Adoption challenges of digital transformation of human resource management in Bangladesh’s healthcare system: a cross-sectional mixed-methods evaluation

Abstract

Background

The integration of digital technologies into healthcare systems can significantly improve human resource management, especially in low- and middle-income countries (LMICs) like Bangladesh. Despite policy-level efforts such as the rollout of the Human Resource Information System (HRIS), adoption remains uneven and under-studied. This study aimed to identify barriers to HRIS adoption and propose strategies to strengthen digital transformation in human resource management within Bangladesh’s healthcare sector.

Methods

A cross-sectional mixed-methods study was conducted from March to June 2023 across five districts- Lakshmipur, Feni, Noakhali, Comilla, and Cox’s Bazar- selected for their varying levels of digital readiness. Quantitative data were gathered from 320 h and IT professionals using a structured questionnaire. Qualitative insights were obtained through 10 in-depth key informant interviews with hospital directors, researchers, and policymakers. Quantitative analysis was performed using SPSS version 26, and qualitative data were analyzed thematically using Braun and Clarke’s method.

Results

Despite widespread awareness and positive perceptions of HRIS, several critical barriers impeded adoption. These included inadequate training in digital systems, insufficient digital literacy among HR personnel, unreliable internet connectivity, lack of uninterrupted power supply, and limited funding. Furthermore, centralized decision-making, weak inter-ministerial coordination, and lack of motivation among senior leadership emerged as institutional obstacles. Participants emphasized the need for hands-on training, need-based resource allocation, infrastructure investment, and stronger leadership engagement. The convergence of quantitative and qualitative findings underscored the systemic and multidimensional nature of the challenges.

Conclusion

Despite progress in digital infrastructure, systemic and organizational barriers continue to hinder the full-scale adoption of HRIS in Bangladesh. Addressing these through targeted interventions is critical for optimizing human resource efficiency and strengthening the health system.

Clinical trial number

Not applicable.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-025-13549-0.

Introduction

Over the past decade, healthcare systems around the world have undergone significant digital transformation driven by globalization and the rapid advancement of information and communication technology (ICT). The World Health Organization (WHO) emphasizes that systematic integrated digital health interventions into national health system can support the achievement of universal health coverage (UHC) and health-related Sustainable Development Goals (SDGs) [1]. Digital transformation in healthcare encompasses a range of technologies, including electronic health records (EHRs), telemedicine, mobile health (mHealth), and health workforce information systems, all of which contribute to strengthening service delivery, enhancing coordination, and ensuring better use of human resources [2].

Human Resources for Health (HRH) form the backbone of any healthcare system. Effective management and equitable distribution of health personnel are critical to achieving improved population health outcomes [3, 4]. However, many low- and middle-income countries (LMICs) face persistent challenges related to HRH shortages, skill imbalances, and urban–rural disparities. In many LMICs, HRH data remain fragmented across multiple sources, including ministry records, professional councils, and national censuses, most of which are not designed to support HRH planning and decision-making [5, 6]. As a result, these countries struggle to optimize workforce distribution, monitor employment trends, or align human resource production with national health needs. A critical factor underlying these challenges is the lack of integrated, timely, and accurate HRH data systems.

Bangladesh, like many LMICs, has historically experienced acute HRH shortages and an inequitable distribution of health workers. According to the WHO, Bangladesh is categorized as a country suffering from a “severe health workforce shortage,” with a large concentration of professionals in urban centers, leaving rural and underserved areas critically deprived of services [7, 8]. These workforce imbalances are further compounded by weak governance mechanisms and inefficient management practices. In response to these systemic challenges, the Government of Bangladesh, under its “Digital Bangladesh Vision 2021,” has initiated several ICT-based reforms to modernize the health system. Notably, in 2017, the Directorate General of Health Services (DGHS) launched the internet-based Human Resource Information System (HRIS), designed to serve as a centralized platform for processing and managing national HRH data [9].

Despite this progress, evidence on the adoption and functionality of digital health technologies, particularly HRIS, remains limited in the Bangladeshi context. While prior studies have explored various digital health applications such as mHealth, EHRs, and telemedicine [10], there has been little empirical research examining the barriers to digital technology adoption specifically in relation to HRH management. Understanding these barriers is crucial, as effective digital integration can significantly enhance human resource planning, improve efficiency, and support the broader goals of health system strengthening and UHC.

This study seeks to fill this critical gap by exploring the barriers of digital technologies adoption for HRH management in Bangladesh and identifying actionable strategies to overcome them. By analyzing the current landscape of digital transformation within the health sector, this research aims to generate evidence that can inform policy and practice for better workforce utilization. The underlying hypothesis of the study is that despite having digital infrastructures like HRIS, various systemic, technical, and organizational barriers continue to obstruct their full-scale adoption and optimal use. Addressing these barriers through informed interventions will be key to maximizing the potential of digital technologies for HRH efficiency in Bangladesh.

Methodology

Study design and area

This study employed a cross-sectional mixed-methods design, integrating both quantitative and qualitative research approaches to explore barriers to digital technology adoption in human resource (HR) management within the healthcare sector in Bangladesh. The two components were conducted sequentially, with the quantitative survey preceding the qualitative key informant interviews. This allowed initial statistical findings to guide the design of the interview guide, ensuring that the qualitative insights complemented and explained the quantitative patterns. The research was conducted from March to June 2023 in five purposively selected districts, Lakshmipur, Feni, Noakhali, Cumilla, and Cox’s Bazar, chosen for their varying levels of digital technology implementation in healthcare. These districts represented different categories of technology adoption, including adopters, prospectors, laggards, and record-keepers. The categorization was based on Directorate General of Health Services (DGHS) reports (2022) and district-level ICT adoption records, triangulated with consultations with district civil surgeons. For clarity, Table 1 summarizes each district’s classification.

Table 1.

Districts and HRIS adoption categories

District	Adoption category	Background information
Lakshmipur	Adopter	Fully operational HRIS integrated into HR processes
Feni	Prospector	Piloting HRIS with limited modules
Noakhali	Laggard	Minimal initiation, resistance observed
Cumilla	Adopter	Routine use of HRIS across facilities
Cox’s Bazar	Prospector	Exploring adoption, partial rollout

Study population

The study targeted healthcare institutions situated in the aforementioned districts. These included district hospitals, upazila health complexes, union sub-centres, and selected private medical colleges. The population for the quantitative component consisted of mid- and top-level managers, as well as senior executives working in the Human Resources (HR) and Information Systems (IS) departments of selected hospitals. Mid-level managers typically referred to Assistant Directors or Senior Medical Officers in HR divisions (average service duration 8–12 years), while top-level managers included hospital directors and deputy directors (> 15 years in service). Senior executives encompassed HR and IS chiefs, most of whom were Class I officers (clinician or non-clinician administrators). For the qualitative component, 10 key informants were selected from among experienced professionals and policymakers. Experienced professionals were defined as those with at least 10 years of service in HR or IS management or a postgraduate degree in health administration. Policymakers included DGHS deputy directors, divisional health administrators, and senior officials from the Ministry of Health and Family Welfare.

Sample size and sampling technique

The sample size was calculated using the formula n = Z²pq/d², where n represents the required sample size, Z is the standard normal deviation at 95% confidence level (1.96), p is the estimated proportion of the population with the characteristic of interest, q is (1–p), and d is the desired precision level (0.05). Based on a previous study conducted in Bangladesh by Alam et al. (2016), which reported a response rate of 69.64% among hospital staff, the value of p was taken as 0.6964, and q as 0.3036, which results in a minimum required sample size of approximately 320 respondents.

A proportional number of employees were selected randomly from each district based on their professional roles and relevance to HR and digital system management. Proportionality was ensured according to district size: for example, if Cumilla contributed 20% of the total HR/IS staff across the five districts, then approximately 20% of the survey sample was drawn from Cumilla. Within each district, professional roles such as HR managers and IS officers were represented proportionally to their actual distribution in the workforce. For the qualitative component, two key informants were selected from each district. Selection was guided by expertise and decision-making authority in HR management and digital health policy. Expertise criteria included years of service, prior involvement in digital health projects, and decision-making responsibilities, such as budget allocation, HR planning, or policy oversight. A total of 371 questionnaires were distributed, of which 320 were valid and included in the final quantitative analysis.

Inclusion and exclusion criteria

Eligible participants for the quantitative survey were professionals working in the HR or IS departments of district hospitals, medical colleges, and upazila health complexes who were available and reachable over email or in-person contact, and willing to participate during the data collection period. Individuals who declined participation were excluded. For key informants, inclusion criteria included relevant managerial or policymaking experience and willingness to participate in interviews.

Data collection tools and techniques

Quantitative data were collected using a semi-structured, self-administered questionnaire comprising two sections: one capturing demographic and institutional information, and another focusing on 13 identified factors influencing digital technology adoption in HR management, such as IT infrastructure, perceived cost, executive engagement, and policy environment (Supplementary File 1). The tool was adapted from validated instruments used in previous studies [11, 12] and revised after a pilot test. For the qualitative component, the interviews followed a semi-structured conversational approach based on literature review [13, 14], where open-ended guiding questions were used but participants were encouraged to elaborate freely based on their professional experiences (Supplementary File 2). Key informants were purposively selected for their managerial or policymaking expertise, ensuring representation across clinical, academic, and administrative domains.

Data collection and quality control

Quantitative data collection was performed via both electronic distributions of questionnaires and face-to-face interviews. Where email communication was not feasible, the principal investigator or trained data collectors approached participants directly. To maintain quality, all responses were reviewed for completeness and consistency. Any ambiguities were clarified through follow-up phone calls. A total of 371 responses were received, out of which 320 were finalized after screening for completeness and accuracy. For the qualitative component, interviews were conducted in quiet, private settings to ensure comfort and confidentiality. Each interview lasted 20–30 min and was audio-recorded with consent. Transcriptions were checked against the recordings to maintain data fidelity.

Study variables

Quantitative variables included demographic factors (age, sex, years of experience), institutional characteristics (hospital type, location), and perceived barriers or facilitators of digital technology adoption, based on a Likert scale. The Likert scale response options were: Strongly Agree, Agree, Neutral, Disagree, and Strongly Disagree. Independent variables were demographic and organizational attributes, while dependent variables included the levels and barriers of digital technology adoption in HR management. For qualitative analysis, thematic areas included leadership attitudes, infrastructure constraints, workforce digital literacy, policy and regulation gaps, and perceptions of cost-effectiveness.

Key informant characteristics

Ten key informants (6 males and 4 female) participated in the qualitative study. They included three hospital directors, three academicians, two researchers, and two hospital managers. Among these, two hospital directors and one academician also held advisory or policymaking roles in DGHS committees, thereby fulfilling the study’s definition of policymakers. Participants were aged between 32 and 56 years, with professional experience ranging from 5 to 21 years (Table 2). These informants were selected based on their strategic roles in HR management or digital health implementation and were deemed capable of providing in-depth, contextual insights into the research objectives.

Table 2.

The characteristics of the key informants

Participant ID	Position	Sex	Age (Years)	Years of experience
01	Director of the Hospital	Male	43	15
02		Female	45	17
03		Male	56	21
04	Academician	Female	37	8
05		Male	52	14
06		Male	36	3
07	Researcher	Male	41	10
08		Female	40	12
09	Manager of the Hospital	Female	39	11
10		Male	38	9

Data coding, processing and analysis

Quantitative data were cleaned, coded, and entered into SPSS software (version 26) for statistical analysis. Descriptive statistics, including frequencies and percentages, were used to summarize demographic variables and adoption-related indicators. For qualitative data, an inductive thematic analysis approach, following Braun and Clarke’s six-step method, was applied. Transcripts were read repeatedly to identify initial codes, which were then grouped into overarching themes. Themes were refined collaboratively by the research team to ensure validity and coherence. Coding was conducted manually by two independent researchers who initially coded the transcripts line by line. Codes were compared, merged, and refined into categories, from which higher-level themes were generated. Discrepancies were resolved through discussion, and themes were emphasized if they were consistently raised across multiple interviews and triangulated with quantitative data. Findings of quantitative and qualitative parts were triangulated to assess validity and reliability.

Results

Quantitative findings

Table 3 shows that most respondents (75%) were between 30 and 50 years of age, and the majority were male (80%). Educational qualifications were nearly evenly distributed, with 50.6% holding postgraduate degrees and 49.4% being graduates. Regarding the HRIS adoption stage, 75.0% of participants were from institutions classified as adopters, followed by record-keepers (21.0%), while prospectors and laggards each accounted for only 2.0%.

Table 3.

Baseline profile of respondents

Characteristic	Category	Frequency (n)	Percentage (%)
Age Group	< 30 Years	72	22.5
	30–50 Years	240	75.0
	> 50 Years	8	2.5
Gender	Male	256	80.0
	Female	64	20.0
Educational Qualification	Graduate	158	49.4
	Postgraduate	162	50.6
HRIS Adoption Stage	Adopters	240	75.0
	Record-Keepers	67	21.0
	Prospectors	6	2.0
	Laggards	7	2.0
Total Respondents	-	320	100.0

Table 4 reveals that significant majority (66.3%) agreed that senior executives are ready to experiment with new information systems, with an identical proportion favoring the creation of new systems over improving existing ones. While 43.8% of respondents believed that all human resource staff are computer literate, 24.4% disagreed. Additionally, 49.4% agreed that human resources possess basic IT skills for using HRIS. Most respondents (68.8%) acknowledged the availability of sufficient software and database resources within their organizations to support HRIS. While 78.1% believed HRIS applications would be compatible, 59.4% noted that some functions still posed operational incompatibilities, indicating that respondents often perceived partial rather than absolute compatibility. Lastly, 75.0% agreed that HRIS aligns with organizational values and beliefs.

Table 4.

Preferences of the respondents regarding implementation of new system

Question	Strongly agree	Agree	Neutral	Disagree	Strongly disagree
Senior Executives (SE) are ready to experiment with new information systems.	110 (31.3%)	212 (66.3%)	8 (2.5%)	0 (0.0%)	0 (0.0%)
Senior Executives prefer creating something new rather than improving existing ones.	110 (31.3%)	212 (66.3%)	8 (2.5%)	0 (0.0%)	0 (0.0%)
All human resource staff are computer literate.	56 (17.5%)	140 (43.8%)	30 (9.4%)	78 (24.4%)	16 (5.0%)
All human resources possess basic IT skills for information systems.	54 (16.9%)	158 (49.4%)	38 (11.9%)	62 (19.4%)	8 (2.5%)
The organization has sufficient software and database resources for HRIS.	56 (17.5%)	220 (68.8%)	14 (4.4%)	30 (9.4%)	0 (0.0%)
HRIS applications would be compatible with existing operational practices.	54 (16.9%)	250 (78.1%)	16 (5.0%)	0 (0.0%)	0 (0.0%)
Some HRIS functions may pose operational incompatibilities	38 (11.9%)	190 (59.4%)	38 (11.9%)	46 (14.4%)	8 (2.5%)
HRIS applications are consistent with our organizational values and beliefs.	56 (17.5%)	240 (75.0%)	24 (7.5%)	0 (0.0%)	0 (0.0%)

In Table 5, most respondents did not find HRIS complex (66.9%) or hard to learn (71.9%). A large majority recognized its potential to reduce operational costs (83.8%) and improve organizational efficiency (100%). Strong management support was evident, with adequate resource allocation (86.3%) and senior leadership involvement and awareness of HRIS benefits (97.5–100%) affirmed by nearly all respondents.

Table 5.

Perception of respondents regarding importance of HRIS usage and management support

Aspect	Response	Frequency (n)	Percentage (%)
Implementation of HRIS is complicated	Yes	106	33.1
	No	214	66.9
HRIS is hard to learn	Yes	90	28.1
	No	230	71.9
HRIS will cut operations cost	Yes	268	83.8
	No	52	16.3
HRIS will increase organization’s profitability	Yes	320	100.0
	No	0	0.0
Top management allocated adequate resources for HRIS adoption	Yes	276	86.3
	No	44	13.8
Top management is aware of HRIS benefits	Yes	320	100.0
	No	0	0.0
All major decisions need top management approval	Yes	304	95.0
	No	16	5.0
Senior management has to be asked before any decision is taken	Yes	312	97.5
	No	8	2.5

Table 6 shows that a significant majority of respondents (95%) reported lack of reliable and high-speed internet connections as a major barrier, followed closely by the lack of motivation to implement relevant policies (89%) and the absence of an uninterrupted power supply (86%). Additionally, 85% identified insufficient funding as a constraint, while 75.6% pointed to inadequate training on digital technology adoption. Moreover, 83.2% of participants acknowledged limited interventions aimed at enhancing hospital managers’ knowledge of digital technologies.

Table 6.

Challenges to adoption of digital technology

Aspect	Response	Percentage (%)
Ensure Uninterrupted Power Supply	Yes	86%
	No	14%
Lack of reliable and high-speed internet connections	Yes	95%
	No	5%
Lack of Strong Motivation to Implement the Relevant Policies	Yes	89%
	No	11%
Lack of Funding for the Digital Technology Adoption	Yes	85%
	No	15%
Lack of Training on Digital Technology Adoption	Yes	75.6%
	No	24.4%
Limited Interventions on Increasing knowledge about Digital Technologies among the hospital managers	Yes	83.2%
	No	16.8%

Qualitative findings

The qualitative component of this study, based on insights from ten key informants, yielded two overarching themes: Barriers to the Adoption of Digital Technology and Strategies to Overcome These Barriers. The narratives from hospital directors, academicians, researchers, and managers revealed a complex interplay of infrastructural, institutional, and motivational factors that continue to shape the pace and scope of digital transformation in HR management within the health sector in Bangladesh. To enhance accessibility, we supplemented thematic analysis with a content analysis table (Table 7) that enumerates key barriers and the corresponding strategies suggested by participants. This dual presentation balances narrative richness with structured clarity.

Table 7.

Barriers and strategies to overcome barriers (Qualitative content analysis)

Barrier	Illustrative quote	Suggested strategy
Unreliable Power Supply	“We emphasized the critical need for reliable power supply…” (KII-2)	Solar backup, dedicated power systems
Poor Internet Connectivity	“Strong internet connectivity is essential…” (KII-3)	Ensure 24/7 internet, government prioritization
Leadership Inertia	“The lack of motivation among leadership hinders…” (KII-2)	Incentives for proactive leaders, monitoring mechanisms
Limited Training & Literacy	“Workshops, seminars, and hands-on training are needed…” (KII-5)	Interactive, hands-on training programs
Insufficient Funding	“Insufficient resource allocation is a major barrier…” (KII-6)	Innovative financing, equitable resource allocation
Weak Inter-ministerial Coordination	“Poor inter-ministerial coordination undermines digital initiatives…” (KII-5)	Stronger governance mechanisms, inter-sectoral committees

Theme 1: Barriers to the adoption of digital technology

One of the most consistently cited barriers was uninterrupted power supply. “We emphasized the critical need for reliable power supply to enable the use of digital technologies in hospitals. Modern technologies for ensuring uninterrupted power are also needed” KII- 2, 3.

Similarly, the availability of strong internet connections emerged as a critical challenge. “Strong internet connectivity is essential for efficient healthcare delivery and management. We urged the government to prioritize robust internet services” KII- 2, 3.

Another recurring concern was the lack of strong motivation among senior leadership to prioritize or enforce the implementation of digitalization policies. “The lack of motivation among leadership hinders the implementation of digitalization policies. Top-level management’s procrastination is a recurring issue” KII- 2, 3.

Additionally, inadequate training and limited digital literacy among healthcare professionals was identified as a major impediment. “Limited training opportunities restrict healthcare providers’ ability to adopt digital technologies effectively. Workshops, seminars, and hands-on training are needed” KII - 5, 7.

The informants also highlighted insufficient resource allocation for digital equipment and inadequate budgetary support as persistent barriers. “Insufficient resource allocation is a major barrier. Increased funding and strategic health financing are necessary for digital adoption” KII- 1, 6.

“Inadequate government expenditure on healthcare limits technological advancements. Innovation in resource mobilization is needed to increase the health budget” KII- 4, 6. These findings have been triangulated with quantitative results (Table 6).

Lastly, poor coordination between government institutions was described as a significant bottleneck in policy implementation. The fragmented communication and lack of synergy across ministries and departments contribute to duplicative efforts and hinder the success of national digital health initiatives. Community involvement and inter-sectoral collaboration were proposed as potential solutions to this governance gap. “Poor inter-ministerial coordination undermines digital initiatives. We stressed the need for unified efforts and community engagement” KII- 5, 8.

The key informants further reported that interrupted and disproportionate power supply significantly hinders the operation of digital systems, especially in rural and semi-urban hospitals. Weak or unstable internet services severely limit real-time data entry, inter-departmental coordination, and remote service delivery, underscore the need for government investment in digital infrastructure. Respondents noted that despite policy availability, passive leadership and bureaucratic inertia have delayed critical reforms. Without structured training opportunities such as workshops and hands-on simulations, staff struggle to adopt and integrate new technologies into their workflows. The lack of funding restricts the procurement of essential devices. Respondents called for innovative budgetary approaches and reallocation of resources to bridge these gaps.

Theme 2: Strategies to overcome barriers

To address the identified challenges, key informants recommended several actionable strategies. Foremost among these was the introduction of interactive, hands-on training programs tailored for healthcare professionals at all levels. “Interactive workshops and training programs can enhance healthcare providers’ knowledge and interest in digital technology” KII- 6, 7.

“Strong motivation among healthcare professionals by providing incentive for dedicated workers may be a method to implementing digital technology effectively” KII- 1, 4.

Addressing infrastructural limitations was also a priority. The provision of uninterrupted power supply, including solar-powered backup systems, was suggested as a sustainable solution to power outages. Similarly, informants advocated for the establishment of 24/7 reliable internet connectivity to ensure continuity in data-driven decision-making and service delivery. “Installing dedicated power systems and exploring alternative energy sources, such as solar power, can address power challenges” KII- 1, 3.

“24/7 strong internet connectivity is crucial for managing resources and delivering high-quality care” KII- 3, 6.

Finally, participants stressed the importance of need-based resource allocation. Resources should be distributed based on facility-specific assessments rather than political or administrative discretion. Strategic planning and equitable funding, aligned with local demand and system capacity, were seen as essential for scaling up digital adoption in a sustainable and impactful manner. “Resource allocation should be aligned with the specific needs of healthcare facilities rather than political influence. Strategic and need-based planning is essential” KII- 1, 4.

Discussion

This study tried to identify the barriers to adopting digital technologies for human resource management in Bangladesh’s healthcare sector, focusing on Human Resource Information Systems (HRIS). The findings affirmed the hypothesis that despite the presence of digital infrastructures like HRIS, systemic, organizational, and infrastructural challenges impede their effective and widespread use, which was triangulated by quantitative findings.

Our study revealed that inadequate training, weak internet infrastructure, and power instability are persistent impediments to HRIS adoption in Bangladesh. These findings are consistent with reports from other LMICs such as Pakistan and Kenya, where similar infrastructural and human resource barriers limit digital health implementation [15, 16].

Although most organizations acknowledged the strategic value of HRIS, widespread technical illiteracy among HR staff and insufficient training programs constrained practical use. This mirrors national and international findings, where skill gaps and low e-health literacy undermine digital health initiatives [17, 18, 12]. Our qualitative findings similarly emphasized the need for interactive, hands-on capacity-building initiatives and stronger leadership engagement to drive change.

While many respondents reported favorable organizational perceptions toward HRIS, including its compatibility with existing practices and alignment with institutional goals, financial constraints and poor interdepartmental coordination remained significant challenges. These findings corroborate the literature which highlights that digital health success is contingent not just on infrastructure, but also on effective governance and consistent funding streams [19, 20]. Inadequate budgetary allocation for digital health transformation has been documented in other contexts as well, including sub-Saharan Africa and South Asia, and our findings affirm this trend within the Bangladeshi health sector.

Another critical barrier identified was leadership inertia. Although management often acknowledged the potential benefits of digital technologies, their commitment to policy enforcement and strategic direction appeared limited. These governance gaps have been echoed in prior studies examining the implementation of sector-wide health reforms in Bangladesh, where policy existence does not always translate into operational execution [21, 22]. Without proactive leadership and inter-ministerial collaboration, digital adoption risks stagnating despite infrastructural investments.

Furthermore, qualitative interviews revealed that power outages and poor internet connectivity disproportionately affected rural and semi-urban facilities. This is consistent with WHO reports noting that infrastructure disparities, especially in underserved regions, are a major hindrance to digital health equity [23, 24]. The recommendation to utilize solar power and reliable internet service underscores the importance of context-specific, decentralized solutions rather than a one-size-fits-all national approach.

Limitations and implications

A notable strength of this study lies in its mixed-methods design, which allowed for an in-depth understanding of both the quantifiable scope of digital adoption and the qualitative context shaping it. However, several limitations must be acknowledged. First, the study was limited to five districts, potentially affecting the generalizability of findings across the entire country. Second, the reliance on self-reported data may have introduced response bias, especially among senior-level staff. Third, the perspectives of frontline healthcare workers, who are also end-users of HR technologies, were not fully captured. Future research should therefore include broader geographic representation, integrate real-time system usability assessments, and consider longitudinal designs to evaluate long-term impact and sustainability.

Future research should also examine the cost-effectiveness of HRIS implementations and explore mechanisms for public-private partnerships in scaling digital health infrastructure. Studies evaluating the correlation between HRIS adoption and health outcomes such as staff retention, service coverage, and patient satisfaction would be valuable. In addition, participatory action research involving healthcare providers, patients, and administrators could provide context-specific innovations to further digital transformation.

To address the identified challenges, we recommend that the Ministry of Health and Family Welfare in Bangladesh strengthen its HR digital strategy through targeted capacity-building initiatives and decentralized budgetary allocations. Policy-makers must prioritize uninterrupted infrastructure provision and strengthen intersectoral coordination to ensure the sustainability of digital health interventions. Investing in the digital literacy of healthcare administrators and HR personnel will be pivotal in driving behavioral change and enhancing institutional readiness.

Conclusion

This study identified infrastructural, organizational, and systemic barriers to the adoption of digital technology in human resource management within Bangladesh’s healthcare system. Despite the availability of HRIS infrastructure in many facilities, weak internet connectivity, limited digital literacy, insufficient training, and leadership inertia hinder effective implementation. Bridging these gaps will require targeted training, strategic resource allocation, and stronger leadership engagement. The adoption of HRIS holds transformative potential for improving workforce efficiency and health system performance, but this potential can only be realized through coordinated, well-funded, and inclusive national strategies. It is recommended that Bangladesh prioritize digital health in workforce planning policies to move toward a more equitable and efficient healthcare system.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

A.T. conceptualized the study, curated and analyzed data, conducted the investigation, developed the methodology, and wrote the original draft. M.M.H.S. contributed to methodology, formal analysis, validation, visualization, and both original and revised writing. S.K. contributed to methodology, provided supervision, and reviewed and edited the manuscript. S.Kh. supported methodology development, provided supervision, and contributed to both original and revised writing. All authors reviewed and approved the final manuscript.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability

All data generated or analysed during this study are included in this published article and its supplementary information files.

Declarations

Ethical approval

The study received ethical approval from the Research Ethics Committee of the Faculty of Health and Life Sciences, Daffodil International University, Dhaka, Bangladesh (Approval No. FHLSREC/DIU/2024/SMIG-46).

Human ethics and consent to participate

Informed consent was obtained from all participants before data collection. Respondents were informed about the study’s objectives, data confidentiality, and their right to withdraw at any stage without consequences. For the quantitative component, an electronic consent form was included in the email communication and attached to the physical questionnaire. For key informant interviews, verbal consent was obtained and recorded at the beginning of each session. Participation was entirely voluntary. Confidentiality and anonymity were maintained throughout the study by de-identifying responses and securely storing all data. The study adhered to the ethical principles of the Declaration of Helsinki and ensured no coercion or exploitation of vulnerable groups.

Consent to publish

Not applicable.

Declaration of generative AI in scientific writing

The authors did not use generative AI or AI-assisted technologies in the development of this manuscript.

Competing interests

The authors declare no competing interests.