{"title":"Methodological progress note: Pilot randomized controlled trials","authors":"Amanda Corley RN PhD, Nicole Marsh RN PhD, Samantha Keogh RN PhD","doi":"10.1002/jhm.13376","DOIUrl":"10.1002/jhm.13376","url":null,"abstract":"<p>Definitive randomized controlled trials (RCTs) are the cornerstone of evidence-based medicine but can be complicated, protracted, and expensive. Given the challenges of large-scale trials, pilot trials serve as a crucial initial step, allowing for refinement and validation before embarking on the definitive RCT.<span><sup>1</sup></span> They are a crucial element of good study design and, while conducting a pilot RCT does not guarantee success of the definitive RCT, it increases the likelihood of successful trial completion.<span><sup>2</sup></span> More than US$100 billion is invested annually in biomedical research but often this research is conducted wastefully from poor study design and/or study procedures.<span><sup>3</sup></span> Conducting a well-designed pilot RCT before launching an expensive, time-consuming definitive trial can minimize research waste and improve study conduct.</p><p>Small RCTs cannot be branded pilot or feasibility trials to justify a small sample size. Pilot RCTs have a very specific purpose and inform future trial conduct.<span><sup>4</sup></span> Indeed, research models, including the Canadian Critical Care Trials Group programmatic model, the UK Medical Research Council, and the Australian Clinical Trials Alliance, highlight the importance of pilot RCTs as an integral and necessary step in interventional clinical research (Figure 1). Early piloting of research methods and interventions is important in evaluating feasibility and acceptability before the definitive RCT.</p><p>The importance of pilot trials has been acknowledged for decades<span><sup>5</sup></span> with trial methods evolving over time. It is within this context that we will discuss pilot RCTs used to inform larger definitive RCTs. We will situate pilot trial methods within a larger research framework and propose important concepts in design and reporting.</p><p>The terms “pilot” and “feasibility” trial are used interchangeably by some, but others purport that each type of trial has unique characteristics and therefore define them separately. Whitehead et al.<span><sup>4</sup></span> proposed that pilot trials are a type of feasibility trial with some distinguishing elements: (i) stricter methodology (closely following the definitive study design); (ii) intended to lead to further work; (iii) a smaller version of the larger study; and (iv) focuses on trial processes. This delineation suggests that a pilot RCT is a specific subset of feasibility trial. Henceforth, we adopt the term “pilot.”</p><p>Pilot RCTs allow researchers to test and establish feasibility of the study protocol, study processes, data collection, and intervention fidelity and acceptability.<span><sup>2, 4, 6</sup></span> Table 1 details trial elements tested by a pilot RCT.</p><p>An important indicator of trial feasibility is the ability to recruit the required numbers of participants, using inclusion/exclusion criteria, from the sample population. Recruitment to RCTs can be challe","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"19 9","pages":"821-826"},"PeriodicalIF":2.4,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jhm.13376","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140659039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Suchita S. Sata MD, FACP, SFHM, Samir S. Shah MD, MSCE, MHM
{"title":"Innovations Corner: A new column in the Journal of Hospital Medicine","authors":"Suchita S. Sata MD, FACP, SFHM, Samir S. Shah MD, MSCE, MHM","doi":"10.1002/jhm.13369","DOIUrl":"10.1002/jhm.13369","url":null,"abstract":"<p>The <i>Journal of Hospital Medicine</i> (JHM) is dedicated to advancing the practice and science of inpatient medicine. As part of our commitment to supporting hospitalists in their pursuit of excellence, we proudly introduce Innovations Corner, a new article type in the journal. We designed Innovations Corner to provide a forum to share inventive solutions to vexing problems encountered by clinicians or patients in the inpatient setting. These short reports are structured to highlight the innovation and its impact and to provide readers with tools to accelerate change in their institutions (Table 1).</p><p>Hospitalists innovate locally and transform globally. JHM's Innovations Corner celebrates the ingenuity of hospitalists while serving as a platform for scalability and shared innovation. Reports in Innovations Corner describe care improvement interventions, emphasizing the process of progress. We welcome submissions that address common challenges for patients, teams, and institutions. We seek reports on innovations in any aspect of care delivery that have the potential for adaptation or scalability. We anticipate that published articles will use a wide array of methodological approaches and apply them to the quotidian issues that arise during the provision of care. Topics of particular interest include common systems challenges that affect patients or clinicians, resource stewardship, patient safety measures, and innovative care pathways. Submissions showcasing interdisciplinary teams or patient involvement are encouraged.</p><p>In this issue,<span><sup>1</sup></span> Sanders et al. describe their efforts to improve inpatient glycemic control through a multifaceted intervention. Their sustained and safe improvement methods can be adopted by other institutions.</p><p>Each article will also be accompanied by a graphical summary, “Driving Change: Keys to Innovation.” This summary visually communicates key components of the innovation and was designed for sharing with administrative stakeholders. This section of Innovations Corner prioritizes readability and visual appeal to convey the salient messages. We understand that frontline clinicians need to communicate succinctly and effectively about complex problems with those who may lack medical training or a nuanced understanding of the care system. In titling this graphical summary, “Driving Change: Keys to Innovation,” we signal that hospitalists are in the driver's seat, accelerating improvement and paving a path of progress.</p><p>Sharing these innovations allows hospitalists to leverage peer wisdom to improve patient care, enhance outcomes, and make meaningful advancements in the field. We seek to foster collaboration and knowledge-sharing among inpatient clinicians to help them work smarter, build upon successes, reduce redundancies, and ensure that the wheel of innovation turns towards benefiting patients, healthcare providers, and the entire healthcare system.</p><p>The authors declare no","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"19 6","pages":"447-448"},"PeriodicalIF":2.6,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jhm.13369","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140673841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michael J. Tchou MD, MSc, Matt Hall PhD, Jessica L. Markham MD, MSc, John R. Stephens MD, Michael J. Steiner MD, MPH, Elisha McCoy MD, Paul L. Aronson MD, MHS, Samir S. Shah MD, MSCE, Matthew J. Molloy MD, MPH, Jillian M. Cotter MD, MSCS
{"title":"Changing patterns of routine laboratory testing over time at children's hospitals","authors":"Michael J. Tchou MD, MSc, Matt Hall PhD, Jessica L. Markham MD, MSc, John R. Stephens MD, Michael J. Steiner MD, MPH, Elisha McCoy MD, Paul L. Aronson MD, MHS, Samir S. Shah MD, MSCE, Matthew J. Molloy MD, MPH, Jillian M. Cotter MD, MSCS","doi":"10.1002/jhm.13372","DOIUrl":"10.1002/jhm.13372","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Research into low-value routine testing at children's hospitals has not consistently evaluated changing patterns of testing over time.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>To identify changes in routine laboratory testing rates at children's hospitals over ten years and the association with patient outcomes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Design, Settings, and Participants</h3>\u0000 \u0000 <p>We performed a multi-center, retrospective cohort study of children aged 0–18 hospitalized with common, lower-severity diagnoses at 28 children's hospitals in the Pediatric Health Information Systems database.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Main Outcomes and Measures</h3>\u0000 \u0000 <p>We calculated average annual testing rates for complete blood counts, electrolytes, and inflammatory markers between 2010 and 2019 for each hospital. A >2% average testing rate change per year was defined as clinically meaningful and used to separate hospitals into groups: increasing, decreasing, and unchanged testing rates. Groups were compared for differences in length of stay, cost, and 30-day readmission or ED revisit, adjusted for demographics and case mix index.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Our study included 576,572 encounters for common, low-severity diagnoses. Individual hospital testing rates in each year of the study varied from 0.3 to 1.4 tests per patient day. The average yearly change in hospital-specific testing rates ranged from –6% to +7%. Four hospitals remained in the lowest quartile of testing and two in the highest quartile throughout all 10 years of the study. We grouped hospitals with increasing (8), decreasing (<i>n</i> = 5), and unchanged (<i>n</i> = 15) testing rates. No difference was found across subgroups in costs, length of stay, 30-day ED revisit, or readmission rates. Comparing resource utilization trends over time provides important insights into achievable rates of testing reduction.</p>\u0000 </section>\u0000 </div>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"19 8","pages":"671-679"},"PeriodicalIF":2.4,"publicationDate":"2024-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140635062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Artificial intelligence in medicine: A primer and recommendation","authors":"Shitij Arora MD, Sunit P. Jariwala MD, Satchit Balsari MD, MPH","doi":"10.1002/jhm.13371","DOIUrl":"10.1002/jhm.13371","url":null,"abstract":"<p>\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"19 12","pages":"1197-1200"},"PeriodicalIF":2.4,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140626309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The development and pilot of a novel mobile application to assess clinician perception of workload and work environment","authors":"Marisha Burden MD, MBA, Lauren McBeth BA, Angela Keniston PhD, MSPH","doi":"10.1002/jhm.13366","DOIUrl":"10.1002/jhm.13366","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Traditional measures of workload such as wRVUs may not be adequate to understand the impact of workload on key outcomes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>The objective of this study was to develop a mobile application to assess, in near real time, clinicians' perception of workload and work environment.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Designs, Settings and Participants</h3>\u0000 \u0000 <p>We developed the GrittyWork™ application (GW App) using the Chokshi and Mann process model for user-centered digital development. Study occured at a single academic medical center with hospitalist clinicians.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Main Outcome Measures and Measures</h3>\u0000 \u0000 <p>Measures included the System Usability Scale (SUS), use measures from GW App, electronic health record (EHR) event log data and note counts, and qualitative interviews.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>From October 28, 2022 to November 3, 2022, six hospitalist clinicians provided feedback on the early prototype of the GW App, and from February 28, 2023 to June 8, 2023, 30 hospitalist clinicians participated in the pilot while on clinical service. All 30 clinicians (100%) participated in the pilot submitting data for a total of 122 shifts. Participants reported working 10 ± 1 h per day (mean ± SD) and were responsible for an average of 11 ± 3 patients per day. The postpilot evaluation of the GW App showed a SUS score of 86 ± 11 and a participant preference toward mobile application-based surveys (73% of participants). Regarding workload measures, EHR event log data and notes data correlated with physician-reported workloads. Applying user-centered design techniques, we successfully developed a mobile application with high usability. These data can be paired with EHR event log data and outcomes to provide insights into the impact of workloads and work environments on outcomes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"19 8","pages":"661-670"},"PeriodicalIF":2.4,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jhm.13366","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140626182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cait Dmitriew MD, PhD, Del J. Houle MA, Michelle Filipovic MD, Ella Chochla MD, Alexander Hemy MD, Celeste Woods MSc, MD, Nawal Farhat MSc, PhD, Alanna Campbell MISt, Lisa J. W. Liu MPH, Jacquelyn J. Cragg MPH, PhD, James A. G. Crispo MSc, PhD
{"title":"Transitional care clinics for patients discharged from hospital without a primary care provider: A systematic review","authors":"Cait Dmitriew MD, PhD, Del J. Houle MA, Michelle Filipovic MD, Ella Chochla MD, Alexander Hemy MD, Celeste Woods MSc, MD, Nawal Farhat MSc, PhD, Alanna Campbell MISt, Lisa J. W. Liu MPH, Jacquelyn J. Cragg MPH, PhD, James A. G. Crispo MSc, PhD","doi":"10.1002/jhm.13359","DOIUrl":"10.1002/jhm.13359","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The transition from hospital to home is a high-risk period. Timely follow-up care is essential to reducing avoidable harms such as adverse drug events, yet may be unattainable for patients who lack attachment to a primary care provider. Transitional care clinics (TCCs) have been proposed as a measure to improve health outcomes for patients discharged from hospital without an established provider. In this systematic review, we compared outcomes for unattached patients seen in TCCs after hospital discharge relative to care as usual.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We searched the following bibliographic databases for articles published on or before August 12, 2022: MEDLINE, Cumulative Index to Nursing and Allied Health Literature, Cochrane Database of Systematic Reviews, PsycINFO, and Web of Science. Five studies were identified that examined the effects of a dedicated postdischarge clinic on emergency department (ED) visits, readmissions, and/or mortality within 90 days of discharge for patients with no attachment to a primary care provider.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Studies were heterogeneous in design and quality; all were from urban centers within the United States. Four of the five studies reported a reduction in either the number of ED visits or readmissions in patients seen in a TCC following hospitalization.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>TCCs may be effective in reducing hospital contacts in the period following hospital discharge in patients with no established primary care provider. Further studies are required to evaluate the health benefits attributable to the implementation of TCCs across a broad range of practice contexts, as well as the cost implications of this model.</p>\u0000 </section>\u0000 </div>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"19 8","pages":"720-727"},"PeriodicalIF":2.4,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jhm.13359","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140578016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Keshav Khanijow MD, Scott Wright MD, Helene Hedian MD, Che Harris MD
{"title":"Hospitalizations and transgender patients in the United States","authors":"Keshav Khanijow MD, Scott Wright MD, Helene Hedian MD, Che Harris MD","doi":"10.1002/jhm.13368","DOIUrl":"10.1002/jhm.13368","url":null,"abstract":"<p>It is known that transgender people experience health inequalities. Disparities in hospital outcomes impacting transgender individuals have been inadequately explored. We conducted this retrospective cohort study using the National Inpatient Sample (01/2018–12/2019) to compare in-hospital mortality and utilization variables between cisgender and transgender individuals using regression analyses. Approximately two-thirds of hospitalizations for transgender patients (<i>n</i> = 10,245) were for psychiatric diagnoses. Compared to cisgender patients, there were no significant differences in adjusted means differences (aMD) in length of stay (LOS) (aMD = −0.29; <i>p</i> = .16) or total charges (aMD = −$486; <i>p</i> = .56). An additional 4870 transgender patients were admitted for medical diagnoses. Transgender and cisgender individuals had similar adjusted odds ratios (aOR) for in-hospital mortality (aOR = 0.96; <i>p</i> = .88) and total hospital charges (aMD = −$3118; <i>p</i> = .21). However, transgender individuals had longer LOS (aMD = +0.46 days; confidence interval [CI]: 0.15–0.90; <i>p</i> = .04). When comparing mortality and resource utilization between cisgender and transgender individuals, differences were negligible.</p>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"19 6","pages":"508-512"},"PeriodicalIF":2.6,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140578011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}