surgeon_medical_equipment
Bridgette Brown

Bridgette Brown

Emerging AI Use Cases in the Medical Device Field

As the market continues to react and recover from the COVID pandemic, we are already seeing AI use cases surface. In the months to come, there will be a variety of additional opportunities for medical device companies to improve their growth and margin in a highly competitive and evolving landscape — and to see measurable effects over the next several years. We can look at a few domains related to revenue recovery and cost control that are getting immediate attention.

A Visit to Your Local Hospital or Clinic Looks Different Than It Did This Time Last Year

As hospitals and clinics are opening up for elective procedures, they are doing so with limited appointment availability and a pruned back workforce. This is necessary to limit exposure and to maximize profitability. Though this lean model demands that medical facilities have solutions to help them prioritize procedures based on the availability of equipment and staff, as well as to minimize or eliminate downtime for capital equipment.

Rescheduled appointments caused by equipment downtime or unoptimized schedules have the potential to negatively impact profitability and delay revenue recovery. Medical device companies that are able to predict when their equipment might fail and have a solution to help coordinate preventative maintenance can help to reduce this financial impact to their customers.

Recovering Revenue Following the Loss of Elective Procedures and Decreased Product Demand 

Medical device companies are also eager to begin recovering lost revenue from formerly halted elective procedures and eliminated demand for their products. They are no longer able to freely walk the halls and attend procedures at their customer’s facilities, so their sales models have had to adapt. This is also a lost opportunity to take visual inventory of stock on hand and to perform immediate kit replenishment activities. Historically, that real-time inventory evaluation and replenishment activity was helpful in reducing supply chain issues that otherwise cause over-ordering or equipment shortages.

With a pent-up and growing demand for elective surgeries, sales reps will need to anticipate, prioritize, and respond to related demand for their products. This presents the possibility to match syndicated procedure data against actual sales data to determine propensity to buy additional products.

Ultimately, sales reps should be able to identify optimal inventory levels and proactively sell based on a measured or anticipated gap. In an ideal scenario, they have solutions that proactively trigger opportunities based on this expected gap or a predicted replenishment date and scoring solutions that keep them focused on those opportunities that have the highest likelihood to convert.

Account Growth and Retention vs. Net-New Account Acquisition for Medical Device Reps

Now and in the near future, we can expect that medical device reps will be challenged with prioritizing their accounts and opportunities based on those that have the highest potential to generate the most revenue. They will orient their sales activities around account growth and retention, as opposed to net-new account acquisition. I have highlighted areas where medical device companies can begin to recognize revenue, but what about solutions that can help to reduce or eliminate costs and improve profitability?

Now is the Time for AI to Positively Impact the Medical Device Field

The medical device industry is plagued by increasing competitive threats. The most successful companies will be the most innovative. They will find methods to introduce products with minor modifications to original product bases and at the low costs that are being forced by the focus on value-based care. This will require improvements to the entire product development life cycle in order to control development costs while also improving quality. Data centralization, intuitive analytics, and AI solutions will help to optimize trial operations and minimize the time that it takes to bring a new device to market.

Prior to being approved for production, AI solutions will also help identify potential issues before they occur, which will reduce the cost related to downtime, product replacement, and other related issues. To reduce R&D expenses, it will be increasingly important for medical device companies to find market whitespace for their existing products. This can be supported by an account scoring model that helps identify target accounts with minimal obstacles to entry and propensity to buy models that determine a potential customer’s likelihood to buy based on their profile compared to other similar accounts.

Emerging AI Use Cases to Consider

There is obviously a tremendous opportunity for AI to positively impact the medical device field, but many of the solutions are still just out of reach. There are real-world use cases, however, that can be considered now — a few that I already touched on. Some depend solely on more sophisticated analytics, while others are dependent on the development of AI models and interpretation of the model results. Here are several practical use cases to consider:

Consumables Analytics and Forecasting for Consumables Revenue Management

This can help companies understand revenue trends related to a variety of product mixes, as well as predict account potential and improve forecasting accuracy based on historic and current pipeline data.

Customer ROI Analysis

This can help companies that sell capital equipment evaluate their customers’ investments and determine how to maximize their ROI through growth and revenue improvements via what-if analysis.

Likelihood That an Account Will Buy a Particular Product

Companies can determine this based on historic buying patterns, procedure volumes, and comparable account profiles via AI-driven guided sales solutions that also recommend actions to take to move qualified deals forward.

Field Inventory Management Solutions

These solutions can help companies reduce the cost to serve and reduce the likelihood of returns and transfers by providing visibility into consignment, trunk stock, and surgical kit inventory, as well as insights into forecast, inventory consumption, and transfer rates.

Likelihood to Prescribe a Particular Therapy

Sales reps can determine a healthcare provider’s likelihood to prescribe a particular therapy requiring the use of their device based on an advocacy score and receive recommendations about what actions to take to improve that score.

Identify Trial Therapy Candidates With the Highest Likelihood to Convert to a Patient

Companies can more effectively identify these candidates and positively impact their path to therapy by connecting with them earlier in their care flow to ensure they are progressing through the stages at the desired rate.

Intelligent Sales and Service Solutions in the Medical Device Field

There are countless use cases that apply to the medical device field. Those I mentioned in detail are just a few.

In the intelligent sales realm, a few additional examples are account white space and cross-sell predictions, pricing and discount recommendations, automated tender forecasting, and solutions to support proactive management of consumables and contract renewals. As for intelligent service solutions, companies can benefit from the prioritization of customer care cases based on factors such as severity, account health score, or account type; workforce optimization paired with field services solutions; and guided, preventative support activities to improve customer health and positively impact retention.

We expect this domain of use cases that will benefit medical device companies to continue to grow and evolve as more companies progress along their path to becoming data-driven, intelligent organizations.

Learn more about how Atrium can help your organization deliver intelligent business solutions in life sciences.

Share this post

LinkedIn
Twitter
Facebook