Dataset Information

National Lung Cancer Screening Utilization Trends in the Veterans Health Administration.

ABSTRACT:

Background

Many Veterans are high risk for lung cancer. Low-dose computed tomography (LDCT) is an effective strategy for lung cancer early detection in a high-risk population. Our objective was to describe and compare annual and geographic utilization trends for LDCT screening in the Veteran's Health Administration (VHA).

Methods

A national retrospective cohort of screened Veterans from January 1, 2011 to May 31, 2018 was used to calculate annual and regional rates of initial LDCT utilization per 1000 eligible Veterans. We identified Veterans with a first LDCT exam using common procedure terminology codes G0297 or 71250 and described as "lung cancer screening," "screening," or "LCS." The number of screen-eligible Veterans per year was calculated as unique Veterans aged 55 to 80 years seen at a Veterans Affairs medical center (VAMC) in that year, multiplied by 32% (estimated proportion with eligible smoking history). We present 95% confidence intervals (CI) for rates.

Results

Screened Veterans had a mean age of 66.1?years (standard deviation [SD] = 5.6); 95.5% male; 77.4% Caucasian. There were 119 300 LDCT exams, of which 80 819 (67.7%) were initial. Nationally, initial screens increased from 0 (95% CI = 0.00 to 0.00) in 2011 to 29.6 (95% CI = 29.26 to 29.88) scans per 1000 eligible Veterans in 2018 (P_trend < .001). Initial screens increased over time within all geographic regions, most prominently in northeastern and Florida VAMCs.

Conclusion

VHA LDCT utilization increased from 2011 to 2018. However, overall utilization remained low. Future interventions are needed to increase lung cancer screening utilization among eligible Veterans.

SUBMITTER: Lewis JA

PROVIDER: S-EPMC7583162 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Publications

National Lung Cancer Screening Utilization Trends in the Veterans Health Administration.

Lewis Jennifer A JA Samuels Lauren R LR Denton Jason J Edwards Gretchen C GC Matheny Michael E ME Maiga Amelia A Slatore Christopher G CG Grogan Eric E Kim Jane J Sherrier Robert H RH Dittus Robert S RS Massion Pierre P PP Keohane Laura L Nikpay Sayeh S Roumie Christianne L CL

JNCI cancer spectrum 20200613 5

<h4>Background</h4>Many Veterans are high risk for lung cancer. Low-dose computed tomography (LDCT) is an effective strategy for lung cancer early detection in a high-risk population. Our objective was to describe and compare annual and geographic utilization trends for LDCT screening in the Veteran's Health Administration (VHA).<h4>Methods</h4>A national retrospective cohort of screened Veterans from January 1, 2011 to May 31, 2018 was used to calculate annual and regional rates of initial LDCT ...[more]

PMID: 33490864

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Project description:IntroductionTo assess healthcare professionals' perceptions of rural barriers and facilitators of lung cancer screening program implementation in a Veterans Health Administration (VHA) setting through a series of one-on-one interviews with healthcare team members.MethodsBased on measures developed using Reach Effectiveness Adoption Implementation Maintenance (RE-AIM), we conducted a cross-sectional qualitative study consisting of one-on-one semi-structured telephone interviews with VHA healthcare team members at 10 Veterans Affairs medical centers (VAMCs) between December 2020 and September 2021. An iterative inductive and deductive approach was used for qualitative analysis of interview data, resulting in the development of a conceptual model to depict rural barriers and facilitators of lung cancer screening program implementation.ResultsA total of 30 interviews were completed among staff, providers, and lung cancer screening program directors and a conceptual model of rural barriers and facilitators of lung cancer screening program implementation was developed. Major themes were categorized within institutional and patient environments. Within the institutional environment, participants identified systems-level (patient communication, resource availability, workload), provider-level (attitudes and beliefs, knowledge, skills and capabilities), and external (regional and national networks, incentives) barriers to and facilitators of lung cancer screening program implementation. Within the patient environment, participants revealed patient-level (modifiable vulnerabilities) barriers and facilitators as well as ecological modifiers (community) that influence screening behavior.DiscussionUnderstanding rural barriers to and facilitators of lung cancer screening program implementation as perceived by healthcare team members points to opportunities and approaches for improving lung cancer screening reach, implementation and effectiveness in VHA rural settings.

Project description:BackgroundStudies show uneven access to Medicare-approved lung cancer screening (LCS) programs across the United States. The Veterans Health Administration (VA), the largest national US integrated health system, is potentially well positioned to coordinate LCS services across regional units to ensure that access matches distribution of need nationally.Research questionTo what extent does LCS access (considering both VA and partner sites) and use match the distribution of eligible Veterans at state and regional levels?MethodsIn this retrospective analysis, we identified LCS examinations in VA facilities between 2013 and 2019 from the VA Corporate Data Warehouse and plotted VA facilities with LCS geographically. We compared estimated LCS rates (unique Veterans screened per LCS-eligible population) across states and VA regional units. Finally, we assessed whether the VA's new partnership with the GO2 Foundation for Lung Cancer (which includes more than 750 LCS centers) closes geographic gaps in LCS access.ResultsWe identified 71,898 LCS examinations in 96 of 139 (69.1%) VA facilities in 44 states between 2013 and 2019, with substantial variation across states (0-8 VA LCS facilities per state). Screening rates among eligible Veterans in the population varied more than 30-fold across regional networks (rate ratio, 33.6; 95% CI, 30.8-36.7 for VA New England vs Veterans Integrated Service Network 4), with weak correlation between eligible populations and LCS rates (coefficient, -0.30). Partnering with the GO2 Foundation for Lung Cancer expands capacity and access (eg, all states now have ≥ 1 VA or partner LCS site), but 9 of the 12 states with the highest proportions of rural Veterans still have ≤ 3 total LCS facilities.InterpretationDisparities in LCS access exist based on where Veterans live, particularly for rural Veterans, even after partnering with the GO2 Foundation for Lung Cancer. The nationally integrated VA system has an opportunity to leverage regional resources to distribute and coordinate LCS services better to ensure equitable access.

Project description:BackgroundChronic spinal pain conditions affect millions of US adults and carry a high healthcare cost burden, both direct and indirect. Conservative interventions for spinal pain conditions, including chiropractic care, have been associated with lower healthcare costs and improvements in pain status in different clinical populations, including veterans. Little is currently known about predicting healthcare service utilization in the domain of conservative interventions for spinal pain conditions, including the frequency of use of chiropractic services. The purpose of this retrospective cohort study was to explore the use of supervised machine learning approaches to predicting one-year chiropractic service utilization by veterans receiving VA chiropractic care.MethodsWe included 19,946 veterans who entered the Musculoskeletal Diagnosis Cohort between October 1, 2003 and September 30, 2013 and utilized VA chiropractic services within one year of cohort entry. The primary outcome was one-year chiropractic service utilization following index chiropractic visit, split into quartiles represented by the following classes: 1 visit, 2 to 3 visits, 4 to 6 visits, and 7 or greater visits. We compared the performance of four multiclass classification algorithms (gradient boosted classifier, stochastic gradient descent classifier, support vector classifier, and artificial neural network) in predicting visit quartile using 158 sociodemographic and clinical features.ResultsThe selected algorithms demonstrated poor prediction capabilities. Subset accuracy was 42.1% for the gradient boosted classifier, 38.6% for the stochastic gradient descent classifier, 41.4% for the support vector classifier, and 40.3% for the artificial neural network. The micro-averaged area under the precision-recall curve for each one-versus-rest classifier was 0.43 for the gradient boosted classifier, 0.38 for the stochastic gradient descent classifier, 0.43 for the support vector classifier, and 0.42 for the artificial neural network. Performance of each model yielded only a small positive shift in prediction probability (approximately 15%) compared to naïve classification.ConclusionsUsing supervised machine learning to predict chiropractic service utilization remains challenging, with only a small shift in predictive probability over naïve classification and limited clinical utility. Future work should examine mechanisms to improve model performance.

Project description:BackgroundPhysician responsiveness to patient preferences for depression treatment may improve treatment adherence and clinical outcomes.ObjectiveTo examine associations of patient treatment preferences with types of depression treatment received and treatment adherence among Veterans initiating depression treatment.DesignPatient self-report surveys at treatment initiation linked to medical records.SettingVeterans Health Administration (VA) clinics nationally, 2018-2020.ParticipantsA total of 2582 patients (76.7% male, mean age 48.7 years, 62.3% Non-Hispanic White) MAIN MEASURES: Patient self-reported preferences for medication and psychotherapy on 0-10 self-anchoring visual analog scales (0="completely unwilling"; 10="completely willing"). Treatment receipt and adherence (refilling medications; attending 3+ psychotherapy sessions) over 3 months. Logistic regression models controlled for socio-demographics and geographic variables.Key resultsMore patients reported strong preferences (10/10) for psychotherapy than medication (51.2% versus 36.7%, McNemar χ21=175.3, p<0.001). A total of 32.1% of patients who preferred (7-10/10) medication and 21.8% who preferred psychotherapy did not receive these treatments. Patients who strongly preferred medication were substantially more likely to receive medication than those who had strong negative preferences (odds ratios [OR]=17.5; 95% confidence interval [CI]=12.5-24.5). Compared with patients who had strong negative psychotherapy preferences, those with strong psychotherapy preferences were about twice as likely to receive psychotherapy (OR=1.9; 95% CI=1.0-3.5). Patients who strongly preferred psychotherapy were more likely to adhere to psychotherapy than those with strong negative preferences (OR=3.3; 95% CI=1.4-7.4). Treatment preferences were not associated with medication or combined treatment adherence. Patients in primary care settings had lower odds of receiving (but not adhering to) psychotherapy than patients in specialty mental health settings. Depression severity was not associated with treatment receipt or adherence.ConclusionsMismatches between treatment preferences and treatment type received were common and associated with worse treatment adherence for psychotherapy. Future research could examine ways to decrease mismatch between patient preferences and treatments received and potential effects on patient outcomes.

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Dataset Information

National Lung Cancer Screening Utilization Trends in the Veterans Health Administration.

Background

Methods

Results

Conclusion

Publications

National Lung Cancer Screening Utilization Trends in the Veterans Health Administration.

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