Why many hospitals have lagged in adopting healthcare analytics

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Across a growing number of hospitals, nurses and physicians are starting to use healthcare analytics to deliver better care and patient outcomes.

These hospitals are finding ways to deliver more efficient and appropriate care while lowering costs, improving outcomes and raising patient and staff satisfaction, says Jean Drouin, MD, CEO at Clarify Health Solutions, which markets an artificial intelligence/predictive analytics real-time care guidance platform.

So why hasn’t analytics been more widely adopted?

Hospitals have lacked recent data because there can be a nine-month time lag in the data being available; or the data is siloed and difficult to find; or data is not delivered at the individual patient level, Drouin explains. “At the patient level, you want to see the right sets of care decisions such as an operation or prescription or referral to another provider.”

Workflow analytics are available to ensure a patient is not receiving duplicate care but is receiving timely appointments—that’s care being done at the patient level, he adds. “We have Precision Medicine to match cancer drugs; we need Precision Medicine for workflows.”

Thus far, the healthcare industry hasn’t really bought into production efficiency, Drouin contends. “Federal Express and Amazon have analytics to predict the route a package should take with follow-up procedures to change the route if necessary. We can do the same with healthcare to deliver care quicker and cheaper. We can reveal to doctors in real time when and where a patient should get the care and not just what care to deliver.”

However, many clinicians remain skeptical of the data being shown to them, contending it can be patchy, late or lacking in precision. But Medicare’s decision to make its data broadly available to the industry will spur provider acceptance of analytics and organizations will have to reframe their investments in analytics, Drouin predicts.

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The annual spend on information technologies and analytics for companies in other industries generally is two percent or more of annual operating income, he notes. That could spur additional healthcare industry consolidation for organizations to attain a certain size that makes additional investments in analytics more affordable and valuable.

Drouin sees a time coming soon when smaller hospitals unable to hire a financial analyst because of a lack of funds will merge into larger entities to take advantage of analytics, among other benefits. When the electronic health record meaningful use program started, some physicians over time started joining larger organizations to save money and take advantage of another provider’s EHRs, he recalls.

The evolution of risk-based and bundled payment reimbursement models by insurers is another carrot enticing physicians to take a new look at adopting analytics, according to Drouin. Doctors are assessing their past care performance and how they can do better in the future as they face the consequence of being paid based on quality and outcomes—and payment transparency enables colleagues of a physician to compare themselves with the physician.

In 2018, healthcare organizations will face having to use advanced analytics engines and patient-level insights to master 3 core capabilities, Drouin predicts. They are:

• Understand variations, both big and small, in care workflows at the individual patient, clinician and facility level to enable clinicians and care delivery partners to improve their performance. The key here is sharing data with physicians and across care teams to gain buy-in and collaborate to make improvements to care delivery.

• Prescribe precise and personalized care journeys by risk-stratifying every patient to produce a transparent care map that everyone can plan against from pre-op through recovery. The key here is physician engagement and adoption, which is the shortcoming of analytics rollouts at most healthcare organizations.

• Monitor and coordinate care in near real-time to identify and address issues before or as they occur. The key here is leveraging analytics internally and for a patient-facing application to help patients become stewards of their own care and true partners of their caregivers.

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