scholarly journals Retrospective Analysis of COVID-19 Pandemic Impact on Breast Cancer Screening Rates in Northwest Indiana

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Daniel L. Green ◽  
Amy Han
Keyword(s):  
Cancer Screening ◽  
Diagnostic Testing ◽  
Healthcare Delivery ◽  
Baseline Period ◽  
Predominantly Black ◽  
Large Hospital ◽  
Level Data ◽  
Average Patient ◽  
Gary Indiana ◽  
Black Populations

Background: Few changes to healthcare delivery during the COVID-19 pandemic altered pre-pandemic diagnostic testing as much as those made to cancer screening. Several studies show that screening volumes decreased by as much as 80% across multiple modalities and cancer types in the spring of 2020. These studies examined large hospital systems in the American East and West, but communities with predominantly Black populations like Gary, Indiana, have been absent from this research. Methods: Our study captures how the COVID-19 pandemic affected access to diagnostic screening for cancerous and precancerous breast lesions through mammography using patient-level data. “Hospital A” provided data from 17,973 mammography encounters that occurred between March 2019 and June 2021. Screening volumes from the eight-week period from March 23rd and May 17th in 2020, the period elective procedures were suspended, was compared to three other distinct periods: the previous 8-week period, the next 8-week period, and the same 8-week period from 2019. Results: From the 17,973 encounters, the average patient age was 61.7 (SD 11.4) years, 61.0% of patients paid with Medicare or Medicaid, and 66.0% of patients identified as Black. Despite performing a weekly average of 190 (12.3) mammograms during the 2019 baseline period and 158 (16.1) mammograms in the eight weeks preceding the COVID-19 pandemic, the weekly average fell to 13 (22.4) mammograms during the study period with zero occurring in a four-week stretch. Fortunately, volume returned sharply to near pre-pandemic levels in the eight weeks following the study period with 139 (18.9) average weekly mammograms. Conclusion: Despite a 93% year-over-year decrease in mammography during the height of the pandemic, volume returned in the summer of 2020. Concerning, however, is that average monthly volume (582 (88.5) mammograms) in the first six months of 2021 remains 22.1% lower than 2019 numbers (747 (66.7) mammograms).

Ensuring privacy and security of genomic data and functionalities

2019 ◽  
Vol 21 (2) ◽  
pp. 511-526 ◽  
Author(s):  
Abukari Mohammed Yakubu ◽  
Yi-Ping Phoebe Chen
Keyword(s):  
Association Studies ◽  
Diagnostic Testing ◽  
Healthcare Delivery ◽  
Genomic Data ◽  
Security And Privacy ◽  
Genome Wide Association Studies ◽  
Privacy And Security ◽  
Security Issues ◽  
Genomic Privacy ◽  
Privacy Problem

Abstract In recent times, the reduced cost of DNA sequencing has resulted in a plethora of genomic data that is being used to advance biomedical research and improve clinical procedures and healthcare delivery. These advances are revolutionizing areas in genome-wide association studies (GWASs), diagnostic testing, personalized medicine and drug discovery. This, however, comes with security and privacy challenges as the human genome is sensitive in nature and uniquely identifies an individual. In this article, we discuss the genome privacy problem and review relevant privacy attacks, classified into identity tracing, attribute disclosure and completion attacks, which have been used to breach the privacy of an individual. We then classify state-of-the-art genomic privacy-preserving solutions based on their application and computational domains (genomic aggregation, GWASs and statistical analysis, sequence comparison and genetic testing) that have been proposed to mitigate these attacks and compare them in terms of their underlining cryptographic primitives, security goals and complexities—computation and transmission overheads. Finally, we identify and discuss the open issues, research challenges and future directions in the field of genomic privacy. We believe this article will provide researchers with the current trends and insights on the importance and challenges of privacy and security issues in the area of genomics.

scholarly journals Analysis of COVID-19 Case Demographics in Gary, Indiana

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Yazan Al-Tarshan ◽  
Maryam Sabir ◽  
Cameron Snapp ◽  
Martin Brown ◽  
Roland Walker ◽  
...  
Keyword(s):  
Low Income ◽  
Household Income ◽  
Black Population ◽  
Health Department ◽  
Poverty Line ◽  
Median Household Income ◽  
Predominantly Black ◽  
Chi Square ◽  
Gary Indiana ◽  
Zip Code

Background and Hypothesis  It has been reported in several recent studies that health disparities associated with COVID-19 infection r are prevalent in Black and impoverished populations. The contribution of multiple causes to these disparities is still not completely elucidated. Gary, Indiana has a large Black population (80%), high number of residents living below the poverty line (34%), and high unemployment rate (20%). We hypothesized that Black individuals in Gary have a higher rate of positive cases, hospitalizations, and deaths than non-Black individuals. Also, we hypothesized that (median household income measured by the zip code) is negatively correlated with COVID-19 positive cases, hospitalizations, and deaths.     Methods  In collaboration with the Gary Health Department, we analyzed data on all positive cases in the city from 06/16/2020 through 06/07/2021(totally 5149 cases). We compared this data to the data from 03/16/2020 through 06/16/2020 (totally 724 cases) that we analyzed previously. Data was de-identified and included age, race, ethnicity, and zip code.  The data was analyzed using Pearson's chi-square test and regression analysis.    Results   When compared to the non-Black population in Gary age and population-adjusted rates of hospitalizations and deaths in the Black population are 3-fold (p<9.385E-11) and 2-fold (p<0.0171) higher, respectively. Surprisingly, the non-Black population had a higher infection rate than the Black population (p<2.69E-09). Median household income of a zip code is negatively correlated with COVID-19 hospitalizations in that zip code (R2=0.6345, p=0.03), but is does not affect the .rates of infections and deaths.     Conclusion   Our data show that in Gary, there is a clear health disparity of both income and race, specifically in the context of COVID-19. IUSMNW and Gary health officials can collaborate and utilize this data to reallocate resources to the highly populated, low income, and predominantly Black neighborhoods.  

OEN: Multi-center, international, real-world evidence studies performed using health records without data pooling—The use of a common data model and shared analytical methods.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e13554-e13554
Author(s):  
Bethany Levick ◽  
Sue Cheeseman ◽  
Eun Ji Nam ◽  
Haewon Doh ◽  
Subin Lim ◽  
...  
Keyword(s):  
Real World ◽  
Data Model ◽  
Clinical Care ◽  
Common Data Model ◽  
Local Data ◽  
Large Hospital ◽  
Patient Level Data ◽  
Patient Level ◽  
Real World Evidence ◽  
Level Data

e13554 Background: The value of real-world evidence derived from the care of patients managed outside the context of clinical trials is well recognised. However, the ability to link data from multiple centres, especially those from different countries, is complicated by complex legal and information governance differences. The Oncology Evidence Network is a collaboration of large hospital centres, with strong clinical informatics capabilities in six countries in Europe and Asia working with the support of an industrial partner to provide high quality, real world data reflecting routine clinical care. We have developed an efficient workflow based on a study-specific common data model (CDM) clinically validated at each site and analysed with a single analysis script, which embeds a set of data quality rules. Local implementation allows each centre to generate analytical outputs aligned across the different sites without the need for any patient level data to leave the participating site. This approach has been designed and tested in Epithelial Ovarian Cancer (EOC) patients. Methods: A CDM was agreed using expert advisors from each centre. Clinical alignment was achieved through iterative assessment of clinical vignettes, to ensure common definitions of clinical assessment, prognosis, and treatment algorithms in EOC patients. A data guide detailing variable level derivations and validation rules, general data coding principles, and conversions/codes from international coding systems was developed. The analysis scripts were implemented as a bespoke package (OpenOvary) in R. The package includes functions to validate the data against the CDM, and generate a standard output including tables, numerical summaries and Kaplan-Meier analysis of progression and overall survival. Results: 2,925 patient records from 6 centres across 6 countries were included in the study with 27 key data items curated by each centre. Treatment data is available detailing relevant surgical procedures and their outcomes, and regimens of SACT throughout patients’ care from diagnosis to death. Data completeness was generally high for key data items, with missing data ranging from 0-16% for FIGO stage at diagnosis and 0-14% for tumour morphology. The CDM and R script will be made publicly available for other centres to adopt and facilitate analysis of their local data. Conclusions: This collaboration has brought together a substantial body of data describing the care and outcomes for EOC patients. A CDM and flexible shared analysis approach enabled unified analysis and reporting whilst avoiding the transfer of patient level data and its pooling into a common database. The process of clinical and data alignment has generated a replicable model for rapid extension to other study centres to join the EOC study, or application to other disease areas.

scholarly journals Time to Diagnostic Testing After a Positive Colorectal Cancer Screening Test

JAMA ◽  
2017 ◽  
Vol 318 (5) ◽  
pp. 483 ◽  
Author(s):  
Chyke A. Doubeni ◽  
Douglas A. Corley ◽  
Theodore R. Levin
Keyword(s):  
Colorectal Cancer ◽  
Cancer Screening ◽  
Colorectal Cancer Screening ◽  
Screening Test ◽  
Diagnostic Testing ◽  
Cancer Screening Test

scholarly journals Examining the Effectiveness of Provider Incentives to Increase CRC Screening Uptake in Neighborhood Healthcare: A California Federally Qualified Health Center

2020 ◽  
Vol 21 (6) ◽  
pp. 898-904
Author(s):  
Melissa Barajas ◽  
Florence K. L. Tangka ◽  
James Schultz ◽  
Kulin Tantod ◽  
Ying Marilyn Kempster ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Screening ◽  
Colorectal Cancer Screening ◽  
Positive Impact ◽  
Cancer Control ◽  
Control Program ◽  
Baseline Period ◽  
Health Centers ◽  
California Department ◽  
Screening Uptake

As an awardee of the Centers for Disease Control and Prevention’s Colorectal Cancer Control Program, the California Department of Public Health partnered with Neighborhood Healthcare to implement evidence-based interventions and provider incentives (incentives offered to support staff, e.g., medical assistants, phlebotomists, front office staff, lab technicians) to improve colorectal cancer screening uptake. The objective of this study was to evaluate the effectiveness and cost of the provider incentive intervention implemented by Neighborhood Healthcare to increase colorectal cancer screening uptake. We collected and analyzed process and cost data to assess fecal immunochemical test (FIT) kit return rates to the health centers and the number of completed FIT kits. We estimated the costs of the preexisting interventions and the new interventions. Analyses were conducted for two time periods: preimplementation and implementation. Most Neighborhood Healthcare health centers experienced an increase in the percentage of FIT kit returns (average of 3.6 percentage points) and individuals screened (an average increase of 111 FIT kits per month) from the baseline period through the implementation period. The cost of the incentive intervention for each additional screen was $66.79. In conclusion, the results indicate that incentive programs can have an overall positive impact on both the percentage of FIT kits returned and the number of individuals screened.

Appropriateness of healthcare interventions: Concepts and scoping of the published literature

2008 ◽  
Vol 24 (03) ◽  
pp. 342-349 ◽  
Author(s):  
Claudia Sanmartin ◽  
Kellie Murphy ◽  
Nicole Choptain ◽  
Barbara Conner-Spady ◽  
Lindsay McLaren ◽  
...  
Keyword(s):  
Scoping Review ◽  
Data Extraction ◽  
Healthcare Delivery ◽  
Healthcare Services ◽  
Exclusion Criteria ◽  
Small Areas ◽  
Clinical Patient ◽  
Average Patient ◽  
Healthcare Interventions ◽  
Net Clinical Benefit

Objectives:This report is a scoping review of the literature with the objective of identifying definitions, conceptual models and frameworks, as well as the methods and range of perspectives, for determining appropriateness in the context of healthcare delivery.Methods:To lay groundwork for future, intervention-specific research on appropriateness, this work was carried out as a scoping review of published literature since 1966. Two reviewers, with two screens using inclusion/exclusion criteria based on the objective, focused the research and articles chosen for review.Results:The first screen examined 2,829 abstracts/titles, with the second screen examining 124 full articles, leaving 37 articles deemed highly relevant for data extraction and interpretation. Appropriateness is defined largely in terms of net clinical benefit to the average patient and varies by service and setting. The most widely used method to assess appropriateness of healthcare services is the RAND/UCLA Model. There are many related concepts such as medical necessity and small-areas variation.Conclusions:A broader approach to determining appropriateness for healthcare interventions is possible and would involve clinical, patient and societal perspectives.

scholarly journals Optimizing the timing of diagnostic testing after positive findings in lung cancer screening: a proof of concept radiomics study

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Zixing Wang ◽  
Ning Li ◽  
Fuling Zheng ◽  
Xin Sui ◽  
Wei Han ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Screening ◽  
Cancer Diagnosis ◽  
Diagnostic Testing ◽  
Delayed Diagnosis ◽  
Pulmonary Nodules ◽  
Lung Cancer Screening ◽  
Lung Cancer Diagnosis ◽  
Risk Patients

Abstract Background The timeliness of diagnostic testing after positive screening remains suboptimal because of limited evidence and methodology, leading to delayed diagnosis of lung cancer and over-examination. We propose a radiomics approach to assist with planning of the diagnostic testing interval in lung cancer screening. Methods From an institute-based lung cancer screening cohort, we retrospectively selected 92 patients with pulmonary nodules with diameters ≥ 3 mm at baseline (61 confirmed as lung cancer by histopathology; 31 confirmed cancer-free). Four groups of region-of-interest-based radiomic features (n = 310) were extracted for quantitative characterization of the nodules, and eight features were proven to be predictive of cancer diagnosis, noise-robust, phenotype-related, and non-redundant. A radiomics biomarker was then built with the random survival forest method. The patients with nodules were divided into low-, middle- and high-risk subgroups by two biomarker cutoffs that optimized time-dependent sensitivity and specificity for decisions about diagnostic workup within 3 months and about repeat screening after 12 months, respectively. A radiomics-based follow-up schedule was then proposed. Its performance was visually assessed with a time-to-diagnosis plot and benchmarked against lung RADS and four other guideline protocols. Results The radiomics biomarker had a high time-dependent area under the curve value (95% CI) for predicting lung cancer diagnosis within 12 months; training: 0.928 (0.844, 0.972), test: 0.888 (0.766, 0.975); the performance was robust in extensive cross-validations. The time-to-diagnosis distributions differed significantly between the three patient subgroups, p < 0.001: 96.2% of high-risk patients (n = 26) were diagnosed within 10 months after baseline screen, whereas 95.8% of low-risk patients (n = 24) remained cancer-free by the end of the study. Compared with the five existing protocols, the proposed follow-up schedule performed best at securing timely lung cancer diagnosis (delayed diagnosis rate: < 5%) and at sparing patients with cancer-free nodules from unnecessary repeat screenings and examinations (false recommendation rate: 0%). Conclusions Timely management of screening-detected pulmonary nodules can be substantially improved with a radiomics approach. This proof-of-concept study’s results should be further validated in large programs.

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