Background Digital health coaching is an increasingly common diabetes self-management support strategy for individuals with type 2 diabetes and has been linked to positive mental and physical health outcomes. However, the relationship between baseline risk and outcomes is yet to be evaluated in a real-world setting. Objective The purpose of this real-world study was to evaluate trends in digital health coaching outcomes by baseline hemoglobin A1c (HbA1c) to better understand which populations may experience the greatest clinical and psychosocial benefit. Methods A retrospective cohort study design was used to evaluate program effect in a convenience sample of participants in a 12-week digital health coaching program administered by Pack Health. Participants were referred through their health care provider, payer, or employer. The program included patient-centered lifestyle counseling and psychosocial support delivered via telephone, text, and/or email. Self-reported HbA1c and weight were collected at baseline and completion. Physical and mental health were assessed using the Patient-Reported Outcomes Measurement Information System (PROMIS) Global Health Short Form and the Diabetes Distress Scale-2. Changes in HbA1c, weight, BMI, and physical and mental health were analyzed within three participant cohorts stratified by baseline HbA1c level. Results Participants with complete HbA1c data sets (n=226) were included in the analysis. The sample population was 71.7% (162/226) female, with 61.5% (139/226) identifying as white and 34.1% (77/226) as black. Most participants (184/226, 81.4%) reported a baseline HbA1c ≥7%, and 20.3% (46/226) were classified as high risk (HbA1c >9%). Across HbA1c cohorts, the mean baseline BMI was 35.83 (SD 7.79), and the moderate-risk cohort (7% ≤ HbA1c ≤ 9%) reported the highest mean value (36.6, SD 7.79). At 12 weeks, patients reported a significant decrease in HbAlc, and high-risk participants reduced their levels by the greatest margin (2.28 points; P<.001). Across cohorts, BMI improved by 0.82 (P<.001), with the moderate-risk cohort showing the greatest reduction (−0.88; P<.001). Overall, participants reported significant improvements for PROMIS scores, with the greatest change occurring in the high-risk cohort for whom physical health improved 3.84 points (P<.001) and mental health improved 3.3 points (P<.001). However, the lowest-risk cohort showed the greatest improvements in diabetes distress (−0.76; P=.005). Conclusions Acknowledging the limitations in this real-world study design, the results reported here suggest that adults with type 2 diabetes with a high baseline HbA1c or high BMI may benefit the most from patient-centered digital health coaching programs when compared to their lower risk counterparts. While all participants improved in physical and mental health categories, participants with high HbA1c experienced the greatest HbA1c reduction and individuals with the highest baseline BMI lost the most weight. These results may be used to inform referrals for patients who are more likely to benefit from digital health coaching.
Objective: To report the psychometric properties of the COmprehensive Score for financial Toxicity (COST) patient-reported outcome measure (PROM), an 11-item scale previously validated among patients diagnosed with cancer and receiving chemotherapy. Methods: Data come from a cross-sectional survey (n = 2755 response rate of 87%) of participants in a remote digital health coaching intervention collected between January 2017 and February 2019. Results: COST demonstrated very good internal consistency ( Cronbach’s alpha = .89) and good convergent validity. Lower financial toxicity was associated with improved physical and mental well-being HRQOL measures after controlling for covariates ( b = 0.13, P < .0001; b = 0.28, P < .0001, respectively). Supplemental analyses indicated that the COST instrument loaded on 2 factors. Conclusions: The COST measure of financial toxicity has good internal consistency and predictive validity in a sample of patients with chronic conditions. However, contrary to previous research examining the psychometric properties of COST in a sample of individuals with cancer, which found COST to be unidimensional, our analyses indicated that the COST measure of financial toxicity is multidimensional in a sample of individuals with chronic conditions. In particular, the items that asked about “general financial wellbeing” loaded on the second factor while “illness-related financial wellbeing” loaded on the first.
Background: Diabetes Self-Management Support (DSMS) programs are designed to assist people with diabetes as they implement and sustain the behaviors needed to manage their disease. In-person DSMS programs have many attendance barriers that can be mitigated through digital delivery. This study looks at results from the only ADA recognized online digital DSMS program (as of Jan 2020). The program collects diverse Patient Reported Outcomes (PROs) to track patient progress and program impact. This analysis presents digital DSMS program outcomes, focusing on individuals with an A1c >9%, for whom health risk is markedly increased. Methods: A retrospective analysis of individuals enrolled in a 12-week digital DSMS program evaluated changes from baseline to program completion. Changes in anxiety, depression, financial toxicity, overall physical and mental health, medication adherence, stress, diabetes distress, body mass index, and A1c were evaluated for cohorts delineated by baseline A1c values. Descriptive statistics define frequency and data collected from validated PROs were analyzed to evaluate the outcomes of the digital DSMS program. Results: To date, 1,349 people with diabetes have participated in the digital DSMS program. Of these, 843 completed and provided both baseline and 3-month outcome measures. Across all A1c categories, there were significant improvements in physical health, medication adherence, stress, and BMI (p < 0.05). Elevated A1c categories (A1c ≥ 7%) all showed decreased A1c values at month 3 compared to enrollment (p < 0.01), people with higher baseline A1c values saw the greatest decrease, A1c ≥ 10% decreased 4.17% (pre:11.32 - post: 7.15%), A1c 9-9.9% decreased 1.34% (pre: 9.29 - post: 7.95%). Conclusions: Outcomes suggest that a digital DSMS program can improve glycemic control, as previously reported, but also PROs, and that a digital delivery of a DSMS program is an effective intervention, particularly for individuals with elevated A1c for whom health risks are elevated. Disclosure J. Patterson: None. M. Allison: Employee; Self; Pack Health. K.J. Brassil: None. S.B. Burton: None. T.T. Norbu: None. M. Rasulnia: None. D. Patel: None.
BACKGROUND Digital health coaching is an increasingly common diabetes self-management support strategy for individuals with type 2 diabetes and has been linked to positive mental and physical health outcomes. However, the relationship between baseline risk and outcomes has yet to be evaluated in a real-world setting. OBJECTIVE The purpose of this real-world study was to evaluate trends in digital health coaching outcomes by baseline A1c to better understand which populations may experience the greatest clinical and psychosocial benefit. METHODS Participants were referred to a 12-week digital health coaching program, administered by Pack Health, through their healthcare provider, payer or employer. The program included patient-centered lifestyle counseling and psychosocial support delivered via telephone, text and/or email. Self-reported A1c and weight were collected at baseline and completion. Physical and mental health were assessed using the PROMIS Global Health short form and the Diabetes Distress Scale-2. A retrospective cohort study design was used to evaluate program effect in a convenience sample of participants. Changes in Alc, weight, BMI, physical and mental health were analyzed within three participant cohorts stratified by baseline A1c level. RESULTS Participants with complete A1c datasets (n = 226) were included in the analysis. Participants were 71.68% female, with 61.50% identifying as white and 34.07% as black. Most participants (81.41%) reported a baseline A1c ≥ 7%, and 20.35% were classified as high-risk (A1c > 9%). Across A1c cohorts, the average baseline BMI was 35.83 (SD = 7.79), and the moderate risk cohort (7% ≤ A1c ≤ 9%) reported the highest average (36.6; SD = 7.77). At 12 weeks, patients reported a significant decrease in Alc, and high-risk participants reduced their levels by the greatest margin (2.28 points; P < .0001). Across cohorts, BMI improved by 0.82 (P < .0001), with the moderate risk cohort showing the greatest reduction (-0.88; P < .0001). Overall, participants reported significant improvements for PROMIS scores, with the greatest change occurring in the high-risk cohort for whom physical health improved 3.84 points (P < .001) and mental health improved 3.3 points (P < .001). However, the lowest risk cohort showed the greatest improvements in diabetes distress (-0.76; P < .0052). CONCLUSIONS Acknowledging the limitations in this real-world study design, the results reported here suggest that adults with type 2 diabetes with a high baseline A1c or high BMI may benefit the most from patient-centered digital health coaching programs when compared to their lower risk counterparts. While all participants improved in physical and mental health categories, participants with high A1c experienced the greatest A1c reduction, while individuals with the highest baseline BMI lost the most weight. These results may be used to inform referrals for patients who are more likely to benefit from digital health coaching.
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