Navigating Organizational Challenges of Digital Transformation: A Qualitative Study of Meso-Level Public Health Officers in an Indian High-Priority Aspirational District

Abstract

Background: Digital transformation is reshaping public organizations worldwide, yet in low-resource contexts, its success is constrained by weak infrastructure and governance. In India, programs such as the Ayushman Bharat Digital Mission and the Aspirational Districts Programme rely on meso-level officers who act as key managerial intermediaries, but their organizational challenges remain understudied. Aim: This study examines sub-district health and nutrition officers’ experiences, organizational barriers, and adaptive strategies in implementing digital reforms. Methods: Eight in-depth interviews were conducted with Medical Officers in Charge (MOICs) and Child Development Project Officers (CDPOs) across urban, semi-urban, rural, and flood-prone blocks of Muzaffarpur, Bihar. Data were transcribed, translated, and thematically analyzed using Braun and Clarke’s approach, informed by organizational and technology adoption theories. Results: Officers valued digital tools for transparency and real-time monitoring but faced systemic barriers, including hardware decay, poor connectivity, fragmented platforms, and limited fiscal autonomy. Despite these, they displayed managerial agency through informal infrastructures such as WhatsApp, peer mentoring, and parallel records. COVID-19 accelerated digital use while widening inequities. Conclusions: Meso-level officers are critical enablers of organizational resilience. Their experiences highlight how leadership, governance, and adaptive management shape digital transformation in resource-constrained settings.

1. Introduction

Digital health is reshaping the fabric of health systems around the globe, promising new pathways toward universal health coverage, especially in low- and middle-income countries (LMICs) where health inequities persist due to chronic resource constraints and infrastructural gaps (Labrique et al., 2018; Vedavalli et al., 2023). The rapid expansion of technologies such as electronic health records (EHRs), mobile health applications, telemedicine, and advanced analytics has opened opportunities to transcend longstanding barriers of distance, limited workforce, and fragmented service delivery (Iyamu et al., 2021). In countries where public health systems must reach vast and often underserved populations, these digital innovations have enabled real-time data collection, remote consultations, and timely decision-making that were previously unattainable (Till et al., 2023; Woods et al., 2024). Digital transformation in public systems is, therefore, best examined through lenses that connect individual adoption with broader socio-technical dynamics and organizational resilience, a view we adopt in this study (Greenhalgh et al., 2017).

India stands at the forefront of this digital health transformation. With a projected population above 1.4 billion in 2025, the country presents an immense challenge of transforming the resource-constrained and poor human development-indexed (HDI) districts and a proving ground for the large-scale application of digital health (Bhatia et al., 2018; Ministry of Health and Family Welfare, Government of India, 2025). Recognizing these dual realities, India has rolled out ambitious initiatives such as the Ayushman Bharat Digital Mission (ABDM) and the Aspirational Districts Programme (ADP), designed not only to modernize the health system but also to reduce deeply entrenched health inequities (Bhatia et al., 2018; National Health Authority (NHA), India, 2022; NITI Aayog, Government of India, 2018). The ABDM, launched in 2021, seeks to build a federated digital health ecosystem in which every citizen is assigned a unique health ID, EHRs are interoperable, and secure information exchange is the norm. By 2025, ABDM has achieved remarkable milestones, including creating over 740 million Ayushman Bharat Health Accounts and registering hundreds of thousands of health facilities. Particularly in extremely poor and health-wise poor performing empowered action group (EAG) states like Bihar, the adoption of digital health technologies has accelerated rapidly, with more than 90 percent of outpatient registrations now conducted online (National Health Authority, n.d.; Arokiasamy & Gautam, 2008).

Running parallel to ABDM, the ADP, launched in 2018, targets 112 districts identified as underperforming across indicators such as health, nutrition, education, financial inclusion, and basic infrastructure. This program represents a national experiment in focused, data-driven development, aiming to reduce disparities through real-time monitoring, intensive support, and outcome-based competition among districts (NITI Aayog, Government of India, 2018).

Central to both the ABDM and ADP are a range of public health programs inculcating various digital platforms tailored for public health management. Some common portals and applications are the Health Management Information System (HMIS), which provides the backbone for aggregating facility and community-level health data (Braa et al., 2004; Meghani et al., 2022). ANM Online (ANMOL), a mobile application designed for Auxiliary Nurse Midwives (ANMs), facilitates early identification and follow-up of high-risk pregnancies and child health issues. The Poshan Tracker, a core digital tool of the Integrated Child Development Services (ICDS) program, enables real-time monitoring of nutrition for millions of children and pregnant women (Ministry of Health and Family Welfare, Government of India, 2023; Ministry of Women and Child Development, Government of India, 2021, 2022). Over the past few years, these platforms have undergone significant upgrades, incorporating features such as biometric authentication, enhanced dashboards, and faster data synchronization, all of which are intended to enhance timeliness, accuracy, and transparency in service delivery (Jaacks et al., 2024; Ministry of Health and Family Welfare, Government of India, 2023).

Despite the scale and ambition of national digital health initiatives, substantial implementation challenges persist. Although digital health is widely recognized for its potential to enhance efficiency, reach, and accountability in healthcare delivery, the translation from policy to practice remains inconsistent. For example, India’s digital health market is projected to grow rapidly, reaching approximately Rs 882.79 billion by 2027, fuelled by increased smartphone penetration, demand for telemedicine, and government investment in digital infrastructure (Medical Buyer, n.d.). Yet, this growth coexists with persistent disparities in access and outcomes, largely attributable to infrastructural gaps, variable digital literacy, inconsistent internet connectivity, and fragmented organizational systems (Inampudi et al., 2024; World Health Organization, 2019).

These barriers are not unique to India. Studies from multiple LMICs highlight similar on-the-ground challenges, including unreliable electricity, frequent disruptions in mobile networks, inadequate technical training, and insufficient ongoing support for users (World Health Organization, 2021, 2024a, 2024b). For frontline community health workers, these issues are compounded by digital overload and the proliferation of poorly integrated platforms, leading to frustration and limited uptake (Pgdha et al., 2023). Evidence from recent studies in India underscores that health workers face a “forced dependency” on personal phones and cyber-cafés to maintain essential data flows, and that gaps in digital literacy further entrench hierarchies within the workforce. Without comprehensive solutions that address these multi-layered barriers, including targeted investments in infrastructure, digital literacy, and robust technical support, the transformative potential of digital health in improving equity and outcomes will remain unrealized in many LMIC contexts (Gudi et al., 2021; Verdezoto et al., 2021).

Most of the academic literature on field-level digital health implementation in India has focused on frontline community health workers (CHWs), also commonly known as the frontline workers (FLWs), a group that includes Accredited Social Health Activists (ASHAs), Auxiliary Nurse Midwives (ANMs) working with the health department, and Anganwadi Workers (AWWs) working with the women and child welfare department (Gopichandran et al., 2023; Scott et al., 2018). These workers are often the first and only point of contact between the health system and the community, and their experiences have yielded critical insights into challenges such as device malfunction, information overload, high workloads, and barriers related to digital literacy (Kalne et al., 2022; Perry, 2020). Recent studies have also highlighted the exacerbation of existing social divides by digital interventions, with issues of privacy, inclusivity, and trust emerging as major concerns for marginalized populations (Gudi et al., 2021; Kurian & Chawada, 2023; Patil et al., 2022; Scott et al., 2019).

However, this focus on the frontline often obscures the pivotal role of so-called “meso-level” officers, those mid-tier managers/officers who supervise, coordinate, and ultimately determine the operational success or failure of public health and nutrition programs on the ground (Birken et al., 2018; Department of Health and Family Welfare, Government of Kerala, 2017; Jyoti, 2023; Schneider & Mianda, 2024). In India’s administrative system, the district is subdivided into blocks, each serving an extremely varied population of around 10,000 to 700,000 people, which is comparable to the population of a mid-sized to large-sized city in many parts of the world, and in some parts, almost as populated as a state or country (Maheshwari, 1984; Nag & Farhat, 2021; Government of India, n.d.). Each block is managed by two key officers: the Medical Officer-in-Charge (MOIC), who oversees public health and primary care, and the Child Development Project Officer (CDPO), who manages nutrition and maternal-child health programs under ICDS (Department of Health and Family Welfare, Government of Kerala, 2017; Jyoti, 2023). Together, these officers supervise hundreds of CHWs, oversee complex dataflows, resolve technical issues, and ensure compliance with a range of public health and nutrition mandates.

The adaptive capacity, decision-making, and day-to-day problem-solving of these block-level officers are crucial determinants of the success of public health programs, including the digital health platforms. Their perspectives shape the translation of high-level policies into locally relevant action, the identification of bottlenecks, and the sustainability of reforms in the face of adversity. Yet, despite their centrality, the lived experiences and adaptive strategies of these officers remain almost invisible in the literature, especially in the context of under-resourced, overburdened districts like the aspirational districts in the Indian scenario (Nag & Farhat, 2021; Sahoo et al., 2016; Bhatia et al., 2019). This represents a significant research gap in the Indian digital health context. Middle managers’ influence on implementing innovations is increasingly recognized, but their perspectives on health IT reforms are seldom documented (Birken et al., 2018; Schneider & Mianda, 2024). This gap in understanding is particularly consequential in complex, resource-constrained settings, where the resilience of the health system is tested daily by challenges such as infrastructure failure, natural disasters, and public health emergencies.

Growing consensus in global health points to the necessity of aligning technology with strong human resources, governance, and context-specific adaptation. Behavioral and technology acceptance models, including the Health Belief Model (HBM), Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB), and Unified Theory of Acceptance and Use of Technology (UTAUT), offer lenses on drivers and barriers of digital health adoption (Ahadzadeh et al., 2015; Ajzen, 1991; Holden & Karsh, 2010; Min et al., 2024; Rosenstock, 1974). These models emphasize the importance of perceived benefits and barriers, organizational support, and the role of attitudes and intentions in shaping behavior. Yet, organizational inertia, bureaucratic fragmentation, and infrastructural weaknesses continue to pose obstacles to realizing the full potential of digital health platforms, and much more needs to be understood about how policies and technologies influence operational management and what attitude these field-level officers have regarding the ongoing programs under the digital health umbrella.

Against this backdrop, the present qualitative study, embedded within a registered doctoral project, seeks to fill a critical knowledge gap by exploring the experiences, perceptions, and strategies of block-level officers in Muzaffarpur district, Bihar, India, an aspirational district context rarely examined in prior research. The study is guided by the following research questions:

How do block-level officers perceive, use, and adapt to digital health platforms in their day-to-day work?

What technical, financial, organizational, and contextual barriers do they encounter, and how do they address these challenges?

In what ways did the COVID-19 pandemic affect digital health adoption and equity in their blocks?

What reforms do block-level officers recommend for building a unified, sustainable, and user-centric digital health system in resource-limited environments?

This study makes three core contributions. First, it theorizes middle digital leadership in resource-constrained public systems by showing how block-level officers convert fragile digital tools into reliable organizational routines despite infrastructural and bureaucratic pressures. Second, it identifies empirically grounded mechanisms, including workarounds, boundary spanning, and stabilizing micro-infrastructures that link everyday adaptations to resilient service delivery. Third, it offers actionable implications for program governance and product design in high-priority districts, such as offline first features, cyclic capacity building, and block-level micro-autonomy for rapid issue resolution.

By centering the voices of these critical yet understudied actors, the research provides policy-relevant recommendations and is among the first to examine block-level health managers’ experiences with digital initiatives in an Indian aspirational district. Lessons from Muzaffarpur extend beyond Bihar, offering transferable insights for other low and middle-income countries (LMICs) facing similar connectivity, capacity, and coordination constraints. The intent is analytic generalization, with mechanisms adaptable to comparable settings rather than statistical inference.

2. Materials and Methods

2.1. Study Design and Rationale

As an exploratory inquiry, this qualitative study took an observational approach and formed an integral part of the first author’s doctoral research, prospectively registered with Clinical Trials Registry-India (CTRI/2023/04/051581, registered on 10 April 2023). Its central aim was to generate an in-depth understanding of the operational realities, adaptive strategies, and decision-making of block-level officers overseeing digital health programs in Muzaffarpur district, Bihar, India. Bihar was selected as it is one of India’s Empowered Action Group (EAG) states, characterized by significant developmental challenges, including low per capita income and human development indices, making it a critical region for studying digital health implementation (Arokiasamy & Gautam, 2008; Basu, 2016; S. Kumar et al., 2020; U. K. Singh, 2022).

A qualitative approach was chosen specifically for its ability to reveal nuanced experiences, contextual influences, and hidden dynamics often inaccessible to quantitative surveys (Patton, 2015). In-depth interviews were deemed most appropriate for exploring these complex phenomena, as this method allows participants to openly discuss challenges and adaptations in their own terms, yielding rich, detailed data (Scally et al., 2021). The focus on MOICs and CDPOs reflects the unique Indian administrative structure, where each of the district’s 16 blocks is led by a single MOIC and CDPO, who are responsible for translating digital health policy into action on the ground.

Semi-structured, in-depth interviews served as the main data collection tool, enabling systematic exploration while providing the flexibility needed to probe emergent themes. The interview guide was carefully constructed based on established theoretical frameworks, including the HBM, TAM, and UTAUT. These frameworks allowed the research to explore not only barriers and facilitators but also officers’ attitudes, informal workarounds, and their recommendations for system improvement.

2.2. Setting and Context

Muzaffarpur district is located in the North-Central part of Bihar state and is one of the major cities in North Bihar. It is one of the 13 Aspirational districts of Bihar state.

Muzaffarpur district in Bihar offers a compelling setting for addressing the evidence gap. As one of India’s 112 Aspirational Districts, Muzaffarpur is characterized by significant health and nutrition challenges, recurrent flooding, and high population density, with nearly six million residents as of 2025 and a recorded population of 4.8 million as per the 2011 census (Government of India, 2011b, n.d.). It is also the most populated aspirational district as per the census records. The district is divided into 16 blocks, each with one MOIC and one CDPO who together oversee the delivery of health and nutrition services across diverse operational contexts: urban, semi-urban, flood-affected, and remote rural environments (Government of India, 2011a, 2011b; District Muzaffarpur, Government of Bihar, India, n.d.-a, n.d.-b). Despite repeated investments in strengthening the public and digital health infrastructure, Muzaffarpur continues to struggle with persistent undernutrition, low rates of institutional deliveries, infrastructural deficits, and the annual disruption of services by floods (P. Kumar et al., 2023; Malaviya et al., 2014; Topno et al., 2025). These challenges render the district an important policy laboratory for studying the real-world barriers and enablers of digital health reform.

Block-level officers are uniquely positioned to respond to these challenges, supervising hundreds of frontline health and nutrition workers (each block-level officer interviewed directly manages more than a hundred community health workers), managing complex flows of digital data, especially the field-level data, and ensuring accountability in health and nutrition programs. These officers’ daily realities, decisions, and adaptive strategies play a decisive role in the success or failure of digital health implementation.

2.3. Sampling and Participant Selection

A purposive maximum variation sampling approach was adopted to capture the district’s full range of operational diversity. Four blocks were selected to represent different settings: Musahari (urban headquarters), Kanti (semi-urban and rapidly developing), Katra (rural, flood-prone in the northeast), and Paroo (remote rural in the southwest). Kanti block comprises 113 villages with a total population of 272,858; Katra block includes 76 villages with a population of 244,823; Paroo block consists of 136 villages with a population of 361,662; and Meshari block, which is predominantly urban, has 49 urban wards with a total population of 396,590 (Government of India, 2011a). This design ensured that the research reflected urban density, peri-urban transition, seasonal flood disruptions, and remote, logistically challenged environments.

Within each selected block, only the MOIC and CDPO were invited to participate, yielding a total sample of eight officers (four MOICs, four CDPOs). All eligible officers approached agreed to participate, resulting in complete coverage of the top-level block officers across diverse operational contexts. Each had at least one year’s tenure in their current post and was actively engaged in the management and oversight of digital health platforms, including the HMIS, ANMOL, uWIN, the Poshan Tracker, etc. The participant profile is available in

Table 1. Characteristics of Block-Level Officers (n = 8).

Participant ID	Cadre	Gender	Years in Service *	Block Setting	Staff Supervised	Principal Digital Platforms	Dominant Implementation Challenges
IMRK1	Medical Officer	Male	3	Rural, flood-prone	≈100	ANMOL, U-WIN, Bhavya, RCH, NCD	Network outage, staff skill gaps
IMRP1	Medical Officer	Male	12	Rural	≈100	Supportive Supervision, U-WIN, HRMS	Mandated BSNL network, data quality issues
IMSUK1	Medical Officer	Male	11	Semi-urban	≈350	ANMOL, Bhavya, U-WIN, IDSP	Forty per cent of staff are digitally weak, app overload
IMUU1	Medical Officer	Male	8	Urban	24	ASHWIN, Bhavya	Limited fiscal autonomy, intermittent internet
ICRK1	Project Officer	Female	22	Rural, flood-prone	330 centres	Poshan Tracker, Angan, PMMVY	Seventy percent of phones are dead, no electricity
ICRP1	Project Officer	Female	22	Rural	345 centres	Poshan Tracker, Angan	Ninety percent of phones are dead, low recharge funds
ICSUK1	Project Officer	Female	16	Semi-urban	345 centres	Poshan Tracker, Angan	Outdated 1 GB phones, broken weighing scales
ICUU1	Project Officer	Male	4	Urban	300 centres	Poshan Tracker, Angan, PMMVY	Multiple app burden, data verification anxiety

* Years in permanent cadre. IMSUK1 previously held a seven-year contractual post (total 18 years).

in the results section. For piloting, a CDPO from a separate block outside the main sample was interviewed by telephone, and feedback from this pilot informed refinements to the final interview guide. Although the sample size was small, it included all key block-level officers in the chosen blocks, as suggested by the district administration and research committee to maximise variation across urban, semi-urban, flood-affected, and remote settings. Given the relative homogeneity of role mandates, by the eighth interview, no new sub-themes or themes were emerging, indicating that thematic saturation had been achieved (Guest et al., 2006).

2.4. Research Team, Reflexivity, and Trustworthiness

The first author (AT, male, PhD Scholar) conducted all recruitment, consent, interviews, transcription, translation, and coding. He brought public health management experience in four states of India; however, he and his team had no professional or personal relationship with participants, which helped foster openness while reducing social desirability bias. Throughout the project, the first author maintained a reflexive diary to record assumptions, analytic decisions, and potential influences of his positionality. The supervisory team included the doctoral guide (BR)), co-guide (PM) and subject experts in public health research (VCS) and social science research (SK) who provided methodological oversight and independently reviewed randomly selected segments of transcripts and coding for quality assurance.

The team’s diversity in gender, academic background, and regional familiarity was leveraged to enhance analytic rigour. Regular team meetings focused on consensus-building, ensuring that interpretations were grounded in data rather than individual bias. Member checking was undertaken with two participants to confirm the accuracy of interview summaries and emerging themes.

2.5. Interview Guide Development and Piloting

The semi-structured interview guide was built upon the HBM and supplemented with TAM, TPB, and UTAUT constructs. Key domains included officers’ professional responsibilities, exposure to and use of digital health platforms, perceived benefits, barriers, support systems, adaptive strategies during crises such as COVID-19, and recommendations for system strengthening. The guide was translated and pretested with a CDPO from a fifth block to refine clarity, context sensitivity, and sequencing. Feedback from this pilot led to improvements in question phrasing and the addition of probes on the impact of recurrent flooding and the administrative workload of integrating multiple digital platforms.

2.6. Data Collection

Data were collected from May to December 2023. All eight interviews were conducted by the first author in Hindi, participants’ preferred language, ensuring comfort and authenticity. The interviews took place in private settings at the officers’ offices to foster open conversation. Sessions ranged from 30 to 80 min, averaging 45 min. Each was audio-recorded with prior written informed consent. No one other than the participant and interviewer was present. Immediately after each interview, field notes were recorded to document non-verbal cues and contextual observations.

All recordings were transcribed verbatim into Hindi, then translated into English by the first author. Special care was taken to preserve culturally significant words and idiomatic expressions, often retaining the original Hindi in brackets within the English transcripts. Random transcript excerpts were reviewed by two co-authors who were fluent in both languages to ensure translation fidelity. Data saturation was achieved by the eighth interview, as no new codes or themes emerged.

2.7. Data Analysis

Thematic analysis was conducted using ATLAS.ti (version 24), following the six-phase process outlined by Braun and Clarke (Braun & Clarke, 2006). Braun and Clarke’s reflexive thematic analysis approach was chosen for its systematic yet flexible process, which allowed us to capture both anticipated and unexpected patterns in the data, aligning well with our exploratory objectives. The first author familiarized himself with the data through repeated readings, then generated initial codes inductively, mapping these codes onto theoretical constructs where relevant. In total, 230 unique codes were developed after multiple rounds of coding, code refining, and merging guided by the two subject matter experts (SK) and (VCS), and done primarily by (AT) in the guidance of (BR), the process encompassing both explicit (semantic) and implicit (latent) content. Codes were iteratively grouped into categories, sub-themes, and overarching themes through constant comparison and team discussion.

Random checks of transcripts and codes by supervisory team members (RB, VCS, SK) further improved the quality. Any discrepancies were resolved through consensus. Detailed audit trails through email, codebooks, and analytic memos were maintained to support transparency and reproducibility. This reflexive analytical process facilitated the integration of deductive and inductive insights, providing a robust basis for identifying how officers perceive and navigate digital transformation in their context.

2.8. Ethical Approval, Preregistration, and Data Protection

Ethical approval for the doctoral project, which this study is a part of, was granted by the Institutional Ethics Committee of Kasturba Medical College & Hospital, Manipal Academy of Higher Education (IEC No. 658/2021. The study was prospectively registered as an observational study with the Indian Council of Medical Research’s (ICMR) wing, the Clinical Trials Registry-India (CTRI/2023/04/051581). Even before the ethical committee approval was obtained, written permission was obtained from the district administration. Before conducting the interviews, written informed consent was obtained from all participants for participation and audio-recording. Confidentiality was ensured by removing all identifying information from transcripts and assigning pseudonyms and codes. All data were securely stored on password-protected devices and were accessible only to the research team.

2.9. Reporting Guidelines

This study has been reported per the Consolidated criteria for reporting qualitative research (COREQ) guidelines to ensure methodological transparency and rigor. The completed 32-item checklist, detailing how the study addresses each reporting standard across its design, analysis, and findings, has been made available as Supplementary Materials.

3. Results

The section highlights five major themes that trace a pathway from structural constraints to adaptive practices and, ultimately, resilient routines: digitalization as an enabler, systemic barriers, adaptive agency, the pandemic as catalyst and divider, and consensus on system-level reform. Results trace the analytic process from the initial reading of transcripts to constructing an integrated thematic schema, following Braun and Clarke’s six-phase approach (Braun & Clarke, 2006). Quotations are presented in participants’ own words and attributed by cadre and block to illustrate the richness of the data and uphold thick description.

3.1. Analytic Process: From Familiarisation to Report Production

3.1.1. Phase 1: Familiarisation

All eight in-depth interviews, covering 139 pages of English translation, were read and reread alongside the original Hindi audio to ensure fidelity. Reflexive memos documented immediate impressions, particularly the officers’ simultaneous pride in digital transformation and frustration with chronic system failures. Initial patterns highlighted three motifs: the symbolic value of real-time rankings, ongoing irritation with the proliferation of fragmented apps, and the omnipresent use of WhatsApp as an unofficial digital infrastructure.

3.1.2. Phase 2: Generating Initial Codes

A combined inductive–deductive coding approach was undertaken in ATLAS.ti. While the initial coding generated approximately 900 codes, these were rigorously reviewed and refined to 230 codes, which were then organized into 27 constructs. The deductive aspect was guided by predefined domains from established behavioral models, ensuring alignment with theoretical constructs relevant to digital health adoption and health worker behavior. At the same time, the coding process was kept open and inductive, allowing for the identification of new, unanticipated themes and nuances in the data. This approach ensured the inclusion of explicit (semantic) and interpretive (latent) content. The coding was highly granular, attentive to topic, affect, or context changes. In vivo codes such as “phones are useless junk” (as described by a CDPO) and “Corona brought tools and opportunities” (MOIC) were retained to preserve the authenticity of participant perspectives. To ensure reliability, fifty percent of transcripts were cross-verified by two co-authors. The final codebook, developed with clear operational definitions, encompassed key constructs such as digital platform usability, infrastructural gaps, financial barriers, training and capacity building, work culture changes during and after COVID-19, peer support, community engagement, interdepartmental coordination, and perceived benefits of digitization, among others.

3.1.3. Phase 3: Searching for Candidate Themes

Codes were iteratively grouped into broader categories. This process surfaced nineteen analytic categories spanning individual, organizational, and systemic levels. Mapping code relationships revealed a sharp divide between enabling factors and persistent barriers to effective digital governance.

3.1.4. Phase 4: Reviewing Potential Themes

Themes were rigorously checked against the complete dataset for coherence and distinction. Categories such as “financial and bureaucratic constraints” merged into Systemic barriers, while “COVID-19 adaptations” was elevated to a standalone theme due to its cross-cutting influence. All categories were well-supported by data from multiple participants, and each was examined for block-level and cadre-level variation.

3.1.5. Phase 5: Defining and Naming Themes

The final thematic scheme included five major themes, each supported by sub-themes reflecting subtle variations by block (urban, semi-urban, rural, flood-prone) and cadre (MOIC, CDPO).

Table 2. Thematic Framework with Exemplar Quotations.

Theme	Sub-Themes	Representative Quotation
Digitalisation as an enabler	Real-time monitoring, transparency, efficiency	“After being online, the entire India can see what work has been done in our hospital.” (MOIC)
Systemic barriers	Hardware decay, network gaps, skills deficit, low stipends, fragmented apps	“Ninety per cent of the phones are not working… they were distributed six years ago.” (CDPO)
Adaptive agency	WhatsApp, peer tutoring, parallel registers	“At 3:09, I put it on WhatsApp; at 3:30, they received it.” (MOIC)
Pandemic catalyst and divider	Rapid diffusion, virtual work culture, digital divide	“Not before COVID, but during COVID, we started virtual meetings.” (MOIC)
Consensus on reform	Integrated app, recurrent training, infrastructure, and fiscal autonomy	“If all apps are merged, data will come in one place, and no one will have a problem.” (MOIC)

summarizes the thematic framework with representative quotations.

3.1.6. Phase 6: Producing the Report

The thematic narratives below elaborate on each theme with direct quotations, emphasizing shared experiences and context-specific nuances.

3.2. Profile of Participants

The eight officers interviewed comprised four Medical Officers and four Child Development Project Officers, with a range of service experience across the district’s diverse block settings. Detailed characteristics of the participants are presented in Table 1.

3.3. Thematic Findings

3.3.1. Theme 1: Digitalisation as an Enabler of Data-Driven Governance

Officers viewed digital tools as transformational levers for transparency, speed, and accountability. One CDPO described the shift from manual to digital registers: “Now you can monitor sitting anywhere… There is no need to call workers to bring bulky registers.” One of the MOIC observed: “Entire India can see what work has been done in our hospital,” underscoring how digital visibility increases motivation and perceived accountability. In rural Katra, dashboards allowed MOICs to respond quickly to emergencies: “During floods, the Disaster Branch requests a line listing of all pregnant women; earlier, it took days; now it’s instant.” OTP-based confirmation in Poshan Tracker enabled direct beneficiary verification: “Beneficiaries themselves now use a public site to track their status,” said one of the CDPOs, building trust and transparency. In settings with high migration, U-WIN’s pan-India immunization data aided continuity of care, especially for children in migrant families.

3.3.2. Theme 2: Systemic Barriers That Blunt the Promise of Technology

Hardware failure was universal. Officers reported that many phones were non-functional, with one CDPO stating, “Around ninety percent of the phones are not working; these are useless junk”. At the same time, another noted that seventy percent of phones at their rural centres were unusable. Frequent power cuts in rural block compounded downtime: “About ninety per cent of centres have no electricity, so phones are charged at neighbours’ houses,” said a CDPO. Network unreliability was a significant problem in rural areas: “Network issue in the field… if there remains no network in far-flung areas, how will servers work?” (one of the MOIC). Urban officers had more reliable broadband but faced app crashes during peak use.

Human resources and digital literacy gaps are layered on these constraints. “They are not even able to understand the buttons, from where to click,” said one MOIC about older Anganwadi workers. App overload was demotivating: “A jungle of multiple apps… repeated the same data entry on different portals and apps” (One MOIC). Financial stipends for internet/data were seen as inadequate: “They receive only INR 200 per month for internet connectivity, which is insufficient,” stated one of the CDPOs. Block officers lacked autonomy to replace broken equipment: “Where machines are damaged, the quality gets slightly compromised.”

Design flaws added further complexity. “Lack of offline work capability in the Poshan Tracker app” was a recurrent grievance. U-WIN frequently froze during mass immunization sessions, necessitating manual records. Officers felt personally responsible for failures driven by higher-level decisions: “This is beyond my control, as it’s a directive from above,” contributing to stress and low morale.

3.3.3. Theme 3: Adaptive Strategies and Professional Agency

Despite these challenges, officers exhibited resilience and agency. WhatsApp was central to communication and coordination: “Last night at 10 PM, I sent a message, and today, everyone came and complied” (one MOIC). In remote Paroo, “Report we take on WhatsApp,” said a CDPO. Peer-learning was encouraged: “Since the younger generation is familiar with smartphones, they assist” (one CDPO). Officers maintained parallel paper registers as insurance: “If the portal shows lower numbers, we pull the registers for verification” (one MOIC). Motivational tactics included public praise for junior staff and supportive supervision.

3.3.4. Theme 4: The Pandemic as Catalyst and Divider

COVID-19 accelerated digital uptake but also exposed and widened existing inequities. “Covid led to digital innovation,” said one MOIC. “During COVID, people could pre-book slots for vaccinations,” recalled a CDPO. However, officers noted persistent barriers: “No special apps during COVID-19… but phone being one of the most important tools during COVID-19” (MOIC). Repairs were impossible, and delayed payments for honoraria disrupted work. Rural blocks faced prolonged isolation: “It was a significant challenge, but our Sevikas handled it with a smile” (CDPO). While virtual meetings became the norm, “challenges of maintaining professionalism during virtual meetings” persisted. Officers preferred in-person capacity-building sessions: “Workers can ask questions more openly.”

3.3.5. Theme 5: Consensus on System-Level Reform

Across settings, officers voiced a near-unanimous reform agenda:

• Integrated Platform: “If all apps are merged, data will come in one place and no one will have a problem.” (MOIC)
• Cyclical, Hands-On Training: “There should be a regular refresher course organized by the department.” (CDPO)
• Robust Infrastructure: “Without electricity, the phone is a decoration.” (CDPO)
• Block-Level Fiscal Autonomy: “No incentives for best performing blocks or sectors.”

They advocated for an offline-capable, interoperable platform, regular local training and tech support, adequate devices and infrastructure, and micro-level fiscal flexibility to empower local innovation.

3.4. Integrating the Themes

These themes depict block-level officers as pragmatic, resourceful mediators bridging the divide between digital policy ambition and ground-level realities. While they recognize the transformational potential of dashboards and e-payments, they face daily friction from outdated devices, poor connectivity, and fragmented systems. Through ingenuity, WhatsApp groups, family tutoring, and parallel registers, they sustain program momentum, highlighting the importance of human agency in fragile systems.

The pandemic intensified both the opportunities and challenges of digital health. Officers’ reform agenda centers on universality: a single, integrated platform, ongoing participatory training, and investments that reach every worker, in every block, including the most remote. The iterative, transparent analytic process starting from 230 codes and ending with five robust themes underscores the methodological rigor of this qualitative inquiry.

3.5. SWOT Analysis of Digital Health Implementation at the Meso-Level

The results are consolidated into a SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis to synthesize the thematic findings strategically. As detailed in

Table 3. SWOT Analysis of Digital Health Implementation at the Meso-Level.

Strengths	Weaknesses
Improved Governance: Digital tools enable real-time monitoring, enhanced transparency, and greater accountability.	Infrastructure Deficit: Widespread hardware failure, unreliable electricity, and poor network connectivity cripple functionality.
Efficient Data Management: Rapid access to beneficiary data facilitates timely decision-making, especially during emergencies.	Fragmented Ecosystem: The proliferation of non-integrated apps (“jungle of apps”) leads to user burden and data duplication.
High Officer Agency: Officers demonstrate significant resilience and resourcefulness through adaptive strategies.	Human Resource Gaps: Low digital literacy among some staff and inadequate financial incentives for data usage demotivate the workforce.
Strong Informal Networks: Effective use of WhatsApp and peer-to-peer learning compensates for formal system gaps and ensures program continuity.	Lack of Autonomy: Block-level officers have no fiscal or administrative power to repair or replace failing equipment.
Opportunities	Threats
Momentum for Change: The COVID-19 pandemic accelerated digital adoption, creating a receptive environment for further innovation.	Widening Inequities: The digital divide threatens to leave the most vulnerable communities and staff further behind.
Clear Reform Agenda: A strong consensus exists among officers for an integrated, offline-capable platform.	System Burnout: Persistent, unaddressed challenges could lead to widespread frustration and abandonment of digital tools.
Targeted Capacity Building: Demand for cyclical, hands-on training provides a clear pathway to improve user skills and confidence.	Data Integrity Risk: Over-reliance on unofficial workarounds can undermine the accuracy and completeness of official data portals.
Infrastructure Investment: The recognized need for better devices and connectivity creates an opportunity for targeted investment.	Policy Failure: The potential for digital health initiatives to fail if systemic barriers are not addressed, wasting investment.

, the primary strengths of the current digital health ecosystem lie in its potential to enhance governance and the profound adaptive capacity of the meso-level officers who navigate its complexities. These strengths, however, are severely undermined by internal weaknesses, most notably the systemic barriers of infrastructural decay, a fragmented application landscape, and gaps in user skills. Externally, this landscape presents opportunities for progress, such as leveraging the momentum from the pandemic-induced digital shift and acting upon the officers’ consensus-driven call for reform. Yet, these are shadowed by significant threats, including the widening digital divide and the risk of system failure if the persistent challenges lead to widespread staff burnout. This framework provides a holistic overview of the operational tensions and sets the stage for a deeper discussion of policy implications.

These results position block-level officers not as bottlenecks but as crucial enablers. Their empowerment through participatory design, robust infrastructure, and continuous support is essential for achieving equitable, sustainable digital health transformation in India’s most underserved regions.

4. Discussion

This qualitative study explores the lived realities, adaptive strategies, and reform priorities of block-level officers, MOICs, and CDPOs who manage digital health programs in Muzaffarpur, an aspirational district in Bihar, India. By giving primacy to these meso-level actors, the research uncovers the transformative potential of digital health innovations and the persistent obstacles that must be addressed to achieve universal health coverage in low-resource settings. The findings reveal a landscape where daily systemic challenges, resourcefulness in local adaptation, and a striking consensus on the urgent need for integrated, context-responsive reforms counterbalance optimism about the promise of digital tools. These insights have significant implications for India’s national digital health trajectory and other LMICs facing similar challenges of scale, complexity, and equity in digitizing health systems. Furthermore, our study highlights the often-underappreciated role of mid-level leadership in fostering health system resilience during digital transformation, echoing global observations that empowering middle managers is a key strategy for building adaptive, robust health services (Forsgren et al., 2022).

4.1. Principal Findings in Context: Promise, Paradox, and Pragmatism

Block-level officers in Muzaffarpur overwhelmingly perceive digital tools as pivotal enablers of data-driven governance, reflecting the broader policy push in India towards real-time monitoring and accountability under initiatives like ABDM and ADP. Across diverse block contexts that are urban, semi-urban, rural, and flood-prone, officers gave examples of how digital platforms (such as the Poshan Tracker, HMIS, or U-WIN) have facilitated quicker responses to local needs, streamlined beneficiary management, and fostered greater transparency. For instance, the ability to instantly generate lists of vulnerable individuals during a flood or to verify a beneficiary’s entitlement status online represents a tangible shift towards more responsive and evidence-based management, as noted in other LMIC settings where digital dashboards have improved decision-making in maternal-child health and epidemic response (Labrique et al., 2018; Vedavalli et al., 2023). Officers also stated that digitalization has introduced a culture of performance tracking that, while pressure-inducing, can improve accountability; for example, public ranking of facilities creates motivation to improve. These perceptions affirm digital transformation’s central promise: better information can lead to better actions.

Yet, the research findings also illustrate a stark paradox. The promise of system-wide improvement due to implementing digital health-facilitated programs is undermined by a persistent array of infrastructural, financial, and human resource barriers. The study brings to light chronic hardware obsolescence, unreliable electricity and network connectivity, and fragmented, poorly coordinated software ecosystems. Officers repeatedly cited that most government-issued phones are non-functional, often due to incompatibility with current network standards or simple wear and tear, and that electricity shortages force them to seek ad hoc charging solutions in the community. These problems are compounded by mandatory contracts with single, unreliable network providers and fiscal arrangements that grant little or no discretionary authority to the block level. These patterns are consistent with the digital divide observed in other Indian states and global LMIC contexts, where outdated devices and insufficient infrastructural investment have led to widespread underutilization of digital health innovations (Faujdar et al., 2021; Pal et al., 2017; Verdezoto et al., 2021).

The findings also reveal that human resource limitations are crucial in shaping digital health outcomes. Many older Anganwadi workers lack basic digital literacy, forcing reliance on younger family members for data entry, undermining data privacy, and placing additional burdens on households. Officers described a demotivating system of low and irregular incentives, typically ₹200–250 per month for internet usage, which, coupled with high workloads and broken equipment, further saps morale and inhibits effective program implementation. These observations echo reports from other Indian states where similar financial and human resource constraints have eroded the effectiveness of frontline health programs (Gudi et al., 2021; Joshi & Verma, 2018; Pgdha et al., 2023).

Despite these constraints, officers in Muzaffarpur demonstrate considerable agency and adaptability. WhatsApp has emerged as a de facto coordination tool, enabling rapid communication, information dissemination, and real-time problem-solving, often filling critical gaps left by official digital platforms. Peer tutoring and family assistance for less digitally savvy staff have become normalized, with officers intentionally leveraging social capital to maintain program momentum. Maintaining parallel digital and paper records, while increasing administrative workload, has become a necessary hedge against unreliable infrastructure. Such resourceful adaptations are consistent with literature from Bangladesh, Nepal, and sub-Saharan Africa, where informal networks and shadow systems have sustained essential services in the face of digital and organizational fragmentation (Owoyemi et al., 2022; Parajuli et al., 2022; Rahman et al., 2022; Scott et al., 2022).

The COVID-19 pandemic accelerated these trends, both as a catalyst for digital adoption and a magnifier of existing inequities. Officers reported the rapid uptake of mobile platforms for meetings, supervision, and vaccination scheduling, but also noted that staff with limited digital skills or connectivity often disengaged or were left behind. The crisis exposed the fragility of digital transitions that do not address the underlying equity and infrastructure gaps, a finding widely echoed in global research on pandemic-driven digital health acceleration (Ahmed et al., 2022; Chang et al., 2021; Jaacks et al., 2024; Kinkade et al., 2022).

4.2. Theoretical and Analytical Implications

Our study was guided by behavior change and technology adoption theories (HBM, TAM, TPB, UTAUT), and the findings both reinforce and challenge aspects of these frameworks when applied to a meso-level, organizational context. For instance, the HBM emphasizes perceived benefits and barriers influencing an individual’s action (Rosenstock, 1974). We found that block officers indeed have strong perceived benefits in mind (e.g., “entire India can see our work,” indicating a belief in the benefit of transparency) and clearly delineated perceived barriers (e.g., “phones are useless junk,” indicating a belief that poor devices hinder performance). This aligns with HBM/TAM constructs that if perceived barriers outweigh benefits, usage will be low (Ahadzadeh et al., 2015). In our data, one can see officers continuing to promote digital tools among their staff because they genuinely believe in the benefits (improved monitoring, etc.), but at the same time, they empathize with resistance from staff because the barriers are quite tangible (crashing apps, etc.). Similarly, UTAUT’s constructs of performance expectancy and effort expectancy are vividly reflected: officers expect high performance gains from digitalization (as long as it works), but the effort required (multiple entries, troubleshooting) is often beyond what was anticipated, affecting behavioral intention to fully embrace a certain system (Holden & Karsh, 2010; Min et al., 2024; Rosenstock, 1974).

However, the research findings also highlight limitations of individual-level models in capturing the reality on the ground. The theories mentioned largely focus on individual attitudes and intentions in adoption. Yet, many challenges we identified are organizational and systemic, not merely attitudinal. No amount of personal positive attitude (say an MOIC’s enthusiasm) can overcome a server outage or a policy that disallows buying a new computer. This suggests that frameworks like the Non-adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework (Greenhalgh et al., 2017) or socio-technical systems theory, which explicitly consider the fit between technology, users, organization, and wider system, may be very relevant. Our study implicitly affirms Greenhalgh et al.’s argument that factors at multiple levels, the technology, the organization’s capacity, and the external environment, determine the success of innovations. For example, from a TPB perspective (Ajzen, 1991), an officer’s intention to use a digital system might be strong (positive attitude, supportive subjective norm from superiors, and confidence in use), but if the facilitating conditions (to use UTAUT’s term (Venkatesh et al., 2003)) like functioning hardware and network are not present, the intention cannot materialize into sustained use. Thus, the research findings argue for extending technology adoption theories to more fully integrate meso-level realities, the management and infrastructural context that shapes individual usage.

Another theoretical implication concerns the concept of organizational resilience and leadership in the face of digital change. The adaptive behaviours we documented (Theme 3) can be seen through the lens of “positive deviance” in organizational behavior, individuals or groups who find better solutions to problems than peers, despite facing the same constraints. The fact that block officers resort to WhatsApp or other improvised solutions indicates a form of grassroots innovation that is not captured by traditional adoption models. It aligns with theories of everyday resilience in health systems, which emphasize how mid-level actors help systems absorb shocks by deviating from norms when necessary (Gilson et al., 2017) From a resilience perspective, the adaptive strategies reported by these officers exemplify ‘everyday resilience’ at the meso level, where frontline management buffers the system against shocks and stresses (Forsgren et al., 2022). This underscores that digital transformation needs to be understood not just as a technical deployment, but as a socio-technical transition requiring resilience and flexibility at multiple levels of the health system.

Moreover, the role of leadership at the meso-level emerges as a pivotal factor. Theoretical models of change management in the digital era suggest that middle managers can act as either change agents or bottlenecks, influencing how top-down innovations are implemented on the ground. Our study provides evidence supporting this: the block officers often acted as champions, mentors, and problem-solvers for digital initiatives, essentially serving as mediators between the technology and the end-users. This resonates with broader public-sector digital transformation literature, which finds that middle managers have varied responses, some feeling increasingly empowered to innovate, others overwhelmed, but ultimately, they are critical to bridging the gap between senior leadership vision and frontline reality (Kusmaryanto & Santoso, 2025). In Muzaffarpur, even with limited formal authority, those in these positions exercised leadership by inspiring their teams, tweaking processes, and lobbying upward for changes. This indicates that theories purely focusing on end-user adoption (like TAM/UTAUT at the worker level) might miss the influence of these intermediate leaders. The research findings, therefore, contribute to an emerging understanding that mid-level management practices (like how an MOIC manages his staff’s use of technology) should be integrated into frameworks predicting the success of digital health interventions.

While existing behavior and technology acceptance models provide a useful starting point, our study highlights the need for an expanded theoretical toolkit, one that incorporates multi-level factors, resilience thinking, and leadership dynamics. The patterns observed suggest that any comprehensive theory of digital health implementation must account for the context in which individuals operate, especially the support (or lack thereof) from the organizational environment and its managers.

4.3. Comparison with Previous Research

The experiences of block-level officers in Muzaffarpur both confirm known challenges in digital health implementation and extend the conversation into less-charted territory. Prior research in India has heavily focused on frontline health workers and beneficiaries, documenting issues such as device usability, workload, data quality, and acceptance (Pal et al., 2017; Pgdha et al., 2023; Verdezoto et al., 2021). The research findings echo many of those front-line challenges, but are viewed through the eyes of the managers who supervise those front-liners. For instance, previous studies have noted that ASHAs and ANMs sometimes struggle with multiple health apps and prefer traditional methods (George, 2009; Joshi & Verma, 2018; Srinidhi et al., 2021; Verdezoto et al., 2021); our study shows that their supervisors are acutely aware of this and themselves struggle with the aggregate burden of multiple systems. By providing the managerial perspective, our work complements studies like Scott et al. (2022) that examined front-line digitization challenges in India’s health system. Scott and colleagues found that health workers often resort to parallel paper records and face pressures to produce “good-looking data.” Our study extends this by revealing that block officers are the ones who often encourage keeping those paper records (to ensure data accuracy), and they are under pressure from above to achieve targets, which trickles down. Similar challenges were found in other research in the LMIC context globally (Haider et al., 2022; Kostkova, 2015; Schradie, 2018).

Notably, our research highlights a layer of organizational dynamics that the frontline-focused literature does not capture in depth. For example, a study by John et al. (2020) examined factors influencing Anganwadi worker performance and touched on supervision quality as one factor. We build on that by directly exploring the supervisors’ roles, revealing how they see their job in enabling (or sometimes inadvertently hindering) the workers’ performance with digital tools. This addresses a gap in implementation research, the “missing middle” where much attention is paid to policy (macro) and frontline execution (micro), but the meso-level (the managers, the local leadership, the connective tissue of the system) is less studied (Birken et al., 2018; Bosch-Capblanch et al., 2011). Our focus aligns with calls in health systems research to pay more attention to this ‘missing middle’, recognizing that middle managers often act as linchpins in program implementation and their practices can greatly influence frontline outcomes (Kusmaryanto & Santoso, 2025).

The study also contributes to the literature on digital inequities and context-specific challenges. For example, we provide detailed evidence from an aspirational (i.e., highly underdeveloped) district context, a setting of extreme resource constraints. While there are many digital health studies from India, relatively fewer have come from the most marginalized districts like Muzaffarpur (which faces annual floods, etc.). Two exceptions in related literature are the work by Topno et al. (2025) on Acute Encephalitis Syndrome and P. Kumar et al. (2023) on Healthcare and Medical Diagnostic Testing Facility Availability in Muzaffarpur, but those did not specifically explore managerial perspectives. The research findings that 70–90% of devices at Anganwadi centers are defunct, or that workers charge phones at neighbors’ homes due to lack of electricity, add granularity to the broad statistics about the digital divide. They humanize what “infrastructural gap” means in practice. This complements broader analyses like Gudi et al. (2021), who discussed challenges in India’s digital health journey at a policy level. We provide the ground-level texture to those challenges.

Comparatively, studies from other LMICs have reported similar adaptive behaviors to ours. In Bangladesh, for example, Studies in Pakistan, India, and African countries documented health workers using social media for professional communication when official systems were lacking (Dzomeku et al., 2023; Jafree et al., 2022; Kapepo et al., 2025; Pahwa et al., 2018). In our study, WhatsApp’s role is analogous, underscoring that this is likely a widespread phenomenon in the Global South’s health systems, the use of consumer technology to fill systemic gaps. Similarly, research in sub-Saharan Africa highlighted the potential of mobile tools but noted issues like network failures requiring creative backup plans (Ohia et al., 2021; Owoyemi et al., 2022). We see the very same in Bihar, reaffirming that context may vary, but certain ground realities of rural health systems are universal.

Where our study breaks new ground is in illustrating how meso-level actors interpret and respond to these issues. The way block officers articulate their frustration (often with a sense of duty-bound resolve) and their detailed wish list for reforms provides actionable insights. It is less common in the literature to see such direct recommendations from the field managers themselves; often, researchers or policy analysts propose solutions. Here, the officers are essentially co-analysts in identifying solutions, which strengthens the call for participatory approaches in designing digital health interventions. In fact, their consensus on solutions (integrate the apps, improve infrastructure, training, etc.) aligns well with recommendations from global health agencies like WHO’s digital health strategy (which emphasizes interoperability, user training, and infrastructure) (World Health Organization, 2015, 2021). This convergence lends credibility to their voices and suggests that policymakers should heed such front-line managerial feedback as a form of practice-based evidence.

Another area of comparison is the effect of COVID-19. Globally, numerous publications have reflected on how COVID-19 accelerated telehealth and digital tools while highlighting new inequities (Krishnan, 2022; O’Donovan et al., 2021; Robinson et al., 2020). Our data offers a microcosm of that global narrative: yes, there was rapid digital uptake (e.g., Zoom meetings in rural Bihar, unthinkable pre-2020), but also exclusion (some staff checked out entirely). Studies like Chang et al. (2021) warned of telehealth exacerbating the digital divide. The research findings confirm this in the public sector context. We add that the management burden increased too; block officers had to now manage remotely and devise new modes of supervision, an aspect less documented in the literature, which focused more on patient care via telehealth.

Our findings are most applicable to high-density, resource-constrained districts with fragmented digital ecosystems and uneven connectivity, contexts that mirror Muzaffarpur’s operational profile. The mechanisms identified, workarounds, boundary spanning, and paper fallbacks as reliability buffers, are likely to transfer, with contextual adaptation, to similar low and middle-income settings where meso-level officers mediate between policy and frontline practice. Transferability will vary with governance arrangements, telecom infrastructure, and device procurement policies; these should be assessed locally before adoption. Accordingly, our intent is analytic generalization rather than statistical inference.

This research extends the knowledge by illuminating the perspective of mid-level implementers who navigate between frontline difficulties and top-down demands. By doing so, it addresses a niche in research that has been relatively understudied and provides empirical evidence to support the intuition that how middle managers handle digital reforms can make or break those initiatives. The study encourages further comparative research and cross-learning: for example, lessons from how a block officer in Bihar innovates with WhatsApp could inform similar strategies in, say, rural Uganda or other LMICs with a similar stage of digital health program implementation or vice versa (Celuppi et al., 2024; Kansiime et al., 2024; Safi et al., 2018).

4.4. Strengths and Limitations

This study’s primary strength is its novel focus on meso-level officers (MOICs and CDPOs), a critical yet under-researched cadre in the digital health ecosystem. By centering their experiences, the research fills a significant evidence gap between high-level policy and frontline implementation. The strategic selection of a high-priority “Aspirational District” and the use of maximum variation sampling, capturing urban, rural, and flood-prone blocks, enhances the analytical transferability of the findings to similar resource-constrained settings. The study’s methodological rigor, including adherence to COREQ guidelines, a prospectively registered protocol, and robust analytical practices like member-checking, further bolsters the credibility of the findings (Tong et al., 2007).

We acknowledge several potential limitations. First, the study’s scope is confined to a single district and a focused sample of eight officers. However, this was a deliberate design bounded by the decision of the district administration, considering the limited time availability and the size of the blocks under these officers. However, this gave us the choice to achieve analytical depth over statistical breadth. By including all incumbent officers in four diverse blocks, we conducted a virtual census of meso-level leadership in these specific contexts, providing a rich, detailed microcosm of the challenges faced. This purposive approach yields transferable insights that a broader, more superficial survey could not capture.

Second, using a single primary coder could be seen as a limitation. To mitigate this, a supervisory team robustly supported the coding process. Three senior researchers independently audited randomly selected transcripts and coding frameworks at multiple stages. All analytical decisions were discussed, and discrepancies were resolved through consensus, ensuring the reliability and validity of the thematic analysis.

Finally, while this paper exclusively presents the views of meso-level officers, we recognize that a complete picture requires perspectives from frontline workers and district officials. This exclusion was an intentional scoping decision to isolate and thoroughly explore this pivotal group’s unique contributions and challenges. The CHWs’ perspectives are being analyzed as part of the broader doctoral study and will be presented in future publications to provide a more holistic, multi-level system analysis. We also recommend interviews with the district- and state-level officers in future research, as we could not obtain permission for those interviews.

4.5. Implications for Policy and Practice

The insights from this study lead to several actionable recommendations for policymakers, program implementers, and other stakeholders involved in digital health initiatives in resource-constrained settings like Muzaffarpur. The block-level officers have effectively voiced a roadmap for improving digital health implementation, and it would be prudent for decision-makers to leverage this ground-up perspective. Here, we distill the key implications:

• Integration and Interoperability of Systems: Policymakers at the state and national level should prioritize the development of an integrated digital health platform (or effective interoperability between existing ones). The current multiplicity of applications creates silos and inefficiencies. A unified platform (or an interoperable suite of platforms) would reduce duplication of data entry, ease the learning curve for users, and enable more holistic data analysis. Importantly, such integration should span across departments (health and nutrition) to reflect the collaborative reality of frontline work. For example, maternal health and child nutrition data should talk to each other. This echoes broader recommendations in India’s National Digital Health Blueprint and would directly address one of the loudest pain points from the field (Ministry of Health and Family Welfare, Government of India, 2019).
• Infrastructure Investment and Offline Functionality: The basics need urgent fixing; no digital initiative can thrive without reliable electricity, connectivity, and hardware. There is a need for dedicated budget provisions for device maintenance and upgrades. This could be in the form of periodic device renewal schemes (like how textbooks are updated in schools) or maintenance grants to district health societies. Additionally, providing alternative power solutions (like solar chargers or generators) in health and nutrition centers and improving network coverage (perhaps through partnerships with telecom providers or installing signal boosters in remote clinics) would go a long way. At the software level, ensuring that applications have an offline mode is critical. App developers and program managers must include offline data capture and later synchronization as a core requirement for any tool meant for rural deployment. The Poshan Tracker, for example, could incorporate a lightweight offline module for Anganwadi workers, as a contingency for network downtime (Labrique et al., 2018).
• Continuous Capacity Building and Support: Training cannot be a one-off event. Health and ICDS departments should institutionalize regular refresher trainings (e.g., every 6 or 12 months) for all digital tool users. These trainings should be hands-on, scenario-based, and preferably on-site (or at least at the block level) so that they can simulate real conditions. Moreover, creating a local support infrastructure is crucial—for instance, designating/block-hiring an IT support officer per district or subdividing this role among existing staff with IT competency. Another approach could be a “digital ambassador” program where one tech-savvy ANM or AWW per area is given additional training and incentives to act as the go-to person for her peers’ technical difficulties. The implications for practice are that mid-level managers (like our participants) should advocate for and possibly facilitate these learning sessions, rather than waiting for orders from above. They can, for example, organize monthly problem-solving meet-ups where workers share issues and solutions with each other (Majhi et al., 2021; Naslund et al., 2019; Shah et al., 2023).
• Empowerment and Incentivization at the Meso-Level: The policy framework should consider decentralizing some decision-making power and resources to the block or even sector level. This could mean giving block officers a small discretionary fund specifically for operational exigencies, e.g., repairing a printer, buying data recharge cards in an emergency, or rewarding a high-performing sub-center with additional supplies. Performance-based incentives that recognize well-maintained digital records or innovative practices by blocks could motivate lagging areas. On the flip side, there should be non-punitive support for struggling blocks (like sending a mobile team to fix issues or train staff) rather than just negative feedback for poor indicators, because, as our study shows, those indicators often reflect system problems more than individual effort. For policymakers, this means crafting schemes that treat block officers as partners who need support and flexibility, not just as cogs in a hierarchical machine (Gudi et al., 2021; N. S. Singh et al., 2021).
• Harnessing Informal Innovations (while formalizing them carefully): The prevalence of WhatsApp and similar tools in our study suggests that any policy that outright bans their use (perhaps out of data security concerns) may face resistance or covert non-compliance. Instead, a more constructive approach is to provide secure, government-approved alternatives that are as convenient as WhatsApp. For example, developing a simple, user-friendly communication app for health workers, or even a WhatsApp API integration that logs messages in a secure server, could bridge this gap. In the interim, acknowledging and legitimizing the positive role of such informal practices can improve morale. For instance, district officials can create WhatsApp groups officially and include block officers, sending periodic guidance and also listening to on-ground updates through them. This would validate the efforts of officers who have been using these tools and bring a degree of oversight to them. The key is not to force the field to abandon what works for them, but to learn from it and incorporate it into the formal system (Celesti et al., 2021; Liyanage et al., 2019; Masoni & Guelfi, 2020).
• Participatory Design and Feedback Mechanisms: Finally, an implication for both policy and program design is to involve block and frontline personnel in the development and refinement of digital tools. Their insights can help avoid pitfalls (like non-offline apps) and make systems more user-friendly. Setting up a regular feedback loop, say quarterly meetings or an online forum where block officers can report issues to state IT cells, would help continuously improve the systems. This participatory approach is emphasized in implementation science and would ensure that the end-users have a voice, increasing their buy-in and the tools’ usability (Simonsen et al., 2017; Tseng et al., 2024).

In implementing these recommendations, a coordinated effort is needed. For policymakers, this means allocating budget and political will to the often “invisible” backbone of digital systems, maintenance, training, support, and not just shiny new apps. It also means revising some governance structures to push decision-making closer to the point of service. For practitioners and program managers, including those at district and state levels, the findings underscore the importance of supporting block-level staff through mentorship, responsive troubleshooting, and by championing their needs to higher authorities. These managers should also document and share success stories of blocks that improved their digital reporting or innovation, to create a positive competitive spirit and cross-learning. For the academic and training community, there is an implication to update curricula for health administration to include digital health management and to offer mid-career training for current officers on change management, data analysis, and basic IT skills, thus professionalizing the capacity to handle digital transformation at the field level.

In essence, our study’s implications boil down to a simple principle: technology alone is not a silver bullet; it must be buttressed by investment in people and processes. By acting on the insights of those who navigate the last-mile challenges of digital health, stakeholders can make strategic improvements that turn a fragile digital experiment into a robust, scalable success.

For policymakers: Ensure integration of systems, reliable infrastructure, and supportive policies that empower local managers (e.g., through flexible funds and recognition programs). For practitioners and program managers: Embrace continuous capacity-building and foster a culture of adaptability and peer support on the ground, while also advocating upwards for the resources and changes your teams need. For the academic and training community: develop evidence-based strategies and curricula that emphasize the role of meso-level leadership in health system digital transformation and continue research that includes these perspectives to inform policy.

4.6. Future Research Directions

While this study has provided valuable insights, it also raises further questions and areas that merit additional inquiry. Future research could build on the research findings in several ways:

Comparative Case Studies: Expanding the geographical scope would be valuable. Comparative studies could look at other aspirational districts versus non-aspirational (better-off) districts to see how contexts differ in digital health uptake. International comparisons with similar administrative structures (like perhaps comparing block-level management in India to district-level management in African countries under similar digital programs) might reveal universal vs. context-specific factors. It would be interesting to see if the adaptive behaviors (like use of WhatsApp or parallel records) are found wherever similar constraints exist, which could suggest these are generalizable phenomena in the Global South’s health systems.

Longitudinal Research: Given that digital health is a rapidly evolving field, longitudinal studies that follow the same blocks over time would be insightful. For example, research could track Muzaffarpur’s digital health metrics and qualitative experiences for a few years to see if the reforms officers suggested (some of which might be implemented) lead to improvements or new challenges. This would also capture how workforce attitudes change as younger, more digitally native staff replace older ones, and whether the digital divide narrows or widens over time.

Intervention Research: The consensus on reform provides a blueprint that could be tested. Pilot interventions, such as providing a batch of new devices, deploying an offline-capable app version, or establishing a local IT helpdesk, could be evaluated using implementation research frameworks. Action research or participatory trials where researchers, policymakers, and block officers co-design a solution (say, a unified reporting system in one district) and iterate on it could produce models that, if successful, can be scaled. Such studies should measure not just outcomes (like data completeness or health indicators) but also process outcomes like user satisfaction, reduction in workload, etc.

Leadership and Management Practices: Another line of inquiry is studying the leadership behaviors and competencies that make some meso-level officers more effective in navigating digital transformation. We anecdotally saw variations (some officers were more proactive, others more resigned). Research could identify traits or practices (e.g., more frequent field visits, tech-savvy mindset, collaborative style) that correlate with better digital program performance at the block level. This could inform training programs for future health administrators. Qualitative studies focusing on exemplary performers (“positive deviants”) might glean best practices that can be taught or emulated.

5. Conclusions

The path to digital transformation in India’s health system is shaped as much by the ingenuity and resilience of block-level officers as by national policy ambition. This study reveals that these officers are not obstacles but essential drivers of system change, navigators who bridge policy and practice through resourceful adaptation and on-the-ground leadership. It highlights that achieving sustainable digital transformation requires not just technological inputs but also investment in human capacity and strong, adaptive leadership at the local level. Their collective call for integration, context-responsive design, and greater empowerment provides a clear, practitioner-informed roadmap for advancing equitable, effective, and robust digital health systems in low-resource settings. The research findings also contribute to broader theoretical understandings by illustrating how mid-level managerial leadership can bolster or impede innovation uptake, reinforcing calls in the literature to strengthen this ‘linchpin’ level of health systems.

In practical terms, addressing the systemic issues identified, from infrastructure upgrades to streamlined software and continuous training, and leveraging the adaptive strategies already in use (like peer learning and flexible communication channels) could dramatically improve the success of digital health initiatives in districts like Muzaffarpur. For policymakers and health administrators, the message is clear: front-line technology will falter without front-line support. By centering the experiences of meso-level actors, this research informs both theory and practice, offering valuable lessons for India and other countries striving for universal health coverage in the digital age. Ultimately, robust digital transformation requires aligning technology with organisational resilience and context, particularly by empowering meso-level leaders who hold the system together.