Enhancing Diabetes Care at Home: A Comprehensive Disease Management Program

Abstract

Introduction

Chronic disease management programs (CDMPs) are crucial for individuals living with diabetes, and incorporating health coaching can significantly improve care coordination and self-management. This study investigates the impact of A Diabetes Home Care Disease Management Program, comparing a face-to-face group health coaching approach (with telephone follow-up) to telephone-only health coaching over 12 months. The primary aim was to evaluate changes in diabetes knowledge, self-reported health status, diabetes distress, body mass index (BMI), and glycemic control in patients participating in these different models of a diabetes home care disease management program.

Methods

In 2013, patients with diabetes at Royal North Shore Hospital in Sydney, Australia, enrolled in a health coaching program designed as a diabetes home care disease management program. Participants completed questionnaires at baseline, 3, 6, and 12 months to assess diabetes knowledge, health status, and diabetes distress. Glycemic control (HbA1c) and BMI were measured at baseline and 12 months. The study compared outcomes for patients who attended a face-to-face CDMP session with telephone follow-up against those who received telephone-only health coaching as part of their diabetes home care disease management program.

Results

A total of 238 patients participated, with 178 in the face-to-face CDMP session group and 60 in the telephone-only health coaching group. While BMI remained unchanged in both groups, significant improvements were observed in glycemic control among patients with elevated baseline HbA1c (>7%), decreasing from 8.5% (SD, 1.0%) to 7.9% (SD, 1.0%) (P = .03). Patients reporting lower health status at the start of the program showed improvement, increasing from 4.4 (SD, 0.5) to 3.7 (SD, 0.9) (P = .001). Across all participants, diabetes knowledge scores increased from 24.4 (SD, 2.4) to 25.2 (SD, 2.4) (P < .001). Notably, diabetes distress significantly decreased in patients who initially reported moderate to severe distress (3.8 [SD, 0.6] to 3.0 [SD, 0.4]; P = .003).

Conclusion

This study demonstrates that diabetes home care disease management programs incorporating health coaching can effectively improve glycemic control and alleviate diabetes distress, particularly for individuals who begin with higher levels of distress or poorer glycemic management. These findings highlight the potential of tailored diabetes home care strategies to enhance patient outcomes and support effective chronic disease management.

Introduction

Diabetes mellitus is a pervasive chronic condition demanding continuous management to mitigate illness and prevent premature mortality (1). The daily challenges of living with diabetes often lead to diminished quality of life and significant diabetes distress (2,3). Diabetes distress, characterized as the emotional burden associated with managing diabetes, coupled with reduced quality of life and insufficient diabetes knowledge, can severely hinder self-management practices and glycemic control. This, in turn, elevates the risk of developing diabetes-related complications (4,5). While the impact of diabetes on a patient’s overall well-being and life satisfaction is not always systematically evaluated in routine clinical settings, such assessments are invaluable for crafting personalized diabetes management plans. A robust diabetes home care disease management program should consider these factors for holistic patient care.

Effective diabetes self-management education programs are recognized as powerful tools for engaging patients in their care decisions and fostering improved health outcomes (6,7). Research indicates that consistent participation in diabetes group education sessions over a year enhances diabetes knowledge and problem-solving skills (8). Similarly, diabetes self-management programs have been shown to improve both quality of life and reduce diabetes distress in individuals with type 1 and type 2 diabetes (9,10). Health coaching, a patient-centered educational approach that emphasizes problem-solving and goal setting, emerges as a valuable complement to standard diabetes education. It holds promise for improving glycemic control and enhancing self-reported health status (11,12), making it an ideal component of a diabetes home care disease management program.

In 2013, Royal North Shore Hospital (RNSH) in Sydney introduced a chronic disease management program (CDMP) that integrated health coaching, specifically designed as a diabetes home care disease management program model. This innovative approach diverged from traditional group diabetes education by prioritizing patient-defined goals and targets. This study aimed to evaluate the impact of this educational intervention on patients’ self-reported health status, diabetes distress, diabetes knowledge, body mass index (BMI), and glycemic control over a 12-month follow-up period. The study considered both face-to-face sessions supplemented with telephone support and telephone health coaching alone, aiming to understand the effectiveness of different delivery methods within a diabetes home care disease management program. The ultimate goal was to identify patient profiles that would benefit most significantly from such programs, thereby enabling a more targeted and efficient approach to program enrollment and resource allocation.

Methods

Diabetes Chronic Disease Management Program within a Home Care Context

The health coaching program, facilitated by the Department of Diabetes, Endocrinology and Metabolism at RNSH, was part of the Northern Sydney Local Health District CDMP. This CDMP targets individuals with chronic conditions—including diabetes, coronary artery disease, chronic obstructive pulmonary disease, congestive heart failure, and hypertension—who are at heightened risk of hospital readmission (13). The program’s services are designed to enhance access to and coordination of healthcare services, offering additional support for effective diabetes self-management. The overarching aim is to reduce complications, improve overall health, and prevent hospitalizations (14), all within a framework adaptable to a diabetes home care disease management program. All patients enrolled in the CDMP at RNSH were invited to participate in the health coaching program; over half (53%) accepted in 2013. Eligibility criteria included being English-speaking, aged 16 years or older, and diagnosed with type 1 or type 2 diabetes. These criteria are important to consider when adapting such programs for broader diabetes home care disease management program implementation.

Diabetes Health Coaching Modalities: Face-to-Face and Telephone

The diabetes health coaching program at RNSH offered two primary modalities: a face-to-face group education session known as the “Empowerment Program,” followed by 12 months of telephone support from a health coach (a diabetes nurse educator); and a telephone-only coaching option for patients unable to attend in-person sessions. The telephone coaching commenced with an initial educational call and continued with follow-up calls from the health coach for 12 months. The frequency of these telephone calls was tailored to patient preference, ranging from weekly to three times per month, with most patients opting for monthly calls. This flexible approach is crucial for a successful diabetes home care disease management program.

Both modalities of the diabetes health coaching program utilized a diabetes conversation map to guide initial discussions, focusing on managing diabetes complications and associated risk factors. Patients received education and advice on healthy eating, recommended physical activity levels, and strategies for preventing diabetes complications. Additionally, the program provided information on diabetes-specific health targets and recommendations for scheduling primary care provider visits to review progress and conduct necessary blood glucose testing. Patients were encouraged to set personal goals related to their diabetes management, such as daily exercise duration, healthy eating goals, or medication adherence. Health coaches guided patients in developing effective strategies to achieve these goals. Subsequent telephone calls served as check-ins for patients to report on their progress, evaluate the effectiveness of their strategies, and adjust their plans as needed. This structured, goal-oriented approach is central to an effective diabetes home care disease management program.

Patient Assessments in the CDMP Health Coaching Program

To assess participants’ understanding of diabetes, the study employed the Diabetes, Hypertension and Hyperlipidemia (DHL) knowledge instrument (15). This validated instrument, originally evaluated in a Malaysian diabetes population (15), includes questions assessing patient knowledge of the importance of glucose, blood pressure, and lipid control in minimizing diabetes complications. The DHL questionnaire comprises 28 questions, with each correct answer scoring one point, yielding a maximum possible score of 28. Self-reported health status was measured using the first question from the Short-Form 36 Quality of Life Instrument (SF-1) (16,17). A score of 4 or higher (maximum 6) on the SF-1 indicates poor health status (17). Diabetes distress was evaluated using the Diabetes Distress Scale (DDS) (18,19). The DDS calculates an overall score (maximum 6) from 17 questions, each rated on a scale of 1 to 6; a score of 3 or higher signifies moderate to severe diabetes distress (20). The DHL, SF-1, and DDS questionnaires were administered at four points: baseline, 3 months, 6 months, and 12 months. These instruments are validated for use in diabetes populations (16–20) and provide critical data for evaluating a diabetes home care disease management program.

Glycemic Control, BMI, and Medical History Data

Glycemic control was assessed using HbA1c measurements taken at baseline (just before health coaching referral) and at the 12-month routine diabetes complications screening appointment. BMI was calculated from weight and height measurements taken at baseline and 12 months (BMI = weight in kilograms [kg] / height in meters [m] squared). Data on dyslipidemia, hypertension, and diabetes complications (retinopathy, neuropathy, or chronic kidney disease, defined clinically by an estimated glomerular filtration rate [eGFR] <60 mL/min/1.73 m2) were extracted from patient medical records. These objective measures are essential for assessing the clinical impact of a diabetes home care disease management program.

Study Design and Setting

This study was an audit of longitudinal data collected prospectively to examine the impact of a diabetes health coaching program on patient outcomes over 12 months. Participants resided within the RNSH catchment area, part of Sydney’s Northern Sydney Local Health District, an area with high socioeconomic status (21). The study received ethical approval from the Northern Sydney Local Health District Human Research Ethics Committee (reference no. RESP/16/58). The demographic context is important for understanding the generalizability of findings to other diabetes home care disease management program settings.

Statistical Analysis

Statistical analyses were performed using GraphPad Prism Version 6. Changes in patient-reported diabetes knowledge, health status, and diabetes distress over time were analyzed using Student’s paired t test for parametric data and Wilcoxon matched-pairs signed-rank test for nonparametric data. Repeated measures were analyzed using one-way ANOVA for parametric data and the Friedman test for nonparametric data. Group differences were assessed using Student’s unpaired t test or the Mann–Whitney test, as appropriate. Changes in HbA1c and BMI were evaluated with paired t tests. Statistical significance was set at P < .05. These statistical methods are appropriate for analyzing the effectiveness of a diabetes home care disease management program.

Results

Patient Demographics and Baseline Characteristics

Between January and December 2013, 178 patients participated in face-to-face health coaching followed by telephone support, while 60 patients received telephone-only health coaching (Table 1). The majority (97.1%) of the cohort had type 2 diabetes, and most participants were older than 65 years. Approximately two-thirds of participants in both groups were women. These demographics reflect a typical population that might benefit from a diabetes home care disease management program.

Comorbidity rates were similar across both groups, with hypertension (69.3%) and dyslipidemia (91.2%) being the most prevalent. No significant differences in age or diabetes duration were observed between groups (Table 1). However, the telephone-only health coaching group presented with a higher baseline HbA1c (7.3%; P = .03) and BMI (31.1; P = .04), and a greater proportion were using insulin (46.7%; P = .001) (Table 1). These baseline differences are important to consider when interpreting outcomes in a diabetes home care disease management program context.

The completion rate for assessments at all time points was 31.1% (74 of 238 patients). Patients who did not complete all assessments were younger (mean age 67.0 years [SD, 10.0 years] vs 71.3 years [SD, 8.7 years]; P = .003) and had a higher baseline BMI (30.2 [SD, 5.3] vs 28.8 [SD, 5.6]; P = .02) compared to those who completed all assessments. No other significant differences were found. Evaluable data (baseline and 12-month data) were available for 50.4% of patients (120/238). Attrition is a common challenge in longitudinal studies of diabetes home care disease management program effectiveness.

Improvement in Diabetes Knowledge

The average baseline diabetes knowledge score for all participants (n = 212) was 24.4 (SD, 2.4). A statistically significant improvement in diabetes knowledge was observed among participants who completed assessments at 12 months, with scores increasing from a mean of 24.4 to 25.2 (SD, 2.2) (P < .001). This indicates that the diabetes home care disease management program positively impacted patient knowledge.

Figure 1. Diabetes Knowledge Improvement Through a Home Care Disease Management Program. This graph illustrates the improvement in diabetes knowledge scores among participants in a diabetes home care disease management program over a 12-month period, as measured by the DHL knowledge instrument. Part A shows data for all participants, and Part B focuses on those who completed all assessments, both demonstrating a statistically significant increase in knowledge.

Baseline diabetes knowledge scores were similar between the face-to-face and telephone-only coaching groups (mean score 24.3 [SD, 2.5] vs 25.1 [SD, 1.8]; P = .10). However, patients attending face-to-face sessions showed a significant improvement in diabetes knowledge at 12 months (mean score 24.3 [SD, 2.5] vs 25.4 [SD, 2.4]; P < .001), whereas the telephone-only group did not show significant improvement (mean score 25.1 [SD, 1.8] vs 25.0 [SD, 2.1]; P = .66). This suggests that face-to-face components may enhance knowledge acquisition in a diabetes home care disease management program.

Enhanced Self-Reported Health Status

At baseline, 27.3% of patients reported poor health status (SF-1 score ≥4). Patients with diabetes complications (retinopathy, neuropathy, chronic kidney disease) reported lower health status at baseline compared to those without complications (3.2 [SD, 1.0] vs 2.9 [SD, 1.0]; P = .01). Among patients with poor baseline health status (n = 65) who completed at least two assessments (n = 51), a significant improvement in health status was observed in 36 patients, from 4.4 [SD, 0.6] at baseline to 3.6 [SD, 1.1] at 6 months (P < .001) and 3.7 [SD, 0.9] at 12 months (P = .001) (Figure 2A). This demonstrates the potential of a diabetes home care disease management program to improve perceived health.

Patients on insulin (n = 68) had similar baseline health status scores to those on oral antihyperglycemic medications (3.2 [SD, 1.0] vs 3.0 [SD 1.0]). No significant difference in self-reported health status was found between face-to-face and telephone-only coaching groups at any time point. The method of delivery did not seem to impact the improvement in perceived health within this diabetes home care disease management program.

Figure 2. Improvements in Health Status and Diabetes Distress through a Home Care Disease Management Program. This figure illustrates the changes in self-reported health status and diabetes distress among participants in the diabetes home care disease management program. Panel A shows the improvement in self-reported health status for patients with poor baseline health status. Panel B demonstrates the reduction in diabetes distress for patients with moderate to high baseline distress.

Reduction in Diabetes Distress

Most participants (91.6%) exhibited low diabetes distress at baseline (DDS score <3). Among the subset with moderate to high baseline diabetes distress (DDS score >3) who completed at least two assessments (n = 17), a small but significant decrease in diabetes distress was observed at 6 months for 15 patients (DDS score 3.2 [SD, 0.7] vs 3.8 [SD, 0.6]; P = .04) and at 12 months for 10 patients (3.0 [SD, 0.4] vs 3.8 [SD, 0.6]; P = .003) compared to baseline (Figure 2B). This highlights the positive impact of a diabetes home care disease management program on emotional well-being.

Diabetes distress levels were similar across both coaching modalities (face-to-face or telephone-only) at each time point. The delivery method did not significantly affect the reduction in diabetes distress within this diabetes home care disease management program.

Glycemic Control Improvement and BMI Stability

The average baseline HbA1c was 7.0% (SD, 1.1%), with 81.5% of patients at or below the target HbA1c level (<7%). For patients with baseline HbA1c above the recommended target (>7%; n = 44), a significant improvement was observed at 12 months (8.5% [SD, 1.0%] vs 7.9% [SD, 1.0%]; P = .03). This indicates that the diabetes home care disease management program was effective in improving glycemic control for those who needed it most. The proportion of patients with poor baseline glycemic control (HbA1c >7%; n = 44) who achieved target HbA1c at 12 months was 20.05%. No significant difference in HbA1c improvement was found between coaching modalities.

No significant changes in BMI were observed at 12 months compared to baseline in either the face-to-face or telephone-only health coaching groups. Similarly, patients with significant obesity at baseline (BMI ≥35; n = 29) showed no BMI reduction at 12 months. The coaching method did not influence BMI changes over time. While the diabetes home care disease management program effectively improved other health metrics, it did not significantly impact BMI within the study timeframe.

Discussion

This study’s findings pinpoint the patient profiles that derive the most benefit from a 12-month diabetes health coaching CDMP, particularly within a diabetes home care disease management program framework. Patients who initially presented with high diabetes distress, poor self-reported health status, and limited diabetes knowledge experienced the most substantial improvements in these areas at both 6 and 12 months following CDMP initiation. The face-to-face health coaching component of the CDMP significantly enhanced general diabetes knowledge, a benefit not as pronounced with telephone health coaching alone. Furthermore, individuals with above-target HbA1c levels at baseline demonstrated significant improvements in glycemic control.

Identifying patients most likely to benefit from a CDMP or health coaching, especially within a diabetes home care disease management program, is clinically crucial. It allows for program tailoring, targeted screening prior to enrollment, and maximized patient outcomes while optimizing healthcare resource utilization. This targeted approach directly benefits patients and ensures efficient healthcare service delivery. Moreover, it facilitates the implementation of specific interventions to address areas where patients report the greatest distress or require additional support and education in managing their diabetes. Consequently, this analysis focused on patients with low self-reported health status, elevated diabetes distress, or above-target HbA1c at baseline. Health coaching, emphasizing patient-driven goal setting, empowers individuals to take control of their health, potentially contributing to reduced psychological stress related to diabetes, improved perceived health status, and decreased diabetes distress. This patient-centered approach is fundamental to a successful diabetes home care disease management program.

Our results align with Beverley et al.’s findings, which indicated that older patients (aged 60–75 years) experienced positive changes in quality of life and diabetes distress following diabetes education in behavioral interventions (22). Similarly, a recent study demonstrated that health coaching for type 2 diabetes patients improved life satisfaction and reduced depressive symptoms (23). A meta-analysis also concluded that self-management and education interventions for diabetes were most effective in patients with baseline depression symptoms or high stress levels (24), reinforcing our findings. In contrast to other studies (7,25), we did not observe overall glycemic control improvement across the entire cohort. This is likely because most participants (81.5%) had already achieved target HbA1c levels before program commencement and maintained this control throughout the 12-month follow-up, despite anticipated declines in β-cell function. However, for patients with suboptimal baseline glycemic control, health coaching led to significant improvement, underscoring its substantial benefit for those with inadequately managed blood glucose levels. This targeted improvement is a key outcome of an effective diabetes home care disease management program.

Diabetes knowledge and attitudes significantly influence self-management behaviors, which in turn affect quality of life (26). Consistent with this, we observed improvements in both diabetes knowledge and diabetes distress, suggesting that enhanced understanding of diabetes can alleviate associated stress and facilitate easier diabetes management for patients. Furthermore, patient feedback on the program was positive, emphasizing the benefits of the health coaching approach to follow-up care. This positive reception is crucial for the long-term sustainability of a diabetes home care disease management program.

The high baseline diabetes education levels in our study population meant that only a subset of patients presented with high diabetes distress or poor glycemic control at program entry. Consequently, observed improvements were concentrated within this subgroup. However, the significant distress reduction in this group, sustained at both 6 and 12 months, indicates a lasting positive impact. Conversely, the observed improvement in self-reported health status may be influenced by response bias due to repeated questionnaire administrations. Additionally, the patient-determined frequency of follow-up telephone calls may have affected outcomes, with more frequent contact potentially leading to greater improvements, although this aspect was not directly assessed in this study. Further research could explore the optimal contact frequency within a diabetes home care disease management program.

Study strengths include the large participant number and longitudinal data capture through routine program assessments. Limitations include a high questionnaire completion attrition rate, potentially introducing response bias. The absence of a control group without diabetes health coaching and the non-randomized study design are also limitations. However, each participant served as their own control, with changes measured against their baseline values. Potential sampling bias exists, and participants may not fully represent the broader chronic condition population. Nevertheless, consecutive recruitment of agreeable patients and representative patient characteristics compared to other Australian diabetes cohorts (27,28) strengthen the study’s relevance to diabetes home care disease management program contexts in similar populations.

In conclusion, patients with high diabetes distress or poor glycemic control at program entry benefited most significantly from this diabetes home care disease management program. Our findings suggest that such patients should be preferentially offered health coaching and specialized chronic disease management interventions, rather than broadly applying interventions that may not be universally relevant or effective. Personalized medicine approaches, including targeted diabetes home care disease management program strategies, are increasingly recognized as effective healthcare delivery models. Identifying patients most responsive to specific education strategies is crucial for optimizing healthcare resource allocation and improving patient outcomes in diabetes management.

Acknowledgments

Grace Delaney and Neroli Newlyn contributed equally to this article. The authors declare no funding was received for this research and have no conflicts of interest.

Author Information

Corresponding Author: Rachel McGrath, Department of Diabetes, Endocrinology and Metabolism, Level 3, Acute Services Building, Royal North Shore Hospital, St Leonards, Sydney, NSW 2065, Australia. Telephone: +61 (2) 9463 1470. Email: [email protected].

Author Affiliations: 1Department of Diabetes, Endocrinology & Metabolism, Royal North Shore Hospital, St Leonards, Sydney, NSW 2065, Australia. 2University of Sydney, Northern Clinical School, Royal North Shore Hospital, St Leonards, NSW 2065, Australia. 3Charles Perkins Centre, University of Sydney, Australia. 4Kolling Institute of Medical Research, University of Sydney, Royal North Shore Hospital, St Leonards, NSW 2065, Australia.

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Table

Table 1. Baseline Characteristics of Patients in the Diabetes Home Care Disease Management Program

Characteristicᵃ,ᵇ	Face-to-Face Health Coachingᶜ (n = 178)	Telephone-Only Health Coaching (n = 60)	All Patients (n = 238)
Age, mean (SD), years	69.0 (9.6)	66.6 (10.1)	68.4 (9.8)
Female, n (%)	119 (66.9)	38 (63.3)	157 (66.0)
Type 1 diabetes, n (%)	6 (3.4)	1 (1.7)	7 (2.9)
Type 2 diabetes, n (%)	172 (96.6)	59 (98.3)	231 (97.1)
Duration of diabetes, mean (SD), years	12.4 (6.9)	13.5 (7.1)	12.7 (6.9)
Insulin use, n (%)	40 (22.6)	28 (46.7)	68 (28.6)
Oral antihyperglycemic medication use, n (%)	149 (83.7)	50 (83.3)	199 (83.6)
HbA1c at baseline, % (SD)	6.9 (1.0)	7.3 (1.2)	7.0 (1.1)
HbA1c at 12 months, % (SD)	6.9 (1.0)	7.0 (1.1)	6.9 (1.0)
BMI at baseline, kg/m² (SD)	29.3 (5.7)	31.1 (5.5)	29.8 (5.4)
BMI at 12 months, kg/m² (SD)	29.2 (5.1)	30.1 (5.6)	29.5 (5.3)
Comorbiditiesᵉ, n (%)
Hypertension	123 (69.1)	42 (70.0)	165 (69.3)
Dyslipidemia	163 (91.0)	54 (90.0)	217 (91.2)
Diabetes complications, n (%)
Retinopathy	20 (11.2)	10 (16.7)	30 (12.6)
Chronic kidney disease	57 (32.0)	20 (33.3)	77 (32.4)
Peripheral neuropathy	39 (21.9)	11 (18.3)	50 (21.0)

Abbreviations: BMI, body mass index; HbA1c, glycated hemoglobin A1c; SD, standard deviation. ᵃ Data are number (percentage) unless otherwise indicated. ᵇ Data obtained from patient medical records at baseline. ᶜ Patients who received one in-person coaching session. ᵈ Patients who received coaching by telephone. ᵉ Comorbidities data recorded at baseline from patient medical records.