How intervention studies measure the effectiveness of medication safety-related clinical decision support systems in primary and long-term care: a systematic review
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| Izdano u: | BMC Medical Informatics and Decision Making vol. 24 (2024), p. 1 |
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| Daljnji autori: | , , , , , |
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Springer Nature B.V.
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| Online pristup: | Citation/Abstract Full Text Full Text - PDF |
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MARC
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| 022 | |a 1472-6947 | ||
| 024 | 7 | |a 10.1186/s12911-024-02596-y |2 doi | |
| 035 | |a 3079155148 | ||
| 045 | 2 | |b d20240101 |b d20241231 | |
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| 100 | 1 | |a Lampe, David | |
| 245 | 1 | |a How intervention studies measure the effectiveness of medication safety-related clinical decision support systems in primary and long-term care: a systematic review | |
| 260 | |b Springer Nature B.V. |c 2024 | ||
| 513 | |a Evidence Based Healthcare Journal Article | ||
| 520 | 3 | |a BackgroundMedication errors and associated adverse drug events (ADE) are a major cause of morbidity and mortality worldwide. In recent years, the prevention of medication errors has become a high priority in healthcare systems. In order to improve medication safety, computerized Clinical Decision Support Systems (CDSS) are increasingly being integrated into the medication process. Accordingly, a growing number of studies have investigated the medication safety-related effectiveness of CDSS. However, the outcome measures used are heterogeneous, leading to unclear evidence. The primary aim of this study is to summarize and categorize the outcomes used in interventional studies evaluating the effects of CDSS on medication safety in primary and long-term care.MethodsWe systematically searched PubMed, Embase, CINAHL, and Cochrane Library for interventional studies evaluating the effects of CDSS targeting medication safety and patient-related outcomes. We extracted methodological characteristics, outcomes and empirical findings from the included studies. Outcomes were assigned to three main categories: process-related, harm-related, and cost-related. Risk of bias was assessed using the Evidence Project risk of bias tool.ResultsThirty-two studies met the inclusion criteria. Almost all studies (n = 31) used process-related outcomes, followed by harm-related outcomes (n = 11). Only three studies used cost-related outcomes. Most studies used outcomes from only one category and no study used outcomes from all three categories. The definition and operationalization of outcomes varied widely between the included studies, even within outcome categories. Overall, evidence on CDSS effectiveness was mixed. A significant intervention effect was demonstrated by nine of fifteen studies with process-related primary outcomes (60%) but only one out of five studies with harm-related primary outcomes (20%). The included studies faced a number of methodological problems that limit the comparability and generalizability of their results.ConclusionsEvidence on the effectiveness of CDSS is currently inconclusive due in part to inconsistent outcome definitions and methodological problems in the literature. Additional high-quality studies are therefore needed to provide a comprehensive account of CDSS effectiveness. These studies should follow established methodological guidelines and recommendations and use a comprehensive set of harm-, process- and cost-related outcomes with agreed-upon and consistent definitions.Prospero registrationCRD42023464746 | |
| 653 | |a Bias | ||
| 653 | |a Morbidity | ||
| 653 | |a Mortality | ||
| 653 | |a Intervention | ||
| 653 | |a Safety | ||
| 653 | |a Drug stores | ||
| 653 | |a Decision support systems | ||
| 653 | |a Computerized physician order entry | ||
| 653 | |a Long-term care | ||
| 653 | |a Categories | ||
| 653 | |a Medical errors | ||
| 653 | |a Evaluation | ||
| 653 | |a Patient safety | ||
| 653 | |a Electronic health records | ||
| 653 | |a Long term health care | ||
| 653 | |a Sociodemographics | ||
| 653 | |a Clinical trials | ||
| 653 | |a Primary care | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Clinical decision making | ||
| 653 | |a System effectiveness | ||
| 653 | |a Errors | ||
| 653 | |a Drugs | ||
| 653 | |a Systematic review | ||
| 700 | 1 | |a Grosser, John | |
| 700 | 1 | |a Grothe, Dennis | |
| 700 | 1 | |a Aufenberg, Birthe | |
| 700 | 1 | |a Gensorowsky, Daniel | |
| 700 | 1 | |a Witte, Julian | |
| 700 | 1 | |a Greiner, Wolfgang | |
| 773 | 0 | |t BMC Medical Informatics and Decision Making |g vol. 24 (2024), p. 1 | |
| 786 | 0 | |d ProQuest |t Healthcare Administration Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3079155148/abstract/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3079155148/fulltext/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3079155148/fulltextPDF/embedded/75I98GEZK8WCJMPQ?source=fedsrch |