The effectiveness of case management for cancer patients: an umbrella review

Wang, Na; Chen, Jia; Chen, Wenjun; Shi, Zhengkun; Yang, Huaping; Liu, Peng; Xiao, Wei; Dong, Xiangling; Wang, Chen; Mao, Ling; Li, Xianhong

doi:10.1186/s12913-022-08610-1

Cited by 42 publications

(13 citation statements)

References 36 publications

(79 reference statements)

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“…Case managers are a vital and effective part of interprofessional cancer care teams (Wang et al, 2022). Appropriate resource allocation decisions can mitigate social risk factors leading to health disparities among these patients (CMS, 2022).…”

Section: Implications For Case Managementmentioning

confidence: 99%

Generating Team-Based Strategies to Reduce Health Inequity in Cancer Care

Moreo,

Sullivan,

Carter

et al. 2023

Professional Case Management

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Purpose/Objectives: Despite increased emphases on reducing racial disparities in the U.S. health care system, interprofessional care teams may inadvertently perpetuate health disparities through lack of awareness or experience in supporting individualized, patient-centered goals of care. Racial disparities can lead to health inequity. Persistent health disparity gaps exist among Black patients with multiple myeloma (MM) when compared with non-Black patients. Black patients experience a two-fold increase in MM risk and earlier age of onset compared with non-Black patients. Black patients are also less likely to receive timely access to some therapies, undergo autologous stem cell transplant, or enroll in clinical trials. This article describes a large-scale, equity-focused implementation science initiative aimed at identifying and overcoming racial disparities and health inequity among patients with MM through quality improvement goals identified by each of the interprofessional cancer care teams. Primary Practice Settings: Interprofessional cancer care teams in two large oncology systems as well as four community clinics were engaged in this study along with their patients with MM. Geographic areas included the following: Chicago, IL; Washington, DC; Charlotte, NC; Columbus, OH; Denver, CO; and Indianapolis, IN. Interprofessional teams included hematologists/oncologists, primary care physicians, nurse practitioners/physician assistants, and case managers/nurse navigators. Teams collectively examined and compared their own beliefs and attitudes about their patients' goals for MM treatment and management versus those of their patients to uncover and address discordances. Medical records from the clinics were audited to evaluate disparities in treatment and practice at the point of care. Live, team-based audit-feedback sessions were implemented among teams to examine data sets, as well as utilize the data to address interprofessional factors that could enhance more equitable care. Findings/Conclusions: Data from comparative surveys between patients and interprofessional team members revealed significant discordances that enabled health care teams to recognize gaps and identify ways to improve patient-centered care, such as shared decision-making. Through audit-feedback sessions, interprofessional teams were able to collaboratively meet and discuss methods to improve access to care coordination services and other strategies aimed at alleviating disparities. Baseline chart audits revealed and confirmed disparities of care including patient/disease characteristics, treatment history, clinical practice metrics, and patient-centered measures. Follow-up chart audits conducted 6 months later measured changes in documented practice behavior. Action plans developed by the interprofessional teams as a result of this study intend to address sustainable reductions in health disparities among patients with MM to improve health equity and overall care. Implications for Case Management Practice: This implementation science initiative and data results have several implications for case managers caring for diverse patients with MM in both large health systems and smaller community practices. Results punctuate the importance of identifying and supporting diverse patients' individualized goals and preferences in their care journey to mitigate health inequity and maximize health outcomes. The value of working collaboratively as an interprofessional team is evident in the study results, as is the role of the case manager in appropriate resource allocation to mitigate health disparities. Lessons learned from this initiative may also be applied to other case management settings where complex care delivery and interprofessional teams are at work.

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Section: Implications For Case Managementmentioning

confidence: 99%

Generating Team-Based Strategies to Reduce Health Inequity in Cancer Care

Moreo,

Sullivan,

Carter

et al. 2023

Professional Case Management

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“…The existing medical and healthcare services are severely challenged by the growing number of chronic patients and the aging population, necessitating the integration of healthcare with emerging information and communication technologies (ICT) to improve services [ 1 , 2 ]. In the evolving healthcare landscape, the upcoming health sector is poised to address the challenges posed by a rising population of chronic patients and the limited availability of treatment options to meet the escalating demands of patients [ 3 , 4 ]. A pertinent illustration of this transformation can be observed in the response to the global COVID-19 pandemic [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

The applications of internet of things in smart healthcare sectors: a bibliometric and deep study

Ziwei,

Dongni,

Man

et al. 2024

Heliyon

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“…Wavelet transform is a popular ECG denoising technique. It can remove the noise from the ECG signals by using the characteristics of noise in the frequency domain ( 13 , 14 ). Although wavelet transform has many advantages over traditional filtering algorithms, there are still some drawbacks.…”

Section: Introductionmentioning

confidence: 99%

A novel approach for denoising electrocardiogram signals to detect cardiovascular diseases using an efficient hybrid scheme

Bing,

Liu,

Zhai

et al. 2024

Front. Cardiovasc. Med.

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BackgroundElectrocardiogram (ECG) signals are inevitably contaminated with various kinds of noises during acquisition and transmission. The presence of noises may produce the inappropriate information on cardiac health, thereby preventing specialists from making correct analysis.MethodsIn this paper, an efficient strategy is proposed to denoise ECG signals, which employs a time-frequency framework based on S-transform (ST) and combines bi-dimensional empirical mode decomposition (BEMD) and non-local means (NLM). In the method, the ST maps an ECG signal into a subspace in the time frequency domain, then the BEMD decomposes the ST-based time-frequency representation (TFR) into a series of sub-TFRs at different scales, finally the NLM removes noise and restores ECG signal characteristics based on structural self-similarity.ResultsThe proposed method is validated using numerous ECG signals from the MIT-BIH arrhythmia database, and several different types of noises with varying signal-to-noise (SNR) are taken into account. The experimental results show that the proposed technique is superior to the existing wavelet based approach and NLM filtering, with the higher SNR and structure similarity index measure (SSIM), the lower root mean squared error (RMSE) and percent root mean square difference (PRD).ConclusionsThe proposed method not only significantly suppresses the noise presented in ECG signals, but also preserves the characteristics of ECG signals better, thus, it is more suitable for ECG signals processing.

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The effectiveness of case management for cancer patients: an umbrella review

Cited by 42 publications

References 36 publications

Generating Team-Based Strategies to Reduce Health Inequity in Cancer Care

Generating Team-Based Strategies to Reduce Health Inequity in Cancer Care

The applications of internet of things in smart healthcare sectors: a bibliometric and deep study

A novel approach for denoising electrocardiogram signals to detect cardiovascular diseases using an efficient hybrid scheme

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