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Mary Chmielowiec

Executive vice president of insurance, PointRight

Barry Fogel

Managing director, PointRight

Insurance claims resulting from a charge of medical malpractice

are all too common in the US, forcing some doctors to think twice about the level of service they offer patients, who ultimately lose out the most.

But the medical profession—doctors, nurses, hospitals and, to an extent, patients—is fighting back through its support of medical liability reform, which has now been boosted by the provisions contained in President Obama’s recently passed healthcare reform bill.

Detailed analysis is needed, however, and PointRight, the industry leader

in providing data-driven analytics, is leading the way. US Captive spoke to executive vice president of insurance Mary Chmielowiec and managing director Barry Fogel to understand the methodology behind the analysis of liability, and the benefits it provides to the medical industry.

Why did PointRight get started in analysing liability?

We have been providing consulting and data analysis to nursing homes for 15 years, but in 2004, we began to really focus on helping nursing homes reduce their professional liability exposure by improving their quality and identifying high-risk situations.

When we tried to sell these services, we had the naive idea that

people should get discounts from commercial carriers, but we soon realised that there’s no such thing as a regular price; so we began to assemble a database of nursing homes’ professional liability loss histories so that we could do predictive modelling on who gets sued and why. So far, we have collected loss data on more than half of the nursing homes in the US.

What sort of information and tools are available to measure risk?

We have come up with a way to measure and stratify risk. The quantitative analysis allows us to identify which risk management programmes will have the most impact on risk reduction. We use very technical predictive risk models that by analysing, managing and controlling the losses can enable captives to act more intelligently and less intrusively.

For example, our underwriting analytics make use of a comprehensive database of public and private information such as occupancy, payer mix, staffing analysis, survey results, survey deficiencies, and measures of structure, care processes and clinical outcomes. These are combined with data elements of known predictive value, which are systematically extracted from the application and from the loss history.

Through our diagnostic process, a facility’s performance is

benchmarked against that of other facilities within its state, survey district and rating territory. Potentially modifiable risk factors that deviate adversely from the benchmarks and have significant impact on risk are identified, and a risk management prescription is developed that focuses on those factors.

For risk management, a facility may make use of its Minimum Data

Set (MDS). The MDS is part of the US federally mandated process for clinical assessment of all residents in Medicare or Medicaid-certified nursing homes. This process provides a comprehensive assessment of each resident’s functional capabilities and helps nursing home staff identify health problems. The completion of an MDS record at least four times a year is a requirement for facilities receiving any government money. For a facility, our tool analyses an MDS record and identifies risk in the residents. The tool is focused on high-risk monitors and identifies residents who are likely to have a fall, who suffer with pressure ulcers or who are near the end of life.

If we are looking at a particular member of a captive and it seems

to have a problem with residents with pressure ulcers, a tool like this could be put into its system so that it can monitor these residents and hopefully avoid anything that might lead to litigation.

How do you help captives manage claims?

Each captive is different when it comes to managing claims. Some

do it themselves and some use a third-party administrator (TPA). It is very typical for a TPA or claims manager to have a one-size-fits- all attitude. Some captives will fight everything, some will bury their heads in the sand and some will pick the lawyer with the lowest hourly rate. Using analytics, you can efficiently triage the claims and decide whether each claim needs to be settled promptly (as it may have a huge exposure) or be defended (as the facility may be in the right). A TPA or a captive can be much more specific about which lawyer it hires, and this could ultimately be the difference between winning and losing. It certainly will impact the settlement amount.

When a claim occurs, how can a facility determine its defensibility?

If there is a claim, tools—via the use of models—can analyse in a couple of hours how bad the claim is for the facility. We can determine whether it is going to have trouble defending itself (because of its track record), or whether this is unusual for the facility and it would have a very good case in defending the claim.

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