Ji Yun Kang, Yu-Li Huang, Minji Lee, Petrine Cerri, Eric Klavetter
{"title":"Characteristics of High-Performing Administrative Leaders in a Physician-Administrator Dyad in an Academic Medical Center.","authors":"Ji Yun Kang, Yu-Li Huang, Minji Lee, Petrine Cerri, Eric Klavetter","doi":"10.1097/JHM-D-24-00157","DOIUrl":null,"url":null,"abstract":"<p><strong>Goal: </strong>The purpose of the research is to explore, through the lens of organizational performance and staff satisfaction, the characteristics of administrative leaders working as dyad partners with physician leaders.</p><p><strong>Methods: </strong>All 54 administrative leaders from 71 clinical departments at the three US Mayo Clinic sites were invited to participate in the study. We used an unsupervised cluster analysis machine learning method to group the leaders based on their characteristics, as measured by the 32-dimension Occupational Personality Questionnaire (OPQ 32r), and we used a three-cluster model to explore the relationships between the clusters and the performance outcome. We took the department performance data from the previous year and compared the percentage of departments with the upward changes among the clusters. For staff survey data, we calculated the percentage of departments with scores that were above average among the three clusters for both physician and administrative staff responses.</p><p><strong>Principal findings: </strong>Analysis of personality data revealed three different clusters. Cluster 1 leaders were caring and democratic, forward-thinking, strategic, optimistic, and trusting of others. Cluster 2 leaders were extremely hardworking and authoritative. Cluster 3 leaders were caring, modest, and rule-following. Cluster 1 leaders showed the best financial performance and sense of belonging among their followers, cluster 2 leaders elicited high engagement from their departments, and cluster 3 leaders encouraged lower burnout among staff members.</p><p><strong>Practical applications: </strong>From this study, we obtained empirical evidence of administrative leaders' characteristics that showed positive relationships with financial and staff-satisfaction metrics. The results showed that distinct types of leaders influence administrative staff and physician staff differently and that different situations require different styles of leadership. We can also conclude that implementing robust, scientifically validated tools to assess leadership traits and tendencies can positively affect leadership and organizational performance for healthcare organizations.</p>","PeriodicalId":51633,"journal":{"name":"Journal of Healthcare Management","volume":"70 4","pages":"288-302"},"PeriodicalIF":1.7000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Healthcare Management","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/JHM-D-24-00157","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/4 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"HEALTH POLICY & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Goal: The purpose of the research is to explore, through the lens of organizational performance and staff satisfaction, the characteristics of administrative leaders working as dyad partners with physician leaders.
Methods: All 54 administrative leaders from 71 clinical departments at the three US Mayo Clinic sites were invited to participate in the study. We used an unsupervised cluster analysis machine learning method to group the leaders based on their characteristics, as measured by the 32-dimension Occupational Personality Questionnaire (OPQ 32r), and we used a three-cluster model to explore the relationships between the clusters and the performance outcome. We took the department performance data from the previous year and compared the percentage of departments with the upward changes among the clusters. For staff survey data, we calculated the percentage of departments with scores that were above average among the three clusters for both physician and administrative staff responses.
Principal findings: Analysis of personality data revealed three different clusters. Cluster 1 leaders were caring and democratic, forward-thinking, strategic, optimistic, and trusting of others. Cluster 2 leaders were extremely hardworking and authoritative. Cluster 3 leaders were caring, modest, and rule-following. Cluster 1 leaders showed the best financial performance and sense of belonging among their followers, cluster 2 leaders elicited high engagement from their departments, and cluster 3 leaders encouraged lower burnout among staff members.
Practical applications: From this study, we obtained empirical evidence of administrative leaders' characteristics that showed positive relationships with financial and staff-satisfaction metrics. The results showed that distinct types of leaders influence administrative staff and physician staff differently and that different situations require different styles of leadership. We can also conclude that implementing robust, scientifically validated tools to assess leadership traits and tendencies can positively affect leadership and organizational performance for healthcare organizations.
期刊介绍:
The Journal of Healthcare Management is the official journal of the American College of Healthcare Executives. Six times per year, JHM offers timely healthcare management articles that inform and guide executives, managers, educators, and researchers. JHM also contains regular columns written by experts and practitioners in the field that discuss management-related topics and industry trends. Each issue presents an interview with a leading executive.