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- Øvretveit, J
(författare)
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Producing useful research about quality improvement
- 2002
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Ingår i: International journal of health care quality assurance incorporating Leadership in health services. - : Emerald. - 1366-0756. ; 15:6-7, s. 294-302
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Tidskriftsartikel (refereegranskat)abstract
- Many quality improvement interventions such as educational programmes, hospital quality strategies, and quality evaluation systems have not been evaluated. The aim of this paper is to encourage research into these “quality improvement processes” by presenting suitable designs and methods, and by describing research approaches which are less familiar in healthcare. The paper proposes that the choice of research design depends on the level and complexity of the intervention. Theory‐building approaches are more suitable than experimental theory testing approaches for evaluating higher‐level complex interventions and for understanding critical context factors. Collaborative action evaluation studies can provide useful information for decision makers – an example is given. “User focused” research can provide knowledge for developing more effective quality intervention processes and for making better decisions about their use and implementation.
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- Sessa, Maurizio, et al.
(författare)
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Artificial Intelligence in Pharmacoepidemiology : A Systematic Review. Part 1—Overview of Knowledge Discovery Techniques in Artificial Intelligence
- 2020
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Ingår i: Frontiers in Pharmacology. - : Frontiers Media S.A.. - 1663-9812. ; 11
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Forskningsöversikt (refereegranskat)abstract
- Aim: To perform a systematic review on the application of artificial intelligence (AI) based knowledge discovery techniques in pharmacoepidemiology.Study Eligibility Criteria: Clinical trials, meta-analyses, narrative/systematic review, and observational studies using (or mentioning articles using) artificial intelligence techniques were eligible. Articles without a full text available in the English language were excluded.Data Sources: Articles recorded from 1950/01/01 to 2019/05/06 in Ovid MEDLINE were screened.Participants: Studies including humans (real or simulated) exposed to a drug.Results: In total, 72 original articles and 5 reviews were identified via Ovid MEDLINE. Twenty different knowledge discovery methods were identified, mainly from the area of machine learning (66/72; 91.7%). Classification/regression (44/72; 61.1%), classification/regression + model optimization (13/72; 18.0%), and classification/regression + features selection (12/72; 16.7%) were the three most frequent tasks in reviewed literature that machine learning methods has been applied to solve. The top three used techniques were artificial neural networks, random forest, and support vector machines models.Conclusions: The use of knowledge discovery techniques of artificial intelligence techniques has increased exponentially over the years covering numerous sub-topics of pharmacoepidemiology.
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