Computer-assisted medication review for asthmatic patients as a basis for intervention Constructing and validating an algorithmic computer instrument in pharmacy practice

OBJECTIVE: To construct and validate a computer instrument that identifies asthma patients receiving--theoretically--suboptimal drug therapy in community pharmacies, by the use of patient medication records. This selection enables the pharmacist to assist these patients in using medicines appropriately. METHODS: According to Dutch asthma guidelines which describe a stepwise approach and in order to define correct profiles for the use at each level of these guidelines, the optimum use of drugs in the different levels in asthma treatment was expressed in defined daily doses (DDDs) per pharmacological drug-group during a period of one year. An algorithmic computer instrument was developed to select patients with medication use deviant from these profiles. By using nine different selection profiles, the computer instrument stratified patients according to the medication records filed in the pharmacy computer. Patient medication records in four community pharmacies were investigated to validate the selection profiles as indicators for theoretically suboptimal drug use by asthma patients. The validation was performed by comparing the professional judgement of participating pharmacists with the selections made by the computer. MAIN OUTCOME MEASURE: Positive predictive value and negative predictive value of the selection made by algorithmic computer instrument. Rate of false-positive results. RESULTS: The computer instrument identified asthma patients using theoretically suboptimal drug therapy with approximately 95% predictive value compared with the professional judgement of the pharmacists. The rate of false-positive results was 5%. CONCLUSION: The results of the algorithmic computer instrument and the professional judgement of the pharmacists are in close agreement. The instrument will be utilised in further research in the IPMP study (Interventions on the principle of Pulmonary Medication Profiles) investigating the role of Dutch community pharmacists in counselling patients who are at risk of suboptimal drug use in the treatment of their asthma.     

20856例急诊患者疾病谱及就诊特点

目的 分析达州市中西医结合医院急诊科就诊患者的疾病谱构成及就诊特点,为进一步明确救治重点、优化急诊流程、优化及合理使用急诊资源提供数据支撑。方法 通过调取达州市中西医结合医院HIS系统2017年1月1日0:00～2017年12月31 日23:59急诊就诊共计20856例患者的基本信息及诊断资料,分析患者的性别、年龄、就诊时间、疾病种类、是否住院等情况,采用描述性统计方法进行分析,SPSS 25.0软件进行统计学处理,率的比较采用X2检验。结果 20856例患者中,男性比例高于女性;年龄组以青年组（45.97%）急诊就诊率最高;一年四季中夏季（26.63%）就诊量最多,春季（23.46%）最低;8月（9.58%）为急诊就诊月高峰,4月（7.49%）为低谷期;急诊就诊量星期时间点波动（14.02%～14.59%）不明显,周末效应不明显;急诊全天1小时高峰时段为20:00～21:00时,4小时高峰时段为18:00～22:00时;疾病谱中以外伤（2330%）、消化系统（21.25%）、其他类（1429%）为前三位病种。全年急诊就诊患者住院率明显高于同期门诊患者住院率。结论 该医院急诊患者就诊有一定的规律性,医院可考虑根据该规律提前增排加强班。急诊科医护人员应加强对排名前位系统疾病的诊治流程进行优化及学习,并加强急诊外科建设。     

Prediction of individual response to antidepressants and antipsychotics: an integrated concept

In both clinical trials and daily practice, there can be substantial inter- and even intraindividual variability in response—whether beneficial or adverse—to antidepressants and antipsychotic medications. So far, no tools have become available to predict the outcome of these treatments in specific patients. This is because the causes of such variability are often not known, and when they are, there is no way of predicting the effects of their various potential combinations in an individual. Given this background, this paper presents a conceptual framework for understanding known factors and their combinations so that eventually clinicians can better predict what medication(s) to select and at what dose they can optimize the outcome for a given individual. This framework is flexible enough to be readily adaptable as new information becomes available. The causes of variation in patient response are grouped into four categories: (i) genetics; (ii) age; (iii) disease; and (iv) environment (internal). Four cases of increasing complexity are used to illustrate the applicability of this framework in a clinically relevant way In addition, this paper reviews tools that the clinician can use to assess for and quantify such inter- and intraindividual variability. With the information gained, treatment can be adjusted to compensate for such variability, in order to optimize outcome. Finally, the limitations of existing antidepressant and antipsychotic therapy and the way they reduce current ability to predict response is discussed.     

Informing the design of clinical decision support services for evaluation of children with minor blunt head trauma in the emergency department: A sociotechnical analysis

Integration of clinical decision support services (CDSS) into electronic health records (EHRs) may be integral to widespread dissemination and use of clinical prediction rules in the emergency department (ED). However, the best way to design such services to maximize their usefulness in such a complex setting is poorly understood. We conducted a multi-site cross-sectional qualitative study whose aim was to describe the sociotechnical environment in the ED to inform the design of a CDSS intervention to implement the Pediatric Emergency Care Applied Research Network (PECARN) clinical prediction rules for children with minor blunt head trauma. Informed by a sociotechnical model consisting of eight dimensions, we conducted focus groups, individual interviews and workflow observations in 11 EDs, of which 5 were located in academic medical centers and 6 were in community hospitals. A total of 126 ED clinicians, information technology specialists, and administrators participated. We clustered data into 19 categories of sociotechnical factors through a process of thematic analysis and subsequently organized the categories into a sociotechnical matrix consisting of three high-level sociotechnical dimensions (workflow and communication, organizational factors, human factors) and three themes (interdisciplinary assessment processes, clinical practices related to prediction rules, EHR as a decision support tool). Design challenges that emerged from the analysis included the need to use structured data fields to support data capture and re-use while maintaining efficient care processes, supporting interdisciplinary communication, and facilitating family-clinician interaction for decision-making.     

Rosiglitazone maleate + metformin hydrochloride extend: review of an emerging compound

Clinical practice guidelines from around the world have continued to highlight the importance of glycemic control in the prevention of diabetes complications. Despite the many tools available to achieve these targets, it remains a constant challenge for healthcare providers and patients alike. Rosiglitazone maleate + metformin hydrochloride extend is a new compound that has the advantage of the clinical experience and knowledge about the current version and the added benefit of being a once daily, single pill option. The existing version of rosiglitazone + metformin has been shown to effectively lower hemoglobin A1C, improve insulin sensitivity and minimize weight gain. It is expected that the new compound will also have similar features, with the added benefit of improved patient adherence given its once daily formulation.     

医疗失效模式与效应分析在药物基因实验质量管理的应用与实践

目的 通过应用医疗失效模式与效应分析(healthfailure mode and effect analysis，HFMEA)，预防药物基因实验的风险事件，提高药物基因实验的操作质量。方法 药学实验室成立失效模式与影响分析(failure mode and effect analysis，FMEA)活动小组，采用头脑风暴法，借助HFMEA模式，识别及分析药物基因实验过程前、中、后可能存在的操作、仪器及环境对药物基因实验质控造成的风险事件，同时制定相对应的解决方案。结果 开展HFMEA活动后，预防与补救了药物基因实验前、中、后的风险事件产生，风险系数值由总分值1 375分降至62.36分，降幅为95.47%(P<0.01)；活动小组成员在品管手法、解决问题能力、沟通配合、积极性等方面得到了显著提高。结论 HFMEA活动有助于降低药物基因实验产生风险事件的频次，有效提升实验室的质量管理。     

Opportunities for Improving Post-Hospital Home Medication Management Among Older Adults

SUMMARY

Effective post-hospital home medication management among older adults is a convoluted, error-prone process. Older adults, whose complex medication regimens are often changed at hospital discharge, are susceptible to medication-related problems (e.g., Adverse Drug Events or ADEs) as they resume responsibility for managing their medications at home. Human error theory frames the discussion of multi-faceted, interacting factors including care system functions, like discharge medication teaching that contribute to post-hospital ADEs. The taxonomy and causes of post-hospital ADEs and related risk factors are reviewed, as we describe in high-risk older adults a population that may benefit from targeted interventions. Potential solutions and future research possibilities highlight the importance of interdisciplinary teams, involvement of clinical pharmacists, use of transitional care models, and improved use of informational technologies.