Keeping up with enterprise demands in the claims management landscape requires a bit of clairvoyance these days. Predictive analytics is providing the bridge between these kinds of needs and present protocols, increasing market insights and business effectiveness.
However, it’s not as easy to make use of predictive analytics as some companies may think. It takes more than just a wealth of data points or a good grasp of industry standards. As technology continues to evolve, user demands change and enterprise apps grant greater insight into the lives and strategies of businesses and consumers alike, there’s more to learn about these sources than ever before.
Gaining a grasp
Knowing what to anticipate in future months in terms of policy management, claims filings and business needs can help companies in the professional liability landscape plan more effectively for these periods. By tapping into the depths of client, corporate and market information already available to a firm, it’s much easier to understand how these factors add into future events.
The trouble is, not all professional liability and insurance providers can grasp how this process works. As Modern Healthcare Online reported, even when companies have access to reams and depths of data points, it’s possible to come up empty handed in strategic planning reviews.
Predictive analytics is a shifty agent, the source noted. It requires that a firm is able to classify its data points, identify trends, limit the number of factors impacting business intelligence calculations, and create a narrow outcome, specific to the firm manufacturing the results.
In this way, strategic and predictive analysis can help a single medical professional liability firm determine the likely actions of its own patients, but it may not take all outside factors into account. Still, Modern Healthcare noted, the results are more reliable than what companies can expect otherwise from some of their medical clients. According to the source, only about 20 percent of voluntarily submitted customer information was actually accurate. By creating predictive analytics based on trends in consumer usage and public information, it’s much easier for organizations to effectively adjust rates and protect themselves from abuse.
“It’s enabling strategic resource allocation among the total population,” said clinical information specialist Rishi Sikka. “If you really want to move the entire population … you need to work on the entire population, not just the most expensive.”
Even with a shaky grasp on predictive analytics, it’s possible for general professional liability practices to anticipate general trends in their user bases and come up with likely scenarios for the coming months and years. As iHealthBeat reported, this technological capability to somewhat tell the future, based on empirical data, may be in its infancy, but it’s also evolving as the more claims management and policy administrators use it.
Scalability and complexity of business infrastructure remain two of the biggest obstacles, a recent report showed. However, as iHealthBeat added, there are also problems like redundancy and compliance issues to deal with.
Still, firms are making major inroads into proper predictive analytics and business intelligence by pioneering programs that evaluate risk, integrate real-time application feedback, and come up with smarter sources for data acquisition and oversight. Electronic health records requirements are assisting professional liability organizations in gaining greater access to pertinent medical information and filing trends, thereby furthering their research and enhancing their understanding of overall market factors.
Such enhancements will hopefully help insurance agencies protect themselves- while better serving their clients. When firms are able to understand what’s likely to come next in the care of a customer, it’s easier to offer targeted referrals and superior coverage to consumers while also protecting corporate liability.