The healthcare sector has seen many improvements over the years, thanks to advancements in technology and in artificial intelligence. While there are numerous ways that machine learning continues to be a benefit, many providers are beginning to understand the important role of how social determinants assists in producing better outcomes for health. That is why more and more providers are looking into how social determinants can boost revenue while improving overall care.
The Importance of Utilizing Predictive Analytics and AI
Recently, an article in Healthcare IT News reported on the importance of social determinants. Some of the many factors that qualify for social determinants of health (SDOH) are social isolation, income security and literacy. Key personal factors, such as these, can greatly influence the patient’s quality of life and overall health outcomes.
Working to understand and improve a patient’s SDOH has for a long time been a vital part in adding to the overall health of the population. However, a recent report looked at how they can inform a more compressed and streamlined cycle of payment as well.
There needs to be more of a granular understanding, with regards to the social determinants of patients, so that providers can achieve a greater insight into many areas from how to create a better care plan to understanding how to approach payments and billing. This is a suggestion from Matt Hawkins, who is the CEO of Waystar, a cloud-based revenue cycle management company.
Presently, a lot of that data is collected using either by using clinician notes or through self-reporting. Waystar has discovered that a large portion of patients who would benefit the most have yet to converse with a provider regarding their social factors; one in five of those considered to be the healthiest patients still experience some risk of SDOH.
Therefore, by leveraging predictive analytics and gaining the assistance of machine learning, Waystar and IT vendors like them could add context that is better to data which is known already about a patient; for instance, their address. This can have a large bearing with their clinicians on having the ability to better structure the care they provide. Hawkins said that, “it’s one thing that a person lives on 100 North & State Street for instance. It’s another to know it’s an apartment building that doesn’t have an elevator and is four stories high.”
The Larger Trends That Social Determinants Create
The information that Hawkins points to included other data points, like whether the patient possesses their own vehicle or relies on public transit. These factors would greatly impact how a provider may go about caring for the patient.
Quality of care, reimbursement and payment are interconnected tightly, as providers are looking to offer the best care possible. Also, the goal is to reduce wasteful or unnecessary` spending while being able to acquire payment with the least amount of problems.
Remembering the simple things, like calling on a patient to take their medications or to remind them of an appointment, or making sure they can acquire adequate transportation back and forth to an examination room, can result to having positive outcomes and avoiding costly readmissions that are costly. Additionally, understanding that every patient has their own social determinants is vital to having the quality of care improve.
Hawkins envisions gaining better insights into SDOH through using predictive analytics as a means of spotting these challenges while addressing them before they turn into barriers to care or payment. Hawkins said that, “the provider is responsible more and more for the total health of patient, not just a single episode. Understanding SDOH can really help understand that patient. All of that would inform how you care for that patient from a clinical perspective and what you can do to make patients life easier from financial perspective.”
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