Decision support in workforce management involves bringing together comparative information on resource availability and demand and delivering knowledge in the form of alerts and dashboards to those charged with making staffing decisions, preferably in real time. Currently, decision support systems fall far short for several reasons. The first is that staffing and scheduling vendors have historically avoided the import of patient data in order to avoid HIPAA compliance. The second is that the patient data is spread across many disparate electronic systems. The development of clinical data exchange protocols like HL7 (Health Level Seven) and the use of coded taxonomies like ICNP (International Classification of Nursing Practice) are helping to bring clinical and staffing information together to help support the decisions required to get the right staff to the right place at the right time.
Much of the current level of practice is to deliver raw activity information on patient arrival or volumes to the clinical leader and let the translation into staffing needs happen with the manager. Sadly the consistency of this translation can be inconsistent and/or hard to track. Decision support systems are needed to help with each of the following steps:
• Analzye data (ADT, pt assessment and acuity, staff experience, etc)
• Predict and forecast (number of patients and their acuity, patient events, available staff and their skill sets, etc.)
• Gap analysis (between patient needs and available staff)
• Decision making (identify standards and policies to guide decisions)
• Evaluation (formal and informal analysis of what is working and what needs further improvement)