An Analytical Approach to Improve Healthcare

It seems as if there is a new catchphrase that emerges routinely as we make changes to improve healthcare. Such terms include "accountable care organization," "shared savings," "population health management," and perhaps the key to significant change: "data analytics."

In a recent white paper authored by Ken Terry, he points out that healthcare analytic application can be broken down into business and clinical intelligence (some experts referring to the acronym "B&CI"). Business intelligence applications address organizations financial and operational aspects such as contract negotiations, facility management, resource utilization, and cost analysis. Clinical intelligence applications support quality improvement, care management, and population health management.

Tools for "B&CI" are essential to the success of "at risk" organizations. In the pay-for-value environment, analytic data is critical. In the past, data has not been adequate due to retrospective collection, clinicians neglecting to enter data elements, difficulty extracting necessary data elements from multiple systems and transforming it into a useable format, and the problem of interoperability. Traditionally, claims data has been used for population health management and risk adjustment to determine financial risk. Experts believe that to get real value, data it must be real-time clinical data.

One of the best ways to collect real-time clinical data is widespread utilization of the Medicare Annual Wellness Visit (AWV). An automated and efficient application to deliver the AWV will satisfy the purpose of clinical intelligence as follows:

• Assess population health needs in order to develop appropriate methods of service delivery
• Stratify the population by level of health risk
• Predict which individuals are likely to become seriously ill
• Identify individual care gaps
• Measure intermediate and long-term outcomes
• Evaluate performance of providers and organizations on quality measures
• Drive quality improvement programs
• Measure and analyze reasons for variations in care

Applications available that couple the automated AWV with automated capture of ICD-9/HCC data will provide business intelligence to assist with financial risk stratification, utilization management, and allocation of provider reimbursement.

Combine business and clinical intelligence with the ability to deliver critical preventive services and an efficient AWV becomes a critical piece of the success of "at-risk" healthcare organizations.

The goal for the future of healthcare has been defined as quality healthcare, decreased costs, and patient engagement and satisfaction. The path to reach that goal seems to be headed towards the accountable care organization (integrated healthcare organization, managed care organization) to deliver care. Patients within these organizations must undergo clinical health risk assessments for the appropriate collection of clinical and business intelligence for the success of the organization. Mandatory AWVs will improve the chance of reaching the goal for the future of healthcare.