8 Requirements for Leveraging Clinical Analytics in an Outcomes-based Environment

There is widespread agreement that the growth in healthcare spending is unsustainable and that continuing down the same path of limited, incremental fixes won't provide the lifeline the healthcare system needs. Albert Einstein famously defined insanity as "doing the same thing over and over again and expecting a different result." Using this definition, until recently most "same-old, same-old" cost-containment efforts could be described as insane.

However, we can "stop the insanity" as the healthcare system evolves from a fee-for-service model that bases reimbursement on the volume of visits as well as tests and procedures — even when there is a lack of evidence about their clinical effectiveness or overall value when compared to other testing and treatment options. The transition to value-based purchasing that ties reimbursement to the quality and cost-effectiveness of patient care is fueling outcomes-based quality initiatives such as eliminating payment for preventable adverse outcomes including 30-day readmissions, reducing avoidable emergency department visits and preventing complications such as surgical-site infections.

Under this new model, hospitals and health systems will be forced to assume greater financial risk through their participation in new payment arrangements such as accountable care organizations, patient-centered medical homes, bundled payments and shared savings programs. This means that their survival will depend on their ability to deliver evidence-based, cost-effective, safe, high-quality care.

The unprecedented availability (some would say the deluge) of data now coming online provides the healthcare industry with an opportunity to embrace rigorous clinical analytics to drive systemic change. This will generate substantial, immediate and ongoing savings while providing smarter, better and more efficient patient care. For example, clinical analytics tools typically enable hospitals to reduce surgical complications by 5 to 10 percent, returning $1.5 to $3 million in annual savings.

To thrive in a business environment that rewards value rather than volume, hospitals must identify and eliminate variations in cost and quality for surgical and other acute specialty care, because surgery-related expenses outpace all other healthcare expenditures.

Eliminating surgical complications and wasteful care will significantly reduce the costs associated with unnecessary care that The Dartmouth Atlas, the New England Healthcare Institute, McKinsey and Thomson Reuters all estimate account for about 30 percent of the nation's healthcare spending.

Clinical analytics tools are now available to identify, quantify and correct variations in surgical and other specialty care, but there is also significant variation in their capabilities, affordability, ease of use and benefits. There are eight "must-have" key features for a clinical analytics solution that can fuel a hospital's success now and into the foreseeable future:

1. An affordable, cloud-based, hosted solution
that won't require scarce internal information technology resources or support.

2. Continuously updated, risk-adjusted clinical data configured for each surgical specialty and sub-specialty. A one-size-fits-all solution won't provide the necessary intelligence. For instance, by applying bariatric-specific clinical measures, a clinical analytics programs established by the Michigan Bariatric Surgery Collaborative helped 38 Michigan hospitals reduce overall bariatric surgery complication rates by 24 percent and decreased post-surgery ED visits by 35 percent.

3. Granular, dynamic benchmarking for procedures, physicians, outcomes and hospitals at the national, regional and enterprise levels, down to determining which treatment is best for a specific patient. For example, a patient with prostate cancer may want to factor in not only which treatment option offers the best prognosis based his specific circumstances, but which one will also preserve his ability to enjoy sexual intimacy.

4. Real-time, easy-to-understand dashboards that provide actionable intelligence based on current data. It really doesn't matter what a retrospective report indicates was occurring six months or a year ago. Capturing what took place within the past 10 minutes provides the relevant information needed to support point-of-care decision-making.

5. The ability to identify best practices,
standardize care processes and provide decision-support as a baseline for eliminating unwarranted variation.

6. Accelerated performance feedback and improvements in efficiency, quality and financial outcomes by capturing and analyzing clinical outcomes and other vital data from multiple disparate sources.

7. Quick speed-to-value
— deployment and training should be completed in two to three months, not years, and should be so easy to use and intuitive that physicians, nurses and administrative personnel can begin utilizing the data-driven intelligence being generated within days of the deployment.

8. Helps meet meaningful use
and other regulatory and accreditation requirements.

The use of clinical analytics can help health systems offset revenue declines, survive and thrive in the evolving marketplace and achieve the triple aim of providing higher quality care, achieving better outcomes and delivering both at lower cost. Using the software to aggregate and analyze clinical, financial and administrative information, healthcare providers will be able to identify actionable opportunities for patient care interventions and quality improvement while gaining the ability to track and benchmark the performance of every physician, hospital, patient, procedure, department and service across their enterprise.

Moving forward, providers will have to change how they do business to survive current and future market forces and healthcare reform. They must be vigilant and proactive about delivering high quality, efficient care, minimizing avoidable complications and bending the cost curve. A robust clinical analytics solution enabling data aggregation that leads to real-time actionable information will play an essential role in hospitals' ability to achieve sustainable, meaningful quality and cost improvements across their enterprise.

Brett Furst is CEO of ArborMetrix, a healthcare analytics and software company that helps hospitals and health systems, surgical specialty societies and health plans bend the curve on cost and quality now to thrive under value-based reimbursement.

More Articles on Healthcare Analytics:

Best Practices for Data Analytics in Value-Based Reimbursement
Intermountain Healthcare, Deloitte Form Alliance for Data Analytics

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