New analytic technologies can help pinpoint wasteful industry spending.
By Lindsey Nolen, staff writer, Healthcare Executive Insight
Behind the scenes, a lot of thought is required of a hospital’s chief financial officer (CFO), especially in terms of inbound and outbound payments as well as treasury operations. To appropriately employ an intended budget, these institutions must work toward optimizing healthcare through the reduction of all financial waste, now capable of assessment via predictive analytic technologies.
The New England Healthcare Institute outlines wasteful expenditure as healthcare spending that can be eliminated without reducing the overall quality of care. According to a 2012 Health Affairs Health Policy Brief, this waste can include disbursements on services that lack evidence of producing better health outcomes compared to their less-expensive alternatives; inefficiencies in the provision of healthcare goods and services; and costs incurred while treating avoidable medical injuries, such as preventable infections in hospitals.1
In an attempt to maintain quality care while eliminating unnecessary spending, numerous studies have examined what should constitute as wasteful or ineffective within institutions. One such study, a July 2014 independent survey of hospital finance professionals by Strata Decision Technology, found that, while the overwhelming majority of provider organizations are trying to cut costs, only 17% of respondents rated their organization as successful, whereas 69% said they are just somewhat successful in reaching their goals.
Furthermore, among the key reasons cited for this shortfall were difficulties in tracking results (55%); lack of accountability (44%); inconsistent focus from senior leaders (30%), and lack of clinician engagement (29%).2 Thus, if healthcare institutions wish to diminish waste, amending these challenges must become a priority.
Implementing actionable and real world solutions to maximize the efficiency and reduce the ongoing costs of healthcare finances, one company, Vizant, has focused its efforts on helping to restore financial optimization.3
Although the majority of institutions use business intelligence (BI), analytics and big data to drive financial decision making, Vizant has employed a new form of analytics: Prescriptive Analytics. This technology instead uses a prescriptive, or preparedness plan, to maximize recourses and profitability given certain business rules, customer demand and behavior.
Additionally, while standard analytic systems are concerned with what has happened or what will happen, prescription analytics alternatively questions how to best deploy resources to elevate profitability. This strategy can ultimately assist the healthcare industry in planning more efficiently to meet budget needs through the control of money and the movement of funds.
“Prescriptive analytics takes data analysis to the next level. It takes information regarding what has happened and what has transpired and turns it into ways to best address it, maximize efficiencies, mitigate costs and increase bottom line profitability,” explained Angie Grunte, executive vice president of Vizant. “This system also helps to optimize all aspects of management and the control of funds while better preparing institutions for the emergence of new systems and banking products which may be introduced into the marketplace.”
However, this system requires an organization to establish an integrated analytics environment capable of instilling intensive data points, business rules and predictive modeling. It also only works if the analytics approach is integrated into every information system and every data base within the organization or institution.
Regardless of its complicated infrastructure, Vizant with its efforts to optimize assessments by helping companies make important decisions and maximizing profitable growth has the ability to efficiently combat financial waste in the healthcare sector. This available technology can help the industry find key ways to reduce excessive spending.
Examples of Implementation
Since data prediction is more useful when transformed into clinical knowledge, it should not merely include evidence, but interpretation and recommended actions for each outcome as well. By linking measurable events, such as cost effectiveness and predictive analytics, healthcare can more closely integrate prediction associated with costs.
“In working with one organization specifically, it had a lot of data which it didn’t know how to look at it holistically and factor into a preparedness plan,” recalled Grunte. “This caused more inefficiencies and financial waste, yet we were able to help them develop a plan to help ensure its best-in-class standing while resulting in significant reductions in treasuries and payments.”
Specifically, the role of a CFO can help to leverage drug claims data to predict potential medical costs and trend changes, while also using industry tools to compare their population against similar demographics. This comparison can additionally predict trends that can be used to put the appropriate preventative programs and measures into place. If the data shows a need for additional resources and programs is unnecessary, an institution can save funds.
The potential for hospital readmission is one element the in-context predication service is able to determine. Instead of just being able to predict which patients are likely to return to a hospital in the proceeding 30 days, “predictive analytics” can help forecast an associated cost simulation, real-time hospital census bed counts, pending medication reconciliation or adjusting order sets for education material and in-home follow-ups, according to Health Catalyst, a mission-driven data warehousing, analytics, and outcomes improvement company.4
“Although no two organizations are identical, by partnering with healthcare organizations we are able to help mitigate and manage the ongoing costs associated with their treasury and payment associations,” clarified Grunte. “For example, we examine the time frame from the point where a dollar value is generated to the processes around billing and collecting that revenue. If the organization isn’t constantly focused on fine-tuning these processes, they can end up generating financial waste.”
Being able to accurately predict an institutions future need further sheds light on what is required in terms of spending. Overall, analytics are becoming a critical tool that will allow health systems to more thoroughly understand how to eradicate waste and respond to the business model change and disruption of any accountable care.
1. “Health Policy Brief.” Available at: http://healthaffairs.org/healthpolicybriefs/brief_pdfs/healthpolicybrief_82.pdf.
2. “To Cut Healthcare Costs, Start at the Top.” Available at: http://www.healthleadersmedia.com/finance/cut-healthcare-costs-start-top##).
3. “Analytics on Steroids.” Available at: http://vizant.com/perspective/analytics-on-steriods.
4. “Prescriptive Analytics Beats Simple Prediction for Improving Healthcare.” Available at: https://www.healthcatalyst.com/prescriptive-analytics-improving-health-care.