Healthcare process mining market to exceed $29 billion by 2032

The healthcare process mining software market is projected to reach US$29.28 billion by 2032, growing at a CAGR of 43.29 percent over the next seven years. That’s according to a report by SNS Insider.

The growth reflects an industry-wide shift toward real-time operational intelligence, advanced cloud infrastructure, and artificial intelligence (AI) driven healthcare workflow optimization, stated SNS Insider.

Process mining platforms are increasingly being adopted by hospitals, payers and life sciences companies to streamline how care is delivered as well as reduce operational bottlenecks and regulatory burden.

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Process mining is transforming healthcare operations

Process mining software is revolutionizing the way health systems function. These tools empower hospitals, insurers, and pharmaceutical companies to map, analyze, and optimize workflows in real time, from claims management and procurement to patient admissions and discharge processes.

Cloud-based solutions are at the forefront of this shift, offering scalability, ease of deployment, and centralized visibility across multiple departments, according to SNS Insider’s report. Combined with AI and predictive analytics, process mining platforms are helping executives make data-driven decisions faster, ensure compliance, and reduce avoidable delays in critical care pathways.

North America currently leads the market, driven by a high adoption of advanced analytics, mature healthcare IT infrastructure, and strong investments from software innovators. Asia-Pacific (APAC) is emerging as the fastest-growing region, powered by national healthcare digitalization programs and increasing adoption among mid-sized hospitals and public health networks.

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Leading players in the healthcare process mining market include:

• Celonis
• SAP SE
• Software AG 
• UiPath
• IBM
• ABBYY 
• Microsoft 
• Apromore
• Nintex

Driving value from process mining in healthcare

Last year, a research paper authored by academics at the University of Debrecen explored the application of process mining in the healthcare sector. The study evaluated process mining software on functionalities, ease of use, cost, technical support, scalability, and security.

The research noted that, despite its potential to enhance efficiency, reduce costs, and improve patient satisfaction, the selection of process mining software poses significant challenges due to the diverse nature of healthcare processes and the lack of comprehensive evaluation methods.

To bridge this gap, the study used a hybrid multi-criteria decision-making (MCDM) approach, integrating the neural network-augmented analytical hierarchy process (NNA-AHP) and grey relational analysis, a technique for order preference by similarity to ideal solution (GRA-TOPSIS).

The paper recommended Disco software for healthcare process optimization due to its superior performance. Celonis and ProM were also proposed as viable alternatives for organizations seeking process mining solutions within the healthcare sector.

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