A Letter to Your Care Providers: Implementation and Analysis of a Letter-based Advance Care Planning Initiative for Gynecologic Oncology Patients.

To determine the impact of a letter-based advance care planning (ACP) healthcare improvement (HI) initiative on rates of ACP conversations and documentation among gynecologic oncology (GO) inpatients. An HI initiative was implemented from January to December 2020 to improve ACP documentation among GO inpatients. Patients admitted to the GO service were given ACP packets with a letter-based ACP worksheet. GO inpatients who were interested in learning more about ACP were visited by medical students trained to lead ACP conversations. ACP documentation rates in the EMR (electronic medical record) pre- and post-intervention were evaluated. Descriptive statistics were calculated. Associations between sociodemographic characteristics and ACP documentation were analyzed using logistic regression. There were 172 patients admitted in 2019 (pre-implementation cohort). Of these, 45/172 patients (26%) had an advance directive (AD) documented in their electronic medical record (EMR). Following the implementation of the ACP HI in 2020, 55/168 patients (33%) had an AD documented in their EMR. This was a 7% absolute increase and 27% relative increase from pre-intervention AD documentation rates. Increasing age was associated with an increased likelihood of having an AD in the chart (p = 0.004). Married women were less likely to have an AD in their chart (p = 0.05). An HI utilizing a letter-based ACP packet given to GO inpatients improved AD documentation in the EMR. This HI offers a unique method for introducing ACP to patients. More work is needed to improve the occurrence and documentation of ACP conversations.

Provider education program on the Khorana score to promote venous thromboembolism chemoprophylaxis in patients with gynecologic cancer.

OBJECTIVE: To evaluate the efficacy of a healthcare improvement initiative to improve provider compliance with the American Society of Clinical Oncology (ASCO) guidelines for venous thromboembolism chemoprophylaxis in patients with gynecologic cancer receiving chemotherapy. METHODS: A healthcare improvement initiative was implemented at our institution to improve compliance with American Society of Clinical Oncology venous thromboembolism chemoprophylaxis guidelines in patients receiving chemotherapy with a Khorana score ≥2. Baseline Khorana score and venous thromboembolism data were retrospectively collected for chemotherapy-naïve patients with gynecologic cancer initiating chemotherapy between December 2018 and November 2019. Data for the post-intervention period from December 2019 to December 2020 were captured prospectively. Primary outcome was compliance with American Society of Clinical Oncology guidelines. Secondary outcomes were incidence of venous thromboembolism and complications surrounding venous thromboembolism chemoprophylaxis. RESULTS: We identified 62 patients in the pre-implementation cohort. Approximately half had a Khorana score of ≥2 (52%). Median Khorana score was 2 (range 1-4). None of these patients received prophylactic chemoprophylaxis. Seven (11%) of these patients were diagnosed with venous thromboembolism. Multivariate logistic regression showed increasing Khorana score was associated with increased venous thromboembolism risk (OR 4.9, p=0.01). With cut-off Khorana score of 2, there was no significant increase in venous thromboembolism. However, with a cut-off Khorana score of 3, patients were 15 times more likely to have venous thromboembolism (OR 15.2, p=0.04). In the post-intervention cohort, 22 patients were eligible for chemoprophylaxis and 11 patients were given anticoagulation (50% compliance with guidelines), with no incidence of venous thromboembolism or adverse effects of therapy noted among those receiving chemoprophylaxis. CONCLUSION: Notifying providers of a patient's Khorana score improves compliance with American Society of Clinical Oncology guidelines for venous thromboembolism chemoprophylaxis among chemotherapy patients.

Stopping the revolving door: An exploratory analysis of health care super-utilization in gynecologic oncology.

The objective of this study was to determine the prevalence of and risk factors for health care super-utilization among gynecologic oncology patients at a single academic hospital. A retrospective cohort study of gynecologic oncology patients with an index unplanned encounter between January and December 2018 was performed. Super-utilizers were defined as patients with 3 or more unplanned hospital encounters during a 12-month period starting at the time of the index unplanned encounter. We identified 553 patients with gynecologic cancer. Of those, 37(7%) met inclusion criteria for super-utilizers accounting for 193/310(62%) of unplanned visits. The median number of unplanned visits was 4 (range 3-24). The most common cancers were uterine (N = 15 (41%)) and ovarian (N = 11 (30%)). Nineteen (51%) super-utilizers had advanced stage disease. Phases of oncologic care at index unplanned encounter included primary diagnosis (N = 24 (65%)), recurrence (N = 10 (27%)), and surveillance (N = 2 (5%)). Twelve super-utilizers (32%) had new diagnoses of cancer without prior therapy, 19(51%) had prior chemotherapy, 17(46%) had prior surgery, and 10(27%) had prior radiation therapy at the time of initial encounter. Fifteen super-utilizers (41%) were in the last year of life. The most common reasons for unplanned encounters were pain (66%) and gastrointestinal symptoms (61%). Multivariable analysis adjusting for key variables demonstrated that Medicaid insurance, ASA classification, and disease status are risk factors for health care super-utilization. The majority of health care utilization occurred during the first year of diagnosis. This exploratory analysis suggests an opportunity to decrease health care utilization, particularly during upfront treatment.

Atomistic simulations of the aggregation of small aromatic molecules in homogenous and heterogenous mixtures.

The relatively weak London dispersion forces are the only interactions that could cause aggregation between simple aromatic molecules. The use of molecular dynamics and high-level ab initio computer simulations has been used to describe the aggregation and interactions between molecular systems containing benzene, naphthalene and anthracene. Mixtures containing one type of molecule (homogenous) and more than one type of molecule (heterogenous) were considered. Our results indicate that as molecular weight increases so does the temperature at which aggregation will occur. In all simulations, the mechanism of aggregation is through small clusters coalescing into larger clusters. The structural analysis of the molecules within the clusters reveals that benzene will orient itself in T-shaped and parallel displaced configurations. Molecules of anthracene prefer to orient themselves in a similar manner to a bulk crystal with no T-shaped configuration observed. The aggregation of these aromatic molecules is discussed in the context of astrochemistry with particular reference to the dust formation region around stars.

Group Prenatal Care Reduces Risk of Preterm Birth and Low Birth Weight: A Matched Cohort Study.

BACKGROUND: Group prenatal care is a promising strategy to improve perinatal outcomes. Research in larger more diverse populations with attention to adherence is needed to inform clinical practice recommendations. We examined the impact of group prenatal care on preterm birth and low birth weight in a large metropolitan hospital, accounting for patient adherence, over an 8.5-year period. MATERIALS AND METHODS: We analyzed data from 9,348 pregnant women with a live, singleton birth who received group (CenteringPregnancy or Expect With Me) or individual prenatal care at Vanderbilt University Medical Center from January 2009 through June 2016. Propensity scores were used for matching based on year of delivery, age, race, pregnancy risk, and adequacy of care. The propensity score matched sample included 1,384 group and 5,055 individual prenatal care patients (total = 6,439 women). Preterm birth (<37 weeks gestation) and low birth weight (<2,500 g) were obtained from systematic medical review. Risks were estimated using Poisson regression. RESULTS: Controlling for individual visits, receiving group prenatal care resulted in significantly lower risk of having a preterm birth (Rate ratio [RR] 0.63, 95% confidence interval [CI] 0.49-0.81) and low birth weight baby (RR 0.62, 95% CI 0.47-0.81), compared to receiving individual care only. Women with ≥5 group prenatal care visits experienced even greater benefits: 68% (RR = 0.32; 95% CI 0.22-0.45) and 66% (RR = 0.34; 95% CI 0.23-0.50) risk reduction in preterm birth and low birth weight, respectively. CONCLUSIONS: Participation in group prenatal care may improve birth outcomes. Efforts to promote adoption and sustainability of group prenatal care by health systems may be warranted.

Mechanism for the amorphisation of diamond.

The breakdown of the diamond lattice is explored by ion implantation and molecular dynamics simulations. We show that lattice breakdown is strain-driven, rather than damage-driven, and that the lattice persists until 16% of the atoms have been removed from their lattice sites. The figure shows the transition between amorphous carbon and diamond, with the interfaces highlighted with dashed lines.

Multi-aspect target discrimination using hidden Markov models and neural networks.

This paper presents a new multi-aspect pattern classification method using hidden Markov models (HMMs). Models are defined for each class, with the probability found by each model determining class membership. Each HMM model is enhanced by the use of a multilayer perception (MLP) network to generate emission probabilities. This hybrid system uses the MLP to find the probability of a state for an unknown pattern and the HMM to model the process underlying the state transitions. A new batch gradient descent-based method is introduced for optimal estimation of the transition and emission probabilities. A prediction method in conjunction with HMM model is also presented that attempts to improve the computation of transition probabilities by using the previous states to predict the next state. This method exploits the correlation information between consecutive aspects. These algorithms are then implemented and benchmarked on a multi-aspect underwater target classification problem using a realistic sonar data set collected in different bottom conditions.

Comparison of different classification algorithms for underwater target discrimination.

Classification of underwater targets from the acoustic backscattered signals is considered here. Several different classification algorithms are tested and benchmarked not only for their performance but also to gain insight to the properties of the feature space. Results on a wideband 80-kHz acoustic backscattered data set collected for six different objects are presented in terms of the receiver operating characteristic (ROC) and robustness of the classifiers wrt reverberation.