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Impact of Electronic Self-Assessment and Self-Care Technology on Adherence to Clinician Recommendations and Self-Management Activity for Cancer Treatment-Related Symptoms: Secondary Analysis of a Randomized Controlled Trial.

ABSTRACT: BACKGROUND:Patients undergoing cancer treatment experience symptoms that negatively affect their quality of life and adherence to treatment. The early identification and management of treatment-related symptoms are critical to prevent symptom distress due to unmanaged symptoms. However, the early identification and management of treatment-related symptoms are complex as most cancer treatments are delivered on an outpatient basis where patients are granted less face-to-face time with clinicians. The Electronic Symptom Assessment and Self-Care (ESRA-C) promotes participant self-management of treatment-related symptoms by providing participants with communication coaching and symptom self-report, education, and tracking features. While the ESRA-C intervention has been demonstrated to improve symptom distress significantly, little is known as to how the ESRA-C influenced participants' self-management practices and adherence to clinician recommendations for symptom/quality of life issues (SQIs). OBJECTIVE:To compare participant adherence to clinician recommendations and additional self-management strategy use for SQIs between ESRA-C intervention and control (electronic symptom assessment and participant symptom reports alone) group participants. Secondarily, we explored the impact of participant adherence to clinician recommendations and additional self-management strategy use for SQIs on symptom control, symptom management satisfaction, and symptom distress. Lastly, we examined baseline predictors of participant adherence to clinician recommendations and additional self-management strategy use for SQIs. METHODS:This study presents an analysis of a randomized controlled trial. Participants beginning a new chemotherapy or radiotherapy regimen were recruited from oncology outpatient centers and were randomized to receive the ESRA-C intervention or control during treatment. Patients were included in this analysis if they remained on study through the duration of treatment and self-reported at least one bothersome SQI three-to-six weeks after beginning treatment. The Symptom Distress Scale-15 and Self-Management of SQIs Questionnaire were completed two weeks later. Based on Self-Management of SQIs Questionnaire ratings, participants were placed into adherence to clinician recommendations (adhered/did not adhere/did not receive recommendations) and additional self-management strategy use (yes/no) categories. RESULTS:Most participants were adherent to clinician recommendations (273/370, 73.8%), while fewer used additional self-management strategies for SQIs (182/370, 49.2%). There were no differences in the frequency of participant adherence to clinician recommendations (chi-square test, P=.99) or self-management strategy use (chi-square test, P=.80) between intervention (n=182) and control treatment groups (n=188). Participants who received clinician recommendations reported the highest treatment satisfaction (n=355, P<.001 by analysis of variance; ANOVA), although lowest distress was reported by participants who did not follow clinician recommendations (n=322, P=.04 by ANOVA) for top 2 SQIs. Women (n=188) reported greater additional self-management strategy use than men (n=182, P=0.03 by chi-square test). CONCLUSIONS:ESRA-C intervention use did not improve participants' adherence to clinician recommendations or additional self-management strategy use for SQIs in comparison to the control. Future research is needed to determine which factors are important in improving patients' self-management practices and symptom distress following ESRA-C use. TRIAL REGISTRATION:ClinicalTrials.gov NCT00852852; https://clinicaltrials.gov/ct2/show/NCT00852852 (Archived by WebCite at http://www.webcitation.org/73rEhNWkU).

SUBMITTER: Knoerl R

PROVIDER: S-EPMC6329427 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Impact of Electronic Self-Assessment and Self-Care Technology on Adherence to Clinician Recommendations and Self-Management Activity for Cancer Treatment-Related Symptoms: Secondary Analysis of a Randomized Controlled Trial.

Knoerl Robert R Hong Fangxin F Blonquist Traci T Berry Donna D

JMIR cancer 20190108 1

<h4>Background</h4>Patients undergoing cancer treatment experience symptoms that negatively affect their quality of life and adherence to treatment. The early identification and management of treatment-related symptoms are critical to prevent symptom distress due to unmanaged symptoms. However, the early identification and management of treatment-related symptoms are complex as most cancer treatments are delivered on an outpatient basis where patients are granted less face-to-face time with clin ...[more]

PMID: 30622093

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Project description:BACKGROUND:The 2007 Guidelines for the Diagnosis and Management of Asthma provide evidence-based recommendations to improve asthma care. Limited national-level data are available about clinician agreement and adherence to these guidelines. OBJECTIVE:To assess clinician-reported adherence with specific guideline recommendations, as well as agreement with and self-efficacy to implement guidelines. METHODS:We analyzed 2012 National Asthma Survey of Physicians data for 1412 primary care clinicians and 233 asthma specialists about 4 cornerstone guideline domains: asthma control, patient education, environmental control, and pharmacologic treatment. Agreement and self-efficacy were measured using Likert scales; 2 overall indices of agreement and self-efficacy were compiled. Adherence was compared between primary care clinicians and asthma specialists. Logistic regression models assessed the association of agreement and self-efficacy indices with adherence. RESULTS:Asthma specialists expressed stronger agreement, higher self-efficacy, and greater adherence with guideline recommendations than did primary care clinicians. Adherence was low among both groups for specific core recommendations, including written asthma action plan (30.6% and 16.4%, respectively; P < .001); home peak flow monitoring, (12.8% and 11.2%; P = .34); spirometry testing (44.7% and 10.8%; P < .001); and repeated assessment of inhaler technique (39.7% and 16.8%; P < .001). Among primary care clinicians, greater self-efficacy was associated with greater adherence. For specialists, self-efficacy was associated only with increased odds of spirometry testing. Guideline agreement was generally not associated with adherence. CONCLUSIONS:Agreement with and adherence to asthma guidelines was higher for specialists than for primary care clinicians, but was low in both groups for several key recommendations. Self-efficacy was a good predictor of guideline adherence among primary care clinicians but not among specialists.

Project description:ImportanceIt is unclear whether mobile technology hypertension self-management programs are associated with blood pressure (BP) control.ObjectiveTo examine whether engagement with a hypertension self-management program with a BP monitor and connected smartphone application with clinically based digital coaching was associated with BP control during a follow-up period of as long as 3 years.Design, setting, and participantsThis cohort study enrolled US adults with elevated BP or hypertension between January 1, 2015, and July 1, 2020. The hypertension self-management program was provided through the participant's (or their spouse's) employer health plan.ExposuresProgram engagement, defined by average number of application sessions.Main outcomes and measuresSystolic and diastolic BP measured by a US Food and Drug Administration-cleared BP monitor, with categories defined as normal (systolic BP, <120 mm Hg), elevated (systolic BP, 120-129 mm Hg), stage 1 hypertension (systolic BP, 130-139 mm Hg), and stage 2 hypertension (systolic BP ≥140 mm Hg). Other measures included age, gender, depression, anxiety, diabetes, high cholesterol, smoking, geographic region, area deprivation index, self-reported weight, and device-measured physical activity (steps per day).ResultsAmong 28 189 participants (median [IQR] age, 51 [43-58] years; 9424 women [40.4%]; 13 902 men [59.6%]), median (IQR) baseline systolic BP was 129.5 mm Hg (120.5-139.6 mm Hg) and diastolic BP was 81.7 mm Hg (75.7-88.4 mm Hg). Median systolic BP at 1 year improved at least 1 category for 495 of 934 participants (53.0%) with baseline elevated BP, 673 of 966 (69.7%) with baseline stage 1 hypertension, and 920 of 1075 (85.7%) with baseline stage 2 hypertension. Participants in the program for 3 years had a mean (SEM) systolic BP reduction of 7.2 (0.4), 12.2 (0.7), and 20.9 (1.7) mm Hg compared with baseline for those starting with elevated, stage 1 hypertension, and stage 2 hypertension, respectively. Greater engagement was associated with lower systolic BP over time (high-engagement group: 131.2 mm Hg; 95% CI, 115.5-155.8 mm Hg; medium-engagement group: 133.4 mm Hg; 95% CI 116.3-159.5 mm Hg; low-engagement group: 135.5 mm Hg; 95% CI, 117.3-164.8 mm Hg; P < .001); these results persisted after adjusting for age, gender, depression, anxiety, diabetes, high cholesterol, smoking, area deprivation index rank, and US region, which was partially mediated by greater physical activity. A very high BP (systolic BP >180 mm Hg) was observed 11 637 times from 3778 participants. Greater engagement was associated with lower risk of very high BP; the estimated probability of a very high BP was greater in the low-engagement group (1.42%; 95% CI, 1.26%-1.59%) compared with the medium-engagement group (0.79%; 95% CI, 0.71%-0.87%; P < .001) and the high-engagement group (0.53%; 95% CI, 0.45%-0.60%; P < .001 for comparison with both groups).Conclusions and relevanceThe findings of this study suggest that a mobile technology hypertension self-management program can support long-term BP control and very high BP detection. Such programs may improve real-world BP monitoring and control.

Project description:Urinary incontinence is involuntary leakage of urine and can affect people of all ages. Incidence rises as people age, often because of reduced mobility or conditions affecting the nervous system, such as dementia and stroke. Urinary incontinence can be a distressing condition and can harm a person's physical, financial, social, and emotional well-being. People with urinary incontinence are susceptible to skin irritation, pressure sores, and urinary tract infections. Urinary incontinence is also associated with an increased risk of falls in older adults.This health technology assessment examined the effectiveness of, budget impact of, and patient values and preferences about electronic monitoring systems to assess urinary incontinence for residents of long-term care homes or geriatric hospital inpatients with complex conditions.A clinical evidence review of the published clinical literature was conducted to June 9, 2017. Critical appraisal of the clinical evidence included assessment of risk of bias and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria to reflect the certainty of the evidence.We calculated the funding required for an electronic urinary incontinence monitoring system in the first year of implementation (when facilities would buy the systems) and in subsequent years.We interviewed six people with urinary incontinence and two caregivers, who described ways urinary incontinence affected daily life.We included one observational study in the clinical review. Most of the 31 participants in the observational study were female (78%) and required high levels of care, primarily because of cognitive impairment. The quality of evidence for all outcomes was very low owing to potential risk of bias and indirectness. We are consequently uncertain about how electronic monitoring systems affect management of urinary incontinence.For patients living in long-term care homes who are eligible for the technology, we estimated that an electronic monitoring system to assess urinary incontinence would cost $6.4 million in the first year of implementation and $1.6 million in subsequent years.Patients said urinary incontinence reduced their independence and social life and adversely affected their quality of life. Incontinence made them embarrassed and reduced their self-esteem. Several respondents mentioned how expensive supplies to manage incontinence were.The effectiveness of using the electronic monitoring system to assess urinary incontinence is uncertain because of the very low quality of the evidence. Introducing electronic monitoring systems would result in incremental costs, and there would be savings only if the systems substantially reduced incontinence.

Project description:BackgroundAccurate measurement and monitoring of patient medication adherence is a global challenge because of the absence of gold standard methods for adherence measurement. Recent attention has been directed toward the adoption of technologies for medication adherence monitoring, as they provide the opportunity for continuous tracking of individual medication adherence behavior. However, current medication adherence monitoring technologies vary according to their technical features and data capture methods, leading to differences in their respective advantages and limitations. Overall, appropriate criteria to guide the assessment of medication adherence monitoring technologies for optimal adoption and use are lacking.ObjectiveThis study aims to provide a narrative review of current medication adherence monitoring technologies and propose a set of technology assessment criteria to support technology development and adoption.MethodsA literature search was conducted on PubMed, Scopus, CINAHL, and ProQuest Technology Collection (2010-present) using the combination of keywords medication adherence, measurement technology, and monitoring technology. The selection focused on studies related to medication adherence monitoring technology and its development and use. The technological features, data capture methods, and potential advantages and limitations of the identified technology applications were extracted. Methods for using data for adherence monitoring were also identified. Common recurring elements were synthesized as potential technology assessment criteria.ResultsOf the 3865 articles retrieved, 98 (2.54%) were included in the final review, which reported a variety of technology applications for monitoring medication adherence, including electronic pill bottles or boxes, ingestible sensors, electronic medication management systems, blister pack technology, patient self-report technology, video-based technology, and motion sensor technology. Technical features varied by technology type, with common expectations for using these technologies to accurately monitor medication adherence and increase adoption in patients' daily lives owing to their unobtrusiveness and convenience of use. Most technologies were able to provide real-time monitoring of medication-taking behaviors but relied on proxy measures of medication adherence. Successful implementation of these technologies in clinical settings has rarely been reported. In all, 28 technology assessment criteria were identified and organized into the following five categories: development information, technology features, adherence to data collection and management, feasibility and implementation, and acceptability and usability.ConclusionsThis narrative review summarizes the technical features, data capture methods, and various advantages and limitations of medication adherence monitoring technology reported in the literature and the proposed criteria for assessing medication adherence monitoring technologies. This collection of assessment criteria can be a useful tool to guide the development and selection of relevant technologies, facilitating the optimal adoption and effective use of technology to improve medication adherence outcomes. Future studies are needed to further validate the medication adherence monitoring technology assessment criteria and construct an appropriate technology assessment framework.

Project description:BackgroundThe National Cancer Institute's Common Terminology Criteria for Adverse Events (NCI-CTCAE) reporting system is widely used by clinicians to measure patient symptoms in clinical trials. The European Organization for Research and Treatment of Cancer's Quality of Life core questionnaire (EORTC QLQ-C30) enables cancer patients to rate their symptoms related to their quality of life. We examined the extent to which patient and clinician symptom scoring and their agreement could contribute to the estimation of overall survival among cancer patients.MethodsWe analyzed baseline data regarding six cancer symptoms (pain, fatigue, vomiting, nausea, diarrhea, and constipation) from a total of 2279 cancer patients from 14 closed EORTC randomized controlled trials. In each trial that was selected for retrospective pooled analysis, both clinician and patient symptom scoring were reported simultaneously at study entry. We assessed the extent of agreement between clinician vs patient symptom scoring using the Spearman and kappa correlation statistics. After adjusting for age, sex, performance status, cancer severity, and cancer site, we used Harrell concordance index (C-index) to compare the potential for clinician-reported and/or patient-reported symptom scores to improve the accuracy of Cox models to predict overall survival. All P values are from two-sided tests.ResultsPatient-reported scores for some symptoms, particularly fatigue, did differ from clinician-reported scores. For each of the six symptoms that we assessed at baseline, both clinician and patient scorings contributed independently and positively to the predictive accuracy of survival prognostication. Cox models of overall survival that considered both patient and clinician scores gained more predictive accuracy than models that considered clinician scores alone for each of four symptoms: fatigue (C-index = .67 with both patient and clinician data vs C-index = .63 with clinician data only; P <.001), vomiting (C-index = .64 vs .62; P = .01), nausea (C-index = .65 vs .62; P < .001), and constipation (C-index = .62 vs .61; P = .01).ConclusionPatients provide a subjective measure of symptom severity that complements clinician scoring in predicting overall survival.

Dataset Information

Impact of Electronic Self-Assessment and Self-Care Technology on Adherence to Clinician Recommendations and Self-Management Activity for Cancer Treatment-Related Symptoms: Secondary Analysis of a Randomized Controlled Trial.

Publications

Impact of Electronic Self-Assessment and Self-Care Technology on Adherence to Clinician Recommendations and Self-Management Activity for Cancer Treatment-Related Symptoms: Secondary Analysis of a Randomized Controlled Trial.

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