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The Association in State Health Outcomes by Provider Type
Difference in Association Between State-Level Health Outcomes for Direct Patient Care FTEs and Population Based FTEs
Robin Pendley, DrPH, MPH, CPHAssistant Professor, ETSU
Department of Health Services Management and Policy
October 29, 2012
Efforts to Enumerate Public Health Workforce
1920-APHA/
USPHS 83 Municipal
Health Depts.
1923 US Treasury/Public Health Service-
100 Largest Cities Health
Depts.
1933 Mountin expenditures,
full time workers, part-
time, per-capita
expenditures nursing,
physicians
1933-1946-US Public
Health Service
personnel and public
expenditures local
agencies
1945 Emerson Report-LHDs
benchmarks for services/staffing
patterns
1947-1964-DHEW yearly reporting of local public health per
capita expenditures
Efforts to Enumerate PH Workforce
1970-1995 ASTHO
Reporting System-
state/local expenditures
1976 Health Professionals
Education Assistance Act
1978 Health Services
Research, Health
Statistics, and Health Technology
Act
1980 USDHHS
Public Health Service
1988 IOM
Report, Future
of Public Health
1990 NACCHO
Profile
1992-1995 PH>Impact-
health status
1996-97 NACCHO
profile
Efforts to Enumerate PH Workforce
1999-2000-
NACCHO Infrastructure survey
2000 HRSA Public Health
Workforce Enumeration
2002 IOM
report, The
Future of Public
Health in the 21st century
2003 IOM report, Who Will Keep the
Public Healthy?
2010/2011 ACA
2010-2012 Enumeration
Crawford et al Research Agenda1
• Workforce size and composition
• Workforce diversity• Workforce
effectiveness and health impact
• Recruitment, Retention, and Separation
• Worker pay, promotion, and job satisfaction
• Demand for public health workforce
• Education, training, and credentialing
• Public health workforce policy
Relevant studies
• Mays 2011-increased spending in public health decreases preventable deaths including infant mortality, diabetes, cardiovascular disease, and cancer2
• Erwin 2010-examined changes in local health department resources with AHR state-level outcomes. Increases in staff significantly associated with decreases in CVD mortality3
Recent PHSSR Agenda
• What factors influence the supply of, demand for, and geographic and organizational distribution of workers with the public health workforce?
• How does the size and composition of the public health workforce affect the volume, mix, quality, and outcomes of public health strategies delivered at local, state, and national levels?
Purpose
• To examine the relationship between workforce, provision of services, and provider type (population-based/clinical) for state health agencies and state level health outcomes
• This will not only be the first attempt to examine state health agencies workforce data and health outcomes at the state level but will be among the first to explore Association of State and Territorial Health Officials (ASTHO) data
InputsWorkfor
ceFundingGoverna
nceState
Health Agency Structur
e
Outputs
Clinical and
Population-
BasedService
s
Outcomes
Improved Health
Methods
• Cross-sectional study of secondary data (ASTHO 2010, AHR 2010, Census 2010)
• Descriptive Statistics• Bivariate Analyses (p-value less than 0.20)• Multiple Imputation, Multivariate Analyses-
Linear Regression, Linear Contrast-Research Question 3
Potential Control Variables
• State health department structure • Capacity variables (governance classification,
role of state health agencies, does your state have a board of health, Enforcement/adjudicatory powers, expenditures, state health official authority, qualifications, salary
• Demographic characteristics-age of population, race, ethnicity
Description of FTEsFTEs n
Mean (SD)Median (Q1, Q3)Min, MaxSkewness
482177.55 (2,944.75)1280.05 (476.75, 2,651.00)199.00, 15,364.003.07
FTEs/Population per 100,000 nMean (SD)Median (Q1, Q3)Min, MaxSkewness
4849.72 (53.76)31.00 (18.03, 65.54)5.41, 263.472.38
Direct Patient Care FTES/Population per 100,000(Physician, Public Health Nurse, Nutritionist)
nMean (SD)Median (Q1, Q3)Min, MaxSkewness
367.46 (9.34)2.90 (0.86, 13.42)0.27, 45.102.18
Population-based FTES/Population per 100,000
nMean (SD)Median (Q1, Q3)Min, MaxSkewness
308.37 (5.68)7.80 (3.12, 11.65)0.79, 21.940.85
Occupational Classifications of FTEsOccupational Classification
Total current FTE
Administrative or clerical Personnel
nMean (SD)Median (Q1, Q3)Min, MaxSkewness
44415.93 (670.44)153.00 (87.01, 25396.50)21.00, 3197.003.18
Public health nurse nMean (SD)Median (Q1, Q3)Min, MaxSkewness
43256.31 (422.39)79.00 (21.00, 374.70)1.00, 2190.003.05
Environmental health worker
nMean (SD)Median (Q1, Q3)Min, MaxSkewness
40144.18 (68.90)183.52(27.25, 181.75)2.00, 677.001.75
Research Question
• Is the association between state-level health outcomes and direct patient care FTEs different than the association between state-level health outcomes and population-based FTEs?
• H0: There is no difference in association between state-level health outcomes and direct patient care FTEs and association between population-based FTEs and state-level health outcomes adjusting for potential control variables.
• Ha: There is a difference in association between state-level health outcomes and direct patient care FTEs and association between population-based FTEs and state-level health outcomes adjusting for potential control variables
Direct Patient Care Job Classification (Clinical)
Population-Based Job Classification (Non-clinical)
PhysicianPublic health nurseNutritionist
Environmental health workerEpidemiologist/statisticianHealth educatorPublic health information specialistLaboratory worker
Linear Contrast Test of Equality 1Outcome Est β
Transformed Population
FTE
Est βTransformed
Direct Care FTE
SEBeta1 SEBeta2CorrB1B2 z p
Obesity -0.96 0.72 0.86 0.53 -0.59 -1.34 0.18
Smoking -0.55 0.51 0.88 0.54 -0.6 -0.83 0.41
Binge Drinking
0.89 -0.84 1.23 0.48 -0.59 1.11 0.27
Occupational 1.19 0.02 0.46 0.33 -0.57 1.65 0.10
Infectious 0.14 0.58 1.39 1.08 -0.63 -0.2 0.84
Air Pollution -0.47 -0.18 0.71 0.34 -0.6 -0.31 0.76
Immunization 0.75 -0.38 0.49 0.35 -0.56 1.53 0.13
Linear Contrast Test of Equality 2Outcome Est β
Transformed Population
FTE
Est βTransformed
Direct Care FTE
SEBeta1 SEBeta2 CorrB1B2 z p
Preventable Hospitalizations
-0.93 0.66 4.26 2.15 -0.48 -0.28 0.78
Early Prenatal Care
0.80 -0.50 2.92 1.51 -0.60 0.32 0.75
Premature Death
-52.7 292 309 165 -0.47 -0.83 0.40
Poor Physical Health
-0.05 0.01 0.11 0.06 -0.26 -0.40 0.69
Geographic Disparity
0.46 0.12 1.24 0.69 -0.58 0.20 0.84
Linear Contrast Test of Equality 3Outcome Est β
Transformed Population
FTE
Est βTransformed
Direct Care FTE
SEBeta1 SEBeta2 CorrB1B2 z p
Infant Mortality
-0.13 0.32 0.21 0.14 -0.58 -1.40 0.16
Cancer Deaths
-3.93 2.55 6.30 2.63 -0.54 -0.81 0.42
CVD Deaths
-4.04 0.98 7.80 5.76 -0.62 -0.41 0.68
Teen Birth Rate
-6.74 5.78 1.76 1.2 -0.62 -4.67 <0.01
Recent Dental Visit
1.86 -1.62 0.90 0.55 -0.44 2.80 0.01
Stroke -0.12 0.18 0.09 0.05 -0.59 -2.33 0.02
Linear Contrast Test of Equality 4Outcome Est β
Transformed Population
FTE
Est βTransformed
Direct Care FTE
SEBeta1 SEBeta2 CorrB1B2 z p
High Cholesterol
1.30 -0.34 0.56 0.30 -0.56 2.12 0.03
Heart Attack
0.06 0.10 0.20 0.10 -0.62 -0.13 0.89
Cardiac Heart Disease
0.21 -0.08 0.15 0.12 -0.54 1.23 0.22
Diabetes -0.47 0.39 0.29 0.19 -0.62 -1.95 0.06
Low Birth Weight
0.58 -0.13 0.20 0.10 -0.55 2.61 0.01
Preterm Birth
0.25 0.10 0.35 0.22 -0.59 0.28 0.78
Conclusion
• Significant differences in association between health outcomes and population based FTEs and association between health outcomes and direct care FTEs
Areas for Future Research
• Evidence linking public health workforce to health outcomes is relatively sparse
• Comparison of Beck’s NACCHO/CHSI 2010• Cross-sectional/Longitudinal
ASTHO/Commonwealth Report State Scorecard, AHRQ National Healthcare Disparities Report
• Repeating Erwin’s study for 2010• NPHPSP for State
References
• 1. Crawford, C.A.G., et al., Perspectives on Public Health Workforce Research. Journal of Public Health Management and Practice, 2009: p. S5-S15.
• 2. Mays, G.P. and S.A. Smith, Evidence Links Increases In Public Health Spending To Declines In Preventable Deaths. Health Affairs, 2011.
• 3. Erwin, P.C., et al., The Association of Changes in Local Health Department Resources With Changes in State-Level Health Outcomes. Am J Public Health, 2011. 101(4): p. 609-615.
Bivariate ScreeningState/Territorial Laboratory Services-Cholesterol Screening
Performed by state/territorial public health agency
Performed by local health dept.led by a state/territorial employee
Performed by local health dept. led by a local employee
Performed by a not-for profit entity
Performed by a for-profit entity
Performed by another state/territorial agency
High Cholesterol
Tp-value
-1.950.06
-0.750.46
0.640.52
0.450.65
1.700.10
1.060.29
Pearson’s CorrelationTransformed
FTE per Population
Transformed Direct Care FTE per Population
Transformed Population FTE per Population
Prevalence of Binge Drinking (Percent of population)
Pearson Correlation
-0.20 -0.24 0.12
N 48.00 36.00 30.00
Air Pollution (Micrograms of fine particles per cubic meter)
Pearson Correlation
-0.38 -0.17 -0.26
N 48.00 36.00 30.00
Preterm Birth (Percent of births under 37 weeks gestation)
Pearson Correlation
0.29 0.32 0.13
N 48.00 36.00 30.00
ANOVA of Governance and Health Outcomes
ANOVA df F Sig.
Prevalence of Binge Drinking
49 1.14 0.36
Immunization Coverage
49 1.21 0.32
Preventable Hospitalizations
49 0.37 0.89
Early Prenatal Care 48 1.17 0.34
Premature Death 49 1.70 0.15
Teen Birth Rate 49 2.20 0.06
Low Birth Weight 49 2.16 0.07
Preterm Birth 49 2.14 0.07