A Community Health Initiative: Evaluation and Early Lessons Learned

Author(s):  
Michael C. Gibbons ◽  
Samantha L. Illangasekare ◽  
Earnest Smith ◽  
Joan Kub
2012 ◽  
Vol 27 (2) ◽  
pp. e59-e68 ◽  
Author(s):  
Allen Cheadle ◽  
Suzanne Rauzon ◽  
Rebecca Spring ◽  
Pamela M. Schwartz ◽  
Scott Gee ◽  
...  

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
C Schluefter ◽  
M Albrecht ◽  
J E Fischer ◽  
S Georg ◽  
K Hoffmann

Abstract As the WHO-Health-in-all-Policies-concept suggests many of the health-related aspects of the social, physical and economic environments can be modified within the community setting. In reality, developing and implementing population-based health initiatives is often challenging for both communities and researchers. To guide future efforts of community health initiatives, we systematically analyzed challenges we encountered and the lessons learned. We systematically reviewed daily logbooks, meeting minutes and press releases about the initiative to identify successes, unexpected challenges and barriers in its implementation. Comments from two reflective workshops held in the partner community identified additional areas of knowledge. Retrospective content analysis of these sources uncovered emerging process-related themes. Success was evident in a high degree of citizen participation in initiative-related forums. Challenges included a greater need to a) develop a common vision before starting initiative activities, b) establish an effective collaboration between community residents and our team, c) create more transparent lines of communication, foster trust and better manage community expectations. Establishing a project office in the community for regular updates, trust building and partnering with a professional communication agency were key steps that helped turn some challenges into successes. Barriers identified were missing resources both within the community and our team, a limited time period and limited possibilities of reach into all systems within the community (e.g. kindergartens). The use of the method of retrospective process analysis helped to uncover detailed insights into the operational implementation process of a community health initiative. These insights serve as a transfer of practical knowledge, which intends to enable researchers and practioneers within communities to plan and conduct their community health initiatives to large success. Key messages Analyzing the process of health initiatives retrospectively uncovers detailed insights into implementation processes and helps to understand successes, challenges and barriers of the initiative. Insights into the implementation process of health initiatives function as guidance to other researchers and practioneers to support future efforts in the field of community health.


PLoS ONE ◽  
2020 ◽  
Vol 15 (5) ◽  
pp. e0232239
Author(s):  
Candyce H. Kroenke ◽  
Gem M. Le ◽  
Shannon M. Conroy ◽  
Alison J. Canchola ◽  
Salma Shariff-Marco ◽  
...  

2009 ◽  
Vol 11 (3) ◽  
pp. 332-339 ◽  
Author(s):  
Leila Kramer ◽  
Pamela Schwartz ◽  
Allen Cheadle ◽  
J. Elaine Borton ◽  
Merrick Wright ◽  
...  

2021 ◽  
Author(s):  
Ruth Dolly Johnson ◽  
Yi Ding ◽  
Vidhya Venkateswaran ◽  
Arjun Bhattacharya ◽  
Alec Chiu ◽  
...  

Large medical centers located in urban areas such as Los Angeles care for a diverse patient population and offer the potential to study the interplay between genomic ancestry and social determinants of health within a single medical system. Here, we introduce the UCLA ATLAS Community Health Initiative-- a biobank of genomic data linked with de-identified electronic health records (EHRs) of UCLA Health patients. We leverage the unique genomic diversity of the patient population in ATLAS to explore the interplay between self-reported race/ethnicity and genetic ancestry within a disease context using phenotypes extracted from the EHR. First, we identify an extensive amount of continental and subcontinental genomic diversity within the ATLAS data that is consistent with the global diversity of Los Angeles; this includes clusters of ATLAS individuals corresponding to individuals with Korean, Japanese, Filipino, and Middle Eastern genomic ancestries. Most importantly, we find that common diseases and traits stratify across genomic ancestry clusters, thus suggesting their utility in understanding disease biology across diverse individuals. Next, we showcase the power of genetic data linked with EHR to perform ancestry-specific genome and phenome-wide scans to identify genetic factors for a variety of EHR-derived phenotypes (phecodes). For example, we find ancestry-specific associations for liver disease, and link the genetic variants with neurological and neoplastic phenotypes primarily within individuals of admixed ancestries. Overall, our results underscore the utility of studying the genomes of diverse individuals through biobank-scale genotyping efforts linked with EHR-based phenotyping.


2007 ◽  
Vol 55 (1) ◽  
pp. S118
Author(s):  
H. Budden ◽  
S. K. Yeong ◽  
L. Taylor ◽  
P. Kretz ◽  
L. Parfitt ◽  
...  

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