Literature DB >> 4093736

Forecasting staffing needs for productivity management in hospital laboratories.

C Y Pang, J M Swint.   

Abstract

Daily and weekly prediction models are developed to help forecast hospital laboratory work load for the entire laboratory and individual sections of the laboratory. The models are tested using historical data obtained from hospital census and laboratory log books of a 90-bed southwestern hospital. The results indicate that the predictor variables account for 50%, 81%, 56%, and 82% of the daily work load variation for chemistry, hematology, and microbiology sections, and for the entire laboratory, respectively. Equivalent results for the weekly model are 53%, 72%, 12%, and 78% for the same respective sections. On the basis of the predicted work load, staffing assessment is made and a productivity monitoring system constructed. The purpose of such a system is to assist laboratory management in efforts to utilize laboratory manpower in a more efficient and cost-effective manner.

Mesh:

Year:  1985        PMID: 4093736     DOI: 10.1007/BF00992574

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


  4 in total

1.  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

2.  Assessing productivity in the laboratory.

Authors:  L A Holloway
Journal:  Hospitals       Date:  1982-08-16

3.  A study of factors affecting laboratory workload.

Authors:  H W Taylor
Journal:  Clin Biochem       Date:  1978-08       Impact factor: 3.281

4.  A laboratory productivity monitoring system.

Authors:  K E Olsen; R J Durej
Journal:  Am J Med Technol       Date:  1981-08
  4 in total
  4 in total

1.  Short term hospital occupancy prediction.

Authors:  Steven J Littig; Mark W Isken
Journal:  Health Care Manag Sci       Date:  2007-02

2.  Forecasting hospital laboratory procedures.

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

3.  A final adjustment for staff allocation under environmental uncertainty.

Authors:  A Jeang
Journal:  J Med Syst       Date:  1989-04       Impact factor: 4.460

4.  Forecasting the demand for inpatient services for specific chronic conditions.

Authors:  J J Hisnanick
Journal:  J Med Syst       Date:  1994-02       Impact factor: 4.460

  4 in total

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