Healthcare data analytics identify trends to steer decisions

Mary sits in a waiting room 6 feet apart waiting to see her oncology specialist for what will most likely be an eleven minute visit.

She has wanted to talk about the fact that her husband lost his job during the pandemic and she has been skipping doses on her critical oncology medications because they cannot afford them.

She is embarrassed to take up time with such trivial matters.

Instead she spends 3 out of the 11 minutes talking about the weather and how crazy the world has become. The next 5 spent in physical exam listening to her lungs and heart and answering some pain assessment questions. The last three minutes talking about next steps in the course of treatment. A smile and out the door the doctor is gone.

He is pleasant, attentive and kind, but he does not have the time she needs. No criticism, just the reality of healthcare today.

How does a hospital capture the things patients are afraid to say out loud? The things that are ultimately affecting not only their treatment but their outcomes?

The CancerSupportSource distress, depression and anxiety screener takes 5 minutes for the patient to complete on any web-enabled device. The data collected is priceless as it provides insight into social determinants of health, mental health risks, health behavior and perception information. All of the data is accessible in real time.

The data analytics show Mary’s doctor before he enters the room to meet with her that her husband lost his job and she has been skipping medicines.

The doctor can see that over time she has become progressively depressed and that her eating habits have changed. All by reviewing a real-time clinical report. The length of the visit still stays at eleven minutes or less but the conversation changes. Mary feels heard and the doctor feels great that he has been able to address or refer Mary to resources that can help her so her outcome is the best it can possibly be. Mary’s voice is represented in the visit. The doctors skills and the care teams automated referrals help provide complete wrap around care for Mary.

A few months down the road and the real-time raw data can show the improvement.

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