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Computerised decision to reduce inappropriate medication in the elderly: a systematic review with meta-analysis protocol.

ABSTRACT: INTRODUCTION:Life expectancy continues to increase in developed countries. Elderly people are more likely to consume more medications and become vulnerable to age-related changes in drugs' pharmacokinetics and pharmacodynamics. Recent studies have identified opportunities and barriers for deprescribing potentially inappropriate medications. It has already been demonstrated that computerised decision support systems can reduce physician orders for unnecessary tests. We will systematically review the available literature to understand if computerised decision support is effective in reducing the use of potentially inappropriate medications, thus having an impact on health outcomes. METHODS AND ANALYSIS:A systematic review will be conducted using MEDLINE, CENTRAL, EMBASE and Web of Science databases, as well as the grey literature assessing the effectiveness of computer decision support interventions in deprescribing inappropriate medication, with an impact on health outcomes in the elderly. The search will be performed during January and February 2018. Two reviewers will conduct articles' screening, selection and data extraction, independently and blind to each other. Eligible sources will be selected after discussing non-conformities. All extracted data from the included articles will be assessed based on studies' participants, design and setting, methodological quality, bias and any other potential sources of heterogeneity. This review will be conducted and reported in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement of quality for reporting systematic reviews and meta-analyses. ETHICS AND DISSEMINATION:As a systematic review, this research is exempt from ethical approval. We intend to publish the full article in a related peer-reviewed journal and present it at international conferences. PROSPEROREGISTRATION NUMBER:CRD42017067021.

SUBMITTER: Monteiro L

PROVIDER: S-EPMC5829874 | biostudies-other | 2018 Jan

REPOSITORIES: biostudies-other

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Computerised decision to reduce inappropriate medication in the elderly: a systematic review with meta-analysis protocol.

Monteiro Luís L Maricoto Tiago T Solha Isabel S IS Monteiro-Soares Matilde M Martins Carlos C

BMJ open 20180130 1

<h4>Introduction</h4>Life expectancy continues to increase in developed countries. Elderly people are more likely to consume more medications and become vulnerable to age-related changes in drugs' pharmacokinetics and pharmacodynamics. Recent studies have identified opportunities and barriers for deprescribing potentially inappropriate medications. It has already been demonstrated that computerised decision support systems can reduce physician orders for unnecessary tests. We will systematically ...[more]

PMID: 29382677

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Project description:BackgroundInappropriate medication use (IMU) by elderly people is a public health problem associated with adverse effects on health. There are a number of methods for identifying IMU, some involving clinical judgment and others, consensually generated lists of drugs to be avoided. This review aims to describe studies that used information from insurance company and social security administrative databases to assess IMU among community-dwelling elderly and to present the risk factors most often associated with IMU.MethodsThe paper search was conducted in Medline and Embase, using descriptors combined with free terms in the title or abstract. The limits applied were: publication date from January 1990 to June 2010, species (human) and publication type (excluding editorials, letters and reviews). Excluded were: case studies; studies in hospitals, nursing homes, or hospital emergency departments; studies of specific drugs or groups of drugs; studies exclusively of subgroups of ill, frail elderly or rural populations. Additional studies were identified from reference lists. Data were selected and extracted after independent reading by two of the authors, with disagreements resolved by a third author. The primary outcome assessed was prevalence of IMU, defined as the proportion of elderly who received at least one inappropriate medication.ResultsOf the 628 studies, 19 met the inclusion criteria, 78.9% of them conducted in the USA. All papers included used explicit criteria of inappropriateness, most commonly Beers criteria (73.7%) in their three versions (1991, 1997 and 2002). Other methods used included Zhan, which is derived from on Beers criteria and was applied in 21% of the papers selected. The study found that prevalence of IMU ranged from 11.5% to 62.5%. Only 68.4% of the studies included examined inappropriate use-related factors, the most important being female sex, advanced age and larger number of drugs.ConclusionsThe results show that the prevalence of IMU among community-dwelling elderly is high and depends partly on the method used to evaluate improper use. Besides the diversity of methods, other factors, such as patient sex, age and number of drugs used concurrently, appear to have influenced the estimates of IMU.

Project description:BACKGROUND:Several approaches to medication optimisation by identifying drug-related problems in older people have been described. Although some interventions have shown reductions in drug-related problems (DRPs), evidence supporting the effectiveness of medication reviews on clinical and economic outcomes is lacking. Application of the STOPP/START (version 2) explicit screening tool for inappropriate prescribing has decreased inappropriate prescribing and significantly reduced adverse drug reactions (ADRs) and associated healthcare costs in older patients with multi-morbidity and polypharmacy. Therefore, application of STOPP/START criteria during a medication review is likely to be beneficial. Incorporation of explicit screening tools into clinical decision support systems (CDSS) has gained traction as a means to improve both quality and efficiency in the rather time-consuming medication review process. Although CDSS can generate more potential inappropriate medication recommendations, some of these have been shown to be less clinically relevant, resulting in alert fatigue. Moreover, explicit tools such as STOPP/START do not cover all relevant DRPs on an individual patient level. The OPERAM study aims to assess the impact of a structured drug review on the quality of pharmacotherapy in older people with multi-morbidity and polypharmacy. The aim of this paper is to describe the structured, multi-component intervention of the OPERAM trial and compare it with the approach in the comparator arm. METHOD:This paper describes a multi-component intervention, integrating interventions that have demonstrated effectiveness in defining DRPs. The intervention involves a structured history-taking of medication (SHiM), a medication review according to the systemic tool to reduce inappropriate prescribing (STRIP) method, assisted by a clinical decision support system (STRIP Assistant, STRIPA) with integrated STOPP/START criteria (version 2), followed by shared decision-making with both patient and attending physician. The developed method integrates patient input, patient data, involvement from other healthcare professionals and CDSS-assistance into one structured intervention. DISCUSSION:The clinical and economical effectiveness of this experimental intervention will be evaluated in a cohort of hospitalised, older patients with multi-morbidity and polypharmacy in the multicentre, randomized controlled OPERAM trial (OPtimising thERapy to prevent Avoidable hospital admissions in the Multi-morbid elderly), which will be completed in the last quarter of 2019. TRIAL REGISTRATION:Universal Trial Number: U1111-1181-9400 Clinicaltrials.gov: NCT02986425, Registered 08 December 2016. FOPH (Swiss national portal): SNCTP000002183. Netherlands Trial Register: NTR6012 (07-10-2016).

Project description:BackgroundInappropriate antibiotic use contributes significantly to the global challenge of antimicrobial resistance. While government-initiated population-level interventions are fundamental in addressing this issue, their full potential remains to be explored. This systematic review aims to assess the effectiveness of such interventions in reducing inappropriate antibiotic use among antibiotic providers and users in healthcare and community settings.MethodsWe will conduct a systematic literature search across multiple databases and grey literature sources. We will include studies which evaluate the effectiveness of population-level interventions to reduce inappropriate antibiotic use in healthcare and community settings in both high-income and low- and middle-income countries. This includes government-initiated measures targeting antibiotic use through education, restriction, incentivization, coercion, training, persuasion, context modification, behavior modeling, or barrier reduction. Two reviewers will independently perform screening to select eligible studies, followed by data extraction. The outcomes of interest are various measures of antibiotic prescription and consumption, such as Defined Daily Dose (DDD) or number of prescriptions per year. We anticipate including a broad range of study designs and outcome measures. Therefore, we will narratively synthesize results using the categories of the population-level policy interventions of the Behavior Change Wheel Framework. We will organize outcome data by economic contexts, target populations, and implementation settings.DiscussionThis review will strengthen the evidence base for the use of population-level interventions to address inappropriate antibiotic use. Drawing lessons from global experiences, the findings will provide valuable guidance to health policymakers, public health authorities, and researchers on tailoring interventions to specific economic contexts, populations, and settings, thereby enhancing their capacity to drive substantial improvement in appropriate antibiotic use.

Project description:BackgroundInappropriate antimicrobial use has been shown to be an important determinant of the emergence of antimicrobial resistance (AMR). Health information technology (HIT) in the form of Computerised Decision Support (CDS) represents an option for improving antimicrobial prescribing and containing AMR.ObjectivesTo evaluate the evidence for CDS in improving quantitative and qualitative measures of antibiotic prescribing in inpatient hospital settings.MethodsA systematic literature search was conducted of articles published from inception to 20th December 2014 using eight electronic databases: MEDLINE, EMBASE, PUBMED, Web of Science, CINAHL, Cochrane Library, HMIC and PsychINFo. An updated systematic literature search was conducted from January 1st 2015 to October 1st 2016 using PUBMED. The search strategy used combinations of the following terms: (electronic prescribing) OR (clinical decision support) AND (antibiotic or antibacterial or antimicrobial) AND (hospital or secondary care or inpatient). Studies were evaluated for quality using a 10-point rating scale.ResultsEighty-one studies were identified matching the inclusion criteria. Seven outcome measures were evaluated: adequacy of antibiotic coverage, mortality, volume of antibiotic usage, length of stay, antibiotic cost, compliance with guidelines, antimicrobial resistance, and CDS implementation and uptake. Meta-analysis of pooled outcomes showed CDS significantly improved the adequacy of antibiotic coverage (n = 13; odds ratio [OR], 2.11 [95% CI, 1.67 to 2.66, p ≤ 0.00001]). Also, CDS was associated with marginally lowered mortality (n = 20; OR, 0.85 [CI, 0.75 to 0.96, p = 0.01]). CDS was associated with lower antibiotic utilisation, increased compliance with antibiotic guidelines and reductions in antimicrobial resistance. Conflicting effects of CDS on length of stay, antibiotic costs and system uptake were also noted.ConclusionsCDS has the potential to improve the adequacy of antibiotic coverage and marginally decrease mortality in hospital-related settings.

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Computerised decision to reduce inappropriate medication in the elderly: a systematic review with meta-analysis protocol.

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Computerised decision to reduce inappropriate medication in the elderly: a systematic review with meta-analysis protocol.

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