Clinical product data challenges are extremely costly for a health system. Although these issues may seem “in the weeds,” they are actually upending health systems and need to be on the radar of a Chief Financial Officer (CFO) for this reason. These challenges cause software implementations to languish, innovative analytics to stall and massive cloud migrations to suffer.
These challenges build into the larger issue of how health systems are currently trying to solve this. Analysts, informatics, value analysis, category leaders, service line leaders and expensive consultants spend an enormous amount of time cleaning this information, which is a significant opportunity cost as this time is not spent on other projects with organizational impact. As a result, savings opportunities are not maximized for the strongest possible fiscal performance.
Instead of using expensive services or hiring additional analysts to solve these problems, they should be fixed by automation through new software solutions. Supply chain teams often spend time evaluating and implementing various software solutions – whether it be enterprise data warehouse initiatives or developing large analytics innovation centers within health systems. As part of this process, IT teams are implementing significant technology solutions as they move clinical product data to the cloud. In the decision-making process, several teams within a health system typically evaluate the presentation-level data given to them, rather than diving into the process it takes to obtain the clinical product data being shown. There are many technology solutions that are sold to health systems based on attributes of the data visualizations, but this presents a challenge as they are not addressing the underlying accuracy of that data, which is what ultimately makes these visualizations more powerful, valuable and trustworthy.
CFOs at health systems have a goal of reducing overall spend and consolidating solutions. This could sometimes be driven by teams’ costs being out of sync or because of any given team not gaining the insights needed to make the most informed decisions. This lack of valuable insight is not necessarily due to the data visualization or the software being used, but it could be due to the health system’s overall challenge of solving the accuracy of the underlying data that makes these technology solutions operate more efficiently.
These data accuracy issues typically center around the complexity of clinical product data. When health systems do not have classification systems that are powerful enough to differentiate clinical parts to the level that delivers accuracy and supports the trust of clinicians, this ultimately limits the movement that organizations can make towards clinical integration.
CFOs gaining clarity into the classification system being used by supply chain teams to determine clinical product data accuracy is essential. However, if they are only relying on the United Nations Standard Products and Services Code® (UNSPSC®), this poses a significant risk. Although this classification system is well maintained, it is often not robust enough for medical devices. Any software that is built on top of this classification system will fall short of the outcomes that a health system strives towards, which is why CFOs must have visibility into this.
CFOs must ensure that the classification system is evaluated as part of the decision process for new technology and should emphasize the importance of classification that is designed specifically to address the complexity and multi-dimensional nature of clinical product data. To mitigate data accuracy issues, CFOs should uncover how a given team has evaluated the cleanliness of the data that drives software performance. Each time a CFO is presented with a decision, whether related to software, supply chain or technology solutions that rely on supply chain data, it is essential that they inquire about the process used to determine the accuracy of the clinical product data. CFOs should get curious about the amount of time front line resources are using to correct clinical product data errors.
Overall, as supply chain teams implement software solutions that drive automation, address clinical product data issues and lower overall costs, CFOs should be keenly aware of why costs accelerate in the first place, and look into the accuracy of clinical product data in all key decisions that come from supply chain, sourcing, value analysis, investment and cloud migrations.
CFOs play a significant role in the financial wellbeing of a health system. As part of the CFO blog series, stay tuned for additional blogs on how CFOs can improve fiscal performance despite the cost of personal protective equipment (PPE), the importance of clinical data variance in moving to the cloud and the CFO’s role in supply chain consolidation.