GUERRE D'IRAK - Les silences diplomatiques de la Chine
In: Le monde diplomatique, Band 50, Heft 588, S. 12-26
ISSN: 0026-9395, 1147-2766
27 Ergebnisse
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In: Le monde diplomatique, Band 50, Heft 588, S. 12-26
ISSN: 0026-9395, 1147-2766
In: Land use policy: the international journal covering all aspects of land use, Band 87, S. 104048
ISSN: 0264-8377
In: SEPPUR-D-22-00526
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In: Waste management: international journal of integrated waste management, science and technology, Band 48, S. 397-403
ISSN: 1879-2456
In: International journal of sustainable development & world ecology, Band 13, Heft 3, S. 211-220
ISSN: 1745-2627
In: Waste management: international journal of integrated waste management, science and technology, Band 178, S. 331-338
ISSN: 1879-2456
In: Environmental management: an international journal for decision makers, scientists, and environmental auditors, Band 48, Heft 6, S. 1173-1181
ISSN: 1432-1009
In: Environmental management: an international journal for decision makers, scientists, and environmental auditors, Band 40, Heft 1, S. 113-122
ISSN: 1432-1009
In: International journal of sustainable development & world ecology, Band 14, Heft 2, S. 182-191
ISSN: 1745-2627
In: International journal of sustainable development & world ecology, Band 11, Heft 2, S. 143-149
ISSN: 1745-2627
In: WM-23-3185
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In: BITE-D-21-06811
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In: International journal of population data science: (IJPDS), Band 1, Heft 1
ISSN: 2399-4908
ABSTRACTObjectivesData linkage algorithms are used to link together multiple episodes of care belonging to the same patient. For example, the HESID algorithm is used to generate Hospital Episode Statistics (HES) in England. HESID is a deterministic algorithm, requiring identifiers to agree or disagree at each step. Data linkage errors occur when episodes belonging to two patients are incorrectly linked (a false match) or when episodes belonging to the same patient are not linked (a missed match). This typically occurs because patient identifiers (e.g. NHS number, postcode) contain errors or have missing data. We previously showed that HESID has a low false match rate (0.2%) but a high missed match rate (4.1%) when applied to paediatric intensive care data. This biased the true readmission rate, particularly for some patient groups including ethnic minorities. The aim of our study was to evaluate whether an additional step involving probabilistic matching would lower the missed match rate in HES without increasing the false matched rate.
ApproachWe simulated three datasets having the same characteristics as HES, for three age groups expected to have different levels of postcode stability (at age 0/1, 5/6 and 18/19). We compared the deterministic algorithm to a probabilistic algorithm, and then to a deterministic algorithm with an additional probabilistic step. In sensitivity analyses, we evaluated the algorithms under different data quality scenarios.
ResultsResults show that deterministic followed by probabilistic matching is the best solution for reducing missed matches, particularly in scenarios where errors in patient identifiers are more common.
ConclusionData linkage algorithms need to be evaluated against good quality reference standard data sets. For hospital data in England, the Personal Demographics Service (PDS) could be used to evaluate our approach, because it contains many of the same patient identifiers used in HES. Reducing data linkage error will improve monitoring of hospital activity in England.
In: International journal of sustainable development & world ecology, Band 11, Heft 4, S. 397-409
ISSN: 1745-2627
In: JEMA-D-22-08483
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