Associations between county-level general surgeon (GS) and gastroenterologist (GA) density and outcomes for hepatobiliary cancer (HBC).

2012 ◽  
Vol 30 (4_suppl) ◽  
pp. 292-292
Author(s):  
Trevor C. Tsang ◽  
Winson Y. Cheung
Keyword(s):  
Level Density ◽  
Population Level ◽  
General Surgeon ◽  
County Level ◽  
Physician Density ◽  
Logistic Regression Models ◽  
Hepatobiliary Cancer ◽  
Incidence And Mortality ◽  
Beta Coefficient ◽  
The Impact

292 Background: Surgical resection is the mainstay of treatment for early, localized HBC. Prior studies consistently show an association between procedure volumes and cancer outcomes, but the impact of surgeon and physician density is unclear. Our aims were to 1) examine the effects of GS and GA density on HBC mortality and 2) compare the relative importance of GS versus GA density on HBC outcomes. Methods: Using county-level data from the Area Resource File, US Census, and National Cancer Institute, we developed both multivariate linear and logistic regression models to determine the effect of GS and GA density on overall HBC mortality between 2002 and 2006, while controlling for cancer incidence, county demographics and socioeconomic factors. Results: In total, 793 counties were analyzed: mean HBC incidence and mortality were 5.89 and 5.34 per 100,000 persons, respectively; 77% were metropolitan; mean GS and GA densities were 10.6 and 3.5 per 100,000 people, respectively. When compared to counties with no GS, those with at least one had a statistically significant decrease in HBC-specific mortality (beta coefficient -.115; p=.001). In contrast, when compared to counties with no GA, those with at least one showed a trend towards lower mortality (beta coefficient -.0677; p=.065). Increasing the county-level density of GS and GA improved outcomes, but increases beyond 10 GS or 4 GA per 100,000 people did not continue to result in significant reductions in HBC mortality; rather, these showed an increase in HBC mortality. Conclusions: Reductions in HBC mortality are more strongly influenced by increasing GS than GA density. There appears to be a ceiling effect at which point increasing GS and GA density does not appear to result in improvements in HBC outcomes. A strategy of allocating healthcare resources and distributing the workforce across counties will optimize outcomes at the population-level.

Surgical density and its effect on esophageal cancer (EC) and gastric (GC) mortality.

2011 ◽  
Vol 29 (4_suppl) ◽  
pp. 16-16
Author(s):  
M. Y. Ho ◽  
J. S. Albarrak ◽  
W. Y. Cheung
Keyword(s):  
Household Income ◽  
Population Level ◽  
Multimodality Treatment ◽  
General Surgeon ◽  
County Level ◽  
Median Household Income ◽  
Hospital Beds ◽  
Beta Coefficient ◽  
General Surgeons ◽  
The Impact

16 Background: Surgical resection plays an integral role in the multimodality treatment of patients with EC or GC. The distribution of thoracic and general surgeons at the county level varies widely across the US. The impact of the allocation of these surgeons on cancer outcomes is unclear. Our aims were to 1) examine the effect of surgeon density on EC or GC mortality, 2) compare the relative roles of thoracic and general surgeons on EC and GC outcomes and 3) determine other county characteristics associated with cancer mortality. Methods: Using county-level data from the Area Resources File, U.S. Census and National Cancer Institute, we constructed regression models to explore the effect of thoracic and general surgeon density on EC and GC mortality, respectively. Multivariate analyses controlled for incidence rate, county demographics (population aged 65+, proportion eligible for Medicare, education attainment, metropolitan vs. rural), socioeconomic factors (median household income) and healthcare resources (number of general practitioners, number of hospital beds). Results: In total, 332 and 402 counties were identified for EC and GC, respectively: mean EC/GC incidence = 5.29/6.83; mean EC/GC mortality=4.70/3.92; 91% were metropolitan and 9% were rural; mean thoracic and general surgeon densities were 10 and 63 per 100,000 people, respectively. When compared to counties with no thoracic surgeons, those with at least 1 thoracic surgeon had reduced EC mortality (beta coefficient -0.031). For GC, counties with 1 or more general surgeons also had decreased number of deaths (beta coefficient -0.095) when compared with those without any surgeons. While increasing the density of surgeons beyond 10 only yielded minimal improvements in EC mortality, it resulted in significant further reductions in GC mortality. Other county characteristics, such as increased number of hospital beds and higher median household income, were correlated with improved outcomes. Conclusions: Mortality from GC appears to be more susceptible to the benefits of increased surgeon density. For EC, a strategic policy of allocating health resources and distributing the workforce across counties will be best able to optimize outcomes at the population-level. No significant financial relationships to disclose.

scholarly journals The potential impact of urine-LAM diagnostics on tuberculosis incidence and mortality: A modelling analysis

PLoS Medicine ◽  
2020 ◽  
Vol 17 (12) ◽  
pp. e1003466
Author(s):  
Saskia Ricks ◽  
Claudia M. Denkinger ◽  
Samuel G. Schumacher ◽  
Timothy B. Hallett ◽  
Nimalan Arinaminpathy
Keyword(s):  
Population Level ◽  
Credible Interval ◽  
Hiv Care ◽  
People Living With Hiv ◽  
Country Level ◽  
Incidence And Mortality ◽  
The Status ◽  
Epidemiological Impact ◽  
Incident Cases ◽  
The Impact

Background Lateral flow urine lipoarabinomannan (LAM) tests could offer important new opportunities for the early detection of tuberculosis (TB). The currently licensed LAM test, Alere Determine TB LAM Ag (‘LF-LAM’), performs best in the sickest people living with HIV (PLHIV). However, the technology continues to improve, with newer LAM tests, such as Fujifilm SILVAMP TB LAM (‘SILVAMP-LAM’) showing improved sensitivity, including amongst HIV-negative patients. It is important to anticipate the epidemiological impact that current and future LAM tests may have on TB incidence and mortality. Methods and findings Concentrating on South Africa, we examined the impact that widening LAM test eligibility would have on TB incidence and mortality. We developed a mathematical model of TB transmission to project the impact of LAM tests, distinguishing ‘current’ tests (with sensitivity consistent with LF-LAM), from hypothetical ‘future’ tests (having sensitivity consistent with SILVAMP-LAM). We modelled the impact of both tests, assuming full adoption of the 2019 WHO guidelines for the use of these tests amongst those receiving HIV care. We also simulated the hypothetical deployment of future LAM tests for all people presenting to care with TB symptoms, not restricted to PLHIV. Our model projects that 2,700,000 (95% credible interval [CrI] 2,000,000–3,600,000) and 420,000 (95% CrI 350,000–520,000) cumulative TB incident cases and deaths, respectively, would occur between 2020 and 2035 if the status quo is maintained. Relative to this comparator, current and future LAM tests would respectively avert 54 (95% CrI 33–86) and 90 (95% CrI 55–145) TB deaths amongst inpatients between 2020 and 2035, i.e., reductions of 5% (95% CrI 4%–6%) and 9% (95% CrI 7%–11%) in inpatient TB mortality. This impact in absolute deaths averted doubles if testing is expanded to include outpatients, yet remains <1% of country-level TB deaths. Similar patterns apply to incidence results. However, deploying a future LAM test for all people presenting to care with TB symptoms would avert 470,000 (95% CrI 220,000–870,000) incident TB cases (18% reduction, 95% CrI 9%–29%) and 120,000 (95% CrI 69,000–210,000) deaths (30% reduction, 95% CrI 18%–44%) between 2020 and 2035. Notably, this increase in impact arises largely from diagnosis of TB amongst those with HIV who are not yet in HIV care, and who would thus be ineligible for a LAM test under current guidelines. Qualitatively similar results apply under an alternative comparator assuming expanded use of GeneXpert MTB/RIF (‘Xpert’) for TB diagnosis. Sensitivity analysis demonstrates qualitatively similar results in a setting like Kenya, which also has a generalised HIV epidemic, but a lower burden of HIV/TB coinfection. Amongst limitations of this analysis, we do not address the cost or cost-effectiveness of future tests. Our model neglects drug resistance and focuses on the country-level epidemic, thus ignoring subnational variations in HIV and TB burden. Conclusions These results suggest that LAM tests could have an important effect in averting TB deaths amongst PLHIV with advanced disease. However, achieving population-level impact on the TB epidemic, even in high-HIV-burden settings, will require future LAM tests to have sufficient performance to be deployed more broadly than in HIV care.

scholarly journals COVID-19 pandemic in the African continent: Forecasts of cumulative cases, new infections, and mortality

2020 ◽  
Author(s):  
T Achoki ◽  
U Alam ◽  
L Were ◽  
T Gebremedhin ◽  
F Senkubuge ◽  
...  
Keyword(s):  
Central Africa ◽  
Population Level ◽  
Eastern Africa ◽  
Local Context ◽  
African Countries ◽  
Enabling Factors ◽  
Western Africa ◽  
Incidence And Mortality ◽  
The Impact ◽  
Mortality Estimates

BackgroundThe epidemiology of COVID-19 remains speculative in Africa. To the best of our knowledge, no study, using robust methodology provides its trajectory for the region or accounts for local context. This paper is the first systematic attempt to provide prevalence, incidence, and mortality estimates across Africa.MethodsCaseloads and incidence forecasts are from a co-variate-based instrumental variable regression model. Fatality rates from Italy and China were applied to generate mortality estimates after making relevant health system and population-level characteristics related adjustments between each of the African countries.ResultsBy June 30 2020, around 16.3 million people in Africa will contract COVID-19 (95% CI 718,403 to 98,358,799). Northern and Eastern Africa will be the most and least affected areas. Cumulative cases by June 30 are expected to reach around 2.9 million (95% CI 465,028 to 18,286,358) in Southern Africa, 2.8 million (95% CI 517,489 to 15,056,314) in Western Africa, and 1.2 million (95% CI 229,111 to 6,138,692) in Central Africa. Incidence for the month of April 2020 is expected to be highest in Djibouti, 32.8 per 1000 (95% CI 6.25 to 171.77), while Morocco will experience among the highest fatalities (1,045 deaths, 95% CI 167 to 6,547).ConclusionLess urbanized countries with low levels of socio-economic development (hence least connected to the world), are likely to register lower and slower transmissions at the early stages of an epidemic. However, the same enabling factors that worked for their benefit can hinder interventions that have lessened the impact of COVID-19 elsewhere.

Associations between county-level surgeon density and colorectal cancer (CRC) mortality.

2011 ◽  
Vol 29 (4_suppl) ◽  
pp. 511-511
Author(s):  
J. S. Albarrak ◽  
M. Y. Ho ◽  
W. Y. Cheung
Keyword(s):  
Level Density ◽  
Population Based ◽  
General Surgeon ◽  
County Level ◽  
Surgical Workforce ◽  
Improved Outcomes ◽  
Level Data ◽  
Colorectal Surgeon ◽  
Annual Changes ◽  
Us Census

511 Background: Strong associations between surgeon procedure volumes and patient outcomes have been observed for many types of cancers. Whether surgeon density in a population has a similar impact on cancer outcomes is unclear. Our aims were to 1) explore the effect of US county-level surgeon density on CRC mortality and on annual changes in death, 2) compare the relative importance of colorectal surgeon (CS) versus general surgeon (GS) density on these CRC outcomes, and 3) identify other county characteristics associated with reduced mortality. Methods: Using county-level data from the Area Resource File, US Census and National Cancer Institute, we developed multivariate regression models to determine the effect of a) CS and b) GS on overall CRC mortality and changes in death between 2002 and 2006, while controlling for CRC incidence, county demographics and other socioeconomic factors. Results: A total of 1,187 US counties were included: mean CRC incidence and death rates were 64.9 and 19.9, respectively; 57% were metropolitan and 43% were rural counties; mean CS and GS densities were 1.23 and 1.94 per 100,000 people, respectively. When compared to counties with no CS and no GS, those with at least of one of these surgeons had a statistically significant decrease in CRC-specific mortality (beta coefficients were -0.035 and -0.051 for CS and GS, respectively; p=0.014). Increasing the county-level density of surgeons improved outcomes, but increasing it beyond 8 CS or 12 GS per 100,000 people did not continue to result in significant reductions in CRC mortality. Similar associations between surgeon density and annual changes in CRC-related death were observed. Counties with a high proportion of Medicare enrollees also showed increased CRC mortality. Conclusions: The presence of CS and GS at the county level is each associated with lower mortality from CRC. However, there appears to be a ceiling effect at which point further increases in their density do not produce continued improvements in CRC outcomes. A balanced strategy of allocating healthcare resources and distributing the surgical workforce evenly across all counties will likely offer the most substantial population-based improvements in CRC mortality. No significant financial relationships to disclose.

scholarly journals Racial Disparities in Context: Student-, School-, and County-Level Effects on the Likelihood of Obesity among Elementary School Students

2017 ◽  
Vol 4 (2) ◽  
pp. 245-260
Author(s):  
Joy Rayanne Piontak ◽  
Michael D. Schulman
Keyword(s):  
Childhood Obesity ◽  
Racial Disparities ◽  
Racial Differences ◽  
The United States ◽  
School Level ◽  
Racial Composition ◽  
County Level ◽  
School Students ◽  
Logistic Regression Models ◽  
The Impact

Childhood obesity rates in the United States have risen since the 1980s and are especially high among racial minorities. Researchers document differentials in obesity rates by race, socioeconomic status, school characteristics, and place. In this study, the authors examine the impact of race on the likelihood of obesity at the student, school, and county levels and the interactions between student race and school racial composition. The data are from 74,661 third to fifth grade students in 317 schools in 38 North Carolina counties. Multilevel logistic regression models showed that racial differences in the likelihood of obesity persisted even when racial composition and socioeconomic disadvantage at the school level were controlled. The differences between white and nonwhite students slightly decreased once school-level measures were added. The magnitude of the effects of student-level race on the relative odds of obesity varied according to the racial composition of the school. These student- and school-level results held even when county-level race and socioeconomic variables were controlled. The results show that contextual factors at the school and county levels are important social determinants of racial disparities in the likelihood of childhood obesity.

scholarly journals Introduction to the Cancer Intervention and Surveillance Modeling Network (CISNET) Breast Cancer Models

2018 ◽  
Vol 38 (1_suppl) ◽  
pp. 3S-8S ◽  
Author(s):  
Oguzhan Alagoz ◽  
Donald A. Berry ◽  
Harry J. de Koning ◽  
Eric J. Feuer ◽  
Sandra J. Lee ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Control Strategies ◽  
Cancer Control ◽  
Population Level ◽  
Breast Cancer Outcomes ◽  
Detection Technology ◽  
Cancer Models ◽  
Incidence And Mortality ◽  
Cancer Intervention ◽  
The Impact

The Cancer Intervention and Surveillance Modeling Network (CISNET) Breast Cancer Working Group is a consortium of National Cancer Institute–sponsored investigators who use statistical and simulation modeling to evaluate the impact of cancer control interventions on long-term population-level breast cancer outcomes such as incidence and mortality and to determine the impact of different breast cancer control strategies. The CISNET breast cancer models have been continuously funded since 2000. The models have gone through several updates since their inception to reflect advances in the understanding of the molecular basis of breast cancer, changes in the prevalence of common risk factors, and improvements in therapy and early detection technology. This article provides an overview and history of the CISNET breast cancer models, provides an overview of the major changes in the model inputs over time, and presents examples for how CISNET breast cancer models have been used for policy evaluation.

scholarly journals Sickness absence among young and middle-aged workers in Norway: The impact of a population-level intervention

2020 ◽  
Author(s):  
Therese Nordberg Hanvold ◽  
Petter Kristensen ◽  
Karina Corbett ◽  
Rachel Louise Hasting ◽  
Ingrid Sivesind Mehlum
Keyword(s):  
Sickness Absence ◽  
Positive Impact ◽  
Population Level ◽  
Sex Industry ◽  
Manufacturing Companies ◽  
Middle Aged ◽  
Study Objective ◽  
Logistic Regression Models ◽  
Female Workers ◽  
The Impact

Abstract Background The study objective was to evaluate the impact of a population-level intervention (the IA Agreement) on the reduction of sickness absence (SA) among young and middle aged workers in Norway. Methods Using an observational design we conducted a quasi-experimental study to analyse registry data on individual SA for all employed individuals in 2000 (n=298 690) and 2005 (n=352 618), born in Norway between 1976 and 1967. The intervention of interest was the tripartite agreement for a more inclusive working life (the IA Agreement). We estimated difference in pre-post differences (DID) in SA between individuals working in IA companies with the intervention and companies without, in 2000 and 2005. We used logistic regression models and present odds ratios (DID OR) with accompanying 95% CI. We stratified analyses by sex, industry and company size. Results. We found no significant impact on the overall risk of sickness absence after implementing the intervention among young and middle aged workers. Stratified by sex, the intervention resulted in a slight decrease in SA among female workers (DID OR 0.93 (0.91-0.96)) while the intervention showed no impact among male workers (DID OR 1.01 (0.97-1.06)). We found that companies signing the IA Agreement were large companies (≥50­ employees) often within the manufacturing and health and social sectors. In large manufacturing companies, we found a reduction in SA among workers both in companies with and without the intervention, resulting in no statistically significant impact of the actual IA intervention on SA. In large health and social companies, we found an increase in SA among workers both in companies with and without the intervention. The increase was smaller among the workers in companies offering the IA intervention compared with workers in companies without, resulting in a positive impact of the actual IA intervention in the health and social industry. This impact was statistically significant only among female workers. Conclusions The results indicate that the impact of the IA Agreement on SA varies considerably depending on sex and industry. These findings suggest that reducing SA may warrant industry-specific interventions.

Acute care utilization (ACU) among women receiving adjuvant chemotherapy for early breast cancer (EBC).

2012 ◽  
Vol 30 (27_suppl) ◽  
pp. 65-65 ◽  
Author(s):  
Katherine Enright ◽  
Eva Grunfeld ◽  
Lingsong Yun ◽  
Rahim Moineddin ◽  
Susan Faye Dent ◽  
...  
Keyword(s):  
Adjuvant Chemotherapy ◽  
Geographic Location ◽  
Population Level ◽  
Population Based ◽  
Care Utilization ◽  
Population Based Study ◽  
Logistic Regression Models ◽  
Ontario Cancer Registry ◽  
Acute Care Utilization ◽  
The Impact

65 Background: Adjuvant chemotherapy is considered standard care for patients with lymph node (LN) positive and high risk LN negative EBC. While toxicities of chemotherapy are documented in clinical trials, the impact of toxicities on ACU at a population level is unknown. We undertook a population based study of ACU in patients undergoing adjuvant chemotherapy for EBC compared with controls. Methods: All EBC patients diagnosed 01/07 – 12/09 in Ontario, Canada, were identified from the Ontario Cancer Registry. Pt records were linked deterministically to provincial healthcare databases. All patients received ≥1 cycle of adjuvant chemotherapy. EBC cases (n = 4,718) were matched to non-cancer controls (n = 4,718) on age and geographic location. ACUs (emergency room or hospitalizations) within 30 days of chemotherapy were identified. If the primary reason for visit was a common toxicity of chemotherapy, the visit was considered chemotherapy associated (CA). All cause and CA visits were compared between cases and controls. Logistic regression models were used to identify covariates associated with ACU. Results: ACU was significantly higher in EBC pts compared with controls for both all cause (42.1% vs 9.1%, p<.001) and CA (30.7% vs 2.4%, p<.001) visits. Fever was the most common CA toxicity (22.9% vs 1.2%, p<.001). Taxanes were significantly associated with increased ACU compared with anthracycline only. Conclusions: ACU is common among EBC receiving chemotherapy and significantly higher than among controls. Interventions aimed at mitigating CA toxicity, particularly with the use of taxanes may reduce ACUs. [Table: see text]

scholarly journals Urologist Density and County-Level Urologic Cancer Mortality

2010 ◽  
Vol 28 (15) ◽  
pp. 2499-2504 ◽  
Author(s):  
Anobel Y. Odisho ◽  
Matthew R. Cooperberg ◽  
Vincent Fradet ◽  
Ardalan E. Ahmad ◽  
Peter R. Carroll
Keyword(s):  
Kidney Cancer ◽  
Cancer Mortality ◽  
Population Level ◽  
Work Force ◽  
The United States ◽  
Test Case ◽  
County Level ◽  
Care Providers ◽  
Urologic Cancers ◽  
The Impact

Purpose The surgical work force distribution at the county level varies widely across the United States, and the impact of differential access on cancer outcomes is unclear. We used urologists as a test case because they are the first care providers for urologic cancers, can easily be identified from available data sources, and are unevenly distributed throughout the country. The goal of this study was to determine the effect of increasing urologist density on local prostate, bladder, and kidney cancer mortality. Patients and Methods Using county-level data from the Area Resource File, US Census, National Cancer Institute, and Centers for Disease Control, regression models were built for prostate, bladder, and kidney cancer mortality, controlling for categorized urologist density, county demographics, socioeconomic factors, and preexisting health care infrastructure. Results For each of the three cancers, there was a statistically significant cancer-specific mortality reduction associated with counties that had more than zero urologists (16% to 22% reduction for prostate cancer, 17% to 20% reduction for bladder cancer, and 8% to 14% reduction for kidney cancer with increasing urologist density) relative to zero urologists. However, increasing density greater than two urologists per 100,000 people had no statistically significant impact on mortality for any of the tumors studied. Conclusion The presence of a urologist is associated with lower mortality for urologic cancers in that county, but increasing urologist density does not yield further improvements. Therefore, a nuanced and geographically aware policy toward the size and distribution of the future work force is most likely to provide the greatest population-level improvement in cancer mortality outcomes.

Does parental migration have any impact on nutritional disorders among left-behind children in Bangladesh?

2018 ◽  
Vol 22 (1) ◽  
pp. 95-103 ◽  
Author(s):  
M Mofizul Islam ◽  
Md Nuruzzaman Khan ◽  
Md Nazrul Islam Mondal
Keyword(s):  
Negative Impact ◽  
Population Level ◽  
Educational Status ◽  
Household Wealth ◽  
Wealth Status ◽  
Cross Sectional ◽  
Logistic Regression Models ◽  
Parental Migration ◽  
Left Behind ◽  
The Impact

AbstractObjectiveRates of migration have increased substantially in recent years and so has the number of left-behind children (LBC). We investigated the impact of parental migration on nutritional disorders of LBC in Bangladesh.DesignWe analysed data from the nationally representative cross-sectional Multiple Indicator Cluster Survey 2012–2013. Child stunting, wasting and underweight were used as measures of nutritional disorders. Descriptive statistics were used to describe characteristics of the respondents and to compare nutritional outcomes based on status of parental migration. Multivariate logistic regression models were used to examine the associations between parental migration and child nutritional disorders.SettingBangladesh.ParticipantsData of 23 402 children (aged <5 years), their parents and households.ResultsIn the unadjusted models, parental migration was found significantly protective for stunting, wasting and underweight – both separately and jointly. After potential confounders were controlled for, no difference was found between LBC and non-LBC in any of these three nutritional outcome measures. Household wealth status and maternal educational status were found to significantly influence the nutritional development of the children.ConclusionsAt the population level there is no negative impact of parental migration on stunting, wasting and underweight of LBC in Bangladesh. Remittance from parental migration might enhance affordability of better foods, health care and supplies for a cleaner environment. This affordability is crucial for the poorest section of the society.

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