Business intelligence depends on the delivery and analysis of relevant data. Real-time location system (RTLS) technology currently generate an enormous, but underused, data trove that hospitals are only starting to tap.
These data, which can provide a time-stamped historical path or real-time tracking of any asset or person through a hospital, can inform decision-making around key aspects of efficient, safe, and timely patient care. These aspects range from asset tracking and patient flow to throughput and even patient safety concerns—all of which have direct financial and reputational impact for the hospital.
Hospital decision-makers clearly can benefit from having a real-time view of wait times across the patient visit, bottlenecks in patient and clinician movement through the facility, and the movement (or misplacing) of expensive equipment. But until recently, the technology to provide such a perspective has been elusive.
Over the past decade, RTLS has benefited from improvements in accuracy, reduced downtime, efficiency, and user interfaces, with the result that it has become a highly effective source for business intelligence. Certain systems—notably RTLS based on ultrasound technology—have become extremely accurate, reliable, and user-friendly. Thus, today, a technology originally designed for hospitals to track equipment, such as wheelchairs and infusion pumps, now can drive business intelligence activities.
Workflow Analysis/Staff Utilization
Labor makes up the bulk of any hospital’s budget, and efficient use of resources can make a big difference in the bottom line. By distinguishing clinicians’ “value-added time”—i.e., direct interaction with patients—from various administrative tasks, or “non-value added time,” a hospital or health system can determine whether administrative duties are taking away valuable face time with patients.
Tracking time in this way allowed one clinic to shorten the patient cycle time by an average of 25 percent. The business improvements, which included being able to add surgical cases with the staff-hours saved, also acted secondarily to improve trust between the clinic’s administration and its providers as directives could be backed by hard numbers rather than by “hunches.”
Patient Flow Analysis
Adding surgical cases with the need to add staff is a clear business intelligence benefit for any outpatient clinic. Such efficiency improvement also helps patients by increasing access to needed procedures and maximizing personal attention from caregivers. RTLS technology can supply data for analyzing patient flow from the patient side, too, by offering patients a wearable tag that can interact with communication devices that provide information about wait times in different phases of their clinical experience. The information is displayed via a central dashboard or display indicating in real-time when a patient has been waiting past a certain threshold.
RTLS technology also can provide business intelligence that can enable a hospital to track and flag where the longest delays or pauses tend to happen, as well as any outliers in the normal rhythm. Instead of creating patient-flow initiatives based on intuition, RTLS data pinpoint where interventions are required and rules out one-off problem spots or delays due to unusual events.
RTLS-derived business intelligence related to patient-flow analysis can help achieve significant goals and milestones in patient care by furnishing the critical insights required to reduce variation in the care process. When providers know what to expect, they can perform their jobs more effectively. When patients know what to expect, they are happier with the clinical encounter and feel more secure that they have received optimal care.
RTLS technology has been used to assess staff compliance with hand hygiene regulations enacted to improve patient safety and prevent infections, thereby also reducing financial penalties and improving population health overall. The technology also has been instrumental in assessing hand hygiene compliance in a simulated clinical environment (and after that to evaluate other ways of testing compliance). a The consequences of poor compliance with regulations and a lack of hand washing are profound, both financially and in terms of human life. Nonetheless, compliance rates remain low—mostly because many healthcare providers do not know they are out of compliance.
RTLS can be used to deliver the data needed to understand the lack of compliance and failure points, thereby helping to better define processes for improving adherence and providing a basis for analyzing and quantifying potential costs of non-compliance.
Most hospitals continue to invest in RTLS technology to locate vital assets such as wheelchairs and infusion pumps when they are needed. But simply reducing the time it takes to locate a piece of equipment does not constitute significant application of business intelligence. However, when historical data are used to identify resource hoarding, or to optimize where assets are stored, or even to inform storage locations at a new facility, it is possible to achieve meaningful process improvements.
Optimizing asset utilization is a good model for even broader and more meaningful business intelligence initiatives around process design and minimizing the time clinical staff must spend on tasks other than patient care.
Patient wait times and lack of interaction with physicians are some of the major points of dissatisfaction for patients filling out satisfaction scores. Using RTLS to enhance that face time, as described above, and for identifying and addressing bottlenecks in the patient experience has the potential to enhance patient satisfaction, which itself has a direct bearing on HCAHPS survey scores.
The areas of business intelligence described here provide only a small glimpse of the potential for useful business intelligence that systemwide RTLS can provide. Analytics packages continue to be developed that promise to make RTLS technology an effective tool for institutions that need to become more data-analytics-driven, to best inform operational and clinical decision makers. Healthcare finance leaders should track these developments and become well-acquainted with this emerging technology and the extent of its capabilities.
a. Srigley, J.A., Furness, C.D., Baker, G.R., and Gardam, M., “Quantification of the Hawthorne Effect in Hand Hygiene Compliance Monitoring Using an Electronic Monitoring System: A Retrospective Cohort Study,” BMJ Quality and Safety, December 2014.