As Markets for Healthcare Information Systems Cool, Demand for Artificial Intelligence Heats Up
By Barry Holleman
Globally, markets for hospital and healthcare information systems will see single-digit growth over the next few years, with a projected compound annual growth rate (CAGR) of 8.4% et 7.8%, respectively. That’s a sign the information systems markets are maturing, which is expected because public and private initiatives for data digitization and integration have made significant progress worldwide.
By contrast, the market for artificial intelligence in healthcare is booming. With a current value of $10.4 billion globally and CAGR projections averaging around 38-46%, healthcare AI is expected to reach a value of $44.5 billion by 2026 and more than $194 billion by 2030. In the U.S. alone, the healthcare AI market will grow from $6.9 billion to $67.4 billion by 2027.
Healthcare providers – who represent the largest portion of market share for healthcare AI companies – have good reason to embrace AI technologies. Artificial intelligence amplifies human intelligence, accuracy and efficiency in ways that produce better decisions, leading to meaningful cost savings and quality improvements. For example, according to an analysis by Accenture, AI applications may save the U.S. economy $150 billion per year in healthcare costs by 2026.
For healthcare supply chain management, the use of AI has been shown to facilitate significant process improvements and cost savings. Supply chain AI replaces manual data collection, aggregation and analysis, eliminating guesswork and data entry errors to ensure the right medications and supplies are in place with less inventory obsolescence and waste – thereby improving patient care and safety as well as clinician satisfaction. For these reasons and more, the global supply chain AI market is expected to triple in value by 2028.
Across many sources that study healthcare markets, analysts have determined several drivers of healthy growth and adoption in healthcare AI. Most notably, these drivers include:
- Increase in patient volume and condition complexity, coupled with the need to avoid overwhelming the system during pandemic-related surges
- Rising demand for personalized medicine
- Influx of large volumes of complex healthcare data requiring advanced computing power
- Growing demand for intelligence that leverages data residing in multiple disparate HIT systems
- Ongoing and rising need to reduce the total cost of care while improving quality, outcomes and experiences in a rapidly changing reimbursement environment
- The decreasing operational labor pool in healthcare as a contributing factor to the “imbalance” of supply and demand between the health workforce and patients
The machine learning platform et IA en tant que service applications we’ve built at MUUTAA address all those drivers in unique but very necessary ways. Where much of today’s healthcare AI is built for advancing diagnostics, ours is dedicated to advancing the healthcare supply chain, where the need for amplified intelligence et robust forecasting tools had been left largely unanswered – until now.
Through the artificial intelligence of l'application DemandAMP+, supply chain teams can factor patient-driven demand into their sourcing, procurement, and inventory management decisions. Just as care delivery becomes increasingly value-based and consumer-centric, the supply chain also benefits when decisions are centered around the realities of actual product usage rather than historical ordering patterns. By pairing medication and medical supply attributes with patient attributes sourced from billing data, protocols, scheduling, real-time and historic ADT (admissions, discharges, transfers), and public health databases – as well as MUUTAA’s own data lakes and libraries – DemandAMP+ improves order management while streamlining the entire process.
It is through those improvements that we come full circle back to the notion of better balance between the healthcare workforce and patients – after all, without the right supplies and medication to treat patients, clinical experts cannot do their jobs. MUUTAA enables precise prediction of patient demand and proposes the best-fit projection (a.k.a. suggested order quantity) for the specific products required by care protocols for individual patient diagnoses.
For each product, thousands of data points from existing inventory, warehouse and order systems are analyzed to provide optimal sourcing and purchasing scenarios that align with demand forecasts. Machine learning and surveillance techniques are built into the design of DemandAMP+ to continuously customize and optimize output over time.
In that way, our solutions improve the strategic discussions that need to happen between supply chain teams and their clinical partners. Additionally, by substantially reducing operational effort while optimizing visibility and decision support for greater accuracy, agility and action, we enable supply chain leaders to become key strategic contributors to higher-quality, lower-cost healthcare.
Earlier in this article, I referenced an Accenture study – and within that study are these important words of wisdom:
“AI is not an innovation coming down the pike—it’s here. It’s in our call centers, our homes and now, in our healthcare. Those who seize the AI opportunity and embrace these applications to deliver high-quality, cost-effective care will be the ones to leapfrog competitors.”
Nous contacter to learn more about what healthcare AI can do for your healthcare supply chain.
About the author
Barry Holleman is the Chief Operating Officer and Cofounder of MUUTAA, a healthcare AI company focused on patient-driven demand for clinically integrated supply chains. With more than two decades of global healthcare technology experience, Barry specializes in healthcare supply chains, healthcare logistics and automation, health IT, and pharmacy logistics. A results-oriented leader, he has helped spearhead market adoption of innovative technologies in healthcare across the European Union and North America. To contact Barry, email email@example.com.