Second Survey of County Health Departments of Kansas and COVID 19: Time for Change in Model for Pandemic Response

Introduction. SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2) causing COVID-19 (Coronavirus Disease 2019) continues to be widespread in Kansas.  County health departments are trying to contain this pandemic.  Methods. This second survey of Kansas county health department directors occurred from August 7 to September 7, 2020.  Since the first survey in April, there have been significant increases in the number of positive cases of COVID-19 and related deaths.  Thus, the aim of the study was to re-evaluate county-level containment efforts and assess shortfalls that were previously identified in the April 2020 survey. Results. In total, 41 out of 105 directors responded to the survey.  Generally, respondents said there were increased supplies for testing, increased testing centers, shorter time to get test results, and in some cases, increased funding.  However, the number of people involved in contact tracing had not substantially increased, which was one of the recommended changes for improving containment.  Moreover, of those persons who were tested, only a few (18%) counties inquired if they wear masks in public.  From comments reported, there was a sense of employees being overwhelmed, especially among the smaller county health departments. Conclusions. As the cases of and deaths from COVID-19 are increasing in the state, especially in high density areas, the respondents to our survey indicate there is continued need for additional  funding with easy access, increased staffing, especially for contact tracing, and significant help for effective messaging to improve adherence to public health directives

A Survey of County Health Departments of Kansas Regarding COVID-19

Introduction. SARS-CoV-2 virus (severe acute respiratory syndrome coronavirus 2) causing COVID-19 (Coronavirus Disease 2019) initially was identified in China in December 2019. It has resulted in a pandemic with increasing spread of the virus in the US. The county health departments around US are spearheading the response to contain the spread of this virus. Methods. This project was a survey of county health departments in the state of Kansas with data collection period from 4/15 to 4/24/2020. This study evaluated the staffing, resources, and funding of these health departments and how it was affecting the efforts to contain COVID-19. Descriptive statistics were used to summarize the responses. Results. A total of 75% of the county health departments in Kansas responded to the survey. In 89% of locations, the staffing had not increased. Most health departments had an average of five people and the four largest ones had 30 to 98 staff working on COVID-19. Most locations used the Kansas Department of Health and Environment criteria for testing and used a combination of state or private laboratories. The results of the tests were available three days or longer in 62% and after five days in 14% of sites. All locations were active in contact tracing, but most had 1-3 people for this purpose and in 90% the contact tracing interview was via phone calls. There was no change in funding in 21% and decreased funding in 8.5% of health departments. Most locations had an average of five nasopharyngeal swabs on the day of the survey. The most common needs expressed were help to increase testing capability, more public education, more personal protective equipment, increased personnel, and assistance with contract tracing. Conclusions. There is an urgent need in Kansas to increase support to county health departments for testing capability, personal protective equipment, increased number of staff, increased help with contact tracing, and especially increase support for public education

Workplace Stress and Productivity: A Cross-Sectional Study

INTRODUCTION. The primary purpose of this study was to evaluate the association between workplace stress and productivity among employees from worksites participating in a WorkWell KS Well-Being workshop and assess any differences by gender and race. METHODS. A multi-site, cross-sectional study was conducted to survey employees across four worksites participating in a WorkWell KS Well Being workshop to assess levels of stress and productivity. Stress was measured by the Perceived Stress Scale (PSS) and productivity was measured by the Health and Work Questionnaire (HWQ). Pearson correlations were conducted to measure the association between stress and productivity scores. T-tests evaluated differences in scores by gender and race. RESULTS. Of the 186 participants who completed the survey, most reported being white (94%), female (85%), married (80%), and having a college degree (74%). A significant inverse relationship was observed between the scores for PSS and HWQ, r = -0.35, p < 0.001; as stress increased, productivity appeared to decrease. Another notable inverse relationship was PSS with Work Satisfaction subscale, r = -0.61, p < 0.001. One difference was observed by gender- males scored significantly higher on the HWQ Supervisor Relations subscale compared with females, 8.4 (2.1) vs. 6.9 (2.7), respectively, p = 0.005. CONCLUSIONS. Scores from PSS and the HWQ appeared to be inversely correlated; higher stress scores were significantly associated with lower productivity scores. This negative association was observed for all HWQ subscales, but was especially strong for work satisfaction. This study also suggests that males may have better supervisor relations compared with females, although no gender differences were observed by perceived levels of stress

Contribution of the BioFire® FilmArray® Meningitis/Encephalitis Panel:: Assessing Antimicrobial Duration and Length of Stay

Introduction. Traditional evaluation of meningitis includes cerebrospinalfluid (CSF) culture and gram stain to pinpoint specific causalorganisms. The BioFire® FilmArray® Meningitis/Encephalitis (ME)Panel has been implemented as a more timely evaluation method.This study sought to assess if the BioFire® ME Panel was associatedwith a decreased length of stay or decreased antimicrobial durationwhen used in the diagnosis of meningitis or encephalitis.Methods.xA case, historical-control, chart review was performed onpatients admitted to a regional medical center with CSF pleocytosisduring Cohort 1 (the year prior to BioFire® ME Panel implementation)and Cohort 2 (the year after BioFire® ME Panel implementation).Length of hospital stay, duration of antimicrobials, and BioFire® MEPanel result were gathered and analyzed.Results. Average length of stay for both cohorts was about fourhospital days. Approximately three-fourths of all patients receivedantibiotic/antiviral treatment with an average of three days duration.No significant differences were observed between groups. The mean(median) duration of antimicrobials in the year prior to and afterthe BioFire® ME Panel implementation was 3.6 (3) and 3.1 (2) days,respectively (p = 0.835). The mean (median) length of stay in the yearprior to and after the BioFire® ME Panel implementation was 5.8 (4)and 5.4 (4) days, respectively (p = 0.941). Among the patients admittedafter the implementation of the BioFire® ME Panel, 4.3 % (n =2) had a positive bacterial result, 38.3% (n = 18) had a positive viralresult, and 57.4% (n = 27) had a negative result. Of the 27 negativeresults, 77.8% (n = 21) were treated with antimicrobial medication.Conclusions. This study suggested there is no difference betweenlength of stay or antimicrobial duration in presumed meningitis casesassessed with traditional methods as compared to the BioFire® MEPanel. Kans J Med 2019;12(1):1-3

Urine Screening for Opiod and Illicit Drugs in the Total Joint Arthroplasty Population

Introduction. Recent studies have shown an increase in post-operative orthopaedic complications associated with pre-operative opioid use. It is, therefore, important to know if patients use opioids before scheduled surgery. The purpose of this study was to determine if urine drug screening (UDS) is an effective screening tool for detecting opioid and illicit drug use prior to joint arthroplasty (JA) procedures. Methods. This retrospective chart review was performed with IRB approval on 166 out of 172 consecutive patients in a community-based practice. All the patients had a pre-operative UDS prior to primary or revision JA by a fellowship trained orthopaedic surgeon between March 2016 and April 2017. Patient demographics documented opioid and illicit drug use, co-morbid diagnosis, and UDS results were collected from clinical charts. Statistical analysis was conducted using Pearson Chi-square, Fisher’s exact, McNemar test, and t-tests with IBM SPSS Statistics, ver. 23. Significant differences were p < 0.05. Results. Sixty-four of 166 patients (38.6%) tested positive for opioids. Among them, 55.0% (35/64) had no history of prescription opioid use. Significant differences were observed when comparing the test results of the UDS with the patient reported history of prescribed opioids (p = 0.001). Conclusion. With a significant number of patients testing positive for opioids without evidence of a previous prescription, UDS may be beneficial for initial risk assessment for patients undergoing JA procedures

Seizures in Pre-term Infants Less than 29 Weeks: Incidence, Etiology, and Response to Treatment

Introduction. Seizures are neurological emergencies with short- and long-term adverse effects in pre-term infants. They may present with or without abnormal movements (clinical versus subclinical). Thus, the true incidence of seizures may be under-reported. Current research indicates that most seizures occur in the first few days of life, are associated with intraventricular hemorrhage (IVH), and show low response to anticonvulsant drugs. The purpose of this study was to evaluate incidence, etiology, clinical antecedents, mortality, and response to treatment of seizures in extremely pre-term infants. Methods. This is a retrospective cohort study of pre-term infants < 29 weeks gestation from January 2011 to December 2013. Presence or absence of seizure was the outcome. Data extraction included demographics, medications, co-morbidities, mortality, and details of seizures. A multivariable prediction model was developed to evaluate risk for seizures. Results. Analysis included 269 pre-term infants. Incidence of EEG-confirmed seizures was 40% (108/269); 49% were clinical and 51% were subclinical. Seizures occurred in 72% of infants ≤ 24 weeks, 57% of those 25-26 weeks, and 23% of those 27-28 weeks. Most seizures (85%) occurred after day eight of life. Mortality was 14% in those with seizures versus 5% in those without (p = 0.019). The model showed seizures were associated significantly with gestational age and medications, while controlling for sex, APGAR score, and co-morbidities, including IVH. At discharge, anticonvulsants were continued in 66% (72/108) of infants with seizures. Conclusion. The incidence of seizures was highest in infants born most premature. Contrary to previous research, nearly two-thirds of pre-term infants with seizures did not have IVH or cystic periventricular leukomalacia; apnea of prematurity was a common presentation of subclinical seizures; and the majority of treated infants responded to Phenobarbital. These findings need be explored in future research

Analysis of Patient Handoff between Providers at a Tertiary Urban Medical Center

Introduction. Few studies have quantified the total number of attending and consulting physicians involved in inpatients’ care, and no other research quantifies the total number of all providers participating in inpatients’ care. The purpose of this study was to calculate the number of attending hand-offs, the attending encounter time, and the total number of providers participating in inpatients’ care for all admitted patients at a tertiary urban medical center. Methods. The study design was an observational retrospective cohort. Subjects included pediatric and adult patients who were admitted to and discharged from Ascension Via Christi St. Francis (AVCSF) in Wichita, Kansas between November 01, 2019 and January 31, 2020. Data were abstracted from the Cerner Electronic Medical Record. Variables included: patient demographics, admitting diagnosis, diagnosis related group (DRG), admission service, and duration of inpatient stay. Provider variables abstracted included provider type and provider specialty. Categorical variables were presented as frequencies and percentages, while continuous variables were presented as means ± standard deviation. Results. The sample included information from 200 patient charts. Patients’ ages ranged from 5 to 94 years, with a mean of 61 years. Approximately 52% were female and 74.9% were admitted to a surgical service. The length of all inpatients’ stays ranged from less than 1 day to 31 days, with a mean of 4 days. Seventy-six different DRGs were recorded. The most frequent attending specialties for medical patients were hospital medicine, internal medicine, general surgery, and interventional cardiology. Consulting physicians had more patient encounters than any other healthcare provider. For all inpatients, an average of two attending physicians participated in care over the duration of their stay with a range of one to six attending physicians. There was an average of one hand-off between attending physicians. Patients had an average of five consulting physicians, two resident physicians, two physician assistants, and two nurse practitioners during a stay. There was an average of 10 total providers, with a range of one to 46 total providers participating in care. Conclusions. Understanding the provider data surrounding an inpatient stay is a foundational step in assessing the quality of the provider-inpatient encounter and potential areas for improvement. In this study, the average number of attending physicians and handoffs was reasonable; however, the total number of providers involved in care was relatively high. Assessment of staffing and scheduling requirements by hospital administration could identify areas of improvement to reduce the potential for medical error caused by multiple providers being involved in patient care.  &nbsp

Deep Neural Networks and Applications in Medical Research

Artificial Intelligence (AI) has played a significant role in improving decision-making within the healthcare system. AI includes machine learning, which encompasses a subset called artificial neural networks (ANNs). These networks mimic how biological neurons in the brain signal one another. In this chapter, we conduct a seminal review of ANNs and explain how prediction and classification tasks can be conducted in the field of medicine. Basic information is provided showing how neural networks solve the problem of determining disease subsets by analyzing huge amounts of structured and unstructured patient data. We also provide information on the application of conventional ANNs and deep convolutional neural networks (DCNNs) that are specific to medical image processing. For example, DCNNs can be used to detect the edges of an item within an image. The acquired knowledge can then be transferred so that similar edges can be identified on another image. This chapter is unique; it is specifically aimed at medical professionals who are interested in artificial intelligence. Because we will demonstrate the application in a straightforward manner, researchers from other technical fields will also benefit

Physician Burnout in a Rural Kansas Community

Introduction Physician wellness and burnout are topics of intensediscussion and study, however, less is known about rural physicianburnout. The aim of this study was to assess levels of physicianburnout in the rural Kansas community of Salina. Methods An electronic, confidential survey was conducted among145 physicians with active privileges at the local health center and/orsurgical center. The survey included demographic features, practicecharacteristics, and the abbreviated Maslach Burnout Inventory™(aMBI). In addition, survey participants were invited to provide freetextresponses to questions concerning specific causes of burnoutand mechanisms to combat feelings of burnout. Results Of 145 invited, 76 physicians completed the survey. Thirty-six respondents self-identified as primary care physicians, 22as subspecialists, and 18 as surgeons. aMBI scores for emotionalexhaustion (EE), depersonalization (D) and personal accomplishment(PA) ranged from 0 to 18. The mean EE score was 8.4 (SD =4.9), mean D score was 4.8 (SD = 3.9), and mean PA score was 15.2(SD = 2.8). Using tertiles, physician burnout (i.e., those in the firsttertile) for EE was 39% (30/76), D was 34% (26/76), and PA was41% (31/75); 22% of physicians surveyed scored high on both EEand D as measured by tertiles, suggestive of more serious burnout.No significant differences in aMBI scores were observed for demographicfeatures or practice characteristics; physicians who workedwith medical students had higher PA scores. Contributing to burnoutwere demands of documentation and difficult patient encounters,while true time away might ameliorate rural physician burnout. Conclusions As measured by aMBI constructs, burnout is prevalentamong the responding rural physicians practicing in the Salina community

A Scoping Review to Assess Risk of Fracture Associated with Anxiolytic Medications

Introduction. Recent research has focused on evaluating the impact of pharmalogical sources on fracture risk. The purpose of this study was to review the literature on anxiolytic medications that may be associated with an increased risk of fracture. Methods. A search was conducted in MEDLINE and Embase databases to identify primary clinical studies of patients who sustained a fracture while prescribed anxiolytic medications and were published prior to July 2021. Anxiolytics defined by ATC Class N05B, beta blockers, and zolpidem were included. The search terms consisted of variations of the following: (“Psychotropic Drugs” or MeSH terms) AND (“Fracture” or MeSH terms).  Results. Of 3,213 studies, 13 (0.4%) met inclusion criteria and were evaluated. Fractures associated with benzodiazepine were reported in 12 of 13 studies; the highest risk occurred in patients aged 60 years and older, RR=2.29, 95% CI (1.48-4.40). The ATC Class N05B showed an increased fracture risk for those < 55 years of age that differed by sex: for men RR=5.42, 95% CI(4.86-6.05) and for women it was RR=3.33, 95% CI (3.03-3.66). Zolpidem also showed an increase fracture risk, RR=2.29, 95% CI(1.48-3.56), but only during the first 4 weeks of treatment. A relative risk of 0.77, 95% CI(.72-.83) was observed for beta blockers. Conclusions.  Fractures are a mainstay of traumatic injuries and are accompanied by economical, physiological, and psychological hardship. Fortunately, with proper assessment and prophylactic measures, fracture risk can be reduced dramatically. Anxiolytic medications have been described widely to increase fracture risk, such as benzodiazepines  in 60+ year old patients, and ATC Class N05B Anxiolytics increased fracture risk of RR=5.42, 95% CI (4.86-6.05) in 55+ year old men and  in 55+ year old women. Yet, some studies showed that at low doses, nitrazepam lowered fracture risk. Other anxiolytic medications, such as zolpidem and beta blockers, also showed a decrease in fracture risk; however, only one study has been published on each of these medications. Ultimately, this scoping review helped to illuminate the inconsistency of anxiolytic fracture risk assessment while simultaneously illustrating the necessary steps to guide future research