Health care organizations that aren’t already prioritizing liability and risk management should consider the current climate. Data published in the ninth annual Zurich Healthcare Risk Insights benchmark study revealed that claim severity has been on the rise since 2006, reported Claim Journal. As a result, the total sums being paid out for closed claims has increased as well.
According to the Aon annual hospital liability report, the cost of the average closed claim reached an all-time high of $463,000 in 2012, said CNN Money. The cost of closed claims has continued to hover in this vicinity, reaching an average price of $459,000 as recently as 2014. Furthermore, a growing trend of cyber attacks on health care organizations and subsequent data breaches has put additional pressure on administrators to account for digital attacks.
Predictive analytics provide improved visibility for hospital stakeholders
Becker’s Hospital Review emphasized that the ability to correctly prioritize tasks is absolutely critical to successful risk management. Few solutions provide health care decision makers with the all-encompassing visibility necessary to prioritize solutions like a reliable predictive analytics solution. The extra data equips users with insights into the nature of risks at a granular level, along with the ability to perform separate cost-to-risk measurements for each department.
The data provided by predictive analytics can do more to help hospitals limit liability claims than help decision-makers to better prioritize risks. Advanced analytics can also be used to study modern and past claims data for trends that predict the future of the industry. By staying on top of the technology curve with the helpful hints provided by big data, healthcare organizations can limit the costs of staying up to date with the industry and compliant with a rapidly evolving claims market.
Data collected in the lab can be used to balance utilization and cut costs
Unnecessary medical expenses, such as the cost of covering avoidable medical tests, make a considerable contribution to the healthcare industry’s expenses. According to the Institute of Medicine, about $750 billion goes toward incorrectly utilized resources each year. In addition to ramping up costs and generating overlapping inefficiencies, poorly managed lab practices can make a healthcare organization liable for numerous compliance failures.
Predictive analytics provides the visibility necessary for decision makers to plan out a multivariate approach to managing utilization. A broader scope and conclusions driven by the data-supported nuances in patient behavior results in far more accurate analysis and fewer liabilities to manage. Pay close attention to what analytics tools can do before making an investment.
Robust reporting and analytics tools can make all the difference
Healthcare organizations depend on reporting and analytics tools to help them get a clearer picture of what’s going on inside the facility. Unfortunately, all the data in the world won’t serve any useful purpose until it is put into context, such as when compared to years of client information and used to make an educated prediction about the future. Healthcare organizations must pay close attention to what predictive analytics tools can actually do before making an investment.
The ability to benchmark performance against industry standards, automate workflows, standardize operations and monitor employee performance are vital features for hospital administrators to look for when choosing a new analytics tool. In addition to providing healthcare employees in the field with more accurate decision-making data, the holistic observations that can be drawn from predictive analytics data is ideal for providing the C-suite with an bird’s eye view of operational efficiency and potential liability issues as they develop. Resources flow more freely when the top level is in touch with the issues impacting the floor.