Skin and soft tissue infections (SSTIs) are commonly encountered in clinical practice. Point-of-care ultrasound (POCUS) is becoming an increasingly valuable tool in hospital medicine, especially with advancements in ultrasound technology that make it easier to perform. POCUS can augment the history and physical exam in patients with suspected SSTIs. POCUS can detect deeper infections, such as abscesses, and expedite time to surgical debridement for life-threatening infections such as necrotizing fasciitis (NF).
Objectives
This review provides an introduction on how to perform and interpret a skin and soft tissue POCUS exam, the key sonographic findings for SSTIs, and how to incorporate these findings into clinical reasoning and management.
Methods
SSTI POCUS literature was reviewed using PubMed. All relevant studies with a defined protocol and reported sensitivity and specificity pertaining to the use of POCUS to diagnose SSTIs in adults were included. The authors provide additional input based on their ultrasound expertise and clinical experience.
Results
A total of seven studies met the criteria to be included in this review.
Conclusions
Soft tissue POCUS is a valuable tool for hospitalists to improve diagnostic accuracy and patient care when assessing suspected SSTIs. Access to equipment, POCUS training, and experience are barriers to widespread use. However, performing a soft tissue POCUS exam is straightforward. It requires less training compared to other POCUS exams, and it has notable potential for routine future practice in the evaluation and management of suspected SSTIs and other dermatologic conditions.
{"title":"Point-of-care ultrasound in skin and soft tissue infections","authors":"Bryan M. Koppa MD, Christopher T. Kelly MD","doi":"10.1002/jhm.13467","DOIUrl":"10.1002/jhm.13467","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Skin and soft tissue infections (SSTIs) are commonly encountered in clinical practice. Point-of-care ultrasound (POCUS) is becoming an increasingly valuable tool in hospital medicine, especially with advancements in ultrasound technology that make it easier to perform. POCUS can augment the history and physical exam in patients with suspected SSTIs. POCUS can detect deeper infections, such as abscesses, and expedite time to surgical debridement for life-threatening infections such as necrotizing fasciitis (NF).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>This review provides an introduction on how to perform and interpret a skin and soft tissue POCUS exam, the key sonographic findings for SSTIs, and how to incorporate these findings into clinical reasoning and management.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>SSTI POCUS literature was reviewed using PubMed. All relevant studies with a defined protocol and reported sensitivity and specificity pertaining to the use of POCUS to diagnose SSTIs in adults were included. The authors provide additional input based on their ultrasound expertise and clinical experience.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A total of seven studies met the criteria to be included in this review.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Soft tissue POCUS is a valuable tool for hospitalists to improve diagnostic accuracy and patient care when assessing suspected SSTIs. Access to equipment, POCUS training, and experience are barriers to widespread use. However, performing a soft tissue POCUS exam is straightforward. It requires less training compared to other POCUS exams, and it has notable potential for routine future practice in the evaluation and management of suspected SSTIs and other dermatologic conditions.</p>\u0000 </section>\u0000 </div>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"19 10","pages":"938-944"},"PeriodicalIF":2.4,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141857493","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}
Rachel Peterson MD, Ajay Bhasin MD, Charlie M. Wray DO, MS, Samir S. Shah MD, MSCE, Gregory W. Ruhnke MD, MS, MPH
{"title":"A beginner's guide to manuscript publication: How to launch your academic manuscript","authors":"Rachel Peterson MD, Ajay Bhasin MD, Charlie M. Wray DO, MS, Samir S. Shah MD, MSCE, Gregory W. Ruhnke MD, MS, MPH","doi":"10.1002/jhm.13461","DOIUrl":"10.1002/jhm.13461","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 10","pages":"953-956"},"PeriodicalIF":2.4,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141857492","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}
Whitney Cameron DO, MSc, MSCTR, Daniel Herchline MD, MSEd
{"title":"Leadership & professional development: The tension in transition: Moving from trainee to hospitalist","authors":"Whitney Cameron DO, MSc, MSCTR, Daniel Herchline MD, MSEd","doi":"10.1002/jhm.13465","DOIUrl":"10.1002/jhm.13465","url":null,"abstract":"","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"19 11","pages":"1035-1036"},"PeriodicalIF":2.4,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141794432","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}
V. Ram Krishnamoorthi MD, MPH, Harold A. Pollack PhD
{"title":"The impact of Medicaid expansion on hospital readmission rates: Too small an effect, or big sigh of relief?","authors":"V. Ram Krishnamoorthi MD, MPH, Harold A. Pollack PhD","doi":"10.1002/jhm.13476","DOIUrl":"10.1002/jhm.13476","url":null,"abstract":"","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"19 12","pages":"1201-1202"},"PeriodicalIF":2.4,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141794434","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}
Michael M. Havranek MD, PhD, Yuliya Dahlem MD, PhD, Selina Bilger MSc, Florian Rüter MD, Daniela Ehbrecht MD, Leonel Oliveira MSc, Rudolf M. Moos MD, Christian Westerhoff MD, Armin Gemperli PhD, Thomas Beck MD
Background
Hospital readmission rates are used for quality and pay-for-performance initiatives. To identify readmissions from administrative data, two commonly employed methods are focusing either on unplanned readmissions (used by the Centers for Medicare & Medicaid Services, CMS) or potentially avoidable readmissions (used by commercial vendors such as SQLape or 3 M). However, it is not known which of these methods has higher criterion validity and can more accurately identify actually avoidable readmissions.
Objectives
A manual record review based on data from seven hospitals was used to compare the validity of the methods by CMS and SQLape.
Methods
Seven independent reviewers reviewed 738 single inpatient stays. The sensitivity, specificity, positive predictive value (PPV), and F1 score were examined to characterize the ability of an original CMS method, an adapted version of the CMS method, and the SQLape method to identify unplanned, potentially avoidable, and actually avoidable readmissions.
Results
Both versions of the CMS method had greater sensitivity (92/86% vs. 62%) and a higher PPV (84/91% vs. 71%) than the SQLape method, in terms of identifying their outcomes of interest (unplanned vs. potentially avoidable readmissions, respectively). To distinguish actually avoidable readmissions, the two versions of the CMS method again displayed higher sensitivity (90/85% vs. 66%), although the PPV did not differ significantly between the different methods.
Conclusions
Thus, the CMS method has both higher criterion validity and greater sensitivity for identifying actually avoidable readmissions, compared with the SQLape method. Consequently, the CMS method should primarily be used for quality initiatives.
背景：再入院率被用于质量和绩效付费计划。要从管理数据中识别再入院率，有两种常用方法，一种是关注非计划再入院率（医疗保险与医疗补助服务中心使用），另一种是关注潜在可避免再入院率（商业供应商使用，如 SQLape 或 3 M）。然而，目前还不清楚这两种方法中哪种方法的标准有效性更高，能更准确地识别出实际可避免的再入院情况：根据七家医院的数据进行人工记录审查，比较 CMS 和 SQLape 方法的有效性：方法：七名独立审查员审查了 738 份单次住院病历。对灵敏度、特异性、阳性预测值（PPV）和 F1 评分进行了检查，以确定 CMS 原始方法、CMS 方法的改编版和 SQLape 方法识别计划外、潜在可避免和实际可避免再入院的能力：与 SQLape 方法相比，两个版本的 CMS 方法在识别相关结果（分别为计划外再入院和潜在可避免再入院）方面的灵敏度（92/86% vs. 62%）和 PPV（84/91% vs. 71%）都更高。在区分实际可避免的再入院方面，两种版本的 CMS 方法再次显示出更高的灵敏度（90/85% vs. 66%），尽管 PPV 在不同方法之间没有显著差异：因此，与 SQLape 方法相比，CMS 方法在识别实际可避免再入院方面具有更高的标准有效性和灵敏度。因此，CMS 方法应主要用于质量计划。
{"title":"Validity of different algorithmic methods to identify hospital readmissions from routinely coded medical data","authors":"Michael M. Havranek MD, PhD, Yuliya Dahlem MD, PhD, Selina Bilger MSc, Florian Rüter MD, Daniela Ehbrecht MD, Leonel Oliveira MSc, Rudolf M. Moos MD, Christian Westerhoff MD, Armin Gemperli PhD, Thomas Beck MD","doi":"10.1002/jhm.13468","DOIUrl":"10.1002/jhm.13468","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Hospital readmission rates are used for quality and pay-for-performance initiatives. To identify readmissions from administrative data, two commonly employed methods are focusing either on unplanned readmissions (used by the Centers for Medicare & Medicaid Services, CMS) or potentially avoidable readmissions (used by commercial vendors such as SQLape or 3 M). However, it is not known which of these methods has higher criterion validity and can more accurately identify actually avoidable readmissions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>A manual record review based on data from seven hospitals was used to compare the validity of the methods by CMS and SQLape.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Seven independent reviewers reviewed 738 single inpatient stays. The sensitivity, specificity, positive predictive value (PPV), and F1 score were examined to characterize the ability of an original CMS method, an adapted version of the CMS method, and the SQLape method to identify unplanned, potentially avoidable, and actually avoidable readmissions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Both versions of the CMS method had greater sensitivity (92/86% vs. 62%) and a higher PPV (84/91% vs. 71%) than the SQLape method, in terms of identifying their outcomes of interest (unplanned vs. potentially avoidable readmissions, respectively). To distinguish actually avoidable readmissions, the two versions of the CMS method again displayed higher sensitivity (90/85% vs. 66%), although the PPV did not differ significantly between the different methods.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Thus, the CMS method has both higher criterion validity and greater sensitivity for identifying actually avoidable readmissions, compared with the SQLape method. Consequently, the CMS method should primarily be used for quality initiatives.</p>\u0000 </section>\u0000 </div>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"19 12","pages":"1147-1154"},"PeriodicalIF":2.4,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jhm.13468","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141763609","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}
Aiden Ahn BA, Anna U. Morgan MD, MSc, Robert E. Burke MD, MS, Katherine Honig BA, Judith A. Long MD, Nancy McGlaughlin RN, MSN, Carlondra Jointer MSN, RN, David A. Asch MD, MBA, Eric Bressman MD, MSHP
Background
Text messaging has emerged as a popular strategy to engage patients after hospital discharge. Little is known about how patients use these programs and what types of needs are addressed through this approach.
Objective
The goal of this study was to describe the types and timing of postdischarge needs identified during a 30-day automated texting program.
Methods
The program ran from January to August 2021 at a primary care practice in Philadelphia. In this mixed-methods study, two reviewers conducted a directed content analysis of patient needs expressed during the program, categorizing them along a well-known transitional care framework. We describe the frequency of need categories and their timing relative to discharge.
Results
A total of 405 individuals were enrolled; the mean (SD) age was 62.7 (16.2); 64.2% were female; 47.4% were Black; and 49.9% had Medicare insurance. Of this population, 178 (44.0%) expressed at least one need during the 30-day program. The most frequent needs addressed were related to symptoms (26.8%), coordinating follow-up care (20.4%), and medication issues (15.7%). The mean (SD) number of days from discharge to need was 10.8 (7.9); there were no significant differences in timing based on need category.
Conclusions
The needs identified via an automated texting program were concentrated in three areas relevant to primary care practice and within nursing scope of practice. This program can serve as a model for health systems looking to support transitions through an operationally efficient approach, and the findings of this analysis can inform future iterations of this type of program.
{"title":"Postdischarge needs identified by an automated text messaging program: A mixed-methods study","authors":"Aiden Ahn BA, Anna U. Morgan MD, MSc, Robert E. Burke MD, MS, Katherine Honig BA, Judith A. Long MD, Nancy McGlaughlin RN, MSN, Carlondra Jointer MSN, RN, David A. Asch MD, MBA, Eric Bressman MD, MSHP","doi":"10.1002/jhm.13466","DOIUrl":"10.1002/jhm.13466","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Text messaging has emerged as a popular strategy to engage patients after hospital discharge. Little is known about how patients use these programs and what types of needs are addressed through this approach.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>The goal of this study was to describe the types and timing of postdischarge needs identified during a 30-day automated texting program.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The program ran from January to August 2021 at a primary care practice in Philadelphia. In this mixed-methods study, two reviewers conducted a directed content analysis of patient needs expressed during the program, categorizing them along a well-known transitional care framework. We describe the frequency of need categories and their timing relative to discharge.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A total of 405 individuals were enrolled; the mean (SD) age was 62.7 (16.2); 64.2% were female; 47.4% were Black; and 49.9% had Medicare insurance. Of this population, 178 (44.0%) expressed at least one need during the 30-day program. The most frequent needs addressed were related to symptoms (26.8%), coordinating follow-up care (20.4%), and medication issues (15.7%). The mean (SD) number of days from discharge to need was 10.8 (7.9); there were no significant differences in timing based on need category.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The needs identified via an automated texting program were concentrated in three areas relevant to primary care practice and within nursing scope of practice. This program can serve as a model for health systems looking to support transitions through an operationally efficient approach, and the findings of this analysis can inform future iterations of this type of program.</p>\u0000 </section>\u0000 </div>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"19 12","pages":"1138-1146"},"PeriodicalIF":2.4,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jhm.13466","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141763608","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}
Secure electronic messaging is increasingly being utilized for communications in healthcare settings. While it likely increases efficiency, it has also been associated with interruptions, high message volumes, and risk of errors due to multitasking.
Objectives
We aimed to characterize patterns of secure messaging among hospitalists to understand the volume of messages, message patterns, and impact on hospitalist workload.
Methods
This was a retrospective cross-sectional study of Epic Secure Chat secure electronic messages received and sent by hospitalists from April 1 to April 30, 2023 at a large academic medical center. Number of conversations per day, number of chats sent and accessed per hour, and average minutes between when a chat was sent and accessed (lag time) were analyzed using a Pearson correlation coefficient test. Measures were plotted against patient volume and time of day.
Results
Hospitalists sent or received an average of 130 messages per day with an average of 13 messages sent or received per hour. The median lag time was 39 s. There was a statistically significant correlation between hospital medicine morning census and number of conversations per day, number of chats sent per hour, and number of chats accessed per hour, but census did not impact lag time.
Conclusion
Secure messaging volumes may be higher than previously reported, which may affect hospitalist workload and workflow and have unintended effects on interruptions, multitasking, and medical errors. Additional work should be done to better understand local messaging patterns and opportunities to optimize volume of work and distractions.
{"title":"Characterizing electronic messaging use among hospitalists and its association with patient volumes","authors":"Claire Brickson MD, Angela Keniston PhD, MSPH, Michelle Knees DO, Marisha Burden MD, MBA","doi":"10.1002/jhm.13462","DOIUrl":"10.1002/jhm.13462","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Secure electronic messaging is increasingly being utilized for communications in healthcare settings. While it likely increases efficiency, it has also been associated with interruptions, high message volumes, and risk of errors due to multitasking.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>We aimed to characterize patterns of secure messaging among hospitalists to understand the volume of messages, message patterns, and impact on hospitalist workload.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This was a retrospective cross-sectional study of Epic Secure Chat secure electronic messages received and sent by hospitalists from April 1 to April 30, 2023 at a large academic medical center. Number of conversations per day, number of chats sent and accessed per hour, and average minutes between when a chat was sent and accessed (lag time) were analyzed using a Pearson correlation coefficient test. Measures were plotted against patient volume and time of day.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Hospitalists sent or received an average of 130 messages per day with an average of 13 messages sent or received per hour. The median lag time was 39 s. There was a statistically significant correlation between hospital medicine morning census and number of conversations per day, number of chats sent per hour, and number of chats accessed per hour, but census did not impact lag time.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Secure messaging volumes may be higher than previously reported, which may affect hospitalist workload and workflow and have unintended effects on interruptions, multitasking, and medical errors. Additional work should be done to better understand local messaging patterns and opportunities to optimize volume of work and distractions.</p>\u0000 </section>\u0000 </div>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"19 12","pages":"1131-1137"},"PeriodicalIF":2.4,"publicationDate":"2024-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141736217","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}
Nazima Allaudeen MD, Joyce Akwe MD, Cherinne Arundel MD, Joel C. Boggan MD, Peter Caldwell MD, Paul B. Cornia MD, Jessica Cyr MD, Erik Ehlers MD, Joel Elzweig MD, Patrick Godwin MD, Kirsha S. Gordon PhD, MS, Michelle Guidry MD, Jeydith Gutierrez MD, MPH, Daniel Heppe MD, Matthew Hoegh MD, Anand Jagannath MD, Peter Kaboli MD, MS, FACP, FHM, Michael Krug MD, James D. Laudate MD, Christine Mitchell MD, Micah Pescetto DO, Benjamin A. Rodwin MD, Matthew Ronan MD, Richard Rose MD, Meghna N. Shah MD, Andrea Smeraglio MD, Meredith Trubitt MD, Matthew Tuck MD, Jaclyn Vargas MD, Peter Yarbrough MD, Craig G. Gunderson MD
Background
Alcohol withdrawal is a common reason for admission to acute care hospitals. Prescription of medications for alcohol-use disorder (AUD) and close outpatient follow-up are commonly recommended, but few studies report their effects on postdischarge outcomes.
Objectives
The objective of this study is to evaluate the effects of medications for AUD and follow-up appointments on readmission and abstinence.
Methods
This retrospective cohort study evaluated veterans admitted for alcohol withdrawal to medical services at 19 Veteran Health Administration hospitals between October 1, 2018 and September 30, 2019. Factors associated with all-cause 30-day readmission and 6-month abstinence were examined using logistic regression.
Results
Of the 594 patients included in this study, 296 (50.7%) were prescribed medications for AUD at discharge and 459 (78.5%) were discharged with follow-up appointments, including 251 (42.8%) with a substance-use clinic appointment, 191 (32.9%) with a substance-use program appointment, and 73 (12.5%) discharged to a residential program. All-cause 30-day readmission occurred for 150 patients (25.5%) and 103 (17.8%) remained abstinent at 6 months. Medications for AUD and outpatient discharge appointments were not associated with readmission or abstinence. Discharge to residential treatment program was associated with reduced 30-day readmission (adjusted odds ratio [AOR]: 0.39, 95% confidence interval [95% CI]: 0.18–0.82) and improved abstinence (AOR: 2.50, 95% CI: 1.33–4.73).
Conclusions
Readmission and return to heavy drinking are common for patients discharged for alcohol withdrawal. Medications for AUD were not associated with improved outcomes. The only intervention at the time of discharge that improved outcomes was discharge to residential treatment program, which was associated with decreased readmission and improved abstinence.
{"title":"Medications for alcohol-use disorder and follow-up after hospitalization for alcohol withdrawal: A multicenter study","authors":"Nazima Allaudeen MD, Joyce Akwe MD, Cherinne Arundel MD, Joel C. Boggan MD, Peter Caldwell MD, Paul B. Cornia MD, Jessica Cyr MD, Erik Ehlers MD, Joel Elzweig MD, Patrick Godwin MD, Kirsha S. Gordon PhD, MS, Michelle Guidry MD, Jeydith Gutierrez MD, MPH, Daniel Heppe MD, Matthew Hoegh MD, Anand Jagannath MD, Peter Kaboli MD, MS, FACP, FHM, Michael Krug MD, James D. Laudate MD, Christine Mitchell MD, Micah Pescetto DO, Benjamin A. Rodwin MD, Matthew Ronan MD, Richard Rose MD, Meghna N. Shah MD, Andrea Smeraglio MD, Meredith Trubitt MD, Matthew Tuck MD, Jaclyn Vargas MD, Peter Yarbrough MD, Craig G. Gunderson MD","doi":"10.1002/jhm.13458","DOIUrl":"10.1002/jhm.13458","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Alcohol withdrawal is a common reason for admission to acute care hospitals. Prescription of medications for alcohol-use disorder (AUD) and close outpatient follow-up are commonly recommended, but few studies report their effects on postdischarge outcomes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>The objective of this study is to evaluate the effects of medications for AUD and follow-up appointments on readmission and abstinence.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This retrospective cohort study evaluated veterans admitted for alcohol withdrawal to medical services at 19 Veteran Health Administration hospitals between October 1, 2018 and September 30, 2019. Factors associated with all-cause 30-day readmission and 6-month abstinence were examined using logistic regression.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Of the 594 patients included in this study, 296 (50.7%) were prescribed medications for AUD at discharge and 459 (78.5%) were discharged with follow-up appointments, including 251 (42.8%) with a substance-use clinic appointment, 191 (32.9%) with a substance-use program appointment, and 73 (12.5%) discharged to a residential program. All-cause 30-day readmission occurred for 150 patients (25.5%) and 103 (17.8%) remained abstinent at 6 months. Medications for AUD and outpatient discharge appointments were not associated with readmission or abstinence. Discharge to residential treatment program was associated with reduced 30-day readmission (adjusted odds ratio [AOR]: 0.39, 95% confidence interval [95% CI]: 0.18–0.82) and improved abstinence (AOR: 2.50, 95% CI: 1.33–4.73).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Readmission and return to heavy drinking are common for patients discharged for alcohol withdrawal. Medications for AUD were not associated with improved outcomes. The only intervention at the time of discharge that improved outcomes was discharge to residential treatment program, which was associated with decreased readmission and improved abstinence.</p>\u0000 </section>\u0000 </div>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"19 12","pages":"1122-1130"},"PeriodicalIF":2.4,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141731702","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":"Clinical guideline highlights for the hospitalist: International consensus criteria for pediatric sepsis and septic shock","authors":"James A. Watson MD, Nichole Samuy MD, MSHI","doi":"10.1002/jhm.13459","DOIUrl":"10.1002/jhm.13459","url":null,"abstract":"<p><b>GUIDELINE TITLE</b>: International Consensus Criteria for Pediatric Sepsis and Septic Shock</p><p><b>RELEASE DATE</b>: January 21, 2024</p><p><b>PRIOR VERSION(S)</b>: International Pediatric Sepsis Consensus Conference: Definitions for Sepsis and Organ Dysfunction in Pediatrics (2005)</p><p><b>DEVELOPER</b>: Society of Critical Care Medicine</p><p><b>FUNDING SOURCE</b>: Society of Critical Care Medicine (grant R01HD105939 from the National Institute of Child Health and Human Development)</p><p><b>TARGET POPULATION</b>: Children with sepsis and septic shock</p>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"19 11","pages":"1037-1039"},"PeriodicalIF":2.4,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jhm.13459","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141617884","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}
Ajay Bhasin MD, Lynn Huang MS, Meng-Shoiu Shieh PhD, Penelope Pekow PhD, Peter K. Lindenauer MD, MS, Tara Lagu MD, MPH
Background
Malnutrition in hospitalized patients is associated increased length of stay, cost, readmission, and death. No recent studies have examined trends in prevalence or outcomes of hospitalized patients with a diagnosis of malnutrition.
Objectives
To study the prevalence of malnutrition diagnostic codes and associated hospital outcomes in the United States between 2016 and 2019.
Methods
We conducted a retrospective trends study to identify use of malnutrition codes in hospitalizations in the National Inpatient Sample between 2016 and 2019. We used direct standardization by logistic regression to adjust outcomes of percutaneous gastrostomy tube placement, mechanical ventilation, and death for age, Gagne comorbidity score, and sex. We then used linear regression to test for trends over time by malnutrition type.
Results
Across all hospitalizations, codes for diagnoses of nonsevere malnutrition and severe malnutrition were present in 3.7% and 4.1% of hospitalizations, respectively. Codes for any malnutrition increased over time, from 6.6% in 2016 to 8.6% in 2018 (p = .03). Codes for severe malnutrition increased from 3.3% to 4.7% (p = .01). Among hospitalizations with coded severe malnutrition diagnoses, there was a statistically significant decrease in adjusted rate of death over time (−0.54% per year, p = .03) which was not seen in hospitalizations without coded malnutrition diagnoses.
Conclusions
Use of malnutrition diagnosis codes increased significantly from 2016 to 2019. During this time, mortality among hospitalizations with a diagnosis code for severe malnutrition decreased. Though the increased prevalence of malnutrition codes may represent a change in the clinical characteristics of hospitalized patients, the decline in mortality suggests some of the increase may be due to lower threshold for coding and assignment of the diagnosis to less ill patients.
{"title":"Malnutrition in hospitalized adults in the United States, 2016–2019","authors":"Ajay Bhasin MD, Lynn Huang MS, Meng-Shoiu Shieh PhD, Penelope Pekow PhD, Peter K. Lindenauer MD, MS, Tara Lagu MD, MPH","doi":"10.1002/jhm.13456","DOIUrl":"10.1002/jhm.13456","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Malnutrition in hospitalized patients is associated increased length of stay, cost, readmission, and death. No recent studies have examined trends in prevalence or outcomes of hospitalized patients with a diagnosis of malnutrition.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>To study the prevalence of malnutrition diagnostic codes and associated hospital outcomes in the United States between 2016 and 2019.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We conducted a retrospective trends study to identify use of malnutrition codes in hospitalizations in the National Inpatient Sample between 2016 and 2019. We used direct standardization by logistic regression to adjust outcomes of percutaneous gastrostomy tube placement, mechanical ventilation, and death for age, Gagne comorbidity score, and sex. We then used linear regression to test for trends over time by malnutrition type.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Across all hospitalizations, codes for diagnoses of nonsevere malnutrition and severe malnutrition were present in 3.7% and 4.1% of hospitalizations, respectively. Codes for any malnutrition increased over time, from 6.6% in 2016 to 8.6% in 2018 (<i>p</i> = .03). Codes for severe malnutrition increased from 3.3% to 4.7% (<i>p</i> = .01). Among hospitalizations with coded severe malnutrition diagnoses, there was a statistically significant decrease in adjusted rate of death over time (−0.54% per year, <i>p</i> = .03) which was not seen in hospitalizations without coded malnutrition diagnoses.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Use of malnutrition diagnosis codes increased significantly from 2016 to 2019. During this time, mortality among hospitalizations with a diagnosis code for severe malnutrition decreased. Though the increased prevalence of malnutrition codes may represent a change in the clinical characteristics of hospitalized patients, the decline in mortality suggests some of the increase may be due to lower threshold for coding and assignment of the diagnosis to less ill patients.</p>\u0000 </section>\u0000 </div>","PeriodicalId":15883,"journal":{"name":"Journal of hospital medicine","volume":"19 12","pages":"1113-1121"},"PeriodicalIF":2.4,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jhm.13456","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141565383","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}
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