Online Program

Physician workforce data as a strategic issue in access to care: Characteristics predictive of response to a state level survey

Tuesday, November 5, 2013 : 9:30 a.m. - 9:50 a.m.

Hannah Maxey, PhD, MPH, RDH, Department of Family Medicine, Indiana University School of Medicine, Indianapolis, IN
Zach Sheff, MPH, Indiana University School of Medicine, Department of Family Medicine, Bowen Research Center, Indianapolis, IN
TITLE Physician Workforce Data as a Strategic Issue: Characteristics predictive of response to a state level survey INTRODUCTION The United States health care system is undergoing massive transformations, in which health workforce capacity is a key issue. Understanding characteristics of the current workforce is crucial to inform pertinent policy and enhance effectiveness. Unfortunately, the United States lacks a comprehensive source of health workforce data. This study seeks to identify characteristics of physicians predictive of response to a state level survey in order to generate evidence based recommendations for the collection and management health workforce data. METHODS This cross sectional study included 13,161 physicians who held an active or probationary Indiana medical license at the completion of the 2011 biennial license renewal period. Univariate tests were performed to generate descriptive statistics on the physician workforce and bivariate tests were used to identify associations between survey response and the physician characteristics included in this study. A model for logistic regression was fit to determine characteristics predictive of response. RESULTS Statistically significant associations were identified between survey response and age (p=0.03), part-/full-time status (p<0.001), race (p=0.03), geography of practice(p<0.0001) , and Medicaid acceptance (p<0.0001). The response rates were 86.0% for full-time practitioners versus 58.6% part-time, 88.4% among whites versus 86.9% minorities, 81.8% among urban practitioners versus 75.6% rural practitioners, and 86.7% among those who accept Medicaid versus 78.8% among those who do not. The logistic regression model identified age (p=0.0054), fulltime/part-time practice (p<0.0001), race (p<0.0001), and Medicaid acceptance (p<0.0001) as being predictive of survey response. DISCUSSION Certain demographic and practice characteristics of physicians were predictive of response. These findings can be used to develop policies aimed at enhancing response rates. The model generated in this analysis may be used to develop more accurate weighting factors for non-respondents of similar surveys.

Learning Areas:

Provision of health care to the public
Public health administration or related administration
Public health or related laws, regulations, standards, or guidelines
Public health or related public policy

Learning Objectives:
Explain the link between physician workforce data and access to health care. Describe the demographic and practice characteristics of physicians associated with and/or predictive response to a state licensure survey. Discuss policy strategies to enhance physician workforce data collection.

Keyword(s): Access to Care, Physicians

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am a doctoral student investigator with access to health care as my primary research interests. I have more than 4 years of experience in health workforce data management and research. I have presented my research at multiple national (APHA and AAMC) and state level (Public and Rural Health)meetings. In addition, I previously contracted with the Indiana State Primary Care Office for projects relating to Health Professional Shortage Area Designations and National Health Service Corps.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

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