It’s time for health systems to get ahead of labor costs

As all healthcare leaders know, the challenge of better managing costs while improving patient care weighs heavily on organizations. And in 2021, with COVID-19 driving already escalating costs, the industry feels unprecedented urgency to identify and manage its greatest healthcare operating expenses—labor management.

Labor encompasses nearly 60 percent of hospital costs, making its understanding and management critical to financial improvement. However, despite labor’s impact on an organization’s bottom line, many healthcare leaders rely on outdated or homegrown labor management systems that lack the infrastructure to aggregate large amounts of labor data from disparate sources and keep pace with today’s workforce demands. It’s time for health systems to get ahead of their labor costs. But what does it look like to harness the  number one expense for an industry traditionally reliant on retrospective, siloed data? Transforming the labor cost landscape begins with access to timely, comprehensive, augmented intelligence (AI)-empowered data and expert oversight of the improvement process.

Labor cost improvement starts with matching staffing hours with patient needs

As a first step towards labor cost improvement, the organization must answer a fundamental question: how many staffing hours do we need to meet patient needs? By pinpointing areas in which staffing hours exceed or fall short of patient needs, leaders can quickly recalibrate the labor outlay without compromising the quality of their care delivery.

While the above supply-and-demand formula sounds simple enough, most health systems don’t have the comprehensive data or AI capabilities to view their current labor resources against patient needs. Many homegrown labor management systems lack the infrastructure to aggregate large amounts of labor data from different source systems—including payroll, EMR, and time and attendance. As a result, end users must manually collate labor reports and fragmented datasets to guide staffing decisions with little valuable insight or ability to forecast.

Healthcare needs labor management solutions for today’s demands

Overcoming the limits of existing labor management systems requires a comprehensive AI-enabled view of labor data by organization, department, team, and job role. A solution for today’s demands must feature embedded AI forecasting to predict patient volumes and allow proactive resource scheduling. The system must also produce timely insight into future hospital needs. Such understanding helps leaders close the gap between required staffing and future patient volumes, control labor expenses, and track progress towards budget and staffing targets while ensuring resources for excellent patient care.

Today’s healthcare labor management solution must perform the following:

  • Display comprehensive labor data in one place:Department and unit managers must be able to analyze labor costs with an integrated view of all labor productivity data, including cost and hours by organization, location, department, team, and job role in one location.
  • Proactively schedule to volume:Decision makers need a complete view of categorized labor hours concerning costs (e.g., regular, overtime, premium, contract labor, and staffing mix), allowing easy identification of labor trends, comparisons, and rollups across departments to accurately predict labor needs, plan for changes in staffing, and optimize staff-to-patient ratios.
  • Drive adoption with expert guidance: To maximize a labor-management application, vendor experts help categorize and refine data through an initial assessment and data integration from multiple data sources (e.g., EMR, billing, HR/payroll, time and attendance, and general ledger). These experts show decision makers how to use the data to optimize their labor resources, improve operations, and ultimately reduce overall labor spend. To drive the most effective adoption, implementation teams also provide train-the-trainer sessions.

Technology, AI, and expertise translate to better healthcare labor management outcomes, lower costs, and improved care

To meet today's healthcare challenges, a labor-management solution must combine advanced technology, AI, and expertise to ensure organizations have optimal resources to deliver excellent patient care. With an AI-powered, comprehensive view of healthcare labor data, leaders can adjust staffing decisions that reduce costs, identify over- and understaffed areas, and understand exact staffing volumes that support patient needs. Timely data-driven insights empower decision makers to address the most significant operating expenses effectively and proactively lead their organizations.

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