Importance of collecting and analyzing bedside data for hospitals

A vital question facing many hospital management teams is whether collecting and analyzing bedside data really is imperative to patient care and overall Medicare reimbursements.

When we live in a data driven world and are in need of continual improvement of patient care, we need to take advantage of all the data we can collect and analyze.

Collecting bedside data is really about the real time health system. The notion of being able to grab patient behavioral data and use it to make adjustments in three main categories - Caregiver Workload Management, Patient Satisfaction, and Quality. Overall, it's a paradigm shift from management teams using retrospective reports to make corrections.

Using live bedside data allows for more effective evaluation not only of workflow, but also of patient care ebbs and flows. It allows management to make real-time care decisions for their patients as opposed to retrospectively correcting a problem for future patients. An example of this is fall risk patients; once we can identify the patient's behavior, we can stop preventable falls and once we successfully do that we can protect our bottom line by not getting penalized by Medicare. As of October 2008, U.S. hospitals ceased to receive Medicare reimbursement for treatment of fall-related injuries that occurred during an inpatient stay, if the fall was preventable.

Appropriately analyzing bedside data can provide a method to identify the patient at risk for falls and the opportunity to implement proactive interventions aimed at decreasing these events. Implementing a computer software system to a couple of these interventions, such as the bed call light system and bed alarms, can capture and correlate real-time unit activity prior to any fall incidence in an inpatient setting. This data would provide the opportunity to reassign staff and increase the care necessary when a patient exhibits behavior known to correlate to a fall.

By collecting and analyzing bedside data, hospital staff will have a better understanding of which fall-prevention technique may be the most viable for their patients. For example, bed alarms may be an appropriate intervention. These devices notify the healthcare providers that the patient is about to have an incident. Yet, the use of so many alarm devices results in sound dispersion and alarm fatigue among healthcare providers. Tracking the data emitted from the patient bed allows for these instances to be verified and allow for the potential education for ancillary staff.

Ideally tracking bed data could actually show improvement in patients' recovery, therefore indicating the patient can be taken off fall precautions, or even start eyeing a discharge date for meeting the ambulatory improvements.

Fall-risk patients are only one example of why it's important to collect and analyze bedside data. This data can also be used to detect and correct many other patient and staff issues. Caregivers, nursing leadership and hospital administration can use analytics from beds in order to find behavioral (patient) and process (staff) changes in order to curb bad behaviors or improve processes. For example, if a single patient demonstrates repeat behavioral problems (calling out too much, getting out of bed repeatedly, etc.) management can "leader round" on the patient in order to get to the root of the issue through discussion, or management can talk with the nurse/ patient care technician responsible to see if there is anything they can do to correct the behavior.

With bedside data, nursing leadership can also see what types of calls happen at certain times of day. So if there are a significant number of toilet requests at 2 pm, a nurse should probably be addressing the toileting needs during his/her hourly rounds. Instead of asking the patients if there is anything he/she can get for them, the nurse/ patient care technician can really hit home with the toileting question based off of the bed data and nurse call data that has been generated. Caregivers could change their strategic conversation to something like, "It's going to get pretty busy here in the next hour, do you need anything? Maybe you'll want to use the restroom before I leave for another hour."

The same strategic conversation can apply to all nurse call initiated calls. The easiest example of this is with bed exists. Caregivers can address a patient with something simple such as, "it is our goal to get around once per hour so you don't feel the need to get everything yourself, how's that going today?" This not only improves patient care, it also gives the patient the feeling of being cared for.

Bottom line is, patient data helps tell the story of the patient experience and helps us understand why certain patients have different behaviors. All of which can usually be addressed through strategic conversations with either the patient or staff, but you need data to identify the gaps or you will be shooting in the dark.

About the Author
Ron Pusey, president & CEO of Communications Specialists, Inc. has been in the healthcare informatics industry for more than 29 years. Communications Specialists, Inc. is a full-service systems integration firm serving the central Virginia region. With 70 employees, the experience and technical strength of its staff, combined with strategic partnerships with the industry's most respected vendors allows the team to provide their customers with high-quality, custom-designed solutions to their electronic system and communication needs. For more information, please visit www.csisystems.net.

The views, opinions and positions expressed within these guest posts are those of the author alone and do not represent those of Becker's Hospital Review/Becker's Healthcare. The accuracy, completeness and validity of any statements made within this article are not guaranteed. We accept no liability for any errors, omissions or representations. The copyright of this content belongs to the author and any liability with regards to infringement of intellectual property rights remains with them.

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