The procurement process in healthcare is the systematic process of identifying an institution's needs, looking for potential suppliers and negotiating contracts, further ensuring the smooth functioning and timely acquisition of medical services. Effective procurement directly results in operational efficiency, cost containment, quality control, and enhanced care delivery in the healthcare setting.(1)

Various industries and sectors have successfully implemented digitisation in communicating and purchasing goods and services.(2) In most Indian tertiary care centres, procurement still relies predominantly on manual processes, which leads to delays in indent processing, quotation comparisons and vendor approvals.(3) These delays further contribute to bottlenecks in the supply chain, stock-outs, and financial waste in various high-volume facilities, especially in resource-limited settings. In this study, procurement delays were observed in a 2000-bed tertiary care teaching hospital and noted to affect inventory availability and interdepartmental coordination.

Digitisation of the procurement process provides the potential for transformation by integrating technologies including management software, cloud computing, radio-frequency identification, blockchain technology, enterprise resource planning and artificial intelligence.(4) These tools would help experts concentrate their efforts towards strategic purchasing by not only optimising processing time but also helping analyse data more effectively, enhancing traceability, anticipating possible problems and lowering demand uncertainty.

In healthcare, such technologies have been used to support supply-demand forecasting, contract management, and traceability of pharmaceuticals and medical devices.(5) These tools remain underused in the Indian healthcare field, which can be owed to barriers in the IT infrastructure, insufficient training, concerns with data privacy and resistance from various points and levels in the administration.

Current procurement workflows need to be identified strategically to identify gaps in the process, thus developing a phased, cost-effective implementation plan that keeps in mind the realistic situation of institutions. Involving various stakeholders, including procurement officers, IT teams, and hospital administrators, will help ensure feasibility and sustainability in the long run. This gap in administration is needed for the study to be conducted.

Observational process mapping and stakeholder engagement were used to analyse the procurement workflow in a tertiary care hospital in South India. The study aims to identify different opportunities or areas for digitisation and develop a phased roadmap for practical use, simultaneously remapping workflows that could serve as a feeder for algorithms for AI-based platforms, leading to adaptive supply chain models.

Research Methodology:

The qualitative study was conducted in the procurement department of a 2000-bed tertiary care teaching hospital in South India over the duration of two weeks.

Study Objectives

Data Collection

Direct, non-participant observation was conducted at each stage of the procurement workflow. Observational field notes were recorded, and key steps were tracked using process flow templates. The primary focus was on documenting routine processes such as indent generation, vendor quotation, approval hierarchies, and manual data handling.

Unstructured interviews and focus group discussions (FGDs) were implemented with 15 stakeholders, including procurement officers, IT professionals, general store managers, nursing staff, clinicians, and hospital operations directors.

Interview notes were transcribed and written manually in Microsoft Excel to identify recurring themes related to workflow inefficiencies, digitisation readiness, and perceived barriers. No audio recordings were made, and responses were summarised in real time.

Process Mapping and Analysis

Each procurement pathway was mapped using workflow diagrams, covering medical equipment, stock, and non-stock items. Process bottlenecks were flagged using Kaizen burst symbols, a lean mapping tool that visually denotes areas requiring improvement.

Each Kaizen burst represented delays or inefficiencies, such as prolonged comparative statement generation, delayed indent approvals, or redundant documentation cycles.

Finally, these maps served as the foundation for data collection from stakeholder and analysis sessions. Group discussion helped reach consensus on which workflow stages could be digitised based on existing infrastructure and user capabilities.

Implementation Roadmap Development

A two-year implementation roadmap was developed and structured based on the findings.

Ethical Considerations

No formal institutional ethics review was required, as the study involved only workflow observation and internal systems analysis. No patient data were accessed. Verbal informed consent was obtained from all participants, and confidentiality of their input was maintained throughout.

An overview of the primary procurement process after qualitative research was mapped and represented by the figures (Figs. 1,2,3). The diagrams explained the procurement sequences for equipment, non-stock, and in-stock items.

This process begins with the user department raising an indent electronically(online) or through paper-based channels(offline). Upon receiving the indent, the procurement department inquiries about pre-listed vendors via the hospital's software. Quotations are received and manually compiled for evaluation. The comparative statement, which lists vendors, prices, and delivery terms, is then prepared, and this process itself often requires up to 2 hours when multiple items are involved. After review, the file moves through multiple layers of administrative approval before a purchase order is placed.

Various inefficiencies found were dual-mode indenting (manual and digital), repeated data entry, and complete reliance on manual preparation of the comparative statement.

This pathway depicts the workflow for items not maintained in the hospital's inventory. Once the indent is raised, the procurement team must identify appropriate vendors, send inquiries, and await quotations. The absence of an established vendor database for such items is why each cycle requires significant time in sourcing, quotation collection, and new comparative statement generation.

The challenges were boiled down to longer turnaround due to ad hoc vendor discovery, absence of item history or predictive demand systems and inconsistency in documentation templates.

This process begins with store verification of stock levels. If inventory is below a defined threshold, a replenishment indent is triggered. This workflow followed a similar part to the above, but vendor engagement is more consistent with non-stock items since these items are recurring.

Across all workflows, initial stages, such as indent submission, inquiry dispatch to vendors, and quotation reception, were digitised to some extent using existing software; however, later steps were mainly manual and time-consuming, including comparative statement generation and approvals.

Using Kaizen burst analysis, delays were most consistently observed in a few areas including comparative statement preparation (up to 2 hours per case), lack of real-time vendor communication, manual follow-ups for approval tracking, absence of data integration with inventory system, the highest priority having been the comparative statement according to multiple stakeholders, due to its frequency and time burden.

On further analysis of the focus group discussions and interviews, a variety of digitisation strategies were proposed which includes procurement management software with requisition, approval, sourcing, and vendor modules, E-procurement platforms for internal and vendor-side access, RFID/barcode systems for inventory traceability, automated comparative statement generation, basic AI-based demand prediction using historical indent data, and blockchain-based product authenticity traceability (as a long-term goal).

One crucial feedback was the need for easy integration into the current hospital information system and a user-friendly interface. Stakeholders also rejected digitising final procurement approvals (e.g., e-signatures) due to administrative and legal constraints.

Allocation of funds into a realistic budget is crucial and has been summarised in the table below (Table 1)

A two-year digitisation strategy was developed, where Year 1 would cover steps including needs analysis, stakeholder engagement, infrastructure evaluation, training, software configuration, and compliance planning. Year 2 would comprise platform deployment, KPI tracking, feedback-based optimisation, integration with EHR and accounting systems, and performance evaluation.

Figure 4 presents the visual roadmap, with milestone-based checkpoints for each quarter. Using remapped workflows would help lay the foundation for developing an AI-based procurement platform, automating demand forecasts, identifying cost-cutting opportunities and optimising vendor selection for an overall predictive model.

The study stresses the role of digital technologies, which can transform the current procurement systems in healthcare institutions. The findings can lead to strategic intervention in operations and the first step towards an artificial intelligence-based supply chain adaptation. Current research reveals that manual processes are prevalent in procurement and cause significant inefficiencies in multiple areas, including tracking indents and comparing quotations and approvals.(6) Automating these steps reduces cycle time and enhances data tracing and interdepartmental coordination. Fragmented procurement workflows are common globally, especially in resource-limited healthcare settings, and the digital capabilities of various back-end systems remain low even though there is increasing digitisation in the clinical services.

Through process mapping, real-time observation, staff interviews and lean methodology like Kaizen bursts, our study identified critical pain points and bottlenecks and proposed designed digital interventions. The result was shaped into a phased and grounded roadmap centred around the current workflows, constraints in the IT infrastructure and the organisational culture. The hospital software supports initial stages, including indent generation and quotation inquiry. However, the areas that remain bottlenecks, including comparative statement preparation and approval processes, have become areas of priority and are proposed to yield the most returns in reducing staff time, labour, and process transparency.

The various stakeholders preferred a user-friendly interface readily integrated into the current hospital information system with minimal training required. Although the technical feasibility proved possible, the administrative resistance around legality, data protection and compliance with regulations, including the e-signatures, disputed transactions, led to the current partial adoption. Even when technology is ready, the governance and institutional policies are lagging.(7) In response to this, as a workaround, our project team proposed a mechanism on the middle ground, where the oldest comparative statement would trigger an automated alert to the head of procurement if it remains unapproved. A comment box would then allow the approver to input and document the reason for rejection, reducing the need for a digital signature. Also, features like vendor item mapping dropdowns, automatically calculating price fields, and approval dashboards were added to the interface mock-up. To showcase how the digital design can easily accommodate the existing constraints, we have depicted these features, including a semi-automated comparative statement generation interface (Fig. 5) and approval dashboards (Fig. 6). For example, the "Add Vendor" interface allows procurement staff to pre-select vendors and match them with item categories from a dropdown, reducing manual data entry errors. While having not implemented them during the study, these elements were demonstrated to stakeholders to help guide future upgrades. These are also very simple yet powerful and help by not overloading users.

This study affirms the conclusions drawn in existing literature and how the digitisation enhances multiple performance metrics. However, our implementation setting, a south Indian tertiary care hospital, gives us a unique infrastructure and behavioural constraints that are not widely covered in global procurement literature.(8) In this real-time, resource-constrained environment, our findings become more applicable for health systems across low- and middle-income countries, both in the private and public spheres.

The core output of the study was a two-year digitisation roadmap where important contributions are owed to the structured, layered data models within the remapped workflows, which can provide an ideal foundation for the algorithmic learning in the development of AI-based procurement platforms. Each process node, from indent generation to vendor quotation, statement preparation, approval tracking and rejection reasoning, can be converted to discrete data variables that can be used in training rule-based machine learning models. The platform could forecast item demand by department, dynamically rank the various vendors based on price and performance history, trigger alerts for potential stock-outs, view seasonal trends and even flag anomalies suggesting fraud or supply disruptions. Even in the emerging literature on AI-based supply chains, automation is not limited to digitising existing workflows but is also moving towards predictive and adaptive decision-making. (9)

Real-world adoption of the proposed technology faces concerns about data authenticity, accountability in audits and lack of national-level policy backing, hence requiring not just IT systems but also a change in fundamental regulatory frameworks. There are also important security concerns since hospitals handle sensitive patient and vendor data. Our study has included budget allocation for areas including initiatives that prioritise HIPAA-aligned safeguards, containing firewalls, role-based access and regular auditing.

To bridge these gaps, various policy directions can be proposed. National-level procurement standards help clarify the legal validity of digital approvals and hence employ a baseline guideline for public and private hospitals. Targeted infrastructure grants would support public hospitals in upgrading their digital backbone. Procurement staff, including non-clinical administrators, should be integrated into digital health capacity-building programs for regular training. Institutions should also require routine cybersecurity audits and policy audits.

This study demonstrates that process mapping, guided by stakeholder input and lean methodology, can effectively identify and address inefficiencies in hospital procurement workflows. The phased digitisation strategy that resulted from the study, which was grounded by realities of institutions and designed for component-based implementation, offers a model that can consistently improve operational efficiency, data accuracy and accessibility, transparency and accountability in healthcare systems.

Digitising the procurement department would come at a significant cost; further research is required in the area to determine the return on investment and potential cost savings. Apart from the immediate gains in cycle time and alleviating the administration burden, these workflows can also help develop AI models in the future. There is untapped potential for predictive supply chain models. Healthcare systems in India and other low and middle-income countries are transitioning towards digital infrastructure, hence such initiatives offer scalability and a pathway to sustainable healthcare practices.