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.
Design/methods
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.
Results
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.
Conclusions
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.
{"title":"Low-value and high-value care recommendations in nursing: A systematic assessment of clinical practice guidelines","authors":"Wilmieke Bahlman-van Ooijen, Jeltje Giesen, Annick Bakker-Jacobs, Hester Vermeulen, Getty Huisman-de Waal","doi":"10.1111/jnu.13029","DOIUrl":"10.1111/jnu.13029","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>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>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design/methods</h3>\u0000 \u0000 <p>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>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>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>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>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>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 ","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":"57 3","pages":"486-499"},"PeriodicalIF":2.9,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jnu.13029","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142683433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Leodoro J. Labrague RN, DM, PhD, CNE, Sulaiman Al Sabei RN, PhD, Raeda AbuAlRub RN, PhD, Ikram Burney MD, Omar Al Rawajfah RN, PhD, FAAN
{"title":"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”","authors":"Leodoro J. Labrague RN, DM, PhD, CNE, Sulaiman Al Sabei RN, PhD, Raeda AbuAlRub RN, PhD, Ikram Burney MD, Omar Al Rawajfah RN, PhD, FAAN","doi":"10.1111/jnu.13034","DOIUrl":"10.1111/jnu.13034","url":null,"abstract":"","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":"57 1","pages":"179-180"},"PeriodicalIF":2.9,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142648780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Missed nursing care: Expanding the research scope for a comprehensive understanding","authors":"Yanling He, Xuerong Zhang","doi":"10.1111/jnu.13035","DOIUrl":"10.1111/jnu.13035","url":null,"abstract":"","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":"57 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142647825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lu Yuan MD, Si-Jie Quan MD, Xin-Yu Li MD, Bo-Zhu Chen MD, Yan-Bing Huang MD, Hui Zheng MD, Ph.D
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.
{"title":"Transcutaneous electrical acupoint stimulation for preventing postoperative nausea and vomiting after laparoscopic surgery: A meta-analysis","authors":"Lu Yuan MD, Si-Jie Quan MD, Xin-Yu Li MD, Bo-Zhu Chen MD, Yan-Bing Huang MD, Hui Zheng MD, Ph.D","doi":"10.1111/jnu.13033","DOIUrl":"10.1111/jnu.13033","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Method</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Seventeen RCTs including 3698 participants were included. In comparison to the control group, TEAS reduced the incidence of PONV (13 trials, <i>n</i> = 3310; RR, 0.56; 95% CI, 0.46–0.67; <i>I</i><sup>2</sup> = 64%; <i>p</i> < 0.01; RIS = 1100), with the level of evidence graded as low. TEAS reduced the incidence of PON (9 trials, <i>n</i> = 2762; RR, 0.64; 95% CI, 0.52–0.79; <i>I</i><sup>2</sup> = 57%, <i>p</i> < 0.01; RIS = 1595), and was also associated with a lower incidence of POV (9 trials, <i>n</i> = 2797; RR, 0.53; 95% CI, 0.45–0.63; <i>I</i><sup>2</sup> = 0%, <i>p</i> < 0.01; RIS = 773).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Clinical Relevance</h3>\u0000 \u0000 <p>Nurses can incorporate TEAS into the rehabilitation nursing of patients experiencing PONV.</p>\u0000 </section>\u0000 </div>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":"57 3","pages":"371-379"},"PeriodicalIF":2.9,"publicationDate":"2024-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142632013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ita Daryanti Saragih MSN, RN, Ira Suarilah PhD, RN, Mulyadi Mulyadi PhD, RN, Ice Septriani Saragih MSN, RN, Bih-O Lee PhD, RN
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.
{"title":"Beneficial effects of non-pharmacological interventions for post-stroke pain: A meta-analysis","authors":"Ita Daryanti Saragih MSN, RN, Ira Suarilah PhD, RN, Mulyadi Mulyadi PhD, RN, Ice Septriani Saragih MSN, RN, Bih-O Lee PhD, RN","doi":"10.1111/jnu.13032","DOIUrl":"10.1111/jnu.13032","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design</h3>\u0000 \u0000 <p>Systematic review and meta-analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>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 <i>I</i><sup>2</sup>) 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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Findings</h3>\u0000 \u0000 <p>Non-pharmacological interventions were effective in reducing pain immediately after intervention (pooled SMDs: −0.79; 95% confidence interval [CI]: −1.06 to −0.53; <i>p</i> < 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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Non-pharmacological approaches appear to be beneficial for reducing post-stroke pain. The outcomes based on the modalities merit further research.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Clinical relevance</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 </div>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":"57 2","pages":"239-252"},"PeriodicalIF":2.9,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142607311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sena Chae, Anahita Davoudi, Jiyoun Song, Lauren Evans, Kathryn H. Bowles, Margaret V. Mcdonald, Yolanda Barrón, Se Hee Min PhD, RN, Sungho Oh PhD, Danielle Scharp MSN, RN, Zidu Xu MMed, BS, RN, Maxim Topaz
<div> <section> <h3> Background</h3> <p>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> </section> <section> <h3> Methods</h3> <p>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> </section> <section> <h3> Results</h3> <p>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> </section> <section> <h3> Conclusions</h3> <p>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
{"title":"Developing a clinical decision support framework for integrating predictive models into routine nursing practices in home health care for patients with heart failure","authors":"Sena Chae, Anahita Davoudi, Jiyoun Song, Lauren Evans, Kathryn H. Bowles, Margaret V. Mcdonald, Yolanda Barrón, Se Hee Min PhD, RN, Sungho Oh PhD, Danielle Scharp MSN, RN, Zidu Xu MMed, BS, RN, Maxim Topaz","doi":"10.1111/jnu.13030","DOIUrl":"10.1111/jnu.13030","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>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>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>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>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>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>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>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","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":"57 1","pages":"165-177"},"PeriodicalIF":2.9,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11771534/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142607312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alessandro Stievano RN, PhD, FAAN, Franklin Shaffer RN, EdD, FAAN
{"title":"Reflections on nursing leadership in socio-contextual and interconnected global scenarios","authors":"Alessandro Stievano RN, PhD, FAAN, Franklin Shaffer RN, EdD, FAAN","doi":"10.1111/jnu.13031","DOIUrl":"10.1111/jnu.13031","url":null,"abstract":"","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":"56 6","pages":"755-756"},"PeriodicalIF":2.9,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142585026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Evangeline Fangonil-Gagalang PhD, MSN, RN, Mary Anne Schultz PhD, MBA, MSN, RN, FAAN, Laurie A. Huryk MSN, RN-BC, Pamela A. Payne DBe, MSN, WHNP-BC (NCC-E), Anna E. Schoenbaum DNP, MS, RN-BC, FHIMSS, Kimberly Velez MSN, RN
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.
{"title":"Precision health: Determining the capacity of practicing nurses across the United States","authors":"Evangeline Fangonil-Gagalang PhD, MSN, RN, Mary Anne Schultz PhD, MBA, MSN, RN, FAAN, Laurie A. Huryk MSN, RN-BC, Pamela A. Payne DBe, MSN, WHNP-BC (NCC-E), Anna E. Schoenbaum DNP, MS, RN-BC, FHIMSS, Kimberly Velez MSN, RN","doi":"10.1111/jnu.13028","DOIUrl":"10.1111/jnu.13028","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>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 <i>purpose</i> 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).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design/Method</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The majority of nurse respondents felt it is important for nurses to become <i>more educated</i> 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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Clinical relevance</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 </div>","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":"57 2","pages":"314-328"},"PeriodicalIF":2.9,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142512539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<div> <section> <h3> Introduction</h3> <p>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.</p> </section> <section> <h3> Design</h3> <p>A systematic review and meta-analysis.</p> </section> <section> <h3> Methods</h3> <p>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.</p> </section> <section> <h3> Results</h3> <p>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.</p> </section> <section> <h3> Conclusion</h3> <p>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.
{"title":"Effectiveness of integrated care models for stroke patients: A systematic review and meta-analysis","authors":"Beixue Liu BSN, Jingyi Cai BSN, Lanshu Zhou PhD","doi":"10.1111/jnu.13027","DOIUrl":"10.1111/jnu.13027","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design</h3>\u0000 \u0000 <p>A systematic review and meta-analysis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>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.","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":"57 2","pages":"266-297"},"PeriodicalIF":2.9,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142309055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<div> <section> <h3> Introduction</h3> <p>The 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.</p> </section> <section> <h3> Design</h3> <p>The scoping review followed the Preferred Reporting Items for Systematic Review and Meta-Analysis Extension for Scoping Reviews (PRISMA-ScR) guidelines.</p> </section> <section> <h3> Methods</h3> <p>A 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).</p> </section> <section> <h3> Results</h3> <p>Twenty-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).</p> </section> <section> <h3> Conclusion</h3> <p>The 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.</p> </section> <section> <h3> Clinical Relevance</h3>
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。
{"title":"Decoding machine learning in nursing research: A scoping review of effective algorithms","authors":"Jeeyae Choi PhD, RN, Hanjoo Lee MS, Yeounsoo Kim-Godwin PhD, RN","doi":"10.1111/jnu.13026","DOIUrl":"10.1111/jnu.13026","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>The 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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design</h3>\u0000 \u0000 <p>The scoping review followed the Preferred Reporting Items for Systematic Review and Meta-Analysis Extension for Scoping Reviews (PRISMA-ScR) guidelines.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A 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).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Twenty-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).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The 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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Clinical Relevance</h3>\u0000 \u0000 ","PeriodicalId":51091,"journal":{"name":"Journal of Nursing Scholarship","volume":"57 1","pages":"119-129"},"PeriodicalIF":2.9,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jnu.13026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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