Dataset Information

Comparison of Satisfaction With Comorbid Depression Care Models Among Low-Income Patients With Diabetes.

ABSTRACT: Introduction: Patient satisfaction is a patient-reported outcome with the potential to assess and improve the quality of newer care-management models such as remote patient monitoring using telecommunication technology.

Objective: To evaluate differences in patient satisfaction among 3 care management groups in a comparative effectiveness trial.

Methods: This study analyzed a comparative effectiveness trial that tested automated remote assessment technology-facilitated comorbid depression care-management (TC, n = 254) in comparison to team-supported depression care (SC, n = 228) and usual primary care (UC, n = 218) among low-income patients with type 2 diabetes. Relationships between patient satisfaction and care group were evaluated at each 6-month phase up to 18 months using linear regression models that controlled for depression status, diabetes symptoms, patient characteristics, and study group differences.

Results: While receiving care management, SC and TC patients were significantly more satisfied with depression care than UC patients. No consistently significant associations between patient satisfaction and patient characteristics or disease symptoms were found.

Conclusions: Patient satisfaction was found to be influenced by elements of care-management, not by patient characteristics or disease symptoms. Results suggest greater patient satisfaction with depression care in a care-management model than UC, whether through clinician team support or automated remote monitoring technology.

SUBMITTER: Evanson O

PROVIDER: S-EPMC7705841 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Comparison of Satisfaction With Comorbid Depression Care Models Among Low-Income Patients With Diabetes.

Evanson Olivia O Wu Shinyi S

Journal of patient experience 20191031 5

<h4>Introduction</h4>Patient satisfaction is a patient-reported outcome with the potential to assess and improve the quality of newer care-management models such as remote patient monitoring using telecommunication technology.<h4>Objective</h4>To evaluate differences in patient satisfaction among 3 care management groups in a comparative effectiveness trial.<h4>Methods</h4>This study analyzed a comparative effectiveness trial that tested automated remote assessment technology-facilitated comorbi ...[more]

PMID: 33294609

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Project description:BACKGROUND:Remote patient monitoring is increasingly integrated into health care delivery to expand access and increase effectiveness. Automation can add efficiency to remote monitoring, but patient acceptance of automated tools is critical for success. From 2010 to 2013, the Diabetes-Depression Care-management Adoption Trial (DCAT)-a quasi-experimental comparative effectiveness research trial aimed at accelerating the adoption of collaborative depression care in a safety-net health care system-tested a fully automated telephonic assessment (ATA) depression monitoring system serving low-income patients with diabetes. OBJECTIVE:The aim of this study was to determine patient acceptance of ATA calls over time, and to identify factors predicting long-term patient acceptance of ATA calls. METHODS:We conducted two analyses using data from the DCAT technology-facilitated care arm, in which for 12 months the ATA system periodically assessed depression symptoms, monitored treatment adherence, prompted self-care behaviors, and inquired about patients' needs for provider contact. Patients received assessments at 6, 12, and 18 months using Likert-scale measures of willingness to use ATA calls, preferred mode of reach, perceived ease of use, usefulness, nonintrusiveness, privacy/security, and long-term usefulness. For the first analysis (patient acceptance over time), we computed descriptive statistics of these measures. In the second analysis (predictive factors), we collapsed patients into two groups: those reporting "high" versus "low" willingness to use ATA calls. To compare them, we used independent t tests for continuous variables and Pearson chi-square tests for categorical variables. Next, we jointly entered independent factors found to be significantly associated with 18-month willingness to use ATA calls at the univariate level into a logistic regression model with backward selection to identify predictive factors. We performed a final logistic regression model with the identified significant predictive factors and reported the odds ratio estimates and 95% confidence intervals. RESULTS:At 6 and 12 months, respectively, 89.6% (69/77) and 63.7% (49/77) of patients "agreed" or "strongly agreed" that they would be willing to use ATA calls in the future. At 18 months, 51.0% (64/125) of patients perceived ATA calls as useful and 59.7% (46/77) were willing to use the technology. Moreover, in the first 6 months, most patients reported that ATA calls felt private/secure (75.9%, 82/108) and were easy to use (86.2%, 94/109), useful (65.1%, 71/109), and nonintrusive (87.2%, 95/109). Perceived usefulness, however, decreased to 54.1% (59/109) in the second 6 months of the trial. Factors predicting willingness to use ATA calls at the 18-month follow-up were perceived privacy/security and long-term perceived usefulness of ATA calls. No patient characteristics were significant predictors of long-term acceptance. CONCLUSIONS:In the short term, patients are generally accepting of ATA calls for depression monitoring, with ATA call design and the care management intervention being primary factors influencing patient acceptance. Acceptance over the long term requires that the system be perceived as private/secure, and that it be constantly useful for patients' needs of awareness of feelings, self-care reminders, and connectivity with health care providers. TRIAL REGISTRATION:ClinicalTrials.gov NCT01781013; https://clinicaltrials.gov/ct2/show/NCT01781013 (Archived by WebCite at http://www.webcitation.org/6e7NGku56).

Project description:PurposeTo determine the effectiveness of the Alleviating Depression Among Patients With Cancer (ADAPt-C) collaborative care management for major depression or dysthymia.Patients and methodsStudy patients included 472 low-income, predominantly female Hispanic patients with cancer age >or= 18 years with major depression (49%), dysthymia (5%), or both (46%). Patients were randomly assigned to intervention (n = 242) or enhanced usual care (EUC; n = 230). Intervention patients had access for up to 12 months to a depression clinical specialist (supervised by a psychiatrist) who offered education, structured psychotherapy, and maintenance/relapse prevention support. The psychiatrist prescribed antidepressant medications for patients preferring or assessed to require medication.ResultsAt 12 months, 63% of intervention patients had a 50% or greater reduction in depressive symptoms from baseline as assessed by the Patient Health Questionnaire-9 (PHQ-9) depression scale compared with 50% of EUC patients (odds ratio [OR] = 1.98; 95% CI, 1.16 to 3.38; P = .01). Improvement was also found for 5-point decrease in PHQ-9 score among 72.2% of intervention patients compared with 59.7% of EUC patients (OR = 1.99; 95% CI, 1.14 to 3.50; P = .02). Intervention patients also experienced greater rates of depression treatment (72.3% v 10.4% of EUC patients; P < .0001) and significantly better quality-of-life outcomes, including social/family (adjusted mean difference between groups, 2.7; 95% CI, 1.22 to 4.17; P < .001), emotional (adjusted mean difference, 1.29; 95% CI, 0.26 to 2.22; P = .01), functional (adjusted mean difference, 1.34; 95% CI, 0.08 to 2.59; P = .04), and physical well-being (adjusted mean difference, 2.79; 95% CI, 0.49 to 5.1; P = .02).ConclusionADAPt-C collaborative care is feasible and results in significant reduction in depressive symptoms, improvement in quality of life, and lower pain levels compared with EUC for patients with depressive disorders in a low-income, predominantly Hispanic population in public sector oncology clinics.

Project description:BACKGROUND:Diabetes is a major contributor to global death and disability. Text-messaging interventions hold promise for improving diabetes outcomes through better knowledge and self-management. OBJECTIVE:The aim of this study was to examine the implementation and impact of a diabetes text-messaging program targeted primarily for low-income Latino patients receiving care at 2 federally qualified health centers (FQHCs). METHODS:A mixed-methods, quasi-experimental research design was employed for this pilot study. A total of 50 Spanish or English-speaking adult patients with diabetes attending 2 FQHC sites in Los Angeles from September 2015 to February 2016 were enrolled in a 12-week, bidirectional text-messaging program. A comparison group (n=160) was constructed from unexposed, eligible patients. Demographic data and pre/post clinical indicators were compared for both the groups. Propensity score weighting was used to reduce selection bias, and over-time differences in clinical outcomes between groups were estimated using individual fixed-effects regression models. Population-averaged linear models were estimated to assess differential effects of patient engagement on each clinical indicator among the intervention participants. A sample of intervention patients (n=11) and all implementing staff (n=8) were interviewed about their experiences with the program. Qualitative data were transcribed, translated, and analyzed to identify common themes. RESULTS:The intervention group had a mean glycated hemoglobin (HbA1c) reduction of 0.4 points at follow-up, relative to the comparison group (P=.06). Patients who were more highly engaged with the program (response rate ≥median of 64.5%) experienced a 2.2 point reduction in HbA1c, relative to patients who were less engaged, controlling for demographic characteristics (P<.001). Qualitative analyses revealed that many participants felt supported, as though "someone was worrying about [their] health." Participants also cited learning new information, setting new goals, and receiving helpful reminders. Staff and patients highlighted strategies to improve the program, including incorporating patient responses into in-person clinical care and tailoring the messages to patient knowledge. CONCLUSIONS:A diabetes text-messaging program provided instrumental and emotional support for participants and may have contributed to clinically meaningful improvements in HbA1c. Patients who were more engaged demonstrated greater improvement. Program improvements, such as linkages to clinical care, hold potential for improving patient engagement and ultimately, improving clinical outcomes.

Dataset Information

Comparison of Satisfaction With Comorbid Depression Care Models Among Low-Income Patients With Diabetes.

Publications

Comparison of Satisfaction With Comorbid Depression Care Models Among Low-Income Patients With Diabetes.

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