Greenbriar Community Care Center’s re-hospitalization numbers decreased following data-driven interventions.
Organization Type: Skilled nursing facility
In 2015, the hospital readmission rate for all payers was more than 28 percent, higher than the adjusted national average of 18.4 percent reported by Centers for Medicare and Medicaid Services. Greenbriar Community Care Center began working closely with one of its primary referral partners on improving communication across settings and established a designated unit for the short-stay skilled population.
Greenbriar had introduced the use of ‘stop and watch’ and SBAR from the INTERACT tools but noted there was inconsistent use. Additionally, the center added a registered nurse to its transitional care unit to alter the skill mix with residents’ growing acuity. Although Greenbriar was responding to these challenges, the response was not impacting the readmission rate.
What We Tried
An opportunity arose to work with a doctoral student from Louisiana State University on a project specific for Greenbriar’s site. The team gathered data to examine the current patterns of re-hospitalization occurring in the facility. A sample from a one-year period was collected. It focused on admission day of the week and shift, transfer day of the week and shift, risk level of the resident, referring location, primary and secondary diagnosis, primary reason for re-hospitalization, level of care and hall location.
Once the initial data analysis was completed, and two primary locations (halls) were identified as the locations for the highest number of re-admissions, the team conducted further analysis . Acuity level by hall had not historically been a standard method to plan staffing in this setting. Using a multi-day sample of resident mix per hallway, the team compared the minutes of care as outlined by CMS per its resource utilization group (RUG) for each set of Greenbriar residents. This allowed the center to compare the routine staffing for each hall with the anticipated staffing needs.
Through understanding the patterns of re-hospitalizations in Greenbriar’s facility, the center was subsequently able to align its interventions. Some interventions included:
-Hiring a registered nurse designated for the early evening hours when the primary admissions related to re-hospitalizations occurred.
-Reassigning workload on halls identified to need higher RN coverage.
-Educating certified nursing assistants on ‘stop and watch,’ emphasizing the importance of minor changes in condition.
-Conducting joint review of data findings with all key team members with plan for a Quality Assurance and Performance Improvement (QAPI) team initiative.
There are a number of additional strategies discussed with the initial team. Based on its findings and interventions, a more formal team will be developed to assure follow-up, goal setting and the spearheading of a focused QAPI initiative.
The project is in it’s infancy with regards to associating the impact of the initial changes to the outcomes; however, the report through December 2015 reflected a re-hospitalization rate of 25 percent, a more than 3-percent decrease from the start of 2015.
-Understanding the root cause of the issue will guide the appropriate interventions. Interventions can be put in place, but, in this case, without understanding the patterns of admission and transfer, the resources were not aligned to the primary risk point.
-The roll out of any initiative requires the implementation of the change in structure to assure ongoing performance. Everyone was aware of the value certified nursing assistants can offer in recognizing changes in condition, but the ‘stop and watch’ as a means of communication had lost emphasis. Nurses need to seek out this information and reward when it is enacted.
-Implementing changes are more palatable when the team members understand the rationale for making the adjustments. Everyone understood the value of reducing re-hospitalizations, but the rationale for the intervention could now be tied to the patterns identified in the data.
-Resource allocation needs to align with the requirements for care of the residents. Standard staffing patterns are no longer feasible in the changing landscape of higher acuity residents.