Dataset Information

Penn Center for Community Health Workers: Step-by-Step Approach to Sustain an Evidence-Based Community Health Worker Intervention at an Academic Medical Center.

ABSTRACT: Community-engaged researchers who work with low-income communities can be reliant on grant funding. We use the illustrative case of the Penn Center for Community Health Workers (PCCHW) to describe a step-by-step framework for achieving financial sustainability for community-engaged research interventions. PCCHW began as a small grant-funded research project but followed an 8-step framework to engage both low-income patients and funders, determine outcomes, and calculate return on investment. PCCHW is now fully funded by Penn Medicine and delivers the Individualized Management for Patient-Centered Targets (IMPaCT) community health worker intervention to 2000 patients annually.

SUBMITTER: Morgan AU

PROVIDER: S-EPMC5055768 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Penn Center for Community Health Workers: Step-by-Step Approach to Sustain an Evidence-Based Community Health Worker Intervention at an Academic Medical Center.

Morgan Anna U AU Grande David T DT Carter Tamala T Long Judith A JA Kangovi Shreya S

American journal of public health 20160915 11

Community-engaged researchers who work with low-income communities can be reliant on grant funding. We use the illustrative case of the Penn Center for Community Health Workers (PCCHW) to describe a step-by-step framework for achieving financial sustainability for community-engaged research interventions. PCCHW began as a small grant-funded research project but followed an 8-step framework to engage both low-income patients and funders, determine outcomes, and calculate return on investment. PCC ...[more]

PMID: 27631747

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Project description:ObjectiveTo synthesize current understanding of how community-based health worker (CHW) programs can best be designed and operated in health systems.MethodsWe searched 11 databases for review articles published between 1 January 2005 and 15 June 2017. Review articles on CHWs, defined as non-professional paid or volunteer health workers based in communities, with less than 2 years of training, were included. We assessed the methodological quality of the reviews according to AMSTAR criteria, and we report our findings based on PRISMA standards.FindingsWe identified 122 reviews (75 systematic reviews, of which 34 are meta-analyses, and 47 non-systematic reviews). Eighty-three of the included reviews were from low- and middle-income countries, 29 were from high-income countries, and 10 were global. CHW programs included in these reviews are diverse in interventions provided, selection and training of CHWs, supervision, remuneration, and integration into the health system. Features that enable positive CHW program outcomes include community embeddedness (whereby community members have a sense of ownership of the program and positive relationships with the CHW), supportive supervision, continuous education, and adequate logistical support and supplies. Effective integration of CHW programs into health systems can bolster program sustainability and credibility, clarify CHW roles, and foster collaboration between CHWs and higher-level health system actors. We found gaps in the review evidence, including on the rights and needs of CHWs, on effective approaches to training and supervision, on CHWs as community change agents, and on the influence of health system decentralization, social accountability, and governance.ConclusionEvidence concerning CHW program effectiveness can help policymakers identify a range of options to consider. However, this evidence needs to be contextualized and adapted in different contexts to inform policy and practice. Advancing the evidence base with context-specific elements will be vital to helping these programs achieve their full potential.

Project description:BACKGROUND:Electronic medical records (EMRs) contain a wealth of information that can support data-driven decision making in health care policy design and service planning. Although research using EMRs has become increasingly prevalent, challenges such as coding inconsistency, data validity, and lack of suitable measures in important domains still hinder the progress. OBJECTIVE:The objective of this study was to design a structured way to process records in administrative EMR systems for health services research and assess validity in selected areas. METHODS:On the basis of a local hospital EMR system in Singapore, we developed a structured framework for EMR data processing, including standardization and phenotyping of diagnosis codes, construction of cohort with multilevel views, and generation of variables and proxy measures to supplement primary data. Disease complexity was estimated by Charlson Comorbidity Index (CCI) and Polypharmacy Score (PPS), whereas socioeconomic status (SES) was estimated by housing type. Validity of modified diagnosis codes and derived measures were investigated. RESULTS:Visit-level (N=7,778,761) and patient-level records (n=549,109) were generated. The International Classification of Diseases, Tenth Revision, Australian Modification (ICD-10-AM) codes were standardized to the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) with a mapping rate of 87.1%. In all, 97.4% of the ICD-9-CM codes were phenotyped successfully using Clinical Classification Software by Agency for Healthcare Research and Quality. Diagnosis codes that underwent modification (truncation or zero addition) in standardization and phenotyping procedures had the modification validated by physicians, with validity rates of more than 90%. Disease complexity measures (CCI and PPS) and SES were found to be valid and robust after a correlation analysis and a multivariate regression analysis. CCI and PPS were correlated with each other and positively correlated with health care utilization measures. Larger housing type was associated with lower government subsidies received, suggesting association with higher SES. Profile of constructed cohorts showed differences in disease prevalence, disease complexity, and health care utilization in those aged above 65 years and those aged 65 years or younger. CONCLUSIONS:The framework proposed in this study would be useful for other researchers working with EMR data for health services research. Further analyses would be needed to better understand differences observed in the cohorts.

Dataset Information

Penn Center for Community Health Workers: Step-by-Step Approach to Sustain an Evidence-Based Community Health Worker Intervention at an Academic Medical Center.

Publications

Penn Center for Community Health Workers: Step-by-Step Approach to Sustain an Evidence-Based Community Health Worker Intervention at an Academic Medical Center.

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