Does a Healthy Population Mean a Healthy Bottom Line?

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Think strategically while adopting new payment models to successfully manage the bottom line

In recent years, the buzz in healthcare has surrounded population health management and value-based care models. A one-size-fits-all population health solution, however, might not produce necessary results for the adopted contractual risk. Different value-based care structures—from shared savings, to bundled payments, to full risk—involve very different needs to manage bottom line.

Key functional drivers of a population health solution include patient engagement, provider oversight, protocol management and financials and costs. However, the type of contractual risk creates different key performance indicators (KPIs), metrics and operational approaches. To manage this, healthcare organizations must first map how changes in the industry and payment rules impact the organization. Based on these regulations and changes, an organization must develop a technology, process and patient strategy to effectively manage desired clinical and financial outcomes.

How Providers were Profitable in Fee-for-Service

In the current value-based care landscape, organizations leverage different population health tools than in the fee-for-service world. Previously, providers who managed contract terms and encounter costs made a profit based on the number of patients they treated.

The required data was solely financial information from revenue cycle and claims systems, and analytics were localized to encounters. The need for clinical data, patient engagement, protocol oversight and provider oversight were minimalized in the fee-for-service world.

Impact of Pay-for-Performance

As the healthcare industry transitioned to a pay-for-performance model, population health tools such as patient engagement applications and patient portals evolved, but were not combined with existing processes and workflow. With the introduction of clinical quality measures such as the Physician Quality Reporting System (PQRS), the Healthcare Effectiveness Data and Information Set (HEDIS), Meaningful Use (MU) and others, providers had to treat these measures as a separate operational process because they were largely being paid for reporting. As a result, the performance measure results did not directly affect payment, and therefore, the systems managing these were not integrated with operational systems.

This process changed when there became a need to manage performance measures. The focus value-based purchasing created on specific protocols meant specific measure performance compliance averages went into the high 90 percentiles. Providers had to shift their processes to be rewarded for the value of care they provided instead of the number of patients they treated.

Bundled Payment Forces Operational Differences

Further, bundled payments and shared savings require different management processes and tools needed to support patient care decisions, and organizations will be looking at their bottom line as they invest for the future. Managing bundled payments is dependent on provider collaboration, ensuring protocols are followed, data is shared across providers, and patients are active participants in their care, especially post-discharge.

Provider collaboration requires communication with patients and other providers in different care settings. To manage these transitions, processes and tools have to support interoperability, scorecards, real-time alerting and automated analytics. As multiple providers share records, the volume of data grows exponentially.  Engaging patients outside the four walls of doctor offices and hospitals could easily increase the volume of data by a hundred times. This will inevitably force a strategic review of system capabilities since traditional analytics tools will not be able handle this type of workload.

Shared Savings Drives Outcomes

A shared savings model adds additional complexity for providers as opportunities to save money must be found in addition to streamlining communication and collaboration. Identifying where costs can be reduced through service or preventing emergency department visits and/or admissions is key for provider organizations.

Data sharing helps providers see a full patient history and understand which patients follow protocols as well as those who do not, and so it is still foundational with shared savings. Tools and processes to measure gaps in care and determine where opportunities are needed can help improve the execution of the system. Normalizing visits and populations followed by statistical analysis provides a foundation for strategic decision making.

Choosing the Best Model for Provider Organizations

Provider organizations have learned there is no one-size-fits-all model. Organizations may end up buying individual tools to solve problems associated with different payment structures. However, integrating different types of analytics and data sources can eventually lead to higher interoperability costs, additional technical oversight and end-user confusion of where to get support and necessary answers.

Healthcare organizations must choose the best model for their organization based on the amount of risk they feel comfortable taking on and the current technology infrastructure in place.

Providers should look at their data strategy to help determine which risk-level makes sense for their organization. A data strategy should manage, normalize and curate data from multiple sources to create a strong interoperability platform. This platform should be able to scale for not just for today, but tomorrow’s needs as well, where organizations will need the processing power to run real time and complex analytics on large scale data.

This foundational data layer can be used to feed other metrics engines to enable a best of breed approach for different types of analysis. The data layer enables a consistent understanding of the enterprise’s data, enabling downstream systems to succeed. Otherwise, there is a high chance an organization could lose credibility over time due to data integrity issues.

Think Strategically on Where Healthcare is Going

As healthcare organizations approach contract negotiations and enter into new payment structures, negotiations will likely trigger many other decisions that will affect an organization’s strategic ability to perform.

Handling these decisions strategically, from people to process to technology, will determine the success of not only the immediate initiative, but also bottom line, regardless of the structure of the payment model.

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About Author

Jeffrey Springer

Jeffrey Springer is vice president of healthcare solutions at CitiusTech. Jeffrey drives the product management and strategy in various areas of healthcare, from payer to provider, clinical to financial, analytics to transactional at CitiusTech. In his over 15 years of healthcare industry experience, Jeff has worked with healthcare technology vendors including Siemens, Medecision, McKesson and CareScience. He also founded the first payer-provider contract management company in the country. Jeffrey holds a Mechanical Engineering Degree and is an MBA from University of Pennsylvania - The Wharton School.

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