The Power of Real-Time Analytics at the Point of Care

January 4, 2016 Inovalon

By Dan Rizzo, CIO, Inovalon

There has been a lot of talk about transforming healthcare into an industry that leverages real-time analytics. Sadly, while the cost of a cup of coffee at Starbucks appears on your iPhone in seconds and your 401k reflects every change in holding and values at any given moment, healthcare has not made it easy for clinicians to leverage similar technology. In fact, patients and clinicians are often left in the dark for months after clinical events, greatly limiting the industry’s efforts to improve quality and efficiency. The infrastructure is there, and so is the technology. The only thing left is a company that will engineer the software itself.

Why are Real-Time Healthcare Data Analytics so Important?

Too often today, healthcare information is disconnected and not readily accessible in a centralized, informed manner, greatly limiting the industry’s efforts to improve quality and efficiency. Real-time analytics tools address this issue head on by bringing disparate information from many sources into the one place it is needed most — at the point of care — in real time where the benefits can truly be life-saving.

The information gained from analyzing massive amounts of aggregated health data can provide actionable insight to improve operational quality and efficiency for clinicians and insurers. This increased efficiency is necessary in a healthcare industry rapidly transitioning from volume- to value-based healthcare. Now, more than ever, it is critical that clinicians be able to identify and address gaps in care, quality, risk and utilization, to support improvements in clinical and quality outcomes and financial performance.

Real-Time Data Analytics can Change the Way Healthcare is Delivered

The shift from volume- to value-based care has realigned the priorities of clinicians, physicians  and insurers. Real-time healthcare analytics can help improve the quality of care, cut costs and meet regulatory requirements by automating and streamlining the process of collecting and measuring massive amounts of healthcare data.

Clinicians want to achieve high quality results and/or are part of an organization that is incentivized to achieve high quality scores. The problem is that there is no way for a clinician to determine, at the point of care, specifically which quality measures will achieve a high score and what the patient has already achieved versus still has outstanding to achieve a strong score. Real-time analytics would provide a report, outlining a patient’s status and the steps necessary to improve quality, achieve compliance and realize full reimbursement for services.

In addition to the frustrations clinicians face in measuring the quality of their work, they are challenged by the lack of access and insight into the medical history of their patients, which can impact the quality of care they can provide. Making matters worse, many EHRs are poorly interconnected and the data may take too long to make its way through the system. Real-time analytics would provide instant and accurate insight into patient medical histories — including past clinical conditions, diagnoses, treatments, utilization and outcomes — even if they occurred in the ER of a resort town across the country. The information can help direct appropriate care and reduce unnecessary costs.

Clinicians often have limited insight into a patient’s disease and comorbidity status, and little time or expertise in risk score coding accuracy requirements. This misalignment can significantly impact the accuracy of documentation, associated claims data, risk score accuracy and related reimbursement for health plans and ACOs. Real-time analytics can provide insight into historical, current and predictive risk score-accuracy gaps to support accurate disease burden documentation and treatment of unaddressed and worsening conditions that need attention so that problems may be addressed before the patient is re-admitted and the hospital is penalized.

Similarly, health plans and clinicians struggle to avoid duplication of tests, because clinicians don’t have full insight on similar tests that may have been ordered. They often don’t have insight into the patient’s benefits parameters for care considerations. Real-time analytics aid clinicians in identifying unnecessary utilization and costs related to tests and insurance benefits coverage, so they can avoid duplication and costly alternatives.

Although it is important that clinicians be aware of care management resources available to a patient, it is often impossible for them to identify the federal, state, and healthcare organization-specific programs that are available. Real-time analytics provide program eligibility insight that accelerates engagement with the right patients and ensures enrollment in the right programs at the right time, to help improve care and decrease costs.

Who Will Benefit from Real-Time Analytics Delivered at the Point of Care?

Every sector of the healthcare industry would benefit from real-time analytics because it would allow clinicians and insurers to get a better picture of their patients.

Clinicians benefit by having the ability to make better-informed decisions at the point of care, a key factor in providing the most appropriate care for their patients. However, they face a dual challenge: to deliver high quality care in an increasingly complex healthcare environment and to be increasingly mindful of factors that impact performance goals such as utilization efficiency, objective metrics and healthcare economics. Real-time analytics would allow clinicians to quickly gain insight into their patients, empowering them to save time, improve care and achieve critical metrics that impact financial performance.

Real-time analytics offer health systems the ability to access the most up-to-date information. This means clinicians can assess patient-specific eligibility, gaps in care, risk scores and historical medical information at the point of care — all of which can be easily integrated into their existing operational model — to improve quality performance, ensure regulatory compliance, avoid waste and reduce cost.

Real-time analytics support health plans, ACOs, hospitals, integrated care delivery systems and physician organizations who are engaged in capitated, shared-risk and other value-based arrangements. Health organizations must demonstrate that they provide quality care to their patients. The insights from these analytics help health organizations achieve and benefit from superior quality scores, comprehensive and accurate risk score data, improved utilization efficiency and greater coordination of care.

Last, but certainly not least, real-time analytics benefit patients receiving superior quality care at a lower cost, since clinicians would have a more informed view of the patient’s comprehensive medical history. This helps clinicians minimize redundant or unnecessary testing, which they can only be certain of, if they have the right information at the right time.

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