aspect of data—and harness the energy of it. It is important to understand what is going on with the team's excitement. Once that excitement is in place, we can ask more specific questions: Should I be examining effective or ineffective leadership? What could we examine that would be of highest value to the team? What action does the data suggest we should take first?
Without effective leadership, change will not occur.
Effective leadership can help staff members follow their excitement into a strategy.
Effective leadership can help staff members follow their excitement into a strategy.
Leaders Using Data for Inspiration: Story 1
Here is an example of how a unit manager used data to work with staff members to plan for change.
A primary goal of the nurse manager of a neuroscience unit was to create a sustainable Primary Nursing care delivery system as an antidote to the task‐based nursing she saw on the unit. Seeing some hesitation in the group about where to begin, she had an idea for how to use data to get the staff council moving in the desired direction. She used call bell data obtained from the nurse call systems to get them started in the design of Primary Nursing on their unit.
The unit planned to build their Primary Nursing system utilizing RN pairs and partnerships.1 Nurses would work in partnerships to help share select tasks such as routine nursing care, medication administration, responding to emergencies, answering call bell lights, and patient and family interactions. It was theorized that by working together as an intentional team for a select portion of the care, nurses and support staff members could serve their patients better.
The first thing they took on was the effort to decrease call bell response time, with consistent RN partners working together to figure out how to respond to patients quickly, with the goal of responding in under two minutes. As call bells rang within a range of the hallway, one of the RN partners would answer the call if the other was occupied with another responsibility. This initiative led to the nurses recognizing the complex aspects of their daily workload and enabled them to prioritize tasks differently. They used data to see what partnering strategies were working as they reduced the response time to call bells. These efforts contributed to improving staff satisfaction with both team relationships and patient care.
It was discovered that patient satisfaction was high only when the staff's satisfaction with collaborating with each other was also high. As the collaboration of the team increased and role clarity improved, the staff council saw a decline in call bell light response time, an increase in staff satisfaction with teamwork and patient care, and improvement in patient satisfaction scores.
As the collaboration of the team increased and role clarity improved, the staff council saw a decline in call bell light response time, an increase in staff satisfaction with teamwork and patient care, and improvement in patient satisfaction scores.
Their ever‐deepening understanding of how to use data even prompted the staff to inquire of the data scientist whether they could study the predictors of workload. The study that followed is described in detail in the article “Measuring Workload of Nurses on a Neurosurgical Care Unit” (Nelson, Valentino, et al., 2015).
Leaders Using Data for Inspiration: Story 2
Here is an example of how a staff‐level leader's enthusiasm for data led to some stellar, long‐lasting outcomes.
A young nurse, in practice for about 3 years, volunteered to be one of the original members of the staff council in an organization implementing Relationship‐Based Care® (Creative Health Care Management, 2017; Koloroutis, 2004). One of the major drivers of her interest was access to the clinical data and the opportunity to improve patient care with full access to outcomes of care. She had never had this sort of access before, and she was very curious about data and its implications for care delivery transformation. Her excitement at the opportunity to hear revealing new data about her unit, firsthand from the data scientist, was a large part of what drew her to take on the leadership responsibility of co‐chairing the staff council. The data was presented and explained in such a way that it motivated her to create enhancements to the professional practice model on her unit while all of the information was fully available to the staff council and unit staff members. She recalls that the availability and transparency of the data led to building relationships among staff members and their manager, and inspired them to build a strong working team.
Her excitement at the opportunity to hear revealing new data about her unit, firsthand from the data scientist, was a large part of what drew her to take on the leadership responsibility of co‐chairing the staff council.
Two major milestones stood out for her. First, she was struck by the power of the Primary Nurse–patient relationships on the unit. During her time co‐chairing the council, this nurse cared for a chronically ill cancer patient who was about her age. As her Primary Nurse, she developed a relationship with this patient and was shocked and humbled when the patient requested—rather insisted—that she have her surgery on a day the Primary Nurse was working. This pattern of the patient coordinating her care with her oncologist and her Primary Nurse continued for months. Over time, patient and nurse worked together to be sure the Primary Nurse was working at the same times the patient came in for treatment. This event represented a milestone in the rollout of the Relationship‐Based Care model. This nurse’s actualization of autonomy as a Primary Nurse became a beacon to all of the staff councils and unit staff members.
This nurse’s actualization of autonomy as a Primary Nurse became a beacon to all of the staff councils and unit staff members.
Secondly, as a co‐chair of the staff council, this nurse engaged in using data to identify barriers to the implementation of Relationship‐Based Care. As staff council members began to recognize patterns in the disruption of patient care, they requested permission from their nurse manager to start a support group for patients and families on their unit. The manager fully supported this idea and gave the nurses one hour per week of protected time in which to conduct a regular support group. The unit social worker, in the role of co‐chair of the Patient‐Family Advisory Council, also supported this effort. An interdisciplinary team met weekly with patients and families to listen to the ways in which the team could make care better for them and other patients. The nurse recalls that practical suggestions emerged from these meetings such as the need to have sandwiches stocked on the floor for patients at night and the need for family members to have more direct access to the Primary Nurse or associate nurse. The meetings produced ideas on which the practice council could take action to implement changes to enhance patient and family satisfaction. The unit‐based Patient‐Family Support Group, created by the staff council, grew to be the model for an institution‐wide Patient‐Family Advisory Council that is still in place today.
How Leaders Can Advance the Use of Predictive Analytics and Machine Learning
Thus far it has been reviewed how leadership at every level of an organization can help advance a framework of care such as RBC. What is most promising with all of the technology we now have available to us, however, is that once we set up systems of data collection to monitor change in a culture, we then have the ability to integrate that cultural data into more complex models of measurement. Access to these complex models of measurement moves the organization from mostly retrospective use of data to the proactive use of data to manage healthcare outcomes
