ISO Standards in Healthcare Organizations: Research Evolution and Trends from a Bibliometric Analysis

Abstract

This study provides an overview of trends and evolution in International Organization for Standardization (ISO) implementation in healthcare over the past three decades, useful for researchers, practitioners, and policymakers in the sector. As an additional contribution, we propose the NU-index, which allows the evaluation of authors’ scientific output in a comprehensive way that will be valuable for researchers, institutions, and funding agencies seeking to assess researcher performance more accurately and understandably. A bibliometric analysis of 476 scientific articles from the Scopus Database was conducted, examining the scientific output, key authors, high-impact journals, and frequent keywords using VOSviewer, Bibliometrix library, and statistical analysis. Results reveal a significant increase in publications on ISO standards in healthcare since 2009, particularly in areas such as telemedicine, artificial intelligence, and information security. The emergence of ISO 11073 (health informatics) and ISO 13606 (electronic health records) highlights a growing trend towards information and communication technologies. Despite reported implementation barriers, such as lack of top management commitment and associated costs, adoption of these standards is increasing due to the demand for high-quality healthcare services and the need to comply with regulatory requirements.

1. Introduction

ISO standards have become increasingly important in healthcare organizations by establishing a comprehensive framework for process management and continuous improvement [1,2]. The implementation of ISO standards, such as ISO 9001 [3] and ISO 14001 [4], has been associated with increased patient satisfaction and safety, as well as improved profitability in healthcare settings. The ISO 9001 standard, centered on quality management, provides a framework for enhancing product and service quality, customer satisfaction, and operational efficiency. By establishing requirements for risk management, continuous improvement, and customer satisfaction, ISO 9001 can enable healthcare organizations to identify and mitigate issues, such as medical errors, process inefficiencies, and communication breakdowns. A systematic review [5] supports this assertion, concluding that the implementation of ISO 9001, in conjunction with the EFQM Model, positively impacts hospital performance. While the study does not elaborate on how the standard addresses specific problems, it suggests an overall enhancement in key areas such as quality of care, patient safety, and efficiency. ISO certifications have also been shown to lead to improvements in productivity and profitability in administrative areas within healthcare organizations [5]. The recent publication of ISO 7101 [6], specifically designed for quality management in healthcare, represents a significant advancement in this field, by providing a more precise and specialized framework for implementing quality standards in health organizations. Healthcare often faces challenges such as medical errors, inefficiency, lack of standardization, and low patient satisfaction, and it is in these areas that the implementation of ISO standards can have a positive impact on the quality of healthcare services [5].

Despite the established advantages, organizations may face various barriers in implementing ISO standards, such as a lack of top management commitment, an inadequate organizational culture, a lack of understanding and interpretation of the standard, the cost associated with implementation [7], and a lack of integration with existing systems [8].

The current trend reveals a growing adoption of ISO standards across diverse healthcare institutions, ranging from hospitals and clinics to laboratories and medical technology companies [5]. This is driven by the increasing demand for high-quality, safe, and efficient healthcare services, as well as the need to comply with regulatory requirements and meet patient expectations. Relevant ISO standards in the healthcare sector include:

• ISO 9001: Quality management [3].
• ISO 14971: Risk management in medical devices [9].
• ISO/IEC 27001: Information security [10].
• ISO 27799: Health information technology [11].
• ISO 13131: Telemedicine [12].
• ISO 13485: Medical devices [13].
• ISO 15189: Clinical laboratories [14].

While existing bibliometric studies have explored standardization in healthcare organizations and the adoption and implementation of ISO standards [15,16], their generalized approach does not facilitate a nuanced analysis of implementation and adoption processes within organizations, nor do they elucidate the most salient trends in research through a multitemporal lens. Furthermore, quantitative assessments of author productivity are typically presented in isolation, preventing a holistic analysis of productivity, acceptance, and impact—an aspect that the present study seeks to address.

This research aims to describe and analyze the evolution and current trends in the adoption of ISO standards in healthcare. Through a bibliometric analysis of relevant articles and a multitemporal analysis of research, scientific output over three decades was examined, identifying major themes and key findings. The results will provide valuable information for researchers, healthcare professionals, managers, and administrators of healthcare organizations to develop the policies and strategies around the identification of ISO standards to be implemented and to define promising areas of research that address the knowledge gaps established in the existing literature.

2. Materials and Methods

In this article, a bibliometric analysis, as a quantitative approach, is employed to analyze the development of standardization processes in health and healthcare institutions based on ISO standards [17,18,19]. The objective of a bibliometric study is to analyze scientific and technological output through the application of quantitative and statistical methods to scientific publications and other documents. This type of research can help identify research trends, assess the impact of publications and authors, and provide an overview of the development of a specific discipline [20,21].

The study encompasses the evolution of research and an analysis of historical events that have shaped research trends in the field over the years. Publications, authors, prominent collaboration indices, and future research landscapes are analyzed through computational analysis, utilizing mathematical tools focused on statistical and graphical descriptions. Additionally, the scientific output of authors and countries/regions is assessed. For data processing and result generation, the statistical packages R version 4.2.2 [22] and JASP version 0.18.3 [23,24] are utilized. In R, the Bibliometrix package version 4.1.3 [25] is employed. MS Excel for Mac version 16.87 is used for database debugging and cleaning, and VOSviewer version 1.6.20 for Mac [26,27] is utilized, with the support of standard text editors for term disambiguation in semantic co-occurrence maps.

2.1. Data Collection

Figure 1 illustrates the information search and filtering process. Initially, 1073 English-language articles were identified in the Scopus Database, with a data cutoff date of 27 May 2024. This database was selected due to its accessibility and the quality of information available [28]. Articles in fields such as biology, engineering, and pharmacology were excluded as they did not contribute to the analysis objectives. Articles directly related to healthcare organizations, such as those focusing on healthcare professionals, medicine, nursing, and related professions, were retained. Finally, the search keywords were reviewed to ensure that the terms used aligned with the research topic. The final analysis was conducted on 476 records. The search equation used was TITLE-ABS-KEY((“ISO” OR “international organization for standardization”) AND (“health*” OR “healthcare” OR “healthcare organization” OR “health organization”)) AND (LIMIT-TO(SUBJAREA, “MEDI”) OR LIMIT-TO(SUBJAREA, “HEAL”) OR LIMIT-TO(SUBJAREA, “NURS”) OR LIMIT-TO(SUBJAREA, “DENT”) OR LIMIT-TO(SUBJAREA, “PSYC”) OR LIMIT-TO(SUBJAREA, “NEUR”)).

In detail, the inclusion criteria were as follows:

• Study Types: Original research articles and systematic reviews that addressed the implementation, impact, or evaluation of ISO standards in healthcare organizations were included.
• Scope: Studies conducted in any type of healthcare organization were considered, including hospitals, clinics, laboratories, primary care centers, etc.
• Language: Articles published in English were included, as it is the predominant language in the scientific literature on ISO standards.

For the exclusion criteria, the following were analyzed:

• Study Types: Qualitative studies, editorials, letters to the editor, and opinion pieces were excluded, as they did not provide quantitative data for bibliometric analysis.
• Scope: Studies that did not focus on healthcare organizations were excluded, such as those addressing the implementation of ISO standards in other sectors.
• Language: Articles published in languages other than English were excluded.
• Title: Articles that did not directly address the implementation, impact, or evaluation of ISO standards in healthcare organizations were excluded, even if they mentioned the standards tangentially or if their title was outside the context of the study.

The final database covered a total of 29 years between 1995 and 2024. The entire period was included in the results, although for some calculations the year 2024 was excluded to avoid bias in the numerical analysis of certain indices.

2.2. Bibliometric Analysis

This research encompasses three types of analysis:

(a)

Research trends in the field: The evolution of research and historical events that have shaped research trends over the years were examined. Publications, authors, prominent collaboration indices, and future research landscapes were analyzed through computational analysis, utilizing mathematical tools focused on statistical and graphical descriptions.

(b)

Productivity of sources, authors, and countries/regions: The scientific output of authors and countries/regions was assessed, considering metrics such as the number of articles, relative production, influence and prestige indices for journals, bibliometric laws, author acceptance, and influence. Author productivity is assessed using various indices, introducing a modification of the Unity index (U-index) proposed by [29], based on a statistical normalization process. Additionally, collaboration and production bases are established to analyze regional productivity.

(c)

Keyword analysis: Keywords are analyzed using semantic and cluster maps to interpret relationships within scientific production, analyze research trends, and explore future research and application perspectives.

2.3. Data Cleaning

This study analyzed the bibliometric results from a single database, as detailed in Section 2.1, resulting in a single, unique dataset. This ensured the absence of duplicate results in the final database. For the author and affiliation normalization process, while the bibliometric package offers tools for normalization using various techniques [25], this study employed a manual approach, corroborating data with author profiles on Google Scholar.

Regarding disambiguation in the generation of semantic maps and trending topics, text files in the .txt format were generated for both tools used, Bibliometrix and VOSviewer. Each tool has a different disambiguation format, as detailed in Figure 2. For Bibliometrix, the disambiguation file has no header and is a plain text file with semicolon-delimited terms (orange legend in Figure 2). The initial column contains the term that will be displayed in the semantic map (green legend in Figure 2), and the second column, after the semicolon, contains the original term (red legend in Figure 2). In the provided example, all variations of “ehr” (electronic health record), including singular and plural forms, were merged into a single term (see Figure 2a).

The disambiguation process in VOSviewer requires a file with a header containing the labels “Label” and “Replace by”, separated by a tab delimiter (orange legend in Figure 2), which is the same delimiter used for the terms. The original term is listed in the first column (red legend in Figure 2), and the term that appears in the maps is listed in the second column, after the delimiter (green legend in Figure 2). It is important to note that there cannot be any spaces or tabs after the second term, as this will result in an error. Additionally, in VOSviewer, to remove a term from the map, the term can be listed in the first column with the delimiter on a separate line. In the example, this was performed with the terms “article” and “review” (see Figure 2b).

3. Results and Discussion

3.1. Publications by Year

Figure 3a illustrates the temporal distribution of scientific publications on the topic of interest (blue series: annual production, orange series: cumulative production), over 29 years from 1995 to 2023. A notable increase in scientific productivity was observed from 2009, sustained until 2014, with a total of 172 articles representing 36.1% of the total selected records ($n=476$). This period of high productivity contrasts with the period before 2009, where publications accounted for 17.4%, which indicates an incremental trend during that time. Between 2015 and 2021, a deceleration in scientific production of 4.6 percentage points is evident compared to the peak period. Following this decline, there was an increase in the rate of scientific production in 2022 and 2023, with 38 publications recorded in the latter year, the highest number in the entire analyzed period. The publication growth rate is 11.09% (calculated using the Biblioshiny tool from the Bibliometrix package in R), excluding 2024 only for this result to avoid bias. As of the date of this study, seven documents for 2024 were reported from the Scopus Database. Figure 3b analyzes the linear growth trend of the research, supported by Kendall’s correlation test, with the hypothesis of a positive growth rate (p < 0.001) at high significance (see

Table 1. Kendall’s Tau Correlations.

	Kendall’s Tau B	p-Value
Articles—Year	0.607	<0.001 ***

).

3.2. Comprehensive Analysis of Scientific Production: Journals, Authors, and Countries/Regions

3.2.1. Distribution of Publications by Journal

Table 2. Scientific Production with the top 10 most productive sources.

Journal Name	Articles	%	SJR 1	Country	FP 2 to LP 3
Studies in Health Technology and Informatics	53	11.13%	Q3	The Netherlands	2015–2023
International Journal of Medical Informatics	13	2.73%	Q1	Ireland	1998–2023
Journal of Biomedical Informatics	10	2.10%	Q1	USA	2010–2021
Journal of Medical Systems	10	2.10%	Q1	USA	2010–2016
BMC Medical Informatics and Decision Making	7	1.47%	Q1	UK	2008–2020
Healthcare Informatics Research	7	1.47%	Q1	Republic of Korea	2010–2018
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS	6	1.26%	Q3	Different countries	2011–2020
Revista de Calidad Asistencial	5	1.05%	Q4 4	Spain	2003–2017
Health Informatics Journal	4	0.84%	Q2	UK	1998–2016
International Journal for Quality in Health Care	4	0.84%	Q2	Different countries	2000–2018
Other Journals	357	75.00%	*	Different countries	1995–2024

¹ Scimago Journal Rank. ² First publication. ³ Last publication. ⁴ Until 2018 it was indexed in SJR, after 2019 it is no longer indexed. * Not applicable.

presents the 10 journals with the highest production in the analyzed database, for the study of ISO standardization trends in health and healthcare organizations. In this analysis, it is important to note that eight of the 10 most productive journals are in the areas of informatics and technology, primarily with publications from the last decade. The last row of Table 2 shows the number of articles published by the remaining journals and the percentage they represent in productivity.

Table 2 reveals that the journal Studies in Health Technology and Informatics accounts for 11.13% of all articles in the database, making it the most prolific journal in terms of publication over an eight-year window to date. A significant number of journals are ranked in the highest quartile of the SJR (Scimago Journal Rank) index, and there is a wide geographical diversity (the Netherlands, Ireland, USA, UK, Republic of Korea, and Spain), suggesting a global interest in the topic. The publication period, spanning from 1995 to 2024, indicates a continuous and evolving research trajectory. These findings highlight the need to consolidate scientific production in specialized, high-impact journals to strengthen the visibility and recognition of research in this field.

3.2.2. Author Productivity

An author’s productivity is measured by the number of articles in which the researcher is a coauthor, while acceptance and impact are measured by the number of times the author is cited (number of citations) and their Hirsch index (H-index), respectively [18,30]. Other aspects that can assess a researcher’s scientific output are collaboration indices and less widespread indices, such as the G index [31], or the Q factor proposed as a comparator of researchers’ curricula [32].

Table 3. Summary of the most productive authors in the studied field.

Authors	Articles *	TTC 1	H-index *	G-index	FP 2 to LP 3	Institution	Country
Luis Serrano	11	124	5	11	2007–2016	Public University of Navarre	Spain
Javier Escayola	10	69	5	8	2007–2013	University of Zaragoza	Spain
Dipak Kalra	9	93	6	9	2008–2023	University College London	UK
José García	9	80	5	8	2007–2016	University of Zaragoza	Spain
Miguel Martínez-Espronceda	8	62	5	7	2007–2013	Public University of Navarre	Spain
Jesús Daniel Trigo	7	70	5	7	2009–2016	University of Zaragoza	Spain
Santiago Led	7	46	4	6	2007–2013	Public University of Navarre	Spain
Ignacio Martínez	7	44	4	6	2007–2013	University of Zaragoza	Spain
Jesualdo Tomás Fernández-Breis	5	188	5	5	2009–2012	University of Murcia	Spain
Bernd Blobel	5	96	3	5	2006–2022	University of Regensburg	Germany

¹ Time total citations. ² First publication. ³ Last publication. * Both the number of articles and the H-index have been calculated on the local database, i.e., the articles downloaded for this study.

summarizes the 10 authors with the highest number of published articles (productivity index) in the analyzed database, as well as the number of times they have been cited globally (acceptance), their institutional affiliation, country of origin, H-index, and G-index (impact of the publications). This summary also illustrates the time window between the first publication (FP) and the last publication (LP) to analyze the author’s period of activity in the specific area of standardization processes in healthcare organizations. This allows us to identify which authors are still active in this research area and their study approaches.

Table 3 reveals that the most productive authors are Luis Serrano (11 articles, 124 citations, H-index = 5), Javier Escayola (10 articles, 69 citations, H-index = 5), and Dipak Kalra (9 articles, 93 citations, H-index = 6), who has the highest impact index among the top 10 most productive authors. Spain is the most represented country, with eight authors in total. Other countries/regions with relevant authors in this area are the UK and Germany (Bernd Blobel, 5 articles, 96 citations, H-index = 3). The publication period of the included articles is mainly concentrated between 2007 and 2013, coinciding with the period of highest scientific production observed in Figure 3a (publications per year). It is also important to note that the indices of productivity, acceptance, and impact are not necessarily consistent, and there is no direct correlation implied between them.

Figure 4 summarizes the information of the 10 most productive authors and their local citations (citations received by an author’s articles per year within the analyzed database, excluding citations from documents outside this database).

Figure 4 suggests that Kalra and Blobel have continued in the period under review in the field, both with acceptance in the scientific community measured from the citations of their articles. Other authors who also show acceptability are Serrano and Fernández-Breis. Kalra primarily focuses on electronic health records (EHRs) and personal health records, examining their implementation and benefits for organizations and patients, with a focus on ISO 13606 standardization [33,34,35,36]. Additionally, this author emphasizes the standardization of information in EHRs through archetypes and semantic interoperability [37,38]. An archetype is defined as a reusable template that establishes the structure, content, and constraints of a particular type of clinical information, acting as a model for representing and sharing clinical data. Semantic interoperability refers to the ability of different health information systems to exchange and interpret information in a meaningful way. Blobel, on the other hand, highlights the importance of semantic interoperability in healthcare systems and proposes methodologies to transform medical ontologies into CTS2 (Clinical Terminology Service Revision 2) terminology resources, facilitating the exchange and understanding of medical data. He also offers insights into the challenges and solutions in designing and managing personalized health ecosystems, emphasizing the need for an interdisciplinary and ontology-based approach to effectively represent and manage medical knowledge [39,40].

The research focus of Serrano et al. in their most cited papers centered on the exchange of medical information [41,42]. In [41], they presented an e-health solution based on the ISO/IEEE 11073 standard for medical device interoperability and EN13606 for the exchange of electronic health records. In [42], they evaluated the security of the ISO/IEEE 11073 standard for personal health devices (X73PHD) and proposed an extension based on the Integrating the Healthcare Enterprise (IHE) initiative to enhance the security and interoperability of personal health devices with healthcare systems. Both studies concluded that standardization is crucial for ensuring interoperability, security, and privacy in the exchange of medical information, which in turn improves patient care and the efficiency of healthcare systems.

Fernandez-Breis et al., in their most accepted papers, addressed the standardization of electronic health records (EHRs) to achieve semantic interoperability, the ability of information systems to exchange and understand clinical information regardless of the system in which it was created [43,44]. They focused on standards based on dual-model architecture (ISO 13606 and openEHR), which define information and knowledge separately.

3.2.3. Most Cited Publications

Table 4. Top 10 documents with the highest citations reported by Scopus Database.

Research Title	Year	TC 2	LC 1	Research Objective
External quality mechanisms for health care: summary of the ExPeRT project on visitatie, accreditation, EFQM, and ISO assessment in European Union countries [45]	2000	130	3	To summarize the operation, findings, and conclusions of a European Union project on external peer review techniques, called “ExPeRT”, to investigate the scope, mechanisms, and use of external quality mechanisms in improving health care.
Detailed clinical models: A review [46]	2010	100	6	Review the Detailed Clinical Models (DCM) for standardization of data elements in the context of the increased use of electronic patient records and other health information technologies.
Applying the ISO/IEEE 11073 Standards to Wearable Home Health Monitoring Systems [47]	2005	97	3	Investigate the feasibility of applying the ISO/IEEE 11073 (also known as X73) standards, originally intended for in-hospital monitoring, to portable multi-sensor monitoring systems designed for home care.
The effect of certification and accreditation on quality management in 4 clinical services in 73 European hospitals [48]	2014	76	5	To investigate the relationship between ISO 9001 certification, healthcare accreditation, and quality management in European hospitals.
An approach for the semantic interoperability of ISO EN 13606 and OpenEHR archetypes [44]	2010	75	6	Address the semantic interoperability of electronic health record (EHR) standards based on the dual-model architecture, namely OpenEHR and ISO EN 13606.
External inspection of compliance with standards for improved healthcare outcomes [49]	2016	60	2	To assess the effectiveness of external inspection of compliance with standards in improving the performance of healthcare organizations, the behavior of healthcare professionals, and patient outcomes.
Advanced and secure architectural EHR approaches [50]	2006	52	4	Discuss electronic health record (EHR) architecture for scalable, flexible, portable, and secure systems, and the need for it to be based on the component and model paradigm, separating platform-independent and platform-specific models.
The ISO/IEC 11179 norm for metadata registries: Does it cover healthcare standards in empirical research? [51]	2013	30	2	Assess the competence of ISO/IEC 11179 “Information technology—Metadata records (MDR)” part 3 edition 3 Final Draft of the Committee “Metamodel of record and basic attributes” to represent health standards.
Home healthcare settop-box for Senior Chronic Care using ISO/IEEE 11073 PHD standard [52]	2010	28	3	Propose a home healthcare decoder that uses the ISO/IEEE 11073 PHD standard to collect health data and provide chronic care service based on the collected data.
Detailed clinical models: representing knowledge, data and semantics in healthcare information technology [53]	2014	20	3	To present an overview of the development effort to harmonize clinical knowledge modeling using Detailed Clinical Models (DCM) and explain how it can contribute to the preservation of Electronic Health Record (EHR) data.

¹ Time total citations (citations that the document has had reported by Scopus throughout its database). ² Time local citations (citations that the document has had in the analyzed database that covers the 476 local documents minus the analyzed document).

summarizes the ten most cited documents in the analyzed database that address ISO standardization in healthcare organizations. They primarily focus on ISO 9001 certification and the 11073 and ISO/TS 13972 standards, exploring their implementation and impact on quality of care, data interoperability, and health information management.

Studies [48,54] examined the relationship between ISO 9001 certification and quality management and outcomes in hospitals. Reference [48] found a positive association between ISO 9001 certification and measures of clinical leadership, patient safety systems, and clinical review, but not with evidence-based clinical practice. Reference [49] revealed that it is unclear whether the standard compliance inspection programs, including ISO certification, improve professional practice and health outcomes.

The ISO/IEEE 11073 and ISO/TS 13972 standards focus on medical device interoperability and clinical information modeling, respectively. Reference [47] investigated the feasibility of applying the 11073 standards to portable home monitoring systems, successfully demonstrating its applicability with minor modifications. Lim et al. [52] proposed a decoder for chronic home care utilizing the 11073 PHD standard, highlighting its interoperability and ease of use. Additionally, references [46,53] delved into clinical knowledge modeling using DCMs (ISO/TS 13972), emphasizing their role in data preservation and semantic interoperability in health information technology.

Additional research investigated semantic interoperability between the OpenEHR and ISO EN 13606 EHR standards, both based on the 13606 standard, using semantic web technologies and model-driven engineering [44]. In [51], the authors assessed the ability of the ISO/IEC 11179 standard to represent healthcare standards, finding that while it is robust for metadata registries, limitations exist that need to be addressed in its future development.

Blobel discussed architectural principles for EHR systems, including the need for component-based models and the separation of platform-independent and platform-specific models to achieve scalable, flexible, portable, and secure EHR systems. The author emphasized the importance of component-based architectures and model-driven engineering for creating such systems. This approach, along with the adoption of standards like HL7 v3 and the SAIF interoperability framework, could enhance semantic interoperability and data management in healthcare settings. Furthermore, the use of semantic web technologies and model-driven engineering, as explored in Martínez-Costa et al. (2010), offers a promising approach to achieving semantic interoperability between different EHR standards [44].

Furthermore, the development of tools for the creation, modeling, and governance of DCMs, as mentioned in Goossen et al., could expedite the implementation and adoption of ISO standards in clinical practice [46]. Research in this area could explore how these tools can be integrated into existing clinical workflows and how they can be utilized to enhance data quality and security.

Overall, Table 4 demonstrates a trend toward research on how ISO standards can improve the quality of care, interoperability, and data management in healthcare organizations. Future research areas could include the evaluation and continuous improvement of ISO standards to address the specific needs of healthcare, the effectiveness of DCM development and implementation in various healthcare settings, and the development of tools and platforms that automate the transformation of archetypes and data between standards, facilitating the exchange and reuse of clinical information.

The research horizon in information technologies for ISO standardization in healthcare is broad and promising. The integration of these technologies into existing healthcare systems and processes has the potential to significantly improve the quality of care, efficiency, and patient safety while presenting significant challenges in terms of patient and data security and privacy.

Table 5. Top 10 documents with more than 1 citation per year on average in the last 10 years (2014–2024) reported by Scopus Database.

Research Title	Year	Research Objective
Metadata repository for improved data sharing and reuse based on HL7 FHIR [55]	2017	The objective of this work is to present a metadata repository developed through the interaction with a FHIR server that utilizes HL7 FHIR resources as both input and output format, with the aim of improving the management of clinical studies and facilitating the exchange of data elements by combining a metadata repository with FHIR.
Risk analysis in healthcare organizations: Methodological framework and critical variables [56]	2021	The objective of this paper is to provide an overview of the critical variables, advantages, disadvantages, strengths, and weaknesses of the risk assessment matrix tool, in accordance with the ISO 31000 risk management framework.
Challenges and solutions for designing and managing pHealth ecosystems [39]	2019	This article aims to present the requirements and solutions for designing and implementing advanced personalized health (pHealth) ecosystems, correctly adopting and integrating existing pHealth interoperability standards, specifications, and projects.
Environmental sustainability in European public healthcare: Could it just be a matter of leadership? [57]	2016	The objective of this paper is to broaden the debate concerning the influence of leadership on the implementation of environmental sustainability in European public healthcare organizations.
Evaluation of nursing information systems: Application of usability aspects in the development of systems [58]	2017	The objective of this study is to evaluate the usability of nursing information systems (NIS) from the perspective of nurses.
The effect of ISO 9001 and the EFQM model on improving hospital performance: A systematic review [5]	2015	The aim of this systematic review was to examine the literature concerning the effects of the ISO 9001 standard and the EFQM model on improving hospital performance.
Obtaining EHR-derived datasets for COVID-19 research within a short time: a flexible methodology based on Detailed Clinical Models [59]	2021	The aim of this study was to design and implement a flexible methodology based on detailed clinical models (DCMs) that would enable the effective reuse of electronic health records (EHRs) generated in a tertiary hospital for secondary uses in COVID-19, without loss of meaning and within a short time frame.
Analysis of ISO/IEEE 11073 built-in security and its potential IHE-based extensibility [42]	2016	The main objective of this work is to enhance the X73PHD standard by incorporating the most suitable IHE profiles, creating a flexible structure that offers features tailored to the needs of each eHealth/mHealth application.
Lessons learned in detailed clinical modeling at Intermountain Healthcare [60]	2014	The objective of this article is to describe lessons learned from Intermountain Healthcare’s efforts in creating detailed clinical models (DCMs), offering guidelines and insights on subjective decisions that modelers frequently need to make when creating a DCM.
Quality-in-use characteristics for clinical decision support system assessment [61]	2021	The objective of this study is to propose a set of (sub)characteristics that should be considered when evaluating the quality-in-use of clinical decision support systems (CDSSs), based on the ISO/IEC 25010 standard and existing literature.

presents the publications with the highest number of citations in a recent period, considering that, from a bibliometric perspective, the number of citations a document receives is influenced by various factors, including its age. This can create a bias by suggesting that older articles are more accepted simply because they have accumulated more citations over time. Table 4 highlights those studies published in the last 10 years with a high number of citations. Table 5 includes the 10 documents published in the last decade (2014–2024) that have received at least one citation per year on average, but that are not among the top 10 most cited in the 30-year period analyzed.

In summary, the articles presented in Table 5 examine the convergence of technology and healthcare, with a particular emphasis on data quality, system interoperability, and the role of informatics in clinical decision-making. Several studies address the challenges and solutions inherent in the design and implementation of health information systems, underscoring the importance of usability, effective data management, and the integration of standards such as HL7 FHIR and ISO 13606. Additionally, methodologies for evaluating the quality of clinical decision support systems and managing risks within the healthcare setting are explored. Collectively, these works demonstrate a clear trend toward personalized and data-driven medicine, highlighting the need for a robust technological infrastructure and interdisciplinary collaboration to optimize patient care and medical research.

3.2.4. Assessing Author Productivity Using the Unity Index

The Unity Index (U-index) was recently developed to assess authors’ scientific production comprehensively [29]. The U-index combines the three most common measures in evaluating a researcher’s scientific output: productivity, measured by the number of articles; acceptance, measured by the number of citations; and impact, measured by the H-index. It is important to note that the U-index is designed as an indicator of author performance, where, counterintuitively, the author with the highest performance obtains the lowest U-index score (contrary to indices like H, G, or M). Figure 5a illustrates the ranking of the top 25 most productive authors in the analyzed database, organized in ascending order based on their U-index scores. Luis Serrano achieves the highest ranking with 1 point, while three authors share the lowest ranking with 23 points.

Figure 5b graphically illustrates how the U-index ranks authors based on their productivity (horizontal axis), acceptance (vertical axis), and H-index (represented by the size of the circle). In this sense, Luis Serrano achieves the best score due to having the highest number of publications with good citations and a significant H-index, followed by Dipak Kalra, who has the highest H-index but a lower number of publications and citations than Serrano. Researchers Menárguez-Tortosa and Fernández-Breis occupy the 3rd and 4th positions, respectively, with 3 points each. Despite having a lower number of publications compared to the previous two researchers, they achieved the highest levels of acceptance based on the citations received.

Considering the U-index results, it is noteworthy that authors like Escayola and García, who rank high in productivity (see Table 3), are displaced when applying the global index due to their lower acceptance and impact.

3.2.5. Normalized Unity Index Approach, the NU-Index

As previously mentioned, the authors of the U-index indicate that their analysis is counterintuitive, as it assigns the lowest score to the highest-ranking researcher within a group [29], contrary to traditional indices where a higher score indicates better researcher performance. Given this, in this research, we propose applying min-max normalization [62,63] to the U-index, so that its analysis becomes intuitive based on the following expression (1). This type of normalization, or feature scaling, is widely used in data analytics to transform indicators to a common scale within the range of 0–1. In expression (1), the value subtracted from one is called the min-max normalized value, and the subtraction process is performed to invert the scale.

$$N{U}_{rank}=1-{\displaystyle \frac{U_{rank}-\min \left(U\right)}{\max \left(U\right)-\min \left(U\right)}}$$

(1)

where

• $U\_rank$: is the U-index score assigned to an author.
• $\min \left(U\right)$: is the lowest score assigned to any of the authors in the whole group.
• $\max \left(U\right)$: is the maximum score assigned to any one of the authors of the whole group.

From Expression (1), the results illustrated in Figure 6 can be obtained. In this figure, authors are ranked by assigning a value of 1 to the author with the best index score (interpreted as 100% productivity within the group), and the score is reduced for other authors based on their global index. It is important to clarify that, in this example, the index is calculated only for the most productive authors to enhance the interpretability of the results. However, for a comprehensive analysis of the database, the index should be calculated for all authors.

3.2.6. Productivity of Countries/Regions

Table 6. Top 10 countries/regions with the highest production.

Country	Articles	SCP 1	MCP 2	%	MCP_Ratio 3	TC 4
USA	49	43	6	10.29%	12.24%	756
Germany	44	31	13	9.24%	29.54%	431
Spain	44	39	5	9.24%	11.36%	422
Italy	22	18	4	4.62%	18.18%	306
UK	15	10	5	3.15%	33.33%	267
France	12	10	2	2.52%	16.66%	116
The Netherlands	12	10	2	2.52%	16.66%	212
Korea	10	9	1	2.10%	10.00%	111
Norway	10	7	3	2.10%	30.00%	179
Turkey	10	10	0	2.10%	0.00%	140

¹ Single country publication. ² Multiple country publications. ³ Multiple country publication ratio. ⁴ Time citations.

summarizes the 10 countries/regions with the highest scientific production in the analyzed field over the last three decades, with the USA, Germany, and Spain leading with almost 30% of the total publications analyzed and the European continent leading in production. The MPC Ratio, as an index of collaboration between countries/regions, identifies the UK as the main collaborator, with five articles coauthored with other countries/regions out of a total of 15 published.

Analysis of international collaboration indices reveals that the main collaborations occur between Germany and the Netherlands with six articles, USA and Germany with seven, UK and Sweden and USA and Canada with six each, and France and the Netherlands with four articles. Figure 7a illustrates productivity, with the USA, Germany, and Spain leading, as summarized in Table 4. Figure 7b shows that the MCP_ratio is led by Finland (A = 1, MCP_ratio = 1), Saudi Arabia (A = 1, MCP_ratio = 1), Israel (A = 1, MCP_ratio = 1), Malta (A = 1, MCP_ratio = 1), Sweden (A = 7, MCP_ratio = 0.571), Switzerland (A = 2, MCP_ratio = 0.5), Australia (A = 6, MCP_ratio = 0.5), Malaysia (A = 2, MCP_ratio = 0.5), and New Zealand (A = 2, MCP_ratio = 0.5). Overall, high collaboration indices are found in countries with low production, making their collaboration indices not directly comparable to those of the highest-producing countries in Table 6.

3.3. Keyword Analysis

For keyword analysis, co-occurrence networks were developed based on the data reported by the authors. Two co-occurrence maps were generated using the software described in the methodology section: network visualization and overlay visualization. In the network visualization map (see Figure 8), a total of 40 keywords are grouped into five clusters, using a minimum occurrence threshold of 4 for each keyword. A disambiguation process was applied, involving software parameterization to recognize synonyms and avoid multiple counting, thus enhancing visualization (e.g., in this research, the keywords “electronic health record” and “electronic health records” were grouped as “EHR”). In Figure 8, the size of each circle represents the frequency of a keyword’s occurrence, while the connecting lines represent the correlation between words, with thicker lines indicating stronger correlations. Clusters are represented by colors, and the keywords belonging to each cluster are summarized in

Table 7. Detail of the semantic map of keywords.

Cluster	Color	Keywords
1		e-health, information security, IoT (internet of things), ISO/IEEE 11073, medical devices, privacy, risk, safety, security, standards, telemedicine
2		accreditation, certification, ISO, ISO 15189, ISO 9000, ISO 9001, nursing, patient safety, QMS (quality management system), risk management
3		evaluation, health information exchange, health information systems, healthcare, hospital, management, process assessment, quality indicators
4		archetype, EHR (electronic health records), health information interoperability, healthcare system, HL7 FHIR (Health Level Seven—Fast Healthcare Interoperability Resources), ISO 13606, ontology
5		artificial intelligence, medical informatics, metadata registry, semantic interoperability

.

Regarding the cluster analysis, the red cluster focuses on security and privacy, particularly in the context of medical devices and telemedicine, reflecting the growing concern for protecting patient data and ensuring the security of health information systems. The positive impact of IT on improving healthcare delivery, disease surveillance, data management, and communication in public health is highlighted, all with a strong focus on health informatics from ISO 11073 [64]. However, challenges associated with IT adoption, such as concerns about data privacy and security, interoperability issues, the digital divide, and the need for healthcare staff training, have also been addressed [65]. Interestingly, within this cluster, the emergence of keywords like “telemedicine”, “IoT” (Internet of Things), and “information security” marks a trend over time. The green cluster leans towards ISO standards and quality management, highlighting the importance of ISO standards in quality management and accreditation of healthcare organizations. ISO 9000 and 9001 are fundamental for quality management systems, while ISO 15189 is specific to clinical laboratories. The yellow cluster has a significant focus on health information systems, relating to the development and implementation of health information systems, including electronic health records. Interoperability is a key issue, as it enables information exchange between different systems [66]. The blue cluster on semantic interoperability and ontologies focuses on semantic interoperability, which aims to ensure that health data is understandable and usable by different systems. Ontologies and standards like ISO 13606 are key tools for achieving this interoperability. Finally, the purple cluster on healthcare and patient safety encompasses general topics related to healthcare, such as patient safety, quality of care, and the role of nursing.

The analysis of these clusters reveals a comprehensive view of trends in ISO standardization within healthcare organizations. While ISO standards are central, they are closely intertwined with quality management, information systems, semantic interoperability, and patient safety. Furthermore, the increasing importance of emerging technologies, such as artificial intelligence and telemedicine, in this field is evident.

3.4. Research Evolution in ISO and Healthcare Organizations

The overlay visualization map in Figure 9 reveals crucial information about the trends and relationships among relevant topics in the field of study over the last decade. Analysis of the map highlights three key aspects in the timeline of the last decade:

• The centrality of ISO standards: ISO standards, particularly ISO 9000, ISO 9001, and ISO 15189, occupy a central position in the network, indicating their fundamental importance in healthcare standardization processes.
• Connections with other themes: ISO standards are strongly linked to other relevant topics, such as quality management (“quality indicators”), patient safety, health information systems, and health information interoperability. This suggests that ISO standardization is integrated into multiple aspects of healthcare management and practice.
• The emergence of new topics: The emergence of more recent topics has been observed, such as artificial intelligence [67,68], telemedicine, and information security. This indicates that ISO standardization is evolving to address the challenges and opportunities presented by new technologies. Regarding the topic of IoT, the appearance of this term on the timeline is closely related to the analysis of Figure 2, where the number of annual publications increased, which is consistent with the mass adoption of IoT in the early 2010s, driven by the reduction in sensor and connectivity costs, along with the development of software platforms to manage large amounts of data [68,69,70]. Additionally, semantic interoperability and health information interoperability are also emerging topics connected with ISO standards, underscoring the importance of ensuring that health information systems can communicate and exchange data effectively [65].

The analysis in Figure 9 reveals that ISO standardization in health organizations is a dynamic and a constantly evolving field. ISO standards remain fundamental but interact with emerging topics such as technology and interoperability. This information is valuable for healthcare professionals, researchers, and policymakers who seek to understand and improve standardization processes in the health sector.

To reinforce the conceptualization of the evolution of research in ISO and healthcare systems, Figure 10 analyzes trending topics over more than two decades. The size of the circle represents the frequency of appearance of a keyword, while the horizontal bar indicates the period between the first and third quartile of publication years. A generalized growth is observed in most topics, indicating an increase in research and publication in these areas. Additionally, topics such as “patient safety”, “telemedicine”, “data security”, and “artificial intelligence” have gained prominence in recent years, reflecting a growing interest in safety, technology, and artificial intelligence in the healthcare field. Other topics, such as “ISO”, “healthcare”, and “standards”, have maintained a constant presence, indicating their continued importance in the field.

In Figure 10, the topic “patient safety” has experienced notable growth, especially from 2010 onwards. This reflects an increased awareness of the importance of ensuring patient safety in all aspects of healthcare, including the use of information technologies. The rise of “telemedicine” and “artificial intelligence” is evident, particularly from 2014 onwards. This reflects the progressive adoption of digital technologies and artificial intelligence in healthcare, driven in part by the need to improve the efficiency, accessibility, and accuracy of health services. The increase in the frequency of the term “data security” from 2016 suggests a significant concern for the protection of patient data and the security of health information systems in the digital age. Topics related to ISO standards, such as “ISO 9000,” “ISO 9001,” and “ISO 13606,” have maintained a constant presence, indicating the importance of having regulatory and quality frameworks in the development and use of health information technologies. Finally, the term “medical informatics” has persisted, indicating that it remains a fundamental area in the research and development of information technologies for health. All the above is consistent with the analysis initiated in Figure 9.

4. Conclusions

This study analyzed the literature on ISO standardization in health and healthcare organizations using data from the Scopus Database, intending to describe and analyze evolutionary trends using bibliometric techniques. Based on the study’s findings, the following conclusions can be drawn:

The bibliometric review conducted in this study reveals a growing trend in the adoption and research of ISO standards in the healthcare field over the past three decades. The fundamental role of these standards in improving the quality, safety, and efficiency of healthcare services, as well as their contribution to patient satisfaction and the profitability of healthcare organizations, is highlighted. The analysis of scientific production over time shows a significant increase in the number of publications, especially since 2009. This increase has been reflected in the emergence and consolidation of new research areas, with a particular focus on emerging technologies such as telemedicine, artificial intelligence, and information security. Additionally, there is a geographical diversification of research, with authors and institutions from different countries/regions contributing to the development of knowledge in this area, which enriches the global perspective on standardization in health.

The analysis of the top 10 journals publishing on ISO standardization trends in healthcare organizations reveals a significant concentration in the fields of informatics and technology, with eight out of ten journals primarily published within the last decade. This highlights the growing importance of technology in shaping standardization practices in healthcare, as well as the need for health organizations to keep up to date and adapt their processes to technological advances to ensure quality, safety, and efficiency in the provision of services.

The analysis of the production by the most prolific authors shows that, although Spanish authors initially led the list, their production decreased in the last decade, with authors from the USA, UK, and Germany becoming more prominent, remaining active, and showing continuity in their research. This work also proposes a new bibliometric index, the NU-index, based on a modification of the unity index through a min-max normalization process, allowing the evaluation of productivity, acceptability, and impact of researchers in a scientific field globally.

In the last three years, there has been a significant increase in publications with a marked trend towards artificial intelligence, health information systems, interoperability, EHR, and the growing relevance of chatbots. The analysis of keywords and the evolution of research topics reveal a strong focus on emerging issues, such as telemedicine, artificial intelligence, and information security in the context of ISO standardization in health. This reflects the need to adapt ISO standards to technological advancements and new challenges facing the healthcare sector. This is further reinforced by the observation that, among the journals with the highest production, 48% have focused on technology and health informatics in recent years.

The rise of the Internet of Things (IoT) has significantly transformed various fields of knowledge, including healthcare. The analysis of thematic trends reveals an increase in publications related to IoT in the healthcare field during this period of expansion, an interest that persists today.

5. Limitations

Despite the valuable findings of this study, it is important to acknowledge some limitations. On one hand, there is the scope of the Scopus Database, which, although one of the most comprehensive and high quality, excludes relevant publications from other sources. On the other hand, when collecting information from scientific articles, there could be a publication bias towards studies with positive results, which could overestimate the benefits of ISO standards if the literature is analyzed in depth. It is important to highlight that the bibliometric approach provides a quantitative view of scientific production but does not capture the qualitative nuances and experiences of ISO standards implementation in the health and healthcare sector practice. Future research is needed to address these limitations and deepen the understanding of the factors influencing the adoption and impact of ISO standards in healthcare organizations. The analysis of articles with a higher number of citations implicitly assumes an equal contribution from all authors to the research, which may introduce bias into the analysis. However, upon examining the documents and publication pages, it was observed that few articles included an explicit author contribution statement.