Mammogram perceptions, communication, and gaps in care among individuals with non-English language preference in Oregon and Washington states

This study examined perceptions of and communication about mammography as drivers of gaps in screening among individuals with non-English language preference (NELP). A survey was fielded in fall 2021 in five languages (Cantonese, English, Russian, Spanish, or Vietnamese) to individuals identified using electronic medical records in Oregon and Washington. The analytic sample consisted of 420 respondents with a median age of 61; approximately 45% of respondents identified as Asian, 37% as Hispanic, Latino, or Spanish origin, and 18% as some other race, ethnicity, or origin. Logistic regression models examined associations between screening and perception and communication items. Individuals who believed mammograms are unnecessary when healthy (aRR = 0.72 [0.57, 0.91]) or absent symptoms (aRR = 0.85 [0.72, 1.00]) were less likely to report a mammogram within the past two years (i.e., be current). Having a provider recommend (aRR = 1.27 [1.09, 1.47]) and discuss mammography (aRR = 1.18 [1.05, 1.32]) were associated with a higher likelihood of being current. Few respondents received written or verbal information in their preferred language (35% and 28.3%, respectively). Financial and logistical support, including language services were most frequently identified as types of support needed to obtain a mammogram. Overall, misperceptions about mammography may act as a barrier but communication may act as a facilitator for individuals with NELP. Provider-patient communication could be an effective way to encourage mammography. Culturally-responsive health promotion materials and provider communication, available in patients’ preferred language, are needed to combat misperceptions and support ongoing, on-time mammography for NELP patients

Drivers of High-Cost Medical Complexity in a Medicaid Population.

BACKGROUND: Efforts to improve outcomes for the 10% of patients using two thirds of health care expenditures increasingly include addressing social determinants. Empiric evidence is needed to identify the highest impact nonmedical drivers of medical complexity and cost. OBJECTIVES: This study examines whether complex, highest cost patients have different patterns of critical life adversity than those with better health and lower utilization. RESEARCH DESIGN: Using a validated algorithm we constructed a complexity/cost risk patient profile. We developed and fielded a life experience survey (Supplemental Digital Content 1, http://links.lww.com/MLR/B920) to a representative sample, then examined how the prevalence of specific adversities varied between complex, high-cost individuals, and others. SUBJECTS: Surveys were sent to 9176 adult Medicaid members in Portland, Oregon. MEASURES: Our primary variable was high medical complexity health cost risk; an alternative specification combined health cost risk and actual utilization/cost. Our survey instrument measured exposure to early and later-life adversities. RESULTS: Compared with healthy individuals in our population, medically complex individuals had significantly higher rates of adversity. The greatest risk of medical complexity and cost was associated with substance use [odds ratio (OR), 4.1], homelessness (OR, 3.0), childhood maltreatment (OR, 2.8), and incarceration (OR 2.4). Those with the highest prior year acute care utilization and cost had the highest rates of these same factors: substance use (62.5%), homelessness (61.7%), childhood maltreatment (55.5%), and incarceration (52.1%). CONCLUSION: Clinical and policy strategies that mitigate high-impact social drivers of poor outcomes are likely critical for improving both health and costs for complex, high-needs patients

Mammogram perceptions, communication, and gaps in care among individuals with non-English language preference in Oregon and Washington states.

This study examined perceptions of and communication about mammography as drivers of gaps in screening among individuals with non-English language preference (NELP). A survey was fielded in fall 2021 in five languages (Cantonese, English, Russian, Spanish, or Vietnamese) to individuals identified using electronic medical records in Oregon and Washington. The analytic sample consisted of 420 respondents with a median age of 61; approximately 45% of respondents identified as Asian, 37% as Hispanic, Latino, or Spanish origin, and 18% as some other race, ethnicity, or origin. Logistic regression models examined associations between screening and perception and communication items. Individuals who believed mammograms are unnecessary when healthy (aRR = 0.72 [0.57, 0.91]) or absent symptoms (aRR = 0.85 [0.72, 1.00]) were less likely to report a mammogram within the past two years (i.e., be current). Having a provider recommend (aRR = 1.27 [1.09, 1.47]) and discuss mammography (aRR = 1.18 [1.05, 1.32]) were associated with a higher likelihood of being current. Few respondents received written or verbal information in their preferred language (35% and 28.3%, respectively). Financial and logistical support, including language services were most frequently identified as types of support needed to obtain a mammogram. Overall, misperceptions about mammography may act as a barrier but communication may act as a facilitator for individuals with NELP. Provider-patient communication could be an effective way to encourage mammography. Culturally-responsive health promotion materials and provider communication, available in patients\u27 preferred language, are needed to combat misperceptions and support ongoing, on-time mammography for NELP patients

Impact of oral health integration training on children\u27s receipt of oral assessment, fluoride varnish and dental services.

OBJECTIVES: To evaluate the impact of an oral health integration training program on children\u27s receipt of oral health and dental services in Southern Oregon. METHODS: Children under 19 years with at least 6 months of Medicaid enrolment and at least one healthcare visit from 2014 to 2018 were included. The treatment group included children with at least one visit with a trained provider (n = 5541); children with no visits with trained providers (n = 8273) were the control group. The percentage of the treatment group who received oral health assessments was calculated, and regression models were developed to estimate the difference in likelihood of receiving fluoride varnish and dental services between treatment and control groups. RESULTS: The percentage of children receiving oral health assessments increased over time. Visiting a trained provider was consistently associated, each year, with a greater likelihood of receipt of fluoride varnish and preventive and diagnostic dental services but was not associated with treatment dental services or dental sealants. CONCLUSIONS: This study reports evidence for the overall impact of an oral health integration training on children\u27s receipt of oral and dental services. Health systems implementing these types of training strategies should consider how to reach specific underserved subgroups, increase paediatric dentists, and expand efforts to include older children

Patient experience and healthcare utilization for a COVID-19 telemedicine home monitoring program offered in English and Spanish.

BACKGROUND: Telemedicine is a vital component of the healthcare system\u27s response to COVID-19. In March of 2020, Providence health system rapidly implemented a telemedicine home monitoring program (HMP) for COVID-19 patients that included use of at-home pulse oximeters and thermometers and text-based surveys to monitor symptoms. By June 2020, Providence updated the HMP to be offered in Spanish. This program was implemented before COVID-19 testing was readily available and therefore was offered to all patients suspected of having COVID-19. This study examines engagement, experience, and utilization patterns for English and Spanish-speaking patients engaged in the COVID-19 HMP. METHODS: A retrospective review of program data was used to understand HMP patient engagement (responsiveness to three daily text to monitor symptoms), satisfaction with the program (likelihood to recommend the program) as well as comfort using home monitoring devices and comfort recovering from home. To understand impact on care for COVID-19 confirmed cases, we used electronic health records to measure patterns in healthcare use for COVID-19 positive HMP participants and non-HMP propensity weighted controls. All patients enrolled in the COVID-19 HMP from March-October 2020 were included in the study. Patients tested for COVID-19 during the time window and not enrolled in HMP were included in the propensity-weighted comparison group. Descriptive and regression analyses were performed overall and stratified by English and Spanish speakers. RESULTS: Of the 4,358 HMP participants, 75.5% identified as English speakers and 18.2% identified as Spanish speakers. There was high level of responsiveness to three daily text-based surveys monitoring symptoms engagement (\u3e80%) and a high level of comfort using the home monitoring devices (thermometers and pulse oximeters) for English- and Spanish-speaking participants (97.3% and 99.6%, respectively). The majority of English (95.7%) and Spanish-speaking (100%) patients felt safe monitoring their condition from home and had high satisfaction with the HMP (76.5% and 83.6%, respectively). English and Spanish-speaking COVID-19 positive HMP participants had more outpatient and emergency departments (ED) encounters than non-participants 7 and 30 days after their positive test. CONCLUSION: This widely implemented HMP provided participants with a sense of safety and satisfaction and its use was associated with more outpatient care and ED encounters. These outcomes were comparable across English and Spanish-speakers, highlighting the importance and potential impact of language-concordant telemedicine

Early Prediction of Breast Cancer Therapy Response using Multiresolution Fractal Analysis of DCE-MRI Parametric Maps

We aimed to determine whether multiresolution fractal analysis of voxel-based dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parametric maps can provide early prediction of breast cancer response to neoadjuvant chemotherapy (NACT). In total, 55 patients underwent 4 DCE-MRI examinations before, during, and after NACT. The shutter-speed model was used to analyze the DCE-MRI data and generate parametric maps within the tumor region of interest. The proposed multiresolution fractal method and the more conventional methods of single-resolution fractal, gray-level co-occurrence matrix, and run-length matrix were used to extract features from the parametric maps. Only the data obtained before and after the first NACT cycle were used to evaluate early prediction of response. With a training (N = 40) and testing (N = 15) data set, support vector machine was used to assess the predictive abilities of the features in classification of pathologic complete response versus non-pathologic complete response. Generally the multiresolution fractal features from individual maps and the concatenated features from all parametric maps showed better predictive performances than conventional features, with receiver operating curve area under the curve (AUC) values of 0.91 (all parameters) and 0.80 (Ktrans), in the training and testing sets, respectively. The differences in AUC were statistically significant (P < .05) for several parametric maps. Thus, multiresolution analysis that decomposes the texture at various spatial-frequency scales may more accurately capture changes in tumor vascular heterogeneity as measured by DCE-MRI, and therefore provide better early prediction of NACT response

DCE-MRI Texture Features for Early Prediction of Breast Cancer Therapy Response

This study investigates the effectiveness of hundreds of texture features extracted from voxel-based dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parametric maps for early prediction of breast cancer response to neoadjuvant chemotherapy (NAC). In total, 38 patients with breast cancer underwent DCE-MRI before (baseline) and after the first of the 6–8 NAC cycles. Quantitative pharmacokinetic (PK) parameters and semiquantitative metrics were estimated from DCE-MRI time-course data. The residual cancer burden (RCB) index value was computed based on pathological analysis of surgical specimens after NAC completion. In total, 1043 texture features were extracted from each of the 13 parametric maps of quantitative PK or semiquantitative metric, and their capabilities for early prediction of RCB were examined by correlating feature changes between the 2 MRI studies with RCB. There were 1069 pairs of feature–map combinations that showed effectiveness for response prediction with 4 correlation coefficients >0.7. The 3-dimensional gray-level cooccurrence matrix was the most effective feature extraction method for therapy response prediction, and, in general, the statistical features describing texture heterogeneity were the most effective features. Quantitative PK parameters, particularly those estimated with the shutter-speed model, were more likely to generate effective features for prediction response compared with the semiquantitative metrics. The best feature–map pair could predict pathologic complete response with 100% sensitivity and 100% specificity using our cohort. In conclusion, breast tumor heterogeneity in microvasculature as measured by texture features of voxel-based DCE-MRI parametric maps could be a useful biomarker for early prediction of NAC response

Early Prediction and Evaluation of Breast Cancer Response to Neoadjuvant Chemotherapy Using Quantitative DCE-MRI

The purpose is to compare quantitative dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) metrics with imaging tumor size for early prediction of breast cancer response to neoadjuvant chemotherapy (NACT) and evaluation of residual cancer burden (RCB). Twenty-eight patients with 29 primary breast tumors underwent DCE-MRI exams before, after one cycle of, at midpoint of, and after NACT. MRI tumor size in the longest diameter (LD) was measured according to the RECIST (Response Evaluation Criteria In Solid Tumors) guidelines. Pharmacokinetic analyses of DCE-MRI data were performed with the standard Tofts and Shutter-Speed models (TM and SSM). After one NACT cycle the percent changes of DCE-MRI parameters Ktrans (contrast agent plasma/interstitium transfer rate constant), ve (extravascular and extracellular volume fraction), kep (intravasation rate constant), and SSM-unique τi (mean intracellular water lifetime) are good to excellent early predictors of pathologic complete response (pCR) vs. non-pCR, with univariate logistic regression C statistics value in the range of 0.804 to 0.967. ve values after one cycle and at NACT midpoint are also good predictors of response, with C ranging 0.845 to 0.897. However, RECIST LD changes are poor predictors with C = 0.609 and 0.673, respectively. Post-NACT Ktrans, τi, and RECIST LD show statistically significant (P < .05) correlations with RCB. The performances of TM and SSM analyses for early prediction of response and RCB evaluation are comparable. In conclusion, quantitative DCE-MRI parameters are superior to imaging tumor size for early prediction of therapy response. Both TM and SSM analyses are effective for therapy response evaluation. However, the τi parameter derived only with SSM analysis allows the unique opportunity to potentially quantify therapy-induced changes in tumor energetic metabolism

Evaluation of Soft Tissue Sarcoma Response to Preoperative Chemoradiotherapy Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging

This study aims to assess the utility of quantitative dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) parameters in comparison with imaging tumor size for early prediction and evaluation of soft tissue sarcoma response to preoperative chemoradiotherapy. In total, 20 patients with intermediate- to high-grade soft tissue sarcomas received either a phase I trial regimen of sorafenib + chemoradiotherapy (n = 8) or chemoradiotherapy only (n = 12), and underwent DCE-MRI at baseline, after 2 weeks of treatment with sorafenib or after the first chemotherapy cycle, and after therapy completion. MRI tumor size in the longest diameter (LD) was measured according to the RECIST (Response Evaluation Criteria In Solid Tumors) guidelines. Pharmacokinetic analyses of DCE-MRI data were performed using the Shutter-Speed model. After only 2 weeks of treatment with sorafenib or after 1 chemotherapy cycle, Ktrans (rate constant for plasma/interstitium contrast agent transfer) and its percent change were good early predictors of optimal versus suboptimal pathological response with univariate logistic regression C statistics values of 0.90 and 0.80, respectively, whereas RECIST LD percent change was only a fair predictor (C = 0.72). Post-therapy Ktrans, ve (extravascular and extracellular volume fraction), and kep (intravasation rate constant), not RECIST LD, were excellent (C &gt; 0.90) markers of therapy response. Several DCE-MRI parameters before, during, and after therapy showed significant (P &lt; .05) correlations with percent necrosis of resected tumor specimens. In conclusion, absolute values and percent changes of quantitative DCE-MRI parameters provide better early prediction and evaluation of the pathological response of soft tissue sarcoma to preoperative chemoradiotherapy than the conventional measurement of imaging tumor size change