Population Health Improvement: A Community Health Business Model That Engages Partners in All Sectors

2014 ◽  
Vol 30 (4) ◽  
pp. 3-20 ◽  
Author(s):  
David A. Kindig ◽  
George Isham
Keyword(s):  
Community Health ◽  
Population Health ◽  
Business Model ◽  
Health Improvement

Community Health Needs Assessment: Potential for Population Health Improvement

2016 ◽  
Vol 19 (3) ◽  
pp. 178-186 ◽  
Author(s):  
Cara L. Pennel ◽  
Kenneth R. McLeroy ◽  
James N. Burdine ◽  
David Matarrita-Cascante ◽  
Jia Wang
Keyword(s):  
Needs Assessment ◽  
Community Health ◽  
Population Health ◽  
Health Needs ◽  
Health Improvement ◽  
Health Needs Assessment ◽  
Community Health Needs Assessment

Community Health Improvement Plans

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Leslie D. Carroll ◽  
Marianna S. Wetherill ◽  
Thomas A. Teasdale ◽  
Alicia L. Salvatore
Keyword(s):  
Community Health ◽  
Health Improvement ◽  
Community Health Improvement

scholarly journals The Role of Social Marketing in Community Health Improvement: A Mixed Approach

2021 ◽  
Author(s):  
Ameneh Rezazadeh ◽  
Majid Fattahi ◽  
Rahman Ghaffari
Keyword(s):  
Community Health ◽  
Social Marketing ◽  
Structural Equation ◽  
World Health ◽  
Equation Modeling ◽  
Health Improvement ◽  
Mazandaran Province ◽  
Statistical Population ◽  
Normative System

Background and Purpose: Social marketing (SM) is a fitting strategy in world health that is aimed to ensure attitude correction in the community, laying the foundation for the behavioral changes resulting in health promotion in the community. The purpose of this research was to explain the role of social marketing in promoting community health. Methods: This was applied research conducted through a descriptive survey. For data gathering, a mixed quantitative/qualitative approach was adopted. The statistical population included the youth under 25 years old who smoked cigarettes in Mazandaran Province. Based on the Cochran formula, a sample consisting of 385 respondents was formed, and the individual members of it were selected using proportionate random sampling. The data on social marketing mix and normative system were collected using the questionnaires constructed by Pang and Kubacki [1] and Issock et al. [2], respectively. The data on advertisement were collected using the questionnaire constructed by Dunn and Nisbett [3]. Data analysis was performed in PLS Software using Structural Equation Modeling. Result: The result indicated that the messenger’s features influenced the user perception of social marketing and had a positive effect on the user normative system. Further, the results suggested that the user normative system affected their perception of social marketing. Conclusion: It was concluded that marketing practitioners can manipulate consumer perception of social marketing by shaping ethical norms.

Overview—Sustainability and Finance: Supporting Partnerships over Time

2019 ◽  
pp. 325-328
Author(s):  
Craig W. Thomas ◽  
Brian C. Castrucci
Keyword(s):  
Health Care ◽  
Health Disparities ◽  
Population Health ◽  
Health Care Services ◽  
Health Improvement ◽  
Care Services ◽  
Financial Investments ◽  
Closing The Gap ◽  
The Individual ◽  
Over Time

This chapter introduces the next section of the book which is about sustainability and finance when it comes to cross-sector collaboratives for population health improvements. It states that the focus should be on closing the gap when it comes to health disparities and a goal needs to be reducing the need for health care services. Effectively acquiring, managing, and sustaining financial investments in health is fundamental to the success of multi-sector and community-led health improvement initiatives. The chapter outlines the topics covered by the individual chapters in this section.

The Role of Primary Care in Population and Community Health: Pragmatic Approaches to Integration

2019 ◽  
pp. 101-108
Author(s):  
Julie Wood ◽  
Kevin Grumbach
Keyword(s):  
Primary Care ◽  
Community Health ◽  
Population Health ◽  
Health Management ◽  
Parks And Recreation ◽  
Centered Care ◽  
Care Models ◽  
Primary Care Clinicians ◽  
Family Centered

This chapter looks at the role of primary health care in community health. Primary care, it argues, has built on its historical roots of holistic family-centered care to embrace the broader concept of population health. The chapter looks at the evolution of care models from patient/family-centered to panel management (the sum of patients being cared for by a primary care practice), to community health management. This broader concept of health necessitates collaboration with partners outside the clinical practice, including public health professionals, policymakers, schools, housing, parks and recreation, law enforcement, transportation, and food systems. The chapter describes the population and community framework and its historical role in the development of primary care, and then turns to the proposal of pragmatic approaches that busy primary care clinicians and care teams can use to integrate population health approaches into their practices.

Priorities for Investing in Community Health Improvement

2019 ◽  
Vol 25 (4) ◽  
pp. 322-331 ◽  
Author(s):  
Michael D. Rozier ◽  
Simone R. Singh ◽  
Peter D. Jacobson ◽  
Lisa A. Prosser
Keyword(s):  
Community Health ◽  
Health Improvement ◽  
Community Health Improvement

DSRIP’s innovation and collaboration in population health management: A cross-sectional segmented time series model

2019 ◽  
Vol 33 (1) ◽  
pp. 2-12
Author(s):  
Amrita Gopinath Shenoy
Keyword(s):  
Time Series ◽  
Population Health ◽  
Development Program ◽  
Hospitalization Rate ◽  
Health Improvement ◽  
Infrastructure Development ◽  
Cross Sectional ◽  
Preventable Hospitalization ◽  
Hospitalization Rates ◽  
The Impact

Texas Medicaid Section 1115 waiver approved Delivery System Reform Incentive Payment (DSRIP) program has four categories, namely infrastructure development, program innovation and redesign, reporting of quality improvement outcomes, and population health improvement. A metric of the fourth category, preventable hospitalization rate, was analyzed for a set of eight diagnostic conditions to assess the impact of DSRIP on participating- and non-participating hospitals over two time periods, pre-DSRIP and post-DSRIP, with the help of a cross-sectional segmented time series regression model. Texas Healthcare Information Collection database was leveraged to obtain preventable hospitalization rate data. The dependent variables were preventable hospitalization rates of eight program-specified conditions and the independent variables were time, intervention, and post-implementation intervention. The overall combined preventable hospitalization rate for DSRIP hospitals was observed to decrease by 25.73%, whereas the overall combined preventable hospitalization rate for non-DSRIP hospitals was observed to increase by 37.57%. DSRIP hospitals had invested in coordinating healthcare projects and were subsequently reimbursed by the state for healthcare improvements. The implementation of DSRIP may have had the capacity to decrease preventable hospitalization rates in regions wherein its adoption may have improved the health of the population.

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