Advanced Analytics Holds the Key to Achieve the Triple Aim and Survive Value-based Purchasing

My Folder

healthcare analytic adoption modelEvery hospital and health system has to juggle significant IT needs with a limited budget. New and innovative solutions are constantly becoming available—with the potential of making care delivery or operations more efficient and more accurate. In the middle of these demands and possibilities, hospital executives have to prioritize and decide which technology solutions are the most critical to the health of their organization.

I call these most critical IT solutions “survival software.”

Survival Healthcare Software of the Past and Present

Much of yesterday’s survival software was deployed to automate manual processes in the operational areas of a facility. Over the past 30 years, organizations have implemented software to manage such areas as patient flow, billing, finance, HR, claims, revenue cycle and time tracking. These solutions have provided a foundation that helps hospitals understand their operations more fully.

More recently, data acquisition solutions have filled the role of must-have survival software. Of course, the biggest of these data-acquisition investments by far has been the electronic health record (EHR). Thanks to major government incentives and requirements attached to EHR use, most providers—in both the acute and ambulatory space—have accelerated their efforts to digitize clinical documentation.

Do these examples of past and current survival software constitute a wise investment? Absolutely. Will they be sufficient for healthcare organizations to survive in an industry evolving toward ”pay for performance”? The answer is no. Healthcare organizations have to be smarter to survive in the new reimbursement environment—and this requires advanced analytics.

Healthcare Analytics Adoption in the Industry

In terms of the sophistication of analytics adoption in the United States, most organizations are at the lowest level of the Healthcare Analytics Adoption Model – a level characterized by patchworked point solutions provided by numerous vendors, with each solution addressing only one specific analytics need. The patchwork-solution level can be very expensive to maintain and produces inconsistency in reports as each point solution is capable of generating reports with only its own data and in its own style. The problems are exacerbated because the point solutions can’t and don’t talk to one another — a system like this is incapable of supporting longitudinal, enterprise-wide analytics.

Ideally, these organizations will progress from point solutions to an analytic framework that will allow them to systematically move through phases of clinical analytics adoption so they can perform and/or produce:

  1. Standardized Vocabulary & Patient Registries
  2. Automated internal reporting
  3. Automated external reporting (CMS, PQRS, HEDIS, etc.)
  4. Population management
  5. Cost-per-case metrics
  6. Cost-per capita metrics
  7. Predictive analytics
  8. Prescriptive analytics

Survival Software of the Future: Advanced Analytics

Advanced clinical analytics solutions are the survival software of the near future. For the most part, however, healthcare organizations have made only minor investments in an advanced analytic software—though this trend is changing rapidly.

Healthcare systems that have invested in a complete framework for advanced analytics have yielded impressive results. Examples include Intermountain Healthcare, The Mayo Clinic and Dartmouth. These analytics pioneers had to invest in and create their own advanced analytics platforms because no sufficient solution was commercially available.

Luckily, commercial solutions are now available that enable organizations to adopt advanced analytics without creating their own platform from the ground up. Many organizations—like North Memorial Health Care, Texas Children’s Hospital and Indiana University Health—are leveraging such products to quickly establish a complete framework for advanced analytics.

These organizations are already:

  • Improving outcomes
  • Improving patient satisfaction
  • Reducing waste
  • Standardizing care based on evidence-based best practices
  • Lowering operating costs
  • Reducing the need for expensive consulting work because they can use their data to answer questions themselves
  • Understanding the impact of the switch to value-based purchasing for each payer contract

These organizations are, in short, moving steadily toward achieving the Triple Aim—reducing cost, improving outcomes and improving the patient experience—while maintaining their own financial health.

Investing in an advanced analytics framework is something that should begin today. Survival in the near future of healthcare will depend on it.

Tell us: What steps has your organization taken to invest in analytics? What is your timeline for adopting an advanced analytics platform?