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Increasing Registered Nurse Hours Per Resident Day for Improved Nursing Home Residents’ Outcomes Using a Longitudinal Study

Author

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  • Juh Hyun Shin

    (College of Nursing, Ewha Womans University, Seoul 03760, Korea)

  • Rosemary Anne Renaut

    (School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ 85281, USA)

  • Mark Reiser

    (School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ 85281, USA)

  • Ji Yeon Lee

    (College of Nursing, Ewha Womans University, Seoul 03760, Korea)

  • Ty Yi Tang

    (Department of Psychology, Arizona State University, Tempe, AZ 85281, USA)

Abstract

The purpose of this study was to estimate how much resident outcomes can improve with an increase in hours per resident day (HPRD) of registered nurses (RNs) staffing. Nursing home (NH) staff in Korea have serious problems with inappropriate nurse staffing standards and poor working conditions, which lead to poor quality of care for NH residents. This study used a longitudinal survey design. A quota sampling was used with a total of several repeated survey measurement from 2017 to 2020 ( n = 74). The independent variable was the amount of nurse staffing HPRD and the outcome variable was the compiled outcome of 15 quality-of-care indicators. Data were directly collected from all participating NHs. A longitudinal, multilevel model was used for analysis. An increase of one unit of RN HPRD (60 min) corresponded to a decrease of about 10.5% of residents with deteriorated quality of care outcomes. This study emphasized that increasing RN HPRD decreased residents’ deteriorated outcomes in NHs. This suggests that professional RNs must be secured to an appropriate level to improve the quality of care for NH residents.

Suggested Citation

  • Juh Hyun Shin & Rosemary Anne Renaut & Mark Reiser & Ji Yeon Lee & Ty Yi Tang, 2021. "Increasing Registered Nurse Hours Per Resident Day for Improved Nursing Home Residents’ Outcomes Using a Longitudinal Study," IJERPH, MDPI, vol. 18(2), pages 1-11, January.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:2:p:402-:d:475896
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    References listed on IDEAS

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    1. Haizhen Lin, 2014. "Revisiting the relationship between nurse staffing and quality of care in nursing homes: An instrumental variables approach," Working Papers 2014-01, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy.
    2. Ying Liu & Fang Luo & Danhui Zhang & Hongyun Liu, 2017. "Comparison and robustness of the REML, ML, MIVQUE estimators for multi-level random mediation model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(9), pages 1644-1661, July.
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    Cited by:

    1. Soo-Kyoung Lee & Juh Hyun Shin & Jinhyun Ahn & Ji Yeon Lee & Dong Eun Jang, 2021. "Identifying the Risk Factors Associated with Nursing Home Residents’ Pressure Ulcers Using Machine Learning Methods," IJERPH, MDPI, vol. 18(6), pages 1-8, March.
    2. Ryuichi Ohta & Yoshinori Ryu & Chiaki Sano, 2021. "Effects of Implementation of Infection Control Measures against COVID-19 on the Condition of Japanese Rural Nursing Homes," IJERPH, MDPI, vol. 18(11), pages 1-9, May.

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    Keywords

    NHs; workforce; nurses;
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