Prescriptive Analytics in Healthcare

Every industry has multiple problem areas where optimization could deliver significant value. As consulting firms, software vendors, visionaries within companies and industry analysts have begun adopting optimization, use cases have begun to spread into other industries including Healthcare.

Prescriptive Analytics in Healthcare: The Best Option

Healthcare meets all the requirements 

The Provider space meets all the requirements for optimization to deliver value (see blog entry on how to spot an optimization use case):

• Decision spaces involve multiple variables (e.g. patient mix, treatment plans, resources, physical space, payment structure, in-house vs. affiliated, etc.) and trade-offs (e.g. cost vs. quality)
• Objectives are definable and often compete with one another (e.g. quality, access to care, cost or profitability, customer satisfaction)
• Constraints limit a firm’s ability to maximize each objective, and interplay with one another – examples include personnel hours across the system, treatment plans, patient affliction curves (e.g. outreach vs. treat), minimum quality objectives, regulatory, budgets
• Complexity and the corresponding impact of deploying optimization are high

Applying Prescriptive Analytics in Healthcare

Through our work with customers and partners, we have seen time and again how solutions that leverage prescriptive analytics drive unique insights and improve planning significantly vis-à-vis using Business Intelligence (BI) tools and/or Excel. Use cases range from the strategic through operational planning. Here are a few examples:

• Long term business model/risk evaluation (e.g. physician employment, ACO)
• Network optimization of facilities and service lines – market share, quality, cost
• Regional policy optimization (throughput, cost and access to care), including coverage network, ambulance/ED, specialized clinics and GP policies
• Population management,/outreach program optimization, downstream resource requirements and financial performance
• Hospital constraint modeling (e.g. ED, OR, Beds, Clinics) to reduce cost and increase throughput understanding domino and cross constraint impacts
• Optimization of physician line up, hospital resources (capacity, insource/out-source) and case mix across service lines to meet demand and financial targets
• Driver-based financial planning (by demand source, e.g. physicians, ED), including physician group hire/fire/M&A
• Clinical process design & optimization
• Optimization of resources/activities for revenue cycle management
• Optimization of ED, OR, PACU and ICU scheduling policies

The more operational use cases (such as scheduling policy optimization) can be delivered within weeks, driving multiple times ROIs within 12 months. Tactical applications, such as driving the monthly planning process across a hospital (also known as Integrated Business Planning or Enterprise Optimization) deliver very high impact, sometimes approaching 5% of revenue in additional margin (or the corresponding improvements in access to care, quality and cost). The power of these solutions is they connect functional silos through true drivers and constraints.

Finally the strategic applications – such as the transition from fee for service into an ACO – are designed to optimize a future business model while predicting, quantifying and minimizing risk with a new level of understanding. The value of these solutions is transformational and in some cases has enabled a new level of dialogue between a Provider organization and policy makers.

Closing remarks

Healthcare providers are going through significant transformation, whether driven by cost pressures, new incentives, new regulations or changes in industry business models. Prescriptive analytics in healthcare can help Provider organizations not only make the right decisions, but also gain a competitive advantage. If you are concerned about the ability to absorb a new type of planning capability, there are multiple service providers that have strong capabilities in prescriptive analytics – feel free to contact me if you’d like an introduction!