Data analytics drive success of new joint-venture health plan

Problem to Solve

As medical groups and hospital systems seek to improve care quality and outcomes while combatting rising operational costs and declining utilization, they are looking at delivering faster and higher-quality access and reducing costs. Unlike years past, hospitals cannot unilaterally raise prices without payer pushback or loss of business, or quickly merge their way into more productive organizations.

A leading health care system sought to develop, in partnership with a national insurer, a new health plan marketed to fully insured individuals and self-insured employers in its market territory. This joint venture would emphasize using data analytics and population health technology to identify at-risk patients sooner than prior clinical practices and provide them with earlier care access by expanding the availability of alternative care sites.

While the national insurer had forged similar 50-50 joint ventures with health systems in other parts of the country, this was the first time that the health care system developed this type of relationship. It was critical at the outset for the health care system to develop a new physician and hospital network to meet patient needs and state guidelines for care quality and access. The health care system lacked the ability to oversee and perform the necessary analytics to drive accuracy and decision-making for this new network. The system partnered with Freed Associates (Freed) to fulfill this need while simultaneously defining scope for future purposes.

Strategy and Tactics

The health care system (and its joint partner) needed all network-related analytics done well in advance of the new calendar year in order to submit its new health care plan to the state for approval, and have the best opportunity to market and sell it to prospective customers. Freed began working with this client to develop and maintain an up-to-date and accurate list of hospitals and providers that would ultimately be part of the new joint venture network – in the end approximately 30 hospitals and 10,000 providers total.

The work began with a gap analysis between the partners’ old and updated lists of providers. This was done to ensure list accuracy and better-inform the health care system’s leadership for network-related decision-making. The work involved manually identifying discrepancies between iterations of the provider lists and the network strategic design and reconciling the differences.

Given the volume and number of data records involved in creating the new network list, Freed’s involvement proved vital for tracking and maintaining all provider list iterations and documenting communications between key representatives of everyone involved in this joint venture.

At the same time, work was completed to define and document the newly created network list processes and reports. This is turn helped determine the role and responsibilities of a future full-time employee to meet the needs of this new venture.

A data analysis tracking toolkit was developed, as well as a role-specific playbook. The former included templates for tracking data files exchanged between the joint venture partners, an inventory of analyses and reports, as well as a new data dictionary defining the common terms used by each partner.

Results

Despite the complexity of verifying and reconciling roughly 10,000 provider records for the new joint venture network, the initiative was completed within the client’s prescribed time frame. The partners gained an accurate, accessible network of hospitals and providers that aligned their business strategy, met the interests of prospective customers, and addressed the state’s network requirements. Foundationally, this effort also established a repeatable methodology that the health care system can use for future new product initiatives.

Conclusion

When new market opportunities beckon, it is incumbent on health care organizations to move forward to meet such opportunities as efficiently and expeditiously as possible. By quickly and effectively performing critical data analytics to support its new joint venture, the health care system was able to reduce error risk, meet its timing goals and benefit from a new strategic growth opportunity.

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