4 Ways Predictive Analytics Can Improve a Clinic’s Supply Chain
If patient visits and diagnoses are at the heart of your medical practice, predictive analytics of your operations has everything to do with the business of your practice. And it’s becoming increasingly important for managing the supply chain of any size medical clinic.
Jacqueline LaPointe at RevCycle Intelligence wrote in 2017 that frontline clinicians spend nearly 20 percent of their workweek dealing with inventory issues. Two-thirds of these frontline clinicians said they wish they could focus more on patient care than supply chain management. At the same time, LaPointe reported in 2018 that healthcare providers ranked the “power of data analytics to inform decision-making” as the No. 1 supply chain goal of the year.
The opportunity to get ahead of the curve here is clear.
So, how can data analytics improve supply chain management for your medical clinic? Gary Brooks, CMO at Syncron explains: “Predictive analytics — the ability to use data to predict future activities — enables real-time decision making and forethought on both strategy and performance.”
The right data gives administrators the ability to make better decisions in the short term and develop strategies for the long term. It’s this proactive nature of predictive analytics that makes it particularly useful for supply chain intelligence, Brooks concludes. After all, supply chains must constantly adapt in order to remain efficient.
Here’s how your clinic’s data can inform those adaptations.
1. It Can Improve the Visibility of Your Supply Chain
Knowing which items are where and when shipments will arrive are constant struggles in supply chain management. This goes for any business, not just clinics. More real-time data provides visibility into those blind spots.
Software strategist Louis Columbus writes at Forbes that, moving forward, this improved visibility is what will set efficient supply chains apart from those left in the past. What has been lacking in the past, and what is needed now, is an architecture based on visible, real-time data.
“Combining machine learning with advanced analytics, IoT sensors, and real-time monitoring is providing end-to-end visibility across many supply chains for the first time,” Columbus concludes. The patterns and data insights easily procured today were not available yesterday, and will revolutionize supply chain management tomorrow.
In a piece for Eye for Transport, Kelli Saunders writes about how predictive analytics improves end-to-end visibility in supply chain across many different industries, including healthcare, in three key ways:
- Providing access to shipment status and location in real time.
- Avoiding the costs of late and off-schedule shipments.
- Predicting when supplies may be running low or running late.
With the right analytics solution in place, a clinic could know exactly how much inventory it has at any given moment. When supplies run low, the clinic could automatically order more from the supplier, with the order information available in the system.
Better yet, with predictive analytics the clinic could order on a schedule that varies with patient flow. An administrator could view these orders — and their delivery status — in real-time.
2. It Can Optimize Supply Chain Planning and Scheduling
The DHL Supply Chain blog points out that a supply chain makes up as much as 25 percent of pharmaceutical costs. Like life science companies, clinics tend to operate on a high profit margin — but they have the same incentives to lower their costs.
Predictive analytics can help clinic administrators make these incremental improvements over time. The same DHL post reports that organizations that use data effectively have seen higher revenue and improved customer service — improving margins by up to 2 percent.
Part of predictive analytics is the use of machine learning software, which can crunch very large data sets to learn everything it can about the efficiencies and inefficiencies of a supply chain. “Areas like order fulfillment, production planning and demand forecasting are strong candidates for increased automation with advanced analytics,” says Gartner’s Noha Tohamy.
Jennifer Bresnick at Health IT Analytics writes that supply chain (and particularly an inefficient supply chain) tops the list of health providers’ largest cost centers. Put another way, supply chains represent one of the best opportunities for healthcare clinics to reduce spending and increase their efficiency.
Bresnick points out three ways predictive analytics can support supply chain decisions:
- Negotiating prices based on real need.
- Reducing the variation in supplies across time.
- Optimizing the ordering process according to predicted supply needs.
The key here is to recognize that predictive analytics can bridge the gap between pure-play logistics management solutions (like inventory tracking) and variability in patient visits and needs.
“With predictive analytics in play, hospitals can obtain a more accurate picture of how many patients will be readmitted, and what complications to care are likely to occur,” writes the team at GreenLight Medical, a healthcare logistics solution. “This gives hospitals a more accurate picture of the quantity of supplies to have on stock, as well as help to connect the larger puzzle of what devices contribute to optimal outcomes.”
Predictive analytics can improve the availability of supplies by looking ahead to future trends in patient admittance and medication needs. Data can help not just supply chain processes, but also supply availability at the point of care.
3. It Can Save Clinics Money
If your goal for using data analytics is to increase your clinic’s bottom line, putting it to use in supply chain management is a great place to start. In fact, Jerry O’Dwyer at Deloitte includes improved cost efficiency as one of the major benefits of predictive analytics. A data-driven approach to logistics allows administrators to “identify hidden inefficiencies to capture greater cost savings.”
Saving money by assessing data and making more informed decisions is achievable even without perfect data sets. Good predictive analytics solutions can work with the patient, supply and resource information unique to each clinic — particularly those that combine diverse data sets
Alvaro Gomez-Meana, chief technologist for health and public service at Hewlett Packard Enterprise, points out that drug management creates significant costs for clinics. Poorly managed expiry dates, for example, lead to waste. “Predictive analytics help you have the right amount of the right drugs at the right time, and that brings strong savings,” Gomez-Meana concludes.
4. It Can Standardize Logistics Processes
Predictive analytics is about more than improving day-to-day operations on the ground level. It is about using data to make informed, strategic decisions across the entire supply chain for your clinic.
There are two parts to this: making sure you are addressing the right areas of your supply chain, and seeking to standardize processes once you identify what needs to be changed.
The starting point on this front is to ask the right questions, argues Dan Brightmore at Supply Chain Digital. “To help transform data into business decisions, and apply this to real-life problems like supply chain management, you should start preparing the pain points in your supply chain that you want to gain insights into before you even start the data gathering process,” Brightmore recommends.
Once you know which problems you want to address, you can start using data to create standardized fixes to the logistics processes.
Writing at the Supply Chain Resource Cooperative, Dr. Robert Handfield says being strategic with your data means first articulating the question that must be answered by understanding the problems that stakeholders are currently facing. For medical clinics, it can be as simple as asking frontline clinicians where they see inefficiencies. From there, procurement teams can “build analytical insight in the absence of perfect data, and be able to leverage whatever data is available.”
One specific area of standardization to address is the automation of data flow. Mira Parakh at logistics firm Wipro writes that data analytics are one way to standardize the documentation process in supply chain management. Data analytics standardize supply chains by taking the likelihood of human error out of the equation.
Taking the First Steps to Improving Your Clinic’s Logistics
Dr. Daniel Kraft, medicine and neuroscience chair at Stanford University, brings home the usefulness of predictive analytics for healthcare:
“During the history of medicine, we have not been involved in healthcare; no, we’ve been consumed by sick care. We wait until someone is sick and then try to treat that person. Instead, we need to learn how to avoid illness and learn what will make us healthy.”
This is precisely what predictive analytics does for the health of a business.
If rolling out predictive analytics seems overwhelming, rest assured that you can find a customized SaaS option that works for your setting. NEJM Catalyst, a journal for medical clinic leaders, points out that cloud-based data analytics solutions can address the concerns that many healthcare organizations feel toward the idea of ripping up and replacing a good portion of their IT infrastructure and staff.
A good predictive analytics solution can complement these existing functions. A great predictive analytics solution will immediately increase efficiencies in processes like supply chain management.Images by: rawpixel, Elevate, Ani Kolleshi