scholarly journals Quality of Care in Long-Term Hemodialysis Patients in Mexico

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Torres-Díaz JA ◽  
◽  
Gonzalez-Gonzalez JG ◽  
Zúniga-Hernández JA ◽  
Olivo-Gutiérrez MC ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Quality Of Care ◽  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
World Literature ◽  
Logistic Regression Model ◽  
Hospital Admissions ◽  
Cross Sectional

Introduction: The End Stage Renal Disease (ESRD) is one of the leading causes of mortality in Mexico. The quality of care these patients receive remains uncertain. Methods: This is a descriptive, single-center and cross-sectional cohort study. The KDOQI performance measures, hemoglobin level >11 g/dL, blood pressure <140/90 mmHg, serum albumin >4 g/dL and use of arteriovenous fistula of patients with ESRD on hemodialysis were analyzed in a period of a year. The association between mortality and the KDOQI objectives was evaluated with a logistic regression model. A linear regression model was also performed with the number of readmissions. Results: A total of 124 participants were included. Participants were categorized by the number of measures completed. Fourteen (11.3%) of the participants did not meet any of the goals, 51 (41.1%) met one, 43 (34.7%) met two, 11 (8.9%) met three, and 5 (4%) met the four clinical goals analyzed. A mortality of 11.2% was registered. In the logistic regression model, the number of goals met had an OR for mortality of 1.1 (95% CI 0.5-2.8). In the linear regression model, for the number of readmissions, a beta correlation with the number of KDOQI goals met was 0.246 (95% CI -0.872-1.365). Conclusion: The attainment of clinical goals and the mortality rate in our center is similar to that reported in the world literature. Our study did not find a significant association between compliance with clinical guidelines and mortality or the number of hospital admissions in CKD patients on hemodialysis.

Statistical Process Control for Monitoring Standardized Mortality Ratios of a Classification Tree Model

2012 ◽  
Vol 51 (04) ◽  
pp. 353-358 ◽  
Author(s):  
S. Eslami ◽  
N. de Keizer ◽  
E. de Jonge ◽  
S. E. de Rooij ◽  
A. Abu-Hanna ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Quality Of Care ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Classification Tree ◽  
Brier Score ◽  
Tree Model ◽  
Care Assessment ◽  
Over Time

SummaryObjectives: The ratio of observed to expected mortality (standardized mortality ratio, SMR), is a key indicator of quality of care. We use PreControl Charts to investigate SMR behavior over time of an existing tree-model for predicting mortality in intensive care units (ICUs) and its implications for hospital ranking. We compare the results to those of a logistic regression model.Methods: We calculated SMRs of 30 equally-sized consecutive subsets from a total of 12,143 ICU patients aged 80 years or older and plotted them on a PreControl Chart. We calculated individual hospital SMRs in 2009, with and without repeated recalibration of the models on earlier data.Results: The overall SMR of the tree-model was stable over time, in contrast to logistic regression. Both models were stable after repeated recalibration. The overall SMR of the tree on the whole validation set was statistically significantly different (SMR 1.00 ± 0.012 vs. 0.94 ± 0.01) and worse in performance than the logistic regression model (AUC 0.76 ± 0.005 vs. 0.79 ± 0.004; Brier score 0.17 ± 0.012 vs. 0.16 ± 0.010). The individual SMRs’ range in 2009 was 0.53–1.31 for the tree and 0.64–1.27 for logistic regression. The proportion of individual hospitals with SMR >1, hinting at poor quality of care, reduced from 38% to 29% after recalibration for the tree, and increased from 15% to 35% for logistic regression.Conclusions: Although the tree-model has seemingly a longer shelf life than the logistic regression model, its SMR may be less useful for quality of care assessment as it insufficiently responds to changes in the population over time.

Physico-Chemical Analysis of Groundwater and Effect of Climatic Change in Angul-Talcher Area

2018 ◽  
Vol 6 (12) ◽  
pp. 26
Author(s):  
Aliva Bera ◽  
D.P. Satapathy
Keyword(s):  
Water Resources ◽  
Linear Regression ◽  
Regression Model ◽  
Climatic Change ◽  
Linear Regression Model ◽  
Ann Model ◽  
Quality Of Water ◽  
Physico Chemical ◽  
Simulation Based

In this paper, the linear regression model using ANN and the linear regression model using MS Excel were developed to estimate the physico-chemical concentrations in groundwater using pH, EC, TDS, TH, HCO3 as input parameters and Ca, Mg and K as output parameters. A comparison was made which indicated that ANN model had the better ability to estimate the physic-chemical concentrations in groundwater. An analytical survey along with simulation based tests for finding the climatic change and its effect on agriculture and water bodies in Angul-Talcher area is done. The various seasonal parameters such as pH, BOD, COD, TDS,TSS along with heavy elements like Pb, Cd, Zn, Cu, Fe, Mn concentration in water resources has been analyzed. For past 30 years rainfall data has been analyzed and water quality index values has been studied to find normal and abnormal quality of water resources and matlab based simulation has been done for performance analysis. All results has been analyzed and it is found that the condition is stable. 

The relationship between disability and suicide: prospective evidence from the Ten to Men cohort

2018 ◽  
Vol 41 (4) ◽  
pp. 707-713 ◽  
Author(s):  
Allison Milner ◽  
Anne-Marie Bollier ◽  
Eric Emerson ◽  
Anne Kavanagh
Keyword(s):  
Mental Health ◽  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
People With Disabilities ◽  
Cross Sectional ◽  
Longitudinal Cohort ◽  
The Past ◽  
The Relationship

Abstract Background People with disabilities often face a range of social and economic adversities. Evidence suggests that these disadvantages result in poorer mental health. Some research also indicates that people with disabilities are more likely experience thoughts about suicide than people without disability, although most of this research is based on small cross-sectional samples. Methods We explored the relationship between self-reported disability (measured at baseline) and likelihood of reporting thoughts of suicide (measured at follow up) using a large longitudinal cohort of Australian males. A logistic regression model was conducted with thoughts of suicide within the past 12 months (yes or no) as the outcome and disability as the exposure. The models adjusted for relevant confounders, including mental health using the SF-12 MCS, and excluded males who reported thoughts of suicide at baseline. Results After adjustment, there was a 1.48 (95% CI: 0.98–2.23, P = 0.063) increase in the odds of thoughts of suicide among men who also reported a disability. The size of association was similar to that of being unemployed. Conclusions Males reporting disability may also suffer from thoughts of suicide. We speculate that discrimination may be one explanation for the observed association. More research on this topic is needed.

scholarly journals Public acceptability of the UK Soft Drinks Industry Levy: repeat cross-sectional analysis of the International Food Policy Study (2017–2019)

BMJ Open ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. e051677
Author(s):  
Jean Adams ◽  
David Pell ◽  
Tarra L Penney ◽  
David Hammond ◽  
Lana Vanderlee ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Food Policy ◽  
Perceived Effectiveness ◽  
Policy Study ◽  
Cross Sectional ◽  
Public Acceptability ◽  
Adjusted Logistic Regression ◽  
The Uk

ObjectivesTo determine whether public acceptability, in terms of both support for and perceived effectiveness of, the UK Soft Drinks Industry Levy (SDIL) changed between 4 months prior to, and 8 and 20 months after, implementation.DesignRepeat cross-sectional online survey.SettingThe UK.ParticipantsUK respondents to the International Food Policy Study aged 18–64 years who provided information on all variables of interest in November–December 2017 (4 months prior to SDIL implementation), 2018 (8 months after) or 2019 (20 months after; n=10 284).Outcome measuresSelf-reported support for, and perceived effectiveness of, the SDIL.ResultsThe adjusted logistic regression model predicted that 70% (95% CI: 68% to 72%) of participants supported the SDIL in 2017, 68% (95% CI: 67% to 70%) in 2018 and 68% (95% CI: 66% to 70%) in 2019. There was no evidence of a difference in support in 2018 vs 2017 (OR: 0.93; 95% CI: 0.81 to 1.05); or in 2019 vs 2017 (OR: 0.90; 95% CI: 0.78 to 1.03). The adjusted logistic regression model predicted that 72% (95% CI: 70% to 74%) of participants perceived the SDIL to be effective in 2017, 67% (95% CI: 65% to 69%) in 2018 and 67% (95% CI: 64% to 69%) in 2019. There was evidence that perceived effectiveness decreased a small amount in 2018 vs 2017 (OR: 0.78; 95% CI: 0.69 to 0.88). The difference in 2019 vs 2017 was similar.ConclusionsWe found high support for the SDIL among UK adults and this did not change between 4 months before implementation and 8 or 20 months after. While perceived effectiveness remained high, there was evidence that this decreased slightly after implementation in 2018, but no further in 2019. Greater understanding of influences on public acceptability of effective structural public health interventions is required.

Procurement planning as a strategic tool for public procurement effectiveness: Experience from selected public procuring entities in Dodoma city, Tanzania

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ismail Abdi Changalima ◽  
Gift Onesmo Mushi ◽  
Shadrack Samwel Mwaiseje
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Public Procurement ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Cross Sectional ◽  
Content Type ◽  
Survival And Development ◽  
Procurement Planning

Purpose The significance of the public procurement function is on the survival and development of procuring entities and that of a nation at large. This study aims to focus on examining the influence of procurement planning on the effectiveness of public procurement, experience from selected public procuring entities in Dodoma city, Tanzania. Design/methodology/approach A cross-sectional design was adopted from which data were collected from 146 respondents who were purposively chosen from several public procuring entities located at Dodoma city in the United Republic of Tanzania by using a survey structured questionnaire and analysed through a binary logistic regression model. Findings Findings revealed that procurement planning as a strategic function significantly influences the effectiveness of public procurement. The binary logistic regression model included the implementation of prepared procurement plans (p = 0.039), the involvement of users as stakeholders and important institutional actors in public procurement (p = 0.033), compliance to procurement laws and regulations when planning (p = 0.016) and adequacy of budget (p = 0.042) as predictors of procurement planning were tested to be significantly related to the effectiveness of public procurement. It was concluded that public procuring entities can achieve public procurement effectiveness through procurement planning. Social implications The implications and policy recommendations of the findings of this study would be useful to procurement practitioners mostly in public procuring entities. Originality/value This study contributes to adding knowledge to the existing body of knowledge on procurement planning as an imperative activity in public procurement in Tanzania.

Ordinal regression model and the linear regression model were superior to the logistic regression models

2006 ◽  
Vol 59 (5) ◽  
pp. 448-456 ◽  
Author(s):  
Colleen M. Norris ◽  
William A. Ghali ◽  
L. Duncan Saunders ◽  
Rollin Brant ◽  
Diane Galbraith ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Regression Models ◽  
Ordinal Regression ◽  
Logistic Regression Models ◽  
Ordinal Regression Model

scholarly journals Influence of the key account manager in the provisioning management: Evidence from staple companies during the events of COVID-19

Accounting ◽  
2022 ◽  
Vol 8 (2) ◽  
pp. 161-170 ◽  
Author(s):  
Luis-Ricardo Flores-Vilcapoma ◽  
Cynthia-Paola A lbengrin-Mendoza ◽  
Gabriela-Briggite Gomez-Rojas ◽  
Yuri Sánchez-Solis ◽  
Wagner Vicente-Ramos
Keyword(s):  
Experimental Design ◽  
Linear Regression ◽  
Correlation Analysis ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Model ◽  
Multiple Linear Regression Model ◽  
Cross Sectional ◽  
Key Account ◽  
The Impact

The purpose of this research was to evaluate the degree of influence exercised by the Key Account Manager in the provisioning management in the main companies called Staple in Peru, during the events of COVID-19. The research was of type quantitative, cross-sectional and temporal, with a non-experimental design, using a multiple linear regression model and correlation analysis to determine the impact that exists between the variables. The data belongs to the Industrias San Miguel company, distributed in a weekly period from June 2019 to March 2021, which gives 88 observations. The results allow us to conclude that the Key Account Manager is an important manager of the supply of goods during the crisis caused by COVID-19 in staple companies.

scholarly journals Variation Among Hospitals in the Continuity of Care for Older Hospitalized Patients: a Cross-sectional Cohort Study

2021 ◽  
Author(s):  
James S. Goodwin ◽  
Shuang Li ◽  
Jie Zhou ◽  
Yong-Fang Kuo ◽  
Ann Nattinger
Keyword(s):  
Logistic Regression ◽  
Length Of Stay ◽  
Regression Model ◽  
Continuity Of Care ◽  
Logistic Regression Model ◽  
Large Degree ◽  
Patient Characteristics ◽  
Hospitalized Patients ◽  
Cross Sectional ◽  
The Impact

Abstract Background: Little is known about how continuity of care for hospitalized patients varies among hospitals. We describe the number of different general internal medicine physicians seeing hospitalized patients during a medical admission and how that varies by hospital. Methods: We conducted a retrospective study of a national 20% sample of Medicare inpatients from 01/01/16 to 12/31/18. In patients with routine medical admissions (length of stay of 3-6 days, no Intensive Care Unit stay, and seen by only one generalist per day), we assessed odds of receiving all generalist care from one generalist. We calculated rates for each hospital, adjusting for patient and hospital characteristics in a multi-level logistic regression model. Results: Among routine medical admissions with 3- to 6-day stays, only 43.1% received all their generalist care from the same physician. In those with a 3-day stay, 50.1% had one generalist providing care vs. 30.8% in those with a 6-day stay. In a two-level (admission and hospital) logistic regression model controlling for patient characteristics and length of stay, the odds of seeing just one generalist did not vary greatly by patient characteristics such as age, race/ethnicity, comorbidity or reason for admission. There were large variations in continuity of care among different hospitals and geographic areas. In the highest decile of hospitals, the adjusted mean percentage of patients receiving all generalist care from one physician was >84.1%, vs. <24.1% in the lowest decile. This large degree of variation persisted when hospitals were stratified by size, ownership, location or teaching status. Conclusions: Continuity of care provided by generalist physicians to medical inpatients varies widely among hospitals. The impact of this variation on quality of care is unknown.

scholarly journals Perception of the Futile Care and its Relationship With Moral Distress in Nurses of Intensive Care Units

2021 ◽  
Vol 31 (2) ◽  
pp. 85-92
Author(s):  
Somayeh Moaddaby ◽  
◽  
Masoomeh Adib ◽  
Sadra Ashrafi ◽  
Ehsan Kazemnezhad Leili ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Intensive Care ◽  
Regression Model ◽  
Intensive Care Units ◽  
Work Experience ◽  
Logistic Regression Model ◽  
Moral Distress ◽  
Cross Sectional ◽  
Futile Care ◽  
The Mean

Introduction: The development of science and technology has provided more opportunities for patients to live and even receiving futile medical care or treatment with no hope of recovery. This process leads to awkward experiences and moral distress in nurses who frequently deliver with such care. Objective: This study aimed to determine the perception of futile care and its relationship with moral distress in nurses working in intensive care units Materials and Methods: This is a cross-sectional study conducted on 155 nurses working in Intensive Care Units (ICUs) employed in educational-therapeutic centers and hospitals of Guilan Province, Iran. They were selected by convenience sampling method. The study data were collected using the researcher-made questionnaire and Corley moral distress questionnaire. The obtained data were analyzed using descriptive statistics and inferential statistics the Kolmogorov-Smirnov test, nonparametric Mann-Whitney U, Kruskal-Wallis, Fisher exact and Backward logistic regression model. Results: The mean±SD age of the samples was 34.71±6.68 years; their mean±SD work experience was 10.24±5.63 years, and the mean±SD work experience in the ICU was 6.76±4.64 years. The results indicated that their mean±SD perception of futile care was 63±7, and their mean±SD moral distress was 92±54. The score of moral distress showed a low but significant and positive correlation with the legal and organizational aspects of futile care (r=0. 279, P=0.001) and the total score of perception futile care (r=0.2, P=0.012). In the multivariate analysis based on the logistic regression model of futile care, only the relationship between the legal and organizational score in care had a significant relationship with moral distress. So that by increasing one unit in the legal and organizational aspect of care, the chances of scoring above the mean of moral distress increases 1.2 times (P=0.0001, 95% CI; 1.077-1.324). Conclusion: Perhaps by familiarizing nurses with the legal and organizational nature of patient’s care, the moral distress of caring can be reduced.

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