Continuous Dependent Variables Research Articles

Unravelling the Influence of Buddhist Liberal Arts Education on College Students’ Self-Reflection

The purpose of this paper is to investigate the measurable impact of Buddhist liberal arts courses on college students’ ability to engage in self-reflection. This study uses the data gathered to establish, through statistical analysis, any correlations between two variables—Buddhist liberal arts as courses as the independent variable and self-reflection intelligence as the continuous dependent variable. First, the following results of the study show that the mean of the four self-reflection sub-categories for the students who found that the courses were helpful was higher than that of the students who found that they were not helpful: self-awareness (4.10 ± 0.49 > 3.90 ± 0.87), self-design (3.84 ± 0.66 > 3.40 ± 0.97), self-regulation (4.01 ± 0.04 > 3.48 ± 0.18), and self-examination (4.21 ± 0.03 > 3.94 ± 0.15), respectively. Second, the mean of the four self-reflection sub-categories for students who experienced a positive change of their perception in the courses was higher than that of students who experienced a negative change, as follows: self-awareness (4.08 ± 0.50 > 3.75 ± 0.82), self-design (3.84 ± 0.68 > 3.51 ± 0.93), self-regulation (4.00 ± 0.59 > 3.56 ± 0.67), and self-examination (4.17 ± 0.49 > 4.04 ± 0.73), respectively. This study illuminates the role of Buddhist-related liberal arts courses in higher education, specifically in fostering students’ self-reflection skills. It offers valuable insights into educational practices aimed at enhancing self-reflection levels.

The Natural History of Splenic Artery Aneurysms: Factors That Predict Aneurysm Growth

PurposeTo examine the natural history of splenic artery aneurysms (SAAs) at a single institution and assess the effect of patient factors and aneurysm characteristics on aneurysm growth. Materials and MethodsThis single-center retrospective study included patients with SAAs who underwent serial imaging over 30 years (1990–2020). Data regarding patient demographics and aneurysm characteristics were collected. The variables contributing to aneurysm growth were assessed using nonparametric tests for continuous variables and chi-square test for categorical variables. Multivariable linear regression was performed using aneurysm growth rate as a continuous dependent variable. ResultsA total of 132 patients were included in this study. The median maximum diameter of the SAAs was 15.8 mm (range, 4.0–50.0 mm). Growth over time was observed in 39% of the aneurysms, whereas the remaining 61% were stable in size. Of aneurysms that increased in size, the median aneurysm growth rate was 0.60 mm/y (range, 0.03–5.00 mm/y). Maximum aneurysm diameter of >2 cm and the presence of >50% mural thrombus were significant positive predictors for aneurysm growth (P = .020 and P = .022, respectively). Greater than 50% rim calcification was a significant negative predictor for aneurysm growth (P = .009) in multivariate analysis. ConclusionsA larger baseline SAA size, presence of mural thrombus, and lack of rim calcification are associated with increased aneurysm growth rate.

Insurance Scheme: Inequality in Untreated Caries and Tooth Loss

Objectives: In Thailand, access to dental care services varies based on different insurance schemes. Our objective was to determine the association of untreated caries and tooth loss with insurance schemes among adult population in Thailand. Methods: This is a cross-sectional study. Secondary data from oral examinations and a questionnaire administered during Thailand’s National Oral Health Survey 2017 were analyzed. Untreated caries and tooth loss were used as continuous dependent variables. Based on the insurance schemes, participants were categorized into four groups: Universal Coverage Scheme (UCS), Civil Servant Medical Benefit Scheme (CSMBS), Social Security Scheme (SSS), and “others” (uninsured, do not use, do not know). Poisson regression with robust variance and sampling weights was used to calculate the ratio of means (RM), and 95% confidence interval (CI) was used for untreated caries and tooth loss, with adjustments for age, gender, and location. Results: A total of 4,534 participants were included. The mean age and number of untreated caries and tooth loss were 39.6±2.9 years, 0.9±1.7 teeth, and 2.2±3.1 teeth, respectively. In covariate-adjusted models, participants under the UCS showed a significantly higher chance of untreated caries compared to those under the CSMBS (RM=1.23, 95% CI=1.04–1.45). Regarding tooth loss, participants under the others category had a substantially higher chance of tooth loss compared with those with the CSMBS. (RM=1.37, 95% CI=1.02–1.85). Conclusions: Insurance schemes are predictors of untreated caries and tooth loss. Expansion of coverage of all insurance schemes to facilitate access to dental services is required.

Abstract P512: Associations of Serum Insulin-Like Growth Factor (IGF)-1 Levels With Cognitive Function and Atherosclerosis in a Japanese General Population: The Tanushimaru Study

Background: Insulin-like growth factor (IGF)-1 is a peptide hormone implicated in insulin sensitivity and anti-inflammatory. However, there is limited exploration of the association of serum IGF-1 levels with cognitive function and atherosclerosis. This study aimed to investigate the association between serum IGF-1 levels and cognitive function, as well as carotid atherosclerosis in a general population. Methods: In 1,345 participants (544 men; mean age, 68.7 (11.3) years) recruited from the Tanushimaru cohort, we measured their serum IGF-1 levels and evaluated cognitive function using mini-mental state examination (MMSE) and atherosclerosis through carotid intima-media thickness (IMT). Linear regression models were utilized to analyze the association between quartiles of serum IGF-1 levels and MMSE scores, as well as IMT, continuous dependent variables. We also visualized the continuous associations using restricted cubic spline models. Two-sided statistical significance was defined as p <0.05. All statistical analyses were performed using the SAS system (Release 9.4, SAS Institute, Cary, NC, USA). Results: The mean serum IGF-1 level was 96.6 (30.2) ng/ml. Multiple linear regression analysis revealed that the highest quartile of serum IGF-1 levels showed a statistically significant association with higher MMSE scores (p=0.0019), and the third quartile also reached statistical significance (p=0.0006) compared to the lowest. We observed a positive association between serum IGF-1 levels and MMSE scores, even when exploring the full spectrum of serum IGF-1 levels with their spline terms (Figure). In contrast, serum IGF-1 levels did not exhibit a significant association with IMT measurements. Conclusion: High serum IGF-1 levels were associated with higher cognitive function, while no significant association was observed with carotid atherosclerosis. Our findings suggest that IGF-1 levels may play a role in preserving cognitive function, potentially distinct from its role in atherosclerosis.

Understanding Factorial Designs, Main Effects, and Interaction Effects: Simply Explained with a Worked Example.

A factorial design examines the effects of two independent variables on a single, continuous dependent variable. The statistical test employed to analyze the data is a two-way analysis of variance (ANOVA). This test yields three results: a main effect for each of the independent variables and an interaction effect between the two independent variables. This article explains factorial designs and two-way ANOVA with the help of a worked example using hypothetical data in a spreadsheet provided as a supplementary file. The main effects and interaction effects are explained and illustrated using tables and figures. A short discussion provides general notes about the concepts explained in this article, along with brief notes on repeated measures ANOVA and higher order ANOVAs. Many additional examples, with figures and explanations, are provided in the supplementary materials, which the reader is strongly encouraged to view.

Epidemiology of Irritable Bowel Syndrome in a Large Academic Safety-Net Hospital.

(1) Background: Irritable bowel syndrome (IBS) is a highly prevalent disorder of gut-brain interaction (DGBI) that is known to reduce the quality of life and raise healthcare costs. The aim of this study was to describe the epidemiology of IBS in a large multiracial academic safety-net hospital. (2) Methods: An electronic query was performed using ICD-9 codes to identify 740 IBS outpatients seen at the Boston Medical Center (BMC) between 1 January 2005 and 30 September 2007. Demographic data were collected from electronic medical records. Bivariate analyses using chi-square tests and ANOVA were used to calculate the significance of categorical and continuous dependent variables, respectively. (3) Results: Compared with the general BMC outpatient population, the IBS cohort consisted of significantly higher proportions of White and Asian patients and lower proportions of Black and Hispanic patients (p < 0.0001). White and Asian patients predominantly had private insurance, while Black and Hispanic patients mostly had government/state-funded or no insurance (p < 0.0001). The IBS subgroup frequencies were similar across racial groups; however, Hispanic patients had IBS with constipation (32%, p < 0.02) more often compared to non-Hispanic patients. (4) Conclusions: Significant differences were found across the racial groups studied in this large outpatient IBS cohort. These findings are likely attributed to racial and socioeconomic disparities in healthcare access and utilization.

Optimizing Chance Constraint Multiple-Objective Fractional Mathematical Programming Problem Involving Dependent Random Variable

This manuscript suggests a methodology to solve chance constraint multiple-objective linear fractional mathematical programming problem in which the parameters are dependent random variables to each other. The proposed problem is formulated by taking few of the parameters as continuous dependent random variables. The proposed model cannot be solved directly by using existing methodology. Thus in order to solve the proposed model, an equivalent deterministic model is derived. The procedure to solve the proposed model is accomplished in two main steps. Initially, the proposed multiple-objective chance constraint linear fractional mathematical problem is transformed to deterministic equivalent multiple-objective linear fractional mathematical programming by the help of chance constrained method. In the second step, multiple-objective functions, which consist of fractional functions is solved by using lexicographic programming approach. Finally, an example is mentioned to illustrate the methodology.

CLINICO-DEMOGRAPHIC CORRELATES OF COGNITIVE IMPAIRMENT AMONG THE OLDER ADULTS IN SELECTED SPECIALTY CLINICS IN MAIDUGURI, NIGERIA.

Background: Older adults with chronic medical conditions have a high prevalence of cognitive impairment, which may be linked to the chronicity of their illnesses. This study aimed to identify demographic and clinical factors associated with cognitive impairment in older adults with chronic medical conditions attending specialty clinics in Maiduguri. Methods: A cross-sectional analytical study was conducted involving older adults aged 60 years and above, utilizing a consecutive sampling approach over a period of six months. Participants completed the sociodemographic questionnaire, clinical proforma and assessment using Community Screening Instrument for Dementia (CSID). Data analysis was performed using SPSS version 26.0, with significance level set at 0.05. Non-parametric tests were employed to compare continuous dependent variables that were not normally distributed across different groups of independent variables. Results: The mean age (±SD) of the respondents was 66.6 (±5.5) years. The prevalence of cognitive impairment was 14.7%. It was higher among the 70-79 age group, the widowed, and those with no formal education. There was a significant association of cognitive impairment with the medical conditions (p = 0.001). It was worst among those with hypertension-diabetes comorbidity, those with the longest duration for ≥21 years, those using ≥5 medications, and those with 3-4 previous admissions. Conclusion: The present findings hold significance for the healthcare of older adults, as they can enhance clinical procedures by raising awareness regarding cognitive impairment. Additionally, these findings may contribute to the establishment of a comprehensive approach to their care, bridging the gap between psychiatric and medical practices.

Discretizing continuous variables in nutrition and obesity research: a practice that needs to be cut short

Background/objectivesNutrition and obesity researchers often dichotomize or discretize continuous independent variables to conduct an analysis of variance to examine group differences. We describe consequences associated with dichotomizing and discretizing continuous variables using two cross-sectional studies related to nutrition.Subjects/methodsStudy 1 investigated the effects of health literacy and nutrition knowledge on nutrition label accuracy (n = 612). Study 2 investigated the effects of cognitive restraint and BMI on fruit and vegetable (F/V) intake (n = 586). We compare analytic approaches where continuous independent variables were either discretized/dichotomized or analyzed as continuous variables.ResultsIn Study 1, dichotomization of health literacy and nutrition knowledge for 2 × 2 ANOVA revealed health literacy had an effect on nutrition label accuracy. Nutrition knowledge has an effect on nutrition label accuracy, but the health literacy by nutrition knowledge interaction was not significant. When analyzed using regression, the nutrition knowledge effect was significant. The simple effect of health literacy was also significant when health literacy equals zero. Finally, the quadratic effect of health literacy was negative and significant. In Study 2, dichotomization and discretization of cognitive restraint and BMI were used for three ANOVAs, which discretized BMI in three ways. For all ANOVAs, the BMI main effect for predicting fruit and vegetable intake was significant, the interaction between BMI and cognitive restraint was non-significant, and cognitive restraint was only significant when both variables were dichotomized. When analyzed using regression, the continuous mean-centered variables, and their interaction each significantly predicted F/V intake.ConclusionsDichotomizing continuous independent variables resulted in distortions of effect sizes across studies, an inability to assess the quadratic effect of health literacy, and an inability to detect the moderating effect of BMI. We discourage researchers from dichotomizing and discretizing continuous independent variables and instead use multiple regression to examine relationships between continuous independent and dependent variables.

Social exclusion of the SGM community in Rwanda: public perceptions and lived experiences of SGM

Abstract Background Sexual and gender minorities (SGM) are “othered” from society. This study quantifies and explores the process of “othering” of SGM Rwandans through the lens of those who “other” and those who experience “othering.” Methods We conducted a mixed methods study surveying 499 &amp; conducting focus groups with 59 SGM. We surveyed 1,254 &amp; conducted 16 interviews with non-SGM. Among non-SGM, the outcome was a continuous variable measuring attitudes toward SGM. Among SGM, the continuous dependent variable was from 13 questions measuring discrimination across life contexts (e.g., work, health). We conducted adjusted linear regressions to explore predictors of “othering” among non-SGM and associations between discrimination and SGM identity among SGM. We report beta coefficients and 95% confidence intervals. We used thematic analysis to analyze the qualitative data to examine the context and nuance of “othering” and its impacts on SGM. Results The average score for SGM support among the public was 12 (SD = 4.7) (20 is more discrimination). As compared to those who knew zero SGM, persons who knew 5+ had scores that were 1.3 points lower (95% CI -2.2, -0.5), while the score was lower for those that knew 1-5 (-0.2), it was not significant (95% CI -0.8, 0.5). Among SGM, 67% experienced discrimination. In adjusted models, we found that transgender &amp; non-straight participants experienced more discrimination. The qualitative findings found that “othering” occurs in many contexts, such as housing, employment, healthcare, and virtually, but trans persons are most impacted. One participant shared, “A transgender [person] may face more discrimination than a gay based on their physical appearance.” Conclusions SGM Rwandans are widely “othered” with negative implications for their ability to live authentically and participate in everyday experiences. However, results indicated that if non-SGM persons were acquainted with LGBTQ+ community members, discrimination is lessened.

Positive contact and empathy as predictors of primary care providers’ willingness to prescribe medications for opioid use disorder

IntroductionPatients with opioid use disorder (OUD) have a heightened need for quality health care, including access to evidence-based medications to reduce cravings and prevent overdose. However, primary care providers (PCPs) are reluctant to work with patients with OUD and implement medication prescribing into primary care practice. Previous studies have sought to identify potential ways to overcome these barriers, but often utilize interventions that facilitate both positive contact with as well as empathy for patients with OUD. In this study, we jointly assess positive contact and empathy to determine their unique impact on treatment attitudes and behaviors among PCPs, after controlling for other known predictors. MethodsWe surveyed 409 PCPs currently practicing in Ohio in 2022. Our primary dependent variables were willingness to work with patients with OUD, receipt of an X-waiver to prescribe buprenorphine, and interest in receiving an X-waiver. Our primary independent variables were positive contact and empathy toward patients with OUD. We computed bivariate correlations and multivariable linear regression (for continuous dependent variables) and logistic regression (for binary dependent variables) to understand the relationship between positive contact, empathy, and our outcome variables while accounting for other known predictors and relevant participant demographics. ResultsPositive contact was positively correlated with willingness to work with patients with OUD, receipt of the X-waiver, an interest in receiving the X-waiver, more frequent checking with patients about the need for naloxone, and higher odds of naloxone prescribing. These relationships held after accounting for PCP demographics, explicit bias toward patients with OUD, and overall levels of contact with patients with OUD. Empathy, conversely, was not a significant predictor of any treatment outcomes in the fully adjusted models. ConclusionInterventions and medical education programs aimed at improving treatment outcomes for patients with OUD should facilitate positive contact between PCPs and patients with OUD.

The Discriminatory Ability of Ganglion Cell Inner Plexiform Layer Complex Thickness in Patients with Preperimetric Glaucoma.

To evaluate diagnostic performance of ganglion cell inner plexiform layer (GCIPL) and retinal nerve fiber layer (RNFL) parameters measured with Cirrus high-definition optical coherence tomography (OCT) in patients with preperimetric glaucoma. In this multicenter cross-sectional study, 150 eyes of 83 patients with preperimetric glaucoma were compared with 200 eyes of age and sex matched healthy subjects. All patients had visual field testing and OCT scanning of GCIPL and RNFL in all quadrants. The independent Samples t-test was used to determine if a difference exists between the means of two independent groups on a continuous dependent variable. The area under the receiver operating characteristic (ROC) curve (AUC) of each parameter was calculated for discriminatory ability between normal controls and preperimetric glaucoma. The sensitivity and specificity were estimated by point coordinates on ROC curve. The best parameters for distinguishing preperimetric glaucoma from healthy eyes were the combined average GCIPL + average RNFL, followed by average RNFL + GCIPL (inferotemporal), and average RNFL + GCIPL (minimum). The GCIPL parameters with the highest to lowest AUC (in decreasing order) were inferotemporal, followed by average, minimum, superior, inferior, superonasal, inferonasal, superotemporal, and quadrants. The RNFL parameters with the highest to lowest AUC (in decreasing order) were average, followed by nasal, temporal, superior, and inferior quadrants. The sensitivity of combined GCIPL + RNFL parameters ranged 85%-88% and the specificity ranged 76%-88%. The sensitivity for RNFL parameters ranged 80%-90% and the specificity ranged 64%-88%. GCIPL and RNFL have good discriminatory ability; the sensitivity and specificity increase when both parameters are combined for early detection of glaucoma.

Natural autoimmunity in oligoarticular juvenile idiopathic arthritis

BackgroundOligoarticular juvenile idiopathic arthritis (oligo-JIA) is considered as an antigen-driven lymphocyte-mediated autoimmune disease. Natural antibodies (NAbs) are pre-immune antibodies produced in the absence of exogenous antigen stimulation, participating in both, innate and adaptive immunity. Considering their major immunoregulatory role in homeostasis and autoimmune pathogenesis, we designed this study to further elucidate their role in oligo-JIA pathogenesis.MethodsSeventy children with persistent oligo-JIA and 20 healthy matched controls were enrolled in the study. Serum IgM and IgA antibodies against human G-actin, human IgG F(ab΄)2 fragments and the hapten TriNitroPhenol (TNP) as well as the total concentration of serum IgM and IgA were measured by in-house enzyme-immunoassays. Kolmogorov–Smirnov normality test, Kruskal–Wallis H and Mann–Whitney tests were used to assess data distribution, and significant differences of non-parametric data between groups of the study. Backward regression analysis was used to analyze the effect of multiple factors (age, gender, disease activity, anti-nuclear antibody positivity, presence of uveitis) on continuous dependent variables (activities and activity/ concentration ratios of IgM and IgA NAbs).ResultsThe ratios of IgA anti-TNP, anti-actin and anti-F(ab΄)2 levels to total serum IgA concentration were found to be significantly increased in patients with oligo-JIA compared to healthy subjects. Significantly elevated levels of IgM anti-TNP antibodies were also found in children with inactive oligo-JIA compared to those of children with active disease and of healthy controls. In the presence of anterior uveitis, IgM anti-TNP levels were significantly higher than in patients without uveitis or in healthy controls. Backward regression analysis revealed that the disease activity and the presence of anterior uveitis independently affect IgM anti-TNP levels.ConclusuionsOur findings are in accordance with the hypothesis that NAbs contribute to the pathogenesis of autoimmune diseases and provide additional evidence that disturbances in natural autoimmunity may contribute to the as yet unclarified pathogenesis of oligo-JIA.

The use of quantile methods in economic history

Quantile regression and quantile treatment effect methods are powerful econometric tools for considering economic impacts of events or variables of interest beyond the mean. The use of quantile methods allows for an examination of impacts of some independent variable over the entire distribution of continuous dependent variables. Measurement in many quantitative settings in economic history have as a key input continuous outcome variables of interest. Among many other cases, human height and demographics, economic growth, earnings and wages, and crop production are generally recorded as continuous measures, and are collected and studied by economic historians. In this paper we describe and discuss the broad utility of quantile regression for use in research in economic history, review recent quantitative literature in the field, point to potential limits in its use, and provide an illustrative example of the use of these methods based on 20,000 records of human height measured across 50-plus years in the 19th and 20th centuries. We suggest that, despite limitations in certain settings, there is still considerably more room in the literature on economic history to convincingly and productively apply quantile regression methods.

Examination of Creativity Levels of Preschool Children

The study aims to examine whether the interaction of parents' education and income levels has a significant effect on the creativity scores of preschool children. The research was conducted in a district of Ankara, where parents are thought to vary in terms of income and education level. 123 children studying in independent kindergartens affiliated with the Ministry of National Education participated in the research. “Early Childhood Creativity Scale” was used as a data collection tool in the study. In the study, a 2x3 two-way analysis of variance was preferred because it was aimed to examine the possible effects or interaction effects of categorical independent variables on the continuous dependent variable. Test procedures were run after ANOVA assumptions were checked and it was observed that the assumptions were met. As a result of the research, it was determined that the interaction between parents' education levels and income levels had an effect on their children's creativity. When looking only through the main effects, independent of the interaction effect, it was determined that the level of parental education was influential on the creativity scores of the children, but the income level alone was not.

Dietary inflammation score is associated with perceived stress, depression, and cardiometabolic health risk factors among a young adult cohort of women

One of the most pressing issues in the field of cardiometabolic disease is the growing co-occurrence of poor mental health. A whole foods-based, hypothesis-driven dietary inflammation score (DIS) was created to better understand the association between dietary patterns, inflammation, and physiological health. However, this diet quality scoring method has not been observed in young adults, nor has its association with mental health been observed. This study 1) examined differences in cardiometabolic health measures by dietary inflammation score (DIS) tertiles and 2) examined the association between DIS and psychosocial stress variables, perceived stress, and depression. Psychosocial and food frequency questionnaires, demographics, anthropometrics, and clinical measures were collected from sixty-two metabolically healthy African American and European American females, ages 18-45, from 2014 to 2016 in Birmingham, AL. Analysis of Variance was used to observe differences in all cardiometabolic variables by DIS tertile. Linear regression was used to observe the relationship between independent, continuous variable DIS and dependent variables, depression, and perceived stress. There were significant differences between DIS tertiles for cardiometabolic and psychosocial stress measures. DIS was significantly positively associated with depression after controlling for body fat percentage (P=0.003) and education, income, and race (P=0.01). DIS was significantly associated with perceived stress after controlling for body fat percentage (P=0.0004), and education, income, and race (P=0.0005). This study is significant for its contribution in understanding how cardiometabolic health differs by DIS tertile, and how dietary inflammation scores are associated with depression and perceived stress among young adult women.

The didactical phenomenology in learning the circle equation

Realistic mathematics education (RME) has proven to be an effective model for mathematics elsewhere. However, students and teachers still grapple to confront the circle equation to learn and teachers to teach. This study explored students’ didactical phenomenological discourses in the circle equation as an alternative. The mixed methods research design was used to collect both quantitative and qualitative data from 50 senior high school students purposely selected from one senior high school. The instruments of data collection were the questionnaire and interview guide. The purpose of the questionnaire and interview guide was to validate and corroborate. The quantitative analyses contain categorical independent and continuous dependent variables and were explored by reliability statistics, simple and multiple analysis of variance tests of independence. On the other hand, the qualitative transcriptions of students’ own perceptions. The results on the types of equations showed low didactical phenomenology as many variables fell below the .20 minimum internal consistency’s criteria. However, the results of the tasks showed high acceptable didactical phenomenology. We therefore concluded that RME could be extended to other domains of mathematics. Thereafter, comprehensive recommendations were advanced for theory, method, research, practice, policy, and context.

Fitting spatial autoregressive logit and probit models using Stata: The spatbinary command

Starting from version 15, Stata allows users to manage data and fit regressions accounting for spatial relationships through the sp commands. Spatial regressions can be estimated using the spregress, spxtregress, and spivregress commands. These commands allow users to fit spatial autoregressive models in cross-sectional and panel data. However, they are designed to estimate regressions with continuous dependent variables. Although binary spatial regressions are important in applied econometrics, they cannot be estimated in Stata. Therefore, I introduce spatbinary, a Stata command that allows users to fit spatial logit and probit models.

The US hospital-acquired condition reduction program: A linear and logistic regression analysis of domains and penalty status

ABSTRACT Background Section 3008 of the 2010 Patient Protection and Affordable Care Act established the Hospital-Acquired Condition Reduction Program (HACRP). Objective The objective of this study is to reasonably decipher those factors that make a hospital vulnerable to be positioned in the bottom quartile of all reporting hospitals; and therefore, be partially reimbursed. Methods Data was sourced from CMS QualityNet public use data files and the American Hospital Directory® website. Linear and logistic regression models were used to analyze continuous and categorical dependent variables, respectively. Results For a one unit increase in inpatient days and the length of stay, the Total HACRP score increased by 0.02 (95% CI: 0.01 0.03 P = .00), and 0.04 (95% CI: −0.02 −0.06 P = .00) units, respectively, when all other variables were held constant. The odds of incurring penalty was 2% less likely (odds ratio = 98 95% CI: 0.97 0.99 P = .00) if the hospital had lesser as opposed to having a greater number of Total Discharges. The odds of incurring penalty was 3% more likely (odds ratio = 1.03 95% CI: 1.02 1.04 P = .00) if the hospital had more as opposed to less Inpatient Days, when all other variables are held constant. Conclusion We infer that greater number of total discharges and inpatient days are predictors of acquiring a far from conducive HACRP score. We, furthermore, infer that greater the number of total discharges and more inpatient days, greater is the likelihood of incurring a reimbursement penalty under this policy.

Review Paper on a Healthcare Prognosis Using Machine Learning

Abstract: Diseases tracing plays important role in daily life. Every one cares about their own health. According to some social study, lot of people spends their time on online searching of health related issues. By browsing they get lot of information about the medical concepts and health related issues. Normally, people use Google to search their queries and that search engine respond them with the answer but that answer is in scattered format. User does not gets the exact answer for their queries. From previous work there has been vital work on the information needs of health seekers in terms of questions and then select those that ask for possible disease of their manifested symptoms for further analytic. To resolve such issues an extensive experiment on a real-world dataset labelled by online doctor’s show the significant performance. In this paper, we discussed the techniques for further restructuring of the question and answer has been done in order to get the exact answer of query. A tag mining framework for health seekers will be proposed; aim to identify discriminant features for each specific disease. In this paper we are going to use one of the most famous algorithm of machine learning that is decision tree. It is a type of supervised learning algorithm that is mostly used for classification problems. Surprisingly, it works for both categorical and continuous dependent variables. In this algorithm, we split the population into two or more homogeneous sets. This is done based on most significant attributes/ independent variables to make as distinct groups as possible. Keywords: SVM (Support Vector Machine), sparse deep learning, Classifiers, Querying, Signature mining