Johns Hopkins School of Medicine
Ontology highlight
ABSTRACT:
PROVIDER: EGAO00000001096 | EGA |
REPOSITORIES: EGA
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Project description:Tumor genomic profiling for personalized oncology therapy is being widely applied in clinical practice even as it is being evaluated more formally in clinical trials. Given the complexities of genomic data and its application to clinical use, molecular tumor boards with diverse expertise can provide guidance to oncologists and patients seeking to implement personalized genetically targeted therapy in practice. A multidisciplinary molecular tumor board reviewed tumor molecular profiling reports from consecutive referrals at the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins over a 3-year period. The tumor board weighed evidence for actionability of genomic alterations identified by molecular profiling and provided recommendations including US Food and Drug Administration-approved drug therapy, clinical trials of matched targeted therapy, off-label use of such therapy, and additional tumor or germline genetic testing. One hundred fifty-five patients were reviewed. Actionable genomic alterations were identified in 132 patients (85%). Off-label therapies were recommended in 37 patients (24%). Eleven patients were treated off-label, and 13 patients were enrolled onto clinical trials of matched targeted therapies. Median progression-free survival of patients treated with matched therapies was 5 months (95% CI, 2.9 months to not reached), and the progression-free survival probability at 6 months was 43%(95% CI, 26% to 71%). Lack of locally available clinical trials was the major limitation on clinical actionability of tumor profiling reports. The molecular tumor board recommended off-label targeted therapies for a quarter of all patients reviewed. Outcomes were heterogeneous, although 43% of patients receiving genomically matched therapy derived clinical benefit lasting at least 6 months. Until more data become available from precision oncology trials, molecular tumor boards can help guide appropriate use of tumor molecular testing to direct therapy.
| S-EPMC6039131 | biostudies-literature
Project description:Organisation EGAO00000000339
| EGAO00000000339 | EGA
Project description:PurposeWhile a strong learning environment is critical to medical student education, the assessment of medical school learning environments has confounded researchers. Our goal was to assess the validity and utility of the Johns Hopkins Learning Environment Scale (JHLES) for preclinical students at three Malaysian medical schools with distinct educational and institutional models. Two schools were new international partnerships, and the third was school leaver program established without international partnership.MethodsFirst- and second-year students responded anonymously to surveys at the end of the academic year. The surveys included the JHLES, a 28-item survey using five-point Likert scale response options, the Dundee Ready Educational Environment Measure (DREEM), the most widely used method to assess learning environments internationally, a personal growth scale, and single-item global learning environment assessment variables.ResultsThe overall response rate was 369/429 (86%). After adjusting for the medical school year, gender, and ethnicity of the respondents, the JHLES detected differences across institutions in four out of seven domains (57%), with each school having a unique domain profile. The DREEM detected differences in one out of five categories (20%). The JHLES was more strongly correlated than the DREEM to two thirds of the single-item variables and the personal growth scale. The JHLES showed high internal reliability for the total score (α=0.92) and the seven domains (α, 0.56-0.85).ConclusionThe JHLES detected variation between learning environment domains across three educational settings, thereby creating unique learning environment profiles. Interpretation of these profiles may allow schools to understand how they are currently supporting trainees and identify areas needing attention.
| S-EPMC4536359 | biostudies-literature
Project description: Not available
| S-EPMC7144612 | biostudies-literature
Project description:ObjectivesRapid telehealth adoption happened at the onset of the coronavirus disease 2019 (COVID-19) pandemic, resulting in a move from in-person predominant to telehealth predominant care delivery. Later, in person visits rebounded with telehealth options remaining. This study aimed to assess differences in healthcare utilization during this changing landscape in terms of health equity determinants.Materials and methodsThis was an observational cohort study of Johns Hopkins Medicine (JHM) patients. We analyzed utilization of video, telephone, and in-person patient-provider visits by eligible patients between March 16, 2019 and December 31, 2020. Percent changes in average weekly patient-provider visits from pre-pandemic (March 16, 2019-June 30, 2019) to early 2020 pandemic (March 16, 2020-June 30, 2020) and from pre-pandemic (July 1, 2019-December 31, 2019) to late 2020 pandemic (July 1, 2020-December 31, 2020). We used a quantile cut off technique to describe disproportionately smaller or greater drops in visits during the first year of the pandemic among health equity determinant groups and according to visit specialty, when compared to the total population.ResultsThere was a 39% drop in patient-provider visits from the pre-pandemic to the early 2020 pandemic period, and a 24% drop from pre-pandemic to the late 2020 pandemic period. We discovered 21 groups according to health equity determinates and visit departments with patterns of disproportionately smaller or greater drops in visits during the first year of the pandemic, when compared to the total population: Pattern 1 -smaller drop in visits early and late 2020 (age 45-64, Medicare insurance, high poverty and high unemployment; mental health and medical specialty visits -P < .001); Pattern 2 -greater drop in visits early 2020 only (age 65-84; OB/GYN and surgical specialty visits-P < .001); Pattern 3 -greater drop in visits early and late 2020 (age 0-5, age 6-17, age 85+, Asian race, Hispanic or Latino ethnicity, private insurance-P < .001); and Pattern 4-smaller drop in visits in early 2020 when compared to late 2020. The age 18-44 group showed a smaller drop in visits early 2020 and then visit levels similar to the total population late 2020. Primary care visits were similar to the total population early 2020 and then a smaller drop in visits late 2020 (P < .001).DiscussionOur study provides evidence of health equity determinant groups having disproportionally smaller or greater drops in visits during the first year of the pandemic. The observed differences may have been influenced by changing telehealth offerings during the first year of the pandemic. Groups with disproportionately smaller drops in visits early 2020 (Pattern #1 and age 18-44 group in Pattern #4), suggests more success with adopting telehealth among those groups. Whereas groups with disproportionately greater drops in visits early 2020 (Pattern #2 and Pattern #3), suggests less success with telehealth adoption. For Pattern #4, more clarification is needed on how changes in telehealth offerings contributed to the downward trend in visits observed from early to late 2020.ConclusionWe describe 4 main patterns to characterize groups with disproportionately smaller or greater drops in visits during the first year of the pandemic. While this work did not specifically study vulnerable populations, these patterns set the stage for further studies of such groups.
| S-EPMC11458551 | biostudies-literature
Project description:Integrase inhibitors (INSTIs) are recommended by expert panels as initial therapy for people with HIV. Because there can be disparities in prescribing and uptake of novel and/or recommended therapies, this analysis assessed potential INSTI prescribing disparities using a combined data set from the Johns Hopkins HIV Clinical Cohort and the DC Cohort. We performed multivariable logistic regression to identify factors associated with ever being prescribed an INSTI. Disparities were noted, including clinic location, age, and being transgender. Identifying disparities may allow clinicians to focus their attention on these individuals and ensure that therapy decisions are grounded in valid clinical reasons.
| S-EPMC8496514 | biostudies-literature
Project description:ProblemVenous thromboembolism (VTE) is a common cause of potentially preventable mortality, morbidity, and increased medical costs. Risk-appropriate prophylaxis can prevent most VTE events, but only a small fraction of patients at risk receive this treatment.DesignProspective quality improvement programme.SettingJohns Hopkins Hospital, Baltimore, Maryland, USA.Strategies for changeA multidisciplinary team established a VTE Prevention Collaborative in 2005. The collaborative applied the four step TRIP (translating research into practice) model to develop and implement a mandatory clinical decision support tool for VTE risk stratification and risk-appropriate VTE prophylaxis for all hospitalised adult patients. Initially, paper based VTE order sets were implemented, which were then converted into 16 specialty-specific, mandatory, computerised, clinical decision support modules.Key measures for improvementVTE risk stratification within 24 hours of hospital admission and provision of risk-appropriate, evidence based VTE prophylaxis.Effects of changeThe VTE team was able to increase VTE risk assessment and ordering of risk-appropriate prophylaxis with paper based order sets to a limited extent, but achieved higher compliance with a computerised clinical decision support tool and the data feedback which it enabled. Risk-appropriate VTE prophylaxis increased from 26% to 80% for surgical patients and from 25% to 92% for medical patients in 2011.Lessons learntA computerised clinical decision support tool can increase VTE risk stratification and risk-appropriate VTE prophylaxis among hospitalised adult patients admitted to a large urban academic medical centre. It is important to ensure the tool is part of the clinician's normal workflow, is mandatory (computerised forcing function), and offers the requisite modules needed for every clinical specialty.
| S-EPMC4688421 | biostudies-literature