Pinpoint cost savings with an advanced purchased services data analytics platform
Any discussion of how to decrease healthcare spending typically focuses on two realms: wasteful patient-care activities or excess medical supplies. What is seldom discussed is purchased services, such as dietary, biomedical, housekeeping, waste management and more than 1,200 other categories, even though these costs typically comprise more than 35% of a health system’s non-labor spending.
The reality is most health systems do not have a timely, accurate and holistic view of this significant portion of their budget. This lack of visibility may be causing organizations to overlook millions of dollars in annual savings and operational efficiency if they had faster and easier actionable intelligence of this spending across the enterprise.
With that comprehensive view and the ability to compare their spending against other health systems across the country, organizations stand to appreciate savings that could help avoid risky budgetary decisions that could impact clinical quality, as well as patient and physician satisfaction. An advanced purchased services data analytics platform offers organizations a complete and granular view of the spending across the enterprise to pinpoint cost savings in every category, department and facility.
The Purchased Services X-factor
Until recently, purchased services spending has been largely overlooked as an actionable budget issue because cost management has historically not been centralized or standardized, while vendors are often local or regional. On the other hand, the costs for the other major portion of the health system’s non-labor budget, medical supplies, is tightly controlled by group purchasing organizations (GPOs) and powerful national distributors. Moreover, health systems can easily track this spending since every medical, surgical and lab product contains an SKU code that can be benchmarked against on more than a dozen readily available data sources.
With purchased services management decentralized to different departments and facilities, enterprise-wide spending behaviors are difficult to track, if even tracked at all. In some health systems, these facilities or departments may even have different contracts with the same vendor and might be paying different rates. Other facilities may have decades-old vendor agreements, such as elevator maintenance, that have been automatically renewed since the first contract.
This lack of purchased services management standardization may cause organizations to overlook wide price fluctuations or vendor redundancies. For example, on a health system’s first day using purchased-services data analytics technology, it discovered it was paying two vendors for the same service during the same time period. Once they reported the oversight, one of the vendors paid a $300,000 credit for invoicing for unused services. Another health system analyzed its new medical gas agreement and the analytics tool identified $380,000 in overspending that did not align with the new agreement. The health system was immediately able to earn a credit for the overcharges.
Considering there are thousands of vendors to track at every health system, these incidents are certainly understandable. With an advanced purchased services spending data analytics platform, regardless of the size or location of the vendor, those costs can be tracked in real-time and compared to historical data.
Consultants and GPOs Alone Falling Short
Until recently, the main challenge facing health systems was that performing purchased service spending data analysis was a highly manual process. Due to the time and staffing-resource demand, the analysis was performed mostly by GPOs or expensive consultants based on spending data that might have been several months to more than a year old. The result would be a static performance report delivered after several months. Even considering the extra time and expense, consultants were typically only able to categorize 80% of an organization’s purchased services instead of the 95% that less expensive data analytics technology can categorize in much less time.
Performing this type of analysis internally with basic spreadsheets or reporting software would be cost prohibitive considering the amount of time it would consume to capture and interpret the data. Worse yet, performing internal analysis without advanced information technology could result in inaccurate results if categories are miscoded in the health system’s general ledger, or vendors are being paid without a signed contract, which happens more often than one may assume.
Advanced analytics technology can offer categorization knowledge and algorithms to identify and correct for miscoding so a complete, accurate analysis is always generated. In addition, when the platform is built on a robust analytic database, health systems can view continuously updated spending performance of hundreds of hospitals and health systems for timely and reliable comparisons.
Reliable Analysis Drives Negotiation and Operational Strategy
With accurate, enterprise-wide purchased services spending data, health systems can view spending trends and identify potentially rogue vendors, which, when eliminated or renegotiated, can easily save 5-10% on those costs. Benchmarking capabilities allow organizations to determine whether they have unfavorable contracts compared to industry peers, or if spending is higher simply due to geographic location; for example, a health system in Burlington, Vt., will likely face higher snow-removal fees than a similar-sized organization in Richmond, Va.
This actionable intelligence can then be used to develop a strategic data-driven work plan to reduce purchased services spending, prepare for vendor negotiations and instantly measure ongoing performance on that plan.
However, some of the largest savings can be identified immediately after a new vendor agreement goes into effect because the sales representatives often have not changed some of the facilities to the new pricing. With the purchased services data analytics technology, the health system can be quickly alerted of this vendor’s contract non-compliance.
Conversely, instead of only reviewing pricing trends, advanced data analytics allows health systems to determine whether overuse of services may be inflating costs. With this insight, organizations can help change the frequency of a service, or adjust staff or provider behaviors and significantly reduce costs without compromising quality of care.
As more health systems look for ways to reduce costs, purchased services is becoming a significant new opportunity to evaluate and find savings. The first step is to understand the organization’s total spend within purchased services categories. Once this intelligence is available, organizations can quickly identify waste and prioritize the work plan to maximize the savings impact.
With the help of new purchased-services data analytics platforms, this is no longer a multi-month engagement that requires a consultant to manage. The health system can have this easily accessible information within just a few days to pursue potentially millions of dollars of savings opportunities.