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Low-value and high-value care recommendations in nursing: A systematic assessment of clinical practice guidelines. 护理中的低价值和高价值护理建议:临床实践指南的系统评估。
IF 2.4 3区 医学 Q1 NURSING Pub Date : 2024-11-20 DOI: 10.1111/jnu.13029
Wilmieke Bahlman-van Ooijen, Jeltje Giesen, Annick Bakker-Jacobs, Hester Vermeulen, Getty Huisman-de Waal
<p><strong>Introduction: </strong>The World Health Organization defines quality of care as providing effective, evidence-based care, and avoiding harm. Low-value care provides little or no benefit to the patient, causes harm, and wastes limited resources. In 2017, shortly after the start of the International Choosing Wisely campaign, the first Dutch nursing "Do-not-do" list was published and has become a widely used practical tool for nurses working in daily practice. However, over the last years new guidelines are published. Therefore, an update of the list is necessary with an addition of high-value care recommendations as alternative care practices for low-value care.</p><p><strong>Design/methods: </strong>In this study, a combination of designs was used. First, we searched Dutch clinical practice guidelines for low-value or high-value care recommendations. All nursing care recommendations were assessed and specified to several healthcare sectors, including hospital care, district care, nursing home care, disability care, and mental health care. Second, a prioritization among nurses regarding low-value care recommendations was done by a cross-sectional survey for each healthcare sector.</p><p><strong>Results: </strong>In total, 66 low-value care recommendations were found, for example, "avoid unnecessary layers under the patient at risk of pressure ulcers" and "never flush the bladder to prevent urinary tract infection." Furthermore, 414 high-value care recommendations were selected, such as "use the Barthel Index to assess and to evaluate the degree of ADL independence" and "application of cold therapy may be considered for oncological patients with pain." In total, 539 nurses from all healthcare sectors prioritized the low-value care recommendations, resulting in a top five low-value care practices per healthcare sector. The top five low-value care recommendations differed per healthcare sector, although "do not use physical restraints in case of a delirium" was prioritized by four out of five sectors.</p><p><strong>Conclusions: </strong>Assessing low-value and high-value care recommendations for nurses will help and inspire nurses to deliver fundamental care for their patients. These initiatives regarding low-value and high-value care are essential to generate a culture of continuous quality improvement based on evidence. This is also essential to meeting the current challenges of the healthcare delivery system.</p><p><strong>Clinical relevance: </strong>This paper provides an update of low-value care recommendations for nurses based on Dutch guidelines from 2017 to 2023, specified to five healthcare sectors, including hospital care, district care, nursing home care, disability care and mental health care, with an accompanying prioritization of these low-value care recommendations to facilitate de-implementation. This paper provides a first overview of high-value care recommendations to reflect on and create alternative care practices for l
导言:世界卫生组织对护理质量的定义是:提供有效的、以证据为基础的护理,并避免伤害。低价值护理对患者几乎没有益处,会造成伤害,并浪费有限的资源。2017 年,在国际明智选择运动开始后不久,第一份荷兰护理 "不做 "清单发布,并已成为护士在日常工作中广泛使用的实用工具。然而,最近几年又有新的指南发布。因此,有必要对该清单进行更新,增加高价值护理建议,作为低价值护理的替代护理措施:本研究采用了多种设计方法。首先,我们搜索了荷兰临床实践指南中的低价值或高价值护理建议。我们对所有护理建议进行了评估,并将其具体化到多个医疗保健部门,包括医院护理、地区护理、疗养院护理、残疾人护理和精神健康护理。其次,通过对各医疗部门进行横断面调查,在护士中对低价值护理建议进行优先排序:结果:总共发现了 66 项低价值护理建议,例如 "避免在有压疮风险的患者身下铺设不必要的垫层 "和 "绝不冲洗膀胱以预防尿路感染"。此外,还选出了 414 条高价值护理建议,如 "使用 Barthel 指数评估和评价 ADL 独立程度"、"肿瘤患者疼痛时可考虑应用冷疗法 "等。共有 539 名来自各医疗保健部门的护士对低价值护理建议进行了优先排序,从而得出了各医疗保健部门的五大低价值护理实践。虽然 "谵妄时不使用身体约束 "被五个医疗部门中的四个部门列为优先考虑事项,但每个医疗部门的前五名低价值护理建议并不相同:评估针对护士的低价值和高价值护理建议将有助于并激励护士为患者提供基础护理。这些有关低价值和高价值护理的倡议对于在证据的基础上形成持续改进质量的文化至关重要。这对于应对当前医疗保健服务体系的挑战也至关重要:本文根据 2017 年至 2023 年的荷兰指南,为护士提供了最新的低价值护理建议,具体到五个医疗保健领域,包括医院护理、地区护理、疗养院护理、残疾护理和心理健康护理,并同时对这些低价值护理建议进行了优先排序,以促进其取消实施。本文首先概述了高价值护理建议,以便对低价值护理进行反思并创建替代护理实践。有关低价值和高价值护理的建议对于形成一种以证据为基础不断改进适当性的文化至关重要,最终将提高护理质量并改善患者的预后。
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引用次数: 0
Missed nursing care: Expanding the research scope for a comprehensive understanding. 护理遗漏:扩大研究范围,全面了解情况。
IF 2.4 3区 医学 Q1 NURSING Pub Date : 2024-11-17 DOI: 10.1111/jnu.13035
Yanling He, Xuerong Zhang
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引用次数: 0
Response to a Letter to the Editor on "The Role of Nurses' Adherence to Clinical Safety Guidelines in Linking Nurse Practice Environment to Missed Nursing Care". 对 "护士遵守临床安全指南在将护士执业环境与护理服务缺失联系起来方面的作用 "的致编辑信的回复。
IF 2.4 3区 医学 Q1 NURSING Pub Date : 2024-11-17 DOI: 10.1111/jnu.13034
Leodoro J Labrague, Sulaiman Al Sabei, Raeda AbuAlRub, Ikram Burney, Omar Al Rawajfah
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引用次数: 0
Transcutaneous electrical acupoint stimulation for preventing postoperative nausea and vomiting after laparoscopic surgery: A meta-analysis. 经皮穴位电刺激用于预防腹腔镜手术后恶心和呕吐:荟萃分析。
IF 2.4 3区 医学 Q1 NURSING Pub Date : 2024-11-10 DOI: 10.1111/jnu.13033
Lu Yuan, Si-Jie Quan, Xin-Yu Li, Bo-Zhu Chen, Yan-Bing Huang, Hui Zheng

Background: Postoperative nausea and vomiting (PONV) is a common adverse event after general surgery. This study aimed to examine the effectiveness and safety of transcutaneous electrical acupoint stimulation (TEAS) for the prevention of nausea and vomiting after laparoscopic surgery.

Method: The Cochrane Library, Pubmed, Embase, and Web of Science databases were accessed from inception to 23 January 2024. The incidence of PONV was the primary outcome measure. The required information size (RIS) of each outcome was estimated by Trial sequential analysis (TSA). The RoB 2.0 tool was used to assess the risk of bias and GRADE to assess the quality of evidence.

Results: Seventeen RCTs including 3698 participants were included. In comparison to the control group, TEAS reduced the incidence of PONV (13 trials, n = 3310; RR, 0.56; 95% CI, 0.46-0.67; I2 = 64%; p < 0.01; RIS = 1100), with the level of evidence graded as low. TEAS reduced the incidence of PON (9 trials, n = 2762; RR, 0.64; 95% CI, 0.52-0.79; I2 = 57%, p < 0.01; RIS = 1595), and was also associated with a lower incidence of POV (9 trials, n = 2797; RR, 0.53; 95% CI, 0.45-0.63; I2 = 0%, p < 0.01; RIS = 773).

Conclusion: The current meta-analysis and TSA provide reliable evidence that TEAS is an effective and safe method to prevent PONV. It may reduce the workload of nursing professionals, alleviate emotional stress, and decrease exposure risk. Adverse events related to TEAS were mild.

Clinical relevance: Nurses can incorporate TEAS into the rehabilitation nursing of patients experiencing PONV.

背景:术后恶心和呕吐(PONV术后恶心和呕吐(PONV)是普外科手术后常见的不良反应。本研究旨在探讨经皮穴位电刺激(TEAS)预防腹腔镜手术后恶心和呕吐的有效性和安全性:方法:访问了从开始到 2024 年 1 月 23 日的 Cochrane Library、Pubmed、Embase 和 Web of Science 数据库。PONV的发生率是衡量研究结果的主要指标。通过试验序列分析(TSA)估算了每项结果所需的信息量(RIS)。使用 RoB 2.0 工具评估偏倚风险,使用 GRADE 评估证据质量:共纳入了 17 项 RCT,包括 3698 名参与者。与对照组相比,TEAS 降低了 PONV 的发生率(13 项试验,n = 3310;RR,0.56;95% CI,0.46-0.67;I2 = 64%;P 2 = 57%,P 2 = 0%,P 结论:TEAS 降低了 PONV 的发生率:当前的荟萃分析和 TSA 提供了可靠的证据,证明 TEAS 是预防 PONV 的有效、安全的方法。它可以减轻护理专业人员的工作量、缓解情绪压力并降低暴露风险。与 TEAS 相关的不良事件较轻:护士可将 TEAS 纳入对 PONV 患者的康复护理中。
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引用次数: 0
Beneficial effects of non-pharmacological interventions for post-stroke pain: A meta-analysis. 非药物干预对中风后疼痛的益处:荟萃分析
IF 2.4 3区 医学 Q1 NURSING Pub Date : 2024-11-08 DOI: 10.1111/jnu.13032
Ita Daryanti Saragih, Ira Suarilah, Mulyadi Mulyadi, Ice Septriani Saragih, Bih-O Lee

Purpose: Pain is a frequent post-stroke health concern, and several non-pharmacological interventions are commonly employed to manage it. However, few reviews have examined the effectiveness of such interventions, making it difficult to draw conclusions about their usefulness. Furthermore, subgroup analysis based on post-stroke pain level or intervention characteristics is rarely performed. This study aimed to investigate the effectiveness of non-pharmacological interventions and evaluate the significant factors associated with post-stroke pain through subgroup analysis.

Design: Systematic review and meta-analysis.

Methods: Relevant studies were obtained from seven databases, from their commencement up to March 2024, as well as from the gray literature. The PICOS approach was used to evaluate the eligibility criteria of the studies. The RoB-2 tool was used to determine the risk of bias in each randomized trial. Pooled estimations of standardized mean difference and heterogeneity (quantified with I2) were obtained using a random-effects model. The stability of the pooled result was then assessed using the leave-one-out approach. STATA 17.0 was used to run the meta-analysis.

Findings: Non-pharmacological interventions were effective in reducing pain immediately after intervention (pooled SMDs: -0.79; 95% confidence interval [CI]: -1.06 to -0.53; p < 0.001). The approach involving acupuncture, aquatic therapy, or laser therapy and rehabilitation training was effective for post-stroke hemiplegic shoulder pain. A pooled analysis of non-pharmacological interventions showed that both less than 4 weeks and more than 4 weeks of interventions were effective in alleviating pain in stroke patients.

Conclusion: Non-pharmacological approaches appear to be beneficial for reducing post-stroke pain. The outcomes based on the modalities merit further research.

Clinical relevance: Further studies are needed to determine the effects of different modalities on pain intensity following a stroke. Furthermore, to avoid overestimation of intervention efficacy, future randomized trials should consider blinding approaches to the interventions delivered.

目的:疼痛是中风后经常出现的健康问题,通常会采用一些非药物干预措施来控制疼痛。然而,很少有综述对这些干预措施的有效性进行研究,因此很难就其有用性得出结论。此外,基于卒中后疼痛程度或干预特点的亚组分析也很少进行。本研究旨在调查非药物干预的有效性,并通过亚组分析评估与卒中后疼痛相关的重要因素:设计:系统回顾和荟萃分析:从七个数据库(从开始到 2024 年 3 月)以及灰色文献中获取相关研究。采用 PICOS 方法评估研究的资格标准。采用 RoB-2 工具确定每项随机试验的偏倚风险。采用随机效应模型对标准化均值差异和异质性(用 I2 量化)进行汇总估算。然后采用 "留一剔除 "法评估汇总结果的稳定性。荟萃分析使用 STATA 17.0 进行:结果:非药物干预能有效减轻干预后的疼痛(汇总 SMDs:-0.79;95% 置信区间 [CI]:-1.06 至 -0.53;P 结论:非药物干预能有效减轻干预后的疼痛(汇总 SMDs:-0.79;95% 置信区间 [CI]:-1.06 至 -0.53):非药物治疗方法似乎有利于减轻卒中后疼痛。基于这些方法的结果值得进一步研究:临床相关性:需要进一步研究确定不同方式对中风后疼痛强度的影响。此外,为避免高估干预效果,未来的随机试验应考虑对所提供的干预措施进行盲法。
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引用次数: 0
Developing a clinical decision support framework for integrating predictive models into routine nursing practices in home health care for patients with heart failure. 开发临床决策支持框架,将预测模型纳入心力衰竭患者家庭医疗的常规护理实践。
IF 2.4 3区 医学 Q1 NURSING Pub Date : 2024-11-07 DOI: 10.1111/jnu.13030
Sena Chae, Anahita Davoudi, Jiyoun Song, Lauren Evans, Kathryn H Bowles, Margaret V Mcdonald, Yolanda Barrón, Se Hee Min, Sungho Oh, Danielle Scharp, Zidu Xu, Maxim Topaz
<p><strong>Background: </strong>The healthcare industry increasingly values high-quality and personalized care. Patients with heart failure (HF) receiving home health care (HHC) often experience hospitalizations due to worsening symptoms and comorbidities. Therefore, close symptom monitoring and timely intervention based on risk prediction could help HHC clinicians prevent emergency department (ED) visits and hospitalizations. This study aims to (1) describe important variables associated with a higher risk of ED visits and hospitalizations in HF patients receiving HHC; (2) map data requirements of a clinical decision support (CDS) tool to the exchangeable data standard for integrating a CDS tool into the care of patients with HF; (3) outline a pipeline for developing a real-time artificial intelligence (AI)-based CDS tool.</p><p><strong>Methods: </strong>We used patient data from a large HHC organization in the Northeastern US to determine the factors that can predict ED visits and hospitalizations among patients with HF in HHC (9362 patients in 12,223 care episodes). We examined vital signs, HHC visit details (e.g., the purpose of the visit), and clinical note-derived variables. The study identified critical factors that can predict ED visits and hospitalizations and used these findings to suggest a practical CDS tool for nurses. The tool's proposed design includes a system that can analyze data quickly to offer timely advice to healthcare clinicians.</p><p><strong>Results: </strong>Our research showed that the length of time since a patient was admitted to HHC and how recently they have shown symptoms of HF were significant factors predicting an adverse event. Additionally, we found this information from the last few HHC visits before the occurrence of an ED visit or hospitalization were particularly important in the prediction. One hundred percent of clinical demographic profiles from the Outcome and Assessment Information Set variables were mapped to the exchangeable data standard, while natural language processing-driven variables couldn't be mapped due to their nature, as they are generated from unstructured data. The suggested CDS tool alerts nurses about newly emerging or rising risks, helping them make informed decisions.</p><p><strong>Conclusions: </strong>This study discusses the creation of a time-series risk prediction model and its potential CDS applications within HHC, aiming to enhance patient outcomes, streamline resource utilization, and improve the quality of care for individuals with HF.</p><p><strong>Clinical relevance: </strong>This study provides a detailed plan for a CDS tool that uses the latest AI technology designed to aid nurses in their day-to-day HHC service. Our proposed CDS tool includes an alert system that serves as a guard rail to prevent ED visits and hospitalizations. This tool can potentially improve how nurses make decisions and improve patient outcomes by providing early warnings about ED visits and hospit
背景:医疗保健行业越来越重视高质量和个性化的护理。接受家庭健康护理(HHC)的心力衰竭(HF)患者常常因症状和合并症恶化而住院。因此,基于风险预测的密切症状监测和及时干预可帮助家庭健康护理临床医生预防急诊室就诊和住院。本研究旨在:(1)描述接受 HHC 治疗的高血压患者中与急诊室就诊和住院风险较高相关的重要变量;(2)将临床决策支持(CDS)工具的数据要求映射到可交换数据标准,以便将 CDS 工具整合到高血压患者的护理中;(3)概述开发基于人工智能(AI)的实时 CDS 工具的流程:我们使用了美国东北部一家大型 HHC 机构的患者数据,以确定可预测 HHC 中高血压患者急诊室就诊和住院的因素(12223 个护理事件中的 9362 名患者)。我们检查了生命体征、HHC 就诊详情(如就诊目的)和临床笔记衍生变量。研究确定了可以预测急诊室就诊和住院的关键因素,并利用这些发现为护士提出了一种实用的 CDS 工具。该工具的设计建议包括一个可以快速分析数据的系统,以便及时向医疗临床医生提供建议:我们的研究结果表明,患者入院时间的长短以及最近出现高血压症状的时间是预测不良事件的重要因素。此外,我们还发现,在急诊室就诊或住院之前的最后几次 HHC 就诊信息在预测中尤为重要。结果和评估信息集变量中的临床人口统计学特征百分之百被映射到可交换数据标准中,而自然语言处理驱动的变量由于其性质无法映射,因为它们是由非结构化数据生成的。建议的 CDS 工具可提醒护士注意新出现或上升的风险,帮助他们做出明智的决定:本研究讨论了时间序列风险预测模型的创建及其在 HHC 中的潜在 CDS 应用,旨在提高患者预后、简化资源利用、改善高血压患者的护理质量:本研究提供了一个 CDS 工具的详细计划,该工具采用最新的人工智能技术,旨在帮助护士开展日常的 HHC 服务。我们提议的 CDS 工具包括一个警报系统,可作为防止急诊室就诊和住院的防护栏。该工具有可能改善护士的决策方式,并通过提供急诊室就诊和住院的预警来改善患者的治疗效果。
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引用次数: 0
Reflections on nursing leadership in socio-contextual and interconnected global scenarios 在社会背景和相互关联的全球环境下对护理领导力的思考。
IF 2.4 3区 医学 Q1 NURSING Pub Date : 2024-11-05 DOI: 10.1111/jnu.13031
Alessandro Stievano RN, PhD, FAAN, Franklin Shaffer RN, EdD, FAAN
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引用次数: 0
Precision health: Determining the capacity of practicing nurses across the United States. 精准健康:确定全美执业护士的能力。
IF 2.4 3区 医学 Q1 NURSING Pub Date : 2024-10-26 DOI: 10.1111/jnu.13028
Evangeline Fangonil-Gagalang, Mary Anne Schultz, Laurie A Huryk, Pamela A Payne, Anna E Schoenbaum, Kimberly Velez

Introduction: Precision Health (PH) holds the promise of revolutionizing healthcare by enabling personalized disease prevention and management through the integration of genomic data, lifestyle factors, environmental influences, and other social determinants of health (SDoH). However, the absence of a baseline assessment of knowledge, skills, and attitudes (KSAs) of practicing nurses' capacity for PH hinders its integration. The purpose of this study is to determine the capacity of practicing Registered Nurses (RNs) for PH across the United States and to assess the validity and reliability of a tool designed for this use-the Precision Health Nurse Capacity Scale (PHNCS).

Design/method: A descriptive exploratory study was conducted to evaluate the capacity of practicing RNs for this evolving phenomenon, PH, using a convenience sample. The survey was sent via email and made available to all members of the American Nurses Association (ANA) who work in a variety of practice environments. The ANA represents the over 4 million nurses practicing in the United States.

Results: The majority of nurse respondents felt it is important for nurses to become more educated about all aspects of PH including SDoH but they lack confidence in the integration of PH. The PHNCS was found to be a valid and reliable tool in measuring the capacity of nurses to practice PH.

Conclusion: The incorporation of PH into nursing practice suffers an immediate impediment: the lack of know-how of the US nursing workforce. This inaugural data on KSAs for PH establishes a logical baseline from which the requisite education and training should commence.

Clinical relevance: Precision Health is an emerging healthcare approach in the United States and globally. Enabling it will require a nursing workforce prepared with the requisite KSAs. Determining the capacity of the nursing workforce is a foundational step to begin this process.

导言:通过整合基因组数据、生活方式因素、环境影响和其他健康的社会决定因素(SDoH),实现个性化的疾病预防和管理,精准健康(PH)有望彻底改变医疗保健。然而,由于缺乏对执业护士 PH 能力的知识、技能和态度 (KSA) 的基线评估,阻碍了 PH 的整合。本研究旨在确定全美执业注册护士(RNs)的 PH 能力,并评估为此设计的工具--精准健康护士能力量表(PHNCS)的有效性和可靠性:设计/方法: 我们进行了一项描述性探索研究,通过方便抽样调查来评估执业护士在 PH 这一不断发展的现象方面的能力。调查通过电子邮件发送给美国护士协会(ANA)的所有会员,他们在各种实践环境中工作。ANA 代表了在美国执业的 400 多万名护士:结果:大多数受访护士认为,护士必须更多地了解包括 SDoH 在内的公共卫生的各个方面,但他们对公共卫生的整合缺乏信心。PHNCS被认为是衡量护士从事卫生保健实践能力的有效而可靠的工具:将公共卫生纳入护理实践的直接障碍是:美国护理人员缺乏专业知识。这项关于健康护理关键能力标准的开创性数据建立了一个合理的基线,必要的教育和培训应从这个基线开始:临床相关性:"精准医疗 "是美国乃至全球新兴的医疗保健方法。要实现这一目标,护理人员必须具备必要的 KSA。确定护理人员队伍的能力是开始这一进程的基础步骤。
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引用次数: 0
Effectiveness of integrated care models for stroke patients: A systematic review and meta-analysis. 中风患者综合护理模式的有效性:系统回顾与荟萃分析。
IF 2.4 3区 医学 Q1 NURSING Pub Date : 2024-09-24 DOI: 10.1111/jnu.13027
Beixue Liu, Jingyi Cai, Lanshu Zhou

Introduction: Given that stroke is a leading cause of disability and mortality worldwide, there is an urgent need for a coordinated healthcare approach to mitigate its effects. The objectives of this study were to perform a systematic review and meta-analysis of stroke integrated care models and develop recommendations for a representative model.

Design: A systematic review and meta-analysis.

Methods: The literature search identified randomized controlled trials comparing integrated care models with standard care for stroke patients. The included studies followed PICOs inclusion criteria. The qualitative analysis included creating a flowchart for the literature screening process, and tables detailing the basic characteristics of the included studies, the adherence to the ten principles and the results of the quality assessments. Subsequently, quantitative meta-analytical procedures were conducted to statistically pool the data and quantify the effects of the integrated care models on stroke patients' health-related quality of life, activities of daily living, and depression. The China National Knowledge Infrastructure (CNKI), Wanfang Data, Chongqing VIP Chinese Science and Technology Periodical Database (VIP), China Biology Medicine Disc (CBMDISC), Cochrane Library, Cumulated Index to Nursing and Allied Health Literature (CINAHL), PubMed, Web of Science, Embase, Google Scholar, and Clinical Trials were searched from inception to March 13, 2024.

Results: Of the 2547 obtained articles, 19 were systematically reviewed and 15 were included in the meta-analysis. The integrated care models enhanced stroke patients' health-related quality of life, ability to perform activities of daily living, and reduced depression. Adherence to the 10 principles varied: comprehensive services, patient focus, and standardized care delivery had strong implementation, while gaps were noted in geographic coverage, information systems, governance structures, and financial management.

Conclusion: Integrated care models improve outcomes for stroke patients and adherence to the 10 principles is vital for their implementation success. This study's findings call for a more standardized approach to implementing integrated care models, emphasizing the need for integrated services, patient-centred care, and interdisciplinary collaboration, while also addressing the identified gaps in terms of integration efforts.

Clinical relevance: This study provides evidence-based recommendations on the most effective integrated care approaches for stroke patients, potentially leading to better patient outcomes, reduced healthcare costs, and improved quality of life.

导言:鉴于脑卒中是全球致残和致死的主要原因,迫切需要一种协调的医疗保健方法来减轻其影响。本研究的目的是对中风综合治疗模式进行系统回顾和荟萃分析,并为具有代表性的模式提出建议:设计:系统综述和荟萃分析:方法:文献检索确定了比较卒中患者综合护理模式与标准护理的随机对照试验。纳入的研究遵循 PICOs 纳入标准。定性分析包括创建文献筛选流程图,以及详细列出纳入研究基本特征、遵守十项原则情况和质量评估结果的表格。随后,进行了定量荟萃分析程序,以统计汇总数据并量化综合护理模式对脑卒中患者健康相关生活质量、日常生活活动和抑郁的影响。研究人员检索了中国国家知识基础设施(CNKI)、万方数据、重庆VIP中文科技期刊数据库(VIP)、中国生物医学文献数据库(CBMDISC)、Cochrane图书馆、护理与联合健康文献累积索引(CINAHL)、PubMed、Web of Science、Embase、Google Scholar和临床试验等数据库:结果:在获得的 2547 篇文章中,有 19 篇进行了系统回顾,15 篇纳入了荟萃分析。综合护理模式提高了脑卒中患者与健康相关的生活质量、日常生活能力并减少了抑郁。对 10 项原则的遵守情况各不相同:综合服务、以患者为中心和标准化医疗服务的实施力度较大,而在地理覆盖范围、信息系统、治理结构和财务管理方面则存在差距:结论:综合护理模式可改善卒中患者的预后,而遵守 10 项原则对其成功实施至关重要。本研究结果呼吁采用更加标准化的方法来实施综合护理模式,强调综合服务、以患者为中心的护理和跨学科合作的必要性,同时也指出了在整合工作方面存在的差距:本研究就中风患者最有效的综合护理方法提出了循证建议,有可能改善患者预后、降低医疗成本并提高生活质量。
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引用次数: 0
Decoding machine learning in nursing research: A scoping review of effective algorithms. 解码护理研究中的机器学习:有效算法范围综述。
IF 3.4 3区 医学 Q1 NURSING Pub Date : 2024-09-18 DOI: 10.1111/jnu.13026
Jeeyae Choi,Hanjoo Lee,Yeounsoo Kim-Godwin
INTRODUCTIONThe rapid evolution of artificial intelligence (AI) technology has revolutionized healthcare, particularly through the integration of AI into health information systems. This transformation has significantly impacted the roles of nurses and nurse practitioners, prompting extensive research to assess the effectiveness of AI-integrated systems. This scoping review focuses on machine learning (ML) used in nursing, specifically investigating ML algorithms, model evaluation methods, areas of focus related to nursing, and the most effective ML algorithms.DESIGNThe scoping review followed the Preferred Reporting Items for Systematic Review and Meta-Analysis Extension for Scoping Reviews (PRISMA-ScR) guidelines.METHODSA structured search was performed across seven databases according to PRISMA-ScR: PubMed, EMBASE, CINAHL, Web of Science, OVID, PsycINFO, and ProQuest. The quality of the final reviewed studies was assessed using the Medical Education Research Study Quality Instrument (MERSQI).RESULTSTwenty-six articles published between 2019 and 2023 met the inclusion and exclusion criteria, and 46% of studies were conducted in the US. The average MERSQI score was 12.2, indicative of moderate- to high-quality studies. The most used ML algorithm was Random Forest. The four second-most used were logistic regression, least absolute shrinkage and selection operator, decision tree, and support vector machine. Most ML models were evaluated by calculating sensitivity (recall)/specificity, accuracy, receiver operating characteristic (ROC), area under the ROC (AUROC), and positive/negative prediction value (precision). Half of the studies focused on nursing staff or students and hospital readmission or emergency department visits. Only 11 articles reported the most effective ML algorithm(s).CONCLUSIONThe scoping review provides insights into the current status of ML research in nursing and recognition of its significance in nursing research, confirming the benefits of ML in healthcare. Recommendations include incorporating experimental designs in research studies to optimize the use of ML models across various nursing domains.CLINICAL RELEVANCEThe scoping review demonstrates substantial clinical relevance of ML applications for nurses, nurse practitioners, administrators, and researchers. The integration of ML into healthcare systems and its impact on nursing practices have important implications for patient care, resource management, and the evolution of nursing research.
引言 人工智能(AI)技术的快速发展给医疗保健带来了革命性的变化,特别是通过将人工智能整合到医疗信息系统中。这一变革极大地影响了护士和执业护士的角色,促使人们对人工智能集成系统的有效性进行广泛研究。本范围界定综述重点关注护理领域中使用的机器学习(ML),特别调查了ML算法、模型评估方法、与护理相关的重点领域以及最有效的ML算法。METHOD根据PRISMA-ScR在以下七个数据库中进行了结构化检索:PubMed、EMBASE、CINAHL、Web of Science、OVID、PsycINFO和ProQuest。结果2019年至2023年间发表的26篇文章符合纳入和排除标准,46%的研究在美国进行。MERSQI 平均得分为 12.2 分,表明研究的质量为中上等。使用最多的 ML 算法是随机森林算法。其次是逻辑回归、最小绝对收缩和选择算子、决策树和支持向量机。大多数 ML 模型都是通过计算灵敏度(召回率)/特异性、准确性、接收者操作特征(ROC)、ROC 下面积(AUROC)和正/负预测值(精确度)来进行评估的。半数研究的重点是护理人员或学生以及再入院或急诊就诊情况。只有 11 篇文章报告了最有效的 ML 算法。结论 该范围界定综述深入分析了护理领域 ML 研究的现状,并认识到其在护理研究中的重要性,证实了 ML 在医疗保健中的益处。建议包括在研究中采用实验设计,以优化 ML 模型在各个护理领域的使用。临床意义范围界定综述表明,ML 应用与护士、执业护士、管理人员和研究人员的临床工作密切相关。将 ML 融入医疗保健系统及其对护理实践的影响对患者护理、资源管理和护理研究的发展具有重要意义。
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Journal of Nursing Scholarship
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