AI in Healthcare – What Patients Want vs. What Providers Offer
Shalini Singh, SVP Research, Insights Square
Jun 17, 2025
Digital health is transforming healthcare delivery worldwide, promising to bridge longstanding gaps in access, quality, and efficiency. While the momentum behind health tech is unmistakable - spurred by technological advances, government initiatives, and shifting patient expectations - the journey is complex. Both established healthcare systems in the West, such as the US, and rapidly evolving markets like India are navigating similar challenges and opportunities, albeit with their unique contexts. Today, let us explore the expectation gap in digital health, the persistent unmet needs of patients, technological and implementation hurdles, and the cost barriers that shape adoption, weaving in examples from India and the broader global landscape.
The Expectation Gap
Patients today increasingly anticipate that healthcare technology will deliver the same seamless, user-friendly experiences they encounter in other sectors. Whether it’s scheduling appointments online, accessing health records instantly, or receiving tailored health recommendations, expectations have risen sharply. The COVID-19 pandemic accelerated this digital shift, with teleconsulting trends and remote care becoming commonplace.
Yet, the reality often falls short. In metropolitan cities, a patient might expect to consult a specialist online through a hospital’s app but finds the service unreliable due to technical glitches or a lack of integration with smart hospitals. Additionally, patients often anticipate frictionless digital interactions but may encounter outdated portals, cumbersome login processes, or incomplete health information. These gaps between expectations and actual experiences can lead to frustration, diminished trust, and lower engagement with e-health tools.
Healthcare professionals also face their own set of expectations and realities. Doctors are expected to embrace AI health tools, but the reality of heavy patient loads and limited time per consultation often make clinical informatics and telehealth integration challenging. For example, a doctor in a developing nation like India may see 40–60 patients a day, have little time to upload detailed patient data.
Areas Where Patient Needs Remain Unmet
Despite the promise of technology-driven patient care, several critical patient needs remain unaddressed across diverse healthcare industry blog discussions.
Digital Health Literacy and Usability
Digital literacy is a significant barrier, especially among older adults and rural populations. In India, while initiatives like eSanjeevani have expanded remote health consultation trends, many patients in rural areas struggle to navigate these platforms without assistance. Language diversity in healthcare apps further complicates matters, as many mobile apps for health monitoring are available only in English or Hindi, leaving out speakers of regional languages. In the more developed nations, usability issues often stem from complex interfaces, frequent logins, and manual data entry requirements, which can discourage even tech-savvy users.
Access Barriers
Reliable internet connectivity and access to devices remain unevenly distributed. In remote Indian villages, patients may lack smartphones or stable internet, excluding them from virtual health benefits. Even in the US, rural areas and underserved urban communities may face broadband infrastructure gaps, limiting the reach of cloud healthcare and other digital services.
Cultural and Language Gaps
Healthcare platforms that do not account for linguistic and cultural diversity risk alienating large sections of the population. For example, the Char Dham Yatra patient monitoring initiative in Uttarakhand leverages digital tools to track pilgrims’ health, but those without smartphones or digital literacy still rely on traditional methods. In Western contexts, non-English speakers and individuals from diverse backgrounds may struggle with platforms that lack adequate language support, perpetuating disparities in access and real-world digital health outcomes.
Technological Limitations Creating Disappointment
The promise of AI in healthcare is often undermined by technological realities on the ground.
Connectivity and Infrastructure
Infrastructural limitations, such as restricted internet connectivity and inadequate medical equipment, are major hurdles in India’s digital health journey. For example, virtual clinics in remote parts of Assam are often disrupted by call drops and video lags, leading to incomplete consultations. Device limitations - such as the need for frequent charging or the lack of durability in harsh environments - can further reduce improving patient engagement digitally.
In the US, while broadband access is more widespread, system errors, slow loading times, and unreliable connections can still disrupt care, particularly in rural communities. Patients and clinicians alike may abandon digital tools if they consistently underperform or fail at critical moments.
Data Quality and Interpretation
Patients frequently receive raw health data from wearable devices for elder care without adequate guidance on interpretation, leading to confusion or anxiety. For instance, AI-powered healthcare platforms in India, such as those used for silicosis detection in Rajasthan, are innovative but face challenges in scaling up due to inconsistent digital infrastructure and a shortage of trained staff to manage the technology. In the US, remote diagnosis systems sometimes transmit incomplete or noisy data, making it difficult for clinicians to rely on the information for decision-making.
Device Stigma and User Experience
Wearable health devices can carry a stigma or be uncomfortable, reducing adherence. For instance, older adults may resist using health trackers like smartwatches due to the perception that these devices are overly complex or intended only for younger generations. Similarly, individuals with chronic conditions may reject wearables such as continuous glucose monitors because they feel these devices make their health struggles visible to others, potentially inviting judgment or pity. Furthermore, devices that fail to provide clear, actionable insights, like fitness trackers that only offer raw step counts without contextual health advice, often lead users to abandon them, as they fail to meet expectations of personalized digital health journeys.
Implementation Challenges for Healthcare Systems
Healthcare organizations worldwide face significant hurdles when integrating new technologies into existing workflows.
Organizational Readiness and Resistance
In India, foundational infrastructure remains a challenge. Many public hospitals lack reliable electricity, sufficient computers, or secure networks necessary for e-clinic access. The expectation that doctors will upload patient data themselves is often unrealistic given their heavy workloads and brief consultations. Challenges in health tech adoption are common, not only among providers but also among administrators wary of disruption and resource-intensive digitization.
Western healthcare systems, while more digitized, are not immune to these challenges. US clinicians often cite increased documentation burdens and workflow disruptions as barriers to digital adoption. Integration challenges are prevalent, as disparate software systems - such as EHRs, billing platforms, and scheduling tools - may not communicate effectively, resulting in data silos and inefficiencies that affect improving doctor-patient interaction online.
Talent and Training Gaps
The shortage of skilled personnel to manage and troubleshoot AI health tools is a global issue. In India, only a fraction of healthcare organizations has moved advanced digital initiatives into production, citing lack of specialized talent and data complexities as key barriers. In the US, ongoing training is required to keep pace with rapidly evolving technologies and regulatory requirements such as those related to digital diagnosis.
Data Privacy and Security
Cybersecurity in patient data systems is a universal concern. In India, high-profile cyberattacks, such as the 2022 breach at AIIMS Delhi, have heightened awareness of the risks associated with digitizing sensitive health information. In the US, compliance with regulations like HIPAA adds layers of complexity. Both contexts underscore the need for robust security measures and clear data governance frameworks to enhance trust in health tech.
Workflow Integration and Interoperability
Integrating new technologies into existing workflows remains a challenge. In India, the fragmentation of public and private healthcare systems complicates efforts to standardize digital health practices. The involvement of multiple intermediaries - state agencies, insurance companies, and pharmaceutical firms - can increase the risk of fragmentation and hinder bridging the digital health divide. Achieving true interoperability has proven elusive despite legislative efforts.
Cost Barriers Preventing Wider Adoption
The financial realities of cost-effective digital health tools are significant, affecting both emerging and mature healthcare markets.
High Upfront and Ongoing Costs
In India, high upfront costs for digital infrastructure, software licenses, and ongoing maintenance deter many smaller hospitals and clinics from investing in new technologies. While large urban hospitals may afford advanced digital tools, smaller facilities in tier-2 and tier-3 cities often cannot justify the expenditure, especially when the return on investment is uncertain. The initial investment required for new technologies - hardware, software, training, and cybersecurity in patient data systems - can be prohibitive, particularly for smaller or underfunded facilities.
Uncertain ROI and Reimbursement
Uncertainty around return on investment makes it difficult for decision-makers to justify expenditures, particularly when benefits may not be immediately apparent or easily quantifiable. In India, government initiatives like the Ayushman Bharat Digital Mission offer incentives for health tech adoption, but the process still requires significant capital and operational investment. In the US, lack of clear reimbursement policies for digital health services, such as telehealth adoption in rural areas, further discourages adoption.
Real-World Examples and Emerging Solutions
Across the globe, innovative medical innovation efforts are making a tangible impact, even as challenges persist.
India’s Ayushman Bharat Digital Mission (ABDM)
India’s ABDM is a flagship initiative aimed at creating a unified digital health ecosystem. It integrates health records across public and private sectors, enabling smoother patient journeys and bridging digital health divide. The eSanjeevani teleconsulting service has facilitated millions of consultations, connecting remote areas to quality healthcare and demonstrating remote care’s potential to bridge disparities.
Private Sector Innovation in India
The private sector in India has seen the rise of unicorns like Practo and Medi Buddy, which have scaled rapidly by offering smart clinics, pharmaceutical delivery, and wellness services. These platforms cater to an increasingly mobile health-first consumer base, especially in urban centers, but also highlight the need for broader digital literacy and access.
In the US, health systems are leveraging digital tools to enhance care delivery. Programs like Hospital at Home combine in-person and virtual consultations with patient monitoring, improving outcomes and reducing costs. Virtual behavioral health services integrate with primary care to expand access to mental health treatment.
Patient Stories
Stories like that of Mrs. Sharma in India, who uses multiple mobile apps for health monitoring to manage her family’s care, reflect the growing reliance on digital tools.
Mrs. Sharma, a schoolteacher residing in a bustling suburb of India, has transformed the way her family accesses healthcare by incorporating digital tools into their daily lives. She uses apps like Practo and MediBuddy to schedule teleconsulting trends, order medication, and track vaccinations. With eSanjeevani, she’s consulted specialists remotely - showcasing the power of inclusive digital healthcare solutions and personalized digital health journeys.
The patients appreciate the convenience of virtual visits and remote monitoring, especially for chronic disease management, but also express frustration when technology fails to deliver on its promise.
Moving Forward: Bridging the Gap
The digital health revolution holds immense promise for transforming healthcare delivery and outcomes. Realizing this potential, however, requires a concerted effort to bridge the expectation gap, address unmet patient needs, overcome technological and implementation barriers, and ensure equitable access for all.
Key Priorities for the Future:
Expand Digital Literacy: Targeted programs to improve digital health literacy, especially in rural and underserved communities, are essential everywhere.
Enhance Usability and Accessibility: Multilingual support, user-friendly interfaces, and offline capabilities can make digital health tools more inclusive.
Strengthen Infrastructure: Investments in reliable internet, electricity, and secure networks are crucial for scaling digital health initiatives.
Foster Collaboration: Public-private partnerships and cross-sector collaboration can drive medical innovation and ensure sustainability.
Promote Data Privacy and Security: Robust cybersecurity in patient data systems and transparent data practices are essential to maintain trust.
Support Sustainable Financing: Incentives and funding models that support long-term adoption and maintenance of cost-effective digital health tools are needed.
Conduct Rigorous Research: Identifying specific need gaps through comprehensive studies and patient feedback is vital to tailor digital health solutions effectively. By understanding these gaps, innovators can design technologies that address critical issues, enhance patient engagement, and improve overall care experiences. Leveraging research to further personalize care and streamline processes, ensuring that AI health tools resonate with diverse patient populations.
By learning from diverse experiences and fostering global collaboration, stakeholders can build a more inclusive, effective, and patient-centered digital health ecosystem - one that meets the needs and expectations of patients and providers alike, regardless of geography.
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