Gender dimorphism and age of onset in malignant peripheral nerve sheath tumor preclinical models and human patients.

BackgroundGender-based differences in disease onset in murine models of malignant peripheral nerve sheath tumor (MPNST) and in patients with Neurofibromatosis type-1-(NF-1)-associated or spontaneous MPNST has not been well studied.MethodsForty-three mGFAP-Cre+;Ptenloxp/+;LSL-K-rasG12D/+ mice were observed for tumor development and evaluated for gender disparity in age of MPNST onset. Patient data from the prospectively collected UCLA sarcoma database (1974-2011, n = 113 MPNST patients) and 39 published studies on MPNST patients (n = 916) were analyzed for age of onset differences between sexes and between NF-1 and spontaneous MPNST patients.ResultsOur murine model showed gender-based differences in MPNST onset, with males developing MPNST significantly earlier than females (142 vs. 162 days, p = 0.015). In the UCLA patient population, males also developed MPNST earlier than females (median age 35 vs. 39.5 years, p = 0.048). Patients with NF-1-associated MPNST had significantly earlier age of onset compared to spontaneous MPNST (median age 33 vs. 39 years, p = 0.007). However, expanded analysis of 916 published MPNST cases revealed no significant age difference in MPNST onset between males and females. Similar to the UCLA dataset, patients with NF-1 developed MPNST at a significantly younger age than spontaneous MPNST patients (p < 0.0001, median age 28 vs. 41 years) and this disparity was maintained across North American, European, and Asian populations.ConclusionsAlthough our preclinical model and single-institution patient cohort show gender dimorphism in MPNST onset, no significant gender disparity was detected in the larger MPNST patient meta-dataset. NF-1 patients develop MPNST 13 years earlier than patients with spontaneous MPNST, with little geographical variance

Predictive Modelling of Bone Age through Classification and Regression of Bone Shapes

Bone age assessment is a task performed daily in hospitals worldwide. This involves a clinician estimating the age of a patient from a radiograph of the non-dominant hand. Our approach to automated bone age assessment is to modularise the algorithm into the following three stages: segment and verify hand outline; segment and verify bones; use the bone outlines to construct models of age. In this paper we address the final question: given outlines of bones, can we learn how to predict the bone age of the patient? We examine two alternative approaches. Firstly, we attempt to train classifiers on individual bones to predict the bone stage categories commonly used in bone ageing. Secondly, we construct regression models to directly predict patient age. We demonstrate that models built on summary features of the bone outline perform better than those built using the one dimensional representation of the outline, and also do at least as well as other automated systems. We show that models constructed on just three bones are as accurate at predicting age as expert human assessors using the standard technique. We also demonstrate the utility of the model by quantifying the importance of ethnicity and sex on age development. Our conclusion is that the feature based system of separating the image processing from the age modelling is the best approach for automated bone ageing, since it offers flexibility and transparency and produces accurate estimate

The influence of patient and doctor gender on diagnosing coronary heart disease

Using novel methods, this paper explores sources of uncertainty and gender bias in primary care doctors’ diagnostic decision making about coronary heart disease (CHD). Claims about gendered consultation styles and quality of care are re-examined, along with the adequacy of CHD models for women. Randomly selected doctors in the UK and the US (n=112, 56 per country, stratified by gender) were shown standardised videotaped vignettes of actors portraying patients with CHD. ‘Patients’ age, gender, ethnicity and social class were varied systematically. During interviews, doctors gave free-recall accounts of their decision making, which were analysed to determine patient and doctor gender effects. We found differences in male and female doctors’ responses to different types of patient information. Female doctors recall more patient cues overall, particularly about history presentation, and particularly amongst women. Male doctors appear less affected by patient gender but both male and especially female doctors take more account of male patients’ age and consider more age-related disease possibilities for men than women. Findings highlight the need for better integration of knowledge about female presentations within accepted CHD risk models, and do not support the contention that women receive better quality care from female doctors

Patient characteristics associated with objective measures of digital health tool use in the United States: A literature review.

The study sought to determine which patient characteristics are associated with the use of patient-facing digital health tools in the United States.We conducted a literature review of studies of patient-facing digital health tools that objectively evaluated use (eg, system/platform data representing frequency of use) by patient characteristics (eg, age, race or ethnicity, income, digital literacy). We included any type of patient-facing digital health tool except patient portals. We reran results using the subset of studies identified as having robust methodology to detect differences in patient characteristics.We included 29 studies; 13 had robust methodology. Most studies examined smartphone apps and text messaging programs for chronic disease management and evaluated only 1-3 patient characteristics, primarily age and gender. Overall, the majority of studies found no association between patient characteristics and use. Among the subset with robust methodology, white race and poor health status appeared to be associated with higher use.Given the substantial investment in digital health tools, it is surprising how little is known about the types of patients who use them. Strategies that engage diverse populations in digital health tool use appear to be needed.Few studies evaluate objective measures of digital health tool use by patient characteristics, and those that do include a narrow range of characteristics. Evidence suggests that resources and need drive use

Colorectal Cancer Screening

The USPSTF gives Colorectal Cancer screening a Grade A recommendation, beginning at age 50 years and continuing until age 75 years. Screening colonoscopies are proven to show dramatic decreased incidence and mortality from colorectal cancer. This project evaluates the percentage of patients at Stowe Family Practice and Community Health Services of Lamoille Valley who are meeting these guidelines. Using chart reviews and patient interviews, the project seeks ways to increase screening rates through provider-patient shared decision making tools and educational materials for the office.https://scholarworks.uvm.edu/fmclerk/1264/thumbnail.jp

Examination of Acute Care Nurses Ability to Engage in Patient Education Related to Physical Activity as a Health Behavior

Physical activity is important for management and prevention of chronic disease. The current physical activity guidelines recommend engaging in physical activity for at least 30 minutes per day on at least 5 days a week. Acute care settings may present opportunities for patient education about physical activity. PURPOSE: The purpose of this study was to examine the ability of acute care nurses to engage in patient education regarding physical activity as a health behavior. Additionally, this study examined the influence of level of nurse training, age, personal physical activity and years of experience on these outcomes. METHODS: Nurses from an academic medical center (N=194) were surveyed. Knowledge of current physical activity guidelines, rank of importance of physical activity as a patient care activity and a healthy lifestyle behavior, and confidence to counsel patients about physical activity were queried. RESULTS: Of nurses queried, 32.5% reported days per week and 83% reported minutes per day to engage in physical activity consistent with current guidelines. Physical activity counseling was ranked least important of ten patient care activities and fifth as a healthy lifestyle behavior. The majority of nurses (51%) felt some degree of confidence to counsel patients regarding physical activity. Baccalaureate level nurses were more likely to be consistent with physical activity guidelines than master’s level nurses. Nurses <25 years of age were more current in knowledge of physical activity guidelines than nurses ≥41 years of age. Nurses who exercised were more likely to report knowing current physical activity guidelines. Reported time spent counseling patientsregarding physical activity averaged 6 minutes per patient per day. CONCLUSION: Acute care nurses are counseling patients regarding physical activity although it is ranked least important of ten patient care activities. Future research should include studying: a variety of patient populations; other hospital settings; objective measures of evaluation; and nurses’ training regarding physical activity

Implementation of a Deconditioning Prevention Program: Getting Dressed Makes a Difference

Implementation of a Deconditioning Prevention Program: Getting Dressed Makes a Difference Seleem R. Choudhury MSN, MBA, RN, CEN, FAEN Purpose. Deconditioning by immobility or bed rest affects essential body systems and diminishes functional capacity. Individuals age 65 and older have more hospital stays than any other age group. they also account for one out of three hospital admissions costing healthcare over $330 Billion annually. Numerous studies demonstrate this age group often struggle to get back to normal level of activity. . Empowering patients to dress and wear their own clothes can prevent deconditioning. Benefits to hospitals include reduced cost through admissions, improved patient flow by reducing their length of stay (LOS) which can lead to timelier admissions for other patients. A longer LOS also raises the probability of a hospital-acquired condition (HAC), which is an undesirable situation or condition that affects a patient during a hospital stay. Finally, patients who get dressed may feel more satisfied with the care they receive. Methods. To prevent deconditioning through the development of promoting activity by getting patients dressed which reduces the risk of deconditioning as measured by three outcomes: 1) LOS, 2) HAC, 3)Patient Satisfaction. LOS and HAC data were collected from chart review. Patient satisfaction was evaluated by HCAHPS metrics. Results. Three months of data were analyzed and compared in 2016 and 2017. The data were also segregated into age groups to analyze any benefit to over 65-year-olds. The comparison did not demonstrate clear correlation that the deconditioning program impacted the LOS and Patient Satisfaction. LOS comparison (n-832) showed improvement in month three in ages 18-59 and over 75. The ages 55-74 showed no decrease in LOS however recalculating the data from median versus mean showed all age groups LOS did decrease. Patient Satisfaction metrics (n-207) showed no clear inference or consistent pattern that deconditioning program improved satisfaction. Scores stayed comparable to previous years, especially among 18-54 age group. The 75 plus age group did see a decline in scores. Hospital Acquired Complications (HAC) was not a reliable indicator with only one incident in a two-year period. Methodological flaws in unreliable data and insufficient ability to separate variables within the electronic health record confounded comparison. Finally, the multi-faceted nature of discharges limited all of the indicators’ validity. Conclusions. The importance of being active is universally understood, yet hospitals struggle to implement this action. Data of 1-year mortalities of over 65 support that hospitals need to do more to improve this outcome. A simple program of getting dressed everyday has the potential to reduce LOS and with further study, improve 1-year mortality. This study also showed that whilst patient satisfaction is not increased, it also does not significantly decrease therefore it’s possible to assume that our patients want hospital staff to be assertive with preventing Deconditioning Syndrome. Finally, whilst not supported in this study future work, could analyze staff’s perception of patient readiness for discharge alongside data gradually demonstrating a decrease of LOS of 75-year old

Prognostic value of troponins in acute coronary syndrome depends upon patient age

Peer reviewedPostprin

Primer on adult patient satisfaction in perioperative settings.

The topic of patient satisfaction has gained increasing importance over the past decade. Due to the impact of patient satisfaction on health care quality, understanding factors that predict satisfaction is vital. The purpose of this review is to examine the literature and identify factors related to patient perioperative satisfaction as well as predictive variables that, if modified, can enhance satisfaction scores of patients undergoing surgery. Our review reports that patient satisfaction scores are affected by modifiable factors such as clinician-patient communication, information provision to patients, and operational function of a hospital. Non-modifiable factors affecting patient satisfaction scores include patient demographics such as gender, age, and education. In order to enhance patient perioperative satisfaction, we suggest that anesthesiologists and surgeons focus their efforts on enhancing their communication skills and providing information that is appropriately tailored to the understanding of their patients

An online experiment to assess bias in professional medical coding.

BackgroundMultiple studies have documented bias in medical decision making, but no studies have examined whether this bias extends to medical coding practices. Medical coding is foundational to the US health care enterprise. We evaluate whether bias based on patient characteristics influences specific coding practices of professional medical coders.MethodsThis is an online experimental study of members of a national professional medical coding organization. Participants were randomly assigned a set of six clinical scenarios reflecting common medical conditions and asked to report encounter level of service codes for these clinical scenarios. Clinical scenarios differed by patient demographics (race, age, gender, ability) or social context (food insecurity, housing security) but were otherwise identical. We estimated Ordinary Least Squares regression models to evaluate differences in outcome average visit level of service by patient demographic characteristics described in the clinical scenarios; we adjusted for coders' age, gender, race, and years of coding experience.ResultsThe final analytic sample included 586 respondents who coded at least one clinical scenario. Higher mean level of service was assigned to clinical scenarios describing seniors compared to middle-aged patients in two otherwise identical scenarios, one a patient with type II diabetes mellitus (Coef: 0.28, SE: 0.15) and the other with rheumatoid arthritis (Coef: 0.30, SE: 0.13). Charts describing women were assigned lower level of service than men in patients with asthma exacerbation (Coef: -0.25, SE: 0.13) and rheumatoid arthritis (Coef: -0.20, SE: 0.12). There were no other significant differences in mean complexity score by patient demographics or social needs.ConclusionWe found limited evidence of bias in professional medical coding practice by patient age and gender, though findings were inconsistent across medical conditions. Low levels of observed bias may reflect medical coding workflow and training practices. Future research is needed to better understand bias in coding and to identify effective and generalizable bias prevention practices