The analysis of clinical demand using an episode or event method is dependent upon the availability of the data needed. As outlined in the discussion on calculating patient needs, these data points include a start and stop time and an assessed level of care. Furthermore, the specific systems that contain these data are outlined in the discussion of sources of information that define clinical demand.
Although the individuals that select and implement electronic systems may be fully competent in project management and technical aspects of automation, it is less likely that they will clearly understand the factors related to managing a clinical workforce. The caring professional must have input at the earliest stages of the project and through implementation and maintenance of the application.
The most difficult aspect of this is the integration, or sharing of data between patient management systems and staff management systems. It is important that the quality and timing of data needed is built in from the start of the project, and the caring professional’s knowledge is a critical ingredient.
The KLAS Vendor Directory is a good place to find Vendors that might meet your organizations needs. A review of the Staff Nurse Scheduling market segment group would be a good start.
Optimizing staff schedules to the demand
Most scheduling plans in caring departments are based more on staff-centric preferences than on patient-centric requirements. This is in part due to two important factors. The first is that, due to the widely publicized caring professional shortage, administrators are hesitant to propose staffing strategies that are unpopular. For example, even though 12 hour shifts have been shown to increase the number of adverse patient events, the personal advantages of working three days per week, have kept 12 hours shifts commonplace if not the norm. Secondly, the reliance on simplistic methods for the measurement of clinical demand has kept true patterns of clinical demand out of the staffing strategy process.
When an evidence based detailed demand pattern is available and depicts demand by time (hour) of day and day of week the basis for more appropriate scheduling plans starts to emerge. A few vendors ( http://kronos.com and http://www.theoptimegroup.com/ ) currently operate in this space and assist in the development of schedules with flexible start times and shift lengths so as to optimize the schedule to meet patient needs at the most competitive cost.