Widespread use of advanced comparative effectiveness and large-scale monitoring may still be a bit far off. But they are on the horizon, and headway is being made.

For health organizations, especially public sector health agencies, there is first the often complicated task of linking disparate pieces of data across multiple sources.

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As LexisNexis Risk Solutions senior director Kim Jayhan will outline at the upcoming Government Health IT Conference & Exhibition, held June 17-18 in Washington, D.C., that's is the first step on the path to meaningful analytics, blending together multiple databases to create a platform for probing immediate needs – then going from there.

For hospitals and health systems, examining a patient’s clinical and claims data in tandem can let analysts create profiles for internal quality research or to comply with Medicare, Medicaid and commercial insurance contracts, especially accountable care ventures.

For federal, state and local health agencies, from CMS on down to the county health department, there is just as much potential to tear down data silos and start picking fruit that even in the early digital age has been slightly out of reach – from providing citizens with comprehensive web and mobile-friendly information on hospital quality, disease rates, pollution, and mass transit, to transforming how the country cares for the 65 million Americans on Medicaid.

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With legislatures around the country growing weary of increasing Medicaid costs – in many states the largest or second-largest part of the budget — state health leaders are being tasked with designing new accountable and managed care policies for millions of Medicaid beneficiaries, many of them new to the system.

Along with implementing modern claims and enrollment systems, a new wave of needs is emerging to track Medicaid beneficiaries going through the healthcare system in real-time, as health policies incentivize an emphasis on home and community-based care.

In New York, public hospitals and community-based providers are in the midst of a Medicaid redesign, tasked by the state with collaborating to try new delivery models for chronic disease management and home-based services.

After paring back the growth rate of New York’s $54 billion Medicaid program, Governor Andrew Cuomo won a waiver from the Centers for Medicare & Medicaid Services to invest $8 billion on a Medicaid program transmission that aims to reduce avoidable admissions by 25 percent in five years.

In Los Angeles, the Department of Health Services, the country’s second-largest municipal health system, is in the midst of transition to a new EHR and, along with that, a large patient database integrating clinical, pharmacy and Medicaid health plan data.

With 20,000 employees, four public hospitals, 18 free standing health centers, and partnerships with 150 community clinics that provide a large amount of primary care, “we’re a large agency trying to run a large system,” said Anish Mahajan, MD, director of system planning, improvement and data analytics.

In California, Medicaid has traditionally been paid for with fee-for-service. “But much of Medicaid is moving to a managed care model of payment, which means we are assigned lives and are responsible and at risk for caring for those lives with high value and high quality,” Mahajan said.

LA DHS and many other Medicaid providers across the country have to submit detailed quality and spending reports to managed care plans and regulators — and they also need to have to have real-time patient profiles to target those at high risk.

The health system is also participating in a health information exchange initiative integrating clinical data from other hospitals, which someday may be used for analytics as well, Mahajan said.

A key to success in learning from big healthcare data “will be to remain focused on our ultimate goal: gaining actionable insights into the best ways to treat the patients in the care system,” as Sebastian Schneeweiss, MD, vice chief of pharmacoepidemiology at Brigham & Women’s Hospital, wrote in the New England Journal of Medicine.