Patient and Health System Experience With Implementation of an Enterprise-Wide Telehealth Scheduled Video Visit Program: Mixed-Methods Study.

BACKGROUND: Real-time video visits are increasingly used to provide care in a number of settings because they increase access and convenience of care, yet there are few reports of health system experiences. OBJECTIVE: The objective of this study is to report health system and patient experiences with implementation of a telehealth scheduled video visit program across a health system. METHODS: This is a mixed methods study including (1) a retrospective descriptive report of implementation of a telehealth scheduled visit program at one large urban academic-affiliated health system and (2) a survey of patients who participated in scheduled telehealth visits. Health system and patient-reported survey measures were aligned with the National Quality Forum telehealth measure reporting domains of access, experience, and effectiveness of care. RESULTS: This study describes implementation of a scheduled synchronous video visit program over an 18-month period. A total of 3018 scheduled video visits were completed across multiple clinical departments. Patient experiences were captured in surveys of 764 patients who participated in telehealth visits. Among survey respondents, 91.6% (728/795) reported satisfaction with the scheduled visits and 82.7% (628/759) reported perceived quality similar to an in-person visit. A total of 86.0% (652/758) responded that use of the scheduled video visit made it easier to get care. Nearly half (46.7%, 346/740) of patients estimated saving 1 to 3 hours and 40.8% (302/740) reported saving more than 3 hours of time. The net promoter score, a measure of patient satisfaction, was very high at 52. CONCLUSIONS: A large urban multihospital health system implemented an enterprise-wide scheduled telehealth video visit program across a range of clinical specialties with a positive patient experience. Patients found use of scheduled video visits made it easier to get care and the majority perceived time saved, suggesting that use of telehealth for scheduled visits can improve potential access to care across a range of clinical scenarios with favorable patient experiences

Global Epidemiology of Lung Cancer.

While lung cancer has been the leading cause of cancer-related deaths for many years in the United States, incidence and mortality statistics - among other measures - vary widely worldwide. The aim of this study was to review the evidence on lung cancer epidemiology, including data of international scope with comparisons of economically, socially, and biologically different patient groups. In industrialized nations, evolving social and cultural smoking patterns have led to rising or plateauing rates of lung cancer in women, lagging the long-declining smoking and cancer incidence rates in men. In contrast, emerging economies vary widely in smoking practices and cancer incidence but commonly also harbor risks from environmental exposures, particularly widespread air pollution. Recent research has also revealed clinical, radiologic, and pathologic correlates, leading to greater knowledge in molecular profiling and targeted therapeutics, as well as an emphasis on the rising incidence of adenocarcinoma histology. Furthermore, emergent evidence about the benefits of lung cancer screening has led to efforts to identify high-risk smokers and development of prediction tools. This review also includes a discussion on the epidemiologic characteristics of special groups including women and nonsmokers. Varying trends in smoking largely dictate international patterns in lung cancer incidence and mortality. With declining smoking rates in developed countries and knowledge gains made through molecular profiling of tumors, the emergence of new risk factors and disease features will lead to changes in the landscape of lung cancer epidemiology

Quality Improvement for the JeffMD Clinical Experience Program

Introduction: The JeffMD curriculum at Sidney Kimmel Medical College, which completed its inaugural year in the spring of 2018, aims to prepare future physicians to “thrive in the landscape of modern healthcare.” The curriculum is based upon the knowledge that human health exists interdependently with all aspects of life, including but not limited to social, health care system, behavioral, and biological factors. The JeffMD Clinical Experience Program (CE) is a mandatory, experiential, value-added component of the curriculum. Through the CE course, which spans the 21-month preclinical period, students work with a Community Health Worker to screen patients for social needs and connect them to community resources. Objective: The purpose of this Quality Improvement study was twofold. First, we sought to evaluate the extent to which the first year of the CE program (1) contributed to student learning, and (2) added value to the clinical sites. Second, we sought to implement site-specific improvements based upon our results. Methods: We followed the Plan-Do-Study-Act (PDSA) model. We measured the current performance of the CE program through electronic surveys administered to the 260 first-year medical students who participated. The surveys included free response and Likert scale questions. We also conducted small group interviews with key stakeholders from four of the clinical sites using a questionnaire adapted from Penn State. Results: Students valued the opportunity to interact with patients and learn about social determinants of health; however, they did not find the CE program to be an effective learning experience. Key themes from the clinical site interviews included lack of student initiative, physical space constraints, communication barriers, and the positive contribution of Community Health Workers. Conclusion: We performed cause analyses and implemented clinical site-specific changes based upon our results. We believe that the student experience will improve from year-to-year so long as we continue to incorporate feedback from students and other stakeholders

Highly selective and sensitive macrocycle-based dinuclear foldamer for fluorometric and colorimetric sensing of citrate in water.

The selective detection of citrate anions is essential for various biological functions in living systems. A quantitative assessment of citrate is required for the diagnosis of various diseases in the human body; however, it is extremely challenging to develop efficient fluorescence and color-detecting molecular probes for sensing citrate in water. Herein, we report a macrocycle-based dinuclear foldamer (1) assembled with eosin Y (EY) that has been studied for anion binding by fluorescence and colorimetric techniques in water at neutral pH. Results from the fluorescence titrations reveal that the 1·EY ensemble strongly binds citrate anions, showing remarkable selectivity over a wide range of inorganic and carboxylate anions. The addition of citrate anions to the 1·EY adduct led to a large fluorescence enhancement, displaying a detectable color change under both visible and UV light in water up to 2 μmol. The biocompatibility of 1·EY as an intracellular carrier in a biological system was evaluated on primary human foreskin fibroblast (HF) cells, showing an excellent cell viability. The strong binding properties of the ensemble allow it to be used as a highly sensitive, detective probe for biologically relevant citrate anions in various applications

3,3′-Bis(quinolin-8-yl)-1,1′-[4,4′-methyl­enebis(4,1-phenyl­ene)]diurea

The title compound, C33H26N6O2, contains two 3-(quinolin-8-yl)urea groups linked to a diphenyl­methane. The asymmetric unit contains two mol­ecules, A and B. Each quinoline plane is essentially parallel to the attached urea unit [dihedral angles = 8.97 (18) and 8.81 (19) in molecule A and 18.47 (18) and 4.09 (19)° in molecule B]. The two benzene rings are twisted, making dihedral angles of 81.36 (8)° in A and 87.20 (9)° in B. The molecular structures are stabilized by intramolecular N—H⋯N hydrogen bonds. In the crystal, each urea O atom is involved in two N—H⋯O hydrogen bonds, generating two inter­penetrating three-dimensional sets of mol­ecules

Hidden Markov Models and their Application for Predicting Failure Events

We show how Markov mixed membership models (MMMM) can be used to predict the degradation of assets. We model the degradation path of individual assets, to predict overall failure rates. Instead of a separate distribution for each hidden state, we use hierarchical mixtures of distributions in the exponential family. In our approach the observation distribution of the states is a finite mixture distribution of a small set of (simpler) distributions shared across all states. Using tied-mixture observation distributions offers several advantages. The mixtures act as a regularization for typically very sparse problems, and they reduce the computational effort for the learning algorithm since there are fewer distributions to be found. Using shared mixtures enables sharing of statistical strength between the Markov states and thus transfer learning. We determine for individual assets the trade-off between the risk of failure and extended operating hours by combining a MMMM with a partially observable Markov decision process (POMDP) to dynamically optimize the policy for when and how to maintain the asset.Comment: Will be published in the proceedings of ICCS 2020; @Booklet{EasyChair:3183, author = {Paul Hofmann and Zaid Tashman}, title = {Hidden Markov Models and their Application for Predicting Failure Events}, howpublished = {EasyChair Preprint no. 3183}, year = {EasyChair, 2020}

1,3-Phenyl­enediammonium dinitrate

In the title compound, C6H10N2 2+·2NO3 −, the dication lies on a crystallographic twofold rotation axis. The nitrate ions are linked to the dications though N—H⋯O hydrogen bonds, forming a three-dimensional network

Preoperative predictors of death and sustained ventricular tachycardia after pulmonary valve replacement in patients with repaired tetralogy of fallot enrolled in the INDICATOR Cohort

Background -Risk factors for adverse clinical outcomes have been identified in patients with repaired tetralogy of Fallot (rTOF) before pulmonary valve replacement (PVR). However, pre-PVR predictors for post-PVR sustained ventricular tachycardia (VT) and death have not been identified. Methods -Patients with rTOF enrolled in the INDICATOR cohort-a 4-center international cohort study- who had a comprehensive preoperative evaluation and subsequently underwent PVR were included. Pre-procedural clinical, electrocardiogram, cardiovascular magnetic resonance (CMR), and postoperative outcome data were analyzed. Cox proportional hazards multivariable regression analysis was used to evaluate factors associated with time from pre-PVR CMR until the primary outcome-death, aborted sudden cardiac death, or sustained VT. Results -Of the 452 eligible patients (median age at PVR 25.8 years), 36 (8%) reached the primary outcome (27 deaths, 2 resuscitated death, and 7 sustained VT) at a median time after PVR of 6.5 years. Cox proportional hazards regression identified pre-PVR right ventricular (RV) ejection fraction < 40% (hazard ratio [HR] 2.39; 95% confidence interval [CI] 1.18 to 4.85; P = 0.02), RV mass-to-volume ratio ≥ 0.45 g/mL (HR 4.08; 95%, CI 1.57 to 10.6; P = 0.004), and age at PVR ≥ 28 years (HR 3.10; 95% CI 1.42 to 6.78; P = 0.005) as outcome predictors. In a subgroup analysis of 230 patients with Doppler data, predicted RV systolic pressure ≥40 mm Hg was associated with the primary outcome (HR 3.42; 95% CI 1.09 to 10.7; P = 0.04). Preoperative predictors of a composite secondary outcome-postoperative arrhythmias and heart failure-included older age at PVR, pre-PVR atrial tachyarrhythmias, and a higher left ventricular end-systolic volume index. Conclusions -In this observational investigation of patients with rTOF, an older age at PVR and pre-PVR RV hypertrophy and dysfunction were predictive of shorter time to postoperative death and sustained VT. These findings may inform the timing of PVR if confirmed by prospective clinical trials

Comparative analysis of long DNA sequences by per element information content using different contexts

BACKGROUND: Features of a DNA sequence can be found by compressing the sequence under a suitable model; good compression implies low information content. Good DNA compression models consider repetition, differences between repeats, and base distributions. From a linear DNA sequence, a compression model can produce a linear information sequence. Linear space complexity is important when exploring long DNA sequences of the order of millions of bases. Compressing a sequence in isolation will include information on self-repetition. Whereas compressing a sequence Y in the context of another X can find what new information X gives about Y. This paper presents a methodology for performing comparative analysis to find features exposed by such models. RESULTS: We apply such a model to find features across chromosomes of Cyanidioschyzon merolae. We present a tool that provides useful linear transformations to investigate and save new sequences. Various examples illustrate the methodology, finding features for sequences alone and in different contexts. We also show how to highlight all sets of self-repetition features, in this case within Plasmodium falciparum chromosome 2. CONCLUSION: The methodology finds features that are significant and that biologists confirm. The exploration of long information sequences in linear time and space is fast and the saved results are self documenting.