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Promising Practices that show evidence of effectiveness in improving public health outcomes in a specific real-life setting, as indicated by achievement of aims consistent with the objectives of the activities, and are suitable for adaptation by other communities.
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Other
This episode from the podcast 99 Percent Invisible reflects on how the COVID-19 pandemic exposed the American public to a long-standing problem: the disjointed nature of the U.S. health system. Because state and local health departments largely operate independently and use their own data collection and analysis tools, health systems across the country lack standardized data definitions and systems. These inconsistencies made it nearly impossible to collect and analyze comprehensive, standardized data on COVID-19 cases, deaths, and vaccines administered amid the pandemic. Health experts featured on this episode believe that the pandemic made the need for an overhaul of America’s informatics system very apparent. When rebuilding this system, it’s important to focus on remedying existing inequalities in data collection and classification that in some cases render the health status of certain populations – think Native American communities and other communities of color – completely invisible in the data. By virtue of being small populations, it can be difficult for health departments to collect sufficient and/or statistically significant data on minority communities. Another issue discussed in this episode is the use of broad racial categories like “other,” “multiple races,” or even “Asian American,” which, if not disaggregated, obscures the health status of diverse populations who are grouped under the same category. Without comprehensive and inclusive health data, it’s difficult to identify disparities and implement policies and programming that promote social mobility and health equity.
Promising Practices that show evidence of effectiveness in improving public health outcomes in a specific real-life setting, as indicated by achievement of aims consistent with the objectives of the activities, and are suitable for adaptation by other communities.
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Toolkit
The Health Equity Assessment Toolkit (HEAT) is a software application that facilitates the assessment of within-country health inequalities. It was developed for use on desktop or laptop computers and mobile devices. Explore inequality, which enables users to explore the situation in one setting of interest (e.g. a country, province or district) to determine the latest situation of inequality and the change in inequalities over time. Compare inequality, which enables users to benchmark, i.e. compare the situation in one setting of interest with the situation in other settings.
Promising Practices that show evidence of effectiveness in improving public health outcomes in a specific real-life setting, as indicated by achievement of aims consistent with the objectives of the activities, and are suitable for adaptation by other communities.
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Toolkit
This is the summary page containing the full guide to HEDA: Conducting a Health Equity Data Analysis: A Guide for Local Health Departments, Version 2. HEDA provides information on how to think about, collect, and analyze local data related to health equity. It provides a starting point for understanding how to document health inequities. This guide provides a detailed process for analyzing health inequities in a local jurisdiction. The guide describes how to use data to identify health differences between population groups, instead of only examining the population as a whole. The process includes steps to identify and examine the causes of population differences in health, and emphasizes the importance of working in partnership at every step with communities experiencing inequities.
Promising Practices that show evidence of effectiveness in improving public health outcomes in a specific real-life setting, as indicated by achievement of aims consistent with the objectives of the activities, and are suitable for adaptation by other communities.
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Toolkit
The purpose of the project is to offer clear concepts, methods, data, and programming code to improve monitoring of, as well as actions to address health inequities, accomplished by using geocoding to link area-based social metrics to public health data.
Novel Practices that show potential to achieve desirable public health outcomes in a specific real-life setting and are in the process of generating evidence of effectiveness or may not yet be tested.
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Toolkit
This blueprint presents recommendations for Illinois to reduce health disparities in rural areas. Recommendations include (1) investing in programs to recruit and retain rural health care workers; (2) improving rural data systems; (3) integrating health care and social services in rural areas; (4) increasing communication between rural health organizations and public health departments; and (5) creating a rural innovation center to coordinate data, policies, and strategies across state agencies.
Promising Practices that show evidence of effectiveness in improving public health outcomes in a specific real-life setting, as indicated by achievement of aims consistent with the objectives of the activities, and are suitable for adaptation by other communities.
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Toolkit
This Vaccine Equity Toolkit, created by Kaiser Permanente, includes guidance for health systems and state and local governments to support equitable vaccine distribution. The toolkit includes sections on goal definition, metrics and reporting, tools for equity, and provides specific examples of Kaiser Permanente-funded initiatives to promote vaccine equity. The practice strategy this resource is focused on is equitable vaccine distribution.
Best Practices that show evidence of effectiveness in improving public health outcomes when implemented in multiple real-life settings, as indicated by achievement of aims consistent with the objectives of the activities.
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Toolkit
The PhenX Social Determinants of Health (SDOH) Assessments Collection, now available in the PhenX Toolkit, contains protocols to help measure upstream factors that shape behaviors and health outcomes. The PhenX Toolkit provides recommended standard data collection protocols for conducting biomedical research. The protocols are selected by working groups of domain experts using a consensus process, which includes the scientific community. The toolkit provides detailed protocols for collecting data and tools to help investigators incorporate these protocols into their studies. Using protocols from the PhenX Toolkit facilitates cross-study analysis, potentially increasing the scientific impact of individual studies.
Emerging Practices that show potential to achieve desirable public health outcomes in a specific real-life setting and produce early results that are consistent with the objectives of the activities and thus indicate effectiveness.
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Toolkit
This data dashboard provides a map that details which states are reporting race and ethnicity in their case, mortality, testing, and vaccination data, and includes a state action chart that provides information on how states plan to focus on equity beyond the COVID-19 pandemic.
Novel Practices that show potential to achieve desirable public health outcomes in a specific real-life setting and are in the process of generating evidence of effectiveness or may not yet be tested.
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Toolkit
The toolkit describes positive and problematic practices for centering racial equity across the six stages of the data life cycle: (1) data collection, (2) data access, (3) use of algorithms and statistical tools, (4) data analysis, and (5) reporting and dissemination.
Novel Practices that show potential to achieve desirable public health outcomes in a specific real-life setting and are in the process of generating evidence of effectiveness or may not yet be tested.
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Toolkit
The Community Information Exchange (CIE) Data Equity Framework’s goal is to build data systems to help institutions, and the communities they serve, approach CIE® planning and systems change work from a place of anti-racism by: (1) naming how data system design reflects understanding of and participation by the intended beneficiaries of current programs and interventions; (2) acknowledging and documenting the effects of a spectrum of data system design types on oppressed populations and communities; (3) identifying strategies needed to eliminate the harm of current processes and practices; (4) highlighting the behavior change needed to rebuild or change the overall data system to better meet community needs across racial and ethnic populations; and (5) adopting practices that promote restorative justice and mitigate harm and exploitation.