A Review on Digital Adherence Technologies for Chronic Disease Management: Global Evidence, Implementation Gaps, and Future Directions

Chronic non-communicable diseases (NCDs), such as diabetes, heart disease, long-term lung conditions, and cancer, account for approximately 74% of deaths worldwide. According to the World Health Organization, over 41 million people die from NCDs every year.¹ It is worth noting that this is not evenly distributed. The heavier blow lands on low- and middle-income countries, where regular care can be patchy and sometimes unpredictable.¹

Managing these illnesses almost always means staying on medication in the long term. However, adherence to prescribed regimens remains suboptimal. Even in wealthier nations, as many as half of patients do not follow their prescriptions properly—and the figure is probably worse where resources are scarce.² And this isn’t just a minor lapse. This translates to worse health, more hospital visits, and, in the US alone, avoidable costs that hover around $290 billion a year.³ Over the last decade, digital health tools have started to slip into everyday chronic care, including mobile apps, wearables, text message nudges, and web dashboards. They first gained attention in diabetes care, showing early promise in helping people manage their own conditions and stay engaged.⁴ More recent research has pointed to gains in adherence, better blood sugar control, and, importantly, a sense of empowerment for patients.⁵ The idea is simple enough: send reminders, track habits in real time, and provide a bit of personal feedback.⁵ Then came the pandemic, which—despite everything—pushed these technologies into the spotlight. Remote care became a necessity, and these tools were suddenly tested at scale.⁶ Remote patient monitoring (RPM) and tele-homecare (THC) are at the heart of this shift. RPM uses connected devices, such as Bluetooth glucometers, blood pressure cuffs, and smart weighing scales, to send data directly to clinicians, flagging problems before they worsen and often saving a hospital trip.^7,8 THC takes it further: medication coaching, scheduled video check-ins, and a bit more hands-on support from afar. For older adults juggling multiple prescriptions, this can be a lifeline. Reviews so far suggest that these setups can help lower blood pressure and blood glucose and may even keep people out of the hospital more often.

The cost benefits? The evidence supports this^7,8

However, it is not all wins and breakthroughs. These digital adherence tools are a mixed bag of advantages and disadvantages. Some deliver real and measurable benefits. Others—barely a ripple. This gap indicates that we need sharper evaluations and more targeted rollouts, not just blanket adoption.^5,9 Therefore, in my view, a close, critical look at what is actually working—and why—feels overdue.

This review goes beyond summarizing the efficacy of digital adherence technologies (DATs). These interventions were situated within the broader context of health policy, regulatory preparedness, and equity-focused implementation. By integrating the most recent clinical evidence with considerations of AI-enhanced personalization, interoperability standards, and behavioural design, this review provides a multi-layered perspective. This approach is intended to support researchers, clinicians, and policymakers in translating evidence into practice in the future. Despite the increasing data on adherence improvements, guidance that is simultaneously evidence-based and implementation-ready remains limited. Accordingly, this synthesis seeks to address this gap, offering insights that may facilitate the wider, more effective, and equitable deployment of DATs.

Conceptualization of digital adherence technologies (DATs) for managing chronic illnesses.  Key categories are depicted in the graphic, such as telehealth services, smartphone apps, smart pill dispensers, AI-driven customisation, and SMS reminders sent to mobile phones. These technologies support medication adherence and patient engagement.

2. OVERVIEW OF MEDICATION ADHERENCE

The World Health Organization simply states that medication adherence is about how well someone follows the treatment plan they have agreed on with their clinician. It is not just taking the right pill at the right time; it is about starting the treatment, maintaining it day after day, and sticking with it over the long haul.² When people do not, the reasons usually fall into two broad categories. One is intentional—skipping doses on purpose because of worries, doubts, or side effects. The other is unintentional—forgetting, getting confused, or running into practical snags.^10,11 And here’s the twist: a huge survey—over 24,000 people living with chronic diseases—found that those “unintentional” mistakes, like missing a dose (62%), running out of pills (37%), or just being a bit careless (23%), often had intentional roots. In other words, what they believed about their medication was quietly shaping these slips.¹⁰ The cost of all this? Not just in money. Conditions worsen, hospital trips increase, and life expectancy decreases. In the US, poor adherence is estimated to cost $100 to $300 billion each year in avoidable healthcare spending. Globally, it is one of the major drivers of rising illness and mortality rates.^12,13 This is not a localized problem. Reviews show the same pattern— wherever you look, weaker adherence drags down chronic disease outcomes and strains the health systems.¹⁴

Traditional fixes—pillboxes, marked calendars, simpler regimens, and face-to-face counselling—can help, especially for unintentional lapses.^14,5 However, they rarely get to the root of the intentional side. Digital approaches have started to step in. These include SMS reminders, app notifications, smart caps on pill bottles, video-based check-ins, and packaging that logs every opening. They do not just nudge; they can tell if a dose was actually taken. Across different conditions—hypertension, diabetes, HIV, and asthma—reviews suggest that these tools can make a moderate but real difference.^5,7

What seems to work best, however, is when the strategy does not pick sides. Stronger interventions tackle both practical barriers—memory and routines—and mental barriers, such as beliefs and motivation.^11,5 This combination tends to outperform single-focus methods. It feels like we are moving away from one-dimensional fixes toward multi-layered, tech-backed approaches that try to capture the full messiness of why people take—or do not take—their medications.

3. TYPES OF DIGITAL TOOLS FOR MEDICATION ADHERENCE

3.1. Comparison of Medisafe and MyTherapy Applications

Mobile health (mHealth) applications are increasingly used for medication adherence, with Medisafe and MyTherapy being among the most widely adopted. Both apps provide reminder alerts and adherence tracking; however, their scope and design differ. Systematic evaluations of medication adherence apps have emphasized that usability, personalization, and clinically relevant features are critical determinants of sustained engagement and effectiveness.^15,16 Medisafe is particularly noted for its medication-specific adherence support, such as drug interaction warnings and intuitive reminder systems, whereas MyTherapy offers additional functionalities, including symptom logging and health parameter monitoring, which may be advantageous for patients with multiple chronic conditions.¹⁶ Evidence from meta-analyses of mobile-based adherence interventions suggests that such digital tools can significantly improve adherence and clinical outcomes in chronic disease management, reinforcing the clinical value of platforms such as Medisafe and MyTherapy.¹⁷

Next, we have the hardware: smart pillboxes and electronic dispensers. These have shifted the game slightly. They combine sound or visual alerts, real-time monitoring, and application-based feedback. In short, they do not just say, “take your medicine”; they can tell if you actually did.

Key elements including reminders, refill notifications, caregiver support, monitoring capabilities, motivational tools, privacy and security standards, and evidence of clinical impact are listed in the table along with citations for each.

Table 1: Comparison Of Medication Adherence Apps

In another study, this time with an Automated Home Medication Dispenser, adherence in caregiver–patient pairs increased from 49% to nearly 97%. This is a significant shift that occurred in the home setting.¹⁹ In Canada, work on the Spencer system—essentially a touchscreen smart pillbox tied into pharmacists and mobile devices—showed similarly high adherence, aided by real-time support.²⁰

Reviews generally align with these results. Electronic adherence tools tend to improve results, particularly when feedback and reminders are included. One large review of 37 clinical trials found adherence gains of up to 34% with the use of electronic packaging.²¹ And there’s a twist—reminders that fit into a person’s routine (context-aware) can work even better than fixed-time prompts. Some hit adherence rates were as high as 92%.²²

The table details commonly used smart pill dispensers and telehealth tools. It outlines their main features, target populations, adherence results, and supporting references.

Table 2: Smart Devices And Telehealth Interventions For Medication Adherence

3.3?Text Messaging (SMS) and IVR Systems

3.3.1 SMS-Based Interventions in Low- and Middle-Income Settings

In many low- and middle-income countries, SMS-based mHealth programs—sometimes nudged forward by the WHO, sometimes run with national health ministries—have shown that simple text messages can shift both patient and provider engagement. And yes, adherence too. Kenya offers a few telling snapshots. One well-known cluster-randomized trial examined malaria care for health workers. Over six months, SMS reminders improved the correct use of artemether–lumefantrine by approximately 23–24 percentage points. The twist? This effect did not fade when the messages stopped; it was still measurable six months later.²⁴

Another Kenyan initiative, the SMS RES MAL project, went for a slightly different target: caregivers of children with malaria. Automated texts reminded them of their medication schedule and follow-up visits. Adherence to the drugs was already high (70% to 97 %), but the texts noticeably improved clinic returns on days 3 and 28. This indicates how SMS can shape care-seeking habits, not just pill-taking.^25,26

The bigger picture? Well-organized text messaging, especially when linked to national treatment guidelines and included in current health systems, can do two things at once. It can support the work of providers and keep caregivers involved in a way that feels relevant to their daily lives.

3.3.2 Blended Messaging Approaches: SMS Plus Voice and Two-Way Systems

However, SMS is not the only card in the deck. Adding interactive voice response calls (IVR) has shown some extra lift, especially in HIV care and maternal health programs. In South India, one group of HIV-positive adults received weekly automated IVR calls plus SMS reminders for six months. Adherence increased from 85% to 91%, and people generally liked it. Interestingly, these gains did not evaporate when the calls and texts stopped.²⁷

In Kenya, a study compared one-way SMS with two-way SMS for new mothers living with HIV. Viral suppression did not differ significantly between the groups; however, two-way messages led to a faster uptake of postpartum contraception. This is not a minor behavioural shift.²⁸

Then, there is South Africa’s Mom Connect. Although not directly related to medication adherence, it is difficult to exclude. This national maternal health SMS platform has reached more than 2.7 million users. It is feasible, scalable, and built to last.²⁹

Taken together, these blended approaches—IVR plus SMS, two-way messaging, and even a bit of human touch—tend to lift behaviours linked to adherence, contraception uptake, and broader engagement with healthcare. Of course, the results still hinge on the setting, program design, and, quite honestly, how well it is executed in the real world.

Table 3A: Digital Communication And Telehealth Interventions For Medication Adherence

Table 3B: Ai-Driven And Digital Therapeutics Interventions

3.4 Wearables and Smartwatches  

3.4.1 Syncing Medication Reminders to Wearables

Smartwatches, such as the Apple Watch and Fitbit, are being used in medication reminder systems. The appeal is obvious. Vibrations, alarms, and visual prompts are delivered straight to the wrist. No phone required. For some, that is a big deal—less fiddling with devices and more immediate nudges.

One randomized controlled trial examined older adults using a medication-reminder wristwatch. The results? Patients exhibited noticeably better adherence over 12 weeks and felt more confident in handling their medicines. Moreover, their average systolic blood pressure dropped to approximately 120 mm Hg compared to approximately 142 mm Hg in those without the device (p < 0.001).³⁰ Scoping reviews back this general trend—wearables do seem to help across various conditions by sending those small but persistent prompts—vibrations, beeps, flashes—right where people cannot easily ignore them.³¹

3.4.2 Biofeedback and Adherence Tracking

Then, there is the more advanced side of things—wearables that do not just remind but also detect. Passive tracking of biofeedback to determine when a dose is actually taken. Cochran and colleagues, in NPJ Digital Medicine, reported that patterns in daily activity and heart rate variability could predict medication-taking behaviour in people with serious mental illness. Not just loosely statistically significant (p = 0.004).³²

Another example is Odhiambo et al. (2023) in the JMIR Human Factors. Using accelerometer data from everyday consumer smartwatches run through a neural network, they identified medication-taking gestures with approximately 96.5% accuracy. Even in new real-world contexts.³³ That’s impressive.

These data streams are not just for the sake of collecting numbers. They can feed into dashboards for doctors and patients—shared visibility, early flags, and a chance to step in before adherence slides too far. Of course, the technology works best when paired with actual human follow-up.

3.5 Telemedicine Platforms

3.5.1 Virtual Follow-Ups & e-Prescription Renewals

Some of the most consistent wins in digital adherence work have come from plain old structured telemedicine—virtual follow-ups, plus the ability to get a prescription renewed without travelling to a clinic. The numbers are not bad either. One 2024 meta-analysis pooling data from 18 RCTs in type 2 diabetes showed a moderate but real lift in adherence when telehealth was built in automated check-ins and e-prescribing (SMD = 0.50; 95% CI 0.23–0.77; p<0.001).³⁴ And there’s more. Systematic reviews have consistently highlighted that telemonitoring does not merely nudge adherence; it can actually trim HbA1c, with some trials finding larger drops for patients in more intensive telehealth setups than for those on simpler remote-monitoring plans. The interesting bit? In some cases, the self-management boost persisted for a year.³⁵

It is not only a diabetes story. In hypertension care, pharmacist-led video consultations combined with e-prescriptions have been linked to steady falls in systolic BP, along with better adherence.³⁶ That’s worth noting. Because it is a reminder that these virtual visits are not only about convenience. They can grease the wheels for medication renewals and keep people moving along in their treatment without so many speed bumps.

3.5.2 Patient–Provider Messaging & Accountability

The patient–provider messaging is the quieter, less flashy side of telehealth. Secure platforms, sometimes paired with calls, have been surprisingly effective in keeping people accountable for actually taking (and refilling) their medications. A 2021 systematic review observed consistent improvements in medication possession and refill rates for chronic conditions, such as diabetes, hypertension, and hyperlipidaemia, when these tools were used.³⁷

Let us now focus on HIV care. A 2023 meta-analysis of five RCTs found that messaging and calls together increased ART adherence by approximately 18% (RR = 1.18; 95% CI 1.03–1.35; p<0.05).³⁸ That’s not trivial. Qualitative work suggests that it is not only the reminders; it is the chance to report side effects, get quick feedback, and feel like the provider is still there in between appointments.³⁹ When these tools are stacked on top of regular virtual check-ins, a sturdier telemedicine loop is created —one that keeps the patient engaged, spots trouble before it snowballs, and helps treatment stick.

3.6 AI Chatbots and Digital Assistants

3.6.1 Reminders, Check-Ins, and Voice-Based Interactions

AI-driven chatbots and voice assistants have been getting a fair bit of attention lately. Not just hype— there is actually some substance. Aggarwal et al. in 2023, for example, pulled together evidence showing that these tools—whether embedded in messaging platforms or sitting on mobile apps—can give a genuine lift to adherence. They have been used to nudge people into more movement, cut down on smoking, and keep medications on schedule, all by firing off reminders, helping set goals, and logging symptoms.⁴⁰ The pattern? They work better when the nudges feel personal and not canned, and when responses come quickly.

Voice assistants are also entering this space. Barreda’s 2025 review noted their growing role in chronic disease care—dropping short verbal prompts about medications, follow-ups, and routine health checks. The kicker is that they sound less like machines than their predecessors. This softer tone matters; it helps people stick with it without feeling worn out.⁴¹ Bérubé et al. (2024) pulled from different studies and described voice systems that timed their check-ins according to a person’s habits or the time of day. That small tweak? This seems to boost satisfaction and keeps the engagement curve from dipping too soon.⁴²

3.6.2 NLP-Driven Behaviour Prompts (2021–Present)

Now, once natural language processing started to hit its stride around 2021, the chatbots themselves shifted. Less scripted. More conversational. And a bit more… human. Oh et al. reported that these NLP-powered bots could nudge healthier habits and, in some cases, give medication adherence a push in the right direction.⁴³ The same Aggarwal review pointed out that they outperformed older rule-based bots, mostly because they could shape language on the fly, respond with empathy, and keep people from tuning out.⁴⁰

Bérubé’s 2024 findings round it out: voice assistants using both NLP and contextual cues— such as altering reminder timing based on earlier responses—end up feeling more personal and trustworthy. Not perfect, but in the long game of habit building, that trust seems to make the difference.⁴²

3.7 Digital Therapeutics (DTx)

3.7.1 FDA-Approved Examples (e.g., reSET-O, Kaia Health)

Some of the clearest signs that prescription digital therapeutics (PDTs) have moved beyond theory come from products like reSET® and reSET-O®. Both were developed by Pear.

Therapeutics, and reSET-O®—which made it through the FDA’s De Novo pathway—sits alongside buprenorphine in treating opioid use disorder (OUD). It is not just another app; trials have shown that it can improve treatment retention and help patients stay abstinent in outpatient settings.⁴⁴ The program leans heavily on cognitive behavioural therapy (CBT) modules, delivered over the phone, and keeps people engaged with structured lessons and personal feedback. Then there is Kaia Health—technically not FDA-approved but still operating under enforcement discretion. It is aimed at musculoskeletal pain using app-based multimodal therapy that blends physical exercises with bite-sized education. Results? Notable decreases in pain, stress, and depression symptoms.⁴⁵ Taken together, these cases suggest that when digital therapeutics receive regulatory recognition—or even a green light to operate—they can deliver evidence-based care, make it easier for patients to get help, and relieve some of the burden on already stretched health systems.

3.7.2 Adherence-Focused Digital Behaviour Change Programs

Another space where these tools are starting to show real value is in fixing one of healthcare’s most stubborn problems— adhering to the treatment plan. A recent (2025) systematic review pointed out that for chronic conditions such as heart disease, diabetes, and COPD, weaving in motivational nudges—reminders, feedback loops, even light gamification, or social encouragement—can move the needle on adherence.⁴⁶ One interesting study followed people using Laddr™, a digital therapeutic that builds in small prompts for self-regulation. Those moments of reflection, triggered at the right time, predicted next-day adherence and were associated with improvements in step counts and fewer cigarettes smoked.⁴⁷ A broader meta-analysis in oncology found that users of digital interventions had approximately a 40% lower risk of poor adherence than non-users (OR 0.60; 95% CI 0.47–0.77). However, the trial results were not perfectly aligned, and heterogeneity was high (I² = 73.1%).⁴⁸ Even so, the takeaway feels consistent enough: when these programs are designed with behaviour change in mind—real-time feedback, habit reinforcement, and prompts that actually make sense in the moment—they can give adherence a solid boost.

4. EVIDENCE FROM STUDIES

A good chunk of solid meta-analyses and RCTs now leave little doubt that digital tools built for adherence can push the needle on both sticking to medications and improving the numbers that matter. We are discussing hypertension, diabetes, asthma, and HIV. In low- and middle-income countries, Boima et al. (2024) noted that simple channels—SMS, smartphone apps, and phone calls—produced a standardized mean bump in adherence of 1.59 (95% CI 0.51– 2.67). This is not bad, especially with parallel drops in systolic BP (−5.75 mmHg) and some lifestyle gains that, while harder to quantify, seem worth noting.⁴⁹

Zoom in on diabetes and hypertension: A systematic review of 17 RCTs found that mobile apps were not just a novelty. They trimmed HbA1c by roughly −0.39% and nudged blood pressure lower, while getting people more engaged with self-management.⁵⁰ In asthma and COPD, the 2022 Cochrane review observed a similar pattern. Tools such as electronic monitoring devices and SMS increased adherence by approximately 14.7 percentage points (95% CI 7.7– 21.6). Better asthma control (SMD 0.31, 95% CI 0.17–0.44) and a modest drop in exacerbations (RR 0.53, 95% CI 0.32–0.91) were also observed.⁵¹

Figure 1. The chart shows adherence improvement (expressed as standardized mean difference [SMD], percentage points, or Cohen’s d) for various chronic conditions, including Hypertention (1.59), diabetes (0.39), asthma/COPD (1.47), and HIV (0.25).

Table 4: Efficacy Of Digital Adherence Tools Across Key Chronic Conditions

5. BENEFITS AND LIMITATIONS OF DIGITAL ADHERENCE TOOLS

Digital adherence tools—or DATs if we’re going to shorten it—cover a wide mix: smart pillboxes, phone apps, wearables, even remote monitoring setups. They tend to pull their weight in a few key areas of the company. First, they can boost patient engagement through targeted reminders, personal feedback, educational snippets, and occasional gamified nudges.

Chronic conditions, such as diabetes and cardiovascular disease, are the obvious beneficiaries.^50,53 They also allow clinicians to monitor things from a distance, such as real-time adherence patterns and key physiological signals, which opens the door to timely interventions and can give patients a stronger sense that they can manage their own care.⁵⁴

The economics are not bad either. Several systematic reviews have examined cost-effectiveness, and the results are fairly consistent. Video-observed therapy (VOT) and mobile-based systems for TB treatment are often cost-effective, sometimes even cost-saving, especially in middle- and high-income settings.^55,56 True, the studies are not all equally tight in methodology, and the way they report economic outcomes can vary. However, once the basic infrastructure is in place, scalability is difficult to argue. The marginal cost per extra user is small, which makes the case for long-term value fairly strong ⁵⁷

However, adoption is not frictionless. Access to devices and the Internet is not universal—older adults and underserved groups are often left behind. Even when technology is available, usability and digital literacy issues can nudge people toward disengagement, sometimes resulting in complete dropout.⁵⁴ Then, there is the matter of privacy and data security, which regularly raises eyebrows. People worry about breaches and sensitive health information going to places it should not. Clinicians, meanwhile, face their own headaches: extra alerts, data overload, and the ongoing mess of integrating these tools with electronic health records when interoperability standards are missing.⁵⁴

Therefore, DATs can do a lot: keep patients engaged, allow remote follow-up, and make economic sense over the long haul. But, and it’s a big but, those gains won’t hold in practice unless the digital gaps are narrowed, the data is safeguarded properly, and the tools are slotted into workflows without adding more chaos.

 6. CHALLENGES IN IMPLEMENTATION

The rollout of digital adherence tools (DATs) is rarely a straight shot. These hurdles tend to overlap.

First, there is a digital divide. Rural areas still lag behind cities in terms of EHR adoption and broadband reach. The gap isn’t small. Older adults also engage far less with digital platforms, which means that outreach is uneven before it even begins. Broader reviews keep pointing to the same bottlenecks—underserved communities lack infrastructure, affordable Internet, and sometimes the basic digital skills to make use of these tools. Without these, DATs cannot be deployed effectively.^57,58

Concerns exist over cybersecurity and data privacy as well. GDPR and HIPAA set clear rules on consent, encryption, breach alerts, and keeping data collection to a minimum. On paper, everything is there. In practice? Enforcement can be minimal. Many consumer-grade tools skirt the legal definitions entirely. Regulations have not caught up with third-party trackers or the movement of health data outside clinical settings. McGraw and Mandl suggested a more layered fix—baking privacy in from the start, adding governance at multiple levels, and still leaving room for innovation.^59,60

Integration with clinical workflows is another challenge. Even where EHRs are common, real interoperability is inconsistent. Rural providers with lower “meaningful use” uptake feel this more sharply. Clinicians face messy, fragmented workflows, in addition to the constant drip of alerts; alert fatigue is real. The absence of standard protocols makes it more difficult. Without addressing these barriers, embedding DATs into day-to-day care will remain an uphill climb.⁶¹

What does it take to move past these limitations? Infrastructure investment to close the rural–urban gap. Digital literacy programs that meet users where they are. Tougher and smarter enforcement of data protection rules. For the clinical side, stronger interoperability and standardized workflows are required. Without these pieces in place, adoption may occur, but it is unlikely to be successful.

7. GLOBAL POLICIES AND REGULATORY ASPECTS

Regulation of digital adherence technologies (DATs) has been gaining speed globally and nationally. The idea is simple: if these tools are going to be part of real healthcare systems, they

need clear rules, standards, and a shared vision for how they fit in. Globally, the WHO’s Global Strategy on Digital Health 2020–2025 attempts to set this direction. Endorsed at the 73rd World Health Assembly, it promotes secure, interoperable systems and equitable access to health data worldwide. The language is big-picture— harmonizing governance, pushing for equity, and building national capacity through shared global standards and pooled investments.⁶² The Global Initiative on Digital Health (GIDH) was then established to turn that blueprint into action. It relies on ethical governance, cross-border interoperability, and the development of digital public goods as core priorities.⁶³ India’s path has been quick by comparison. The Ayushman Bharat Digital Mission (ABDM), launched in 2021, is creating a federated, consent-based health ecosystem. These include unique health IDs (ABHA), national registries of healthcare professionals and facilities, and a unified Health Information Exchange (HIE). The aim is to let patient data follow the patient across states, sectors, and providers. With over 400 million citizens already linked, it is a sizable leap toward a national-scale digital health infrastructure.⁶⁴ Elsewhere, regulations and reimbursements have taken different forms. The U.S. The FDA uses a risk-based model for Software as a Medical Device (SaMD), housed under its Digital Health Innovation Action Plan. Oversight runs through the Digital Health Centre of Excellence, which manages precertification programs and helps move digital therapeutics toward approval, ideally backed by both clinical trial results and real-world evidence.⁶⁵ Germany offers a contrasting model to the United States. Under its DiGA pathway, certain physician-prescribed apps receive statutory reimbursement once vetted by the Federal Institute for Drugs and Medical Devices.

(BfArM). In contrast, the United States still has a fractured picture—private insurers, some Medicare pilots, and new billing codes slowly making their way into practice. Despite its infrastructure progress, India is still figuring out how to fund this space. Early pilots linked to Ayushman Bharat-PNJAY and the talk of value-based assessment from expert committees hint at where it might go.⁶⁶

Taken together, these efforts point to the same conclusion: coordinated policy—whether global or national— is not just helpful; it is essential if DATs are going to be deployed in a way that is safe, effective, and built to last.

Table 5: Policy Landscape For Digital Adherence Technologies

 8. FUTURE TRENDS IN DIGITAL ADHERENCE TECHNOLOGIES

The next wave of digital adherence technologies (DATs) is being pushed forward by a mix of forces—AI, interoperability standards, behavioural economics, and a sharper look at multimorbidity. These trends are not isolated; they feed into each other.

First, artificial intelligence is used. Machine learning has already made it possible to send hyper-personalized “nudges” that shift in real time with a person’s behaviour. Scoping reviews note that AI-driven digital behaviour changes interventions—using reinforcement learning, conversational bots, and recommendation systems—can offer custom-tailored support and, in many cases, modest but measurable improvements in health behaviours. However, the long-term effects of this approach remain uncertain.⁶⁷ On the design side, there is experimentation with generative AI for crafting adherence messages for diabetes. Early work shows that it can produce huge volumes of varied, evidence-aligned content—enough to keep messaging fresh at scale.⁶⁸

Second, interoperability is required. Getting DATs to talk to electronic health records is not a nice-to-have; it is a backbone requirement. The FHIR standard, with its modular RESTful architecture, is emerging as the go-to standard for smooth data exchange and API-based integration. Reviews emphasize that semantic interoperability and systematic FHIR adoption— especially for telemonitoring and adherence apps—are already making deployment easier and more scalable.^69,70

Third, the blend of gamification with behavioural economics is explored. This is not just badges and points. Studies have shown that AI-enhanced “choice architecture” can make nudges more persuasive—enough to shift adherence patterns and pull patients into deeper clinical engagement. Reward systems, goal-setting, and feedback loops, all grounded in behavioural economics, have become standard in managing complex chronic care ⁷¹

Finally, tool design is being stretched to handle multimorbidity and polypharmacy. This means that systems can adjust messaging when patients juggle multiple regimens—simplifying when needed, highlighting the essentials, and reducing cognitive overload. AI has already demonstrated how this can work in practice, although the evidence base is still in its early days.^67,68

Together, these trends hint at where DATs are heading—AI making them more personal, interoperability making them more connected, behavioural science making them more engaging, and multimorbidity support making them more relevant to the patients who need them most.

Figure 2.