Patients as People: creating clinically relevant social insights (part II)

Guest Editor Sarianne Gruber (@subtleimpact) continues her interview of Mandi Bishop, founder and Chief Evangelist of Aloha Health. Ms Bishop’s goal with Aloha Health is to put the ‘patient as person’ into the present healthcare model. Ms Gruber interviewed Ms Bishop at #MedMo16 where Aloha Health won the People’s Choice award in the Equity Crowd Challenge. The first half of the interview was previously published in Part I.

How does Social Determinants Of Healthcare (SDOH) data relate to me as a patient?

Bishop: SDOH attributes are available both the individual patient level and a “high propensity that this is you” level via micro-segmentation. Optimally, there will be personalization of information where personalization is possible and micro-segmentation profiles for when it is not.  Also, we are not trying to give the doctor more data since we think that is a big part of the problem.  “What about your lifestyle” matters which respect to you as a patient, and we at Aloha Health convert that data into insights.  When the doctor pulls up an encounter, based on our models, the EHR is populated with the insights that are available about you and your conditions.

As a workflow example, I pull up your encounter.  Aloha then pings the Aloha insights section and gets all this information about you. This is the use case we are going after:  a diabetic patient and this is the demographic information we are going after about that person.  Pertinent and clinically relevant information would be pulled up about you and on your profile.  We are only showing things that matter.  The fact that you are a 40-year woman is information the doctor already knows.  But the fact that you are a single mother, who just got divorced 3 weeks ago, is caring for an elderly parent, and has all of these other “things”, all of these “things” would influence your ability to have an insulin pump.

What makes SDOH data a must have for patient engagement and patient-centered care?

Bishop: We can really take a look at data at the individual level as well as the population level.  Everything that we are building is probabilistic in nature and will include stochastic models.  I will use myself as an example to better understand our initiative.  I have gained 20 lbs. in a year and my blood pressure had gone up 10 points.  If I went to see my doctor right now without knowing anything except that my BMI has gotten substantially high worse. Perhaps my blood work is going to be poorer than it was last time since I was on a paleo diet a year ago. I might appear to be on the verge of becoming hypertensive or pre-diabetic if you just took those things on the “outside”.   But if there was an understanding that I just got married, I traveled 300 out of 365 days last year, and I am running a new startup. Then all of these mitigating factors can create an opportunity for context.

On average, a doctor has seven minutes with you.  If your doctor has only seven minutes with you to find out all of the mitigating circumstances about your life, that might influence your care plan and you engage in your health.  If doctors could develop personal relationships with their patients it would be great, but the mass majority don’t. If my case load is 300 diabetic patients, the likelihood that I have enough time to get to know them as individuals and understand each patient’s life in context is minimal.  Think about the cancer patients and something as simple as transportation. If I had to go for infusion treatments three times a week and I can’t get there, how would my doctor know this? Aloha Health would make it possible.

Are you going to take SDOH data and build out models for common use cases?

Bishop: Yes. This is part of what we are doing right now. We have clinicians as part of our founding team, and they work with our clients as an extension of our primary research. We are also working with their clinicians to further develop and validate the clinical use cases. Also, we are validating the relevance of all these social determinants on datasets by disease state.

An opportunity space for us, once the data are integrated into the EHR, would be to address the most likely conditions that may influence the typical intervention or would influence the care pathway. What do you do for a homeless diabetic that doesn’t have a refrigerator? What is routinely prescribed for a diabetic patient may not be the answer for a different set of circumstances.  Our goal is to be able to surface all those deviations in pathways according to the clinical relevance of social determinants.  Aloha Health would provide a recommendation based on a validated clinical decision support algorithms, which we are building as part of this effort.

We are social. As founders, we all really believe in patients as partners. We believe in collaborative care delivery, and we are really interested in engagement. We know this data matters.

This article was originally published in RCM Answers and is republished here with permission and with appreciation to Sarianne plus Answers Media Company LLC’s Roberta Mullins and Carol Flagg.

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