Examining cancer screening disparities by race/ethnicity and insurance groups: A comparison of 2008 and 2018 National Health Interview Survey (NHIS) data in the United States.

BACKGROUND: Pervasive differences in cancer screening among race/ethnicity and insurance groups presents a challenge to achieving equitable healthcare access and health outcomes. However, the change in the magnitude of cancer screening disparities over time has not been thoroughly examined using recent public health survey data. METHODS: A retrospective cross-sectional analysis of the 2008 and 2018 National Health Interview Survey (NHIS) database focused on breast, cervical, and colorectal cancer screening rates among race/ethnicity and insurance groups. Multivariable logistic regression models were used to assess the relationship between cancer screening rates, race/ethnicity, and insurance coverage, and to quantify the changes in disparities in 2008 and 2018, adjusting for potential confounders. RESULTS: Colorectal cancer screening rates increased for all groups, but cervical and mammogram rates remained stagnant for specific groups. Non-Hispanic Asians continued to report consistently lower odds of receiving cervical tests (OR: 0.42, 95% CI: 0.32-0.55, p<0.001) and colorectal cancer screening (OR: 0.55, 95% CI: 0.42-0.72, p<0.001) compared to non-Hispanic Whites in 2018, despite significant improvements since 2008. Non-Hispanic Blacks continued to report higher odds of recent cervical cancer screening (OR: 1.98, 95% CI: 1.47-2.68, p<0.001) and mammograms (OR: 1.32, 95% CI: 1.02-1.71, p<0.05) than non-Hispanic Whites in 2018, consistent with higher odds observed in 2008. Hispanic individuals reported improved colorectal cancer screening over time, with no significant difference compared to non-Hispanics Whites in 2018, despite reporting lower odds in 2008. The uninsured status was associated with significantly lower odds of cancer screening than private insurance for all three cancers in 2008 and 2018. CONCLUSION: Despite an overall increase in breast and colorectal cancer screening rates between 2008 and 2018, persistent racial/ethnic and insurance disparities exist among race/ethnicity and insurance groups. These findings highlight the importance of addressing underlying factors contributing to disparities among underserved populations and developing corresponding interventions.

Incidence density of hyperuricemia and association between metabolism-related predisposing risk factors and serum urate in Chinese adults: a cohort study.

Background: Evidence regarding the association between metabolism-related indicators and serum urate (SU) is limited. We aimed to obtain the incidence density of hyperuricemia and to explore the association between metabolism-related predisposing risk factors and SU. Methods: A total of 48,979 Chinese adults from the Beijing Physical Examination Center were included in the study. The partial least squares path model was used to explore the relationship between SU and metabolism-related risk factors. The generalized additive model was used for smooth curve fitting, showing the sex-specific associations of SU at follow-up with baseline fasting blood glucose (FBG) concentrations and age. Results: The incidence density of hyperuricemia was 78/1000 person-years. Baseline SU, age, sex, obesity, FBG, and lipid metabolism were significantly associated with SU at follow-up (all P values <0.05). Non-linear relationships were found between the baseline FBG concentrations and SU at follow-up, while U-shaped associations were observed between baseline age and SU at follow-up. Conclusions: The SU concentration is associated with several metabolism-related risk factors such as obesity and FBG. Recognition of these associations will aid in a deeper understanding of the multifaceted nature of SU regulation.

The public-private partnerships in healthcare sector in China.

This manuscript is a narrative review on experience in the healthcare public-private partnerships (PPP) field project in China. The PPP model allows healthcare officials to share the risk of building new facilities with the private sector. The objective of this study is to evaluate and to review the PPP of healthcare sector in China, and to investigate the critical success factors and best practice of PPP. We adapted the PPP evaluation framework of the World Bank Independent Evaluation Group as our conceptual framework to summarize the literatures. The current study systematically reviewed the evolution and current status of public and private hospitals development in China, and to investigate factors related to the successful and less successful deployment and performance of PPP in the healthcare sector of China, and to develop best practice models of PPP among hospitals of China. We found that the PPP organizations providing finance and political risk coverage, thus enabling specific PPP transactions to reach financial closure-potentially setting demonstration effects. Such PPPs may then contribute to improving access to infrastructure and social services, which drives economic growth and other optimal outcomes.

Performance of Deep-Learning Solutions on Lung Nodule Malignancy Classification: A Systematic Review.

OBJECTIVE: For several years, computer technology has been utilized to diagnose lung nodules. When compared to traditional machine learning methods for image processing, deep-learning methods can improve the accuracy of lung nodule diagnosis by avoiding the laborious pre-processing step of the picture (extraction of fake features, etc.). Our goal is to investigate how well deep-learning approaches classify lung nodule malignancy. METHOD: We evaluated the performance of deep-learning methods on lung nodule malignancy classification via a systematic literature search. We conducted searches for appropriate articles in the PubMed and ISI Web of Science databases and chose those that employed deep learning to classify or predict lung nodule malignancy for our investigation. The figures were plotted, and the data were extracted using SAS version 9.4 and Microsoft Excel 2010, respectively. RESULTS: Sixteen studies that met the criteria were included in this study. The articles classified or predicted pulmonary nodule malignancy using classification and summarization, using convolutional neural network (CNN), autoencoder (AE), and deep belief network (DBN). The AUC of deep-learning models is typically greater than 90% in articles. It demonstrated that deep learning performed well in the diagnosis and forecasting of lung nodules. CONCLUSION: It is a thorough analysis of the most recent advancements in lung nodule deep-learning technologies. The advancement of image processing techniques, traditional machine learning techniques, deep-learning techniques, and other techniques have all been applied to the technology for pulmonary nodule diagnosis. Although the deep-learning model has demonstrated distinct advantages in the detection of pulmonary nodules, it also carries significant drawbacks that warrant additional research.

Relationship between socioeconomic status and cognitive ability among Chinese older adults: the moderating role of social support.

BACKGROUND: Understanding the causes and pathways of cognitive decline among older populations is of great importance in China. This study aims to examine whether the discrepancy in socioeconomic status (SES) makes a difference to the cognitive ability among Chinese older adults, and to disentangle the moderating role of different types of social support in the process in which SES influences cognition. METHODS: We utilized a nationally representative sample from the 2018 Chinese Longitudinal Healthy Longevity Survey. A cumulative SES score was constructed to measure the combined effect of different socioeconomic statuses on the cognitive ability of the elderly. We further examined the moderating role of two types of social support, including emotional support, and financial support. Hierarchical regression analysis was applied to test the direct effect of SES on cognitive ability, and to investigate the moderating role of social support on the association of the SES with the dependent variables. RESULTS: The results showed that the higher SES of older adults was significantly associated with better cognitive ability (ß = 0.52, p < 0.001) after controlling for age, sex, marital status, living region, Hukou, health insurance, lifestyle factors, and physical health status. Emotional support and financial support were moderated the relationship between SES score and cognitive ability. CONCLUSION: Our results reveal the importance of considering social support in buffering the effects of SES and the associated cognitive ability for aging populations. It highlights the importance of narrowing the socioeconomic gap among the elderly. Policymakers should consider promoting social support to improve the cognitive ability among older adults.

The COVID-19 vaccination decision-making preferences of elderly people: a discrete choice experiment.

COVID-19 is a continuing threat to global public health security. For elderly people, timely and effective vaccination reduces infection rates in this group and safeguards their health. This paper adopted an offline Discrete Choice Experiment (DCE) to research the preference for COVID-19 vaccination amongst Chinese adults aged 50 years and above. Through multinomial logistic regression analysis, our DCE leverages five attributes-the risk of adverse reactions, protective duration, injection doses, injection period, and effectiveness-each of which is split into three to four levels. The risk of adverse reaction and the protective duration were demonstrated to be determinants of vaccination preference. Moreover, it was found that socio demographic factors like region, self-health assessment and the number of vaccinated household members can strengthen or weaken the effects of vaccine attributes. In conclusion, the preferences of the elderly population should be considered when developing COVID-19 vaccination programs for this population in China. Accordingly, the results may provide useful information for policymakers to develop tailored, effectively vaccination strategies.

Genetic modification effects of physical frailty on the morbidity of mental disorders in the UK Biobank.

Objectives: Depression and anxiety are two major categories of mental disorders that are highly prevalent in the general population. This study aims to explore the genetic modification effects of physical frailty on the morbidity of mental disorders.Methods: Using data from UK Biobank, we calculate genetic risk scores for depression, anxiety and mental disorders based on 37/44 single-nucleotide polymorphisms (SNPs) of Major Depressive Disorder (MDD) and 9/10 SNPs of anxiety. Frailty status was defined by a modified version of the frailty phenotype based on five individual components. Cox proportional hazard models were used to estimate the hazard ratio (HR) and 95% confidence interval (CI) of depression and anxiety risk among groups with different frailty status.Results: Of 267,755 participants in UK Biobank, 4,905 (2%) were considered frail, 98,907 (37%) pre-frail and 163,943 (61%) not frail. Compared with the non-frail group, the pre-frail group (HR = 1.53; [95% CI:1.47-1.61]), and frail group (HR = 2.75; [95% CI:2.46-3.07]) were significantly associated with increased risk of depression. Per 1-number increment in frailty component counts were significantly associated with increased risk of mental disorders. In each genetic risk score (GRS) strata, people with pre-frailty and frailty suffered higher risks of mental disorders than the non-frail group.Conclusion: Our results indicate that physical frailty plays an important role in the incidence of mental disorders, even after adjustments for covariates, and patients with genetic individual differences are also affected. Therefore, it is crucial that while diagnosing mental disorders, professionals pay closer attention to those patients who present symptoms of frailty.

Exposome approach for identifying modifiable factors for the prevention of colorectal cancer.

Previous studies have shown certain exposure factors (such as lifestyle and metabolism) are associated with colorectal cancer (CRC) events. However, the application of the exposome theoretical frame and the extent to which the exposome domain can modulate the risk of CRC remain unknown. Our study aimed to construct valid exposome measurements and examine the relationship between exposome counts and the risk of CRC. This study included 335,370 individuals in the UK Biobank. We used exploratory factor analysis to identify a valid construct of exposome factors. We then summed the exposome counts within each domain. Cox proportional hazard models were used to estimate the hazard ratios and 95% confidence intervals of CRC risk related to the exposome factors and counts. During an 8.69 year median follow-up, 10,702 CRC cases were identified. Five domains were extracted from 12 variables, including ecosystem, lifestyle, tobacco and alcohol use, social economics, and social support. The Cox model results showed that the ecosystem was positively related to the reduced CRC risk (HR = 0.970; 95% CI 0.952-0.989). Similar results were also found among the domains of healthy lifestyles (HR = 0. 889; 95% CI 0.871-0.907), and no tobacco and alcohol use (HR = 0.892; 95% CI 0.876-0.909). The disadvantageous social economic (HR = 1.081; 95% CI 1.058-1.105) and insufficient social support domains (HR = 1.036; 95% CI 1.017-1.056) were associated with an increased risk of CRC. Similar risk trends were also observed across the exposome count groups with CRC incidence. Our findings suggest that certain exposure domains are related to the incidence of CRC. Ecosystem, lifestyle, and social factors can be incorporated into prediction models to identify individuals at high risk of CRC.

Sleep pattern, healthy lifestyle and colorectal cancer incidence.

Researchers have identified an association between lifestyle factors and colorectal cancer (CRC) risk. This study examined the relationship between sleep patterns and CRC events. 392,252 individuals were sampled from the UK Biobank. Chronotype, sleep duration, insomnia, snoring, and excessive daytime sleepiness were combined to measure a healthy sleep score. A number of healthy sleep factors were defined, along with factors for healthy lifestyle scores. Using Cox proportional hazards regression, computed hazard ratios (HRs) were used to examine the associations between sleep patterns, healthy lifestyles, and the incidence of CRC. Healthy sleep scores were inversely associated with CRC events. The HRs for CRC were 0.90 (95% CI, 0.88-0.92) and 0.95 (95% CI, 0.92-0.98) for a 1-point healthy sleep score increase among males and females. When analyzing sleep components, sleeping 7-8 h/day, no frequent insomnia, no snoring, and no frequent daytime sleepiness were independently associated with a 9%, 14%, 8%, and 14% lower risk of CRC, respectively, whilst healthy lifestyle scores were inversely associated with CRC incidence across all models. Sleep pattern and lifestyle are significantly correlated with CRC risk. The healthier the subject's lifestyle and sleep pattern, the lower their CRC risk.

The Effect of Built Environment on Physical Health and Mental Health of Adults: A Nationwide Cross-Sectional Study in China.

At present, there is a lack of research examining the relationships between the built environment and health status from a social epidemiological perspective. With this in mind, the present study aimed to explore the construct validity of housing/neighborhood conditions and evaluate the associations between the built environment and self-rated health among Chinese residents. To conduct the analysis, data from 4906 participants were derived from the 2016 China Labor-force Dynamics Survey (CLDS). Specifically, we used exploratory factor analysis to identify construct of housing/neighborhood factors and performed principal component regression (PCR) to assess the relationship between the built environment and both self-rated physical health and mental health. This process identified five common factors that corresponded to the built environment, including housing affordability, housing quality, neighborhood services, neighborhood physical environment, and perceived environment. The regression results suggested that housing affordability was negatively related to health status. Meanwhile, the services, physical environment, and perceived environment of neighborhoods were related to positive health outcomes. The influence of housing on health exhibits group heterogeneity: respondents in the 41 to 65 age group were most vulnerable to poor built environments. Whilst the results indicated that housing factors and neighborhood conditions were related to health outcomes, their influence varied across different age groups. Future interventions should be intentionally designed to target housing affordability and neighborhood factors, which may include the provision of housing assistance programs and planning layouts.

Importance of ideal cardiovascular health metrics in the risk of colorectal cancer among people aged 50 years or older: a UK Biobank cohort study.

OBJECTIVE: To explore the correlation between the ideal cardiovascular health metrics (ICVHMs) and the incidence of colorectal cancer (CRC) among people aged 50 years or older. DESIGN: Prospective cohort study. SETTING: The UK Biobank, a prospective cohort of middle-aged participants recruited between 2006 and 2010. PARTICIPANTS: The study included 342 226 participants from the UK Biobank aged 50 years or older without prevalent cancer. EXPOSURE: The ICVHMs consist of four behavioural factors (abstinence from smoking, ideal body mass index (BMI), physical activity at goal and consumption of healthy diet) and three cardiometabolic factors (untreated total cholesterol <200 mg/dL, untreated blood pressure <120/80 mm Hg and untreated fasting plasma glucose <100 mg/dL). MAIN OUTCOMES: The outcome was ascertained by linkage to cancer and death registries using the International Classification of Diseases, Tenth codes C18-C20. RESULTS: During a median follow-up time of 8.72 years, 3060 CRC cases were identified. Compared with the reference (participants with ICVHMs ≤2), the multivariable-adjusted HRs for subgroups with 3, 4, 5 and ≥6 ICVHM factors were 0.98 (95% CI 0.85 to 1.12), 0.90 (95% CI 0.77 to 1.02), 0.85 (95% CI 0.71 to 0.98) and 0.69 (95% CI 0.48 to 0.90), respectively. Among the seven ICVHM factors, lower BMI, healthier diet and ideal fasting plasma glucose were significantly associated with lower risk of CRC (HR: 0.86, 95% CI 0.78 to 0.95; HR: 0.92, 95% CI 0.84 to 0.99; HR: 0.90, 95% CI 0.80 to 0.99). CONCLUSIONS: Adherence to the ICVHMs was associated with a lower risk of CRC among people aged 50 years or older. Among the seven ICVHM factors, BMI, diet and fasting plasma glucose played a more critical role in the prevention of CRC. These findings imply that adherence to ICVHMs should be encouraged to reduce the burden of cardiovascular disease as well as CRC.

Longitudinal study of the earliest pilot of tiered healthcare system reforms in China: Will the new type of chronic disease management be effective?

BACKGROUND: In 2016, the tiered healthcare model featuring "specialists + general practitioners + health managers" in Xiamen was recognized by the Medical Reform Office of State Council and was promoted as a model to replace hospital-centric care with community-based care. This study evaluated the impact of the Xiamen's tiered healthcare system reform on health outcomes and healthcare spending among chronic disease patients. METHODS: Data were derived from Xiamen's electronic health record (EHR) and medical claims systems. The sample included 154,651 individuals with hypertension and 50,722 individuals with diabetes from Xiamen between 2012 and 2016. The dependent variables included rates of disease under control and total treatment costs. Patients were grouped by the types of chronic disease management: precision management, regular management, or without management. Kaplan-Meier, Cox survival analysis and PSM + DID method (Propensity score matching and difference-in-difference method) were used to compare the management outcomes by group. FINDINGS: The precision management group showed better clinical quality performance than the regular management group. Under-control disease rates in the precision management group showed a continuous improvement trend, while the regular management group showed a ceiling effect after ten months. Under-control rates in the precision management group increased over 40% for hypertension and over 30% for diabetes, higher than that increases found in the regular management group. Reform was also associated with consistent reductions in annual per capita total treatment costs across groups. The cost-savings in the precision management group between 2014 and 2016 was 381 Chinese yuan (CNY) for hypertension and 1117 CNY for diabetes, compared with the group without management. INTERPRETATION: The results in this study demonstrated the associations between tiered healthcare system reform and better clinical quality performance and improved treatment cost-saving. Developing methods to promote the policy and increase implementation are also important aspects of healthcare reform.

The convergence of racial and income disparities in health insurance coverage in the United States.

OBJECTIVE: This study applied the vulnerability framework and examined the combined effect of race and income on health insurance coverage in the US. DATA SOURCE: The household component of the US Medical Expenditure Panel Survey (MEPS-HC) of 2017 was used for the study. STUDY DESIGN: Logistic regression models were used to estimate the associations between insurance coverage status and vulnerability measure, comparing insured with uninsured or insured for part of the year, insured for part of the year only, and uninsured only, respectively. DATA COLLECTION/EXTRACTION METHODS: We constructed a vulnerability measure that reflects the convergence of predisposing (race/ethnicity), enabling (income), and need (self-perceived health status) attributes of risk. PRINCIPAL FINDINGS: While income was a significant predictor of health insurance coverage (a difference of 6.1-7.2% between high- and low-income Americans), race/ethnicity was independently associated with lack of insurance. The combined effect of income and race on insurance coverage was devastating as low-income minorities with bad health had 68% less odds of being insured than high-income Whites with good health. CONCLUSION: Results of the study could assist policymakers in targeting limited resources on subpopulations likely most in need of assistance for insurance coverage. Policymakers should target insurance coverage for the most vulnerable subpopulation, i.e., those who have low income and poor health as well as are racial/ethnic minorities.

Housing and Adult Health: Evidence from Chinese General Social Survey (CGSS).

Housing is one of the social determinants of health and the most basic survival needs of human beings. Many studies have preliminarily confirmed that housing factors can influence residents' health. The aims of this study were: to evaluate the housing factors associated with self-rated health and mental health among Chinese residents; to explore the regional heterogeneity of the impact of housing on health; and to assess the effects of housing on health among different age groups. Data was derived from the Chinese General Social Survey (CGSS). Housing factors were analyzed along six dimensions: housing property, living space, number of living people, number of houses, living region and housing price. Self-rated health and mental health were used to measure health outcomes. Multivariate ordered logistic regression was performed to assess the relationship between housing and health. The living space, living region and housing price was significantly associated with self-rated health. The number of living people living region and housing price were related to mental health. The influence of housing factors on health were more pronounced among residents living in eastern and central area and among the middle-aged group (41-65). Present findings support the notion that housing factors were related to health outcomes. Future studies may focus on the impact of interventions that target on these factors, and the impact of housing on health among special groups such as migrant population and low-and-middle income families.

Application of the Internet Platform in Monitoring Chinese Public Attention to the Outbreak of COVID-19.

Objectives: The internet data is an essential tool for reflecting public attention to hot issues. This study aimed to use the Baidu Index (BDI) and Sina Micro Index (SMI) to confirm correlation between COVID-19 case data and Chinese online data (public attention). This could verify the effect of online data on early warning of public health events, which will enable us to respond in a more timely and effective manner. Methods: Spearman correlation was used to check the consistency of BDI and SMI. Time lag cross-correlation analysis of BDI, SMI and six case-related indicators and multiple linear regression prediction were performed to explore the correlation between public concern and the actual epidemic. Results: The public's usage trend of the Baidu search engine and Sina Weibo was consistent during the COVID-19 outbreak. BDI, SMI and COVID-19 indicators had significant advance or lag effects, among which SMI and six indicators all had advance effects while BDI only had advance effects with new confirmed cases and new death cases. But compared with the SMI, the BDI was more closely related to the epidemic severity. Notably, the prediction model constructed by BDI and SMI can well fit new confirmed cases and new death cases. Conclusions: The confirmed associations between the public's attention to the outbreak of COVID and the trend of epidemic outbreaks implied valuable insights into effective mechanisms of crisis response. In response to public health emergencies, people can through the information recommendation functions of social media and search engines (such as Weibo hot search and Baidu homepage recommendation) to raise awareness of available disease prevention and treatment, health services, and policy change.

DNA Nanomachines for Identifying Cancer Biomarkers in Body Fluids and Cells.

Identifying molecular biomarkers promises to significantly improve the accuracy in cancer diagnosis at its early stage. DNA nanomachines, which are designable and switchable nanostructures made of DNA, show broad potential to detect tumor biomarkers with noninvasive, inexpensive, highly sensitive, and highly specific advantages. This Feature summarizes the recent DNA nanomachine-based platforms for the early detection of cancer biomarkers, both from body fluids and in cells.

Dietary Approaches to Stop Hypertension (DASH) Score and Its Association with Sleep Quality in a National Survey of Middle-Aged and Older Men and Women.

: Complex processes appear to link sleep duration and quality with dietary patterns. Numerous studies show healthful benefits of the Dietary Approaches to Stop Hypertension (DASH) diet, but few have examined its association with sleep duration or quality. The current study tested cross-sectional associations of DASH diet quality score with sleep quality among adults. Analyses of participants were from the 2005-2008 wave of the National Health and Nutrition Examination Surveys (n = 3941 adults ≥ 30 years of age, complete data). We performed sex- and age group-stratified multiple OLS regression analyses with DASH total score and components as main predictors and sleep quality as main outcomes, adjusting sequentially for socio-demographic, behavioral and health-related factors. Sex and age differences in associations of DASH with sleep quality, adjusting for covariates, were also examined by incorporating two-way interaction terms between sex/age and the DASH score in each unstratified model. We found that the DASH diet score was inversely related to poor sleep-related daytime dysfunction adjusted by age, sex, demographic and socio-economic factors. Some sex-specific associations were detected between DASH diet component scores and sleep quality. Notably, the potassium DASH component was inversely associated with Factor 1 ("sleepiness and sleep disturbance") among women. The fiber DASH component was associated with better sleep quality and inversely related to Factor 2 ("sleep-related daytime dysfunction") in younger subjects. This study indicates health benefits of the DASH diet for sleep duration and quality. Future longitudinal studies and randomized placebo-controlled trials are required to ascertain protective effects.

Data mining-based model and risk prediction of colorectal cancer by using secondary health data: A systematic review.

OBJECTIVE: Prevention and early detection of colorectal cancer (CRC) can increase the chances of successful treatment and reduce burden. Various data mining technologies have been utilized to strengthen the early detection of CRC in primary care. Evidence synthesis on the model's effectiveness is scant. This systematic review synthesizes studies that examine the effect of data mining on improving risk prediction of CRC. METHODS: The PRISMA framework guided the conduct of this study. We obtained papers via PubMed, Cochrane Library, EMBASE and Google Scholar. Quality appraisal was performed using Downs and Black's quality checklist. To evaluate the performance of included models, the values of specificity and sensitivity were comparted, the values of area under the curve (AUC) were plotted, and the median of overall AUC of included studies was computed. RESULTS: A total of 316 studies were reviewed for full text. Seven articles were included. Included studies implement techniques including artificial neural networks, Bayesian networks and decision trees. Six articles reported the overall model accuracy. Overall, the median AUC is 0.8243 [interquartile range (IQR): 0.8050-0.8886]. In the two articles that reported comparison results with traditional models, the data mining method performed better than the traditional models, with the best AUC improvement of 10.7%. CONCLUSIONS: The adoption of data mining technologies for CRC detection is at an early stage. Limited numbers of included articles and heterogeneity of those studies implied that more rigorous research is expected to further investigate the techniques' effects.

Cancer screening among racial/ethnic groups in health centers.

BACKGROUND: Underserved and low-income population are placed at a disadvantage for receiving necessary cancer screenings. This study aims to measure the rates of receiving three types of cancer screening services, Pap test, mammogram and colorectal cancer screening, among patients seen at U.S. health centers (HCs) to investigate if cancer screening among patients varies by race/ethnicity. METHODS: We analyzed data from the 2014 U.S. Health Center Patient Survey, and included samples age 21 and above. We examined three cancer screening indicators as our dependent variables including cervical, breast, and colorectal cancer screening. Logistic regressions were used to assess the racial/ethnic disparities on cancer screening, while controlling for potentially confounding factors. RESULTS: The rates of receiving three types of cancer screening were comparable and even higher among HC patients than those for the U.S. general population. Both bivariate and multivariate results showed there were racial/ethnic differences in the likelihood of receiving cancer screening services. However, the differences did not favor non-Hispanic Whites. African Americans had higher odds than Whites (OR: 1.92, 95% CI: 1.44-2.55, p < 0.001) of receiving Pap tests. Similar results were also found in measures of the receipt of mammogram (OR = 1.96, 95% CI: 1.46-2.64, P < 0.001) and colorectal cancer screening (OR = 1.28, 95% CI: 1.02-1.60, p < 0.05). CONCLUSION: The current study presents U.S. nationally representative estimates and imply that HCs are helping fulfill an important role as a health care safety-net in reducing racial/ethnic disparities in the delivery of cancer screening services.

The patient-centered oncology care on health care utilization and cost: A systematic review and meta-analysis.

BACKGROUND: Optimal cancer care entails coordination among multiple providers and continued follow-up and surveillance over time. The patient-centered care brings opportunities to improve the delivery of cancer care. The adoption of patient-centered oncology care (PCOC) is in its infancy. Evidence synthesis on the model's effectiveness is scant. PURPOSES: This is the first systemic review and meta-analysis on associations of PCOC with cancer patients' adverse health care utilization, cost, patient satisfaction, and quality of care. METHODS: Our study was guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) framework. Quality appraisal was performed using Downs and Black's quality checklist. Study-level effect sizes of adverse health care utilization were computed using Cohen's d and summarized using forest plots. Funnel plots were constructed to examine publication bias. RESULTS: Of 334 studies that were reviewed, 10 met eligibility criteria and were included into the final analysis. Many included studies implemented almost all six of patient-centered care core attributes, plus three additional attributes that specifically addressed cancer patients' needs, including triage pathways, standardized and evidence-based symptom management, as well as support patient navigation. PCOC patients had lower utilization of inpatient care (standardized means difference [SMD] = -0.027, p = .049). Overall positive effect of PCOC on emergency department use was small and not significant (SMD = -0.023, p = .103). With regard to cost and quality of care, our narrative summaries showed an overall positive direction, though we found limitations in individual study quality that precluded a meta-analysis. PUBLIC IMPLICATION: The results showed that it is possible to utilize patient-centered model to support best practice of cancer care. Early evidence shows that the PCOC model has potential to improve health care utilization, cost, and quality of care, but limited numbers of included articles and heterogeneity of those studies implied that more rigorous research is expected to further investigate the model's effects.