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An evaluation of the use of time series analysis designs in clinical guidelines implementation studies

Time-series analysis designs strengthen before and after studies and are regarded as easy and cheap to use. These designs have recently become more popular in guideline implementation studies but there is suspicion that time series analysis designs are used inappropriately or without sufficient understanding or the underlying methodology. In this thesis, we attempt to evaluate their use by means of a systematic review of published studies, and by actively using time series analysis to evaluate the effect of dissemination of the 3rd edition of the Royal College of Radiologists' guidelines on imaging referral patterns from primary care in the North East of Scotland. The systematic review established that indeed many time series studies are conducted inappropriately with key issues such as the use of adequate number of data points and adjustment for trends not taken into consideration. Often results are tested using non-statistical analyses. Our findings suggest that there should be an increased awareness among investigators of the correct statistical technique for performing and analysing time series analyses. From the guideline evaluation study, it was found that the passive dissemination of the imaging guideline in the North East of Scotland did not affect GPs' imaging referral patterns. This may suggest the need for reinforcement with more active dissemination strategies. It was also established that time series analysis can be complex, requiring a clear understanding before use if researchers are to achieve the best from them. Compared to time series analysis before and after studies were shown to be unreliable with the potential of giving misleading results.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:364496
Date January 2001
CreatorsMatowe, Lloyd K.
PublisherUniversity of Aberdeen
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU137968

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