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What's the Cost of Not Utilizing Predictive Analytics in Healthcare?

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By Jackie Larson, President, Avantas


Predictive analytics with advanced labor management signifies a breakthrough in the way the work of nurses and other clinicians is planned and managed at healthcare facilities across the nation. To chief nursing officers, finance directors, HR departments, the overall healthcare enterprise and, of course, registered nurses themselves, it represents a significant change from traditional scheduling and staffing methods.

What does this change bring to hospitals and other healthcare organizations, and what is lost by ignoring this technological advancement? First of all, an analysis of our clients has consistently shown that healthcare organizations that utilize predictive analytics with advanced labor management practices can save 4% to 7% of their total workforce budget. Doesn’t sound like much? It is. Workforce is the largest single cost for almost any healthcare organization – and certainly for hospitals – representing 50% to 60% of the total enterprise budget. That can mean millions of dollars in savings.

But there is something more important than the bottom line – and that is the quality of patient care. The recent survey on predictive analytics by AMN Healthcare and Avantas showed that nurse managers and registered nurses are concerned about the impact of scheduling and staffing problems on patient care and patient satisfaction. Both said very specifically that when scheduling and staffing problems cause understaffing in staffing – which are among the most frequent and significant consequences – there are negative impacts on the quality of patient care.

Closely linked to patient care quality is staff morale. When staff morale is down, quality can be affected. But poor morale also affects turnover, retention, job satisfaction and other issues. Predictive analytics with advanced labor management can have a big impact in staff satisfaction; over a period of several years, RN job satisfaction at a large, multi-facility regional provider improved from the 18th percentile to the 81st percentile in data from staff satisfaction questionnaires.

The 97% accuracy in staffing forecasts 30 days in advance of the shift also results in financial savings. For instance, Avantas clients can establish open-shift management methodologies that fill 75% of open shift hours more than two weeks ahead of the shift. That means you can avoid much of the last-minute open-shift hourly incentives that hospitals are so often forced to pay. In fact, one of our clients saw a drop in average open-shift hourly incentive from $16.80 to $7.75 over the period of a few years. This is pretty typical of the savings we’ve seen.

Another client saw its bonus shift hourly incentive drop from $20 to $5 over a five-year period. Relying on bonus and open-shift pay to fill openings is really an inefficient and ineffective way to schedule and staff nursing. It makes a lot more sense to utilize available technology to know what you need months ahead of time and then manage (and proactively incentivize) your staff to meet that need.

Other industries have been forecasting demand and managing resources for years using big data crunched through algorithms, then creating and validating predictive models and crafting advanced management processes based on accurate forecasts of resource demands. Healthcare can do that, too, with its most precious resource – healthcare professionals.

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