Using Local Health Information To Promote Public Health

Luck, Jeff; Chang, Carol; Brown, E. Richard; Lumpkin, John R.

doi:10.1377/hlthaff.25.4.979

Cited by 31 publications

(21 citation statements)

References 4 publications

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“…Technical limitations are a frequently cited barrier to the development and dissemination of local health information [8, 12, 24–26]. For example, much of the data that are available are reported for geographic areas that do not provide the local-level information needed for public health intervention.…”

Section: Discussionmentioning

confidence: 99%

A geographic information system-based method for estimating cancer rates in non-census defined geographical areas

Freeman

Boylan

Pugach

et al. 2017

Cancer Causes Control

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Purpose To address locally relevant cancer-related health issues, health departments frequently need data beyond that contained in standard census area-based statistics. We describe a geographic information system-based method for calculating age-standardized cancer incidence rates in non-census defined geographical areas using publically available data. Methods Aggregated records of cancer cases diagnosed from 2009 through 2013 in each of Chicago’s 77 census-defined community areas were obtained from the Illinois State Cancer Registry. Areal interpolation through dasymetric mapping of census blocks was used to redistribute populations and case counts from community areas to Chicago’s 50 politically defined aldermanic wards, and ward-level age-standardized 5-year cumulative incidence rates were calculated. Results Potential errors in redistributing populations between geographies were limited to <1.5% of the total population, and agreement between our ward population estimates and those from a frequently cited reference set of estimates was high (Pearson correlation r = 0.99, mean difference = −4 persons). A map overlay of safety-net primary care clinic locations and ward-level incidence rates for advanced-staged cancers revealed potential pathways for prevention. Conclusions Areal interpolation through dasymetric mapping can estimate cancer rates in non-census defined geographies. This can address gaps in local cancer-related health data, inform health resource advocacy, and guide community-centered cancer prevention and control.

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Section: Discussionmentioning

confidence: 99%

A geographic information system-based method for estimating cancer rates in non-census defined geographical areas

Freeman

Boylan

Pugach

et al. 2017

Cancer Causes Control

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“…Local health data can be a powerful vehicle for improving the health of a community [1]. When aggregated, local health data helps monitor the incidence, trends, and patterns and disease in a given population [2].…”

Section: Introductionmentioning

confidence: 99%

“…Adequate data storage is vital as health datasets can consume large amounts of data storage space. Usability problems have also been reported, as systems are often difficult to navigate and use, and data are missing or incomplete [1]. Usability includes the functionality, the ability to retrieve data, and the usefulness of these data.…”

Section: Introductionmentioning

confidence: 99%

Challenges faced with the implementation of Web-Based Data Query Systems for population health: development of a questionnaire based on expert consensus

Ahuja

Aseltine

Warren

et al. 2018

Pilot Feasibility Stud

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BackgroundState health agencies (SHA) and local health agencies (LHA) face several challenges with the dissemination of local health data using Web-Based Data Query Systems (WDQS). To help guide future research, this study aimed to utilize expert consensus to identify the most relevant items that contribute to these challenges.MethodsA total of 17 researchers and public health professionals agreed to participate in a three-round Delphi process. In round 1, four topics were represented on a 42-item questionnaire using a 5-point Likert scale, along with free-text responses. Free-text responses were analyzed leading to a series of items for a second Delphi round. Participants were given an opportunity to revise results in round 3 for items that did not meet consensus in round 1 or round 2. Consensus on expert opinions was defined at interquartile range (IQR) ≤ 1.ResultsThe experts reached consensus on a total of 21 (50%) of the 42 items presented in the initial questionnaire. Eleven of the 15 (73%) of the items extracted from the free-text responses met consensus. Items in consensus from this pilot study were used to develop an instrument for a broader survey across Behavioral Risk Factor Surveillance System (BRFSS) coordinators across all 50 US states.ConclusionExperts confirmed that software development costs, inadequate human resources, data sharing gaps, a lack of political support, and poor data quality contribute significantly to challenges in their data implementation. The findings from this pilot study inform us of items of public health significance that will help guide future research.

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“…Luck, et al [10], explains that social informatics has been a powerful driver for improving e-health and community health services. The authors noted that social informatics can help in highlighting the existence of opportunities and problems for the purposes of improvement.…”

Section: Introductionmentioning

confidence: 99%

The Potential Use of Multi-agent and Hybrid Data Mining Approaches in Social Informatics for Improving e-Health Services

Sharma

Shadabi

2014

2014 IEEE Fourth International Conference on Big Data and Cloud Computing

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Social and health informatics has the potential of improving the general wellbeing and health of individuals. Although the structure and nature of health facilities and services in some countries may pose a challenge for a short while, such obstacles according to many studies will be streamlined in the near future. The widespread utilization and implementation of healthcare information system in the day-to-day health care operations will lead to cost effective clinical trials and selfhealthcare management. On the other hand, recent rapid development of computer technology in this area has introduced a data explosion challenge. This paper provides brief background information on Social Informatics and e-Health Systems. Follow by an overview of two hybrid intelligent techniques that might be utilized as a new generation of predictive analytics for big data particularly for knowledge discovery in big data and decision making processes in social systems.

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Using Local Health Information To Promote Public Health

Cited by 31 publications

References 4 publications

A geographic information system-based method for estimating cancer rates in non-census defined geographical areas

A geographic information system-based method for estimating cancer rates in non-census defined geographical areas

Challenges faced with the implementation of Web-Based Data Query Systems for population health: development of a questionnaire based on expert consensus

The Potential Use of Multi-agent and Hybrid Data Mining Approaches in Social Informatics for Improving e-Health Services

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