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Using Predictive Analytics to Improve Healthcare Outcomes


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Authority

       The right to act in areas in which one has been given and has accepted responsibility

       The level of authority must be appropriate for the responsibility

      Creative Health Care Management uses four levels of authority to establish clear expectations for decision making:

       Level 1: Authority to collect information

       Level 2: Authority to collect information, assess, then make recommendations

       Level 3: Authority to collect information, assess, determine actions, pause to communicate and enhance, then act

       Level 4: Authority to assess and act, informing others after taking action

       Accountability

       Ownership for the consequences of one's decision and actions

       Sets the stage for learning and directing future actions

      When responsibility is understood and accepted and accountability measures are mutually agreed upon, people must always be given the authority necessary to be successful.

      Several times in this book, a better understanding of R+A+A is identified as a key solution to management issues uncovered in studies on nurse job satisfaction.

      Clarity of Self, Role, and System

       Clarity of Self

      I am clear that I am an instrument of healing—that what I do or don't do matters. Either way, there is an impact. I am clear that I am responsible for my own growth and contribution to the team.

       Clarity of Role

      I know the broadest boundaries of my role and the roles of others, so I/we can optimize our individual and collective efforts for the team and the patients and families we serve.

       Clarity of System

      I embrace the mission, vision, and values of the organization. The operating functions behind the scenes can make or break our organization's ability to deliver the best care. Therefore, we must involve and empower first‐line staff members to shape our systems to be reliable and effective for patients, families, and teams.

      It is gratifying to see, in nearly every case study in this book, how many people in organizations across the world have resonated with this idea that we have long known to be so important.

      Primary Nursing

      Past measurement of Primary Nursing has included (a) assignment of the primary patient relationship at or soon after admission, (b) assessment of the continuity of care, (c) collaboration of the nurse with interprofessional colleagues involved with the patient's care, (d) care planning with the care team, (e) patient and family satisfaction, and (f) the relationship between patient and nurse (Nelson, 2001). The importance of Primary Nursing to nurse job satisfaction has been confirmed using factor analysis of the Healthcare Environment Survey (HES) in the United States (Nelson, Persky, et al. 2015), Scotland (Nelson & Cavanagh, 2017), and Turkey (Gozum, Nelson, Yildirim, & Kavla, 2021).

      Several American studies in this book show that Primary Nursing is a chief satisfier of nurses. In studies around the world, it is often the case that while the term Primary Nursing is either not well known or has a negative association for nurses, the tenets of Primary Nursing (once the barrier of the term is removed) are consistently shown to contribute to nurse job satisfaction.

      If you think of clinical competence as being the combination of relational competence and technical competence—which implies that there is no clinical competence without relational competence (Koloroutis & Trout, 2012)—you will understand more fully how important it is to measure the effect that caring, clarity, and relationships have on healthcare outcomes. As you learn about the ways in which predictive analytics are being used to improve outcomes in healthcare, notice the vital role that the context of care plays every time. It is not just the technical aspects of care that are being measured now, because it is not just the technical aspects of care that matter. Caring, clarity, and relationships matter, so we are measuring them.

       There is no clinical competence without relational competence.

      Note

      1 1 Felgen & Koloroutis, 2007.

       Mary Ann Hozak

      An organization's performance improvement plan has traditionally been based on data that measures a compilation of (a) demographic information, (b) prevalence of outcomes such as use of restraints or pressure injuries, and (c) percentage of policy compliance such as: How many falls? How many appointments were canceled? Were patients happy or unhappy? What percentage of the form was completed? Although helpful as a starting point for identifying and quantifying quality indicators, the only thing these scores really show us is an abundance of data points moving up or down each month. They indicate whether a specific task is being performed well or poorly, but they do little to help us understand the big picture. Since “task performance”