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BMJ Open. 2019 Nov 27;9(11):e030017. doi: 10.1136/bmjopen-2019-030017.

Associations between community well-being and hospitalisation rates: results from a cross-sectional study within six US states.

Author information

1
Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA brita.roy@yale.edu.
2
Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
3
Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA.
4
Center for Outcomes Research and Evaluation, Yale-New Haven Health, New Haven, Connecticut, USA.
5
Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
6
Sharecare Inc, Atlanta, Georgia, USA.
7
Tivity Health, Nashville, Tennessee, USA.
8
Tivity Health, Franklin, Tennessee, USA.
9
Health Policy and Management, Yale School of Public Health, New Haven, Connecticut, USA.

Abstract

OBJECTIVE:

To evaluate the association between community well-being, a positively framed, multidimensional assessment of the health and quality of life of a geographic community, and hospitalisation rates.

DESIGN:

Cross-sectional study SETTING: Zip codes within six US states (Florida, Iowa, Nebraska, New York, Pennsylvania and Utah) MAIN OUTCOME MEASURES: Our primary outcome was age-adjusted, all-cause hospitalisation rates in 2010; secondary outcomes included potentially preventable disease-specific hospitalisation rates, including cardiovascular-related, respiratory-related and cancer-related admissions. Our main independent variable was the Gallup-Sharecare Well-Being Index (WBI) and its domains (life evaluation, emotional health, work environment, physical health, healthy behaviours and basic access).

RESULTS:

Zip codes with the highest quintile of well-being had 223 fewer hospitalisations per 100 000 (100k) residents than zip codes with the lowest well-being. In our final model, adjusted for WBI respondent age, sex, race/ethnicity and income, and zip code number of hospital beds, primary care physician density, hospital density and admission rates for two low-variation conditions, a 1 SD increase in WBI was associated with 5 fewer admissions/100k (95% CI 4.0 to 5.8; p<0.001). Results were similar for cardiovascular-related and respiratory-related admissions, but no association remained for cancer-related hospitalisation after adjustment. Patterns were similar for each of the WBI domains and all-cause hospitalisations.

CONCLUSION AND RELEVANCE:

Community well-being is inversely associated with local hospitalisation rates. In addition to health and quality-of-life benefits, higher community well-being may also result in fewer unnecessary hospitalisations.

KEYWORDS:

community health; healthcare utilisation; hospitalisation rates; population health; preventive medicine; well-being

PMID:
31780588
DOI:
10.1136/bmjopen-2019-030017
Free PMC Article

Conflict of interest statement

Competing interests: Partial support from the Agency for Healthcare Research and Quality (BR and ES), the Robert Wood Johnson Foundation (CR and BR) and the Veterans Administration (BR) for the submitted work. CR and BR receive funding from the Institute for Healthcare Improvement to support their effort in developing and implementing the measurement framework for the 100 Million Healthier Lives initiative. BH, EYR and KPK are current or former employees and shareholders of the Healthways corporation (acquired by Sharecare), the company that developed the measure of well-being used in this article. ES, JH and HK also report receiving support from the Centers for Medicare and Medicaid Services. HK is a recipient of research agreements from Medtronic and Johnson & Johnson (Janssen), through Yale, to develop methods of clinical trial data sharing; is the recipient of a grant from Medtronic and the Food and Drug Administration, through Yale, to develop methods for postmarket surveillance of medical devices; works under contract with the Centers for Medicare and Medicaid Services to develop and maintain performance measures; chairs a cardiac scientific advisory board for UnitedHealth; is a participant/participant representative of the IBM Watson Health Life Sciences Board; is a member of the advisory board for Element Science and the physician advisory board for Aetna; and is the founder of Hugo, a personal health information platform.

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