Literature DB >> 3100881

Nursing home case mix. Patient classification by nursing resource use.

G Arling, R H Nordquist, B A Brant, J A Capitman.   

Abstract

A model is presented for classifying nursing home patients according to nursing resource use. The model is derived from a study of 558 Medicaid nursing home patients in 12 facilities in Virginia. Data were obtained from self-reports of nursing staff for care delivered over a 52-hour period. The measure of care time was validated through concurrent work sampling. Project staff also assessed the patients' health and functional status using a standardized instrument. Using AID analysis patients were classified into six groups that were homogeneous in their use of nursing resources. Patients were initially categorized by presence or absence of conditions requiring specialized care (e.g., nutritional intake problems, quadriplegia, wounds or lesions, coma, and physical rehabilitation potential). For the specialized care category, two groups were formed by presence or absence of a catheter/ostomy. In the nonspecialized care category, four groups were formed by ADL impairment score and assistance required in eating/feeding. Mean resource use for the highest group was nearly four times that of the lowest group. The model accounted for 53% of the variance in nursing resource use.

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Year:  1987        PMID: 3100881     DOI: 10.1097/00005650-198701000-00002

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  10 in total

1.  Does investor ownership of nursing homes compromise the quality of care?

Authors:  C Harrington; S Woolhandler; J Mullan; H Carrillo; D U Himmelstein
Journal:  Am J Public Health       Date:  2001-09       Impact factor: 9.308

2.  Nursing home cost and ownership type: evidence of interaction effects.

Authors:  G Arling; R H Nordquist; J A Capitman
Journal:  Health Serv Res       Date:  1987-06       Impact factor: 3.402

3.  Functional disability and nursing resource use are predictive of antimicrobial resistance in nursing homes.

Authors:  Lillian Min; Andrzej Galecki; Lona Mody
Journal:  J Am Geriatr Soc       Date:  2015-04-08       Impact factor: 5.562

4.  Reducing the use of physical restraints in nursing homes: will it increase costs?

Authors:  C D Phillips; C Hawes; B E Fries
Journal:  Am J Public Health       Date:  1993-03       Impact factor: 9.308

5.  Incorporating Quality into Data Envelopment Analysis of Nursing Home Performance: A Case Study.

Authors:  Daniel G Shimshak; Melanie L Lenard; Ronald K Klimberg
Journal:  Omega       Date:  2009-06-01       Impact factor: 7.084

6.  Patterns of change in functional status in extended care.

Authors:  J E Rohrer; C Yesalis; P R Laughlin; R Wiley
Journal:  Health Serv Res       Date:  1988-10       Impact factor: 3.402

Review 7.  Activities of daily living and costs in nursing homes.

Authors:  B C Williams; B E Fries; W J Foley; D Schneider; M Gavazzi
Journal:  Health Care Financ Rev       Date:  1994

8.  Nursing home resident assessment and case-mix classification: cross-national perspectives.

Authors:  S B Clauser; B E Fries
Journal:  Health Care Financ Rev       Date:  1992

9.  Comparing case-mix systems for nursing home payment.

Authors:  B E Fries
Journal:  Health Care Financ Rev       Date:  1990

10.  Case mix for nursing home payment: resource utilization groups, version II.

Authors:  D P Schneider; B E Fries; W J Foley; M Desmond; W J Gormley
Journal:  Health Care Financ Rev       Date:  1988-12
  10 in total

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