76% of Execs to Invest in Predictive Analytics for Revenue Cycle
Most hospital and health system executives have plans to dedicate at least ten percent of the 2020 IT budget to predictive analytics for revenue cycle management.
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By - Investment in predictive analytics for revenue cycle management is up, according to a recent survey of nearly 1,500 hospital and health system CFOs, VPs of finance, controllers, and other revenue cycle leaders.
The survey conducted by Black Book Research found that only seven percent of CFOs do not have a plan to use predictive analytics for revenue cycle management in the near future.
Furthermore, 76 percent of hospital and health system executives expect to dedicate at least ten percent or more of their 2020 IT budgets to predictive analytics for revenue cycle management, the survey found.
“As fiscal pressures continue to build across the health care industry and as value-based care payment initiatives slowly simmer, health care organizations are recognizing the need for employing a robust data analytics program to pinpoint revenue cycle inefficiencies,” Doug Brown, president of Black Book, said in the press release.
Hospitals and health systems are turning to predictive analytics for revenue cycle management to supplement the skills of their current workforce. Overall, 77 percent of respondents said they do not believe their organization has staff with the appropriate skills to analyze vast amounts of data or use sophisticated predictive modeling solutions.
Other reasons for investing in predictive analytics for revenue cycle management in the next 12 to 18 months included:
- Predicting payer remittance dates to manage organizational cash flow (91 percent)
- Identifying potential claim denials before they happen (83 percent)
- Pinpointing revenue cycle management inefficiencies and breakdowns in the early stages (82 percent)
- Leveraging machine learning to predict changes in payer-specific claims adjudication rules (73 percent)
- Decreasing dependency on IT resources for accessing necessary information (69 percent
Slightly over one-half of respondents also said they plan to acquire predictive analytics solutions in the near future to streamline revenue cycle management each fiscal year, identify organization-specific indicators of revenue cycle management leakage and strength, and support patient engagement goals by improving patient payment processes.
Strengthening revenue cycle management in response to new patient payment trends is key for surviving in the current landscape. New data from TransUnion Healthcare revealed that average patient financial responsibility increased 12 percent from 2017 to 2018. Research shows that as out-of-pocket costs go up, the likelihood of collecting payments from patients significantly drops.
Ninety percent of providers also still use paper or manual processes for patient collections, creating payment capture delays and growing A/R.
“Health care providers spend significant resources and time to try to collect payment with outdated, often very manual, processes,” said Brown. “Even with patient liability increasing five times faster than overall reimbursement, some health systems are not equipped to adapt to this trend and disparate data sources and the lack of internal analytics skills are immobilizing some providers.”
Predictive analytics solutions can help hospitals and health systems not only improve collection rates, but advance revenue cycle management overall.
RCCH Healthcare Partners in Tennessee has seen a significant improvement in claim denials rates and management following the implementation of a predictive analytics solution for revenue cycle management. A machine learning tool for revenue cycle management also helped Minnesota-based Allina Health collect $2 million more in patient collections by creating a propensity-to-pay model.
Overall, 93 percent of hospital and physician financial executives believe exploring new ways to use data analytics is critical to meeting the demands of value-based reimbursement and healthcare consumerism.
However, hospitals and health system will have to overcome challenges before realizing the benefits of predictive analytics, the new Black Book survey found. Twenty-one percent of CFOs said their organization’s lack of enterprise data and disparate data sources are making predictive analytics implementation a challenge.
“Predictive analytics is a game changer in health care revenue cycle performance because it can be used to forecast revenue and correct issues that impact revenue before they occur,” Brown concluded.
