5 Reasons Clinical Data Analytics Are Worth The Effort

By M. Evan Hétu, SVP, data & analytics, Altegra Health

Recent survey results by CDW Healthcare found more than two-thirds of healthcare decision makers say analytics is one of their organizations top three priorities, while other recent survey results from KPMG found only 10 percent of organizations are using advanced tools for data collection with analytics and predictive capabilities.

This incongruity is not surprising. With all the health information technology (HIT) projects occurring at healthcare organizations right now: optimizing electronic health records (EHR), increasing electronic health information exchange (HIE) and expanding and securing wireless networks for mobile devices and hospital equipment, HIT professionals are understandably preoccupied with other projects.

Improving an organization’s analytics capabilities, however, is worth the effort and is completely synchronous with the concurrent HIT projects occurring in most organizations today. A key benefit of optimizing EHRs, increasing HIE and expanding wireless networks is that they all allow an organization to easily capture more data in real-time. Simultaneously building an analytics platform can leverage all data capture to drive clinical interventions and improve outcomes.

Even with the limited systems integration or data standardization that some organizations have now, powerful, actionable analytics is possible. This requires a dedicated analytics team that can be pulled away from competing HIT projects. However, once properly implemented, the following are the top five ways data analytics can improve financial and clinical outcomes.

1. Identify and intervene with high-risk patients
   The greatest benefit data analytics can bring to healthcare providers is the ability to identify and intervene with high-risk patients before an adverse event or avoidable hospitalization occurs. The organization’s internal clinical and demographic EHR data is the foundation for this analysis, but for more accurate insight into which patients are in most need of an intervention, providers need to combine claims, other outside data and advanced risk-stratification algorithms.
    
2. Prepare for value-based payment
   Earlier this year, the U.S. Department of Health and Human Services’ (HHS) Secretary Sylvia Mathews Burwell announced she would like to shift at least 30 percent of Medicare provider payments to “alternative payment models” that reimburse for value and clinical quality instead of just service volume. The alternative payment model proportion, Burwell said, may expand to 50 percent by 2018. Whether Burwell’s goals come to fruition or not, it is clear that government payers are fully committed to reducing healthcare costs through financial incentives and penalties associated with achieving care-quality metrics.
   
   Data analytics will help organizations bridge the transition from fee-for-service to value-based alternative payment models. Any participant in a Medicare-sponsored pay-for-performance program can attest that the list of quality metrics organizations must report is exhaustive. These alternative payment models Burwell mentions are likely to have similar performance and reporting requirements.
    
3. Better payer collaboration
   Closer collaboration with payers may not seem like a benefit to some healthcare provider organizations, but payers have data that providers need for more accurate analysis. Health insurers have diagnosis, treatment and medication data about patients that may be inaccessible to providers if they were reported by a provider unaffiliated with their health system or physician group. Chances are the patient or the unaffiliated provider will not update other physicians about this care either, so it is up to the payer to fill those information gaps.
    
4. Improve patient engagement
   Greater insight into patients’ conditions through analytics translates to more outreach and non-emergent encounters with high-risk patients. The increased contact and care-management support can foster a closer relationship between providers and their patients, which can nurture engagement and improve outcomes.
    
5. Insight into network leakage
   As stated earlier, claims data offers providers insight into care their patients received from unaffiliated providers. Accountable Care Organizations (ACOs) participating in the Medicare Shared Savings Program (MSSP) will likely attest that intelligence surrounding where patients are seeking care outside of the ACO network is valuable information. Out-of-network care can impact the ACO’s quality and cost metrics, so ensuring the outside providers are following evidence-based care protocols, closing care gaps and encouraging better condition management is in the ACO’s best interest. Analytics platforms that are configured to monitor quality metrics such as those associated with the MSSP, can deliver those answers in seconds instead of hours or days later.

If provider organizations are already overwhelmed with the data they are capturing, but are interested in beginning their analytics journey, apart from forming a dedicated analytics team, they should consider seeking outside assistance. Experienced advisors who are knowledgeable of provider organizations’ best practices, but also of payer organizations’ methods and risk-stratification algorithms can offer valuable insight. Advisors who have expertise with the most common IT systems used in healthcare organizations, such as Epic, would also accelerate the analytics integration.

With the right strategy and systems in place, organizations can finally take analytics off the to-do list and make it an integral part of their daily workflows.

About The Author
M. Evan Hétu is senior vice president, data & analytics at Altegra Health.