Progress Note Research Articles

Clinical progress note: Management of the hospitalized patient who uses methamphetamine.

Clinical progress note: Management of the hospitalized patient who uses methamphetamine.

Identifying Elective Induction of Labor Among a Diverse Pregnant Population from Electronic Health Records within a Large Integrated Healthcare System.

Distinguishing between medically indicated induction of labor (iIOL) and elective induction of labor (eIOL) is a daunting process for researchers. We aimed to develop a Natural Language Processing (NLP) algorithm to identify eIOLs from electronic health records (EHR) within a large integrated healthcare system. We used structured and unstructured data from Kaiser Permanente Southern California's EHR of patients who were <35 years old and had singleton deliveries between 37 and 40 gestational weeks. Induction of labor (IOL) pregnancies were identified if there was evidence of an IOL diagnosis code, procedure code, or documentation in a delivery flowsheet or progress note. A comprehensive NLP algorithm was developed and refined through an iterative process of chart reviews and adjudications, where IOL-associated reasons (medically indicated versus elective induction) were reviewed. The final algorithm was applied to discern the indications of IOLs performed during the study period. A total of 332,163 eligible pregnancies were identified between 01/01/2008-12/31/2022. Of these eligible pregnancies, 68,541 (20.6%) were IOL, of which 6,824 (10.0%) were eIOL. Validation of the NLP process against 300 randomly selected pregnancies (100 eIOL, iIOL, and non-IOL cases each) yielded a positive predictive value of 83.0% and 88.0% for eIOL and iIOL, respectively. The rates of eIOL among the maternal age groups ranged between 9.6% -10.3%, except for the < 20 years group (12.2%). Non-Hispanic White individuals had the highest rate of eIOL (13.2%), while non-Hispanic Asian/Pacific Islanders had the lowest rate of eIOL (7.8%). The rate of eIOL increased from 1.0% in the 37 weeks gestational age group to 20.6% the 40 weeks gestational age group. Findings suggest that the developed NLP algorithm effectively identifies eIOL. It can be utilized to support eIOL-related pharmaco-epidemiological studies, filling in knowledge gaps and providing content more relevant to researchers.

Clinical progress note: Interventions for improving outcomes among hospitalized older adults.

Clinical progress note: Interventions for improving outcomes among hospitalized older adults.

Methodological progress note: Stepped-wedge cluster randomized trial design.

Methodological progress note: Stepped-wedge cluster randomized trial design.

External Validation of an Electronic Phenotyping Algorithm Detecting Attention to High Body Mass Index in Pediatric Primary Care.

The lack of feasible and meaningful measures of clinicians' behavior hinders efforts to assess and improve obesity management in pediatric primary care. In this study, we examined the external validity of a novel algorithm, previously validated in a single geographic region, using structured electronic health record (EHR) data to identify phenotypes of clinicians' attention to elevated body mass index (BMI) and weight-related comorbidities. We extracted structured EHR data for 300 randomly selected 6- to 12-year-old children with elevated BMI seen for well-child visits from June 2018 to May 2019 at pediatric primary care practices affiliated with Yale. Using diagnosis codes, laboratory orders, referrals, and medications adapted from the original algorithm, we categorized encounters as having evidence of attention to BMI only, weight-related comorbidities only, or both BMI and comorbidities. We evaluated the algorithm's sensitivity and specificity for detecting any attention to BMI and/or comorbidities using chart review as the reference standard. The adapted algorithm yielded a sensitivity of 79.2% and specificity of 94.0% for identifying any attention to high BMI/comorbidities in clinical documentation. Of 86 encounters labeled as "no attention" by the algorithm, 83% had evidence of attention in free-text components of the progress note. The likelihood of classification as "any attention" by both chart review and the algorithm varied by BMI category and by clinician type (p < 0.001). The electronic phenotyping algorithm had high specificity for detecting attention to high BMI and/or comorbidities in structured EHR inputs. The algorithm's performance may be improved by incorporating unstructured data from clinical notes.

Clinical progress note: Steroids in severe community-acquired pneumonia.

Clinical progress note: Steroids in severe community-acquired pneumonia.

Gender Differences in Electronic Health Record Usage Among Surgeons.

Understanding gender differences in electronic health record (EHR) use among surgeons is crucial for addressing potential disparities in workload, compensation, and physician well-being. To investigate gender differences in EHR usage patterns. This cross-sectional study examined data from an EHR system (Epic Signal) at a single academic hospital from January to December 2022. Participants included 224 attending surgeons with patient encounters in the outpatient setting. Statistical analysis was performed from May 2023 to April 2024. Surgeon's gender. The primary outcome variables were progress note length, documentation length, time spent in medical records, and time spent documenting patient encounters. Continuous variables were summarized with median and IQR and assessed via the Kruskal-Wallis test. Categorical variables were summarized using proportion and frequency and compared using the χ2 test. Multivariate linear regression was used with primary EHR usage variables as dependent variables and surgeon characteristics as independent variables. This study included 222 529 patient encounters by 224 attending surgeons, of whom 68 (30%) were female and 156 (70%) were male. The median (IQR) time in practice was 14.0 (7.8-24.3) years. Male surgeons had more median (IQR) appointments per month (78.3 [39.2-130.6] vs 57.8 [25.7-89.8]; P = .005) and completed more medical records per month compared with female surgeons (43.0 [21.8-103.9] vs 29.1 [15.9-48.1]; P = .006). While there was no difference in median (IQR) time spent in the EHR system per month (664.1 [301.0-1299.1] vs 635.0 [315.6-1192.0] minutes; P = .89), female surgeons spent more time logged into the system both outside of 7am to 7pm (36.4 [7.8-67.6] vs 14.1 [5.4-52.2] min/mo; P = .05) and outside of scheduled clinic hours (134.8 [58.9-310.1] vs 105.2 [40.8-214.3] min/mo; P = .05). Female surgeons spent more median (IQR) time per note (4.8 [2.6-7.1] vs 2.5 [0.9-4.2] minutes; P < .001) compared with male surgeons. Male surgeons had a higher number of median (IQR) days logged in per month (17.7 [13.8-21.3] vs 15.7 [10.7-19.7] days; P = .03). Female surgeons wrote longer median (IQR) inpatient progress notes (6025.1 [3692.1-7786.7] vs 4307.7 [2808.9-5868.4] characters/note; P = .001) and had increased outpatient document length (6321.1 [4079.9-7825.0] vs 4445.3 [2934.7-6176.7] characters/note; P < .001). Additionally, female surgeons wrote a higher fraction of the notes manually (17% vs 12%; P = .006). After using multivariable linear regression models, male gender was associated with reduced character length for both documentations (regression coefficient, -1106.9 [95% CI, -1981.5 to -232.3]; P = .01) and progress notes (regression coefficient, -1119.0 [95% CI, -1974.1 to -263.9]; P = .01). Male gender was positively associated with total hospital medical records completed (regression coefficient, 47.3 [95% CI, 28.3-66.3]; P < .001). There was no difference associated with gender for time spent in each note, time spent outside of 7 am to 7 pm, or time spent outside scheduled clinic hours. This cross-sectional study of EHR data found that female surgeons spent more time documenting patient encounters, wrote longer notes, and spent more time in the EHR system compared with male surgeons. These findings have important implications for understanding the differential burdens faced by female surgeons, including potential contributions to burnout and payment disparities.

Methodological progress note: Social network analysis as a community health research tool

Methodological progress note: Social network analysis as a community health research tool

Clinical progress note: Anti-amyloid monoclonal antibodies.

Clinical progress note: Anti-amyloid monoclonal antibodies.

Time and Note Characteristic Effects of an Electronic Health Record Template for Internal Medicine Resident Notes.

Background Inpatient internal medicine (IM) residents spend most of their time on indirect patient care activities such as clinical documentation. Objective We developed optimized electronic health record (EHR) templates for IM resident admission and progress notes, with the objective to reduce note-writing time, shorten note length, and decrease the percentage of progress note text that was copy-forwarded from prior notes. Methods In 2022, a multidisciplinary team created, over an 8-month period, optimized EHR templates for IM resident admission and progress notes. A retrospective analysis was performed to assess differences in resident time spent writing notes, note length in characters, and percentage of progress note text that was copy-forwarded. All 94 residents in the IM residency program had the opportunity to use the novel templates. Results Following implementation of the novel templates, residents spent on average 3.6 minutes less per progress note compared to pre-intervention (P=.008; 95% CI of the difference: 1.1-6.0 minutes). Notes in the post-intervention period were shorter for admission notes (mean reduction of 1041 characters; P<.001; 95% CI of the difference: 448-1634 characters) and progress notes (mean reduction of 764 characters; P<.001; 95% CI of the difference: 103-1426 characters). Progress notes also saw an average 22% decrease of copy-forwarded text (P<.001, 95% CI of the difference: 18.7%-25.4%). Conclusions The optimized note templates led to a reduction in resident progress note-writing time, shortened note length, and a lower percentage of copy-forwarded text.

Methodological progress note: Pilot randomized controlled trials.

Methodological progress note: Pilot randomized controlled trials.

Clinical progress note: Glucagon-like peptide-1 receptor agonists and hospitalized patients.

Clinical progress note: Glucagon-like peptide-1 receptor agonists and hospitalized patients.

Information heterogeneity between progress notes by physicians and nurses for inpatients with digestive system diseases

This study focused on the heterogeneity in progress notes written by physicians or nurses. A total of 806 days of progress notes written by physicians or nurses from 83 randomly selected patients hospitalized in the Gastroenterology Department at Kagawa University Hospital from January to December 2021 were analyzed. We extracted symptoms as the International Classification of Diseases (ICD) Chapter 18 (R00–R99, hereinafter R codes) from each progress note using MedNER-J natural language processing software and counted the days one or more symptoms were extracted to calculate the extraction rate. The R-code extraction rate was significantly higher from progress notes by nurses than by physicians (physicians 68.5% vs. nurses 75.2%; p = 0.00112), regardless of specialty. By contrast, the R-code subcategory R10–R19 for digestive system symptoms (44.2 vs. 37.5%, respectively; p = 0.00299) and many chapters of ICD codes for disease names, as represented by Chapter 11 K00–K93 (68.4 vs. 30.9%, respectively; p < 0.001), were frequently extracted from the progress notes by physicians, reflecting their specialty. We believe that understanding the information heterogeneity of medical documents, which can be the basis of medical artificial intelligence, is crucial, and this study is a pioneering step in that direction.

Clinical progress note: Xylazine use and its sequelae.

Clinical progress note: Xylazine use and its sequelae.

Palliative care communication with stroke patients: a best practice implementation project.

Stroke patients frequently experience debilitating deficits, and some receive a terminal diagnosis. Palliative care services are introduced to prioritize care, with the goal of improving quality of life. However, palliative care communication (PCC) is often delayed or used inefficiently with stroke patients. This project aimed to promote PCC evidence-based practices (EBPs) with stroke patients. This project used the JBI Evidence Implementation Framework to improve compliance with PCC EBPs with stroke patients in a medical center in Mississippi, USA. Four EBPs were identified from a JBI evidence summary and used as audit criteria. A baseline audit was conducted to measure compliance of current practice with best practice. Barriers to EBPs were identified, improvement strategies were implemented, and a follow-up audit was conducted to determine compliance changes. The baseline audit revealed 53% to 80% compliance with the four EBPs. Barriers to EBPs included lack of health care professionals' knowledge regarding EBPs; lack of PCC, miscommunication, or delayed PCC with patients regarding hospitalization timeline and quality of life; and no standardized documentation or location for PCC within the electronic health record. Improvement strategies included a PCC education program for health care professionals and a concise statement and validation checkbox to the "progress note" in the electronic health record to promote daily PCC with patients. The follow-up audit revealed 20% to 34% compliance rate improvement with EBPs. Annual PCC training should be conducted for health care professionals. Implementing PCC through a multidisciplinary approach can promote more meaningful discussion and efficient decision-making, prioritizing patients' quality of life. http://links.lww.com/IJEBH/A174.

Improving medical record completeness at Wallaga University Referral Hospital: a multidimensional quality improvement project

BackgroundAppropriately documented medical records enhance coordination, patient outcomes and clinical research.ObjectiveThe aim of this project was to improve Wallaga University Referral Hospital’s (WURH) medical record completeness rate from 53% to...

Methodological progress note: Choosing analytic methods for randomized trials.

Methodological progress note: Choosing analytic methods for randomized trials.

Methodological progress note: How to handle race in research according to the research aim.

Methodological progress note: How to handle race in research according to the research aim.

Evaluation of a Large Language Model to Identify Confidential Content in Adolescent Encounter Notes

This cross-sectional study assesses the ability of a language learning model to classify whether a progress note contains confidential information and to identify the specific confidential content in the note.

Clinical progress note: 5 Essential point-of-care ultrasound skills for hospitalists.

Clinical progress note: 5 Essential point-of-care ultrasound skills for hospitalists.