Operationalizing the strategic and secure use of healthcare data to deliver insights that transform healthcare systems and organizations around the world
Recent advancements in processing power, data science, and digital applications are making it possible to uncover unprecedented insights in healthcare, creating new sources of value that could reshape the sector. However, capturing the full value of healthcare data requires an analytics approach. McKinsey's Nebula platform is a team of healthcare-technology experts managing a secure data-and-technology platform and helping deliver a suite of data and application services to increase the effectiveness of healthcare organizations.

What we do

We support healthcare organizations every step of the way in delivering lasting change.

Analytics as a service

We design and develop an analytic asset, deliver the asset or outputs through production analytics on an ongoing basis, and transfer the capability to the healthcare organization or a third-party IT provider.

Platform as a service

We support healthcare organizations through a private platform and accompanying support. We design and deliver a portfolio of use cases, with a strong emphasis on capability building, integration of operating model and resources, and transfer to the healthcare organization or a third-party IT provider.

Development of a healthcare-analytics organization

For healthcare analytics, we help create an organizational structure, define talent needs, identify internal priorities and sponsors to champion through implementation, develop new processes and prioritization criteria, and deliver analytics and digital competencies.

Capability building

We provide expertise and support to help healthcare organizations improve their organization and the capabilities of their analytics team.

Examples of our work

Reducing operations costs for a healthcare-information-management company

We supported a company which lacked a data-drive approach to plan its capacity proactively in reducing operations costs by improving demand forecasting and capacity planning. We designed and delivered a sustainable forecasting solution enabled by a machine-learning model based on extensive client historical data and advanced-analytics methodologies. This led to an organizational shift in data culture and accountability. The total labor waste because of inefficient capacity planning was estimated at $24 million to $30 million, out of which $8 million to $10 million was targeted for savings in the first year.

Increasing staffing compliance levels for a private hospital group

An organization faced escalating costs across several hospitals, driven by poor staffing practices because of a lack of data-driven insights and controls. We designed, developed, and deployed an end-to-end automated process to identify the hospitals that were not complying with staffing norms and needed assistance, which enabled intervention in near-real time. Within three months after deployment of the dashboard, the group saw its hospitals improve their staffing-compliance levels by around 15 percent.

Visualizing patient journeys for a government payer

As one team, we completed a long-term project to implement and fine-tune a government payer’s episode-based payment program. We then supported the payer in the next step on its path, exploring the differences in members’ medical journeys in different risk-stratification segments and developing insights that would guide intervention design for high-risk perinatal patients. We delivered an interactive perinatal-journey visualization and empowered the payer to drive its own analysis offline and test its own hypotheses to support vulnerable populations better.

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