PDF(Pubmed)
Abstract：
BACKGROUND: Falls are a significant public health problem and constitute a major cause of injuries and mortality. Risk factors for falls are multifactorial and include medication use.
OBJECTIVE: To develop and investigate the content validity of the Medication-Related fall (MRF) screening and scoring tool.
METHODS: The MRF tool was developed from clinical practice guidelines addressing medication-related problems, and additional medications identified by specialist pharmacists across a region of the United Kingdom (Northern Ireland). Medication classes were categorised according to their \'potential to cause falls\' as: high-risk (three points), moderate-risk (two points) or low-risk (one point). The overall medication-related falls risk for the patient was determined by summing the scores for all medications. The MRF was validated using Delphi consensus methodology, whereby three iterative rounds of surveys were conducted using SurveyMonkey®. Twenty-two experts from 10 countries determined their agreement with the falls risk associated with each medication on a 5-point Likert scale. Only medications with at least 75% of respondents agreeing or strongly agreeing were retained in the next round.
RESULTS: Consensus was reached for 19 medications/medication classes to be included in the final version of the MRF tool; ten were classified as high-risk, eight as moderate-risk and one as low-risk.
CONCLUSIONS: The MRF tool is simple and has the potential to be integrated into medicines optimisation to reduce falls risk and negative fall-related outcomes. The score from the MRF tool can be used as a clinical parameter to assess the need for medication review and clinical interventions.
OBJECTIVE: To develop and investigate the content validity of the Medication-Related fall (MRF) screening and scoring tool.
METHODS: The MRF tool was developed from clinical practice guidelines addressing medication-related problems, and additional medications identified by specialist pharmacists across a region of the United Kingdom (Northern Ireland). Medication classes were categorised according to their \'potential to cause falls\' as: high-risk (three points), moderate-risk (two points) or low-risk (one point). The overall medication-related falls risk for the patient was determined by summing the scores for all medications. The MRF was validated using Delphi consensus methodology, whereby three iterative rounds of surveys were conducted using SurveyMonkey®. Twenty-two experts from 10 countries determined their agreement with the falls risk associated with each medication on a 5-point Likert scale. Only medications with at least 75% of respondents agreeing or strongly agreeing were retained in the next round.
RESULTS: Consensus was reached for 19 medications/medication classes to be included in the final version of the MRF tool; ten were classified as high-risk, eight as moderate-risk and one as low-risk.
CONCLUSIONS: The MRF tool is simple and has the potential to be integrated into medicines optimisation to reduce falls risk and negative fall-related outcomes. The score from the MRF tool can be used as a clinical parameter to assess the need for medication review and clinical interventions.
摘要：
背景：跌倒是一个重要的公共卫生问题，是造成伤害和死亡的主要原因。跌倒的危险因素是多因素的，包括药物使用。
目的：开发并研究药物相关性跌倒（MRF）筛查和评分工具的内容效度。
方法：MRF工具是根据解决药物相关问题的临床实践指南开发的，以及由英国（北爱尔兰）地区的专业药剂师确定的其他药物。药物类别根据其“导致跌倒的潜力”分类为：高风险（3分），中等风险(两点)或低风险(一点)。通过对所有药物的评分求和来确定患者的总体药物相关跌倒风险。MRF使用Delphi共识方法进行了验证，其中使用SurveyMonkey®进行了三轮迭代调查。来自10个国家的22名专家以5点Likert量表确定了与每种药物相关的跌倒风险。在下一轮中，仅保留至少75％的受访者同意或强烈同意的药物。
结果：达成共识，将19种药物/药物类别纳入MRF工具的最终版本；十种被归类为高风险，八个为中等风险，一个为低风险。
结论：MRF工具很简单，有可能被整合到药物优化中，以降低跌倒风险和跌倒相关的负面结果。来自MRF工具的评分可以用作临床参数以评估药物审查和临床干预的需要。
目的：开发并研究药物相关性跌倒（MRF）筛查和评分工具的内容效度。
方法：MRF工具是根据解决药物相关问题的临床实践指南开发的，以及由英国（北爱尔兰）地区的专业药剂师确定的其他药物。药物类别根据其“导致跌倒的潜力”分类为：高风险（3分），中等风险(两点)或低风险(一点)。通过对所有药物的评分求和来确定患者的总体药物相关跌倒风险。MRF使用Delphi共识方法进行了验证，其中使用SurveyMonkey®进行了三轮迭代调查。来自10个国家的22名专家以5点Likert量表确定了与每种药物相关的跌倒风险。在下一轮中，仅保留至少75％的受访者同意或强烈同意的药物。
结果：达成共识，将19种药物/药物类别纳入MRF工具的最终版本；十种被归类为高风险，八个为中等风险，一个为低风险。
结论：MRF工具很简单，有可能被整合到药物优化中，以降低跌倒风险和跌倒相关的负面结果。来自MRF工具的评分可以用作临床参数以评估药物审查和临床干预的需要。
