Using a positive deviance framework to identify Local Health Departments in Communities with exceptional maternal and child health outcomes: a cross sectional study
Abstract Background The United States spends more than most other countries per capita on maternal and child health (MCH), and yet lags behind other countries in MCH outcomes. Local health departments (LHDs) are responsible for administering various maternal and child health programs and interventio...
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doaj-2139ad887e8b4ac2827fcd4258e94b2e2020-11-24T21:08:03ZengBMCBMC Public Health1471-24582016-07-011611810.1186/s12889-016-3259-7Using a positive deviance framework to identify Local Health Departments in Communities with exceptional maternal and child health outcomes: a cross sectional studyTamar Klaiman0Athena Pantazis1Anjali Chainani2Betty Bekemeier3AccessMattersUniversity of Washington School of Nursing, Psychosocial & Community HealthUniversity of the SciencesUniversity of Washington School of Nursing, Psychosocial & Community HealthAbstract Background The United States spends more than most other countries per capita on maternal and child health (MCH), and yet lags behind other countries in MCH outcomes. Local health departments (LHDs) are responsible for administering various maternal and child health programs and interventions, especially to vulnerable populations. The goal of this study was to identify local health department jurisdictions (LHDs) that had exceptional maternal and child health outcomes compared to their in-state peers – positive deviants (PDs) - in Washington, Florida and New York in order to support the identification of strategies that can improve community health outcomes. Methods We used MCH expenditure data for all LHDs in FL (n = 67), and WA (n = 35), and most LHDs in NY (n = 48) for 2009–2010 from the Public Health Activities and Services Tracking (PHAST) database. We conducted our analysis in 2014–2015. Data were linked with variables depicting local context and LHD structure. We used a cross-sectional study design to identify communities with better than expected MCH outcomes and multiple regression analysis to control for factors outside of and within LHD control. Results We identified 50 positive deviant LHD jurisdictions across 3 states: WA = 10 (29 %); FL = 24 (36 %); NY = 16 (33 %). Overall, internal factor variables improved model fit for identifying PD LHD jurisdictions, but individual variables were not significant. Conclusions We empirically identified LHD jurisdictions with better MCH outcomes compared to their peers. Research is needed to assess what factors contributed to these exceptional MCH outcomes and over which LHDs have control. The positive deviance method we used to identify high performing local health jurisdictions in the area of maternal and child health outcomes can assist in better understanding what practices work to improve health outcomes. We found that funding may not be the only predictor of exceptional outcomes, but rather, there may be activities that positive deviant LHDs are conducting that lead to improved outcomes, even during difficult financial circumstances. This method can be applied to other outcomes, communities, and/or services.http://link.springer.com/article/10.1186/s12889-016-3259-7Positive devianceLocal health departmentsOutcomesMethods |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Tamar Klaiman Athena Pantazis Anjali Chainani Betty Bekemeier |
spellingShingle |
Tamar Klaiman Athena Pantazis Anjali Chainani Betty Bekemeier Using a positive deviance framework to identify Local Health Departments in Communities with exceptional maternal and child health outcomes: a cross sectional study BMC Public Health Positive deviance Local health departments Outcomes Methods |
author_facet |
Tamar Klaiman Athena Pantazis Anjali Chainani Betty Bekemeier |
author_sort |
Tamar Klaiman |
title |
Using a positive deviance framework to identify Local Health Departments in Communities with exceptional maternal and child health outcomes: a cross sectional study |
title_short |
Using a positive deviance framework to identify Local Health Departments in Communities with exceptional maternal and child health outcomes: a cross sectional study |
title_full |
Using a positive deviance framework to identify Local Health Departments in Communities with exceptional maternal and child health outcomes: a cross sectional study |
title_fullStr |
Using a positive deviance framework to identify Local Health Departments in Communities with exceptional maternal and child health outcomes: a cross sectional study |
title_full_unstemmed |
Using a positive deviance framework to identify Local Health Departments in Communities with exceptional maternal and child health outcomes: a cross sectional study |
title_sort |
using a positive deviance framework to identify local health departments in communities with exceptional maternal and child health outcomes: a cross sectional study |
publisher |
BMC |
series |
BMC Public Health |
issn |
1471-2458 |
publishDate |
2016-07-01 |
description |
Abstract Background The United States spends more than most other countries per capita on maternal and child health (MCH), and yet lags behind other countries in MCH outcomes. Local health departments (LHDs) are responsible for administering various maternal and child health programs and interventions, especially to vulnerable populations. The goal of this study was to identify local health department jurisdictions (LHDs) that had exceptional maternal and child health outcomes compared to their in-state peers – positive deviants (PDs) - in Washington, Florida and New York in order to support the identification of strategies that can improve community health outcomes. Methods We used MCH expenditure data for all LHDs in FL (n = 67), and WA (n = 35), and most LHDs in NY (n = 48) for 2009–2010 from the Public Health Activities and Services Tracking (PHAST) database. We conducted our analysis in 2014–2015. Data were linked with variables depicting local context and LHD structure. We used a cross-sectional study design to identify communities with better than expected MCH outcomes and multiple regression analysis to control for factors outside of and within LHD control. Results We identified 50 positive deviant LHD jurisdictions across 3 states: WA = 10 (29 %); FL = 24 (36 %); NY = 16 (33 %). Overall, internal factor variables improved model fit for identifying PD LHD jurisdictions, but individual variables were not significant. Conclusions We empirically identified LHD jurisdictions with better MCH outcomes compared to their peers. Research is needed to assess what factors contributed to these exceptional MCH outcomes and over which LHDs have control. The positive deviance method we used to identify high performing local health jurisdictions in the area of maternal and child health outcomes can assist in better understanding what practices work to improve health outcomes. We found that funding may not be the only predictor of exceptional outcomes, but rather, there may be activities that positive deviant LHDs are conducting that lead to improved outcomes, even during difficult financial circumstances. This method can be applied to other outcomes, communities, and/or services. |
topic |
Positive deviance Local health departments Outcomes Methods |
url |
http://link.springer.com/article/10.1186/s12889-016-3259-7 |
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