Nevin Manimala

Stud Health Technol Inform. 2025 May 15;327:1353-1357. doi: 10.3233/SHTI250623.

ABSTRACT

As pressure to increase operational efficiency in clinical trials grows, organizations are looking to advances such as tools enabling extraction of Electronic Health Record (EHR) data and transmission to the study database or electronic Case Report Form (eCRF). As interest and adoption of these tools, often called EHR-to-eCRF software, grows in clinical research, consistent evaluative data on key outcomes, such as data accuracy, remains limited. This study compared the accuracy of data collected from EHRs using EHR-to-eCRF technology to traditional methods of clinical trial data collection. The accuracy of the EHR-extracted data was significantly higher than that of data collected through the traditional approach. These results suggest that EHR-based data collection could substantially enhance data quality in clinical trials.

PMID:40380726 | DOI:10.3233/SHTI250623

Stud Health Technol Inform. 2025 May 15;327:1338-1342. doi: 10.3233/SHTI250620.

ABSTRACT

Implementing Electronic Medical Records (EMRs) is a key advancement in modern healthcare. These systems aim to improve operational efficiency, patient care, and staff satisfaction. However, their implementation often faces challenges that affect workflows, especially in high-pressure environments like emergency rooms (ERs). This paper presents a comprehensive evaluation of an EMR system implemented at Niguarda Hospital’s ER, focusing on its impact on documentation efficiency, staff satisfaction, and overall operational performance. We employed a combination of time-based metrics and qualitative staff feedback to capture both the quantitative and human factors influencing the adoption of the system. Our findings indicate significant improvements in documentation times, patient flow, and staff workflow following the adoption of Dedalus’ EMR system. However, initial challenges, such as resistance to change and system integration issues, were also observed.

PMID:40380723 | DOI:10.3233/SHTI250620

Stud Health Technol Inform. 2025 May 15;327:1318-1322. doi: 10.3233/SHTI250616.

ABSTRACT

In implementing the new Electronic Health Record (EHR) Epic working practices change for clinicians in mental health care and their use of an Electronic Medication Management System (EMMS). In this case study two main aspects affecting their work practices were found. The new EMMS led to the work being more time-consuming, but it was also experienced as safer.

PMID:40380719 | DOI:10.3233/SHTI250616

Stud Health Technol Inform. 2025 May 15;327:1313-1317. doi: 10.3233/SHTI250615.

ABSTRACT

Monitoring the end-user experiences of electronic health records (EHR) and client information systems (CIS) in Finland enables data driven decision-making. This study focuses on a single individual-level indicator and identifies a predictive model that can help apply these modeling results in practice. The findings suggest that themes related to this indicator – specifically, the good grade given to the primary system’s (EHR/CIS) – are related to the functionality, usability, and support for nursing documentation within the primary system. Moreover, the information systems (IS) landscape, it’s potential to support carrying out duties and exchanging information, and benefits of IS, were crucial. IS benefits are usually linked to factors such as continuity of care, avoid duplicate tests, and medication safety. Improving all these themes could improve circumstances where end-users could achieve better performance in the care of the patients.

PMID:40380718 | DOI:10.3233/SHTI250615

Stud Health Technol Inform. 2025 May 15;327:1308-1312. doi: 10.3233/SHTI250614.

ABSTRACT

The mapping from the International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) to the 11th Revision (ICD-11), initiated by the World Health Organization (WHO), presents a challenge for healthcare systems, most of which currently rely on extensive ICD-10 coded data for billing purposes. This paper introduces a methodology to generate a FHIR (Fast Healthcare Interoperability Resources) ConceptMap from the WHO-provided ICD-10 to ICD-11 mapping tables. The resulting ConceptMap allows healthcare organizations to automate the mapping process, facilitating the integration of ICD-11. The final ConceptMap includes ICD-11 mappings for 12,952 ICD-10 codes. This approach prepares healthcare systems for the transition to ICD-11.

PMID:40380717 | DOI:10.3233/SHTI250614

Stud Health Technol Inform. 2025 May 15;327:1305-1306. doi: 10.3233/SHTI250612.

ABSTRACT

This study explores how well large language models (like the kind that powers ChatGPT) can analyze online conversations about disability rights. We specifically looked at whether these models could: 1) identify if tweets about people with disabilities were positive or negative, and 2) tell if the tweets viewed disability as a problem with society (social model) or a problem with the individual (medical model). We collected 5,000 tweets and trained a language model to analyze them. The results demonstrated promising accuracy levels for sentiment analysis and social vs. medical model classification.

PMID:40380716 | DOI:10.3233/SHTI250612

Stud Health Technol Inform. 2025 May 15;327:1301-1302. doi: 10.3233/SHTI250610.

ABSTRACT

Assessing healthcare professionals’ (HCPs’) perceptions on the appropriateness, ease of use and reliability of connected digital health technologies can help to understand acceptance and their recommendations to patients/caregivers for personalization of growth hormone (GH) therapy. Two study cases representing different versions of a digital device were used to facilitate expert panel discussions in the UK and France involving 19 paediatric HCPs. Panel members commented that the new functionalities embodied user-friendly technological progression. The evolution of the easypod device should sustain clinical decision support and enhance personalized approaches to care and management of patients receiving GH therapy.

PMID:40380714 | DOI:10.3233/SHTI250610

Stud Health Technol Inform. 2025 May 15;327:1299-1300. doi: 10.3233/SHTI250609.

ABSTRACT

The project xShare supports citizens’ empowerment within the EHDS through the use of the “yellow button” which allows individuals to share their own structured data with third parties, also for secondary use purposes. Focusing on the six information domains listed by the EHDS, the project articulates the artefacts for each domain and for identified real-live use cases. To identify current and prospective useful use cases for Public Health (PH), it is important to understand if and how the different European states are getting ready for the implementation of the EHDS and the main existing challenges. To collect this information, we analysed the available literature and launched a survey exploring the current state of consolidation of PH datasets, the standards used, the associated workflows and the possible prospective use cases. We also identified and studied four countries that represent the best “only once” practice examples in Europe.

PMID:40380713 | DOI:10.3233/SHTI250609

Stud Health Technol Inform. 2025 May 15;327:1295-1296. doi: 10.3233/SHTI250607.

ABSTRACT

The KIADEKU project combines datascience and the clinical expertise of wound experts to develop and evaluate an AI-application for incontinence-associated-dermatitis (IAD) and pressure ulcer (PU) wound care. The evaluation study is a controlled, non-randomized clinical trial that investigates the effects of the AI-based system on wound care time, guideline adherence and the task load of the nurse, using a pre-post design with two data collection periods. We observe nurses providing wound care for PU and IAD in the control group according to the standard and in the intervention group using the developed AI-based app. We analyze the data using linear regression including further covariates (professional experience of the nurse, general load of the shift and severity of the wound). As a further outcome, we determine the accuracy and the usability of the AI-based digital system and the standard clinical documentation systems. We expect the study to support nurses in wound care and to promote the use of AI in nursing.

PMID:40380711 | DOI:10.3233/SHTI250607

JMIR Form Res. 2025 May 16;9:e60294. doi: 10.2196/60294.

ABSTRACT

BACKGROUND: In recent times, the telemedicine landscape has changed dramatically; it serves as a bridge, connecting health care providers and patients, especially during challenges such as the recent COVID-19 pandemic.

OBJECTIVE: This study seeks to explore the Swedish telemedicine landscape in terms of primary patient symptoms for teleconsultation and the patterns of telemedicine use in the periods before COVID-19, during COVID-19, and after COVID-19, including the primary care use dynamics with respect to the teleconsultations done.

METHODS: Secondary data was used in this observational retrospective study. The study population consisted of Swedish residents who had online telemedicine consultations. Telemedicine consultations were divided by text and video delivery; the period of analysis ranged from November 2018 to June 2023. The statistical methods used for the data analysis were descriptive analysis, 2-way cross tabulation, and a generalized linear model.

RESULTS: During the pandemic, the number of teleconsultations concerning general, unspecified symptoms increased in comparison to the other analyzed symptoms, signaling a change in care-seeking behavior under epidemiological pressure. General health-related issues were the most pronounced symptom across all periods: 186.9 of 1000 consultations before COVID-19, 1264.6 of 1000 consultations during COVID-19, and 319.2 of 1000 consultations after COVID-19. There was no significant main effect of COVID-19 period on the number of telemedicine consultation meetings (F2=1.653; P=.38). The interaction effect between delivery type and period was statistically significant (F2=14.723; P<.001).

CONCLUSIONS: The findings are in favor of the COVID-19 pandemic having had a considerable effect on telemedicine use. Telemedicine could subsequently be used more often for general health consultations and acute conditions. Video consultations were more prominent because of the importance of bidirectional communication. The study suggests that there was a transformation of patterns of demand for health care; there is a necessity for health care systems to respond to these changes.

PMID:40378415 | DOI:10.2196/60294