Optimization of Cleaning and Hygiene Processes in Healthcare Using Digital Technologies and Ensuring Quality Assurance with Blockchain

Abstract

Many hospitals still lack digital traceability in hygiene and cleaning management, leading to operational inefficiencies and inconsistent quality control. This study aims to establish cleaning and hygiene processes in healthcare services that are planned in accordance with standards, as well as to enhance the traceability and sustainability of these processes through digitalization. This study proposes a Hyperledger Fabric-based blockchain architecture to establish a reliable and transparent quality assurance system in process management. The proposed Quality Assurance Model utilizes digital technologies and IoT-based RFID devices to ensure the transparent and reliable monitoring of cleaning processes. Operational data related to cleaning processes are automatically recorded and secured using a decentralized blockchain infrastructure. The permissioned nature of Hyperledger Fabric provides a more secure solution compared to traditional data management systems in the healthcare sector while preserving data privacy. Additionally, the execute–order–validate mechanism supports effective data sharing among stakeholders, and consensus algorithms along with chaincode rules enhance the reliability of processes. A working prototype was implemented and validated using Hyperledger Caliper under resource-constrained cloud environments, confirming the system’s feasibility through over 100 TPS throughput and zero transaction failures. Through the proposed system, cleaning/hygiene processes in patient rooms are conducted securely, contributing to the improvement of quality standards in healthcare services.

1. Introduction

In recent years, the integration of digital transformation applications into healthcare services has led to significant advancements in hospital service management. These advancements not only focus on patient care and treatment processes but also play a critical role in improving hygiene and cleaning processes in healthcare environments [1]. The lack of digital support in cleaning processes poses certain risks in terms of patient safety and operational efficiency, creating obstacles to achieving optimal healthcare outcomes. The integration of digital technologies into cleaning operations transforms practices into faster, more traceable, and more efficient processes. These technologies provide a suitable infrastructure for monitoring, reporting, and detecting disruptions in cleaning services. Digital cleaning processes enable a proactive approach to potential issues, minimizing resource waste and reducing operational costs.

The standardized planning of hospital cleaning process management and the integration of these processes with digital technologies not only improve service quality but also ensure the sustainability of these processes. Digital technologies enable the effective planning, monitoring, and auditing of cleaning activities. They also ensure the secure recording and storage of data generated throughout the process. The measurability of service quality and the optimization of processes depend on the accessibility of this data.

In the literature, it has been observed that the integration of technologies such as the Internet of Things (IoT), artificial intelligence (AI), and Big Data analytics into healthcare services supports the monitoring and improvement of cleaning/hygiene practices in these environments [2,3,4,5,6]. For example, the use of sensors enables real-time monitoring of room occupancy and cleaning processes, facilitating the instant sharing of information [7]. Automated hand hygiene monitoring systems track compliance with established standards, supporting performance improvements [8]. Additionally, IoT-based applications allow for the monitoring of cleaning equipment and the verification of sterilization processes [9]. Cleaning activities are facilitated by aligning the routes of areas to be cleaned with autonomous robots [8]. The implementation of technologies such as sensors and wearable devices contributes to the precise monitoring and analysis of cleaning-related data [10]. The reviewed studies indicate that healthcare institutions leveraging these innovations have improved their cleaning/hygiene processes and ensured their efficient implementation.

The proper management of cleaning and hygiene processes is crucial not only for operational efficiency but also as a critical factor that directly affects patient safety. In this context, findings related to the risk of healthcare-associated infections (HAIs) clearly demonstrate the importance of the issue. HAIs pose a serious threat to patient safety and place a significant financial and resource burden on healthcare systems. In the United States alone, a total of 721,800 HAI cases were recorded in 2011, resulting in the deaths of 75,000 patients. Various studies have shown that surfaces in patient rooms—such as curtains, bed rails, and equipment—are frequently contaminated with pathogens like Clostridioides difficile, MRSA, or Acinetobacter baumannii, and that inadequate cleaning practices allow these pathogens to be transmitted directly or indirectly between patients and healthcare workers. According to the CDC (Centers for Disease Control and Prevention) guidelines, individuals who occupy a room after an infected patient have a significantly higher likelihood of developing an infection [11]. Furthermore, it has been reported that pathogens can survive for extended periods on insufficiently disinfected surfaces and cause serious infections [12]. These findings demonstrate that cleaning procedures are not merely a support service but are in fact a critical safety practice with a direct impact on patient health. However, these manually executed processes are inadequate in terms of traceability, transparency, and quality control. In this regard, our study aims to transform cleaning and hygiene processes into observable and measurable structures through the use of digital technologies, as well as to integrate these processes into a quality assurance framework using a secure blockchain-based system.

In this study, three consecutive key solution proposals are addressed to overcome various challenges related to efficiency, traceability, and compliance with standards in traditional cleaning processes applied to patient rooms. In the first phase of the solution, the focus is on planning all processes to ensure that all applicable standards for cleaning and hygiene in patient rooms within the healthcare sector are efficiently met. The activities within the processes will be carried out using a planned and organized management model. This model includes defining the scope of the types of cleaning to be applied and specifying the appropriate equipment and expert units required for the operations within the defined scope.

In the second phase, the pre-planned and organized cleaning and hygiene processes, which have been aligned with healthcare standards, will be digitalized to ensure effective management, traceability, and auditability. This will help minimize the risk of adverse events related to cleaning and hygiene affecting patients, healthcare workers, and visitors. Additionally, it is expected to improve operational efficiency along with general hygiene standards and safety in patient rooms.

In the third and final phase, the aim is to secure the designed and digitalized processes. In traditional systems, proving that cleaning tasks are performed accurately and on time generally relies on manual records and physical inspections. However, these methods carry significant limitations in terms of data security and audit reliability. Therefore, in our study, the use of blockchain technology is proposed to securely store data related to cleaning processes, enable easy verification of data accuracy, and allow retrospective audits when necessary. Accordingly, it is envisioned that blockchain technology will be integrated into a system that includes all stakeholders such as patients, caregivers, cleaning staff, healthcare professionals, hospital administrators, and public health authorities. Blockchain is one of the most advanced technologies used as a decentralized database system where records, once created, are extremely difficult to alter for each participant. With the integration of the model into a blockchain-based system, it is expected to function as a Quality Assurance Model in which all processes are secured through the participation of authorized personnel, administrators, and users.

In summary, the cleaning processes of patient rooms in the healthcare sector are of great importance for patient safety and infection control. However, studies on the optimization of these processes in the literature are limited, and the integration of digital technologies remains insufficient. This study aims to establish a quality assurance system that ensures traceability, transparency, interoperability, and sustainability in cleaning and hygiene processes in healthcare services. Additionally, it seeks to create a reliable system by verifying the compliance of operations with established standards.

By utilizing blockchain technology, digital-technology-supported cleaning processes ensure transparency in monitoring hygiene protocols, verifying sterilization processes, and maintaining immutable records of cleaning activities.

The proposed model provides a foundation for achieving strategic goals such as improving operational efficiency and minimizing infection rates while enhancing patient safety standards in the healthcare sector’s digital transformation journey. While blockchain technology has found various applications in areas such as electronic health records and pharmaceutical supply chains, its potential to support real-time hygiene task validation and quality assurance in hospital cleaning practices remains largely unexplored. This study addresses this critical gap by introducing a verified, blockchain-enabled quality assurance framework specifically tailored to the needs of hygiene management in patient room environments.

The structure of this paper is as follows: Section 2 provides a literature review on digital technologies and blockchain use in healthcare. Section 3 introduces the proposed system’s architecture and methodology. Section 4 evaluates the implementation and performance results. Finally, Section 5 presents the conclusions and outlines directions for future work.

2. Literature Review

Today, digital technologies offer significant innovations in cleaning and hygiene processes in the healthcare sector, enhancing operational efficiency through effective applications in these areas. In particular, ensuring hygiene standards, reducing costs, and improving service quality in the long term highlight the potential of digital technologies in the healthcare sector. This section includes significant studies on digital technologies used in cleaning and hygiene, assessing their contributions to healthcare services. Additionally, a literature review has been conducted on blockchain-based applications developed for the healthcare sector, leveraging its advantages such as data security, operational efficiency, and decentralization. By organizing the literature into two categories, digital cleaning technologies and blockchain in healthcare, we aim to highlight both the established and underexplored dimensions relevant to our proposed solution. However, no studies have been found that directly address the use of blockchain in managing cleaning and hygiene processes in the healthcare sector. In this context, the literature has been analyzed under two separate headings: digital technologies used in cleaning and hygiene processes and the role of blockchain technology in healthcare services.

2.1. Digital Technologies Used in Cleaning and Hygiene Processes

The literature presented in this section addresses current approaches to the use of digital technologies in maintaining cleaning and hygiene standards in healthcare services. Existing studies enable monitoring, management, as well as continuous improvement of cleaning, hygiene, and sterilization processes through sensor-based systems, AI-supported processes, automated monitoring applications, and IoT-based solutions.

Systems for monitoring air quality and personnel movements stand out among the capabilities provided by digital technologies. For example, an application proposed by Colella et al. [13] uses sensor-based techniques to monitor particle density levels and staff activities in operating rooms for air quality control, utilizing a fuzzy logic model implemented with this data. The main goal of this approach is to minimize the risk of hospital-acquired infections by reducing airborne transmission hazards during surgical operations. A similar method examined in the study by Wang et al. focuses on minimizing the chances of disinfection by utilizing an AI-assisted PDCA (Plan, Do, Check, Act) cycle [3]. This strategy enables process improvements through the analysis of extensive data sets.

Researching the monitoring and enhancement of hand hygiene practices is a significant area of study that deserves attention in the field of healthcare compliance standards, as highlighted by Levchenko et al. [14], who monitored healthcare personnel’s hand hygiene practices in real time through wearable devices and automated reminders. Similarly, Geilleit et al. [4] introduced a hand hygiene alert system powered by machine learning technology for real time use at hospitals that provides an affordable approach to improving adherence to hand hygiene guidelines in order to reduce the transmission of hospital-acquired infections.

The use of RFID (Radio Frequency Identification) and IoT-based systems among the digital technologies employed in operational process management has also been extensively discussed in the literature. A system that monitors hand hygiene independently and utilizes technologies has been suggested to improve infection prevention measures effectively [5]. This setup can track handwashing behaviors through gadgets and intelligent dispensers while offering immediate guidance if handwashing protocols are not followed accurately. Cheng and Kuo [7] in their study on healthcare technology innovation implementation in hospitals and clinics utilized RFID technology for tracking the real-time locations of patients well as staff members and medical equipment to effectively reduce the potential risks associated with the transmission of infectious diseases within healthcare facilities. Similar systems used in intensive care units and emergency departments [15] involve the live tracking of patient information to promptly identify situations that call for immediate action. Additionally, the system proposed by Masri and Hamdi [16] aimed to improve healthcare personnel’s adherence to standards by monitoring hand hygiene practices regarding patient beds through RFID technology.

Digital tracking systems stand out in monitoring cleaning processes. Çetin [17] introduced a QR-code-based digital cleaning monitoring system that digitizes cleaning forms, thereby increasing operational efficiency. Karimpour et al. [18] developed a system using Bluetooth Low Energy (BLE) beacons to track the location and hand hygiene compliance of healthcare personnel. The mobile app called “I Scrub” developed by Bal and Abrishambaf [10] stands out as a practical tool for monitoring and managing hand hygiene compliance. This application is proposed as an alternative solution to expensive and time-consuming methods.

Within the scope of the literature reviewed, these studies show that integrating digital technologies into cleaning and hygiene processes in healthcare services enhances service quality, patient safety, and operational efficiency. In this context, technologies such as sensors, automated monitoring systems, artificial intelligence, and big data analytics make significant contributions toward making cleaning and hygiene practices more effective, sustainable, measurable, and open to improvement.

2.2. The Role of Blockchain Technology in Healthcare Services

Lately, blockchain technology has become a cutting-edge solution in healthcare services by providing features that boost transparency and data security while decreasing the reliance on control systems in sector operations. Various studies have explored the applications of blockchain in improving healthcare services.

Ichikawa et al. [19] highlighted the significance of technology in safeguarding and organizing healthcare information by creating a mobile health (mHealth) app focused on treating insomnia on smartphones with data security ensured through the Hyperledger Fabric framework and Practical Byzantine Fault Tolerance (PBFT). The application they proposed caters to the data handling requirements of patients and healthcare professionals alike while setting the groundwork for enhancing mHealth apps with blockchain technology. Similarly, Vora et al. [20] in a study on electronic health records (EHRs) implemented a decentralized architecture to guarantee the secure storage and control of data that safeguards patient privacy and enables seamless data exchange between various parties, such as healthcare professionals and insurers.

Rouhani et al. [21] explored how blockchain technology could be utilized for efficient data handling in the healthcare sector specifically focusing on the storage of medical imaging data in a secure and patient-centered manner. They introduced a system that empowers patients to take charge of their health information through easy-to-use mobile and web platforms, giving them greater control over their healthcare data management processes. Similarly, Dobre and Văsilateanu [22] utilized blockchain infrastructure and QR codes to provide fast and secure access to health data. This system accelerates patient–doctor communication and can be effectively applied in scenarios requiring urgent intervention.

Jamil et al. [23] analyzed the role of blockchain technology in healthcare supply chains by introducing a model designed to minimize the risks of products at every stage. Starting from production to reaching the patients’ hands, this proposed model enhances the tracking of medications to ensure patients receive treatments and improves overall operational effectiveness in healthcare delivery systems.

Studies focusing on the integration of blockchain, IoT, and artificial intelligence offer significant perspectives for the development of digital health solutions. For instance, Xie et al. [24] implemented a blockchain system to store health data from wearable devices and offer personalized healthcare services using AI analyses techniques in an innovative way. In a vein of innovation in healthcare technology research by Ratta et al., real-time monitoring systems for diabetic patients have been developed to help individuals manage their health more effectively [25]. Such advancements truly benefit patients, and these systems provide significant advantages for individual patients.

Focusing on the secure management of data obtained from IoT devices [26], the proposed system utilizes blockchain technology to ensure the secure handling of electronic health records (EHRs). In this system, blockchain technology is integrated with IoMT devices using a low-cost embedded system. The authors secure healthcare data on the blockchain through encryption. Additionally, Ganapathy et al. [27] combined federated learning and blockchain technologies to provide secure data transmission in IoT networks, thereby enhancing security levels with intrusion detection mechanisms. The framework presented in their study can manage data diversity and heterogeneity in healthcare IoT networks.

Studies focusing on improving resource allocation and data sharing in healthcare systems emphasize the capacity of blockchain technology to enhance operational performance. Alfakeeh and Javed [28], addressing resource allocation problems in healthcare systems, offered an innovative approach by integrating blockchain technology with the knapsack algorithm. Shen [29] proposed a ‘digest chain’ mechanism to optimize the verification of IoT data streams and transferred modifiable data to P2P networks, thereby reducing the load on the blockchain. The study preserved user privacy while also facilitating data sharing. Such studies provide forward-looking solutions to increase the efficiency and effectiveness of healthcare systems.

From a broader perspective, the study by Mozumder et al. [30] combined artificial intelligence, IoT, and blockchain technologies within a metaverse environment to present an innovative framework for anti-aging healthcare services. In this study, augmented reality (AR) and virtual reality (VR) technologies made significant contributions to the training of healthcare professionals and patient treatment. The study revealed that metaverse-based healthcare services provide cost-effective solutions for the healthcare sector.

The technical advantages of blockchain in the secure management of health data have been elaborated upon in the works [31,32,33,34]. These studies, focusing on the use of permissioned blockchain networks, emphasize key advantages such as patient privacy protection and regulatory compliance.

These studies detailing the application of blockchain technology in healthcare services demonstrate its wide range of use cases and associated technologies. The table below presents a summarized assessment of these studies from the literature.

Table 1. Detailed applications of blockchain technology in the healthcare sector existing in the literature.

Ref.	Usage Field	Technologies	Data	Stakeholders	Contribution
[19]	EHR Management	Blockchain-based on Hyperledger Fabric and PBFT algorithm	Data on cognitive behavioral therapy for insomnia (CBTi)	Patients, therapists, and mobile application providers	Data collected via mobile devices has been securely stored in a decentralized manner.
[20]	EHR Management	Ethereum-based blockchain and Smart Contracts	Patient diagnosis information, medical history, and data related to treatment processes	Patients, healthcare providers, and third parties	A model has been proposed to enhance data immutability and patient privacy.
[21]	Health Information Transfer and Management	Hyperledger-based blockchain with off-chain data storage	Patient diagnosis information, medical history, and data related to treatment processes	Patient, caregiver, health practitioner	The off-chain data storage method has reduced transaction costs on the blockchain.
[22]	Health Information Transfer and Management	Ethereum-based blockchain, QR codes, smart contracts	Patient history, diagnoses, and treatment plans	Patient, doctor	Integration of blockchain and QR code for enabling patients to gain full control over their health data.
[23]	Pharmaceutical Supply Chain and Anti-Counterfeiting	Hyperledger Fabric-based blockchain, Hyperledger Caliper	Pharmaceutical production information, shipment data, delivery reports	Doctor, patient, nurse, pharmacist	An innovative model has been developed to enhance the traceability of pharmaceuticals and detect counterfeit drugs.
[24]	EHR Management	Ethereum-based blockchain, IoT sensors, AI, health digital twins	Glucose levels, blood pressure measurements, biometric health data	Patients, healthcare providers, and research institutions	Real-time health monitoring has been achieved by integrating AI and blockchain technologies.
[25]	EHR Management	Ethereum-based blockchain, smart contracts, machine learning, IoT	Blood sugar and blood pressure measurements; records associated with patients, doctors, and hospitals	Patient, doctor, hospitals	A novel five-layer model integrating IoT, blockchain, and machine learning has been developed for remote monitoring of diabetes patients.
[26]	EHR Management	IoMT devices, Ethereum-based blockchain, Proof of Work, Keccak algorithm	Blood pressure, oxygen concentration, electroencephalogra, measurements, medical imaging	Patient, doctor, pharmacist, insurance companies	An energy-efficient and reliable health monitoring system integrated with IoMT devices has been developed.
[27]	EHR Management	Hyperledger Fabric and Ethereum-based blockchain, Federated Learning, Proof of Work, IoT	Patient diagnoses, treatment plans, vital measurements, IoT device data, and data related to network attacks	Patients, IoT network administrators, healthcare providers	Attack detection and data integrity optimization have been achieved in IoT networks.
[28]	EHR Management	Consortium blockchain, Knapsack algorithm, SHA-256, secure hash algorithm, Load Balancing Mechanism	Biometric data, critical, medium, and low-priority patient information	Patient and healthcare providers	Prioritization of critical patient data processing over other types of data.
[29]	Health Information Transfer and Management	Consortium blockchain, P2P network, Digest chain, Merkle tree	Patient health data	Patients, healthcare providers, researchers, and insurance companies	A solution has been developed to reduce the data load on the blockchain network.
[30]	Health Information Transfer and Management	Ethereum-based blockchain, AI, IoT, Digital Twins, AR and VR	Patient health data, medical records	Patients, healthcare providers, and third parties	Personalized treatments and education were delivered in the metaverse.
[32]	EHR Management	Hyperledger Fabric-based blockchain, Byzantine Fault Tolerance (BFT) consensus algorithm, P2P Network	Patient health data, medical records	Patients, healthcare providers, insurance companies, and organizations requesting data for medical research	Data privacy and access control have been ensured.
[31]	EHR Management	Blockchain based on Hyperledger Fabric, Smart Contracts	Patient health data, medical records	Patients, healthcare providers, insurance companies, and organizations requesting data for medical research	Effective and secure data sharing has been achieved among healthcare providers.
[33]	EHR Management	Blockchain based on Hyperledger Fabric, Smart Contracts	Patient health data, medical records	Patient and doctor	Patient privacy is protected, unauthorized access to data is prevented, and all data transactions are immutably recorded.

concretizes the potential of blockchain technology in the healthcare sector by systematically examining the application usage field, featured technologies, data, stakeholders, and contributions of each study. Although several studies utilize blockchain to secure IoT-generated health data, none of them focus on integrating real-time operational workflows such as hygiene inspections or cleaning routines into quality assurance frameworks.

This literature review on the utilization of digital technologies in cleaning and hygiene processes, as well as blockchain technologies in the health sector, highlights the critical role these technologies play in enhancing healthcare services. Digital technologies applied in hygiene and cleaning processes provide substantial benefits, particularly in maintaining hygiene standards, reducing operational costs, and optimizing business workflows. Similarly, current blockchain applications in the healthcare field offer innovative solutions in areas such as data security, transparency, and traceability.

However, our analysis reveals a significant gap in the literature at the intersection of these two technologies—particularly regarding the direct application of blockchain technology in cleaning and hygiene processes. This gap is not only theoretical but also a practical issue that directly threatens operational efficiency and patient safety. Despite the growing interest in blockchain-based health solutions, no existing study directly applies blockchain to monitor, verify, and secure hygiene and cleaning operations within hospital environments. Despite the fact that digital technologies and blockchain-based applications have achieved remarkable advancements in healthcare services, there are still notable limitations in the current literature. Specifically, data security vulnerabilities in IoT and RFID systems, the restricted application of blockchain technology primarily to EHR systems, and the lack of quality assurance in digital cleaning monitoring systems pose direct threats to patient safety in modern healthcare. This research aims to address these critical gaps in the existing literature and enhance traceability, transparency, and security in hospital cleaning operations in order to contribute to operational efficiency.

This dual perspective from the literature underscores the importance of developing a system that integrates the strengths of digital traceability and blockchain security to address pressing gaps in hospital hygiene process management. In this context, our study proposes a system architecture that enables the sustainable improvement of service quality and the development of effective quality assurance systems for cleaning and hygiene processes in hospitals. The proposed system architecture contributes to the continuous enhancement of quality and safety standards in healthcare services.

3. Materials and Methods

Ensuring hygiene and maintaining traceability through digital technologies are critically important in healthcare systems. Sustaining high-quality cleaning and hygiene practices in patient rooms, optimizing these processes operationally, and utilizing digital technologies integrated into the existing hospital information management system are essential for creating a traceable patient room concept [35].

This study presents a comprehensive technological process management framework for hospital room cleaning. The main objective is to plan cleaning processes in accordance with standards and to support this planning with digital technologies integrated into the management information system. To ensure the security of the designed model, a permissioned blockchain architecture is utilized. Among various blockchain frameworks, Hyperledger Fabric was selected due to its support for permissioned networks, modular consensus protocols, and integration flexibility with enterprise systems. Blockchain is one of the latest technologies that can enhance the security and management of a quality assurance system through its strong security features. It can provide transparency, traceability, immutability, and secure sharing, thereby contributing to the establishment of a reliable environment for high-quality operations.

With the proposed approach, a decentralized and secure model is created, aiming to ensure process integrity and continuous improvement. There are various architectures in blockchain applications, and the proposed architecture for the designed model will be based on the Hyperledger Fabric architecture. This architecture was chosen for its capability to support modular consensus (e.g., Raft), fine-grained access control, and high interoperability in enterprise-grade infrastructures. This architecture facilitates the development of a shared, immutable, secure, scalable, and interoperable solution while offering advanced transparency, privacy, and security features.

In the proposed model for optimizing cleaning processes, cleaning operations in patient rooms are divided into three main categories: routine cleaning, detailed cleaning, and cleaning on demand.

• Routine cleaning involves tasks aimed at ensuring basic hygiene according to daily schedules.
• Detailed cleaning includes disinfecting all surfaces and equipment in the room after the patient is discharged.
• Cleaning on demand is a flexible process carried out based on specific requests, without being tied to a set schedule.

The effective management of cleaning processes is carried out by different specialized units, as shown in Figure 1. These include planning, control, cleaning services, hygiene services, and the textile laundry unit, as described below.

• Planning Unit: Organizes all activities and creates work orders.
• Control Unit: Monitors the completed cleaning through random sampling and ensures compliance with quality standards.
• Cleaning Services Unit: Carries out cleaning activities involved in routine cleaning (daily cleaning tasks) and cleaning on demand processes.
• Hygiene Services Unit: Executes the activities defined in the detailed cleaning process after the patient is discharged.
• Textile Laundry Unit: Ensures that textile products meet hygiene standards. The cleaning of textile products (washing, drying, ironing, folding) is carried out under RFID control.

The framework illustrating the organizational structure of cleaning and hygiene processes and the distribution of responsibilities among the relevant management units is presented in Figure 1. This architecture outlines which units will be involved in the process, how tasks will be distributed among these units, how collaborations will be structured, and how quality assurance will be ensured. It also reveals through which units the proposed structure for the integration of digital technologies into cleaning processes will be implemented and how it will be aligned with the organizational workflow. While the Planning Unit organizes all cleaning activities, the Control Unit monitors the processes and ensures compliance with quality standards. On the other hand, the Cleaning Services Unit carries out routine hygiene operations. In addition to the digitalization of processes and the assurance of quality standards, the blockchain-based system enables transparent and reliable management by ensuring the immutability of records.

Each patient room is associated with a unique RFID tag, and cleaning staff carry RFID-enabled ID cards. When cleaning activities are performed, the staff scan their ID at the corresponding room sensor to log the task with a timestamp. These real-time records are automatically transmitted to the system and stored immutably on the blockchain, ensuring traceability, accountability, and auditability of hygiene operations.

As is well known, blockchain is a cryptography-based system with a decentralized and distributed ledger structure designed to securely record and display transactions. As shown in the blockchain architecture and transaction flow in Figure 2, it enforces the verification and approval of transactions according to predefined rules before they are added to the blockchain network. The ordering of transactions, network security, and management processes rely on the consensus mechanism. The Raft mechanism used in this architecture ensures enterprise-level data integrity, facilitates record-keeping, and enhances transparency through authorized nodes.

As illustrated in Figure 2, the blockchain network includes peer and orderer nodes. The endorsement and commit operations are carried out by the relevant peer nodes. Endorsing peers receive transaction requests from authorized users who aim to record data on the blockchain. These peers verify the validity of transactions by checking compliance with predefined smart contracts (chaincode) and forward valid transactions to the orderer node for inclusion in the blockchain. The orderer node sequences blockchain transactions based on the Raft consensus mechanism and converts them into blocks. These blocks are then distributed to the peers, where they are validated and committed to the ledger. With this step, the “execute–order–validate” phases are completed. This mechanism enhances system security by managing authentication and authorization processes for different user roles, including hospital management, cleaning service providers, and health authorities, through the Membership Service Provider (MSP), which is part of the network. In addition to digitalizing the quality assurance of cleaning and hygiene processes, the system ensures transparency and an immutable record structure.

3.1. IoT Integration Process

When the scheduled cleaning time arrives, the system automatically generates a work order. After completing the task, the cleaning staff initiates a process by scanning their RFID identification card on the reader. The RFID reader captures identity information, room details, and a timestamp, then formats this data into a structured JSON message. Instead of using the MQTT protocol, the RFID reader transmits this data via an HTTP POST request to the IoT gateway. The gateway, acting as an intermediary, validates the received data for integrity, authentication, and consistency. If the data passes validation, it is forwarded to the hospital’s Hyperledger Fabric peer node via a secure HTTP REST API call. If validation fails, the data is rejected, and no further action is taken. This API interacts with a Fabric Client SDK, which converts the received data into a transaction request for the blockchain network.

Upon reaching the peer node, the data is transmitted to the endorser nodes, which evaluate the transaction against predefined chaincode rules to ensure compliance. If the endorsement policy requirements are met, the transaction is signed and submitted to the orderer node, where it is structured into a block using the Raft consensus mechanism. The orderer then distributes this block to all relevant peer nodes, ensuring the data is permanently recorded on the blockchain ledger in an immutable and verifiable manner.

Once the transaction is successfully committed to the ledger, a confirmation response is sent back through the same channel—from the Hyperledger Fabric network to the IoT gateway, and then to the RFID reader—informing the cleaning staff about the transaction status in real time. Additionally, the hospital’s management system is integrated with the blockchain ledger through a REST API, enabling administrators to query and verify completed cleaning tasks in real time, ensuring a secure, transparent, and tamper-proof audit trail for room cleaning processes.

3.2. Blockchain Transaction Lifecycle and Chaincode Execution

This section explains how transactions are executed among stakeholders using the “execute–order–validate” mechanism of Hyperledger Fabric, which ensures both traceability and trust in distributed environments. The proposed Hyperledger Fabric-based system continuously records and stores all activities and events related to the transaction in the immutable ledger of the blockchain. First, all participants must identify and authenticate their identities using digital certificates and cryptographic functions through MSP. The MSP component handles identity management and permission control for all actors in the network. All stakeholders are registered and identified by the health authority in the peer-to-peer blockchain network. When user registrations such as patients, cleaning teams, hygiene teams, etc., are made, each is assigned a chaincode address and ready to perform transactions on the network.

A transaction request, such as patient room assignment, is sent to the endorsement peers determined according to the blockchain’s endorsement policy. The system consists of various parameters, including patient identity information, the list of transactions to be performed, the chaincode identifier; a one-time random number; and the transaction proposal identifier, according to the MSP. The algorithm describes a chaincode in which transaction activities are represented as different functions. This stage is called the endorsement phase or proposal phase. Designated peers, as specified in the endorsement policy, simulate the transaction by executing the chaincode without committing it. This ensures compliance with network rules and enhances protection against unauthorized actions. These peers validate the transaction and, if the results are correct, sign and return the outcome. The execution results are encrypted in output format and recorded along with the cryptographic signatures of the endorsing peers. This resulting message is called an endorsement. This validation mechanism not only ensures transaction correctness but also reinforces system-level security. Figure 3 illustrates two core chaincode functions in pseudocode format, representing typical interactions such as patient registration and routine room cleaning.

The chaincode designed for patient registration efficiently handles the processes of registering patients in the blockchain and managing room allocation. By first confirming whether the patient is previously registered and verifying room availability, the system ensures that patient and room information are accurately recorded on the blockchain, facilitating the seamless and effective management of both. Figure 4 shows the sequence diagram provides a comprehensive overview of the blockchain processes involved. Furthermore, the routine cleaning operations, governed by a specialized chaincode, ensure that patient rooms are cleaned in a consistent, transparent, and reliable manner. All cleaning requests and routine cleaning activities are timestamped and securely stored on the blockchain, ensuring data integrity and traceability.

Figure 4 illustrates how patients are registered in a blockchain-based system in healthcare services and how this process is securely executed. The patient registration process begins with the creation of the patient’s identity information, health status, and room allocation details. When a new patient is added to the system, a unique identifier is generated for the patient, and an electronic certificate (E-Cert) is requested. This certificate is issued by a local certification authority (Local CA) integrated into the blockchain network and assigned to the patient. Once the certificate is created, the patient registration verification process is initiated by the hospital’s endorser nodes. In this process, the patient’s information is transmitted to designated endorser nodes according to the blockchain’s endorsement policy and undergoes a verification process.

According to the RAFT-based consensus approval mechanism, the patient registration process can only be recorded on the blockchain after approval by the hospital and health authority nodes. The approved patient data is divided into blocks by the ordering service and added to the blockchain ledger. This stage ensures that the patient’s identity information is securely stored and immutable while also preserving data integrity. Once the patient is assigned to a hospital room, the room allocation information is updated in the system, creating a unique record for each patient. Thus, the patient admission and placement process is completed in a decentralized, transparent, and traceable manner.

Figure 5 provides a detailed explanation of how cleaning operations in patient rooms are digitally recorded and integrated into the blockchain system. This process is built on a structure that requires the collaboration of IoT devices, RFID technology, and blockchain systems to ensure the reliability and traceability of cleaning services. The RFID readers, acting as part of the IoT layer, collect operational data in real time and trigger blockchain transaction requests. The process begins with the execution of cleaning activities in patient rooms, where operations performed by cleaning staff are monitored in real-time using RFID-based IoT devices through a gateway. To enable the recording of cleaning operations, IoT devices must request an E-Cert before being integrated into the blockchain network. This certificate, issued by the Local CA, ensures that only authorized devices can write data to the ledger. The certificate, approved by the Local CA, is assigned to the IoT device responsible for cleaning operations, allowing the device to perform authorized transactions on the blockchain.

Once the certificate is obtained, details of the cleaning operations such as which room was cleaned, the identity of the cleaning personnel, the materials used, and the duration of the process are collected via RFID-based sensors and transmitted to the cleaning service provider. The cleaning service provider processes this data through the relevant chaincode and generates a transaction request to write it onto the blockchain network. At this stage, according to the RAFT approval policy, the cleaning operations are verified by the endorser nodes designated by the cleaning service provider, hospital management, and health authorities. The approval process aims to confirm whether the cleaning operations have been completed, whether they were conducted in compliance with the established hygiene standards, and whether any deficiencies exist. Once all approvals are obtained, the transaction is directed to the ordering service and recorded on the blockchain network. This record establishes a digitally secured and immutable cleaning history, ensuring transparency in hospital hygiene processes. Additionally, the system allows for automatic reporting of cleaning operations, enables retrospective review of past records, and ensures that hygiene protocols are fully implemented for patient safety. This structure not only enhances the reliability of cleaning management in healthcare services by providing real-time auditable records but also ensures the continuous maintenance of hygiene standards.

4. Technical Implementation of the Healthcare Hygiene Quality System

4.1. Implementation Details

The development environment for the proposed blockchain-based hospital hygiene and cleaning event management system was designed and implemented on a distributed multi-VM architecture using Google Cloud Platform. The architecture involved six Ubuntu 22.04 LTS virtual machines (VMs), each hosting an independent organization (Org1, Org2, Org3, and the Orderer organizations) in the Hyperledger Fabric network. The back-end configuration, the REST API services, and benchmarking tools, along with the client, peer, and orderer components, were deployed across multiple virtual machines. All nodes were provisioned with identical hardware configurations consisting of 2 vCPUs and 8 GB of RAM, reflecting a resource-constrained yet practical deployment setting.

The system leveraged Hyperledger Fabric v2.5.5 and Docker Swarm for orchestration of containers across multiple machines. Identity and certificate management were handled using Fabric CA, and Docker Compose was used locally to manage the service stacks. The client SDK and REST API server were developed using Node.js v18.20.8 and Python v3.10, and communication between clients and the blockchain was achieved via secure gRPC and HTTPS interfaces.

To evaluate performance under realistic workloads, Hyperledger Caliper v0.6.0 was configured with a Fabric gateway connector, and cryptographic identities were explicitly defined in the networkConfig.yaml file. Each organization’s wallet was populated with admin certificates and private keys for transaction endorsement.

The configuration details of the software and hardware components utilized in this implementation are summarized in

Table 2. Software and hardware components and their definitions used in the implementation.

Component	Description
Blockchain Framework	Hyperledger Fabric v2.5.5
Identity Service	Fabric Certificate Authority (Fabric CA)
CLI Tools	Docker CLI (v24.0.6), Docker Compose (v2.24.5)
Benchmark Tool	Hyperledger Caliper (v0.6.0)
Chaincode Language	Go
Operating System	Google Cloud Compute Engine (Ubuntu 22.04 LTS)
Hardware	2 vCPU, 8 GB RAM (All virtual machines)
Communication	TLS-enabled gRPC for peer/orderer and HTTPS for REST client interaction
Caliper Configuration	Docker container setup with Fabric Gateway binding and automatic identity injection
Client SDK	Node.js (v18.20.8), Python (v3.10)
REST API Interface	Fabric Gateway SDK with Express.js and gRPC middleware

.

4.2. Chaincode Implementation

In the proposed system, several smart contract functions were designed to support the digital management of healthcare operations, including patient admission, room assignment, and event logging. One essential component is the routine cleaning registration function, which contributes to hygiene assurance by allowing cleaning personnel to log sanitation tasks directly onto the blockchain using RFID-enabled tools. As explained in Section 3.2, this chaincode enforces predefined validation rules and integrates with the transaction flow managed by peer and orderer nodes.

This functionality is implemented using a smart contract (chaincode) written in Go and deployed on a multi-organization Hyperledger Fabric network. The chaincode includes data structures and logic that control access and enforces rules for each operation. Although the system contains multiple functions, Listing 1 presents a representative example: RoutineCleaning. This function records a cleaning event on the ledger using three input parameters—RoomID, CleaningStaffID, and Date. It checks that the room exists and is currently assigned to a patient before logging the event with a timestamp and updating the room’s cleaning status.

Listing 1. Chaincode structure of the Routine Cleaning function.

func (s *SmartContract) RoutineCleaning(APIstub shim.ChaincodeStubInterface, args []string) sc.Response {     if len(args) != 3 {      return shim.Error(“Expecting 3 arguments: RoomID, CleaningStaffID, Date”)     }     roomID := args [0]     staffID := args [1]     cleaningDate := args [2]

roomBytes, err := APIstub.GetState(“ROOM” + roomID)     if err != nil || roomBytes == nil {      return shim.Error(“Room ” + roomID + “ does not exist.”)     }

var room Room     if err := json.Unmarshal(roomBytes, &room); err != nil {      return shim.Error(“Failed to parse room data.”)     }     if room.AssignedPatientID == “” {      return shim.Error(“Room ” + roomID + “ is not assigned to any patient.”)     }     timestamp := time.Now().Format(time.RFC3339)     event := CleaningEvent{      RoomID:      roomID,      CleaningStaffID: staffID,      Date:          cleaningDate,      Operation:          “Routine Cleaning”,      Timestamp:       timestamp,     }     eventKey := “CLEANING_” + roomID + “_” + timestamp     eventBytes, _ := json.Marshal(event)     if err := APIstub.PutState(eventKey, eventBytes); err != nil {      return shim.Error(“Failed to record cleaning event.”)     }

// Update the room’s cleaning status     room.CleaningStatus = “Routine Cleaned”     room.LastCleaned = timestamp     updatedRoomBytes, _ := json.Marshal(room)     if err := APIstub.PutState(“ROOM”+roomID, updatedRoomBytes); err != nil {      return shim.Error(“Failed to update room status.”)     }

return shim.Success([]byte(“Routine cleaning for Room ” + roomID + “ is complete.”))

}

4.3. Ledger Level Representation

Although the proposed system includes multiple smart contract functions handling various aspects of healthcare workflows—such as patient registration, room occupancy management, and hygiene feedback logging—this section focuses on a representative function to demonstrate the blockchain-based data storage mechanism. The RoutineCleaning function was selected due to its relevance to hygiene traceability and its straightforward data model, making it ideal for illustrating how cleaning actions are recorded and queried within the distributed ledger.

Upon successful execution of this function, a new cleaning record is immutably written to the world state database, which is backed by CouchDB in this implementation. Each cleaning entry is uniquely identified using a composite key formed by the concatenation of the room identifier and the specified date. This design ensures both uniqueness and temporal traceability.

Figure 6 illustrates an actual cleaning event document stored in the CouchDB database. In this example, the event was recorded by a staff member named Semra for Room R101 on 14 May 2025. The chaincode appends a system-generated timestamp at the moment of execution, thereby enabling verifiable chronological ordering of cleaning events.

4.4. Performance Evaluation

To assess the performance of the proposed blockchain-based hygiene monitoring system, a set of benchmarking tests were conducted using Hyperledger Caliper on the deployed multi-organization Hyperledger Fabric network. The RoutineCleaning smart contract function was invoked under controlled conditions with a target of 1500 successful transactions submitted at a rate of approximately 178.8 transactions per second (TPS). The performance metrics obtained from the benchmark are summarized in

Table 3. Summary of key performance metrics recorded during benchmark execution using Hyperledger Caliper.

Metric	Value	Description
Successful Transactions	1500	Total number of transactions successfully committed to the ledger.
Failed Transactions	0	Number of transactions that failed during submission or endorsement.
Submission Rate	178.8 TPS	Transactions submitted per second.
Maximum Latency	7.80 s	Highest delay observed in processing a transaction.
Minimum Latency	1.67 s	Lowest delay observed in processing a transaction.
Average Latency	5.55 s	Mean delay across all transactions.
Throughput	114.27 TPS	Number of transactions successfully processed per second.
Latency/TPS Ratio	~0.0486 s/TPS	Efficiency indicator combining latency and throughput.

, which presents throughput, latency, and transaction success rates.

All 1500 transactions were successfully processed, with no recorded failures. The network achieved a maximum throughput of 114.27 TPS, indicating the system’s capacity to sustain high transaction volumes under optimal conditions. Latency measurements ranged from a minimum of 1.67 s to a maximum of 7.80 s, with an average latency of 5.55 s per transaction. These results indicate a balanced system capable of handling routine events with reasonable responsiveness and without overload.

In addition to performance outcomes, detailed system-level resource utilization data was collected to analyze the impact of various components on the network’s behavior.

Table 4. Resource consumption across Fabric components during the Routine Cleaning benchmark test.

Component	CPU% (Max)	Memory (Max MB)	Disk Write (MB)
/peer0.org1.example.com	8.10	174	5.07
/couchdb0	13.02	64.9	1.51
/orderer2.example.com	2.05	67.6	11.5
/dev-peer0.org1.example.com-performance	3.89	75.2	0

shows the resource utilization details of key Hyperledger Fabric components during benchmarking, highlighting performance bottlenecks.

Notably, /peer0.org1.example.com exhibited the highest CPU load (8.10%) and memory consumption (174 MB), confirming its role as the primary endorser during the test. Similarly, /couchdb0—used as the world state database for Org1—recorded the highest CPU usage (13.02%) among CouchDB containers, reflecting intense read/write operations during transaction commits. Ordering nodes also showed moderate but consistent disk writes, particularly /orderer2.example.com, which recorded 11.5 MB of disk write, indicating its active participation in block generation and propagation. These observations suggest that system performance is primarily influenced by endorsement policies, peer workload distribution, and CouchDB efficiency. The bottlenecks identified here can be addressed in future iterations by adjusting endorsement strategies or horizontally scaling database components.

Taken together, these results suggest that the proposed system can reliably handle sanitation event workloads with high success rates and acceptable latency. Notably, the benchmarking tests were conducted on modest hardware configurations, where all virtual machines operated with 8 GB RAM and 2 vCPUs. Despite these limited resources, the system consistently achieved over 100 TPS throughput with zero transaction failures, demonstrating both operational efficiency and resource-conscious scalability. Minor bottlenecks were observed in endorsement and database operations; however, these did not compromise transaction integrity or responsiveness. These results confirm the system’s practical viability for real-world healthcare scenarios and suggest that further optimization—such as peer load balancing or database tuning—could enhance performance even on lightweight cloud environments.

4.5. Security Considerations

Ensuring the security of healthcare data is critical in blockchain-based hygiene and quality management systems. Although Hyperledger Fabric offers a permissioned architecture that restricts network participation through the Membership Service Provider (MSP), X.509 certificates, and TLS encryption, these features alone do not guarantee protection against all potential attack vectors [36,37].

Vulnerabilities can arise from misconfigured endorsement policies, chaincode design flaws, or malicious peer behavior. For instance, an attacker could exploit poorly validated chaincode to manipulate room status or cleaning records [37]. Moreover, a lack of fine-grained access control can lead to unauthorized users executing sensitive operations, jeopardizing data confidentiality and process integrity [36,38].

To mitigate these risks, robust security practices must be integrated at the application level. This includes secure chaincode development, rigorous testing before deployment, and continuous monitoring of peer behavior. Furthermore, best practices such as endorsement policy hardening, attribute-based access control (ABAC), and audit logging at the transaction level enhance resilience against both insider threats and external attacks [38,39].

5. Conclusions

In this article, a Hyperledger Fabric–based blockchain architecture is proposed to effectively manage cleaning and hygiene processes in hospital rooms. This approach aims to enhance transparency and reliability in healthcare services by integrating digital technologies, particularly the Internet of Things (IoT), for secure monitoring of cleaning activities. The study emphasizes that incorporating such methods into healthcare cleaning and hygiene protocols can significantly improve the efficiency of monitoring and maintenance processes. Additionally, the system establishes a reliable and transparent quality control mechanism, digitally recording cleaning tasks to create a structured database and ensuring the consistent maintenance of hygiene standards.

The proposed system manages routine, detailed, and on-demand cleaning activities in separate categories, enabling more effective oversight of these processes. Additionally, cleaning operations are carried out within a quality assurance framework thanks to the immutable record structure provided by blockchain technology. As explained in Section 3.2, Hyperledger Fabric’s permissioned blockchain architecture offers a more reliable alternative than traditional data management systems used in the healthcare sector, as it protects patient information and operational data privacy. The blockchain system also supports regulatory compliance and auditability through immutable logs and decentralized verification mechanisms.

The potential benefits of the proposed system for the healthcare sector include increased operational efficiency, minimized infection risks, and improved healthcare service quality. In the future, the use of blockchain-based quality assurance systems in healthcare cleaning processes can be expanded by developing large-scale applicability and user-friendly solutions. In addition, detailed studies on the cost-effectiveness of technological integrations and their effects on user experience will support the widespread adoption of the system.

In support of the proposed model, the system was successfully implemented and tested on a multi-organization Hyperledger Fabric network using modest hardware configurations (8 GB RAM, 2vCPUs per node). The real-time recording of sanitation events via smart contracts was verified through performance benchmarking with Hyperledger Caliper, during which the system sustained over 100 transactions per second without any failures. These results confirm both the technical feasibility and the practical scalability of the architecture for real-world healthcare deployments, even under resource-constrained environments. Furthermore, attribute-based access control (ABAC) was incorporated at the smart contract level to enforce fine-grained, role-specific access policies during the execution of cleaning operations, thereby reinforcing the system’s integrity and auditability.

Despite these advantages, certain challenges must also be considered. The deployment and maintenance costs of permissioned blockchain networks, such as Hyperledger Fabric, can be a significant factor, particularly in large-scale implementations. Moreover, ensuring full compliance with data privacy regulations, such as GDPR and HIPAA (Health Insurance Portability and Accountability Act), presents a technical challenge due to the immutable nature of blockchain records. Addressing these challenges requires further research in areas such as scalability optimization, hybrid data management models, and AI-driven compliance mechanisms.

Future work will focus on expanding and evaluating the proposed system in broader healthcare settings. The architecture is planned to be integrated into multiple hospital environments to assess its applicability in inter-institutional scenarios. Additionally, edge computing solutions are envisioned to reduce latency in communication with IoT devices. To improve operational flexibility, the development and deployment of diverse chaincode scenarios are targeted. Moreover, the impact of the system on hygiene outcomes and patient safety will be evaluated using patient satisfaction surveys, contributing to the continuous improvement of cleaning protocols. These research directions are expected to further validate and extend the architectural robustness, scalability, and patient-centered applicability of the proposed blockchain-based solution in healthcare environments.