AI Will Make Finding the Right Healthcare Provider Much Easier

March 3, 2020
It’s important to feel like you can trust your doctor, and that process should start before you even see him or her

Consumers increasingly expect convenience, ease of access, and choices. In part, this is due to disruptive technologies that have fundamentally altered a number of industries, making them more consumer-centric in recent years. Uber, for example, revolutionized transportation on demand; travel websites replaced agents, and Amazon brought outlet shopping to the home.

The healthcare industry has yet to transform similarly. However, circumstances and technologies are converging in a way that promises future change. One example is the process of finding the right healthcare provider, which will hopefully be far smoother and more effective in the future.

The problem: limitations on finding providers

The rise of the Internet and social media has certainly changed how people locate healthcare providers. Once upon a time, people relied on word-of-mouth referrals from family or friends, suggestions from their insurance company, or the Yellow Pages. 

Now, the patient journey to find a healthcare provider typically takes place online. Sources used include:

  • Online reviews: According to one survey, 72 percent of patients rely on online reviews to find a new provider.
  • Google search: The results that appear are ranked according to Google's search engine optimization (SEO) algorithms, and not all providers are included (depending on their online presence).
  • Social media: Patients solicit recommendations via Facebook and Twitter.
  • Healthcare and business directory listings: These rely primarily on providers' input of information, and the information may be outdated or incomplete.
  • Centers for Medicare & Medicaid Services (CMS) quality ratings: CMS' Quality Payment Program uses 423 measures to assess providers, but these ratings do little to provide an overall view of how good that doctor is or whether that provider is the right choice.

Though the Internet offers a wealth of information, the sources of data are disconnected, and searches are fragmented. Additionally, consumers don't necessarily know how to evaluate the results adequately, nor are those results equally valid or useful. 

The goal: transparency and interoperability for better customer choices
Consumers want better choices. In a recent consumer survey, 78 percent are interested in having a menu of options for their care, offered by multiple providers, which would allow them to choose from local providers or virtual care from specialists across the country. 

Ideally, a patient deciding which physician to use could go to a trusted website, enter her condition or symptoms, insurance plan, and location, and receive a list of options. Ideally, that list would be comprised of physicians in her area as well as those available remotely. The list could be aggregated by quality score, and include a filter such that only physicians who accept her insurance and are currently accepting new patients would show up. She could dig deeper into the quality score to see other patients' ratings and comparative outcome measures. The patient could also confirm the costs charged by each physician.

Much of the data that would help guide the search for a genuinely qualified health professional already exists. However, a significant barrier to accessing this data is the current lack of interoperability between the multiple, disparate information repositories. Different software systems do not easily communicate and use various fields, formats, and protocols. 

Another barrier is a lack of transparency in sharing this data. Currently, health plans and other payers, government databases, healthcare providers, review sites, and others either do not share or share only limited data.

The possible solution: using learning algorithms to connect information repositories

In the U.S. alone, 2.5 quintillion bytes of data are generated every day. Hospitals and other healthcare providers have an abundance of data, mostly unused, from patient demographics to financial statistics to treatment outcomes.
Artificial intelligence (AI) and machine learning are capable of understanding and using this data not only to decrease costs and improve care but to facilitate the process of selecting a healthcare provider — and ultimately improve patient outcomes. AI can process enormous data sets to make connections, extract actionable insights, and make finding a healthcare provider in the future much more straightforward.

Ultimately, finding providers is just one way in which interoperability among data systems will affect the overall healthcare industry. However, it’s an important one, underscored by the very fact that we enjoy the benefits of such a huge range of specialist providers. A general practitioner usually isn’t the right choice for spinal care. A pediatrician has none of the specific knowledge that a gerontologist needs. And everyone loses when a patient denies medical treatment because he can’t find the doctor who will accept his insurance. The right providers, on the other hand, grant a win to everyone -- especially the patients, whose outcomes are immeasurably better in the hands of the best doctor for the job. 

In other words, this matters much more than just in terms of convenience. When you’re looking for a doctor, there’s usually something wrong. You’re vulnerable in some way. The relationship between doctor and patient is a sacred one -- at once personal and professional. The search process should thus instill confidence in the person searching for care. It’s important to feel like you can trust your doctor, and that process should start before you even see him or her. 

Jeffrey Cronk DC, JD, is the CEO of Spinal Kinetics

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