National Healthcare Quality and Disparities Report
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AHRQ Research Studies Date
Topics
- Access to Care (1)
- Cancer (12)
- (-) Cancer: Lung Cancer (12)
- Diagnostic Safety and Quality (2)
- Disparities (2)
- Electronic Health Records (EHRs) (1)
- Emergency Department (1)
- Evidence-Based Practice (1)
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- Hospital Readmissions (1)
- Imaging (1)
- Learning Health Systems (1)
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- Primary Care (1)
- Quality Measures (1)
- Quality of Care (1)
- Racial and Ethnic Minorities (4)
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- Rural Health (1)
- Screening (4)
- Shared Decision Making (1)
- Surgery (2)
AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 12 of 12 Research Studies DisplayedStevens ER, Caverly T, Butler JM
Considerations for using predictive models that include race as an input variable: the case study of lung cancer screening.
Indiscriminate use of predictive models incorporating race can reinforce biases present in source data and lead to an exacerbation of health disparities. In some countries, such as the United States, there is therefore a push to remove race from prediction models; however, there are still many prediction models that use race as an input. Biomedical informaticists who are given the responsibility of using these predictive models in healthcare environments are likely to be faced with questions like how to deal with race covariates in these models. The authors report that there is a need for a practical framework to facilitate model user thinking on how to incorporate race in their chosen model to avoid inadvertently amplifying disparities. The purpose of this paper is to utilize a case study of lung cancer screening to propose a simple framework to guide model users in approaching race inputs in the predictive models they are attempting to leverage in electronic health records and clinical workflows.
AHRQ-funded; HS028791.
Citation: Stevens ER, Caverly T, Butler JM .
Considerations for using predictive models that include race as an input variable: the case study of lung cancer screening.
J Biomed Inform 2023 Nov; 147:104525. doi: 10.1016/j.jbi.2023.104525..
Keywords: Cancer: Lung Cancer, Cancer, Racial and Ethnic Minorities
Kukhareva PV, Li H, Caverly TJ
Implementation of lung cancer screening in primary care and pulmonary clinics: pragmatic clinical trial of electronic health record-integrated everyday shared decision-making tool and clinician-facing prompts.
The authors conducted pre- and post-intervention analysis in primary care and pulmonary clinics to explore whether clinician-facing electronic health record (EHR) prompts and an EHR-integrated shared decision-making (SDM) tool designed to support incorporation of SDM into primary care could improve low-dose computer tomography scan imaging ordering and completion. Subjects were patients who met US Preventive Services Task Force criteria for lung cancer screening (LCS). The results indicated that EHR prompts and the EHR-integrated SDM tool were promising approaches to improving LCS in the primary care setting. The authors noted that further research is warranted.
AHRQ-funded; HS026198; HS028791.
Citation: Kukhareva PV, Li H, Caverly TJ .
Implementation of lung cancer screening in primary care and pulmonary clinics: pragmatic clinical trial of electronic health record-integrated everyday shared decision-making tool and clinician-facing prompts.
Chest 2023 Nov; 164(5):1325-38. doi: 10.1016/j.chest.2023.04.040..
Keywords: Cancer: Lung Cancer, Cancer, Screening, Primary Care, Electronic Health Records (EHRs), Health Information Technology (HIT), Shared Decision Making
Godfrey CM, Shipe ME, Welty VF
The thoracic research evaluation and treatment 2.0 model: a lung cancer prediction model for indeterminate nodules referred for specialist evaluation.
In this research study the authors updated and expanded the Thoracic Research Evaluation and Treatment (TREAT) model into a more generalized, robust approach for lung cancer prediction in patients referred for specialty evaluation to improve lung cancer prediction accuracy. Clinical and radiographic data on 1401 patients with indeterminate pulmonary nodules (IPNs) from six sites were collected retrospectively and divided into groups by clinical setting: pulmonary nodule clinic (n = 374; cancer prevalence, 42%), outpatient thoracic surgery clinic (n = 553; cancer prevalence, 73%), or inpatient surgical resection (n = 474; cancer prevalence, 90%). The new prediction model was developed using a missing data-driven pattern submodel approach and compared with the original TREAT, Mayo Clinic, Herder, and Brock models. Two-thirds of patients were found to have missing data; nodule growth and fluorodeoxyglucose-PET scan avidity were missing most frequently. The TREAT version 2.0 mean area under the receiver operating characteristic curve across missingness patterns was 0.85 compared with the original TREAT (0.80), Herder (0.73), Mayo Clinic (0.72), and Brock (0.68) models with improved calibration.
AHRQ-funded; HS026122.
Citation: Godfrey CM, Shipe ME, Welty VF .
The thoracic research evaluation and treatment 2.0 model: a lung cancer prediction model for indeterminate nodules referred for specialist evaluation.
Chest 2023 Nov; 164(5):1305-14. doi: 10.1016/j.chest.2023.06.009..
Keywords: Cancer: Lung Cancer, Cancer
Bonner SN, Lagisetty K, Reddy RM
Clinical implications of removing race-corrected pulmonary function tests for African American patients requiring surgery for lung cancer.
This study’s objective was to identify how many hospitals providing lung cancer surgery use race correction in pulmonary function tests (PFTs), examine the association of race correction with predicted lung function, and test the effect of decorrection on surgeons' treatment recommendations. Percent predicted preoperative and postoperative forced expiratory volume in 1 second (FEV1) was calculated for African American patients who underwent lung cancer resection between January 1, 2015, and September 31, 2022, using race-corrected and race-neutral equations for hospitals performing race correction. Randomization of US cardiothoracic surgeons was conducted to receive 1 clinical vignette that differed by the use of Global Lung Function Initiative equations for (1) African American patients (percent predicted postoperative FEV1, 49%), (2) other race or multiracial patients (percent predicted postoperative FEV1, 45%), and (3) race-neutral patients (percent predicted postoperative FEV1, 42%). A total of 515 African American patients (308 [59.8%] female; mean age, 66.2 years) were included in the study. Among these patients, the percent predicted preoperative FEV1 and postoperative FEV1 would have decreased by 9.2% and 7.6%, respectively, if race-neutral equations had been used. A total of 225 surgeons (194 male [87.8%]; mean time in practice, 19.4 years) were successfully randomized and completed the vignette items regarding risk perception and treatment outcomes (76% completion rate). Surgeons randomized to the vignette with African American race-corrected PFTs were more likely to recommend lobectomy (79.2%) compared with surgeons randomized to the other race or multiracial-corrected (61.7%) or race-neutral PFTs (52.8%).
AHRQ-funded; HS028038.
Citation: Bonner SN, Lagisetty K, Reddy RM .
Clinical implications of removing race-corrected pulmonary function tests for African American patients requiring surgery for lung cancer.
JAMA Surg 2023 Oct; 158(10):1061-68. doi: 10.1001/jamasurg.2023.3239..
Keywords: Racial and Ethnic Minorities, Cancer: Lung Cancer, Cancer, Surgery, Diagnostic Safety and Quality
Marcotte LM, Khor S, Flum DR
Factors associated with lung cancer risk factor documentation.
This cross-observational study’s objective was to identify factors associated with the minimum necessary information to determine an individual’s eligibility for lung cancer screening (ie, sufficient risk factor documentation) and to characterize clinic-level variability in documentation. The authors calculated the relative risk of sufficient lung cancer risk factor documentation by patient-, provider-, and system-level variables using Poisson regression models, clustering by clinic. They compared unadjusted, risk-adjusted, and reliability-adjusted proportions of patients with sufficient smoking documentation across 31 clinics using logistic regression models and 2-level hierarchical logit models to estimate reliability-adjusted proportions across clinics. A majority (60%) of 20,632 individuals were found to have sufficient risk factor documentation to determine screening eligibility. Patient-level factors were inversely associated with risk factor documentation including Black race, non-English preferred language, Medicaid insurance, and nonactivated patient portal, with documentation varying across clinics.
AHRQ-funded; HS026369.
Citation: Marcotte LM, Khor S, Flum DR .
Factors associated with lung cancer risk factor documentation.
Am J Manag Care 2023 Sep; 29(9):89354..
Keywords: Cancer: Lung Cancer, Cancer, Risk
Landy R, Gomez I, Caverly TJ
Methods for using race and ethnicity in prediction models for lung cancer screening eligibility.
The purpose of this study was to compare eligibility for lung cancer screening in a representative United States population by refitting the life-years gained from screening-computed tomography (LYFS-CT) model to exclude race and ethnicity versus a counterfactual eligibility method that recalculates life expectancy for racial and ethnic minority individuals utilizing the same covariates but substitutes White race and utilizes the higher predicted life expectancy, preventing historically underserved groups from being penalized. The National Health Interview Survey (NHIS) 2015-2018 included 25,601 individuals aged 50 to 80 years who ever smoked. The study found that removing race and ethnicity from the submodels underestimated lung cancer death risk and all-cause mortality in African American individuals. It also overestimated mortality in Hispanic American and Asian American individuals. As a result, the LYFS-CT NoRace model increased Hispanic American and Asian American eligibility by 108% and 73%, respectively, while decreasing African American eligibility by 39%. Utilizing LYFS-CT with the counterfactual all-cause mortality model better maintained calibration across groups and increased African American eligibility by 13% without decreasing eligibility for Hispanic American and Asian American individuals.
AHRQ-funded; HS026198.
Citation: Landy R, Gomez I, Caverly TJ .
Methods for using race and ethnicity in prediction models for lung cancer screening eligibility.
JAMA Netw Open 2023 Sep; 6(9):e2331155. doi: 10.1001/jamanetworkopen.2023.31155..
Keywords: Racial and Ethnic Minorities, Cancer: Lung Cancer, Cancer, Screening, Prevention
Murphy DR, Zimolzak AJ, Upadhyay DK
Developing electronic clinical quality measures to assess the cancer diagnostic process.
Electronic clinical quality measures (eCQMs) to evaluate quality of cancer diagnosis could facilitate quantification and improvement of diagnostic performance. The purpose of this study was to developed 2 eCQMs to evaluate diagnostic assessment of red-flag clinical findings for colorectal cancer (CRC) and lung cancer. At each site the researchers assessed 100 positive and 20 negative randomly chosen records for each eCQM at each site to validate accuracy and categorized missed opportunities associated with system, provider, or patient factors. The researchers applied the CRC eCQM at both sites, while the lung cancer eCQM was only applied at the VA due to an absence of structured data indicating level of cancer suspicion on most chest imaging results at Geisinger. The study found that for the CRC eCQM, the appropriate follow-up took place in 26, 746 out of 74, 314 patients (36.0%) in the VA after removing clinical exclusions and in 1,009 out of 2,461 patients (41.1%) at Geisinger. The appropriate assessment for lung cancer in the VA took place in 25, 166 out of 40, 924 patients (61.5). Provider factors were cited by reviewers the primary source of missed opportunities at both sites.
AHRQ-funded; HS022087.
Citation: Murphy DR, Zimolzak AJ, Upadhyay DK .
Developing electronic clinical quality measures to assess the cancer diagnostic process.
J Am Med Inform Assoc 2023 Aug 18; 30(9):1526-31. doi: 10.1093/jamia/ocad089..
Keywords: Cancer: Lung Cancer, Cancer, Quality Measures, Diagnostic Safety and Quality, Quality of Care
Lee SJC, Lee J, Zhu H
Assessing barriers and facilitators to lung cancer screening: initial findings from a patient navigation intervention.
This study’s objective was to examine the challenges to providing lung cancer screening using low-dose computed tomography for patients, particularly minority, under-, and uninsured populations. The authors conducted a pragmatic randomized controlled trial of telephone-based navigation for lung cancer screening in an integrated, urban safety-net health care system. They used bilingual navigators (Spanish and English) to make systematic contact with patients, recording standardized call characteristics in a study-specific database. A total of 225 patients (mean age 63 years, 46% female, 70% racial/ethnic minority) were assigned navigators, with a total of 559 barriers to screening identified during 806 telephone calls. The most common barrier types were personal (46%), provider (30%), and practical (17%). System (6%) and psychosocial (1%) barriers were described by English-speaking patients, but not by Spanish-speaking patients. Provider-related barriers decreased by 80% over the course of the lung cancer screening process.
AHRQ-funded; HS022418.
Citation: Lee SJC, Lee J, Zhu H .
Assessing barriers and facilitators to lung cancer screening: initial findings from a patient navigation intervention.
Popul Health Manag 2023 Jun; 26(3):177-84. doi: 10.1089/pop.2023.0053..
Keywords: Cancer: Lung Cancer, Cancer, Screening, Prevention, Imaging
Richmond J, Murray MH, Milder CM
Racial disparities in lung cancer stage of diagnosis among adults living in the southeastern United States.
The purpose of this study was to identify factors contributing to racial disparities in stage of lung cancer stage diagnosis in low-income adults. The researchers identified cases of incident lung cancer from the prospective observational Southern Community Cohort Study by linking them with state cancer registries in 12 southeastern states. A subset of participants who answered psychosocial questions such as those related to racial discrimination experiences were assessed to determine if model predictive power improved. The study identified 1,572 patients with incident lung cancer with available lung cancer stage. Compared with White participants Black participants with lung cancer reflected higher unadjusted odds of distant stage diagnosis. Higher neighborhood area deprivation was related with distant stage diagnosis. No significant differences were found in distant stage disease for Black vs White participants after controlling for individual- and area-level factors, but participants with COPD showed decreased odds of distant stage diagnosis in the primary model.
AHRQ-funded; HS026122.
Citation: Richmond J, Murray MH, Milder CM .
Racial disparities in lung cancer stage of diagnosis among adults living in the southeastern United States.
Chest 2023 May; 163(5):1314-27. doi: 10.1016/j.chest.2022.11.025..
Keywords: Disparities, Racial and Ethnic Minorities, Cancer: Lung Cancer, Cancer
Ray EM, Hinton SP, Reeder-Hayes KE
Risk factors for return to the emergency department and readmission in patients with hospital-diagnosed advanced lung cancer.
The objectives of this study were to examine the patterns of care and risk factors for subsequent acute care utilization among patients with hospital-diagnosed advanced lung cancer (ALC). Researchers identified patients with incident ALC from 2007-13 and an index hospitalization within 7 days of diagnosis in Surveillance, Epidemiology, and End Results-Medicare. Results showed that more than half of the incident ALC patients were hospitalized around the time of diagnosis; among those who survived to discharge, only 37% received systemic cancer treatment. Many patients experienced an early readmittance and most died within 6 months. The researchers conclude that such patients may benefit from increased access to palliative and other supportive care during hospitalization to prevent subsequent health care utilization.
AHRQ-funded; HS000032.
Citation: Ray EM, Hinton SP, Reeder-Hayes KE .
Risk factors for return to the emergency department and readmission in patients with hospital-diagnosed advanced lung cancer.
Med Care 2023 Apr;61(4):237-46. doi: 10.1097/mlr.0000000000001829.
Keywords: Emergency Department, Hospital Readmissions, Cancer: Lung Cancer, Cancer, Risk
Logan CD, Feinglass J, Halverson AL
Rural-urban disparities in receipt of surgery for potentially resectable non-small cell lung cancer.
This study examined the reasons there are lower rates of surgical treatment for potentially resectable non-small cell lung cancer (NSCLC) for patients living in rural areas than in urban areas. The National Cancer Database was used to identify patients with clinical stage I-IIIA NSCLC between 2004 and 2018. Reasons for nonreceipt of surgery was evaluated for rural and urban area patients. The study included 328,785 patients with NSCLC with 13% from rural areas. Overall, 62.4% of patients from urban areas and 58.8% of patients from rural areas underwent surgery. Patients from rural areas had increased odds of (1) being recommended primary nonsurgical management, (2) surgery being deemed contraindicated due to risk, (3) surgery being recommended but not performed, and (4) overall failure to receive surgery.
AHRQ-funded; HS026385.
Citation: Logan CD, Feinglass J, Halverson AL .
Rural-urban disparities in receipt of surgery for potentially resectable non-small cell lung cancer.
J Surg Res 2023 Mar;283:1053-63. doi: 10.1016/j.jss.2022.10.097.
Keywords: Cancer: Lung Cancer, Cancer, Disparities, Surgery, Rural Health, Access to Care
Strayer TE, Spalluto LB, Burns A
Using the framework for reporting adaptations and modifications-expanded (frame) to study adaptations in lung cancer screening delivery in the Veterans Health Administration: a cohort study.
The purpose of this study was to apply the Framework for Reporting Adaptations and Modifications-Expanded (FRAME) to study adaptations in lung cancer screening delivery processes in a Veterans Health Administration (VHA) Initiative. Between 2019 and 2021 the researchers prospectively administered semi-structured interviews with lung cancer screening program navigators at 10 Veterans Affairs Medical Centers (VAMCs). Baseline process maps were developed for each program, and each program navigator reviewed process maps in subsequent years 1 and 2. Researchers then identified, documented, and mapped adaptations in screening processes to the FRAME categories. 16 interviews were conducted across 10 VHA lung cancer screening programs, with 6 of these being operational, and of those 3 reported adaptations to their screening processes that were planned or in response to COVID-19. In year 2 all 10 programs were operational and eligible. Programs reported 14 adaptations in year 2. The adaptations identified were both planned and unplanned and often prompted by increased workload; 57% of year 2 adaptations were associated with the identification and eligibility of Veterans and 43% were associated with follow-up with Veterans for screening results. During the 2 years, adaptations associated with data management and patient tracking took place in 60% of programs to improve the data collection and tracking of Veterans in the screening process. The study concluded that adaptations took place predominantly in the categories of patient identification and communication of results due to increased workload.
AHRQ-funded; HS026122; HS026395.
Citation: Strayer TE, Spalluto LB, Burns A .
Using the framework for reporting adaptations and modifications-expanded (frame) to study adaptations in lung cancer screening delivery in the Veterans Health Administration: a cohort study.
Implement Sci Commun 2023 Jan 12; 4(1):5. doi: 10.1186/s43058-022-00388-x..
Keywords: Cancer: Lung Cancer, Cancer, Screening, Evidence-Based Practice, Learning Health Systems