Unfortunately, healthcare systems can generate upwards of 100 incidents per month, and available claim management resources do not extend beyond the constraints of full blown lawsuits. Consequently, incident reports pile up and obscure the real risks. With risk analytics, incidents can be rapidly and cost-effectively analyzed. Then, "real" risk is identified sooner, triaged appropriately, and dealt with proactively.

Logistically, it is a simple process. The unique circumstances of each incident are captured. The situation is analyzed in the context of similar facilities and resident health. This provides the immediate insight necessary to gain perspective and focus resources accordingly. Within the long-term care industry, public access to Online Survey, Certification and Reporting (OSCAR) data, Minimum Data Set (MDS) assessments and survey results provides for highly effective predictive modeling opportunities.

Advantages of Analytics

While a few risk managers are truly gifted with a sixth sense for risk, most are not. With access to risk analytics, all claim managers can be equally and consistently equipped with the tools and potential to greatly improve their performance. Risk analytics provides the critical information needed to move forward with confidence and direct attention to the high-risk situations that will benefit most from a proactive stance.

In addition to providing a virtual red, yellow, or green flashing light on each incident, risk analytics can provide a number of other advantages, some of which are listed below:

1. Accelerate the acquisition of knowledge. The quicker we can investigate, understand, and evaluate the claim, the quicker we can reach our decision points. Does the claim have value? What is the potential value of this claim? Are we comfortable defending it at trial? Risk analytics helps us tailor the investigations because if we can identify problem areas, we can dig deeper and perform more pointed and specific investigations.

"Anytime we have access to critical information about the facility, staffing levels, potential problem areas, and so forth early in the claim handling process, we improve our chances of being able to evaluate the claim accurately and resolve it in an optimal fashion," explained Paul Hamlin, founder and president of Hamlin and Burton Liability Management and expert in the field of claims management.

2. Place claims into proper context. All falls are not created equal. The actual context of individual claims may be quite different. For example, one facility's data may demonstrate that the fall was an anomaly that occurred despite having excellent protocols and risk-management practices, while the other facility's data may reveal a true risk management weakness. This knowledge advantage offers rapid discernment of the overall quality of care provided at one facility versus another. It can also chart the course for improved negotiations with plaintiffs and, ideally, lower overall settlements.

"Risk analytics has allowed us to focus on critical claims by gaining rapid clinical and analytical insight to help us put claims into a broader context and obtain more favorable outcomes," noted Jonathan Swann, underwriter, CareSurance Nursing Home Program at Lloyd's. At a minimum, the information guides claim professionals and gives them the wisdom to determine which claims to defend and which to settle, fast.

3. Lower claim administration costs. Claim managers who research files in the traditional approach will spend between 25 and 50 percent more time completing the legwork necessary to obtain the data necessary to evaluate a claim. "Most data in the comprehensive risk analysis we could find out on our own, but it would take a tremendous amount of leg work -- [which] would be done slowly, expensively, and inconsistently," says Paul Hamlin. If risk analytics can save an insurer just 5 percent of the total claim management expense, then that impact could easily be converted into a significant competitive advantage.

4. Detect fraud. Claim fraud is a multi-billion dollar problem, to which healthcare fraud is the major contributor. While the reasons for this are many, the sad truth is that insurers can only investigate a small percentage of suspected cases because of limited resources. Consequently, it is critical to rapidly evaluate every file to identify the likelihood of fraud and then focus investigative resources accordingly. Failure to identify fraud raises claim costs, which in turn increases premiums for all insured. For insurers, even a minor improvement in the ability to detect fraud can generate a significant return on investment.

5. Triage claims. By identifying underlying problems quicker, risk analytics gives the insurer the clarity to identify real risk and fast-track the potentially large settlements at a much earlier stage in the process. These cases -- which are more likely to evolve into large settlements -- are instantly identified, designated a priority, and handled appropriately.

As the application of risk analytics becomes more widespread in the claim-handling arena, new uses of these tools will be discovered. One application currently being explored concerns causation defense. To illustrate, let's assume that a nursing home resident is afflicted with severe skin breakdown that leads to an amputation of a lower extremity. Such a case is likely to result in a lawsuit. To prepare for that possibility, the insurer can use predictive modeling to develop an effective defense strategy. By processing the detailed circumstances of the case through a sophisticated data analysis, the insurer can look at the medical condition of the resident and infer what probability existed that the resident would have experienced severe skin breakdown regardless of the facility's quality of care or resident specific care plan.

Proceed with Caution

Any statically driven predictive modeling tool has limitations, and the old adage, "garbage in, garbage out" will always apply.

While risk analytics and predictive modeling offer tremendous advantages to insurers and risk management organizations, the ultimate value is derived when the experts interpret the information correctly and make the right decisions. After all, there are many variables that go into each and every case that ultimately determine how it is settled. Once a case proceeds to court, the deciding factor is the six or eight people in the jury box. Just how they will decide is extraordinarily unpredictable. "There are precious few variables that exist between the cases we win in trial and the ones we lose in trial," Hamlin added.

Timing is Everything

With the passage of time, the cost to settle any case may increase exponentially. Risk analytics and predictive modeling provide the insurer and the defense team with rapid access to the information needed to manage incidents proactively, triage claims effectively, and settle claims before that critical window of opportunity closes. It is simply an industry "best" practice available for any insurer ready to harness the power of knowledge and technology and apply the old adage: "An ounce of prevention is worth a pound of cure."

Mary Chmielowiec is the executive vice president for insurance and Paul Marshall is director of insurance business development at PointRight. Formerly known as LTCQ, PointRight is based in Lexington, Mass. For additional information, contact Mr. Marshall at [email protected].