scholarly journals Not so welcome here? Modelling the impact of ethnic in-movers on the length of stay of home-owners in micro-neighbourhoods

Urban Studies ◽  
2019 ◽  
Vol 56 (14) ◽  
pp. 2847-2862
Author(s):  
Sue Easton ◽  
Gwilym Pryce
Keyword(s):  
Length Of Stay ◽  
Survival Time ◽  
Home Ownership ◽  
Ethnic Population ◽  
Data Set ◽  
Consistent Finding ◽  
Neighbourhood Level ◽  
Name Matching ◽  
The Impact ◽  
House Buyers

This paper considers the length of stay of home-owners with white British names in the 40% most-deprived census areas of Glasgow, Scotland. We estimate the impact of ethnically ‘other’ name-group inflows through property purchases at the micro-neighbourhood level. We use a novel longitudinal data set, constructed from the population of home-buyers recorded in all property transaction records from 2003 to 2014, from which we impute ethnicity using name-matching software. We estimate how the survival time (length of ownership) of home-owners with white British names is affected by in-migration of house-buyers from different ethnic name-groups into the micro-neighbourhood, defined as a 50 m radius around each home. Results suggest a complex set of associations between ethnically ‘other’ purchasers/in-movers (based on name groups) and duration of home-ownership for white-British named owners. The most consistent finding is for in-moving purchasers with Pakistani (primarily Muslim) names, which tend to have a relatively large accelerant effect on the moving propensity of home-owners who have white British names. This was true in areas of both high and low non-white ethnic population share. We also find evidence of nonlinearity in this relationship: the accelerant effect diminishes with each additional in-move from purchasers with Pakistani names. The name group with the largest overall accelerant effect was for in-movers with non-white Other names, which were also primarily Muslim in origin, though this effect was less consistent across models.

scholarly journals Using propensity for pre-diagnosis behavior as a predictor of cancer survival time: an example in esophageal cancer.

2019 ◽  
Author(s):  
Paul Patrick Fahey ◽  
Andrew Page ◽  
Glenn Stone ◽  
Thomas Astell-Burt
Keyword(s):  
Esophageal Cancer ◽  
Health Behavior ◽  
Health Behaviors ◽  
Survival Time ◽  
Cell Cancer ◽  
Demographic Characteristics ◽  
Background Information ◽  
Actual Behavior ◽  
Data Set ◽  
The Impact

Abstract Background: Information on the associations between pre-diagnosis health behavior and post-diagnosis survival time in esophageal cancer could assist in choosing treatments and planning health services but can be difficult to obtain using established study designs. We postulated that, with a large data set, using estimated propensity for a behavior as a predictor of survival times could provide useful insight as to the impact of actual behavior. Methods: Data from a national health survey and logistic regression were used to calculate the propensity of selected health behaviors from participant’s demographic characteristics for each esophageal cancer case within a large cancer registry data base. The associations between survival time and the propensity of the health behaviors were investigated using Cox regression. Results: Observed associations include: a 0.1 increase in the probability of smoking one year prior to diagnosis was detrimental to survival (Hazard Ratio (HR) 1.21, 95% CI 1.19,1.23); a 0.1 increase in the probability of hazardous alcohol consumption 10 years prior to diagnosis was associated with decreased survival in squamous cell cancer (HR 1.29, 95% CI 1.07, 1.56) but not adenocarcinoma (HR 1.08, 95% CI 0.94,1.25); a 0.1 increase in the probability of physical activity outside the workplace is protective (HR 0.83, 95% CI 0.81,0.84). Conclusions: We conclude that propensity for health behavior estimated from demographic characteristics can assist in determining existence of the association between pre-diagnosis health behavior and post-diagnosis health outcomes, allowing some sharing information across otherwise unrelated data collections.

scholarly journals Hypoglycemia and Clinical Outcomes in Hospitalized Patients With Diabetes: Does Association With Adverse Outcomes Remain When Number of Glucose Tests Performed Is Accounted For?

2017 ◽  
Vol 11 (4) ◽  
pp. 720-723 ◽  
Author(s):  
Gregory C. Jones ◽  
Joseph G. Timmons ◽  
Scott G. Cunningham ◽  
Stephen J. Cleland ◽  
Christopher A. R. Sainsbury
Keyword(s):  
Length Of Stay ◽  
Simulated Data ◽  
Economic Modeling ◽  
Adverse Outcomes ◽  
Health Board ◽  
Minor Effect ◽  
Data Set ◽  
Sample Number ◽  
Mathematical Association ◽  
The Impact

Background: Hypoglycemia is associated with increased length of stay in hospital patients, but previous studies have not considered the confounding effect of increased hypoglycemia detection associated with increased capillary blood glucose (CBG) measurement in prolonged admissions. We aimed to determine the effect of recorded hypoglycemia on length of stay of hospital inpatients (LOS) when this mathematical association is subtracted. Methods: CBG data were analyzed for inpatients within our health board area (01/2009-01/2015). A simulated CBG data set was generated for each patient with an identical sampling frequency to the measured CBG data set. The mathematical component of increased LOS was determined using the simulated data set. Subtraction of this confounding mathematical association was used to provide measurement of the true clinical association between recorded hypoglycemia (CBG < 4 mmol [< 72mg/dl]) and LOS. Results: A total of 196 962 admissions of 52 475 individuals with known diabetes were analyzed. 68 809 admissions of 29 551 individuals had >4 CBG measurements made and were included in analysis. After subtraction of the mathematical association of increased sample number, the clinical effect of recorded hypoglycemia is reduced—but persists—compared to previous studies. 1-2 days with recorded hypoglycemia has a relatively minor effect on LOS. LOS increases rapidly if there are ≥3 days with recorded hypoglycemia, with an increase of 0.75 days LOS per additional day with hypoglycemia. Conclusions: This technique increases accuracy of economic modeling of the impact of hypoglycemia on health care systems. This could assist study of the impact of hypoglycemia on other outcomes by factoring for bias of increased sample numbers.

Validation and Calibration of the Risk Stratification Index

2017 ◽  
Vol 126 (4) ◽  
pp. 623-630 ◽  
Author(s):  
George F. Chamoun ◽  
Linyan Li ◽  
Nassib G. Chamoun ◽  
Vikas Saini ◽  
Daniel I. Sessler
Keyword(s):  
Length Of Stay ◽  
Risk Stratification ◽  
Hospital Mortality ◽  
Analysis Data ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Data Set ◽  
Procedure Codes ◽  
The Impact ◽  
Present On Admission

Abstract Background The Risk Stratification Index was developed from 35 million Medicare hospitalizations from 2001 to 2006 but has yet to be externally validated on an independent large national data set, nor has it been calibrated. Finally, the Medicare Analysis and Provider Review file now allows 25 rather than 9 diagnostic codes and 25 rather than 6 procedure codes and includes present-on-admission flags. The authors sought to validate the index on new data, test the impact of present-on-admission codes, test the impact of the expansion to 25 diagnostic and procedure codes, and calibrate the model. Methods The authors applied the original index coefficients to 39,753,036 records from the 2007–2012 Medicare Analysis data set and calibrated the model. The authors compared their results with 25 diagnostic and 25 procedure codes, with results after restricting the model to the first 9 diagnostic and 6 procedure codes and to codes present on admission. Results The original coefficients applied to the 2007–2012 data set yielded C statistics of 0.83 for 1-yr mortality, 0.84 for 30-day mortality, 0.94 for in-hospital mortality, and 0.86 for median length of stay—values nearly identical to those originally reported. Calibration equations performed well against observed outcomes. The 2007–2012 model discriminated similarly when codes were restricted to nine diagnostic and six procedure codes. Present-on-admission models were about 10% less predictive for in-hospital mortality and hospital length of stay but were comparably predictive for 30-day and 1-yr mortality. Conclusions Risk stratification performance was largely unchanged by additional diagnostic and procedure codes and only slightly worsened by restricting analysis to codes present on admission. The Risk Stratification Index, after calibration, thus provides excellent discrimination and calibration for important health services outcomes and thus appears to be a good basis for making hospital comparisons.

scholarly journals Attributable Cost and Length of Stay Associated with Nosocomial Gram-Negative Bacterial Cultures

2018 ◽  
Vol 62 (11) ◽  
Author(s):  
Richard E. Nelson ◽  
Vanessa W. Stevens ◽  
Makoto Jones ◽  
Karim Khader ◽  
Marin L. Schweizer ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Financial Burden ◽  
Time Dependent ◽  
Inpatient Cost ◽  
Resistance Level ◽  
Data Set ◽  
Gram Negative ◽  
Content Type ◽  
Conventional Analysis ◽  
The Impact

ABSTRACT Few studies have estimated the excess inpatient costs due to nosocomial cultures of Gram-negative bacteria (GNB), and those that do are often subject to time-dependent bias. Our objective was to generate estimates of the attributable costs of the underlying infections associated with nosocomial cultures by using a unique inpatient cost data set from the U.S. Department of Veterans Affairs that allowed us to reduce time-dependent bias. Our study included data from inpatient admissions between 1 October 2007 and 30 November 2010. Nosocomial GNB-positive cultures were defined as clinical cultures positive for Acinetobacter, Pseudomonas, or Enterobacteriaceae between 48 h after admission and discharge. Positive cultures were further classified by site and level of resistance. We conducted analyses using both a conventional approach and an approach aimed at reducing the impact of time-dependent bias. In both instances, we used multivariable generalized linear models to compare the inpatient costs and length of stay for patients with and without a nosocomial GNB culture. Of the 404,652 patients included in the conventional analysis, 12,356 had a nosocomial GNB-positive culture. The excess costs of nosocomial GNB-positive cultures were significant, regardless of specific pathogen, site, or resistance level. Estimates generated using the conventional analysis approach were 32.0% to 131.2% greater than those generated using the approach to reduce time-dependent bias. These results are important because they underscore the large financial burden attributable to these infections and provide a baseline that can be used to assess the impact of improvements in infection control.

Age at Exposure to Parental Suicide and the Subsequent Risk of Suicide in Young People

Crisis ◽  
2018 ◽  
Vol 39 (1) ◽  
pp. 27-36 ◽  
Author(s):  
Kuan-Ying Lee ◽  
Chung-Yi Li ◽  
Kun-Chia Chang ◽  
Tsung-Hsueh Lu ◽  
Ying-Yeh Chen
Keyword(s):  
Young People ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Birth Registry ◽  
Data Set ◽  
Parental Suicide ◽  
The Impact ◽  
Age At Exposure

Abstract. Background: We investigated the age at exposure to parental suicide and the risk of subsequent suicide completion in young people. The impact of parental and offspring sex was also examined. Method: Using a cohort study design, we linked Taiwan's Birth Registry (1978–1997) with Taiwan's Death Registry (1985–2009) and identified 40,249 children who had experienced maternal suicide (n = 14,431), paternal suicide (n = 26,887), or the suicide of both parents (n = 281). Each exposed child was matched to 10 children of the same sex and birth year whose parents were still alive. This yielded a total of 398,081 children for our non-exposed cohort. A Cox proportional hazards model was used to compare the suicide risk of the exposed and non-exposed groups. Results: Compared with the non-exposed group, offspring who were exposed to parental suicide were 3.91 times (95% confidence interval [CI] = 3.10–4.92 more likely to die by suicide after adjusting for baseline characteristics. The risk of suicide seemed to be lower in older male offspring (HR = 3.94, 95% CI = 2.57–6.06), but higher in older female offspring (HR = 5.30, 95% CI = 3.05–9.22). Stratified analyses based on parental sex revealed similar patterns as the combined analysis. Limitations: As only register-­based data were used, we were not able to explore the impact of variables not contained in the data set, such as the role of mental illness. Conclusion: Our findings suggest a prominent elevation in the risk of suicide among offspring who lost their parents to suicide. The risk elevation differed according to the sex of the afflicted offspring as well as to their age at exposure.

State Medical Boards' Perceptions of a Minimum Data Set and Current Practices for Collecting Physician Information

2013 ◽  
Vol 99 (4) ◽  
pp. 40-45 ◽  
Author(s):  
Aaron Young ◽  
Philip Davignon ◽  
Margaret B. Hansen ◽  
Mark A. Eggen
Keyword(s):  
Media Coverage ◽  
The United States ◽  
Minimum Data Set ◽  
Direct Patient Care ◽  
Physician Workforce ◽  
Data Set ◽  
Minimum Data ◽  
State Medical Boards ◽  
The Impact ◽  
Current Practices

ABSTRACT Recent media coverage has focused on the supply of physicians in the United States, especially with the impact of a growing physician shortage and the Affordable Care Act. State medical boards and other entities maintain data on physician licensure and discipline, as well as some biographical data describing their physician populations. However, there are gaps of workforce information in these sources. The Federation of State Medical Boards' (FSMB) Census of Licensed Physicians and the AMA Masterfile, for example, offer valuable information, but they provide a limited picture of the physician workforce. Furthermore, they are unable to shed light on some of the nuances in physician availability, such as how much time physicians spend providing direct patient care. In response to these gaps, policymakers and regulators have in recent years discussed the creation of a physician minimum data set (MDS), which would be gathered periodically and would provide key physician workforce information. While proponents of an MDS believe it would provide benefits to a variety of stakeholders, an effort has not been attempted to determine whether state medical boards think it is important to collect physician workforce data and if they currently collect workforce information from licensed physicians. To learn more, the FSMB sent surveys to the executive directors at state medical boards to determine their perceptions of collecting workforce data and current practices regarding their collection of such data. The purpose of this article is to convey results from this effort. Survey findings indicate that the vast majority of boards view physician workforce information as valuable in the determination of health care needs within their state, and that various boards are already collecting some data elements. Analysis of the data confirms the potential benefits of a physician minimum data set (MDS) and why state medical boards are in a unique position to collect MDS information from physicians.

The Institute for Healthcare Improvement–NeuroPoint Alliance collaboration to decrease length of stay and readmission after lumbar spine fusion: using national registries to design quality improvement protocols

2020 ◽  
Vol 33 (6) ◽  
pp. 812-821
Author(s):  
Scott L. Zuckerman ◽  
Clinton J. Devin ◽  
Vincent Rossi ◽  
Silky Chotai ◽  
E. Hunter Dyer ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Length Of Stay ◽  
Discharge Planning ◽  
Lumbar Fusion ◽  
Nonparametric Tests ◽  
Learning System ◽  
Design Quality ◽  
Implementation Phase ◽  
Healthcare Improvement ◽  
The Impact

OBJECTIVENational databases collect large amounts of clinical information, yet application of these data can be challenging. The authors present the NeuroPoint Alliance and Institute for Healthcare Improvement (NPA-IHI) program as a novel attempt to create a quality improvement (QI) tool informed through registry data to improve the quality of care delivered. Reducing the length of stay (LOS) and readmission after elective lumbar fusion was chosen as the pilot module.METHODSThe NPA-IHI program prospectively enrolled patients undergoing elective 1- to 3-level lumbar fusions across 8 institutions. A three-pronged approach was taken that included the following phases: 1) Research Phase, 2) Development Phase, and 3) Implementation Phase. Primary outcomes were LOS and readmission. From January to June 2017, a learning system was created utilizing monthly conference calls, weekly data submission, and continuous refinement of the proposed QI tool. Nonparametric tests were used to assess the impact of the QI intervention.RESULTSThe novel QI tool included the following three areas of intervention: 1) preoperative discharge assessment (location, date, and instructions), 2) inpatient changes (LOS rounding checklist, daily huddle, and pain assessments), and 3) postdischarge calls (pain, primary care follow-up, and satisfaction). A total of 209 patients were enrolled, and the most common procedure was a posterior laminectomy/fusion (60.2%). Seven patients (3.3%) were readmitted during the study period. Preoperative discharge planning was completed for 129 patients (61.7%). A shorter median LOS was seen in those with a known preoperative discharge date (67 vs 80 hours, p = 0.018) and clear discharge instructions (71 vs 81 hours, p = 0.030). Patients with a known preoperative discharge plan also reported significantly increased satisfaction (8.0 vs 7.0, p = 0.028), and patients with increased discharge readiness (scale 0–10) also reported higher satisfaction (r = 0.474, p < 0.001). Those receiving postdischarge calls (76%) had a significantly shorter LOS than those without postdischarge calls (75 vs 99 hours, p = 0.020), although no significant relationship was seen between postdischarge calls and readmission (p = 0.342).CONCLUSIONSThe NPA-IHI program showed that preoperative discharge planning and postdischarge calls have the potential to reduce LOS and improve satisfaction after elective lumbar fusion. It is our hope that neurosurgical providers can recognize how registries can be used to both develop and implement a QI tool and appreciate the importance of QI implementation as a separate process from data collection/analysis.

The Impact of Green Labels on U.S. Hotel Net Operating Income: Operating Statements Analyses

2019 ◽  
Vol 11 (1) ◽  
pp. 156-173
Author(s):  
Spenser Robinson ◽  
A.J. Singh
Keyword(s):  
Environmental Design ◽  
Green Buildings ◽  
Small Sample ◽  
Sample Survey ◽  
Data Set ◽  
Operating Income ◽  
Energy Star ◽  
The Impact ◽  
Industry Professionals

This paper shows Leadership in Energy and Environmental Design (LEED) certified hospitality properties exhibit increased expenses and earn lower net operating income (NOI) than non-certified buildings. ENERGY STAR certified properties demonstrate lower overall expenses than non-certified buildings with statistically neutral NOI effects. Using a custom sample of all green buildings and their competitive data set as of 2013 provided by Smith Travel Research (STR), the paper documents potential reasons for this result including increased operational expenses, potential confusion with certified and registered LEED projects in the data, and qualitative input. The qualitative input comes from a small sample survey of five industry professionals. The paper provides one of the only analyses on operating efficiencies with LEED and ENERGY STAR hospitality properties.

Does Tax Increment Financing Pass the “But-for” Test in Missouri?

2019 ◽  
Vol 33 (3) ◽  
pp. 187-202
Author(s):  
Ahmed Rachid El-Khattabi ◽  
T. William Lester
Keyword(s):  
Economic Development ◽  
Kansas City ◽  
Time Series Data ◽  
Local Level ◽  
Conclusive Evidence ◽  
Series Data ◽  
Tax Increment Financing ◽  
Data Set ◽  
Development Indicators ◽  
The Impact

The use of tax increment financing (TIF) remains a popular, yet highly controversial, tool among policy makers in their efforts to promote economic development. This study conducts a comprehensive assessment of the effectiveness of Missouri’s TIF program, specifically in Kansas City and St. Louis, in creating economic opportunities. We build a time-series data set starting 1990 through 2012 of detailed employment levels, establishment counts, and sales at the census block-group level to run a set of difference-in-differences with matching estimates for the impact of TIF at the local level. Although we analyze the impact of TIF on a wide set of indicators and across various industry sectors, we find no conclusive evidence that the TIF program in either city has a causal impact on key economic development indicators.

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