Presentation is loading. Please wait.

Presentation is loading. Please wait.

New Data, Same Story? A Replication of Studies Using National Public Health Performance Data Michelyn W. Bhandari, DrPH, MPH 2008 AcademyHealth Public.

Published byMarcus Walters Modified over 9 years ago

Similar presentations

Presentation on theme: "New Data, Same Story? A Replication of Studies Using National Public Health Performance Data Michelyn W. Bhandari, DrPH, MPH 2008 AcademyHealth Public."— Presentation transcript:

1 New Data, Same Story? A Replication of Studies Using National Public Health Performance Data Michelyn W. Bhandari, DrPH, MPH 2008 AcademyHealth Public Health Systems Research Interest Group Meeting Washington, DC June 7, 2008

2 Acknowledgements Contributing authors – F. Douglas Scutchfield, MD 2 – Richard Charnigo, Ph.D. 2 – Martha Riddell, Dr.P.H. 2 – Madhubindu Kanneganti, MBBS, (MPH) 1 – Glen P. Mays, Ph.D. 3 Research Funded by the National Network of Public Health Institutes in cooperation with the Office of Chief of Public Health Practice at the Centers for Disease Control and Prevention 1 Eastern Kentucky University, College of Health Sciences, Department of Health Promotion and Administration, 2 University of Kentucky, College of Public Health, Center for Public Health Systems & Services Research, 3 University of Arkansas for Medical Sciences, Fay W. Boozman College of Public Health

3 Research Objectives 1.To increase the science base allowing communities to develop improved public health systems 2.To determine the relationship between public health agency structure, organization and management and local public health system performance

4 Background Previous studies by Scutchfield et al. (2004) and Mays et al. (2006) used non contemporaneous survey data and test versions of the National Public Health Performance Standards Program (NPHPSP) local public health system performance assessment instrument

5 Purpose To achieve the research objectives, these previous studies were repeated using more up-to-date, contemporaneous data with a larger sample size

6 Study Population 529 local public health systems/jurisdictions from within 30 states that completed Version 1 of the NPHPSP local instrument between 2002 and 2007 78 repeat observations were removed 98 systems were excluded because they could not be matched by jurisdiction type or had not completed one or more secondary data sets Study sample: 353 systems within 23 states

7 Data: Dependent Variables Measures of system performance on the 10 Essential Public Health Services (EPHS) were obtained from Version 1 of the NPHPSP local public health system performance assessment instrument EPHS score is the average of all indictors of the model standards that fall under an EPHS 11 variables (1 for each EPHS & Overall)

8 Data: Independent Variables Characteristics of public health agency structure, finance, organization and management were obtained from the 2005 NACCHO Profile (24 variables) County-level information on area demographic, socioeconomic, and health resource characteristics were obtained from the 2005 ARF (4 variables) Federal public health spending was obtained from the Census Bureau’s 2005 Consolidated Federal Funds Report (CFFR) (1 variable)

9 Analysis Computed cross-sectional multivariate regression models to estimate associations between system characteristics and the performance of essential services – Mays et al. (2006) entered independent variables which were selected a priori into mixed regression models with random effects that account for within-state correlations – Scutchfield et al. (2004) entered stepwise only those variables which are significantly related to performance in the bivariate analysis into linear regression models

10 Table 1: Effects of system characteristics on performance of essential public health services: Standard Regression Estimates (Mays Study Repeat) Standardized Regression Coefficient (Standard Errors) EPHS 1EPHS 2EPHS 3EPHS 4EPHS 5EPHS 6EPHS 7EPHS 8EPHS 9EPHS 10 Population size (1000s), log 0.220.23-0.020.060.110.280.00-0.13-0.040.24 (0.09)***(0.08)***(0.09) (0.07)(0.08)***(0.09)(0.08) (0.08)*** LHD spending per capita, $1000s, log 0.01-0.05-0.08-0.01-0.06-0.030.12-0.060.08-0.10 (0.10)(0.09)(0.10)(0.11)(0.09)(0.10) (0.09)(0.10) Direct federal spending per capita, $1000s, log -0.05-0.040.01-0.010.05-0.030.03 -0.050.10 (0.06)(0.05)(0.06) (0.05) (0.06) (0.05)(0.06)* LHD staff per 100,000 population, log 0.000.050.07-0.030.120.090.02-0.03-0.150.07 (0.10) (0.11)(0.09)(0.10) State-local public health authority--Centralized -0.17-0.080.08-0.02-0.11-0.19-0.06-0.27-0.09-0.21 (0.15) (0.16)(0.15)(.15)(0.16)(0.15)(0.16)**(0.15)(0.16) State-local public health authority--Decentralized -0.11 0.16-0.10-0.01-0.03 -0.17-0.06-0.18 (0.16) (0.15)(0.17) (0.16)(0.17) (0.16) County jurisdiction type -0.070.03-0.01-0.08-0.03-0.04-0.05-0.17-0.07-0.01 (0.07)(0.06)(0.07) (0.06) (0.07)(0.06)***(0.06) City/County jurisdiction type -0.090.00-0.14-0.12-0.04-0.07-0.14-0.15-0.100.00 (0.06) (0.06)**(0.07)*(0.05)(0.06)(0.06)**(0.06)***(0.06)*(0.06) Poverty rate 0.030.02-0.01-0.05-0.04-0.08-0.01-0.040.060.00 (0.06) (0.07) (0.05)(0.06) Physicians per capita, log 0.070.050.110.070.010.03 0.110.190.06 (0.07) (0.08)(0.05)(0.07) (0.07)***(0.07) R2R2 0.10 0.020.030.060.120.04 0.070.12 *P<.10; **P<.05, ***P<.01

11 Table 2: Effects of system characteristics on performance of essential public health services: Standard Regression Estimates (Scutchfield Study Repeat) EPHS 1EPHS 2EPHS 3EPHS 4EPHS 5EPHS 6EPHS 7EPHS 8EPHS 9EPHS 10OVERALL Log Population (5)*0.260.300.240.340.380.25 Local Board of Health (8)*-0.28-0.26-0.32-0.36-0.52-0.37-0.42-0.22-0.51 Policy Making Board (7)*0.22 0.330.230.280.240.230.28 BOH--Not Elected (2)-0.40-0.44 Director--Masters Degree (3)-0.21-0.27-0.16 Director--MD, DDS, DVM (1)-0.15 Director--Bachelor Degree (3)-0.20-0.14-0.15 Director--Nursing Degree (5)*0.140.200.130.110.120.19 Director--Public Health (MPH, DrPH) (1) -0.20 Log Per Capita Expenditures (1)0.14 Log Expenditures (1)0.19 R2R2 0.150.170.120.080.320.260.200.130.22 0.26 Number in parentheses represents the total number of EPHS for which there is a significant relationship; * = significant relationship with overall performance

12 Conclusions: Same story? Findings confirmed from Mays (2006): – A larger population size is one of the strongest predictors of performance across many essential services; – Combined city-county jurisdictions is an important predictor of performance for EPHS 3, inform and educate, and EPHS 7, link to health services; and – Direct federal spending per capita is an important predictor of improved performance on EPHS 10, research for new insights and solutions.

13 Conclusions: Same story? Findings confirmed from Scutchfield (2004): – Increased population size is associated with improved performance on EPHS 10, research for new insights; – Existence of a local board of health that makes policy is associated with improved performance on EPHS 4, mobilize community partnerships; – Local Health Department (LHD) Director with a nursing degree is associated with improved performance on EPHS 8, ensure a competent workforce; and – LHD Director with a public health degree is associated with lower performance on EPHS 10, research for new insights.

14 Conclusions: New Story? Previous findings not confirmed: – Mays et al. (2006) found per capita spending of the LHD and the governmental relationship between the state and local health departments (i.e. centralized, decentralized, etc.) influenced local public health performance – Scutchfield et al. (2004) found LHD Director with a public health background had poorer performance on many of the EPHS

15 Conclusions: New Story? This study suggests that systems with a local board of health have poorer performance on many EPHS, yet… Those that have a policy making board of health perform better on many of the EPHS

16 Discussion Findings from this study indicate that we do not have enough evidence or clear evidence to make decisions about the optimal organization, leadership, and financing of public health systems

17 Discussion Findings from previous studies, this study, and another concurrent study by the authors suggest that local boards of health figure prominently in the performance of local public health systems/departments – Used cross-sectional data – No consistent BOH indicator that reflects performance or that provides a measure of the quality and effectiveness of boards of health – Use this research to generate hypotheses for further research on the work of boards of health

18 References Mays, G.P, McHugh, M.C, Shim, K, Perry, N., Lenaway, D., Halverson, P.K., and Moonesinghe, R. (2006). Institutional and Economic Determinants of Public Health System Performance. American Journal of Public Health, 96 (3):523-531. Scutchfield, F.D., Knight, E.A., Kelly, A.V., Bhandari, M.W., and Vasilescu, I.P. (2004) Local Public Health Agency Capacity and its Relationship to Public Health System Performance. Journal of Public Health Management and Practice, 10 (3): 204-215.

19 Contact Information Michelyn Wilson Bhandari, DrPH, MPH Eastern Kentucky University Department for Health Promotion and Administration 420 Begley, 521 Lancaster Ave. Richmond, KY 40475 michelyn.bhandari@eku.edu 859.622.1145

20 QUESTIONS??

Download ppt "New Data, Same Story? A Replication of Studies Using National Public Health Performance Data Michelyn W. Bhandari, DrPH, MPH 2008 AcademyHealth Public."

Similar presentations

Understanding Changes in Local Public Health Spending Glen Mays, PhD, MPH Department of Health Policy and Management University of Arkansas for Medical.

Understanding Changes in Local Public Health Spending Glen Mays, PhD, MPH Department of Health Policy and Management University of Arkansas for Medical.
Findings from the 2008 National Profile of Local Health Departments Study Minnesota Local Health Departments.

Findings from the 2008 National Profile of Local Health Departments Study Minnesota Local Health Departments.
Findings from the 2008 National Profile of Local Health Departments Study Wisconsin Local Health Departments.

Findings from the 2008 National Profile of Local Health Departments Study Wisconsin Local Health Departments.
Findings from the 2008 National Profile of Local Health Departments Study Washington Local Health Departments.

Findings from the 2008 National Profile of Local Health Departments Study Washington Local Health Departments.
Findings from the 2008 National Profile of Local Health Departments Study Florida Local Health Departments.

Findings from the 2008 National Profile of Local Health Departments Study Florida Local Health Departments.
Findings from the 2008 National Profile of Local Health Departments Study New Jersey Local Health Departments.

Findings from the 2008 National Profile of Local Health Departments Study New Jersey Local Health Departments.
Findings from the 2008 National Profile of Local Health Departments Study Missouri Local Health Departments.

Findings from the 2008 National Profile of Local Health Departments Study Missouri Local Health Departments.
Findings from the 2008 National Profile of Local Health Departments Study Iowa Local Health Departments.

Findings from the 2008 National Profile of Local Health Departments Study Iowa Local Health Departments.
Findings from the 2008 National Profile of Local Health Departments Study Kansas Local Health Departments.

Findings from the 2008 National Profile of Local Health Departments Study Kansas Local Health Departments.
Findings from the 2008 National Profile of Local Health Departments Study Alabama Local Health Departments.

Findings from the 2008 National Profile of Local Health Departments Study Alabama Local Health Departments.
Findings from the 2008 National Profile of Local Health Departments Study Illinois Local Health Departments.

Findings from the 2008 National Profile of Local Health Departments Study Illinois Local Health Departments.
Findings from the 2008 National Profile of Local Health Departments Study Arizona Local Health Departments.

Findings from the 2008 National Profile of Local Health Departments Study Arizona Local Health Departments.
Revenue Generation as Budget Strategy: Predictors of Per Capita Local Health Department Non ‐ Local Government Revenues Senay Goitom Robert M. La Follette.

Revenue Generation as Budget Strategy: Predictors of Per Capita Local Health Department Non ‐ Local Government Revenues Senay Goitom Robert M. La Follette.
The Role of Accreditation Intent in LHDs’ Decision to collaborate with Hospitals around the Community Health Assessment Simone R. Singh 1 and Erik L. Carlton.

The Role of Accreditation Intent in LHDs’ Decision to collaborate with Hospitals around the Community Health Assessment Simone R. Singh 1 and Erik L. Carlton.
Tax Levy Financing for Public Health: The Moderating Influence of Long-Term Debt J. Mac McCullough, PhD, MPH Assistant Professor School for the Science.

Tax Levy Financing for Public Health: The Moderating Influence of Long-Term Debt J. Mac McCullough, PhD, MPH Assistant Professor School for the Science.
Local Board of Health Training in Montana Presented to MLC-3 Open Forum Roundtable discussion group by Sue Miller Director, Montana Learning Collaborative.

Local Board of Health Training in Montana Presented to MLC-3 Open Forum Roundtable discussion group by Sue Miller Director, Montana Learning Collaborative.
SUPERINTENDENT AND BOARD OF EDUCATION MEMBER PERCEPTIONS REGARDING PREFERRED LEADERSHIP BEHAVIORS FOR SUPERINTENDENTS IN WEST VIRGINIA Keith A. Butcher.

SUPERINTENDENT AND BOARD OF EDUCATION MEMBER PERCEPTIONS REGARDING PREFERRED LEADERSHIP BEHAVIORS FOR SUPERINTENDENTS IN WEST VIRGINIA Keith A. Butcher.
Update on Public Health Financing & Economic Studies Glen Mays, PhD, MPH University of Kentucky publichealtheconomics.org National Coordinating.

Update on Public Health Financing & Economic Studies Glen Mays, PhD, MPH University of Kentucky publichealtheconomics.org National Coordinating.
Reinventing the 21 st Century Public Health Workforce: Innovation, Evaluation & Practice-Based Research Glen P. Mays, PhD, MPH University of Kentucky HRSA.

Reinventing the 21 st Century Public Health Workforce: Innovation, Evaluation & Practice-Based Research Glen P. Mays, PhD, MPH University of Kentucky HRSA.
Is Psychosocial Stress Associated with Alcohol Use Among Continuation High School Students? Raul Calderon, Jr. Ph.D., Gregory T. Smith, Ph.D., Marilyn.

Is Psychosocial Stress Associated with Alcohol Use Among Continuation High School Students? Raul Calderon, Jr. Ph.D., Gregory T. Smith, Ph.D., Marilyn.

Similar presentations

Ads by Google