Are Your Clinical Leaders Empowered to Make Data-Driven Changes that Impact Labor Spend?
Using data to drive decisions seems like an obvious choice when managing labor. However, selecting the most appropriate data to analyze is easier said than done, as healthcare systems continue to collect more and more information throughout the patient stay.
Collecting, validating, and sharing actionable information is critical in supporting healthcare executives and department managers to make data-driven decisions that maximize labor savings opportunities without negatively impacting care at the bedside.
The key is clearly understanding which data trends should drive operational intervention.
Avoiding “Analysis Paralysis”
Seemingly immeasurable amounts of data are available for healthcare system leaders to review and make operational improvement decisions. However, clinical leaders are rarely taught to make data-driven process improvements, as schools typically—and appropriately—focus mostly on direct patient care. The good news is that when organizations take time to provide education on labor-management data, we find that clinical leaders quickly understand the operational impact and how to take action.
While providing this education to clinical leaders seems like a simple concept, in reality, it is common to find organizations sharing an overwhelming number of data-packed reports without accompanying education for recipients, leading to “analysis paralysis.”
Empowering Managers with Targeted Information
A prerequisite to improving labor-management performance in your organization is understanding which reports are shared and the expectation of department leaders upon review.
In my experience working with managers, many are initially hesitant to be honest about their frustrations with current practices because they want to come across as responsible leaders that are capable of any challenge that executives throw at them. However, when they feel it is safe to speak directly, they often share that they are truly overwhelmed with multiple initiatives and reports.
Conducting a thoughtfully developed, brief and anonymous survey of department leaders may reveal that reports generated by various software tools are confusing and unhelpful in making staffing and flexing decisions.
Clinicians and non-clinicians alike are inspired by Florence Nightingale’s directive to first “do no harm.” So when administrators ask managers to make operational changes without straightforward data indicators that clearly illustrate the need and expected result from the change, many managers quickly resort to a safe response like, “we’ve always done it this way.” Rather than fighting this clinical instinct to ensure safe care through conservatism, executives should work with this important philosophy, providing clear and concise guidance to managers, alongside the expected outcomes, to support positive change. If communicated well, clinical leaders will feel confident in expected results and convey the importance of these changes to employees on their unit, engaging all team members in long-term improvement.
Aligning Staff Schedules with Historical Census Trends
Providing timely labor management data to staffing decision-makers is critical to successfully reducing avoidable labor spend. With few exceptions, historical patient volumes, and staffing patterns during those times are very useful operational indicators.
Reviewing historical patient census and staffing for at least 24 months reveals trends during certain hours of the day, week, or year that a department was over- or understaffed compared to budget guidelines. This review process commonly reveals that staffing grids are not being used properly or are misaligned with the department’s budget.
Analyzing these numbers has proven extremely illuminating, in my experience. Despite the best efforts of department management and executive leadership, an in-depth review of census and staffing data commonly reveals millions of avoidable labor dollars. Worse still, there are often days and hours where the ratios staffed are far leaner than budget expectations, which can compromise initiatives centered around quality, patient engagement, or other operational improvement efforts.
Validate Census and Staffing Data Before Publishing
It is critical to validate census and staffing data prior to publishing analyses and implementing new processes.
We all want to assume that our data is accurate, but upon closer review, it is common to find mistakes—particularly when calculations are involved. In cases where volume data is incorrect, it is often due to algorithms that allocate various minutes or hours to the wrong unit, or the wrong value is assigned.
Sharing data without validation is risky, as errors can create doubt and cause clinical leaders to become disengaged in the improvement process. Organizational change management leaves little room for error, as engagement from nearly all managers is required to drive improvement. While time-consuming, ensuring data reflects operations before sharing is important.
Establishing the Expectation of Improvement
Once a data-driven solution is implemented, leaders charged with staffing—whether on the unit or in administration—should regularly monitor performance and make adjustments as needed.
Executives leading healthy organizations know that a balance of support and accountability is required for sustainable success with labor-management initiatives. When productivity performance requires course correction, understanding the root cause is key. Organizational leaders should provide re-education, require managers to develop and implement action plans for improvement, and ensure that regular data-driven performance reviews occur. Leadership diligence around both support and accountability with departments struggling to perform is a key success factor in organizational labor-management improvement.
Commitment to data-driven improvement strategies helps high-performing organizations to contain labor costs for years to come, while simultaneously supporting their clinical commitment to bedside patient care and positive outcomes in the communities they serve.