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U.S. healthcare costs have steadily increased for years and now represent more than 17 percent of the gross domestic product (GDP). Lower reimbursements and chronic illness are considered primary culprits of increasing costs, although many experts blame a system that focuses too much on treatments and not enough on outcomes.

However, an overlooked problem is a lack of understanding about the true cost of care. Costs are typically analyzed and generalized at the service department level instead of at the patient level. Also, are we talking about the cost to insurance companies and the government, or the cost to healthcare providers? Are costs based on reimbursements or the care itself?

The inconsistency, confusion and lack of concrete measurement related to healthcare costs make it virtually impossible to implement cost-saving changes. Instead, areas such as administrative costs, personnel, salaries and expensive services are targeted for cuts, which does little to solve the bigger problem. Successful providers aren’t rewarded and are unable to thrive, which gives ineffective providers little motivation to do better.

Activity-based costing (ABC) helps to overcome these challenges by identifying the correlation between a specific activity and the resources required to execute that activity, and then determining the cost of those resources. More informed healthcare decisions can be made when you have a clear understanding of the cost of each service at the patient level for the full cycle of care.

Activity data collected through the ABC model may include the number of patients that call a practice and schedule appointments, the number and type of diagnostic tests and procedures performed, medication, staffing requirements, and how much time is spent with each patient by a doctor, nurse, tech, etc. Expenses may include salaries, supplies, equipment and facility costs. This data is used to create more accurate cost and profit projections, which leads to more efficient processes without compromising the quality of care.

Although the majority of healthcare organizations are interested in using ABC, most are manually collecting and analyzing data from disparate sources. Aside from this process being slow and inefficient, it can lead to estimates and conclusions that are grossly inaccurate. The healthcare industry as a whole needs to explore new methods and technology for leveraging the mountains of data at its disposal.

Big data analytics is the process of gathering, integrating, organizing and analyzing large sets of structured and unstructured data for the purpose of discovering valuable business insights. In the healthcare sector, this means using data from sources ranging from insurance claims and a doctor’s examination notes to test results and social media. Big data analytics can be used to pinpoint the best possible treatment for an individual or group of people, optimize procedures, create operational efficiencies, and understand patient behavior. Predictive analytics can be used to help healthcare professionals proactively intervene with certain patients to prevent illness and reduce the risk of complications or readmission. By identifying trends and patterns, providers can identify at-risk patients based on geography, age or other relevant data.

Healthcare organizations can also use big data analytics tools to crunch the numbers for ABC, providing more reliable measurement and forecasting of healthcare costs. Armed with solid data and insights that all parties can support, industry stakeholders can then make data-driven decisions that not only reduce costs but deliver better outcomes for patients.

The trend of skyrocketing healthcare costs can only be reversed in a responsible way if costs are accurately identified and measured. Those insights exist within big data. Pivot Technology Solutions, through its portfolio companies, can help healthcare providers embrace ABC and use big data analytics to address the cost crisis head-on.

by John Flores