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Transforming Care Through Clinical Nursing Information Systems and Standardized Nursing...
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Transforming Care Through Clinical Nursing Information Systems and Standardized Nursing Terminologies: Optimizing Data-Driven Care in Hospital and Community Settings

A special issue of Healthcare (ISSN 2227-9032). This special issue belongs to the section "Clinical Care".

Deadline for manuscript submissions: 31 January 2027 | Viewed by 13639

Editors

Dr. Antonello Cocchieri

E-Mail Website
Guest Editor
1. Section of Hygiene, Woman and Child Health and Public Health, Gemelli IRCCS University Hospital Foundation, Largo Agostino Gemelli 8, 00168 Rome, Italy
2. Section of Hygiene, University Department of Life Sciences and Public Health, Catholic University of the Sacred Heart, Largo Francesco Vito 1, 00168 Rome, Italy
Interests: complexity of care; nursing minimum data set; standardized nursing terminologies; clinical nursing information systems; clinical decision support systems; nursing care delivery models; health literacy
Dr. Manuele Cesare

E-Mail Website
Guest Editor Assistant
A. Gemelli IRCCS University Hospital Foundation, Section of Hygiene, Department of Health Science and Public Health, Catholic University of the Sacred Heart, 00168 Rome, Italy
Interests: standardized nursing terminologies; nursing complexity; nursing documentation; health literacy; pediatric & adult inpatient care

Special Issue Information

Dear Colleagues,

The digital transformation in healthcare is reshaping nursing practice, with Clinical Nursing Information Systems (CNISs) and Standardized Nursing Terminologies (SNTs) emerging as essential tools for optimizing patient-centered care in both hospital and community settings. CNISs provide structured data that support nurses in planning, documenting, and assessing care with enhanced precision, while SNTs enable standardized, clear communication across healthcare teams, promoting interoperability.

We are pleased to invite you to contribute to this Special Issue titled "Transforming Care Through Clinical Nursing Information Systems and Standardized Nursing Terminologies: Optimizing Data-Driven Care in Hospital and Community Settings." This Special Issue will publish original studies and reviews that examine the application and impact of CNISs and SNTs on clinical practice, including their effects on care quality, patient outcomes, and data-driven decision-making.

We welcome contributions that explore innovative uses of CNIS and SNTs in clinical settings. Topics may include how CNIS and SNTs data support resource allocation, policy-making, and strategic planning. This collection will serve as a resource for healthcare organizations looking to integrate digital tools and standardize care processes for improved patient outcomes.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:

  • Real-World Applications of CNIS and SNTs: Examining practical applications of CNIS and SNTs across hospital and community care settings, focusing on specific patient population characteristics, and evaluating their impact on clinical outcomes, workflow efficiency, and quality of care;
  • Enhancing Care Quality Through SNTs: Investigating the role of SNTs in standardizing communication, promoting patient safety, and elevating the overall quality of care within and across healthcare environments;
  • Data-Driven Decision-Making in Nursing Practice: Exploring how CNIS-derived data inform evidence-based decision-making, resource allocation, and policy development, ultimately optimizing nursing practices and organizational strategies;
  • Advancing Continuity of Care: Innovative uses of CNIS and SNTs that enable seamless transitions between hospital and community care, supporting integrated management of care;
  • Interoperability and Integration Across Systems: Studies on the effectiveness of CNIS and SNTs in achieving interoperability across healthcare systems, promoting consistent data exchange, and facilitating collaboration among diverse healthcare teams.

We look forward to receiving your contributions.

Dr. Antonello Cocchieri
Dr. Manuele Cesare
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Healthcare is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • clinical nursing information systems
  • standardized nursing terminologies
  • nursing informatics
  • nursing documentation
  • healthcare digitalization
  • interoperability in healthcare

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Published Papers (5 papers)

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Research

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12 pages, 252 KB  
Article
Developing a Subset of ICNP® Terminology for NICU and Neonatology Settings
by Valentina Tommasi, Laura E. A. Stabilini, Giulia Vercesi, Serena Rampini, Patrizio Sannino, Vincenza Aloia, Sara Marotta, Luca G. Re, Camilla Ripari, Stefania C. Rippa, Barbara Bassola and Maura Lusignani
Healthcare 2026, 14(5), 594; https://doi.org/10.3390/healthcare14050594 - 27 Feb 2026
Viewed by 461
Abstract
Background/Objectives: The International Classification for Nursing Practice (ICNP®) is a standardized nursing language that enables the description of nursing care through diagnoses, interventions, and outcomes. An ICNP® Subset is a sub-group of ICNP® terms appropriate for settings of [...] Read more.
Background/Objectives: The International Classification for Nursing Practice (ICNP®) is a standardized nursing language that enables the description of nursing care through diagnoses, interventions, and outcomes. An ICNP® Subset is a sub-group of ICNP® terms appropriate for settings of practice, facilitating the direct use of the ICNP® in nursing documentation. As far as we know, there are no Subsets concerning neonatology and Neonatal Intensive Care Unit (NICU) settings. The aim of this study is to develop a Subset of ICNP® for NICU and neonatology settings, presenting terms that are validated and harmonized with SNOMED CT nomenclature. Methods: This is a two-phase study. In the first phase, ICNP® terms were validated through a qualitative study using a four-round Delphi method and a focus group involving experts in NICU and neonatology settings and education. The second phase focused on harmonizing the proposed ICNP® Subset with SNOMED CT. Results: A total of 479 ICNP® terms belonging to the Diagnosis/Outcome (DC) and Intervention (IC) axes were validated by the experts. Of these, 99.65% were found to be compatible with SNOMED CT. In addition, 97 new terms (30 Diagnoses/Outcomes and 67 Interventions) were validated and are currently awaiting approval by the International Council of Nurses. Of the newly proposed terms, 93.81% were compatible with SNOMED CT. Conclusions: The proposed Subset consists of 576 ICNP® terms, including 177 Diagnoses/Outcomes and 399 Interventions. Its implementation may support the adoption of electronic health records in neonatal and NICU settings and contribute to improving the quality and standardization of nursing care. Full article
(This article belongs to the Special Issue Transforming Care Through Clinical Nursing Information Systems and Standardized Nursing Terminologies: Optimizing Data-Driven Care in Hospital and Community Settings)
15 pages, 982 KB  
Article
Ranking Nursing Diagnoses by Predictive Relevance for Intensive Care Unit Transfer Risk in Adult and Pediatric Patients: A Machine Learning Approach with Random Forest
by Manuele Cesare, Mario Cesare Nurchis, Nursing and Public Health Group, Gianfranco Damiani and Antonello Cocchieri
Healthcare 2025, 13(11), 1339; https://doi.org/10.3390/healthcare13111339 - 4 Jun 2025
Cited by 14 | Viewed by 3249
Abstract
Background/Objectives: In hospital settings, the wide variability of acute and complex chronic conditions—among both adult and pediatric patients—requires advanced approaches to detect early signs of clinical deterioration and the risk of transfer to the intensive care unit (ICU). Nursing diagnoses (NDs), standardized [...] Read more.
Background/Objectives: In hospital settings, the wide variability of acute and complex chronic conditions—among both adult and pediatric patients—requires advanced approaches to detect early signs of clinical deterioration and the risk of transfer to the intensive care unit (ICU). Nursing diagnoses (NDs), standardized representations of patient responses to actual or potential health problems, reflect nursing complexity. However, most studies have focused on the total number of NDs rather than the individual role each diagnosis may play in relation to outcomes such as ICU transfer. This study aimed to identify and rank the specific NDs most strongly associated with ICU transfers in hospitalized adult and pediatric patients. Methods: A retrospective, monocentric observational study was conducted using electronic health records from an Italian tertiary hospital. The dataset included 42,735 patients (40,649 adults and 2086 pediatric), and sociodemographic, clinical, and nursing data were collected. A random forest model was applied to assess the predictive relevance (i.e., variable importance) of individual NDs in relation to ICU transfers. Results: Among adult patients, the NDs most strongly associated with ICU transfer were Physical mobility impairment, Injury risk, Skin integrity impairment risk, Acute pain, and Fall risk. In the pediatric population, Acute pain, Injury risk, Sleep pattern disturbance, Skin integrity impairment risk, and Airway clearance impairment emerged as the NDs most frequently linked to ICU transfer. The models showed good performance and generalizability, with stable out-of-bag and validation errors across iterations. Conclusions: A prioritized ranking of NDs appears to be associated with ICU transfers, suggesting their potential utility as early warning indicators of clinical deterioration. Patients presenting with high-risk diagnostic profiles should be prioritized for enhanced clinical surveillance and proactive intervention, as they may represent vulnerable populations. Full article
(This article belongs to the Special Issue Transforming Care Through Clinical Nursing Information Systems and Standardized Nursing Terminologies: Optimizing Data-Driven Care in Hospital and Community Settings)
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Review

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16 pages, 342 KB  
Review
Gordon’s Functional Health Patterns and Their Association with Patient and Organizational Outcomes: A Scoping Review
by Clarissa Santos de Lima Araújo, Larissa Maiara da Silva Alves Souza, Agueda Mª Ruiz Zimmer Cavalcante, Janaína Guimarães Valadares, Flaviana Vely Mendonça Vieira, Dorothy Jones, Natália Del Angelo Aredes and Luca Bertocchi
Healthcare 2026, 14(9), 1144; https://doi.org/10.3390/healthcare14091144 - 24 Apr 2026
Viewed by 1964
Abstract
Background/Objectives: Nursing assessment frameworks play a critical role in guiding holistic patient evaluations, standardizing documentation, and supporting organizational quality and safety initiatives. Among these, Gordon’s Functional Health Patterns (FHPs) offer a comprehensive and widely used framework for nursing assessment. However, no review [...] Read more.
Background/Objectives: Nursing assessment frameworks play a critical role in guiding holistic patient evaluations, standardizing documentation, and supporting organizational quality and safety initiatives. Among these, Gordon’s Functional Health Patterns (FHPs) offer a comprehensive and widely used framework for nursing assessment. However, no review has synthesized evidence on their association with outcomes. This scoping review aimed to map evidence on the use of FHPs in relation to patient and organizational outcomes, and to examine their integration into electronic health records (EHRs) and the analytical methods employed. Method: A scoping review was conducted following Joanna Briggs Institute methodology and PRISMA-ScR guidelines. PubMed, CINAHL, and Scopus were searched for quantitative primary studies reporting associations between FHPs and outcomes, and the final search was conducted on 22 March 2024. Three reviewers independently screened abstracts and full texts and extracted data. Results: Seven studies met the inclusion criteria. FHPs’ use was associated with improvements in several patient outcomes, including quality of life, psychological well-being, clinical parameters, self-management, dependency level, and functional performance. Organizational outcomes included reduced hospital readmission rates and a positive association between FHP-derived nursing diagnoses and nursing workload. Most studies used standardized nursing terminologies such as NANDA-I, NOC, or NIC, in conjunction with FHPs. Over half of the studies used EHR-based nursing documentation, reflecting increasing digital integration and enabling more structured and interoperable nursing data. Methodological approaches varied widely: most studies used associative analyses, two employed experimental designs, and one investigated the predictive utility of FHP-based assessment data. Conclusions: FHPs provide a structured framework for nursing practice with potential benefits for patient and organizational outcomes. Their increasing integration into EHRs supports standardized documentation and data-driven nursing practice, enhancing assessment quality, diagnostic accuracy, and the availability of structured data for clinical and managerial decision-making in health information systems. Further experimental and longitudinal research is needed to strengthen causal evidence and guide implementation. Full article
(This article belongs to the Special Issue Transforming Care Through Clinical Nursing Information Systems and Standardized Nursing Terminologies: Optimizing Data-Driven Care in Hospital and Community Settings)
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21 pages, 1109 KB  
Review
Standardized Nursing Terminologies and Electronic Health Records: A Secondary Analysis of a Systematic Review
by Luca Bertocchi, Cristina Petrucci, Vittorio Masotta, Alessia Marcotullio, Dorothy Jones, Loreto Lancia and Angelo Dante
Healthcare 2025, 13(16), 1952; https://doi.org/10.3390/healthcare13161952 - 9 Aug 2025
Cited by 4 | Viewed by 6011
Abstract
Background/Objectives: Standardized nursing terminologies (SNTs) have been associated with improved patient and organizational outcomes. This secondary analysis aims to examine how structured nursing assessment data and documentation are integrated into electronic health records (EHRs) in studies that report on the impact of American [...] Read more.
Background/Objectives: Standardized nursing terminologies (SNTs) have been associated with improved patient and organizational outcomes. This secondary analysis aims to examine how structured nursing assessment data and documentation are integrated into electronic health records (EHRs) in studies that report on the impact of American Nurses Association–recognized SNTs. Methods: Data were extracted from all 53 primary studies included in a previously published systematic review. The original literature search was conducted in PubMed, Scopus, CINAHL, and OpenGrey. Extracted data focused on nursing assessment tools, use of EHRs, inter-rater reliability, and methodological characteristics. Results: Gordon’s Eleven Functional Health Patterns was the most frequently used nursing assessment framework, often in combination with NANDA-I diagnoses. However, details regarding assessment tools and their application in EHRs were inconsistently reported. Only about one-third of the studies explicitly indicated the use of EHRs, though an upward trend in their use has been observed over the last decade. Inter-rater reliability was reported in a limited number of studies, with considerable variation. An overall increasing trend in the use of nursing assessment data in electronic health records was observed over the past decade. Conclusions: The integration of SNTs with structured assessment frameworks into EHRs is increasing but remains inconsistently reported. Standardized documentation practices could strengthen nursing visibility, support quality improvement, and enhance outcome measurement in both clinical and research contexts. Full article
(This article belongs to the Special Issue Transforming Care Through Clinical Nursing Information Systems and Standardized Nursing Terminologies: Optimizing Data-Driven Care in Hospital and Community Settings)
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Other

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19 pages, 1086 KB  
Systematic Review
Automated Discharge Instructions in Medical and Surgical Care: A Systematic Review of Patient Engagement and Clinical Outcomes
by Maissa Trabilsy, Ariana Genovese, Cesar A. Gomez-Cabello, Syed Ali Haider, Srinivasagam Prabha, Bernardo Collaco, Nadia G. Wood, Sanjay Bagaria, James London and Antonio Jorge Forte
Healthcare 2026, 14(6), 798; https://doi.org/10.3390/healthcare14060798 - 20 Mar 2026
Viewed by 719
Abstract
Background: Automated discharge instructions are increasingly used to support post-discharge communication, patient education, and nursing follow-up, yet the current state remains unidentified. This systematic review explores the types of automated discharge instructions used and their effectiveness in enhancing patient engagement and reducing readmission, [...] Read more.
Background: Automated discharge instructions are increasingly used to support post-discharge communication, patient education, and nursing follow-up, yet the current state remains unidentified. This systematic review explores the types of automated discharge instructions used and their effectiveness in enhancing patient engagement and reducing readmission, emergency department visits and reoperation rates. Methods: A systematic search was conducted on 15 April 2025, using Embase, PubMed, Scopus, Web of Science, and CINAHL, following PRISMA guidelines. Inclusion criteria required peer-reviewed original research evaluating the utilization of automated patient discharge instructions following hospital admission or surgical stay. Exclusion criteria included correspondence, reviews, educational materials, not peer-reviewed, retracted reports, not retrievable, and no English translation. Risk of bias was assessed independently using NIH, JBI, ROB-2, and ROBINS-I tools. Two investigators independently conducted the screening, extraction, and synthesis of results using Endnote and Microsoft Excel. Results: Of the 1252 records identified, 13 studies were selected for analysis. There was a total of 34,386 patients across a diverse range of healthcare settings and clinical contexts. The average sample size per study was approximately 4912, with study samples ranging from 16 to 13,188 patients. The modalities of discharge instructions included automated phone calls (23.1%) and/or text messages (53.8%), as well as printed out auto-generated summaries (15.4%). Patient engagement was generally high, with automated phone calls showing the most consistent interaction, with completion rates ranging from 44% to 56%, often prompting clinical follow-up. SMS tools demonstrated strong scalability and response rates up to 87%. Two studies reported on hospital readmission outcomes and only a single study reported on emergency department revisit rates, while none assessed reoperation outcomes. Among those reporting readmission, automated phone calls and SMS were associated with lower or proxy-reduced readmission rates. Included studies had low to moderate levels of bias. Conclusions: While evidence on clinical outcomes such as readmissions, emergency department revisits, and reoperations remains limited and inconclusive, automated discharge tools—particularly phone calls and SMS—consistently demonstrated high patient engagement. Automated discharge tools show promise for supporting transitional care, discharge education, and post-discharge monitoring, highlighting the future role of automated tools in nursing workflows to support follow-up, escalation, and continuity of care. Full article
(This article belongs to the Special Issue Transforming Care Through Clinical Nursing Information Systems and Standardized Nursing Terminologies: Optimizing Data-Driven Care in Hospital and Community Settings)
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