Business Intelligence Specialist Gunjan Sharma shares insights on the impact of health-related social needs, Beer’s criteria medication prescribing patterns, and how research can inform the development of support services for patients with cancer. 

My name is Gunjan Sharma. I am a senior business intelligence analyst with the US Oncology Network. I started working with the impact analytics group within the US Oncology Network about two years ago and have been heavily involved in programs like the Oncology Care Model (OCM) and its successor the Enhancing Oncology Model (EOM), and commercial analytics programs. Prior to my current role, I worked with the geriatric Medicare population and analyzed trends and patterns within Medicare and Medicare Advantage population to understand how to control cost, increase engagement, limit utilization, and use existing tools to improve patient wellness. 

One of my roles with Oak Street Health several years ago focused on understanding population health patterns in areas of Chicago. That work really gave me exposure to older underserved populations. I've also been working on alternate payment models (APMs), which explore ways to bring reform to the health care payment systems. 

Could you share some examples of health-related social needs (HRSN) and why they may especially impact the outcomes and experience of patients with cancer? 

CMS is heavily focused on HRSN in EOM and practice redesign activities. Some examples of HRSN are food, housing, etc. In these early stages, we are trying to evaluate the data we have related to HRSN. Our goal is to learn about the impact of social determinants of health (SDOH).

To reach this goal, we first need to understand how much data we are collecting. And health-related social data points can vary from person to person depending on their finances, social needs, gender identity, etc. All of these are very important details that we want to include going forward when we are thinking about our patients and delivering tailored care. 

In the past, the typical experience for a patient in the US health care system is to meet with a provider for 20 minutes and then go home. The provider often does not understand a patient’s background and unique needs. But we want to meet patients where they are. This change could have a very positive effect on the overall understanding of patient needs but also impact costs and care utilization. 

Please share an overview of your research around the effects of megestrol and any key findings. 

We looked at prescribing patterns for megestrol within the Medicare population. For background,  Beer’s criteria are used for understanding the list of inappropriate drugs for people aged 65 and older. This is a widely use criterion and gives a very broad list of medications not advised for geriatric patients for various reasons such as adverse effects on the heart and other organs. 

We studied megestrol, just one of the many medications on the list, to understand the results of taking the prescribed medication. Megestrol is prescribed to patients with cancer as an appetite stimulant to help them to gain weight. Our cohort of patients was aged 65 years and older and selected from our HER. We followed the patients who were prescribed megestrol for 12 weeks. Typically, you would see the results of a medication after 12 weeks. 

We compared the average weight of the cohort patients who were not prescribed megestrol to those who were and saw no significant difference. That is how we concluded that megestrol has no weight-gaining effect on the geriatric population. It is known to have some harmful effects, which we want to study further in the future. 

In what ways do you think that this research could inform the development of support services and community resources for cancer patients to address their health-related social needs? 

In this research around Beer's criteria, we wanted to make our body of evidence based on data available to the oncology community and providers so that they can make informed prescribing decisions depending on their patients. 

As far as SDOH is concerned, understanding the limitations of prescription patterns and the ability of a medication to perform is important for the betterment of patients. SDOH comes from holistically looking at a patient as a whole. We want to give providers evidence that helps them avoid prescribing a medication that may lead to adverse events in the oncology patient population. While our study was a database study that showed that megestrol has no weight-gain effects for geriatric patients with cancer, with a given patient with a specific set of needs could benefit from megestrol. We still want providers to use their best judgment for specific patients in terms of the treatment plan they choose.