Literature DB >> 8064208

Forecasting the demand for inpatient services for specific chronic conditions.

J J Hisnanick1.   

Abstract

While the proposed forecasting methodology has a well-established record in evaluating economic time-series, there is minimal, if any, use of this technique in projecting hospitalizations for specific chronic conditions. Using an established taxonomy of disease codes for alcoholism and alcohol abuse in a national inpatient database, a monthly time-series of hospitalizations was modeled. The model derived in both statistically adequate and accurate in forecasting future monthly demand for inpatient hospitalizations. This type of model specifications could be used by hospital planners and policy makers in evaluating monthly resources for specific chronic conditions.

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Year:  1994        PMID: 8064208     DOI: 10.1007/bf00999320

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  6 in total

1.  Forecasting hospital laboratory procedures.

Authors:  J H Wilson; S J Schuiling
Journal:  J Med Syst       Date:  1992-12       Impact factor: 4.460

2.  Statistical forecasting in a hospital clinical laboratory.

Authors:  V E McGee; E Jenkins; H M Rawnsley
Journal:  J Med Syst       Date:  1979       Impact factor: 4.460

3.  Forecasting staffing needs for productivity management in hospital laboratories.

Authors:  C Y Pang; J M Swint
Journal:  J Med Syst       Date:  1985-12       Impact factor: 4.460

4.  Hospital resource utilization by American Indians/Alaska Natives for alcoholism and alcohol abuse.

Authors:  J J Hisnanick; P M Erickson
Journal:  Am J Drug Alcohol Abuse       Date:  1993       Impact factor: 3.829

5.  The Indian Health Service approach to alcoholism among American Indians and Alaska Natives.

Authors:  E R Rhoades; R D Mason; P Eddy; E M Smith; T R Burns
Journal:  Public Health Rep       Date:  1988 Nov-Dec       Impact factor: 2.792

  6 in total
  1 in total

1.  Time series modelling and forecasting of emergency department overcrowding.

Authors:  Farid Kadri; Fouzi Harrou; Sondès Chaabane; Christian Tahon
Journal:  J Med Syst       Date:  2014-07-23       Impact factor: 4.460

  1 in total

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