Khalil Hanan, Bell Brian, Chambers Helen, Sheikh Aziz, Avery Anthony J
Faculty of Medicine, Nursing and Health Sciences, School of Rural Health, PO Box 973, Moe, Victoria, Australia, 3825.
Cochrane Database Syst Rev. 2017 Oct 4;10(10):CD003942. doi: 10.1002/14651858.CD003942.pub3.
Medication-related adverse events in primary care represent an important cause of hospital admissions and mortality. Adverse events could result from people experiencing adverse drug reactions (not usually preventable) or could be due to medication errors (usually preventable).
To determine the effectiveness of professional, organisational and structural interventions compared to standard care to reduce preventable medication errors by primary healthcare professionals that lead to hospital admissions, emergency department visits, and mortality in adults.
We searched CENTRAL, MEDLINE, Embase, three other databases, and two trial registries on 4 October 2016, together with reference checking, citation searching and contact with study authors to identify additional studies. We also searched several sources of grey literature.
We included randomised trials in which healthcare professionals provided community-based medical services. We also included interventions in outpatient clinics attached to a hospital where people are seen by healthcare professionals but are not admitted to hospital. We only included interventions that aimed to reduce medication errors leading to hospital admissions, emergency department visits, or mortality. We included all participants, irrespective of age, who were prescribed medication by a primary healthcare professional.
Three review authors independently extracted data. Each of the outcomes (hospital admissions, emergency department visits, and mortality), are reported in natural units (i.e. number of participants with an event per total number of participants at follow-up). We presented all outcomes as risk ratios (RRs) with 95% confidence intervals (CIs). We used the GRADE tool to assess the certainty of evidence.
We included 30 studies (169,969 participants) in the review addressing various interventions to prevent medication errors; four studies addressed professional interventions (8266 participants) and 26 studies described organisational interventions (161,703 participants). We did not find any studies addressing structural interventions. Professional interventions included the use of health information technology to identify people at risk of medication problems, computer-generated care suggested and actioned by a physician, electronic notification systems about dose changes, drug interventions and follow-up, and educational interventions on drug use aimed at physicians to improve drug prescriptions. Organisational interventions included medication reviews by pharmacists, nurses or physicians, clinician-led clinics, and home visits by clinicians.There is a great deal of diversity in types of professionals involved and where the studies occurred. However, most (61%) of the interventions were conducted by pharmacists or a combination of pharmacists and medical doctors. The studies took place in many different countries; 65% took place in either the USA or the UK. They all ranged from three months to 4.7 years of follow-up, they all took place in primary care settings such as general practice, outpatients' clinics, patients' homes and aged-care facilities. The participants in the studies were adults taking medications and the interventions were undertaken by healthcare professionals including pharmacists, nurses or physicians. There was also evidence of potential bias in some studies, with only 18 studies reporting adequate concealment of allocation and only 12 studies reporting appropriate protection from contamination, both of which may have influenced the overall effect estimate and the overall pooled estimate. Professional interventionsProfessional interventions probably make little or no difference to the number of hospital admissions (risk ratio (RR) 1.24, 95% confidence interval (CI) 0.79 to 1.96; 2 studies, 3889 participants; moderate-certainty evidence). Professional interventions make little or no difference to the number of participants admitted to hospital (adjusted RR 0.99, 95% CI 0.92 to 1.06; 1 study, 3661 participants; high-certainty evidence). Professional interventions may make little or no difference to the number of emergency department visits (adjusted RR 0.71, 95% CI 0.50 to 1.02; 2 studies, 1067 participants; low-certainty evidence). Professional interventions probably make little or no difference to mortality in the study population (adjusted RR 0.98, 95% CI 0.82 to 1.17; 1 study, 3538 participants; moderate-certainty evidence). Organisational interventionsOverall, it is uncertain whether organisational interventions reduce the number of hospital admissions (adjusted RR 0.85, 95% CI 0.71 to 1.03; 11 studies, 6203 participants; very low-certainty evidence). Overall, organisational interventions may make little difference to the total number of people admitted to hospital in favour of the intervention group compared with the control group (adjusted RR 0.92, 95% CI 0.86 to 0.99; 13 studies, 152,237 participants; low-certainty evidence. Overall, it is uncertain whether organisational interventions reduce the number of emergency department visits in favour of the intervention group compared with the control group (adjusted RR 0.75, 95% CI 0.49 to 1.15; 5 studies, 1819 participants; very low-certainty evidence. Overall, it is uncertain whether organisational interventions reduce mortality in favour of the intervention group (adjusted RR 0.94, 95% CI 0.85 to 1.03; 12 studies, 154,962 participants; very low-certainty evidence.
AUTHORS' CONCLUSIONS: Based on moderate- and low-certainty evidence, interventions in primary care for reducing preventable medication errors probably make little or no difference to the number of people admitted to hospital or the number of hospitalisations, emergency department visits, or mortality. The variation in heterogeneity in the pooled estimates means that our results should be treated cautiously as the interventions may not have worked consistently across all studies due to differences in how the interventions were provided, background practice, and culture or delivery of the interventions. Larger studies addressing both professional and organisational interventions are needed before evidence-based recommendations can be made. We did not identify any structural interventions and only four studies used professional interventions, and so more work needs to be done with these types of interventions. There is a need for high-quality studies describing the interventions in more detail and testing patient-related outcomes.
基层医疗中与药物相关的不良事件是导致住院和死亡的重要原因。不良事件可能源于人们发生药物不良反应(通常不可预防),也可能是由于用药错误(通常可预防)。
确定与标准护理相比,专业、组织和结构干预措施在减少基层医疗专业人员导致成人住院、急诊就诊和死亡的可预防用药错误方面的有效性。
我们于2016年10月4日检索了CENTRAL、MEDLINE、Embase以及其他三个数据库和两个试验注册库,并进行参考文献核对、引文检索以及与研究作者联系以识别其他研究。我们还检索了多个灰色文献来源。
我们纳入了医疗专业人员提供社区医疗服务的随机试验。我们还纳入了医院附属门诊的干预措施,在这些门诊中,医疗专业人员会诊治患者但患者不住院。我们仅纳入旨在减少导致住院、急诊就诊或死亡的用药错误的干预措施。我们纳入了所有参与者,无论年龄大小,只要他们由基层医疗专业人员开具药物。
三位综述作者独立提取数据。每个结局(住院、急诊就诊和死亡)均以自然单位报告(即随访时发生事件的参与者数量占总参与者数量的比例)。我们将所有结局表示为风险比(RR)及95%置信区间(CI)。我们使用GRADE工具评估证据的确定性。
我们在综述中纳入了30项研究(169,969名参与者),这些研究涉及预防用药错误的各种干预措施;4项研究涉及专业干预(8266名参与者),26项研究描述了组织干预(161,703名参与者)。我们未找到任何涉及结构干预的研究。专业干预包括使用健康信息技术识别有用药问题风险的人群、由医生建议并实施的计算机生成护理、关于剂量变化的电子通知系统、药物干预及随访,以及针对医生旨在改善药物处方的药物使用教育干预。组织干预包括药剂师、护士或医生进行的药物审查、临床医生主导的诊所,以及临床医生进行的家访。所涉及的专业人员类型以及研究开展地点存在很大差异。然而,大多数(61%)干预措施由药剂师或药剂师与医生联合实施。这些研究在许多不同国家进行;65%在英国或美国进行。随访时间从三个月到4.7年不等,均在基层医疗环境中进行,如全科医疗、门诊、患者家中和老年护理机构。研究参与者为正在服药的成年人,干预措施由包括药剂师、护士或医生在内的医疗专业人员实施。一些研究也存在潜在偏倚的证据,只有18项研究报告了充分的随机分配隐藏,只有12项研究报告了适当的防止沾染措施,这两者都可能影响总体效应估计和总体合并估计。
专业干预
专业干预可能对住院人数几乎没有影响(风险比(RR)1.24,95%置信区间(CI)0.79至1.96;2项研究,3889名参与者;中等确定性证据)。专业干预对住院参与者人数几乎没有影响(调整后RR 0.99,95% CI 0.92至1.06;1项研究,366名参与者;高确定性证据)。专业干预可能对急诊就诊人数几乎没有影响(调整后RR 0.71,95% CI 0.50至1.02;2项研究,1067名参与者;低确定性证据)。专业干预可能对研究人群的死亡率几乎没有影响(调整后RR 0.98,95% CI 0.82至1.17;1项研究,3538名参与者;中等确定性证据)。
组织干预
总体而言,不确定组织干预是否能减少住院人数(调整后RR 0.85,95% CI 0.71至1.03;11项研究,6203名参与者;极低确定性证据)。总体而言,与对照组相比,组织干预可能对干预组住院总人数影响不大(调整后RR 0.92,95% CI 0.86至0.99;13项研究,152,237名参与者;低确定性证据)。总体而言,不确定与对照组相比,组织干预是否能减少干预组的急诊就诊人数(调整后RR 0.75,95% CI 0.49至1.15;5项研究,1819名参与者;极低确定性证据)。总体而言,不确定组织干预是否能降低干预组的死亡率(调整后RR 0.94,95% CI 0.85至1.03;12项研究,154,962名参与者;极低确定性证据)。
基于中等和低确定性证据,基层医疗中减少可预防用药错误的干预措施可能对住院人数、住院次数、急诊就诊人数或死亡率几乎没有影响。合并估计值中异质性的差异意味着我们的结果应谨慎对待,因为由于干预措施的提供方式、背景实践、文化或干预措施的实施存在差异导致这些干预措施在所有研究中可能并非始终有效。在能够提出基于证据的建议之前,需要开展针对专业和组织干预的更大规模研究。我们未识别出任何结构干预措施,且仅有四项研究使用了专业干预措施,因此需要对这些类型的干预措施开展更多工作。需要高质量研究更详细地描述干预措施并测试与患者相关的结局。