Healthcare providers and insurers partnering in accountable care organizations must work to avoid data wars, says IDC analyst.
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As IT executives at health plans and healthcare delivery organizations strive to establish successful accountable care initiatives, they'll need to develop more transparent procedures and practices as they analyze business and clinical data, concluded Cynthia Burghard, research director at IDC Health Insight.
Burghard outlined her thoughts in a blog that squarely identifies data analytics as the foundation upon which a successful accountable care organization (ACO) will depend. However, in approaching the task of collecting, sharing, and acting upon clinical and financial data, providers and health plans must organize and coordinate their collaboration in a way that avoids "data wars."
As they work together to craft a business intelligence driven model, both partners must strengthen their trust as they work toward meeting the goal of tying reimbursements to quality measures and cost reductions.
"Every party comes to the table with a different set of data, which rapidly turns the discussion into one about data accuracy, not about terms and conditions of the relationship," Burghard wrote in her blog. "Transparency and consensus, particularly on reimbursement and performance measurement, will be critical to success."
She said previous reimbursement and business models have failed in healthcare, in part, because of this lack of transparency and a lack of tools to access and sort critical information.
"Typically it will be a provider organization asking for health plan data, so from an IT perspective the provider has to be able to accept the data from the health plan, understand how it's mapped, understand what the data means, and determine how you're going to integrate that data with [the provider's] information," Burghard told InformationWeek Healthcare .
ACOs will also need experienced analysts to reconcile data quality issues, as well as advise other analysts on data interpretation. Likewise, experts will need to know how to use business and clinical data to meet accountable care quality measures.
"Health plans and provider organizations will have to hire analysts that know both payer and provider data, so if I'm a provider and I'm bringing in all this payer data, I need to understand all the nuances of that data," Burghard said during an interview. "For example, they need to know what a member benefit means. There is just all of the domain knowledge about insurance processes and data that's really important to understand."
In her blog, Burghard also noted that in situations where there are similar uses of the data, "ecosystem" members--including hospitals, physician group practices, and employer members--must agree to use the same data and methodologies. She said this is critical to forming a relationship of trust between health plans and providers.
Furthermore, health IT executives need to be flexible and have adaptable data models to accommodate new sources of data. New provider reimbursement methodologies will also require new clinical and financial data expertise, Burghard observed.
"All of a sudden quality is going to be an important factor in reimbursement methodologies. There are models today that model only financial data for reimbursement, but we need to add clinical quality data and determine what metrics we are going to use to define and then evaluate a reasonable performance against that quality ... so it's again new data sources," Burghard said. "Because the development of these methodologies is still in their infancy it will take a while for providers to settle on an appropriate methodology."
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