Literature DB >> 11890500

Establishing a case-finding and referral system for at-risk older individuals in the emergency department setting: the SIGNET model.

L C Mion1, R M Palmer, G J Anetzberger, S W Meldon.   

Abstract

Older emergency department (ED) patients have complex medical, social, and physical problems. We established a program at four ED sites to improve case finding of at-risk older adults and provide comprehensive assessment in the ED setting with formal linkage to community agencies. The objectives of the program are to (1) improve case finding of at-risk older ED patients, (2) improve care planning and referral for those returning home, and (3) create a coordinated network of existing medical and community services. The four sites are a 1,000-bed teaching center, a 700-bed county teaching hospital, a 400-bed community hospital, and a health maintenance organization (HMO) ED site. Ten community agencies also participated in the study: four agencies associated with the hospital/HMO sites, two nonprofit private agencies, and four public agencies. Case finding is done using a simple screening assessment completed by the primary or triage nurse. A geriatric clinical nurse specialist (GCNS) further assesses those considered at risk. Patients with unmet medical, social, or health needs are referred to their primary physicians or to outpatient geriatric evaluation and management centers and to community agencies. After 18 months, the program has been successfully implemented at all four sites. Primary nurses screened over 70% (n = 28,437) of all older ED patients, GCNSs conducted 3,757 comprehensive assessments, participating agency referrals increased sixfold, and few patients refused the GCNS assessment or subsequent referral services. Thus, case finding and community linkage programs for at-risk older adults are feasible in the ED setting.

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Year:  2001        PMID: 11890500     DOI: 10.1046/j.1532-5415.2001.49270.x

Source DB:  PubMed          Journal:  J Am Geriatr Soc        ISSN: 0002-8614            Impact factor:   5.562


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