Clinical effectiveness and cost-impact after two-years of a ketogenic diet and virtual coaching intervention for patients with diabetes

Abstract

Aims

We previously evaluated the impacts at 5-months of a digitally delivered coaching intervention in which participants are instructed to adhere to a very low carbohydrate, ketogenic diet. With extended follow-up (24 months), we assessed the longer-term effects of this intervention on changes in clinical outcomes, healthcare utilization and costs associated with outpatient, inpatient and emergency department (ED) use in the Veterans Health Administration (VHA).

Materials and Methods

We employed a difference-in-differences model with a waiting list control group to estimate the 24-month change in HbA1c, body mass index (BMI), blood pressure, prescription medication use, healthcare utilization rates and associated costs. The analysis included 550 people with type 2 diabetes who were overweight or obese and enrolled in the VHA for healthcare. Data were obtained from electronic health records from 2018 to 2021.

Results

The virtual coaching and ketogenic diet intervention was associated with significant reductions in BMI (−1.56 [SE 0.390]) and total monthly diabetes medication usage (−0.35 [SE: 0.054]). No statistically significant differences in HbA1c, blood pressure, outpatient visits, inpatient visits, or ED visits were observed. The intervention was associated with reductions in per-patient, per-month outpatient spending (-$286.80 [SE: 97.175]) and prescription drug costs (-$105.40 [SE: 30.332]).

Conclusions

A virtual coaching intervention with a ketogenic diet component offered modest effects on clinical and cost parameters in people with type 2 diabetes and with obesity or overweight. Healthcare systems should develop methods to assess participant progress and engagement over time if they adopt such interventions, to ensure continued patient engagement and goal achievement.

Introduction

Veterans have a disproportionately high prevalence of diabetes mellitus (DM). DM is diagnosed in about 25% of Veterans, compared to 20% of the general population.^1,2 The cost and consequences of diabetes care, including medication costs, make it important for the Veterans Health Administration (VHA) to consider potential non-pharmacologic treatment options as an adjunct to medications. Since weight-management is a cornerstone of lifestyle modifications for patients with DM, the VHA recently explored the efficacy and cost impacts of a ketogenic diet and virtual coaching intervention among patients with DM.

Virtual dietary coaching programs have been proposed as interventions for short-term weight loss and improving glucose levels in patients with DM.^3–12 While reduced calorie diets per se are the mainstay of weight-loss programs, some have suggested that coaching programs that include a carbohydrate-reduced diet, which produces mild ketosis, may facilitate tapering DM medications.¹³ Despite these claims, there is limited evidence that ketogenic-focused, virtual coaching programs can sustain clinical effectiveness beyond a relatively short timeframe.^4,14,15 Furthermore, there is virtually no long-term evidence as to their impact on associated changes in healthcare utilization and spending.

We evaluated two-year outcomes among Veterans enrolled in a digitally delivered coaching intervention in which participants are encouraged to adhere to a very low carbohydrate, ketogenic nutrition program (Virta Health). In a prior report we observed significant changes in clinical outcomes after five-months of the intervention.¹² To determine if changes are sustained for two-years after program initiation, we employed a quasi-experimental design to evaluate clinical outcomes, healthcare utilization and costs associated with pharmacy, outpatient, inpatient and emergency department (ED) use. The overarching goal of this research is to determine whether a virtual coaching intervention and ketogenic diet might be an effective, longer-term treatment strategy for Veterans with type 2 DM (T2D) and overweight or obesity.

Materials and Methods

Study Design

We employed a difference-in-differences study design with a cohort of Veterans with T2D who applied to participate in the virtual coaching and ketogenic diet program. A treatment group was created from the Veterans with T2D who were given access to the program on a first-come-first-serve basis, and a control group was created from Veterans with T2D who applied to participate but were unable to enroll after program capacity was reached in October of 2019.

An initial evaluation of the impact of the program was conducted at a 5-month follow-up interval.¹² The present study extends the follow-up to 24-months. During that period, 40 patients who were initially on the wait list were offered access to the program. Those patients are excluded from the present analyses, and additional details on their characteristics can be found in Appendix A. The study was reviewed and considered exempt research by the VA Boston Healthcare System Institutional Review Board (R&D #3317-X).

Intervention

The program is a virtual coaching intervention in which participants are instructed to eat a ketogenic diet.¹⁶ The intervention adheres to the standard definition of a ketogenic diet, which typically comprises a maximum of 50 grams or 5–10% of carbohydrates daily. Participants are provided with guidance and resources, including suggested meal plans, to help them adhere to this carbohydrate limit. The intervention also includes educational components and regular medication management counselling, including medication adjustments. Participants receive dietary advice regularly from certified nutritionists and dietitians who are part of the intervention team. This guidance is provided both at the onset and throughout the program in scheduled sessions and as needed based on participant progress. Medication management counseling is provided online to participants, facilitated by clinicians associated with the intervention platform. This is separate from the guidance provided by their primary care physicians, though coordination between both is encouraged to ensure optimal patient care. Medication adjustments are informed by an algorithm that takes into account blood glucose levels, weight, and other relevant clinical parameters. The intervention application allows participants to log these metrics, making them available to counselors in real-time. This facilitates timely and personalized medication management.

Participants were required to meet specific inclusion criteria: enrollment in benefits through VHA, a current T2D diagnosis (HbA1c >= 6.5%) confirmed by their primary care provider, overweight or obese BMI categories, at least one current prescription for diabetes medication other than, or in addition to, metformin, and enrolled in the VHA for healthcare. Exclusion criteria included active-duty status, type 1 diabetes, end stage renal disease, heart failure, and active chemotherapy treatment. The target enrollment for the program was 450 participants, and was based on the VHA’s contract with Virta Health for the pilot phase of the intervention.

Data

Data for this study came from the VHA Corporate Data Warehouse, which contains administrative records on sociodemographic characteristics as well as electronic health records documenting health status, prescription medications and healthcare utilization. Virta Health provided the name, address, social security number and telephone number for all program and waitlist patients to the research team. These data were used to match participants to their VHA administrative records. Data on healthcare costs were obtained from the VA’s Managerial Cost Accounting System which contains costs of outpatient visits, inpatient hospitalizations, and dispensed outpatient prescriptions.

Dependent Variables

We examined 13 outcomes related to diabetes care, healthcare utilization, and healthcare costs. Health outcomes included HbA1c, weight, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), number of insulin prescriptions, and number of all diabetes prescriptions. Utilization outcomes were the number of outpatient visits, number of inpatient hospitalizations, and number of emergency department (ED) visits. Cost outcomes included outpatient costs, inpatient costs, prescription costs, and total costs. In these data, total costs are the sum of outpatient and inpatient costs. Prescription costs are a subset of outpatient costs. All outcomes were captured up to 24-months after the application date to the program. Because control participants do not have a treatment date, we used the application month as the relevant post-period comparison for both the treatment and the control groups.

Independent Variables

The primary independent variable of interest was the effect of participation in the virtual coaching and ketogenic diet program and is operationalized as the interaction term between a dichotomous variable for treatment status and a dichotomous variable for the post-application period. Additional covariates included baseline sociodemographic characteristics (i.e., sex, age, race/ethnicity, and urban/rural residence), Charlson comorbidity index,¹⁷ and VHA enrollment priority status, which is a proxy for service-connected disability and socio-economic status. All models included dichotomous variables for individual months (fixed effects), a standard approach in difference-in-differences analyses.

Statistical Analyses

We compared baseline characteristics of treatment and control groups using t-tests for binary or continuous variables and chi-square tests for categorical variables. Differences in outcomes were estimated using difference-in-differences equations using the following specification:

$$y_{it}=\alpha +{{\beta }_{1}T}_i+{{\beta }_{2}Post}_{it}+{{\mathit{\beta }}_3\left(T*Post\right)}_{it}+{\theta X}_i^{\text{'}}+{\gamma }_t{+\epsilon }_{it}$$ (1)

where y_it is one of 13 outcomes for individual, i, in month, t; β₃ is the change in outcome associated with receiving the treatment, T_i,, in the post period, Post_it. X_i are covariates and γ_t are month fixed effects. Huber-White robust standard errors were calculated at the patient level.¹⁸

We conducted sensitivity analyses to examine the potential for differential missingness of data between treatment and control outcomes for three outcomes: HbA1c, BMI, and systolic/diastolic BP (combined). The purpose of this analysis was to detect any potential documentation bias in the administrative health records that was specifically related to program participation. We created a dichotomous indicator variable for outcome-specific missingness and regressed this indicator on the variables included in equation 1 to indicate the percentage point probability that program participation was associated with missingness for any of the three outcomes. For outcomes with evidence of differential missingness, we tested specifications weighting the observations using the inverse of the probability of having a non-missing outcome in the post-application period.¹⁹

Additional sensitivity analyses were conducted to investigate whether or not simultaneous changes in weight loss medications—specifically GLP-1 receptor agonists—could explain any observed changes in BMI. Specifically we examined the impact of treatment on changes in days’ supply of GLP-1 receptor agonists.

Results

Baseline Characteristics

The baseline characteristics of the treatment and control groups are presented in Table 1. Treatment group participants were less likely to be male and more likely to be white, non-Hispanic relative to control patients. The treatment group had slightly lower HbA1c and monthly insulin prescriptions and were more likely to have participated in VA’s intramural weight loss program (MOVE!) at baseline. All other measures of baseline socio-demographic characteristics, healthcare utilization, health status, and prescription patterns were balanced between the treatment and control groups.

Table 1.

Baseline characteristics of Veterans enrolled in the ketogenic diet virtual coaching program and in the waitlist-control group, 2018–2022.

Baseline variables	Treatment (n=275)	Control (n=275)	p-value
Socio-demographic Characteristics
Males (%)	85.8	92.7	0.009***
Age (avg.)	58.1 (7.88)	58.0 (7.66)	0.512
Urban resident (%)	66.2	71.3	0.198
Race/Ethnicity (%)
Black, non-Hispanic	13.8	20.4	0.032*
White, non-Hispanic	68.4	56.4
Hispanic	7.3	10.9
Other, non-Hispanic	7.3	10.2
Missing	3.3	2.2
Priority Status (%)			0.900
1–3	73.5	72.0
4–6	16.4	17.8
7–8	10.2	10.2
VA Utilization
Outpatient visits (monthly avg.)	2.2 (2.3)	2.1 (2.2)	0.050
Emergency Department visits (monthly avg.)	0.07 (0.31)	0.08 (0.31)	0.771
VA MOVE! Participation (%)^	13.1	7.3	0.024*
Inpatient admissions (monthly average)	0.02 (0.003)	0.01 (0.003)	0.810
Health Status
Co-morbidity index (avg.)	1.0 (1.34)	1.2 (1.29)	0.207
BMI (kg/m2, avg.)^^	35.2 (6.08)	34.7 (6.44)	0.778
HbA1c (%, avg.)	8.8 (1.71)	9.2 (1.94)	0.006**
Systolic BP	132.9 (15.31)	132.0 (16.09)	0.451
Diastolic BP	79.0 (8.7)	77.9 (9.69)	0.102
Prescriptions (Rx)
Metformin (%)	73.1	66.9	0.114
Insulin (monthly avg. prescriptions)	0.5 (0.87)	0.6 (0.90)	0.028*
Diabetes medications (monthly avg. prescriptions)	1.1 (1.23)	1.2 (1.32)	0.568
Total no. of non-metformin prescriptions (monthly avg.)	6.2 (4.15)	6.5 (4.35)	0.367

Notes: p-values were computed using two-sample t-tests for differences in continuous variables, and chi-square tests for categorical variables.

^***p<0.001,

^**p<0.01,

^*p<0.05. For calculation of average BMI, there were 260 non-missing subjects. For calculation of average systolic and diastolic BP, there were 272 non-missing treated and 269 non-missing control subjects. Standard deviations for continuous variables are reported in parentheses.

^{^}VA MOVE! participation indicates whether a Veteran has previously participated in a formal VA sponsored weight loss program.

^{^^}The number of observations for BMI are smaller due to missingness in the variable. Sample size for this metric is presented in parentheses next to group averages.

Impacts of the Treatment Program on Diabetes Outcomes and Healthcare Utilization

The difference-in-differences estimates comparing health outcomes before and after application dates to the treatment program are reported in Table 2. Treatment was associated with a significant reduction in absolute weight (−8.89 kg (Standard Error [SE]: 2.83)) and BMI (−1.56 (Standard Error [SE]: 0.39)) during the 24-month study period. Significant reductions were also detected in monthly insulin prescriptions (−0.21 [SE: 0.04]) and all monthly diabetes-related medications (−0.35 [SE: 0.05]). No significant changes in HbA1c, diastolic or systolic blood pressure were detected. Similarly, no significant changes were detected in outpatient, inpatient or emergency department utilization rates.

Table 2.

24-month changes in diabetes outcomes for Veterans in the ketogenic diet virtual coaching treatment and control groups, before and after application dates.

		Outcomes
Variables	HbA1c (%)	Body mass index	Weight (kg)	Systolic blood pressure (mm Hg)	Diastolic blood pressure (mm Hg)	Outpatient visits (no.)	Inpatient Admissions (no.)	ED visits (no.)	Insulin prescriptions (no.)	Any diabetes prescriptions (no.)
Treatment*Post (DiD Estimator)	−0.20	−1.56***	−8.89**	−1.01	−0.88	−0.14	−0.0049	−0.016	−0.21***	−0.35***
	(0.149)	(0.390)	(2.827)	(1.050)	(0.561)	(0.118)	(0.005)	(0.014)	(0.038)	(0.054)
Treatment group indicator	−0.28	0.88	6.28	−0.23	0.77	0.25	−0.0049	−0.00059	−0.047	0.011
	(0.154)	(0.630)	(4.573)	(1.257)	(0.675)	(0.211)	(0.005)	(0.015)	(0.051)	(0.062)
Post period indicator	−0.59***	−0.29	−3.13	0.50	0.24	0.46*	−0.0030	−0.0017	−0.0087	0.021
	(0.155)	(0.524)	(3.669)	(1.311)	(0.684)	(0.189)	(0.006)	(0.015)	(0.038)	(0.062)
Observations	3,051	4,096	4096	4,913	4,913	17,050	17,050	17,050	17,050	17,050
R2	0.072	0.064	0.111	0.024	0.105	0.071	0.005	0.008	0.036	0.028

Notes: The treatment*post-period difference-in-difference (DiD) indicator estimates the impact of treatment. All regression models included time fixed effects and individual-level controls (age, sex, co-morbidity index, urban, past MOVE participation, race/ethnicity and priority status) not shown here. Number of observations are reported at the patient-month level.

^***p<0.001,

^**p<0.01,

^*p<0.05.

Impacts of the Treatment Program on Costs

The 24-month changes in diabetes costs for people with T2D in the treatment and control groups before and after application dates are presented in Table 3. The treatment program was associated with a significant reduction in per-patient, per-month outpatient costs (-$286.80 [SE: 97.175]) and a -$105.40 [SE: 30.332] per-patient, per-month reduction in prescription drug costs. There were no statistically significant differences in overall costs or inpatient costs between treatment and control groups at 24-months.

Table 3.

24-month changes in diabetes costs for Veterans in the ketogenic diet virtual coaching treatment and control groups, before and after application dates.

	Outcomes
Variables	Total Cost ($)	Outpatient Cost ($)	Rx Cost ($)	Inpatient Cost ($)
Treatment*Post (DiD Estimator)	−484.4	−286.8**	−105.4***	−197.6
	(283.553)	(97.175)	(30.332)	(266.501)
Treatment group indicator	156.0	117.3	34.7	38.7
	(159.329)	(114.143)	(56.012)	(99.741)
Post period indicator	339.3	337.7**	66.1	1.63
	(267.863)	(112.922)	(47.087)	(231.455)
Observations	17050	17050	17050	17050
R2	0.002	0.037	0.011	−0.000

Notes: The treatment*post-period difference-in-difference (DiD) indicator estimates the impact of treatment. All regression models included time fixed effects and individual-level controls (age, sex, co-morbidity index, urban, past MOVE participation, race/ethnicity and priority status) not shown here. Number of observations are reported at the patient-month level.

^***p<0.001,

^**p<0.01,

^*p<0.05.

Sensitivity Analyses

We conducted tests for differential missingness in outcomes between treatment and control groups for several clinical outcomes, HbA1c, BMI and systolic/diastolic BP (Appendix B). Two outcomes, BMI and BP, showed evidence of differential attrition. Treatment group patients were 6% and 4% more likely to have a missing BMI and BP measurement, respectively, relative to control group patients. However, results from sensitivity analyses using inverse-probability weighted models were not meaningfully different from the results presented in the primary specifications (Appendix C). We also examined whether or not the intervention was associated with changes in the days’ supply of GLP-1 receptor agonists (Appendix D). Indeed we find that the intervention slightly reduced the days’ supply of GLP-1 receptor agonists for treatment patients relative to control patients. Relative to changes in the days’ supply of insulin medications or all diabetes medications in general, we interpret this as a small change. Nonetheless, we do not believe use of GLP-1 receptor agonists are the primary mechanism driving our findings.

Discussion

In this analysis of the two-year outcomes of a virtual coaching and ketogenic diet program, we found that treatment was associated with a 4% reduction in BMI in the treatment group at 24 months. This compares to a 3% change observed at 5-months of follow-up of the same cohort. A full comparison of percent changes at months 5 and 24 can be found in Appendix E. While the observed changes in BMI were statistically significant, they did not meet standard criteria for clinically meaningful changes, typically defined as weight loss exceeding 5% of the initial body weight.^20–22 Although significant reductions in HbA1c and blood pressure were observed at the five-month follow-up period,¹² there were no significant differences in HbA1c or blood pressure outcomes at 24 months. This inability to sustain improvements in health outcomes is consistent with many dietary interventions for DM, which typically find that health benefits diminish or return to baseline as patient adherence to dietary recommendations wanes over time.²³

We used electronic health data to examine the impacts of the virtual coaching and ketogenic diet intervention on diabetes medication usage, healthcare utilization and healthcare costs. We found that the intervention led to significant, sustained differences in monthly diabetes-related medications. Treatment participants received 0.21 fewer insulin prescriptions per month and 0.35 fewer prescription fills for all diabetes medications per month, representing a 32.5% reduction in medication usage relative to baseline. The magnitude of this change is similar to those reported in other virtual diabetes programs.^4–7,10 The sustained nature of these changes is likely reflective of the fact that the virtual coaching intervention includes medication management as a prominent component. It may be viewed as a somewhat positive finding that fewer diabetes medications were needed to maintain similar levels of HbA1c. However, clinical programs for DM management should impact HbA1c levels and possibly other clinical biomarkers to be considered successful.

No statistically significant changes in healthcare utilization were noted for outpatient, inpatient or ED care at 24-months. We did observe a $286 difference in per-patient, per-month outpatient costs and a $105 reduction in per-patient, per-month diabetes prescription drug costs likely due to fewer pharmacy and primary care visits. It is unclear if these changes reflect actual clinical improvements among the participants or merely a shifting of care management and costs from VHA to the virtual coaching component of the intervention. The extent to which the costs of the intervention offset these spending reductions depends on the monthly price of the intervention and whether reduced medication usage and outpatient visits can be sustained over time.

Several limitations of the study are worth mentioning. This was not a randomized controlled trial. Although a difference-in-differences approach with a waitlist control offers the advantage of quasi-experimental evidence, the results of our study should be interpreted cautiously. While our results are consistent with many long-term evaluations of virtual dietary interventions, future randomized trials could provide a more definitive perspective. In particular, all patients expressed interest in participating in the program, those in the control group were offered a chance to receive treatment, and some patients eventually elected to participate in the intervention. Although patients who switched to the treatment group were excluded from the analyses and appeared similar to control patients, they were slightly younger, had higher BMI and lower HbA1c relative to control patients who did not switch into treatment (Appendix A). We are unable to determine intervention intensity and/or attrition for those who enrolled in the treatment group, and therefore all results should be interpreted as intent-to-treat estimates. Although we are unable to report how many patients maintained contact with the intervention for 24-months, from a cost-estimation standpoint this approach aligns with the fact that VHA paid the vendor regardless of patients’ usage of program resources. Also, as dietary preferences are likely to vary based on patients’ personal and cultural preferences, we are unable to determine which of the program components is most important or valued by patients.

Conclusions

Although health improvements were observed for participants receiving a virtual coaching and ketogenic diet intervention after 5-months, these effects were diminished after two-years. With respect to the findings that were sustained— lower BMI and reduced diabetes medication usage—it remains unclear whether these effects can be attributed to personalized coaching, a ketogenic diet, some combination of these two, or other unknown factors. These health outcome and cost results suggest that health plans and healthcare delivery systems considering the adoption of virtual dietary coaching programs should review participants’ progress, participation, and outcome measures on a periodic basis, with continued participation being conditional on patient engagement and goal achievement.