Having the right skill mix and nurses with the necessary skills readily available to take care of the right patient at the right time is essential to quality of care, patient safety and financial health. Still, it is common for nurses, unions, and state regulators to question hospitals’ staffing level decisions. An intensive care unit RN, for instance, may contend that a patient’s acuity demands his or her sole attention or the services of an additional nurse. This questioning or complaint about inadequate staffing, which tends to increase when facilities institute layoffs in poor economic times, is often emotional.
A patient classification system enables hospitals to remove emotion from the equation by demonstrating through hard data that its decisions are valid, not arbitrary. The tool applies an evidence-based approach to assign, match, and schedule nurses where they are needed the most based on patient acuity level.
Institutions that use the technology to assess acuity on every shift across all patient care units are able to provide objective documentation showing they are not understaffed, which of course places patients at risk. This proactive assessment of patient acuity helps ensure business continuity when regular charge nurses are out sick or on vacation. Replacements typically are less familiar with a unit’s policies and procedures, which can result in poor patient outcomes and higher costs.
A patient classification system promotes operational consistency by offering data on fill-ins that can be used to run a department efficiently in the absence of the regular charge nurse. More importantly, the process of assessing acuity on every shift gives health systems the ability to act immediately to prevent understaffing and overstaffing, both of which result in higher costs from potential malpractice lawsuits, disputes with employees, lost productivity and overtime.