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Darwin leverages our Cartographer technology to predict the surgical supplies that will be used next time a particular case is performed. Often times, preferences cards that contain the specific supplies a surgeon needs go years without updates because of the difficulty and inefficiency involved with updating them. Darwin provides an accessible user interface to build better, more accurate preference cards.
Reducing costs and improving supply status decreased costs of supply in each case, and reduces the need to frantically search for forgotten supplies during operations. Data has found that there is a 22% decrease in supply costs vs. the status quo to date.
Preference cards: These cards include the pick list a surgeon develops for a given procedure (including their personal preferences and supply items they need for the surgery). This frequently lists specific supply vendors surgeons want to use. After the cards are initially completed, nurses are responsible for collecting the supply items for each surgery, as well as maintaining the cards.
Challenges with existing preference card use: Since the decision maker for the card (the surgeon) only indirectly feels the frustration of the card being inaccurate, and the cards themselves are tedious to update, most preference cards go years without updates. As a result, many items are wasted or missing. When picklists are not accurate, nurses must run out to retrieve missing items, or find themselves opening and throwing out expensive items for hygiene reasons. Additionally, there is substantial list variation between surgeons as they rarely coordinate which vendors or items to use. This leaves some surgeons using more expensive or lower quality items for similar surgeries. It also makes it harder for the vendor negotiators to buy in bulk or lower prices for the hospital.
Our solution: Our UI displays the various supplies used in the OR and their corresponding costs. It provides recommendations for improved supply management based on ML, and clear suggestions for improving pick lists. We’ve found service leads who are looking at the recommendation usually adopt it immediately. However, we also provide supporting evidence to show why the recommendation was made (such as usage of an item over time, and a graph of the quantity used per surgery).
Support: In addition to the UI, we support our clients with consulting. We work to explain the UI, coordinate the service leads, create reports on demand, and explore revenue capture improvements (sometimes the items aren’t charged despite usage). We anticipate integrating more of the consulting work into the software over time.
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