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ArtikelThe Influence of Institutional Characteristics on Length of Stay for Psychiatric Patients: A National Database Study in South Korea  
Oleh: Chung, Woojin ; Cho, Woo Hyun ; Yoon, Chung Won
Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Social Science & Medicine (www.elsevier.com/locate/sosscimed) vol. 68 no. 6 (Mar. 2009), page 1137-1144.
Topik: South Korea; Length of stay; Psychiatric care; Hospital characteristics; Institutions
Ketersediaan
  • Perpustakaan Pusat (Semanggi)
    • Nomor Panggil: SS53
    • Non-tandon: 1 (dapat dipinjam: 0)
    • Tandon: tidak ada
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Isi artikelThe institutionalization of psychiatric patients has put a tremendous burden on many societies, but few studies have examined the effects of institutional characteristics on patient length of stay (LOS). This paper investigated the association between institutional characteristics and LOS for 160,517 psychiatric patients in South Korea by applying a two-level modeling technique to administrative claims databases covering the entire patient population. Patient LOS, expressed in terms of days, was analyzed by taking account of institutional type, ownership, location, inpatient capacity, staffing, and patient demographics. The characteristics of inpatients were used as control variables and consisted of gender, age, sub-diagnosis, and the type of national health security program. The main findings of this study are: (1) patient LOS was 69% longer at psychiatric hospitals than at tertiary-care hospitals; (2) neither location nor inpatient capacity was associated with LOS; (3) larger staffs reduced LOS; and (4), LOS increased with a higher proportion of male inpatients, inpatients =65 years old, or inpatients diagnosed with organic or schizophrenic disorders, possibly through contextual effects. The results of this study suggest that researchers and policy makers could improve their assessment of psychiatric patient LOS and its association with health outcome by taking into account institutional characteristics and using multi-level analyses.
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