Cost-Effectiveness of a Digital Health Intervention for Acute Myocardial Infarction Recovery

Abstract

Background:

Acute myocardial infarction (AMI) is a common cause of hospital admissions, readmissions, and mortality worldwide. Digital health interventions (DHIs) that promote self-management, adherence to guideline-directed therapy, and cardiovascular risk reduction may improve health outcomes in this population. The “Corrie” DHI consists of a smartphone application, smartwatch and wireless blood pressure monitor to support medication tracking, education, vital signs monitoring and care coordination. We aimed to assess the cost-effectiveness of this DHI plus standard care in reducing 30-day readmissions among AMI patients in comparison to standard care alone.

Methods:

A Markov model was used to explore cost-effectiveness from the hospital perspective. The time horizon of the analysis was 1 year, with 30-day cycles, using inflation-adjusted cost data with no discount rate. Currencies were quantified in US dollars and effectiveness was measured in quality-adjusted life year (QALYs). The results were interpreted as an incremental cost-effectiveness ratio at a threshold of $100,000 per QALY. Univariate sensitivity and multivariate probabilistic sensitivity analyses tested model uncertainty.

Results:

The DHI reduced costs and increased QALYs on average, dominating standard care in 99.7% of simulations in the probabilistic analysis. Based on the assumption that the DHI costs $2,750 per patient, use of the DHI leads to a cost-savings of $7,319 per patient compared to standard care alone.

Conclusions:

Our results demonstrate that this DHI is cost-saving through the reduction of risk for all-cause readmission following AMI. DHIs that promote improved adherence with guideline-based healthcare can result in reduced hospital readmissions.

Clinical Trial Registration:

NCT03760796; https://clinicaltrials.gov/ct2/show/NCT03760796

INTRODUCTION

Reducing hospital readmissions has become a major health policy goal in the U.S. to reduce potentially avoidable costs.¹ A recent Medicare report showed that up to 76% of 30-day readmissions are potentially preventable by adhering to post-discharge care practices.² Acute myocardial infarction (AMI) is a significant driver of readmissions and is a priority condition for the Hospital Readmissions Reductions Policy (HRRP).³ Among more than 1 million patients in the U.S. hospitalized with AMI, nearly 1 in 6 experience an all-cause, unplanned, non-reimbursable readmission within 30 days post-discharge, costing the healthcare system over $1 billion dollars annually.^4,5,6 Additionally, Medicare penalties targeting 3,241 eligible hospitals reached $564 million in 2018, up from $528 million in 2017.³

Digital health interventions (DHIs) have the potential to reduce cardiovascular disease (CVD) risk factors and improve outcomes.⁷ The Corrie Health Digital Platform (“Corrie”) is a smartphone-based application developed in collaboration between patients, researchers, and clinicians at Johns Hopkins University and Apple (Cupertino, CA). The DHI aims to empower patients in their own post-discharge recovery, improve the patient experience, and reduce hospital readmissions and keep patients connected to providers. Due to the scalability of DHIs and ability to improve patient outcomes, there is significant potential for cost-savings for the healthcare system. Cost-effectiveness analyses have been used to study DHIs in the areas of telemedicine,⁸ cardiac rehabilitation,⁹ and weight management¹⁰; however, studies evaluating smartphone-based interventions in AMI are scarce.

Therefore, the current analysis aims to conduct an economic evaluation, from the hospital perspective, of the cost-effectiveness of the Corrie DHI plus standard discharge practices in reducing 30-day readmissions when compared to standard discharge practices alone after hospitalization for AMI. The evaluation specifically aims to identify the cost-savings to the hospital from the introduction of the DHI. The analysis would not, therefore, include an analysis of the cost-savings from a societal perspective. We hypothesize that the Corrie DHI is cost-effective compared to standard care at a willingness-to-pay threshold of $100,000 per quality-adjusted life year (QALY).

METHODS

The MiCORE Study

The Johns Hopkins Myocardial infarction, COmbined-device, Recovery Enhancement (MiCORE) Study was approved by the Johns Hopkins School of Medicine Institutional Review Board (IRB00099938). Further information about the MiCORE study’s objectives and methodology has been described in detail in the rationale and design paper.^11–13 In brief, this study’s primary objective was to determine if AMI patients using the DHI had lower rates of first all-cause unplanned 30-day readmissions as compared to a historical standard of care control group. Patients admitted to Johns Hopkins Hospital, Johns Hopkins Bayview Medical Center, Massachusetts General Hospital, and Reading Hospital for a ST-elevation myocardial infarction (STEMI) or type 1 non-ST-elevation myocardial infarction (NSTEMI) from October 1, 2016 to April 14, 2019 were enrolled prospectively into the DHI group if they (1) were 18 years or older, (2) were English speaking, (3) owned a smartphone, (4) had no visual, auditory, cognitive, or motor impairment that would preclude DHI use, (5) were hemodynamically stable, and (6) were approved to participate by his/her inpatient care team. The historical control group consisted of English-speaking patients, 18 years or older, admitted to 1 of the 4 hospitals with a STEMI or NSTEMI from September 27, 2015 to October 1, 2016, prior to the availability of the DHI. Patients were excluded from the historical control group if they were ineligible for readmission, meaning that they experienced an in-hospital death or were transferred to another hospital at the time of discharge. If patients were transferred to another hospital at the time of discharge then the hospital at which they were enrolled would no longer be the hospital subject to penalties in the case of 30-day readmission. Ultimately, 200 participants were enrolled in the DHI group and 864 in the historical control group.

After enrollment into the DHI group, study researchers downloaded the Corrie app onto the participant’s personal iPhone or the participant was given an “iShare,” which was a refurbished iPhone preloaded with Corrie and equipped with a SIM card.¹⁴ Participants were given an iShare if they owned an Android, or iPhone 5 or older iPhone model as these smartphones were not compatible with the Corrie app. The HIPAA-compliant DHI consists of (1) a smartphone application, (2) cooperative sensors including an Apple Watch and an iHealth wireless blood pressure monitor (model BPL3), and (3) a data backend.

The DHI integrates constructs from the widely-accepted Health Belief Model and Social Cognitive Theory to promote health behavior change.^15,16 The DHI allowed participants to (a) manage their medications (track daily adherence, indication, and side effects), (b) monitor their vital signs (heart rate, blood pressure, weight, mood, and steps), (c) learn about the risk factors for CVD and lifestyle modification through educational articles (all at a sixth or seventh grade reading level as determined by the Flesch-Kincaid Readability Test Tool) and animated videos (Nucleus Media), (d) schedule and track follow-up appointments, (e) connect with their providers, and (f) store health information.^13,17 Apple Watch integration allowed participants to monitor their heart rate and physical activity, receive reminders on medications and appointments (also delivered on the iPhone home screen), and track medications.^13,17 The wireless blood pressure monitor integration allowed participants to track and review blood pressure recordings within the DHI.^13,17 There was no monitoring of real-time data by the study or patient’s clinical team.^13,17 At this stage, the DHI was exclusively a self-management tool for patients.^13,17

The primary results of the MiCORE study have been published previously.17 At baseline, patients in the DHI group differed significantly from the historical control group on a number of sociodemographic, clinical, and hospitalization characteristics.17 Patients in the DHI group were younger, more likely to be male, more likely to have private insurance, and had a lower comorbidity burden.17

Model Development

We developed a Markov model to evaluate the cost-effectiveness of the DHI plus standard discharge practices versus standard discharge practices alone in the 30-day discharge period after AMI from the U.S. hospital perspective.^18,19 A semi-Markov model of care provided through the intervention is advantageous over a decision tree because it can capture state-transitions between different stages before and after an AMI event and death within the acute care setting. The model was run for 12 months in 30-day cycles. Our model was informed by data from the literature on post-AMI outcomes as well as from outcomes documented in the historical control group (Table 1). Four authors (X, X, X and X) had full access to all data in the study and take responsibility for its integrity and data analysis.

Table 1.

Probabilities associated with each transition state

Probability	Base Case Estimate
Death due to AMI12,43	0.236
Recurrent MI44	0.089
Death due to recurrent MI44	0.297
Death due to non-MI complications45	0.012
Readmission due to recurrent MI (with Corrie)17	0.02
Readmission due to non-MI complications (with Corrie)17	0.03
Recovery after recurrent MI	0.87
Recovery after recurrent MI (with Corrie)	0.87

AMI: acute myocardial infarction

MI: myocardial infarction

Ten-thousand simulated patients were followed as they transitioned through a series of health states during the 30-day post-discharge period after AMI (Figure 1), with a probability associated with each transition state. These probabilities were derived from the literature about post-discharge outcomes for AMI (Tables 1 and 2). During this period, patients were at risk for readmission either due to recurrent AMI or due to other disease states (e.g., pneumonia). If none of these events occurred, patients remained in a “stable outpatient” state. The simulated patients were followed in the model either until their death or for 1 year. Transition probabilities were used to generate the series of states in which the simulated individuals would be found; then, costs and QALYs were summed.

Figure 1.

Markov model for post-MI patients. Discharged patients can cycle through 3 states - no complications (stable outpatient), readmissions for recurrent AMI, or readmissions for another cause (e.g., pneumonia). Patient mortality is represented by the death state.

Table 2.

Utility values for each health state

Parameter	Base case estimate (mean ± SD)	Sensitivity analysis range tested
AMI17	0.725 (0.3–0.96)	(0.3–0.96)
No Complications46	0.93	(0.41–0.97)
Readmission due to MI22	0.81	(0.34–0.82)
Readmission due to non-MI47	0.68	(0.47–0.84)

AMI: acute myocardial infarction

MI: myocardial infarction

SD: standard deviation

Population of Model Transition Parameters

For the control arm, we obtained rates of post-AMI events (i.e., readmission for recurrent AMI or other causes, or no complications state) and case fatality from the literature (Table 1). Additional readmission rates were obtained from the MiCORE study for both the DHI and historical control groups. The rate of all-cause readmission for participants in the DHI group was 6.5% (13/200) and 16.8% (145/864) among those in the historical control group. Of the 6.5% all-cause readmission in the DHI group, 38.5% were cardiac-related and none were due to recurrent AMI.¹⁷ The model assumes unchanging efficacy and constant readmission rates.

Effectiveness Measure

We assigned a health utility weight (i.e., QALYs) to each of the health states that reflected the preference for, or desirability of, that particular health state (Table 3). We used contingent market valuation techniques in determining our effectiveness measure. Given the 1 year time horizon, the model does not consider a discount rate. All utility values were taken from studies that used standardized models (i.e., the time-tradeoff or standard gamble techniques).²⁰ The utility weight for AMI (0.725) was obtained by using EuroQOL (EQ-5D) index scores collected in the Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease database.²¹ The utility for post-AMI without complications was similarly obtained from EQ-5D scores and time tradeoff techniques. We considered utility weights for readmission due to recurrent AMI or due to another complication separately. The utility value for readmission due to recurrent AMI (0.81) was obtained from a study in which individuals were assigned a specific index, or utility value, for the time they spent in a health state, measured using the EQ-5D instrument.²² For readmission due to other complications, we interpreted a utility value based on data (0.68) from a study that used time trade-off and contingent valuation techniques.²³

Table 3.

Expected results of the cost-effectiveness analysis comparing prevention to standard care for Corrie

Intervention	Cost ($)	Incremental cost	Effectiveness (QALYs)	Incremental Effectiveness	ICER ($/QALY)
Corrie	17,195		7.88
Standard of care	27,940	10,024	7.08	−0.80	Dominated

ICER: incremental cost effectiveness ratio

QALY: quality adjusted life year

Cost Information

We focused on hospital costs for unplanned 30-day readmissions (Table 3). In order to generate a value proposition for the DHI, we developed a threshold analysis to determine the cost-savings that the DHI may accrue. We estimated typical costs associated with readmissions or death of AMI patients discharged with standard practices using 2014 U.S. hospital costs from the Agency for Healthcare Research and Quality (AHRQ) and these values ranged from $17,600 for readmission due to recurrent AMI to $20,800 for the cost of AMI health state.^24–26 We used the HCUPnet tool to generate the cost of each transition state.²⁷ All cost data were then inflated to match 2019 U.S. Dollars using the general Consumer Price Index Inflation Calculator from the Bureau of Labor and Statistics.²⁸

Cost-effectiveness and Sensitivity Analyses

We calculated the incremental cost-effectiveness ratio (ICER) of using the DHI plus standard discharge practices compared to standard discharge practices alone, over the simulated 1-year study period. The willingness-to-pay threshold to determine acceptable cost-effectiveness was set at $100,000 per quality-adjusted life year (QALY).²⁹ Means and 95% confidence intervals were calculated using 10,000 model iterations. To assess model robustness, we performed extensive deterministic sensitivity analyses. We used 50% to 200% of the base-case estimates to perform 1-way sensitivity analyses of all input parameters (probability of AMI, recurrent AMI, readmission due to other complications, mortality, utilities, and costs of post-AMI events). Two-way sensitivity analyses were performed by simultaneously altering the costs, utilities and probabilities. We also conducted a probabilistic sensitivity analysis, in which the model was run using a value of each parameter drawn randomly from the distribution assigned to that parameter. We used beta distributions for probabilities and gamma distributions for costs and utility decrements.

Budget Impact Analysis

The budget impact of adopting the DHI across the Johns Hopkins hospital was calculated over the total population enrolled in a Johns Hopkins Healthcare managed care plan, which was 429,000 in 2017.³⁰ The budget impact model considered the impact on the Johns Hopkins hospital budget of adopting the DHI compared to a scenario where the standard of care was maintained. A one year time horizon was assumed. The total budget impact was calculated by looking at the cost per patient from our Markov model multiplied by the number of hospitalizations under both standard of care and in a scenario where the DHI was adopted. The net impact was determined by dividing the overall cost savings by the total number of payors into the Johns Hopkins Healthcare managed care plan.

RESULTS

Cost-effectiveness of Corrie

Compared to standard discharge practices alone, DHI use in addition to standard discharge practices after hospitalization for AMI improved quality-adjusted survival by 0.80 QALYs and reduced costs by $10,024 per patient (Table 3), principally through the reduction in readmissions. Given that the DHI yielded greater health benefits at a lower cost over the full 1-year time horizon observed, the DHI was the dominant option over standard discharge practices alone. The DHI was cost-saving compared to standard of care in 99.926% of the simulations and was cost-effective at a conventional willingness-to-pay threshold of $100,000/QALY gained in 99.7% of simulations, with a dominant ICER (Figure 2). Overall, our results show that the DHI increases the lifespan of patients at a lower cost than the standard of care.

Figure 2.

An incremental cost-effectiveness ratio (x) scatterplot from the Bayesian Multivariate probabilistic sensitivity analysis regarding the use of Corrie compared to standard discharge practices alone, based on 10,000 Monte Carlo simulations.

Sensitivity Analysis

Univariate sensitivity analyses indicated that the DHI always dominated the standard of care. Two-way sensitivity analyses also maintained dominance of the DHI over standard of care. Even at the highest risk of recurrent AMI or other readmission causes with the DHI compared to standard discharge practices, and with the lowest bound of spending on recurrent AMI or other readmission causes under standard discharge practices, the DHI was still the preferred option at a conventional willingness-to-pay threshold of $100,000/QALY.

Cost Analysis

From our model, we calculated that the health benefits achieved from the DHI were at least as high as those achieved among patients who received standard care, at approximately $10,000 less per patient. However, this figure does not include the implementation costs of the DHI. Although the MiCORE study provided loaner iPhones to patients who did not own a Corrie compatible iOS device, we determined that enabling all patients to download Corrie onto their own phones would allow for greater impact and avoid the need to purchase devices. To facilitate this, we have developed an Android version of Corrie. Thus, we based our cost analysis on the assumption that patients will be using their own devices.

The cost of Corrie was estimated to be $229 per month per patient for a 1-year use term ($2,750 per year). Based on this cost estimate, the use of the DHI leads to a cost-savings of $7,319 per patient compared to standard of care alone (i.e., $10,024 - $2,750). The $2,750 figure is composed of a: (1) bluetooth blood pressure monitor (approximately $40), (2) refurbished smartwatch (approximately $250), (3) medication pill box (approximately $10), (4) tote bag (approximately $12.50), (5) printed instructions (approximately $5), and (6) clinical support for onboarding and maintenance of platform by engineering inclusive of server storage fees and helpline access per user (approximately $2,432 annually). A full inventory of costs analyzed in this study is presented in Supplemental Digital Content 2.

DISCUSSION

Principal Findings

DHIs are an innovative solution that demonstrate promise to improve outcomes and control costs by enabling improved patient monitoring, communication and self-management. Using data from the MiCORE study as well as from the literature, we have demonstrated that this DHI appears to increase QALYs while saving costs. Overall, for the DHI group, the probability of readmission due to non-AMI related complications as well as the likelihood of death was low. Therefore, we have focused our discussion on the main outcome of interest, which was readmission due to recurrent AMI, in keeping with the central objective of the study.

Our results suggest that the DHI is cost-saving through the reduction of risk for all-cause readmission.¹⁷ Based on the routinely-used willingness-to-pay threshold of $100,000 per QALY gained, the DHI is cost-effective. The DHI dominates standard of care in every scenario, accounting for different levels of risk of readmission for AMI or other complications (the most sensitive parameters used in the model). The cost-savings calculated in this study were specific to the costs saved by a payor (i.e., hospital and insurance company). Accounting for the estimated cost of Corrie, the cost-savings per QALY per patient is $7,274 compared to the standard of care alone. This study did not account for potential costs saved by the patient or society, such as through prevented missed days of work and out-of-pocket medical costs. It is possible that the DHI may demonstrate additional cost-saving potential from those perspectives. Based on the results of our study, it appears that the DHI is cost saving (i.e., the cost of deploying the DHI vs using the standard of care alone), provides better outcomes (i.e., greater effectiveness or QALYs), and the results are robust to examinations of uncertainty in the model’s assumptions.

Budget Impact Analysis

Based on the national estimated risk for AMI,31 we estimated that 9.5% of (107,000) inpatient visits recorded annually were AMI-related admissions. The total cost of hospitalizations at the standard of care cost was estimated to be approximately $284 million per year. The total cost of hospitalizations with the DHI is approximately $182 million per year. This represents a net budget impact of approximately -$101.9 million or a 36% financial saving to the hospital managed care plan (Supplemental Digital Content 1). Considering that there are 429,000 individuals enrolled in the Johns Hopkins Healthcare managed care plan, this works out to a lowering of costs of $236 per individual annually ($101.9 million/429,000) covered by the plan.

The adoption of Corrie in AMI care could lower the average amount paid by each individual member into his/her Johns Hopkins Hospital managed care plan by $236 per year, based on data from this study with consideration of all members of the plan (both those who have had an AMI and used the DHI and those who have not). Therefore, by reducing the overall cost of hospitalization, and the number of hospitalizations, cost-savings could be realized by managed care plans and passed on to the individual members of the plan. However, further analysis would be needed to determine the specific cost-savings that would be accrued to the individual payor. The figures given here are simply indicative of potential cost-savings to the insurance scheme.

Comparison to Prior Literature

While there is a lack of prior cost-effectiveness studies of smartphone-based DHIs for CVD,^8,9,32–34 the addition of digital telemedicine components to a cardiac rehabilitation program in Belgium has been shown to reduce readmissions and be cost-effective with an ICER of €−21,707/QALY (~24,033 USD).⁹ In the U.S., patients often do not enter cardiac rehabilitation until weeks after hospital discharge, if at all,³⁵ creating a need for the immediate post-discharge guidance that Corrie provides. The reduction in cost/QALY as well as the overall reduction in recurrent AMI and all-cause readmission reported in MiCORE imply that there is justification for using Corrie to enhance existing post-AMI care.¹⁷

As payers continue to transition to value-based models, the desirability of DHIs for health systems is increasing. For example, recent studies suggest that HRRP may be associated with fewer readmissions but may also be associated with increased mortality during the 30-day post-discharge period for some patients.³⁶ This indicates that focus on a common value-based metric, reduced readmissions, may unintentionally result in poor outcomes for some patients. A DHI like Corrie can improve monitoring and support of patients during the critical post-discharge period, providing value to healthcare providers, hospital systems, and patients alike. Our analysis indicates that the DHI not only has potential to support health system cost-savings and success in value-based payment models, but that it can also serve as a valuable resource for patients in their recovery. Although the study is focused on Corrie in AMI recovery, we believe the analysis has broader implications for transitions of care and home-based care models.

Limitations, Strengths, and Future Directions

The risk of recurrent AMI within the DHI group is currently noted as being zero due to no readmissions due to AMI. However, these are unadjusted figures and do not necessarily reflect the risk in the general population of post-AMI patients. While the MiCORE study used propensity scores to ensure a balanced distribution of measured confounding variables at baseline between the DHI and historical control groups and also provides strong data on real world effectiveness, a randomized controlled trial would provide more definitive efficacy data. Furthermore, the sample size of 200 AMI patients in the DHI group could pose a limitation; however, sufficient power was achieved in the MiCORE study to compare 30-day readmission between the DHI and control group.¹⁷ In addition, while the budget impact analysis offers an initial assessment beyond the focused hospital perspective, future studies should attempt to evaluate the cost-effectiveness of DHIs from a more comprehensive societal perspective.

Furthermore, it should be noted that most of the MiCORE participants were admitted to 2 hospitals in [State], which operate under an all-payor global budget system, which incentivizes hospitals to reduce readmissions. Even so, 2018 reports from the Centers for Medicare and Medicaid Services and other investigators demonstrate no appreciable differences in 30-day readmission rates for all inpatient admissions between [State] hospitals and matched control groups, so [State]’s unique health economics should not substantially impact the external validity of our results.^37,38

While DHIs like Corrie Health offer a non-invasive mechanism to reduce readmissions, making them available to all patients entails additional complexity and resources. Transitioning this research to routine practice will require consideration of the costs associated with study personnel, liability insurance, data maintenance, and security measures. Additional costs may be required to make a resource like Corrie available to patients with sensory impairments or cognitive decline. These costs should all be factored in when computing an overall ICER that accounts for wider costs.

The benefits of Corrie may not be uniformly experienced by the target patient population, particularly by older adults.¹⁷ Selection bias may hinder the generalizability of these results. Ultimately, only 22% of eligible inpatients were enrolled in the DHI group in the MiCORE study,17 which is similar to another inpatient DHI study with an enrollment rate of 14%. ³⁹ The majority of patients were excluded from the DHI group because they did not own a smartphone.¹⁷ Yet, the DHI group was still a diverse sample with a mean age of 59.2 (SD: 11.5) years, 29% women, 29% non-White, and median household income of $70,000.¹⁷ The median household income in the DHI group was similar to the U.S. Census 2015–2019 American Community Survey which estimated household income at $62,843.40

A future step would be to incorporate features that make the DHI accessible to a wider population, regardless of education or income levels. Nevertheless, 71% of low-income adults and 53% of adults aged 65 and older in the U.S. own a smartphone.⁴¹ Among low-income adults, 26% are dependent on smartphones for Internet access.⁴¹ Thus, DHIs have the potential to expand access to care. However, in an analysis from the MiCORE study, it was found that age, sex, and race were not significantly associated with DHI use even after adjusting for a number of covariates.42 Thus, DHIs may have a role in improving health equity. Cost-effective interventions that are potentially reimbursable by Medicare/Medicaid may have particular impact among underserved populations. Finally, although Corrie was available only on iOS devices during the MiCORE study, we provided ‘loaner’ iPhones to patients with other types of smartphones.¹⁴ This allowed us to recruit a more socioeconomically diverse sample and mitigate selection bias.¹⁴

Sustainability

There are a number of factors that need to be considered for long-term success of the program. In the research environment, MiCORE study team members identified potential participants through the electronic medical record, delivered the DHI to patients, educated patients on technology use, and acted as tech support if needed. Future success of the program will depend upon integration of the DHI into clinical practice. Instead of study team members, this could be done through a transitional care navigator or an automatic electronic medical record feature to identify eligible patients and send a message to download the DHI. Then the patients and their family could use short videos that guide the set-up process. From that point, intervention fidelity is crucial and future research could assess the role of a clinician portal and automated reminders generated from real-time patient data to increase interactivity and feedback, and patient engagement. Ultimately, long-term clinical adoption of the program will likely depend upon how well the technology can be integrated into the usual care pathway.

Conclusion

The current results, among the first to systematically evaluate the cost-effectiveness of a DHI specific to CVD, suggest that DHIs have significant potential to enhance standard treatments while cutting costs associated with post-MI treatment.