Tag: pubmed

Mil Med. 2021 Dec 24:usab526. doi: 10.1093/milmed/usab526. Online ahead of print.

ABSTRACT

INTRODUCTION: The purpose of this quality improvement project was to develop and evaluate the use of an electronic medication request dashboard to reduce the amount of time required for medication processing and decrease time lost to workflow interruptions during patient discharge. Delayed discharges are associated with increased health care costs and adverse patient outcomes. Processing of medication requests at discharge contributes to these delays and to workflow interruptions for nursing and pharmacy staff at the project site. Electronic dashboards have been successfully implemented in multiple medical settings to streamline patient processing and enhance communication.

MATERIALS AND METHODS: The Human Protections Office at Carl R. Darnall Army Medical Center (Fort Hood, TX) reviewed and approved the project with a non-human research determination. A multi-disciplinary workgroup with representatives from nursing, pharmacy, and health information technology (HIT) was formed to develop the dashboard. Based on a logic flow diagram of the desired communication, HIT created a medication request form and status dashboard using SharePoint and Nintex workflows. The dashboard was implemented for a 30-day pilot on a 25-bed medical/surgical nursing unit. The time required for medication processing, the time from discharge order to patient exit, the number of phone calls between nursing and pharmacy, and the usability of the medication request process were measured before and after implementation. The results were analyzed with descriptive statistics and evaluated for statistical significance with a P value ≤.05.

RESULTS: With implementation of the dashboard, the average medication processing time decreased from 125 minutes to 48 minutes (P < .0001), and the average patient discharge time decreased from 137 minutes to 117 minutes (P = .002). The usability score of the medication request process increased from 40 to 87 for nursing (P < .0001) and from 62 to 85 for pharmacy (P = .003). The total number of voice calls between nursing and pharmacy decreased from 1,115 to 434, while the total time on voice calls decreased from 33 hours and 50 minutes to 13 hours and 19 minutes (P < .0001).

CONCLUSIONS: The electronic dashboard is an effective method to enhance interdisciplinary communication during patient discharge and significantly reduces medication processing times. However, despite the medication processing time decreasing by over an hour, the discharge time only decreased by 20 minutes. Additional investigation is needed to evaluate other contributors to delayed discharge. A key limitation of this study was the convenience sampling used over a 30-day pilot on a single unit. The process has since been adopted by the entire hospital, and additional analysis could better reveal the impact to the organization. This communication system shows high usability and reduces phone call interruptions for both nursing and pharmacy staff. Additionally, this technology could easily be applied to other communication pathways or request processes across military medicine.

PMID:34950952 | DOI:10.1093/milmed/usab526

Mil Med. 2021 Dec 24:usab519. doi: 10.1093/milmed/usab519. Online ahead of print.

ABSTRACT

INTRODUCTION: Computed tomography (CT) Hounsfield units (HU) recently emerged as a promising screening tool for low bone mineral density (BMD). We hypothesized that CT HU measurements of the thoracic spine would significantly and positively correlate with dual X-ray absorptiometry (DXA) BMD scans of the femoral neck.

MATERIALS AND METHODS: The study included patients with DXA scans and thoracic CT scans at the Walter Reed National Military Medical Center. One author, blinded to the DXA scans, measured HU from the cancellous bone in T4 vertebrae. Another author statistically compared femoral neck DXA T-scores to the CT HU measurements.

RESULTS: The study included 145 patients with CT scans and femoral neck DXAs. The osteoporotic and osteopenic groups had a significant difference in HU measurements compared to the normal group within the study (P < .0001 and .002, respectively). A low BMD screening value of 231 HU provided a sensitivity of 90.1% and negative predictive value of 85.7%.

CONCLUSION: Thoracic vertebrae HU measurements correlate with a low BMD of the femoral neck as determined by DXA T-scores. A high sensitivity and negative predictive value was achieved with a screening value of 231 HU. Utilization of chest or thoracic spine CT imaging as a screening method provides a quick and available screening tool for assessing low BMD in patients with these scans.Level of Evidence: III (Diagnostic).

PMID:34950956 | DOI:10.1093/milmed/usab519

Mil Med. 2021 Dec 24:usab520. doi: 10.1093/milmed/usab520. Online ahead of print.

ABSTRACT

INTRODUCTION: Airway obstruction is the third most common cause of preventable death on the battlefield, accounting for 1%-2% of total combat fatalities. No previous surgical cricothyroidotomy (SC) studies have analyzed the learning curve required to obtain proficiency despite being studied in numerous other surgical technique training experiments. The aims of this study were to establish expert SC performance criteria, develop a novel standardized SC curriculum, and determine the necessary number of practice iterations required by a novice to reach this pre-determined performance goal.

MATERIALS AND METHODS: A standardized checklist and SC performance standards were established based on the performance of 12 board certified Military Health System surgeons with prior experience on performing a SC using a simulated trauma mannequin. Expert-level criteria were defined as a SC time to completion of 40 s or less and checklist score of at least 9/10, including all critical steps. Study subjects included 89 novice providers (54 active-duty first- and second-year medical students and 35 Navy corpsmen). Subjects received instruction on performing a SC using the principles of mastery learning and performed a final test of SC proficiency on a trauma mannequin within a realistic simulated MEDEVAC helicopter. The total number of subject practice attempts, checklist scores, and time to completion were measured and/or blindly scored. Learning curve and exponential plateau equations were used to characterize their improvement in mean time to SC completion and checklist scores.

RESULTS: Mean pre-test knowledge scores for the entire group were 11.8 ± 3.1 out of 24 points. Total mean practice learning plateaued at checklist scores of 9.9/10 after 7 iterations and at a mean completion time of 30.4 s after 10 iterations. During the final test performance in the helicopter, 67.4% of subjects achieved expert-level performance on the first attempt. All subjects achieved expert-level performance by the end of two additional attempts. While a significantly larger proportion of medical students (79.9%) successfully completed the helicopter test on the first attempt compared to corpsmen (54.3%), there were no statistically significant differences in mean SC completion times and checklist scores between both groups (P > 0.05). Medical students performed a SC only 1.3 s faster and scored only 0.16 points higher than corpsmen. The effect size for differences were small to negligible (Cohen’s d range 0.18-0.33 for SC completion time; Cohen’s d range 0.45-0.46 for checklist scores).

CONCLUSION: This study successfully defined SC checklist scores and completion times based on the performance of experienced surgeons on a simulator. Using these criteria and the principles of mastery learning, novices with little knowledge and experience in SC were successfully trained to the level of experienced providers. All subjects met performance targets after training and overall performance plateaued after approximately seven iterations. Over two-thirds of subjects achieved the performance target on the first testing attempt in a simulated helicopter environment. Performance was comparable between medical student and corpsmen subgroups. Further research will assess the durability of maintaining SC skills and the timing for introducing refresher courses after initial skill acquisition.

PMID:34950946 | DOI:10.1093/milmed/usab520

Clin Infect Dis. 2021 Dec 24:ciab1047. doi: 10.1093/cid/ciab1047. Online ahead of print.

ABSTRACT

BACKGROUND: Household contact tracing for tuberculosis (TB) may facilitate TB diagnosis and identify individuals who may benefit from TB preventive therapy (TPT). In this cluster-randomised trial, we investigated whether household contact tracing and intensive TB/HIV screening would improve TB-free survival.

METHODS: Household contacts of index TB patients in two Provinces of South Africa were randomised to home tracing and intensive HIV/TB screening (sputum Xpert and culture; HIV testing with treatment linkage; and TPT, if eligible), or standard of care (SOC, clinic referral letters). The primary outcome was incident TB or death at 15-months. Secondary outcomes included tuberculin skin test (TST) positivity in children ≤14 years and undiagnosed HIV. (ISRCTN16006202).

RESULTS: From December 2016-March 2019, 1,032 index patients (4,459 contacts) and 1,030 (4,129 contacts) were randomised to the intervention and SOC arms. 3.2% (69/2166) of intervention arm contacts had prevalent microbiologically-confirmed TB. At 15-months, the cumulative incidence of TB or death did not differ between the intensive screening (93/3230, 2.9%) and SOC (80/2600, 3.1%) arms (hazard ratio: 0.90, 95% confidence interval (CI): 0.66-1.24). TST positivity was higher in the intensive screening arm (38/845, 4.5%) compared to the SOC arm (15/800, 1.9%, odds ratio: 2.25, 95% CI: 1.07-4.72). Undiagnosed HIV was similar between arms (41/3185, 1.3% vs. 32/2543, 1.3%; odds ratio: 1.02, 95% CI: 0.64-1.64).

CONCLUSIONS: Household contact tracing with intensive screening and referral did not reduce incident TB or death. Providing referral letters to household contacts of index patients is an alternative strategy to home visits in high TB/HIV-prevalence settings.

PMID:34950944 | DOI:10.1093/cid/ciab1047

J Gerontol A Biol Sci Med Sci. 2021 Dec 24:glab382. doi: 10.1093/gerona/glab382. Online ahead of print.

ABSTRACT

This review identifies frequent design and analysis errors in aging and senescence research and discusses best practices in study design, statistical methods, analyses, and interpretation. Recommendations are offered for how to avoid these problems. The following issues are addressed: 1) errors in randomization, 2) errors related to testing within-group instead of between-group differences, 3) failing to account for clustering, 4) failing to consider interference effects, 5) standardizing metrics of effect size, 6) maximum lifespan testing, 7) testing for effects beyond the mean, 8) tests for power and sample size, 9) compression of morbidity versus survival curve-squaring, and 10) other hot topics, including modeling high-dimensional data and complex relationships and assessing model assumptions and biases. We hope that bringing increased awareness of these topics to the scientific community will emphasize the importance of employing sound statistical practices in all aspects of aging and senescence research.

PMID:34950945 | DOI:10.1093/gerona/glab382

Patterns (N Y). 2021 Dec 10;2(12):100393. doi: 10.1016/j.patter.2021.100393. eCollection 2021 Dec 10.

ABSTRACT

The paper highlights how each step of a data science pipeline can be performed in a “responsible” way, taking into account privacy, ethics, and quality issues. Several examples from the Italian public sector contribute to clarifying how data collections and data analyses can be carried out under a responsible view.

PMID:34950908 | PMC:PMC8672189 | DOI:10.1016/j.patter.2021.100393

Patterns (N Y). 2021 Dec 10;2(12):100368. doi: 10.1016/j.patter.2021.100368. eCollection 2021 Dec 10.

ABSTRACT

Numerous arguments strongly support the practice of open science, which offers several societal and individual benefits. For individual researchers, sharing research artifacts such as data can increase trust and transparency, improve the reproducibility of one’s own work, and catalyze new collaborations. Despite a general appreciation of the benefits of data sharing, research data are often only available to the original investigators. For data that are shared, lack of useful metadata and documentation make them challenging to reuse. In this paper, we argue that a lack of incentives and infrastructure for making data useful is the biggest barrier to creating a culture of widespread data sharing. We compare data with code, examine computational environments in the context of their ability to facilitate the reproducibility of research, provide some practical guidance on how one can improve the chances of their data being reusable, and partially bridge the incentive gap. While previous papers have focused on describing ideal best practices for data and code, we focus on common-sense ideas for sharing tabular data for a target audience of academics working in data science adjacent fields who are about to submit for publication.

PMID:34950899 | PMC:PMC8672137 | DOI:10.1016/j.patter.2021.100368

Patterns (N Y). 2021 Oct 27;2(12):100372. doi: 10.1016/j.patter.2021.100372. eCollection 2021 Dec 10.

ABSTRACT

We introduce a new method for single-cell cytometry studies, FAUST, which performs unbiased cell population discovery and annotation. FAUST processes experimental data on a per-sample basis and returns biologically interpretable cell phenotypes, making it well suited for the analysis of complex datasets. We provide simulation studies that compare FAUST with existing methodology, exemplifying its strength. We apply FAUST to data from a Merkel cell carcinoma anti-PD-1 trial and discover pre-treatment effector memory T cell correlates of outcome co-expressing PD-1, HLA-DR, and CD28. Using FAUST, we then validate these correlates in cryopreserved peripheral blood mononuclear cell samples from the same study, as well as an independent CyTOF dataset from a published metastatic melanoma trial. Finally, we show how FAUST’s phenotypes can be used to perform cross-study data integration in the presence of diverse staining panels. Together, these results establish FAUST as a powerful new approach for unbiased discovery in single-cell cytometry.

PMID:34950900 | PMC:PMC8672150 | DOI:10.1016/j.patter.2021.100372

Palliat Care Soc Pract. 2021 Dec 16;15:26323524211063217. doi: 10.1177/26323524211063217. eCollection 2021.

ABSTRACT

AIMS: The study aimed to explore the quality and impact of care provided through an innovative palliative care project to improve the quality of life of older people in an urban informal settlement in Bangladesh.

METHODS: Center for Palliative Care (CPC) at Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, in collaboration with the Worldwide Hospice Palliative Care Alliance (WHPCA) has been operating this community project since 2015. A cross-sectional observational design was used in this program evaluation study. A total of 594 people received services including 227 patients (Group-1) receiving regular and intensive palliative care and 367 patients with less intense needs (Group-2) receiving relatively less support based on need. In addition, current group-1 patients (total 114) and a matched cohort of 58 group-2 patients were interviewed with an experience of care survey questionnaire. Baseline and demographic data were presented in tables. The Z-test was used to measure mean statistical differences between two groups.

RESULTS: Multiple comorbidities were common. Pain was the most frequently noted physical symptom along with anxiety, sadness, and depression as common psychological concerns. Compassionate palliative care for the older people had significant (p < 0.05) impact on psycho-social and spiritual care, caregiver training, responding to emergencies, and reduction of out of pocket healthcare expenditure among the intensive intervention group.

CONCLUSION: Using a community-based approach following this model may play a significant part in expansion of palliative care throughout Bangladesh to meet the huge need and scarcity of such services.

PMID:34950874 | PMC:PMC8689427 | DOI:10.1177/26323524211063217

Patterns (N Y). 2021 Oct 4;2(12):100364. doi: 10.1016/j.patter.2021.100364. eCollection 2021 Dec 10.

ABSTRACT

Current cardiovascular risk assessment tools use a small number of predictors. Here, we study how machine learning might: (1) enable principled selection from a large multimodal set of candidate variables and (2) improve prediction of incident coronary artery disease (CAD) events. An elastic net-based Cox model (ML4H_EN-COX) trained and evaluated in 173,274 UK Biobank participants selected 51 predictors from 13,782 candidates. Beyond most traditional risk factors, ML4H_EN-COX selected a polygenic score, waist circumference, socioeconomic deprivation, and several hematologic indices. A more than 30-fold gradient in 10-year risk estimates was noted across ML4H_EN-COX quintiles, ranging from 0.25% to 7.8%. ML4H_EN-COX improved discrimination of incident CAD (C-statistic = 0.796) compared with the Framingham risk score, pooled cohort equations, and QRISK3 (range 0.754-0.761). This approach to variable selection and model assessment is readily generalizable to a broad range of complex datasets and disease endpoints.

PMID:34950898 | PMC:PMC8672148 | DOI:10.1016/j.patter.2021.100364