Providers’ mediating role for medication adherence among cancer survivors

Trogdon, Justin G.; Amin, Krutika; Gupta, Parul; Urick, Benjamin Y.; Reeder‐Hayes, Katherine E.; Farley, Joel F.; Wheeler, Stephanie B.; Spees, Lisa P.; Lund, Jennifer L.

doi:10.1371/journal.pone.0260358

Cited by 6 publications

(4 citation statements)

References 44 publications

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“…45 For example, among cancer survivors with MCCs, those who report seeing a higher number of clinicians also report higher levels of treatment burden, lower levels of health-related quality of life, and no significant benefit in medication adherence. 46,47 Although our study advances knowledge about both clinical MTS size and diversity of specialties, future work should assess the broader organizational or health system context that may affect MTS care delivery, such as geographic dispersion among clinical teams or if they are affiliated with a single health system or multiple practice settings. This study underscores a need for understanding how variations in MTS composition, complexity, and functioning, as critical components of care delivery processes, contribute to health and health care disparities for different populations.…”

Section: Discussionmentioning

confidence: 99%

Clinical Multiteam System Composition and Complexity Among Newly Diagnosed Early-Stage Breast, Colorectal, and Lung Cancer Patients With Multiple Chronic Conditions: A SEER-Medicare Analysis

Doose

Verhoeven

Sanchez

et al. 2023

JCO Oncology Practice

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PURPOSE: Sixty percent of adults have multiple chronic conditions at cancer diagnosis. These patients may require a multidisciplinary clinical team-of-teams, or a multiteam system (MTS), of high-complexity involving multiple specialists and primary care, who, ideally, coordinate clinical responsibilities, share information, and align clinical decisions to ensure comprehensive care needs are managed. However, insights examining MTS composition and complexity among individuals with cancer and comorbidities at diagnosis using US population-level data are limited. METHODS: Using SEER-Medicare data (2006-2016), we identified newly diagnosed patients with breast, colorectal, or lung cancer who had a codiagnosis of cardiopulmonary disease and/or diabetes (n = 75,201). Zaccaro's theory-based classification of MTSs was used to categorize clinical MTS complexity in the 4 months following cancer diagnosis: high-complexity (≥ 4 clinicians from ≥ 2 specialties) and low-complexity (1-3 clinicians from 1-2 specialties). We describe the proportions of patients with different MTS compositions and quantify the incidence of high-complexity MTS care by patient groups. RESULTS: The most common MTS composition was oncology with primary care (37%). Half (50.3%) received high-complexity MTS care. The incidence of high-complexity MTS care for non-Hispanic Black and Hispanic patients with cancer was 6.7% (95% CI, −8.0 to −5.3) and 4.7% (95% CI, −6.3 to −3.0) lower than non-Hispanic White patients with cancer; 13.1% (95% CI, −14.1 to −12.2) lower for rural residents compared with urban; 10.4% (95% CI, −11.2 to −9.5) lower for dual Medicaid-Medicare beneficiaries compared with Medicare-only; and 16.6% (95% CI, −17.5 to −15.8) lower for colorectal compared with breast cancer. CONCLUSION: Incidence differences of high-complexity MTS care were observed among cancer patients with multiple chronic conditions from underserved populations. The results highlight the need to further understand the effects of and mechanisms through which care team composition, complexity, and functioning affect care quality and outcomes.

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Section: Discussionmentioning

confidence: 99%

Clinical Multiteam System Composition and Complexity Among Newly Diagnosed Early-Stage Breast, Colorectal, and Lung Cancer Patients With Multiple Chronic Conditions: A SEER-Medicare Analysis

Doose

Verhoeven

Sanchez

et al. 2023

JCO Oncology Practice

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show abstract

“…We have no information on whether providers may emphasize the importance of taking the medications as prescribed and recommended. Therefore, we cannot test the hypothesis as to whether it is the patients who are primarily responsible for making the decision to get their prescription refilled or for taking their medication as recommended; however, the lack of continuous medication management services for cancer survivors or the lack of seamless care transition from specialty care to primary care in these underserved areas may also influence patient adherence to AET in the long run [ 41 , 42 ].…”

Section: Discussionmentioning

confidence: 99%

Geographic Variations and the Associated Factors in Adherence to and Persistence with Adjuvant Hormonal Therapy for the Privately Insured women Aged 18–64 with Breast Cancer in Texas

Kim

Rajan

et al. 2023

Current Oncology

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The purpose of this study is to examine the geographical patterns of adjuvant hormonal therapy adherence and persistence and the associated factors in insured Texan women aged 18–64 with early breast cancer. A retrospective cohort study was conducted using 5-year claims data for the population insured by the Blue Cross Blue Shield of Texas (BCBSTX). Women diagnosed with early breast cancer who were taking tamoxifen or aromatase inhibitors (AIs) for adjuvant hormonal therapy with at least one prescription claim were identified. Adherence to adjuvant hormonal therapy and persistence with adjuvant hormonal therapy were calculated as outcome measures. Women without a gap between two consecutively dispensed prescriptions of at least 90 days were considered to be persistently taking the medications. Patient-level multivariate logistic regression models with repeated regional-level adjustments and a Cox proportional hazards model with mixed effects were used to determine the geographical variations and patient-, provider-, and area-level factors that were associated with adjuvant hormonal therapy adherence and persistence. Of the 938 women in the cohort, 627 (66.8%) initiated adjuvant hormonal therapy. Most of the smaller HRRs have significantly higher or lower rates of treatment adherence and persistence rates relative to the median regions. The use of AHT varies substantially from one geographical area to another, especially for adherence, with an approximately two-fold difference between the lowest and highest areas, and area-level factors were found to be significantly associated with the compliance of AHT. There are geographical variations in AHT adherence and persistence in Texas. Patient-level and area-level factors have significant associations explaining these patterns.

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“…European journal of surgical oncology ... 0.631 29846174 [52] Impact of long-term antihypertensive and antidiabetic medications on the prognosis of post-surgical colorectal cancer: the Fujian ... Aging 0.600 34843550 [53] Providers' mediating role for medication adherence among cancer survivors.…”

Section: B Methodsmentioning

confidence: 99%

CCS Explorer: Relevance Prediction, Extractive Summarization, and Named Entity Recognition from Clinical Cohort Studies

Al-Hussaini¹,

An²,

Lee³

et al. 2022

Preprint

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Clinical Cohort Studies (CCS), such as randomized clinical trials, are a great source of documented clinical research. Ideally, a clinical expert inspects these articles for exploratory analysis ranging from drug discovery for evaluating the efficacy of existing drugs in tackling emerging diseases to the first test of newly developed drugs. However, more than 100 articles are published daily on a single prevalent disease like COVID-19 in PubMed. As a result, it can take days for a physician to find articles and extract relevant information. Can we develop a system to sift through the long list of these articles faster and document the crucial takeaways from each of these articles? In this work, we propose CCS Explorer, an end-to-end system for relevance prediction of sentences, extractive summarization, and patient, outcome, and intervention entity detection from CCS. CCS Explorer is packaged in a web-based graphical user interface where the user can provide any disease name. CCS Explorer then extracts and aggregates all relevant information from articles on PubMed based on the results of an automatically generated query produced on the back-end. For each task, CCS Explorer fine-tunes pre-trained language representation models based on transformers with additional layers. The models are evaluated using two publicly available datasets. CCS Explorer obtains a recall of 80.2%, AUC-ROC of 0.843, and an accuracy of 88.3% on sentence relevance prediction using BioBERT and achieves an average Micro F1-Score of 77.8% on Patient, Intervention, Outcome detection (PIO) using PubMedBERT. Thus, CCS Explorer can reliably extract relevant information to summarize articles, saving time by ∼ 660×.

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Providers’ mediating role for medication adherence among cancer survivors

Cited by 6 publications

References 44 publications

Clinical Multiteam System Composition and Complexity Among Newly Diagnosed Early-Stage Breast, Colorectal, and Lung Cancer Patients With Multiple Chronic Conditions: A SEER-Medicare Analysis

Clinical Multiteam System Composition and Complexity Among Newly Diagnosed Early-Stage Breast, Colorectal, and Lung Cancer Patients With Multiple Chronic Conditions: A SEER-Medicare Analysis

Geographic Variations and the Associated Factors in Adherence to and Persistence with Adjuvant Hormonal Therapy for the Privately Insured women Aged 18–64 with Breast Cancer in Texas

CCS Explorer: Relevance Prediction, Extractive Summarization, and Named Entity Recognition from Clinical Cohort Studies

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