John M. Cunningham MD, FHM, FACP, Robert Leverence MD, FACP, Nico Gotera DO, MPH, Phillip A. Minor MS, Nathan Sevigny BS, Ankur Segon MD, MPH, MEd, FACP, SFHM
Communication between consulting and consultant services is essential to provide high-value care. We implemented a collaborative project between hospital medicine (HM), emergency medicine (EM), and departmental leadership of the major consulting services to provide feedback regarding consultant communication, promptness, and follow-up planning. We conducted pre- and postintervention surveys of HM and EM clinicians and measured the mean turnaround time (TAT) from consult order to consultant note completion. Perceptions of consultant promptness and follow-up communication improved postintervention. Mean TAT was significantly reduced postintervention (1098 vs. 1011 min, p = .002, confidence interval [CI]: 30.7–143.3). A collaborative approach using interdepartmental feedback improved perceptions of the quality of interactions with consulting services.
咨询和咨询服务之间的沟通对于提供高价值的护理至关重要。我们在医院医学（HM）、急诊医学（EM）和主要咨询服务的部门领导之间实施了一个协作项目，以提供关于顾问沟通、及时性和后续计划的反馈。我们对HM和EM临床医生进行了干预前和干预后的调查，并测量了从咨询订单到咨询记录完成的平均周转时间（TAT）。干预后，对咨询师的及时性和随访沟通的看法有所改善。平均TAT在干预后显著降低(1098 vs 1011 min, p =。002，置信区间[CI]: 30.7-143.3)。采用部门间反馈的协作方法提高了对咨询服务相互作用质量的认识。
{"title":"Improving promptness and quality of hospitalist-consultant interactions at an academic teaching hospital","authors":"John M. Cunningham MD, FHM, FACP, Robert Leverence MD, FACP, Nico Gotera DO, MPH, Phillip A. Minor MS, Nathan Sevigny BS, Ankur Segon MD, MPH, MEd, FACP, SFHM","doi":"10.1002/jhm.70047","DOIUrl":"10.1002/jhm.70047","url":null,"abstract":"<p>Communication between consulting and consultant services is essential to provide high-value care. We implemented a collaborative project between hospital medicine (HM), emergency medicine (EM), and departmental leadership of the major consulting services to provide feedback regarding consultant communication, promptness, and follow-up planning. We conducted pre- and postintervention surveys of HM and EM clinicians and measured the mean turnaround time (TAT) from consult order to consultant note completion. Perceptions of consultant promptness and follow-up communication improved postintervention. Mean TAT was significantly reduced postintervention (1098 vs. 1011 min, <i>p</i> = .002, confidence interval [CI]: 30.7–143.3). A collaborative approach using interdepartmental feedback improved perceptions of the quality of interactions with consulting services.</p>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"20 8","pages":"903-907"},"PeriodicalIF":2.3,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jhm.70047","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144000993","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}
Hannah Kerman MD, Andre Kumar MD, MAEd, Byron Crowe MD, William Collins MD
Generative Artificial Intelligence (Gen AI) shows significant promise as a technology that could improve healthcare delivery, but its implementation will be influenced by the spheres in which it is studied and the limited resources of hospitals. The Point authors argue that we should focus on is the cognitive abilities of GenAI or we risk being left out of a technological leap that will change the way doctors practice. The Counterpoint argues that we should focus on using GenAI to ease system burdens and address workflow issues, focusing our efforts on fixing the problems that would improve doctors’ quality of life and increase time spent with patients.
{"title":"Point-counterpoint: What is the best strategy for developing generative AI for hospital medicine?","authors":"Hannah Kerman MD, Andre Kumar MD, MAEd, Byron Crowe MD, William Collins MD","doi":"10.1002/jhm.70070","DOIUrl":"10.1002/jhm.70070","url":null,"abstract":"<p>Generative Artificial Intelligence (Gen AI) shows significant promise as a technology that could improve healthcare delivery, but its implementation will be influenced by the spheres in which it is studied and the limited resources of hospitals. The Point authors argue that we should focus on is the cognitive abilities of GenAI or we risk being left out of a technological leap that will change the way doctors practice. The Counterpoint argues that we should focus on using GenAI to ease system burdens and address workflow issues, focusing our efforts on fixing the problems that would improve doctors’ quality of life and increase time spent with patients.</p>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"20 8","pages":"893-898"},"PeriodicalIF":2.3,"publicationDate":"2025-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144016040","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}
Shih-Chun Lin RN, PhD, Chi-Yin Kao RN, PhD, Hsueh-Fen Chen PhD, Sriyani Padmalatha Konara Mudiyanselage RN, PhD, Hsiang-Ying Lu MSN, Mei-Chih Huang RN, PhD
Background
Disparities in specialist palliative care (SPC) are complex. Families of children and young adults with life-limiting conditions in digitally advanced areas have better access to health information and services.
Objectives
To examine SPC and end-of-life care for these patients, focusing on SPC referral rates and associated disparities.
Methods
A retrospective study used national health insurance data in Taiwan. Patients aged 1–25 years who died with life-limiting conditions between 2009 and 2017 were included in this study (n = 6863). The main focus was on referrals to SPC, identified through service codes for palliative shared care, home care, and inpatient hospice.
Results
A total of 979 patients (14.3%) received SPC at least 3 days before death. Cancer patients were over 10 times more likely to receive SPC than noncancer patients, with an odds ratio of 10.77 (95% confidence interval [CI]: 9.08–12.77). Conversely, patients with congenital, hematological, neurological, or respiratory conditions were over 60% less likely to receive SPC than those without such conditions. Patients in well-digitally developed townships had higher SPC referrals rates (adjusted odds ratio [aOR]: 1.28; 95% CI: 1.11–1.48). SPC was associated with longer hospital stays in the last month of life (aOR: 2.64; 95% CI: 2.28–3.06) and increased hospital deaths (aOR: 8.36; 95% CI: 5.66–12.35), but less likely to be admitted to hospitals in the last 5 days of life (aOR: 0.61; 95% CI: 0.50–0.74).
Conclusions
Few patients in Taiwan received SPC, highlighting that diagnosis is a significant predictor. This suggests a need for further investigation into resources for SPC.
{"title":"Disparities in specialist palliative care for Taiwanese children and young adults impacted by local digital development and noncancer diagnoses","authors":"Shih-Chun Lin RN, PhD, Chi-Yin Kao RN, PhD, Hsueh-Fen Chen PhD, Sriyani Padmalatha Konara Mudiyanselage RN, PhD, Hsiang-Ying Lu MSN, Mei-Chih Huang RN, PhD","doi":"10.1002/jhm.70068","DOIUrl":"10.1002/jhm.70068","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Disparities in specialist palliative care (SPC) are complex. Families of children and young adults with life-limiting conditions in digitally advanced areas have better access to health information and services.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>To examine SPC and end-of-life care for these patients, focusing on SPC referral rates and associated disparities.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A retrospective study used national health insurance data in Taiwan. Patients aged 1–25 years who died with life-limiting conditions between 2009 and 2017 were included in this study (<i>n</i> = 6863). The main focus was on referrals to SPC, identified through service codes for palliative shared care, home care, and inpatient hospice.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A total of 979 patients (14.3%) received SPC at least 3 days before death. Cancer patients were over 10 times more likely to receive SPC than noncancer patients, with an odds ratio of 10.77 (95% confidence interval [CI]: 9.08–12.77). Conversely, patients with congenital, hematological, neurological, or respiratory conditions were over 60% less likely to receive SPC than those without such conditions. Patients in well-digitally developed townships had higher SPC referrals rates (adjusted odds ratio [aOR]: 1.28; 95% CI: 1.11–1.48). SPC was associated with longer hospital stays in the last month of life (aOR: 2.64; 95% CI: 2.28–3.06) and increased hospital deaths (aOR: 8.36; 95% CI: 5.66–12.35), but less likely to be admitted to hospitals in the last 5 days of life (aOR: 0.61; 95% CI: 0.50–0.74).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Few patients in Taiwan received SPC, highlighting that diagnosis is a significant predictor. This suggests a need for further investigation into resources for SPC.</p>\u0000 </section>\u0000 </div>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"20 11","pages":"1156-1165"},"PeriodicalIF":2.3,"publicationDate":"2025-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144048524","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}
Melissa B. Weimer DO, MCR, Michele J. Buonora MD, MS, MHS, Alexandra M. Hajduk PhD, MPH, Adam L. Ackerman MD, Krishna R. Daggula MS, William C. Becker MD, Sarwat I. Chaudhry MD, David A. Fiellin MD
Background
The management of analgesia in people hospitalized with chronic pain and elevated risk for opioid-related harm is challenging. While opioid stewardship programs could provide guidance, their feasibility in this population has not been examined.
Objectives
To develop a case identification tool and evaluate the feasibility of an electronic medical record (EMR)-delivered opioid stewardship and pain intervention among hospitalized people with chronic pain and elevated risk for opioid-related harm.
Methods
After developing and evaluating the operating characteristics of a case identification tool to identify people with chronic pain and elevated risk for opioid-related harm, hospitalized adults with chronic pain and elevated risk for opioid-related harm were randomized to an EMR-delivered opioid stewardship and pain intervention versus usual care. Primary outcomes were feasibility-based. Exploratory outcomes were pain-related clinical outcomes.
Results
The case identification tool had a sensitivity of 88.9% and a specificity of 95.7%. The trial recruited 52/97 (54%) of potential participants who completed 52/52 (100%) potential assessments and of whom 45/52 (87%) were retained in the study at 4 weeks, demonstrating feasibility. On average, both treatment arms received 56% of the recommended guideline-concordant care and there was no significant difference in opioid and pain-related care in the two groups.
Conclusion
It is both feasible to develop an EMR-based tool to prospectively identify hospitalized people with chronic pain and elevated risk for opioid-related harm as well as recruit these individuals to an EMR-delivered opioid stewardship and pain intervention. Additional strategies to support the provision of guideline-concordant care may be warranted.
{"title":"Intervention for hospitalized people with chronic pain and elevated risk for opioid-related harm: A pilot randomized controlled trial","authors":"Melissa B. Weimer DO, MCR, Michele J. Buonora MD, MS, MHS, Alexandra M. Hajduk PhD, MPH, Adam L. Ackerman MD, Krishna R. Daggula MS, William C. Becker MD, Sarwat I. Chaudhry MD, David A. Fiellin MD","doi":"10.1002/jhm.70066","DOIUrl":"10.1002/jhm.70066","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The management of analgesia in people hospitalized with chronic pain and elevated risk for opioid-related harm is challenging. While opioid stewardship programs could provide guidance, their feasibility in this population has not been examined.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>To develop a case identification tool and evaluate the feasibility of an electronic medical record (EMR)-delivered opioid stewardship and pain intervention among hospitalized people with chronic pain and elevated risk for opioid-related harm.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>After developing and evaluating the operating characteristics of a case identification tool to identify people with chronic pain and elevated risk for opioid-related harm, hospitalized adults with chronic pain and elevated risk for opioid-related harm were randomized to an EMR-delivered opioid stewardship and pain intervention versus usual care. Primary outcomes were feasibility-based. Exploratory outcomes were pain-related clinical outcomes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The case identification tool had a sensitivity of 88.9% and a specificity of 95.7%. The trial recruited 52/97 (54%) of potential participants who completed 52/52 (100%) potential assessments and of whom 45/52 (87%) were retained in the study at 4 weeks, demonstrating feasibility. On average, both treatment arms received 56% of the recommended guideline-concordant care and there was no significant difference in opioid and pain-related care in the two groups.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>It is both feasible to develop an EMR-based tool to prospectively identify hospitalized people with chronic pain and elevated risk for opioid-related harm as well as recruit these individuals to an EMR-delivered opioid stewardship and pain intervention. Additional strategies to support the provision of guideline-concordant care may be warranted.</p>\u0000 </section>\u0000 </div>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"20 10","pages":"1079-1086"},"PeriodicalIF":2.3,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144002002","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":"Things We Do for No Reason™: Avoiding intravenous iodinated contrast material in patients with acute kidney injury or chronic kidney disease","authors":"Caroline Coleman MD, Meredith Trubitt MD, MPH, Joel Topf MD, FACP, Monee Amin MD","doi":"10.1002/jhm.70063","DOIUrl":"10.1002/jhm.70063","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":"20 10","pages":"1108-1111"},"PeriodicalIF":2.3,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144061338","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}
Valerie G. Press MD, MPH, James D. Harrison PhD, Sagar B. Dugani MD, PhD, MPH, Blair P. Golden MD, Nicolas Caravelli MA, Andrea Jackson-Sagredo MS, Valerie M. Vaughn MD, MSc, Andrew McWilliams MD, MPH, Juliessa M. Pavon MD, Ashley M. Jenkins MD, MSc, Andrew Sumarsono MD, MPH, Maylyn Martinez MD, MSc, Micah Prochaska MD, Stephanie K. Mueller MD, MPH
Hospital medicine (HM), a well-established clinical specialty, requires clarity of research priorities to identify target areas for investment in HM research infrastructure and activities. The Society of Hospital Medicine's Research Committee developed a 20-item survey and used purposeful sampling of US hospitalist leaders to prioritize primary research topic domains and subdomains. Respondents were asked to rank their HM research priorities using a scale (1 [highest] to 8 [lowest]). Of 239 surveys distributed, 81 (34%) responded. Respondents were predominantly White (53%) and from academic institutions (57%). “Overall, 46% of respondents were male and 33% were female.” Top-ranked research domains were innovation in care delivery (median 2, IQR 1,3), value-based care (median 3.5, IQR 2,6), and health disparities (median 4, IQR 2,5). This survey identified top HM research priorities including systems-based topics and health disparities, aligning with HM's identity as a specialty focused on improving systems of care and inequities in care.
{"title":"Research priorities for adult hospital medicine: A survey of US hospital medicine leaders","authors":"Valerie G. Press MD, MPH, James D. Harrison PhD, Sagar B. Dugani MD, PhD, MPH, Blair P. Golden MD, Nicolas Caravelli MA, Andrea Jackson-Sagredo MS, Valerie M. Vaughn MD, MSc, Andrew McWilliams MD, MPH, Juliessa M. Pavon MD, Ashley M. Jenkins MD, MSc, Andrew Sumarsono MD, MPH, Maylyn Martinez MD, MSc, Micah Prochaska MD, Stephanie K. Mueller MD, MPH","doi":"10.1002/jhm.70053","DOIUrl":"10.1002/jhm.70053","url":null,"abstract":"<p>Hospital medicine (HM), a well-established clinical specialty, requires clarity of research priorities to identify target areas for investment in HM research infrastructure and activities. The Society of Hospital Medicine's Research Committee developed a 20-item survey and used purposeful sampling of US hospitalist leaders to prioritize primary research topic domains and subdomains. Respondents were asked to rank their HM research priorities using a scale (1 [highest] to 8 [lowest]). Of 239 surveys distributed, 81 (34%) responded. Respondents were predominantly White (53%) and from academic institutions (57%). <i>“</i>Overall, 46% of respondents were male and 33% were female.<i>”</i> Top-ranked research domains were innovation in care delivery (median 2, IQR 1,3), value-based care (median 3.5, IQR 2,6), and health disparities (median 4, IQR 2,5). This survey identified top HM research priorities including systems-based topics and health disparities, aligning with HM's identity as a specialty focused on improving systems of care and inequities in care.</p>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"20 11","pages":"1206-1211"},"PeriodicalIF":2.3,"publicationDate":"2025-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12353494/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144065514","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}
<p>There is a traveler on the road. The traveler has been through a long and difficult journey, and now the traveler arrives at a mountain stretching high up. Theoretically, the traveler could go around the mountain, but this would set the traveler back a few days. The traveler has companions, and the efficiency of the journey is of utmost significance to them.</p><p>The traveler decides to scale the mountain.</p><p>Climbing the mountain is treacherous and perilous. The traveler confronts many dangers, the crumble of rock beneath feet, and the peril of a narrow path along a cliff.</p><p>But the traveler gets to the summit.</p><p>The traveler considers the difficult journey that led here. They drop their backpack to the ground, the pain from the straps felt in their shoulders, the pain in their muscles was a reminder of the difficulty of the climb.</p><p>But the mountain <i>was</i> climbable. This challenge, though difficult, <i>was</i> surmountable.</p><p>Then, the traveler looks toward the road ahead. What they find: many more mountains.</p><p>The traveler hesitates. The road is much more challenging than anticipated.</p><p>But the traveler's companions are shocked by this hesitation. The traveler just demonstrated the capability to climb a challenging mountain. Why hesitate at the prospect of climbing all the other mountains?</p><p>The traveler considers how many supplies this climb demanded, how much effort, the exhaustion felt now at the summit.</p><p>The companions respond: but you <i>did</i> climb this mountain. This mountain <i>was</i> surmountable. Each of these other mountains is <i>also</i> surmountable. There is truth to this. <i>Each</i> mountain is surmountable. But are <i>all</i> mountains, consecutively, surmountable?</p><p>The traveler recognizes there is an alternative: to go around the other mountains, to have a journey with less challenge and more enjoyment. But the companions are expecting the traveler to pursue the most efficient route.</p><p>The traveler continues to climb the mountains instead of going around.</p><p>Each mountain seems more difficult. There is perhaps no difference from the perspective of objective terms, but the traveler feels the mounting challenge of each step. There's a fall, then a strain, each injury increasing the possibility of another error during the climb.</p><p>Then, the traveler reaches their limit. The injuries they have accumulated have rendered them not capable of climbing any more mountains, at least not without a significant opportunity to recover.</p><p>But there is a mountain ahead. The traveler recognizes that this is the mountain they must go around. They are too exhausted to climb. There is no alternative.</p><p>When the traveler approaches, they recognize there is no manner in which to go around this mountain. There are even more difficult mountains flanking this mountain, no other path but to climb. There is no alternative.</p><p>The traveler recognizes that, perhaps if they had not
{"title":"Climbable mountain","authors":"Nike Izmaylov MD, Michelle Izmaylov MD","doi":"10.1002/jhm.70064","DOIUrl":"10.1002/jhm.70064","url":null,"abstract":"<p>There is a traveler on the road. The traveler has been through a long and difficult journey, and now the traveler arrives at a mountain stretching high up. Theoretically, the traveler could go around the mountain, but this would set the traveler back a few days. The traveler has companions, and the efficiency of the journey is of utmost significance to them.</p><p>The traveler decides to scale the mountain.</p><p>Climbing the mountain is treacherous and perilous. The traveler confronts many dangers, the crumble of rock beneath feet, and the peril of a narrow path along a cliff.</p><p>But the traveler gets to the summit.</p><p>The traveler considers the difficult journey that led here. They drop their backpack to the ground, the pain from the straps felt in their shoulders, the pain in their muscles was a reminder of the difficulty of the climb.</p><p>But the mountain <i>was</i> climbable. This challenge, though difficult, <i>was</i> surmountable.</p><p>Then, the traveler looks toward the road ahead. What they find: many more mountains.</p><p>The traveler hesitates. The road is much more challenging than anticipated.</p><p>But the traveler's companions are shocked by this hesitation. The traveler just demonstrated the capability to climb a challenging mountain. Why hesitate at the prospect of climbing all the other mountains?</p><p>The traveler considers how many supplies this climb demanded, how much effort, the exhaustion felt now at the summit.</p><p>The companions respond: but you <i>did</i> climb this mountain. This mountain <i>was</i> surmountable. Each of these other mountains is <i>also</i> surmountable. There is truth to this. <i>Each</i> mountain is surmountable. But are <i>all</i> mountains, consecutively, surmountable?</p><p>The traveler recognizes there is an alternative: to go around the other mountains, to have a journey with less challenge and more enjoyment. But the companions are expecting the traveler to pursue the most efficient route.</p><p>The traveler continues to climb the mountains instead of going around.</p><p>Each mountain seems more difficult. There is perhaps no difference from the perspective of objective terms, but the traveler feels the mounting challenge of each step. There's a fall, then a strain, each injury increasing the possibility of another error during the climb.</p><p>Then, the traveler reaches their limit. The injuries they have accumulated have rendered them not capable of climbing any more mountains, at least not without a significant opportunity to recover.</p><p>But there is a mountain ahead. The traveler recognizes that this is the mountain they must go around. They are too exhausted to climb. There is no alternative.</p><p>When the traveler approaches, they recognize there is no manner in which to go around this mountain. There are even more difficult mountains flanking this mountain, no other path but to climb. There is no alternative.</p><p>The traveler recognizes that, perhaps if they had not","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"20 10","pages":"1122-1123"},"PeriodicalIF":2.3,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://shmpublications.onlinelibrary.wiley.com/doi/epdf/10.1002/jhm.70064","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144012267","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}
Greg Attard MS, James C. Gay MD, Katherine A. Auger MD, MSc, Matt Hall PhD, Alison R. Carroll MD, MPH, Troy Richardson PhD
Pediatric readmissions are important for hospitals to measure and monitor to identify potential improvement opportunities but require benchmarks to contextualize observed and expected readmissions. We developed and validated the Pediatric Readmissions Encounter Predictor (PREP) in administrative data as pediatric readmission benchmarks using the All-Patient Refined Diagnosis-Related Groups with severity of illness subclasses. We developed the model using data from the National Readmission Database in 2019. We subsequently validated these models in the same data set from 2018. The overall 30-day unplanned readmission rate was 2.5%. The model demonstrated acceptable discriminatory performance (area under the receiver operator characteristic curve [AUC] = 0.738, 95% confidence interval [CI]: 0.734, 0.741) and was well calibrated across all levels of predicted probabilities. PREP is a promising readmission prediction model which hospitals can use to assist in identifying improvement opportunities.
{"title":"Development of a pediatric readmissions encounter predictor: Benchmarks for 30-day unplanned pediatric readmission","authors":"Greg Attard MS, James C. Gay MD, Katherine A. Auger MD, MSc, Matt Hall PhD, Alison R. Carroll MD, MPH, Troy Richardson PhD","doi":"10.1002/jhm.70061","DOIUrl":"10.1002/jhm.70061","url":null,"abstract":"<p>Pediatric readmissions are important for hospitals to measure and monitor to identify potential improvement opportunities but require benchmarks to contextualize observed and expected readmissions. We developed and validated the Pediatric Readmissions Encounter Predictor (PREP) in administrative data as pediatric readmission benchmarks using the All-Patient Refined Diagnosis-Related Groups with severity of illness subclasses. We developed the model using data from the National Readmission Database in 2019. We subsequently validated these models in the same data set from 2018. The overall 30-day unplanned readmission rate was 2.5%. The model demonstrated acceptable discriminatory performance (area under the receiver operator characteristic curve [AUC] = 0.738, 95% confidence interval [CI]: 0.734, 0.741) and was well calibrated across all levels of predicted probabilities. PREP is a promising readmission prediction model which hospitals can use to assist in identifying improvement opportunities.</p>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"20 12","pages":"1337-1341"},"PeriodicalIF":2.3,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144046756","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}
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