2026-09-22T01:35:47Zhttps://bura.brunel.ac.uk/oai/request

oai:bura.brunel.ac.uk:2438/79012014-11-01T13:19:40Zcom_2438_58col_2438_3672

Macdonald, P Crowe, Walter Ramsey 2014-01-16T12:21:17Z 2014-01-16T12:21:17Z 1977 http://bura.brunel.ac.uk/handle/2438/7901 This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University. Economic stringencies have compelled Canadian hospitals to examine their administrative effectiveness critically. Improved supplies and inventory procedures adopted by leading industrial corporations, suggest that hospitals might benefit from such systems. Lack of the profit incentive, and the high ratio of wages to total expenses in hospitals, have delayed adoption of modern inventory management techniques. This study examined the economic status of Canadian hospitals, and endeavoured to discover whether a computer-based inventory management system, incorporating short-term statistical demand forecasting, would be feasible and advantageous. Scientific forecasting for inventory management is not used by hospitals. The writer considered which technique would be most suited to their needs, taking account of benefits claimed by industrial users. Samples of demand data were subjected to a variety of simple forecasting methods, including moving averages, exponentially smoothed averages and the Box-Jenkins method. Comparisons were made in terms of relative size of forecast errors; ease of data maintenance, and demands upon hospital clerical staffs. The computer system: BRUFICH facilitated scrutiny of the effect of each technique upon major components of the system. It is concluded that either of two methods would be appropriate: moving averages and double exponential smoothing. The latter, when combined with adaptive control through tracking signals, is easily incorporated within the total inventory system. It requires only a short run of data, tracks trend satisfactorily, and demands little operator intervention. The original system designed by this writer was adopted by the Hospital for Sick Children, Toronto, and has significantly improved their inventory management. Submitted by Terese Jonsson (terese.jonsson@brunel.ac.uk) on 2014-01-16T12:21:05Z No. of bitstreams: 2 452675_vol.2.pdf: 25452350 bytes, checksum: eadd3885f52216f7415a9d11df362097 (MD5) 452675_vol.1.pdf: 6678697 bytes, checksum: 9df2c3822d2bc9d6f8ed5e582abdc309 (MD5) Approved for entry into archive by Terese Jonsson(terese.jonsson@brunel.ac.uk) on 2014-01-16T12:21:17Z (GMT) No. of bitstreams: 2 452675_vol.2.pdf: 25452350 bytes, checksum: eadd3885f52216f7415a9d11df362097 (MD5) 452675_vol.1.pdf: 6678697 bytes, checksum: 9df2c3822d2bc9d6f8ed5e582abdc309 (MD5) Made available in DSpace on 2014-01-16T12:21:17Z (GMT). No. of bitstreams: 2 452675_vol.2.pdf: 25452350 bytes, checksum: eadd3885f52216f7415a9d11df362097 (MD5) 452675_vol.1.pdf: 6678697 bytes, checksum: 9df2c3822d2bc9d6f8ed5e582abdc309 (MD5) Lakehead University and the Ministry of Health, Government of Ontario. en http://bura.brunel.ac.uk/bitstream/2438/7901/1/FulltextThesis.pdf Hospital inventory management Statistical demand forecasting Moving averages Double exponential smoothing Statistics Forecasting and inventory control for hospital management Thesis