Aaron Spaulding1, Bita A Kash, Christopher E Johnson, Larry Gamm. 1. Aaron Spaulding, PhD, is Associate Consultant I, Department of Health Sciences Research, Division of Health Care Policy and Research, Mayo Clinic, Jacksonville, Florida. E-mail: spaulding.aaron@mayo.edu. Bita A. Kash, PhD, MBA, FACHE, is Associate Professor and Director, Center for Health Organization Transformation, Health Policy & Management, Texas A&M University, College Station. Christopher E. Johnson, PhD, is Professor and Chair Department of Health Management and Systems Sciences, School of Public Health and Information Sciences, University of Louisville, Kentucky. Larry Gamm, PhD, is Regents Professor, Health Policy & Management, Texas A&M University, College Station.
Abstract
BACKGROUND: We do not have a strong understanding of a health care organization's capacity for attempting and completing multiple and sometimes competing change initiatives. Capacity for change implementation is a critical success factor as the health care industry is faced with ongoing demands for change and transformation because of technological advances, market forces, and regulatory environment. PURPOSE: The aim of this study was to develop and validate a tool to measure health care organizations' capacity to change by building upon previous conceptualizations of absorptive capacity and organizational readiness for change. METHODOLOGY/APPROACH: A multistep process was used to develop the organizational capacity for change survey. The survey was sent to two populations requesting answers to questions about the organization's leadership, culture, and technologies in use throughout the organization. Exploratory and confirmatory factor analyses were conducted to validate the survey as a measurement tool for organizational capacity for change in the health care setting. FINDINGS: The resulting organizational capacity for change measurement tool proves to be a valid and reliable method of evaluating a hospital's capacity for change through the measurement of the population's perceptions related to leadership, culture, and organizational technologies. PRACTICAL IMPLICATIONS: The organizational capacity for change measurement tool can help health care managers and leaders evaluate the capacity of employees, departments, and teams for change before large-scale implementation.
BACKGROUND: We do not have a strong understanding of a health care organization's capacity for attempting and completing multiple and sometimes competing change initiatives. Capacity for change implementation is a critical success factor as the health care industry is faced with ongoing demands for change and transformation because of technological advances, market forces, and regulatory environment. PURPOSE: The aim of this study was to develop and validate a tool to measure health care organizations' capacity to change by building upon previous conceptualizations of absorptive capacity and organizational readiness for change. METHODOLOGY/APPROACH: A multistep process was used to develop the organizational capacity for change survey. The survey was sent to two populations requesting answers to questions about the organization's leadership, culture, and technologies in use throughout the organization. Exploratory and confirmatory factor analyses were conducted to validate the survey as a measurement tool for organizational capacity for change in the health care setting. FINDINGS: The resulting organizational capacity for change measurement tool proves to be a valid and reliable method of evaluating a hospital's capacity for change through the measurement of the population's perceptions related to leadership, culture, and organizational technologies. PRACTICAL IMPLICATIONS: The organizational capacity for change measurement tool can help health care managers and leaders evaluate the capacity of employees, departments, and teams for change before large-scale implementation.
Authors: Daniel M Walker; Jennifer L Hefner; Cynthia J Sieck; Timothy R Huerta; Ann Scheck McAlearney Journal: J Med Syst Date: 2018-07-16 Impact factor: 4.460