The Relationship Between Local Public Health Agency Administrative Variables and County Health Status Rankings in Kentucky April L. Harris, MPH; F. Douglas Scutchfield, MD; Georgia Heise, DrPH; Richard C. Ingram, DrPH rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
Objectives: The purpose of this research study was to determine whether specific local public health agency (LPHA) characteristics were associated with favorable county health status. Specifically, financial and administrative comparisons were made to determine whether variables such as budget size or number of employees, among others, were associated with community health status among the 120 counties in Kentucky. Other financial and administrative variables collected from LPHA data were also investigated in this study. Methods: Administrative and financial data were collected for each local public health agency in Kentucky. This was matched with data on the health status of Kentucky counties from the 2010 University of Wisconsin MATCH (Mobilizing Action Towards Community Health Assessment) counties in select measures of health. MATCH data used included measures of health outcomes, specifically socioeconomic status (SES), mortality, and morbidity. Logistic regressions were used to determine the relationship, if any, between variations in the health agency data variables, SES, and health status. Results: Analysis suggests that SES is the strongest link to county health status. Several other variables that appear to have statistically significant association with health status include the education level of the director, whether the LPHA employees received a raise, whether the LPHA had an associated Home Health agency, and the amount of money used from their reserve account to balance the LPHA budget. Conclusions: For many years, public health in Kentucky has measured the number of clinical visits and other LPHA services but failed to determine specific characteristics and variables that influence community health status. This study suggests that LPHAs in Kentucky can advance public health J Public Health Management Practice, 2014, 20(4), 378–383 C 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins Copyright
practice by having well-educated directors, giving annual incremental raises, and utilizing the agency reserve funds to meet budget shortfalls in the short run. Furthermore, LPHAs with an associated home health agency may need to reassess their impact and need in their community, considering the negative effect it may have on county health status. KEY WORDS: community health status, health outcomes, local
public health agency, performance Local public health agencies (LPHAs) across the country are dedicated to and1,2 responsible for improving the public’s health. The community’s health status rests largely on the ability of LPHAs to effectively deliver public health services. There is significant variability in administrative characteristics among LPHAs; this variation may be positive or negative in its influence on the effectiveness of the LPHAs; however, little research has examined this variability and impact on the performance of the LPHA3 In a similar way, little research exists to suggest what administrative variables may be associated with improved LPHAs’ outcomes, particularly the health status of their community.2,4,5,6 This study seeks to add to this body of research by examining the relationship between LPHA administrative variables in 119 of 120 Kentucky counties and their community health status. Substantial variation exists across Kentucky in the administrative structure of LPHAs, as well as the services they provide. Local public health agencies in
Author Affiliations: Three Rivers District Health Department, Owenton, Kentucky (Ms Harris and Dr Heise); and Department of Health Services Management, University of Kentucky College of Public Health, Lexington, Kentucky (Drs Scutchfield and Ingram). The authors declare no conflicts of interest. Correspondence: April L. Harris, MPH, Three Rivers District Health Department, 510 S Main St, Owenton, KY 40359 ([email protected]). DOI: 10.1097/PHH.0b013e3182a5c2f8
378 Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Kentucky’s Local Public Health and County Health Status
Kentucky can serve single counties, districts (multicounty), and city-county jurisdictions. Agency chief executive officers (CEOs) have a wide variety of educational attainment; they range from a high school diploma to various doctoral degrees, a variation of particular interest given that an executive’s level of education may be a significant predictor of local public health system7,8 performance, and that system performance may be associated with community health. LPHAs in Kentucky also vary widely in other agency capacity characteristics, for example, number of public health workers per capita and characteristics that appear to7,8 influence departmental performance. Wide variation in demographic factors exists between counties in Kentucky, but the state can be classified largely rural9 and has a high percentage of population living in poverty.10 While a variety of inputs appear to be associated with public health system performance, evidence suggests that certain inputs, notably finances, particularly noncategorical funding, may be major factors that influence LPHA performance.7,11-13 This is of particular interest, given the evidence that suggests that public health system performance may be associated with health outcomes.2,4 While LPHAs are mandated by the state and federal governments to perform many of the same services, nonrestricted funding (primarily local tax dollars) allows LPHAs the flexibility to provide additional services.6 These nonrestricted services allow for LPHAs to respond to local needs and provision of essential public health services that are not provided by other members of the public health system and that appear to have the most significant need in their local community. In Kentucky, LPHAs provide some of these services, which include initiatives such as smoke-free ordinances, primary care provision, home health services, and health education efforts. This study examines the administrative structure of LPHAs in Kentucky, using data obtained from the Kentucky Department for Public Health, and the relationship between variation in agency structure and county morbidity and mortality status ranking as reflected in the 2010 County Health Rankings (CHR) Report.14
● Methods Overall county health outcome rankings for 119 counties in Kentucky served as the dependent variable in this analysis. The CHR use a number of dependent community health outcome variables, including mortality rates, morbidity measures, and those related to quality of life, to determine overall health rankings of every county in the United States. Health rankings data for each county were paired with corresponding socioeconomic data as control variables (also obtained
❘ 379
from the CHR data set). These data were then merged with selected administrative variables obtained from the Kentucky Department for Public Health, Division of Administration and Financial Management, which served as independent variables for analysis. It is important to note that the financial variables reflect the 2010 fiscal year, which includes data from July 2009 through June 2010. Table 1 contains a list of the independent variables examined, including the administrative variables. The single nonadministrative variable, socioeconomic status (SES), was obtained from the MATCH (Mobilizing Action Towards Community Health Assessment) data set and is calculated using a formula that includes a number of different items: employment, income, education, community safety, and family and social support.15 One Kentucky county, Jefferson County, the county containing Louisville, Kentucky’s largest city, was excluded from this study because of a lack of available data. Statistical Analysis Software was used for statistical analysis. Two regression models were developed using Statistical Analysis Software. Stepwise selection, using the Aikake Information Criterion, using a cutoff for inclusion of α ≤ .05, was used to develop the first regression model used in the analysis. Z scores of the health rankings of the counties contained in the analysis were the dependent variable (z scores were used to standardize the county ranking system and thus account for a normal error distribution). The independent variables used were those contained in Table 1. The second model was developed using logistic regression. Counties were ordered into 3 categories: the 10 healthiest counties, the 10 least healthy counties, and those 99 counties that fell between those 2 groups. This model predicted which explanatory variables were associated with ranking status (top 10, middle, or bottom 10).
● Results Table 2 shows the association between county health ranking z scores and the various independent variables examined. County SES was by far the most significant predictor of health rank, with a P value of less than .0001, and a positive parameter estimate, suggesting that as SES increases, health ranking increases. Three LPHA financial variables were positively associated with health ranking: percentage of the LPHA budget coming from local taxing district contribution, if the LPHA had given employees raise in 2009-2010 fiscal year, and the cash reserve budgeted for the 2010-2011 fiscal year per $100 000 (P values of .0023, .0003, and .0158, respectively). Two other variables had significant negative associations with health ranking: membership in KALBOH (the Kentucky Association of Local Boards
Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
380 ❘ Journal of Public Health Management and Practice TABLE 1 ● Independent Variables Included in Analysis
qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq
Per Capita Budget
Paid Membership to KHDA
Total Reserve Funds
Percentage of the LPHA budget coming from local taxing district contribution Education level of agency director
Paid membership to KPHA
Agency served single county or district jurisdiction Contained home health agency
Participation in Passport-managed care program
Paid membership to KALBOH
Percentage of agency budget from Medicaid
Other programmatic funds outside of Medicaid and not included in their local taxes Agency had given employees raise in 2009-2010 fiscal year
Amount of funds used to balance current fiscal year budget per $100 000 Amount of reserve budgeted for use in 2010-2011 fiscal year per $100 000 Rate county has set to collect for local public health tax Percentage of the LPHA budget that comes from local public health taxes Socioeconomic status
Abbreviations: KALBOH, Kentucky Association of Local Boards of Health; KHDA, Kentucky Health Directors Association; KPHA, Kentucky Public Health Association; LPHA, local public health agency.
of Health) and participation in the Passport Managed Care Program, a privatized Medicaid-managed care program (P values of .0023 and .0003, respectively). Table 3 shows the association between presence in the 3 tiers of county health ranking (top 10, middle 99, and bottom 10) and the various independent variables examined. County SES was again the most significant predictor of health rank, with a P value of less than .0001, and a positive parameter estimate, suggesting that as SES increases, health ranking increases. Two financial variables were significantly positively associated with ranking tier: if the LPHA had given employees raise in 2009-2010 fiscal year and amount of reserve funds used to balance the previous year’s budget per $100 000 (P values of .0058 and .0071, respectively). Education level of agency director was also positively associated with ranking tier (P value of .0234), suggesting that agencies headed by directors with higher levels of education had higher ranks. One variable, presence of a home health agency, had a significant negative association with ranking tier (P value of .0245), suggesting that public health agencies that provided home health services were associated with lower rankings.
● Discussion It is no surprise that SES was the most significant predictor of both measures of health ranking (z scores and ranking tier)—other data suggest that it may be one of the strongest determinants of health. SES is the only independent variable that was found to be significant in both models and this underscores the significant influence that it has on community health; SES was a significant predictor of both overall health rank (Table 1) and presence in the top, middle and bottom counties (Table 2). It is possible that some of the other items that were significant in only one of the models may have either large or small amounts of variance, and thus significant differences may be found only when categorizing them by top, middle, and bottom ranks (Table 2), and which makes a clearer distinction between agencies, or by including all agencies in the model and removing the effect of any tightly clustered variables. Given the strong link between poverty and health, and the positive coefficients seen in the regression models, any attempts to improve community health may need to be rooted in addressing the socioecological determinants of
TABLE 2 ● Results of Stepwise Regression Examining Relationship Between Variables in Table 1 and Z Score of Health
Rankings for All Counties Examined qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq Variable
Parameter Estimate
Standard Error
P
0.12566 − 0.23594 − 0.49581 0.01020 0.09135 0.01690 0.01526
0.04031 0.08783 0.13359 0.00335 0.02464 0.00689 0.00130
.0023 .0083 .0003 .0029 .0003 .0158
Objectives: The purpose of this research study was to determine whether specific local public health agency (LPHA) characteristics were associated with favorable county health status. Specifically, financial and administrative comparisons were made to determine whether variables such as budget size or number of employees, among others, were associated with community health status among the 120 counties in Kentucky. Other financial and administrative variables collected from LPHA data were also investigated in this study. Methods: Administrative and financial data were collected for each local public health agency in Kentucky. This was matched with data on the health status of Kentucky counties from the 2010 University of Wisconsin MATCH (Mobilizing Action Towards Community Health Assessment) counties in select measures of health. MATCH data used included measures of health outcomes, specifically socioeconomic status (SES), mortality, and morbidity. Logistic regressions were used to determine the relationship, if any, between variations in the health agency data variables, SES, and health status. Results: Analysis suggests that SES is the strongest link to county health status. Several other variables that appear to have statistically significant association with health status include the education level of the director, whether the LPHA employees received a raise, whether the LPHA had an associated Home Health agency, and the amount of money used from their reserve account to balance the LPHA budget. Conclusions: For many years, public health in Kentucky has measured the number of clinical visits and other LPHA services but failed to determine specific characteristics and variables that influence community health status. This study suggests that LPHAs in Kentucky can advance public health J Public Health Management Practice, 2014, 20(4), 378–383 C 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins Copyright
practice by having well-educated directors, giving annual incremental raises, and utilizing the agency reserve funds to meet budget shortfalls in the short run. Furthermore, LPHAs with an associated home health agency may need to reassess their impact and need in their community, considering the negative effect it may have on county health status. KEY WORDS: community health status, health outcomes, local
public health agency, performance Local public health agencies (LPHAs) across the country are dedicated to and1,2 responsible for improving the public’s health. The community’s health status rests largely on the ability of LPHAs to effectively deliver public health services. There is significant variability in administrative characteristics among LPHAs; this variation may be positive or negative in its influence on the effectiveness of the LPHAs; however, little research has examined this variability and impact on the performance of the LPHA3 In a similar way, little research exists to suggest what administrative variables may be associated with improved LPHAs’ outcomes, particularly the health status of their community.2,4,5,6 This study seeks to add to this body of research by examining the relationship between LPHA administrative variables in 119 of 120 Kentucky counties and their community health status. Substantial variation exists across Kentucky in the administrative structure of LPHAs, as well as the services they provide. Local public health agencies in
Author Affiliations: Three Rivers District Health Department, Owenton, Kentucky (Ms Harris and Dr Heise); and Department of Health Services Management, University of Kentucky College of Public Health, Lexington, Kentucky (Drs Scutchfield and Ingram). The authors declare no conflicts of interest. Correspondence: April L. Harris, MPH, Three Rivers District Health Department, 510 S Main St, Owenton, KY 40359 ([email protected]). DOI: 10.1097/PHH.0b013e3182a5c2f8
378 Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
Kentucky’s Local Public Health and County Health Status
Kentucky can serve single counties, districts (multicounty), and city-county jurisdictions. Agency chief executive officers (CEOs) have a wide variety of educational attainment; they range from a high school diploma to various doctoral degrees, a variation of particular interest given that an executive’s level of education may be a significant predictor of local public health system7,8 performance, and that system performance may be associated with community health. LPHAs in Kentucky also vary widely in other agency capacity characteristics, for example, number of public health workers per capita and characteristics that appear to7,8 influence departmental performance. Wide variation in demographic factors exists between counties in Kentucky, but the state can be classified largely rural9 and has a high percentage of population living in poverty.10 While a variety of inputs appear to be associated with public health system performance, evidence suggests that certain inputs, notably finances, particularly noncategorical funding, may be major factors that influence LPHA performance.7,11-13 This is of particular interest, given the evidence that suggests that public health system performance may be associated with health outcomes.2,4 While LPHAs are mandated by the state and federal governments to perform many of the same services, nonrestricted funding (primarily local tax dollars) allows LPHAs the flexibility to provide additional services.6 These nonrestricted services allow for LPHAs to respond to local needs and provision of essential public health services that are not provided by other members of the public health system and that appear to have the most significant need in their local community. In Kentucky, LPHAs provide some of these services, which include initiatives such as smoke-free ordinances, primary care provision, home health services, and health education efforts. This study examines the administrative structure of LPHAs in Kentucky, using data obtained from the Kentucky Department for Public Health, and the relationship between variation in agency structure and county morbidity and mortality status ranking as reflected in the 2010 County Health Rankings (CHR) Report.14
● Methods Overall county health outcome rankings for 119 counties in Kentucky served as the dependent variable in this analysis. The CHR use a number of dependent community health outcome variables, including mortality rates, morbidity measures, and those related to quality of life, to determine overall health rankings of every county in the United States. Health rankings data for each county were paired with corresponding socioeconomic data as control variables (also obtained
❘ 379
from the CHR data set). These data were then merged with selected administrative variables obtained from the Kentucky Department for Public Health, Division of Administration and Financial Management, which served as independent variables for analysis. It is important to note that the financial variables reflect the 2010 fiscal year, which includes data from July 2009 through June 2010. Table 1 contains a list of the independent variables examined, including the administrative variables. The single nonadministrative variable, socioeconomic status (SES), was obtained from the MATCH (Mobilizing Action Towards Community Health Assessment) data set and is calculated using a formula that includes a number of different items: employment, income, education, community safety, and family and social support.15 One Kentucky county, Jefferson County, the county containing Louisville, Kentucky’s largest city, was excluded from this study because of a lack of available data. Statistical Analysis Software was used for statistical analysis. Two regression models were developed using Statistical Analysis Software. Stepwise selection, using the Aikake Information Criterion, using a cutoff for inclusion of α ≤ .05, was used to develop the first regression model used in the analysis. Z scores of the health rankings of the counties contained in the analysis were the dependent variable (z scores were used to standardize the county ranking system and thus account for a normal error distribution). The independent variables used were those contained in Table 1. The second model was developed using logistic regression. Counties were ordered into 3 categories: the 10 healthiest counties, the 10 least healthy counties, and those 99 counties that fell between those 2 groups. This model predicted which explanatory variables were associated with ranking status (top 10, middle, or bottom 10).
● Results Table 2 shows the association between county health ranking z scores and the various independent variables examined. County SES was by far the most significant predictor of health rank, with a P value of less than .0001, and a positive parameter estimate, suggesting that as SES increases, health ranking increases. Three LPHA financial variables were positively associated with health ranking: percentage of the LPHA budget coming from local taxing district contribution, if the LPHA had given employees raise in 2009-2010 fiscal year, and the cash reserve budgeted for the 2010-2011 fiscal year per $100 000 (P values of .0023, .0003, and .0158, respectively). Two other variables had significant negative associations with health ranking: membership in KALBOH (the Kentucky Association of Local Boards
Copyright © 2014 Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
380 ❘ Journal of Public Health Management and Practice TABLE 1 ● Independent Variables Included in Analysis
qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq
Per Capita Budget
Paid Membership to KHDA
Total Reserve Funds
Percentage of the LPHA budget coming from local taxing district contribution Education level of agency director
Paid membership to KPHA
Agency served single county or district jurisdiction Contained home health agency
Participation in Passport-managed care program
Paid membership to KALBOH
Percentage of agency budget from Medicaid
Other programmatic funds outside of Medicaid and not included in their local taxes Agency had given employees raise in 2009-2010 fiscal year
Amount of funds used to balance current fiscal year budget per $100 000 Amount of reserve budgeted for use in 2010-2011 fiscal year per $100 000 Rate county has set to collect for local public health tax Percentage of the LPHA budget that comes from local public health taxes Socioeconomic status
Abbreviations: KALBOH, Kentucky Association of Local Boards of Health; KHDA, Kentucky Health Directors Association; KPHA, Kentucky Public Health Association; LPHA, local public health agency.
of Health) and participation in the Passport Managed Care Program, a privatized Medicaid-managed care program (P values of .0023 and .0003, respectively). Table 3 shows the association between presence in the 3 tiers of county health ranking (top 10, middle 99, and bottom 10) and the various independent variables examined. County SES was again the most significant predictor of health rank, with a P value of less than .0001, and a positive parameter estimate, suggesting that as SES increases, health ranking increases. Two financial variables were significantly positively associated with ranking tier: if the LPHA had given employees raise in 2009-2010 fiscal year and amount of reserve funds used to balance the previous year’s budget per $100 000 (P values of .0058 and .0071, respectively). Education level of agency director was also positively associated with ranking tier (P value of .0234), suggesting that agencies headed by directors with higher levels of education had higher ranks. One variable, presence of a home health agency, had a significant negative association with ranking tier (P value of .0245), suggesting that public health agencies that provided home health services were associated with lower rankings.
● Discussion It is no surprise that SES was the most significant predictor of both measures of health ranking (z scores and ranking tier)—other data suggest that it may be one of the strongest determinants of health. SES is the only independent variable that was found to be significant in both models and this underscores the significant influence that it has on community health; SES was a significant predictor of both overall health rank (Table 1) and presence in the top, middle and bottom counties (Table 2). It is possible that some of the other items that were significant in only one of the models may have either large or small amounts of variance, and thus significant differences may be found only when categorizing them by top, middle, and bottom ranks (Table 2), and which makes a clearer distinction between agencies, or by including all agencies in the model and removing the effect of any tightly clustered variables. Given the strong link between poverty and health, and the positive coefficients seen in the regression models, any attempts to improve community health may need to be rooted in addressing the socioecological determinants of
TABLE 2 ● Results of Stepwise Regression Examining Relationship Between Variables in Table 1 and Z Score of Health
Rankings for All Counties Examined qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq Variable
Parameter Estimate
Standard Error
P
0.12566 − 0.23594 − 0.49581 0.01020 0.09135 0.01690 0.01526
0.04031 0.08783 0.13359 0.00335 0.02464 0.00689 0.00130
.0023 .0083 .0003 .0029 .0003 .0158
