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Identification of older hospitalised patients at risk for functional decline, a study to compare the predictive values of three screening instruments

Authors

  • Jita G Hoogerduijn,

    1. Authors:Jita G Hoogerduijn, MScN, RN, PhD Candidate, Research Group Care for the Chronically Ill, Faculty of Health Care, Hogeschool Utrecht, University of Applied Science; Marieke J Schuurmans, PhD, RN, Professor, Research Group Care for the Chronically Ill, Faculty of Health Care, Hogeschool Utrecht, University of Applied Science, Utrecht, The Netherlands; Johanna C Korevaar, PhD, Senior Epidemiologist, Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre; Bianca M Buurman, MScN, RN, PhD Candidate, Department of Internal Medicine and Geriatrics, Academic Medical Centre; Sophia E de Rooij, PhD, MD, Associate Professor, Department of Internal Medicine and Geriatrics, Academic Medical Centre, Amsterdam, The Netherlands
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  • Marieke J Schuurmans,

    1. Authors:Jita G Hoogerduijn, MScN, RN, PhD Candidate, Research Group Care for the Chronically Ill, Faculty of Health Care, Hogeschool Utrecht, University of Applied Science; Marieke J Schuurmans, PhD, RN, Professor, Research Group Care for the Chronically Ill, Faculty of Health Care, Hogeschool Utrecht, University of Applied Science, Utrecht, The Netherlands; Johanna C Korevaar, PhD, Senior Epidemiologist, Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre; Bianca M Buurman, MScN, RN, PhD Candidate, Department of Internal Medicine and Geriatrics, Academic Medical Centre; Sophia E de Rooij, PhD, MD, Associate Professor, Department of Internal Medicine and Geriatrics, Academic Medical Centre, Amsterdam, The Netherlands
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  • Johanna C Korevaar,

    1. Authors:Jita G Hoogerduijn, MScN, RN, PhD Candidate, Research Group Care for the Chronically Ill, Faculty of Health Care, Hogeschool Utrecht, University of Applied Science; Marieke J Schuurmans, PhD, RN, Professor, Research Group Care for the Chronically Ill, Faculty of Health Care, Hogeschool Utrecht, University of Applied Science, Utrecht, The Netherlands; Johanna C Korevaar, PhD, Senior Epidemiologist, Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre; Bianca M Buurman, MScN, RN, PhD Candidate, Department of Internal Medicine and Geriatrics, Academic Medical Centre; Sophia E de Rooij, PhD, MD, Associate Professor, Department of Internal Medicine and Geriatrics, Academic Medical Centre, Amsterdam, The Netherlands
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  • Bianca M Buurman,

    1. Authors:Jita G Hoogerduijn, MScN, RN, PhD Candidate, Research Group Care for the Chronically Ill, Faculty of Health Care, Hogeschool Utrecht, University of Applied Science; Marieke J Schuurmans, PhD, RN, Professor, Research Group Care for the Chronically Ill, Faculty of Health Care, Hogeschool Utrecht, University of Applied Science, Utrecht, The Netherlands; Johanna C Korevaar, PhD, Senior Epidemiologist, Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre; Bianca M Buurman, MScN, RN, PhD Candidate, Department of Internal Medicine and Geriatrics, Academic Medical Centre; Sophia E de Rooij, PhD, MD, Associate Professor, Department of Internal Medicine and Geriatrics, Academic Medical Centre, Amsterdam, The Netherlands
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  • Sophia E De Rooij

    1. Authors:Jita G Hoogerduijn, MScN, RN, PhD Candidate, Research Group Care for the Chronically Ill, Faculty of Health Care, Hogeschool Utrecht, University of Applied Science; Marieke J Schuurmans, PhD, RN, Professor, Research Group Care for the Chronically Ill, Faculty of Health Care, Hogeschool Utrecht, University of Applied Science, Utrecht, The Netherlands; Johanna C Korevaar, PhD, Senior Epidemiologist, Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre; Bianca M Buurman, MScN, RN, PhD Candidate, Department of Internal Medicine and Geriatrics, Academic Medical Centre; Sophia E de Rooij, PhD, MD, Associate Professor, Department of Internal Medicine and Geriatrics, Academic Medical Centre, Amsterdam, The Netherlands
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Jita G Hoogerduijn, PhD Candidate, Hogeschool Utrecht, Bolognalaan 101, 3584 CJ Utrecht, The Netherlands. Telephone: +(31) 30 258 52 01.
E-mail:Jita.hoogerduijn@hu.nl

Abstract

Aims and objectives.  To establish a screening instrument for identifying older hospitalised patients at risk for functional decline by comparing the predictive values of three screening instruments: identification of seniors at risk, care complexity prediction instrument and hospital admission risk profile.

Background.  After being hospitalised, 30–60% of older patients experience a decline in functioning, resulting in a decreased quality of life and autonomy.

Design.  A prospective cohort study.

Methods.  Included were patients, aged 65 years and older, acutely admitted to a general internal ward of a university teaching hospital. Within 48 hours after hospital admission, baseline data were completed – demographic, cognitive, social and pre-admission functional status and the screening instruments. Three months after discharge, functional status was measured by telephone interview. The Katz index was used to measure functional status (six activities). Functional decline was defined as a decline of at least one point on the Katz index at three months after discharge compared to pre-admission state.

Results.  Included were 177 patients; mean age was 77·6 years and 51·7 % were male. Functional decline was found in 27·8% of all patients. Sensitivity, specificity and area under receiver operating curve for identification of seniors at risk (ISAR) were 93, 39% and 0·67, respectively. The corresponding results for the care complexity prediction instrument (COMPRI) were 70, 62% and 0·69 and for the hospital admission risk profile (HARP) 21, 89% and 0·56.

Conclusion.  The discriminative values of both identification of seniors at risk and care complexity prediction instrument are fair. Hospital admission risk profile shows the poorest results. Identification of seniors at risk shows the best ability to predict those patients at risk for functional decline and seems to be the easiest instrument in clinical practice.

Relevance to clinical practice.  Identifying patients at risk for functional decline is a first step in prevention, followed by geriatric assessment and targeted interventions. Studying the validity of existing instruments is necessary before implementation in clinical practice.

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