Take the guesswork out of staffing with machine learning
As hospitals, health systems and outpatient clinics struggle with workforce shortages, a clear understanding of current and future staffing levels is crucial. Machine learning provides busy healthcare leaders with the information they need to accurately forecast patient volumes, thus empowering them to hire and schedule vital healthcare workers with confidence. The results are cost savings for healthcare organizations and better patient and employee experiences. During a recent webinar, executives with Medical Solutions — Jason Lander, executive vice president of product and services innovation, and Scott Armstrong, senior director of client growth — explained how machine learning can help leading hospitals and health systems respond to staffing constraints, improving overall resiliency of their organization during a challenging time.
1 Machine learning enables the transition from descriptive to predictive analytics
Many healthcare organizations rely solely on descriptive analytics or raw historical data to evaluate past events and why they might have occurred. Descriptive analytics are limiting because they don’t allow healthcare leaders to prepare for what may happen in the future. Predictive analytics leverage statistical techniques such as machine learning to predict likely business outcomes with the aid of historical data and real-time data. Predictive analytics are exciting in healthcare because they enable healthcare organizations to plan for future needs and concerns.
2 Machine learning is crucial as staffing constraints persist
The demand for quality healthcare professionals is only increasing, and there’s no sign this will change anytime soon. It’s estimated that 10.6 million new nurses are needed in the next eight years, taking into account existing shortages, heightened levels of burnout and increased demand for healthcare services from an aging population, according to the American Journal of Nursing. Machine learning technology can help healthcare organizations better plan for their staffing needs because of its ability to predict future staffing needs based on current and past data. In fact, 60% of healthcare leaders had adopted some form of predictive analytics by 2019, and 20% of healthcare leaders suggest they plan to use predictive analytics within the next three to five years, according to the Society of Actuaries.
3 Leveraging predictive analytics generates timesaving and financial benefits
Healthcare organizations that currently use machine learning are already seeing evidence of the positive impact. Of the 60% of healthcare leaders previously mentioned who adopted predictive analytics, 42% saw improved satisfaction in patient care, and 39% experienced some form of cost savings benefits.
4 Predictive analytics can address staffing challenges
There are key areas in which machine learning and predictive analytics can offer guidance to address staffing concerns: supply planning, attrition prevention, demand planning and cost projections. For example, in regards to supply planning, using machine learning can help a healthcare organization understand ahead of time how challenging a role will be to fill, allowing them to modify job characteristics proactively and intelligently, which will ultimately help attract more talent. 5 The right partners are key for success Staffing companies are an important partner for healthcare organizations as they apply machine learning and predictive analytics to address staffing challenges. Identify staffing partners that work closely with healthcare facilities to understand their unique situation and goals. Medical Solutions, for example, uses data science and business intelligence teams to create the most applicable solution possible for their healthcare partners. When evaluating your partner, consider the following:
• Does your partner have combined capabilities of product, client success and access to machine learning? • Does your partner provide value by anticipating clients’ staffing needs and delivering data-driven recommendations based on relevant past experiences, ultimately saving clients time and money?
• The healthcare industry is ever changing. Does your partner evolve with it by investing in its technology and people?
• Is your staffing partner passionate and knowledgeable about the industry and able to make recommendations based on current and future market trends?