Current management systems prioritize quality-driven healthcare and the suppression or mitigation of unsafe practices. In this respect, the World Health Organization1 has proposed a series of validation procedures to determine the appropriateness of specific healthcare processes. These procedures comprise a series of techniques aimed at finding documentary evidence that the results of a given process consistently comply with the predetermined specifications and the required quality standards.

Drug administration is undoubtedly one of the most important and complex processes that take place in any health center. However, it is often forgotten that before reaching the patient's bedside, the drug goes through a lengthy circuit that often involves more or less sophisticated manipulation. Guaranteeing the safety of the personnel handling those medications, especially when such medications are hazardous drugs (HDs), is a key concern for any hospital2.

It must be taken into consideration that healthcare providers may be exposed to risks related to drug manipulation both within the hospital and at the patients’ homes, where conditions tend to be poorly controlled and direct supervision nonexistent3.

Clinical guidelines and recommendations have been produced to minimize the incidence of errors involved in drug handling in those environments. A well-defined protocol goes a long way in ensuring the theoretical feasibility, quality, and safety of the process for which it has been designed. The factor that determines whether the desired goals can be achieved is adherence by the healthcare providers to such protocols when performing the various steps of the drug handling process.

In these high-risk contexts it is essential to ensure that all pre-established protocols are followed during drug handling and that the expected results are achieved. To do this, certain points of time and/or events, known as control points (CPs), must be defined at which the actions carried out must (should) be monitored. CPs allow verification of the requirements established.

Now, not all CPs are equally critical. For every hazardous process there will be CPs that require specific monitoring; these are known as critical control points (CCPs)4. Both CPs and CCPs are used as a basis to generate data records containing information on the monitoring exercise. Such data records, known as traces, allow for an explicit statement to be made about the states and/or interactions between the different elements involved in the various processes carried out. A thorough and complete log of traces makes it possible to trace the history, usage, and location of an entity. This ability is known as traceability.

It is essential to ensure that all operations are performed in the expected manner and to take the steps required to carry out an exhaustive assessment of the HD process. However, current monitoring systems tend to be retrospective and, although they are capable of identifying potential errors, i.e., potential areas for improvement, they are unable to avoid deficiencies in the follow-up process5.

The availability of rapid-response systems that allow avoidance, or at least prevention, of potential risks associated to HDs would significantly contribute to bolstering healthcare providers’ safety. In this regard, this project proposes introducing Semantic Web and Big Data technologies which, through the implementation of tools capable of processing large amounts of data within a short period of time, may produce patterns that could guide decision-making.

Although the clinical significance of the risks associated with continuous exposure of low levels of HDs has not been firmly established, enough signs exist indicating that such an exposure may result in long-term adverse events warranting the adoption of prevention measures. A better understanding and an evaluation of the risks inherent in the HD handling process could contribute to minimizing the hazards associated with these drugs.

The purpose of this study is to describe a study protocol aimed at developing and implementing an integrated Big Data-based IT risk analysis system capable of monitoring/verifying the HP handling process, which allows continuous and dynamic quality and traceability control of HDs by hospitalat-home units (HHUs).

The controls and techniques developed on the basis of this study will be applied to the chemical risks associated to the storage, transport, administration and management of HD residues by the pharmacy departments and HHUs of the two participating (third-level) hospitals.

A standardized graphical modeling tool called Business Process Model Notation will be used to design processes based on the previously implemented methodology5, which will allow representation of the different phases in one single workflow.

The study cohort will be made of the HDs included in the List of Hazardous Drugs of the National Institute for Occupational Safety and Health6.

Using a general flowchart (Figure 1) as a basis, specific flowcharts will be designed by an expert group with details of the different stages of the process and the operations they comprise. The stages of the process were obtained from the systematic review carried out by Bernabeu et al.7 Consensus among the experts will be obtained through the nominal group technique and a series of documentary techniques. This combined method will comprise two face-to-face rounds (meeting of participants and approval of proposals) and three masked rounds (individualized review).

Figure 1.

Flowchart of the general process of hazardous drugs (HDs) management.

(0,12MB).

Standardized hazard identification techniques will be used to create a dashboard that will allow detection of significant hazards and application of appropriate control measures to prevent or mitigate risks.

Sequencing of decisions geared towards identifying CCPs will be carried out in accordance with the Recommended International Code of Practice: General Principles of Food Hygiene (CAC/RCP 1-1969, Rev. 5-2020)8.

The variables considered for characterizing each hazard will be as follows: [1] existence of a hazard; [2] incorporation and contamination; [3] inception or escalation of the hazard; and [4] persistence of the hazard (continuity).

The variables for managing the process will be: [1] stage; [2] likelihood of occurrence (L); [3] severity of the damage (S); [4] criticality index (CI): L x S; [5] Steps of the decision tree: S1, S2, S3 and S4; [6] CP; [7] CCP; [8] Control measure.

Each hazard identified will be evaluated using the criteria established in the IFS Global Markets HPC program9.

The criticality index (CI) is the value obtained by multiplying the likelihood of occurrence of an undesired event by the severity of its potential consequences (CI = L x S).

Calculation of the CI helps determine which points will be CPs and which must be subject to sequencing of decision-making to decide whether they constitute CCPs and, if appropriate, establish a control protocol to address any potential hazards.

Initial quantification of the L and S of undesired events and their potential consequences to determine the CI of each stage in the process is carried out by consensus among the experts (nominal group and documentary techniques). These will be healthcare providers (physicians, nurses, and pharmacists) adept at managing HDs as a result of either their work experience (at a hospital, healthcare center or HHU) or because of their technical expertise in the area. Recruitment of such experts will be carried out with the assistance of the Spanish Group for the Development of Hospital Pharmacy (GEDEFO), the Spanish Society of Hospital Pharmacists (SEFH), the Management and Quality Working Group of the Spanish Hospital at Home Society (SEHAD), and occupational hazard and preventive medicine practitioners from the Spanish School of Occupational Medicine (ENMT).

A digital Hazard Analysis and Critical Control Points (HACCP) system will be generated to capture all relevant data (all the models proposed for the analysis of risks and their traceability will also have been tested in the hospital setting)10-11. A series of client software agents will be used to this effect which can be executed on adapted devices (tablets and smartphones) to centralize all the data in a common data server.

After this first phase, all data will be processed using data analytics techniques. The Big Data analysis will be carried out using mathematical models that allow monitorization of both CPs and CCPs. These models will be applied to the data stored in the project's server and will allow real-time determination of the values corresponding to each specific parameter.

Management, implementation, and piloting data will be collected using Android-supported next-generation optical scanning devices (tablets or smartphones) and stored in a repository located in the project's server.

Documentary and technological support data will be generated following the development of the HACCP system.

Events will be registered on the basis of a formalized knowledge model in accordance with the standards laid out in the Semantic Web (the SPARQL language that allows operations for the maintenance, creation, erasure and modification of data). In addition, a cross-domain ontology will be constructed that will be supplemented by an upper layer dedicated to HD modeling. This information will be stored in a Linked Open Data (LOD) repository overlaid with a SPARQL endpoint. This technology facilitates flowchart design and makes it possible for such flowcharts to be shared across different environments and users.

Once the system has been designed, it will be subjected to a verification process that will encompass all documents generated and all techniques implemented.

Tests will include local emulations for the different areas of interest. This will require a series of tests/retests aimed at detecting potential errors or conflicting situations in the different contexts and control processes across the whole HD lifecycle11. This will allow monitoring the interval validity of the process.

The HD control system will be independently verified at each participating hospital. Once the appropriateness of the whole system is ascertained, a validity period will be established, together with review and verification milestones (external validity).

The HACCP system will be compatible with any surveillance measures that the prevention services of participating hospitals may decide to enforce.

The project proposed is only based on the monitoring of the HD-related phases, without any consideration of the patients’ personal data. At any event, the confidentiality of the participating healthcare providers’ data will be guaranteed in accordance with the stipulations of the 1975 Helsinki Declaration and its subsequent amendments.

The project was approved by the Research Ethics Committee of the Alicante General University Hospital (Ref. CEIC PI2017/93).

The research team have invaluable experience of designing and implementing platforms such as the one described in this study11,17. At the same time, previous studies have demonstrated that low-cost easy-to-use mobile applications such as the one proposed in this study enjoy wide acceptance on account of their adaptability and beneficial application to clinical practice18.

Moreover, the exhaustive review made in this study of all the different stages in the process and the multicenter nature of the analysis will allow application of the tool to other centers in the future.

The limitations of this study are related to the unavailability of reference levels for all HDs (critical limits), which would make it possible to easily reduce exposure to HDs, which is the ultimate goal of the HACCP system. Having said this, the risk reduction achieved by controlling the quality and traceability of the handling process, and the access obtained to updated information on potential non-conformities ensures a better control of the stages that could pose the greatest hazards, thereby helping to (indirectly) minimize potential exposure.

The foregoing indicates that HDs should be integrated within a standardized management system that promotes the safety of both patients and healthcare providers, optimizes resource utilization, and minimizes procedural issues, guaranteeing the quality, traceability, and safety of HD handling in HHUs.