Introduction

Today, morbidity and mortality resulting from chronic diseases affect over 133 million Americans [1]. With about 17% Hispanics, 13% Blacks, and 5% Asians comprising the US population, health outcomes among these racial and ethnic minorities are of critical importance to the American Healthcare System [2]. Racial disparities in the burden of disease and mortality caused by chronic conditions like diabetes, heart disease, and chronic respiratory conditions are well documented [3, 4]. Since 1988, non-Hispanic Blacks have experienced much higher age-adjusted prevalence of diabetes, hypertension, and obesity compared to the other racial/ethnic groups [5]. According the Center for Disease Control and Prevention, non-Hispanic Blacks, Hispanics (particularly Mexican Americans and Puerto Ricans), and Asian Americans had higher risk of developing diabetes compared to non-Hispanic whites [6]. Non-Hispanic Blacks bear a higher cardiovascular disease burden in the USA, with a higher prevalence of hypertension and poor control compared to non-Hispanic Whites and Mexican Americans [7]. For chronic pulmonary conditions like chronic obstructive pulmonary disease (COPD), historically, Whites had a much higher prevalence and hospitalization risk. However, the prevalence among non-Hispanic Blacks is increasing [8]. Doshi et al. examined the existing evidence on racial disparities in preventable hospitalizations due to chronic ambulatory care sensitive conditions. Non-Hispanic Blacks suffer from a significantly higher burden of preventable hospitalizations due to chronic conditions like diabetes, congestive heart failure, and hypertension [9].

The primary objective of this narrative review is to present evidence regarding the different approaches to chronic disease management in general population and racial/ethnic minority population in the context of chronic ambulatory care sensitive conditions (ACSCs). Successful behavioral and digital health approaches involving interventions targeting patients were identified. In addition, we discuss the impact of digital interventions in improving health outcomes among racial/ethnic minority patients with chronic ACSCs. For this study, we have limited our focus to chronic ACSCs resulting in the highest rates of morbidity and mortality and where racial and ethnic disparities are already demonstrated [9].

For this study, we examined studies involving interventions targeting chronic ACSCs like diabetes, congestive heart failure, hypertension, asthma, and COPD among general population and specifically targeting racial and ethnic minority patient populations. Search terms including “digital health,” “ehealth,” “mhealth,” “diabetes,” “congestive heart failure,” “hypertesion,” “asthma,” “COPD,” “minority,” “race,” “ethnicity,” “racial disparity,” “Black,” “African-American,” “Hispanic,” and “Asian” were used. We evaluated over 1500 abstracts from MEDLINE and Google Scholar and cited over 59 articles.

Diabetes

In one of the early meta-analysis of interventions for diabetes, Padgett et al. (1988) reviewed 93 studies, which used didactic education, enhanced education, diet instruction, exercise instruction, self-monitoring instruction, social learning, counseling, and relaxation training. Among these interventions, diet instruction (mean effect size 0.68; CI ± 0.33) was found to be most effective in improving glycemic control and patient knowledge [10]. In a review evaluation studies for interventions for adult minority diabetic patients, Peek et al. identified 17 patient-targeted interventions (13 RCT, 1 controlled trial, 3 pre-post studies). They found that computer-based interventions were ineffective when applied without a human interaction component. In addition, culturally tailored interventions significantly reduced HbA1c (mean HbA1c reduction 69%; CI 0.37–1.0) [11]. Joo identified nine interventions published between 2005 and 2013 involving culturally tailored diabetes programs targeting older Asian (Bangladesh, China, Philippines, Korea) adults in the USA and examined their effect on improving intermediate health outcomes (HbA1c, lipids, weight, blood pressure), quality of life, and satisfaction. While three studies found positive changes in HbA1c, the fourth study did not see a significant change in HbA1c [12,13,14,15]. Dauvrin and Lorant identified 61 publications related to culturally competent interventions for type 2 diabetes and applied the equity model framework to examine the quality of research in this area. However, a majority of these studies failed to consider other factors such as health insurance coverage, socioeconomic determinants, and gender that impact health equity among minority patients [16]. Baig et al. reviewed 18 articles that involved digital quality improvement interventions focused on diabetes health disparities among Blacks and Hispanics between 2006 and 2009. A patient-centered approach was employed, in combination with culturally tailored interventions using peers and social networks, for the digital interventions in six of these studies. They found cognitive-behavioral education and self-care management interventions adapting the current National Diabetes Prevention program were effective in improving glycemic control. Improvements in HbA1c were associated with interventions using personalized reports of laboratory values and goals [17].

More recently, the application of a long-term, multi-disciplinary, primary-secondary integrated care model applied to disadvantaged, multicultural population, reduced diabetes-related potentially preventable hospitalizations by 50% at 24 months [18]. In the early 1990s, Fedder et al. demonstrated that community health worker visits and phone calls had the potential to reduce hospitalization among African-American Medicare patients with diabetes by a third [19]. A prospective follow-up study on adult, African-American diabetes patients in 2001–2003 found that frequent contact (≥ 4 visits) with nurse care managers and community health worker was associated with a significant reduction in hospitalizations [20]. A nurse-led team intervention involving a detailed algorithm to provide appropriate care to diabetes patients reduced hospitalization rates by 51% in a predominantly African-American and Latino sample [21].

Electronic and mobile health interventions have used a number of different approaches to reduce hospitalizations among patients with diabetes. In one of the earliest telemedicine interventions, Smith et al. attempted to test the effectiveness of phone calls in reducing hospitalizations among diabetes patients. They found that while the intervention did improve compliance with scheduled physician visits, it did not reduce hospitalizations significantly [22]. Van den Berg et al. reviewed 18 studies using telemedicine interventions to improve diabetes outcomes among ambulatory elderly patients (≥ 60 years). The studies considered objective (medical outcomes, hospitalizations, mortality, healthcare utilization), patient reported (quality of life, acceptance, satisfaction, empowerment), and economic outcomes (costs, cost-effectiveness). Among the 16 studies that had hospitalizations as an outcome, 11 showed positive results, four were similar outcomes among intervention and control groups, and one had mixed results [23]. Health Buddy, a web-based patient interface technology, has been in use for monitoring diabetes and heart failure patients for over a decade. A recent pre-post study revealed that the use of the Health Buddy technology reduced the 1 year readmission rate among indigent border residents in California suffering from diabetes by 32% [24]. Cotter et al. reviewed the application of internet-based interventions to lifestyle modification among type II DM patients. They found nine studies, two of which demonstrated improvements in diet and/or physical activity and two demonstrating improvements in glycemic control. Almost all of these interventions focused on the individuals’ use of the technology to create an online community while ignoring the ecology surrounding the individual in real life. They concluded that there was need for more research involving high-risk and under-served populations in order to reduce health disparities [25].

Congestive Heart Failure

Between 1966 and 1999, there were 11 trials testing disease management programs for heart failure patients. While the effect varied by intervention, overall risk ratio of hospitalization due to heart failure was 0.87 (CI 0.79–0.96) in the intervention group. A substantial reduction in hospitalization rates (RR 0.77; CI 0.68–0.86) was observed for interventions involving specialized follow-up by multidisciplinary teams [26]. In Australia, exposure to general practitioner-led clinical management reduced readmissions among heart failure patients by 23%. The 1-year readmission rate for heart failure among exposed patients was 8.6% compared to 10.7% among unexposed patients [27]. Among older adults and elderly patients with history of heart failure, home-based telemanagement programs have shown great promise, with 1-year readmission rates among those exposed to the intervention almost half those of controls (19% readmitted vs. 32%; RR 0.49) [28]. Picture-based educational materials in combination with scheduled telephone follow-up showed reduction in hospitalizations among low literacy population (IRR = 0.39; CI 0.16, 0.91). Interventions like the iGetBetter system, which used transmission of self-monitored metrics through an iPad, improved patient engagement but no significant changes in planned (p value 0.23) and unplanned (p value 0.99) hospitalizations [29]. In their review, Delgado-Passler and McCaffrey demonstrated that advanced practice nurse-led telemanagement program reduced not only readmissions but also multiple admissions and healthcare costs among heart failure (HF) patients [30]. Manning took into consideration evidence regarding predictors of heart failure readmissions including race while developing a simple bedside screening tool for nurses. When used in combination with access to HF nurse educator for high-risk HF patients, there was marked reduction in 6-month hospitalization rates [31]. The Tele-HF randomized controlled trial found that daily monitoring by telephone reduced all-cause hospitalization rates among congestive heart failure (CHF) patients [32]. In their review evaluating evidence regarding mhealth interventions for CHF patients, Cajita et al. found that none of the nine studies showed conclusive evidence regarding its effectiveness in reducing heart failure-related hospitalizations [33].

Nahm et al. applied the transtheoretical model to examine the behavioral intention and readiness to use for a web-based learning module and telemonitoring and found that there was no significant difference between Black and White Medicare patients [34]. In a comparative effectiveness study for nurse telemonitoring (along with home monitoring device that transfer physiological monitoring data to providers) vs nurse home visits in a predominantly Black population, it was found that the former significantly reduced HF readmissions at 3 months (p ≤ .001) and 6 months (p ≤ .05) [35]. Conversely, Copeland et al. found that nurse telemanagement interventions including education and coaching for behavior change showed no improvement in patient outcomes in a 22% Hispanic patient sample in a single site pre-post study conducted at the Veterans Health administration [36]. More recently, significant improvement in maintenance and management was observed in predominantly Black sample of HF patients using automated text messaging heart failure program delivering self-care reminders, patient education on diet, symptom recognition, and health care navigation [37].

Hypertension

Basic approaches to interventions for management of hypertension include diet modification and behavior change targeting salt consumption and weight reduction. With the availability of novel technologies in the early to mid-1990s, researchers started applying electronic and mobile-based interventions to improve outcomes among hypertensive patients. A number of studies targeted biologically vulnerable populations. In their “Five Plus Nuts and Beans” trial with African American patients, Miller et al. used a dietary intervention providing the treatment group with coach-directed dietary advice and assistance with weekly online ordering and purchasing of high-potassium foods (DASH-plus diet). The control group received information about the DASH diet. The DASH-plus group increased their consumption of fruits, vegetables, and estimated potassium intake. However, they found no significant difference in blood pressure in the two groups after 8 weeks [38]. The findings of this study point to the difficulties in remediating racial disparities in hypertension given the biological vulnerabilities of African-Americans.

Digital interventions such as internet-based counseling have been widely evaluated for their efficacy in reducing blood pressure. Lui et al. performed a systematic review identifying 13 trials and concluded that interventions that lasted 6 months or longer, used five or more behavior change techniques, or delivered health messages proactively were more likely to have the greatest impact on reducing blood pressure [39].

While a number of studies have utilized mobile-based interventions to monitor and reduce high blood pressure, very few mhealth studies have looked at hospitalizations as an outcome. In their systematic review of telemonitoring interventions, Verberk et al. concluded that telecare was a valuable tool for management of patients with high blood pressure [40]. Currently, there are two ongoing studies, which will utilize text messaging to control hypertension. The use of a text messaging system, BPMED, to increase medication adherence among African-American patients was tested recently [41]. The StAR trial, a South African study, has medication adherence as the primary outcome and hospital admissions as the secondary outcome [42]. Findings of the hypertension intervention nurse telemedicine study revealed that combined behavioral and medication management improved the mean systolic blood pressure among African-American patients at 12 months by 6.6 mmHg (95% CI − 12.5, − 0.7; p = 0.03) and at 18 months by 9.7 mmHg (95% CI − 16.0, − 3.4; p = 0.003) [43].

Asthma

Asthma has been one of the health conditions that is most amenable to improved management via telehealth interventions. In mid-1990’s, Hoskins et al. demonstrated the effectiveness of self-management plans in reducing hospital admissions among asthma patients [44]. Griffith et al. found that a specialist nurse-led, liaison model-based intervention in East London reduced unscheduled care among White patients but had no impact on South Asian, Hispanic, and non-Hispanic Blacks [45]. This finding is in keeping with other studies showing that asthma education has lower impact on South Asians in the UK compared to Whites [46]. Subsequently, digital interventions for asthma self-care and management have been used to improve health service use, medication use, and self-management behaviors among patients. Apter made a case for the use of patient portals as resources for disease management education, communication with healthcare providers and improved access to healthcare thereby reducing racial disparities in asthma outcomes [47]. Fiks utilized an electronic health record-tethered patient portal on 60 families with asthmatic children and found marked reduction in emergency department use and hospitalizations [48]. However, five RCTs tested web-based interventions to reduce hospitalizations among adults and children but found no significant impact [49]. Lorig et al. used an internet-based self-management program including interactive self-management instructions and tools, four bulletin board discussion groups, and an instructional book (“Living a Healthy Life with Chronic Conditions”). This intervention, which was grounded in self-efficacy theory, was tested using a prospective, longitudinal, repeated measures design and reported no impact on 12-month hospitalization rates in the intervention group [50]. However, a small RCT using SMS messaging for peak expiratory flow rate monitoring was associated with significantly reduced hospitalization rates [51]. Two recent studies examining the use of smart phone applications to improve outcomes among asthma patients found no statistically significant effect on frequency of 6-month hospital admissions. However, one of these studies did observe a statistically significant reduction in emergency department use [52, 53]. A small pilot study examining the effect of tailored mhealth intervention with a gaming approach with incentives for positive behaviors among African-American adolescents on inhaled corticosteroids showed a marked improvement in medication adherence at 8 weeks. However, when the researchers conducted a randomized controlled trial with a larger intervention, they found significant improvement in self-reported adherence (p < 0.001) but no improvement in objectively measured adherence (p 0.929) at week 10 [54, 55].

Chronic Obstructive Pulmonary Disease

A meta-analysis of 26 randomized controlled trials involving multidisciplinary or multi-treatment integrated COPD management programs with duration of at least 3 months revealed that admissions were lower among intervention groups compared to control groups. The mean duration of hospital stays among the intervention groups was 3.78 days shorter than controls [56]. However, two large well-designed international studies have reported that telemonitoring of patients with COPD did not improve short-term hospitalization rates [57, 58]. Similarly, use of an electronic diary intervention with COPD patients in Philadelphia produced a small, non-statistically significant reduction in hospitalizations in the intervention group. However, the lack of significant differences could be because of the Hawthorne effect due to the rigorous symptom monitoring of symptoms among the control group. A systematic review of nine studies testing the effectiveness of home telemonitoring of COPD patients found that there was significant reduction in hospitalization rates [59]. Overall, evidence suggested that interventions with longer durations improved the long-term admission rates for COPD. Despite the marked racial disparities in healthcare utilization for COPD, there is scarcity of research focusing on mhealth interventions targeting racial and ethnic minorities.

Table 1 presents the summary of review papers that addressed the efficacy of digital health interventions to improve outcomes in chronic ACSCs.

Table 1 Highlighting systematic reviews of interventions for chronic ambulatory care sensitive conditions
Full size table

Conclusions

Interventions to reduce preventable hospitalizations have shown great promise. The most promising have typically involved long-term interventions with multiple contacts over time involving human interaction and have been most effective for diabetes, congestive heart failure, and asthma [18, 20, 30]. Within this group of successful interventions, a number of electronic and mobile health approaches to individual and population-level interventions involving telephones, internet and web-based resources, and mobile platforms have been deployed in controlled studies to improve chronic disease outcomes. Electronic monitoring of health metrics was found to be an effective approach for reducing hospitalizations related to COPD and asthma, while telemonitoring was effective in reducing hospitalizations for CHF patients and improving overall control among hypertensive patients [32, 40]. For asthma, SMS monitoring of a specific disease metric (PEFR) was associated with decreased hospitalization [51]. While smart phone applications were ineffective in reducing hospitalizations, one application was associated with decreased utilization of emergency care [52, 53]. Home telemonitoring was a particularly effective intervention for COPD patients [59].

Although this research demonstrates that behavioral and digital interventions may be useful for improving health outcomes, it is not clear whether they can meaningfully reduce race and ethnic disparities in hospitalization among those with chronic diseases. Very few interventions have specifically targeted chronic ACSC hospitalizations in racial minorities, and the evidence for their effectiveness is at this point promising but inconclusive. In addition, intervention studies focusing on minority populations often use the same approach as studies targeting general population. While Manning et al. successfully identified race as a risk factor for diabetes, their study outcomes did not measure the impact of their educational interventions on racial disparities [31]. However, culturally tailored interventions have been associated with improved outcomes among Blacks and Asians [12, 16]. Furthermore, our review of this literature suggests that most telehealth and mhealth interventions mainly target basic theoretical factors implicated in preventable hospitalizations, such as socioeconomic status and health behavior, and do not address the complex sets of exposures and psychological stress resulting from minority status that are likely implicated race and ethnic disparities in these outcomes. Given this gap in approach to interventions, mhealth interventions addressing race and ethnic disparities would be well served by adopting a more comprehensive and multifactorial approach targeting the causes of racial disparities to reducing preventable hospitalizations among minority population with chronic diseases.