Literature DB >> 9127973

Composition of the home care service package: predictors of type, volume, and mix of services provided to poor and frail older people.

S Diwan1, C Berger, E K Manns.   

Abstract

This study of 270 poor and frail elders in a Medicaid waiver program examined the service package, that is, the type of service (health or social), volume, and the mix or combinations of services provided. Predictors of use and volume of service differed depending on type of service. The most frequently prescribed service combinations were: (a) nursing, home health, and homemaker; (b) homemaker only; (c) nursing and home health; (d) nursing and homemaker; and (e) nurse only. Across the service combinations, living alone increased the odds of receiving social services such as a homemaker, whereas declining primary ADL function increased the odds of receiving health services such as a home health aide.

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Year:  1997        PMID: 9127973     DOI: 10.1093/geront/37.2.169

Source DB:  PubMed          Journal:  Gerontologist        ISSN: 0016-9013


  5 in total

Review 1.  Transitions between care provisions demanded by Dutch elderly.

Authors:  Edwin Van Gameren; Isolde Woittiez
Journal:  Health Care Manag Sci       Date:  2005-11

2.  Nurse Generated EHR Data Supports Post-Acute Care Referral Decision Making: Development and Validation of a Two-step Algorithm.

Authors:  Kathryn H Bowles; Sarah J Ratcliffe; Mary D Naylor; John H Holmes; Susan K Keim; Emilia J Flores
Journal:  AMIA Annu Symp Proc       Date:  2018-04-16

3.  Home-care clients' need for help, and use and costs of services.

Authors:  Teija Hammar; Pekka Rissanen; Marja-Leena Perälä
Journal:  Eur J Ageing       Date:  2008-05-21

4.  Factors identified by experts to support decision making for post acute referral.

Authors:  Kathryn H Bowles; John H Holmes; Sarah J Ratcliffe; Matthew Liberatore; Robert Nydick; Mary D Naylor
Journal:  Nurs Res       Date:  2009 Mar-Apr       Impact factor: 2.381

5.  Combinations of long-term care insurance services and associated factors in Japan: a classification tree model.

Authors:  Ayumi Igarashi; Tomoaki Ishibashi; Tomohiro Shinozaki; Noriko Yamamoto-Mitani
Journal:  BMC Health Serv Res       Date:  2014-09-10       Impact factor: 2.655

  5 in total

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