Literature DB >> 7649461

Prediction of length of stay in an inpatient dual diagnosis unit.

R D Serota1, A Lundy, E Gottheil, S P Weinstein, R C Sterling.   

Abstract

The institution of prospective payment systems, in which flat fees are paid per discharge, raised the concern that hospitals might preferentially admit patients expected to have a short length of stay (LOS). This concern presupposes that intake workers could accurately predict psychiatric hospitalization LOS, but this does not appear to have been empirically demonstrated. Accordingly, we examined the ability of two psychiatrists heading separate treatment teams on an inpatient, dual-diagnosis unit and a program coordinator who worked with both teams to predict LOS for 94 patients consecutively admitted to one or the other of these teams. Predictions were highly consistent across the raters and were significantly correlated with actual LOS (r = 0.25, 0.35, and 0.45 for the three raters). However, we found that the psychiatrists were accurate predictors only for patients for whom they were the attending psychiatrist. The program coordinator, who was involved in the treatment of all patients, was an accurate predictor for the patients of either psychiatrist. We concluded that the relationships found between predicted and actual LOS held true only when the rater also influenced treatment management and discharge. Our results do not support the proposition that specialized intake workers independent of those providing care would be able to predict LOS accurately.

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Year:  1995        PMID: 7649461     DOI: 10.1016/0163-8343(95)00024-l

Source DB:  PubMed          Journal:  Gen Hosp Psychiatry        ISSN: 0163-8343            Impact factor:   3.238


  1 in total

1.  Length of Hospital Stay Prediction at the Admission Stage for Cardiology Patients Using Artificial Neural Network.

Authors:  Pei-Fang Jennifer Tsai; Po-Chia Chen; Yen-You Chen; Hao-Yuan Song; Hsiu-Mei Lin; Fu-Man Lin; Qiou-Pieng Huang
Journal:  J Healthc Eng       Date:  2016       Impact factor: 2.682

  1 in total

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