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Effective asthma management is a necessity for the control and optimal outcomes of the condition. A number of factors may either facilitate or act as barriers to the management of asthma in adolescents. The objective of this study was to assess the feelings, thoughts, and behaviors of adolescents diagnosed with asthma regarding the management of their condition. This exploratory qualitative study was conducted using semi-structured, in-depth interviews with 12 adolescents aged 12–18 years who were followed up with a diagnosis of asthma at a university hospital pediatric allergy clinic between October 15 October 2023, and December 15 December 2023. The study was written using the COREQ checklist. Three main themes were identified in this study: (1) facilitators, (2) barriers, and (3) information. Adolescents reported that they needed more information about medication use and asthma disease to manage asthma. Asthma control ability, positive beliefs, and supportive relationships were facilitators of asthma management. However, poor asthma control, negative beliefs, lack of support, poor communication, and asthma-related stigma were identified as barriers to asthma self-management. Adolescents had information needs in asthma management. This study highlights that barriers to asthma self-management in adolescents are much greater than the facilitators. For adolescents to manage their asthma well, their information needs must be met. Therefore, pediatric nurses should prepare individualized training to meet the specific needs of adolescents. [ABSTRACT FROM AUTHOR]

Objectives: To assess the impact of the COVID-19 pandemic on disability insurance grants and related costs for workerswith cancer. Methods: This ecological time series study uses the inflection point regression model and the federal government's open-access dataset. We analyze the annual grant and cost rates of cancer-related disability insurance in Brazil (2010-2021). Results: In 2020, the number of disability insurance grants due to malignant neoplasms decreased by 62.26%, and the total annual cost decreased by 62.94% compared to those in 2019. All illnesses and injuries were reduced by 2.56% and 20.02%, respectively. Between 2010 and 2021, the COVID-19 pandemic has reversed the increasing trend in annual disability insurance granted due to cancer and its associated expenses to a stable trend. Conclusion: The COVID-19 pandemic has harmed the provision of disability insurance for workers with cancer. [ABSTRACT FROM AUTHOR]

Background: Patient's privacy protection is a challenging ethical issue. The complex situation of the COVID-19 pandemic was a probable predictor of breaching confidentiality. This study aimed to assess the viewpoints of COVID-19-confirmed patients, who were hospitalized, and their healthcare providers about the compliance of different aspects of patient's privacy. Methods: This cross-sectional study included 3433 COVID-19-confirmed patients who were hospitalized in Kerman, between 2020 and 2021, and about 1228 related physicians, nurses, and paraclinical staff. Two separate validated researcher-made questionnaires were developed, each including subscales for physical, informational, and spatial privacy, as well as a satisfaction rate of privacy protection. The data were analyzed using SPSS software version 26, with independent samples t test, Mann-Whitney-U, Kruskal Wallis, and Multiple Linear Regression tests at a 95% confidence interval. Results: The mean percentages of the patients' privacy scores in physical, spatial, and informational areas were significantly lower (P<0.001) than the average of the medical staff's scores in all three areas (Difference: 10.27%, 14.83%, and 4.91%, respectively). Physical and spatial privacy scores could be predicted based on the participants' classification, patients or medical staff, and sex. The mean patients' satisfaction score was 9.25% lower than the medical staff's (P<0.001). Moreover, only academic hospitals showed a statistically significant difference between the patient's satisfaction with privacy protection and medical staff's viewpoints (P<0.001). Conclusion: Although this study indicated the benefits of protecting patients' privacy in the healthcare setting, patients' privacy scores and satisfaction were lower than their healthcare providers. The pandemic conditions might have been an obstacle to preserving patients' rights. These findings demonstrated the importance of sensitizing healthcare providers to manage these ethical challenges in a complicated critical state such as the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Background: As patients interact with a healthcare service system, patterns of service utilization (PSUs) emerge. These PSUs are embedded in the sparse high-dimensional space of longitudinal cross-continuum health service encounter data. Once extracted, PSUs can provide quality assurance/quality improvement (QA/QI) efforts with the information required to optimize service system structures and functions. This may improve outcomes for complex patients with chronic diseases. Method: Working with longitudinal cross-continuum encounter data from a regional health service system, various pattern detection analyses were conducted, employing (1) graph community detection algorithms, (2) natural language processing (NLP) clustering, and (3) a hybrid NLP–graph method. Result: These approaches produced similar PSUs, as determined from a clinical perspective by clinical subject matter experts and service system operations experts. Conclusions: The similarity in the results provides validation for the methodologies. Moreover, the results stress the need to engage with clinical or service system operations experts, both in providing the taxonomies and ontologies of the service system, the cohort definitions, and determining the level of granularity that produces the most clinically meaningful results. Finally, the uniqueness of each approach provides an opportunity to take advantage of the various analytical capabilities that each approach brings, which will be further explored in our future research. [ABSTRACT FROM AUTHOR]

Background: This article reports on a study that investigated data professionals in health care. The topic is interesting and relevant because of the ongoing trend towards digitisation of the healthcare domain and efforts for it to become data driven, which entail a wide variety of work with data. Objective: Despite an interest in data science and more broadly in data work, we know surprisingly little about the people who work with data in healthcare. Therefore, we investigated data work at a large national healthcare data organisation in Denmark. Method: An explorative mixed method approach combining a non-probability technique for design of an open survey with a target population of 300+ and 11 semi-structured interviews, was applied. Results: We report findings relevant to educational background, work identity, work tasks, and how staff acquired competences and knowledge, as well as what these attributes comprised. We found recurring themes of healthcare knowledge, data analytical skills, and information technology, reflected in education, competences and knowledge. However, there was considerable variation within and beyond those themes, and indeed most competences were learned "on the job" rather than as part of formal education. Conclusion: Becoming a professional working with data in health care can be the result of different career paths. The most recurring work identity was that of "data analyst"; however, a wide variety of responses indicated that a stable data worker identity has not yet developed. Implications: The findings present implications for educational policy makers and healthcare managers. [ABSTRACT FROM AUTHOR]

Background: In Portugal, trained physicians undertake the clinical coding process, which serves as the basis for hospital reimbursement systems. In 2017, the classification version used for coding of diagnoses and procedures for hospital morbidity changed from the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) to the International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS). Objective: To assess the perceptions of medical coders on the transition of the clinical coding process from ICD-9-CM to ICD-10-CM/PCS in terms of its impact on data quality, as well as the major differences, advantages, and problems they faced. Method: We conducted an observational study using a web-based survey submitted to medical coders in Portugal. Survey questions were based on a literature review and from previous focus group studies. Results: A total of 103 responses were obtained from medical coders with experience in the two versions of the classification system (i.e. ICD-9-CM and ICD-10-CM/PCS). Of these, 82 (79.6%) medical coders preferred the latest version and 76 (73.8%) considered that ICD-10-CM/PCS guaranteed higher quality of the coded data. However, more than half of the respondents (N = 61; 59.2%) believed that more time for the coding process for each episode was needed. Conclusion: Quality of clinical coded data is one of the major priorities that must be ensured. According to the medical coders, the use of ICD-10-CM/PCS appeared to achieve higher quality coded data, but also increased the effort. Implications: According to medical coders, the change off classification systems should improve the quality of coded data. Nevertheless, the extra time invested in this process might also pose a problem in the future. [ABSTRACT FROM AUTHOR]

Background: Electronic health records (EHR) are seen as a promising endeavour, in spite of policies, designs, user rights and types of health data varying across countries. In many European countries, including Austria, EHR usage has fallen short when compared to the deployment plans. Objective: By adopting a qualitative approach, this research aimed to explore facilitators and barriers experienced by patients and physicians across the entire EHR usage process in Austria. Method: Two studies were conducted: In Study 1, discussions were held with four homogeneously composed groups of patients (N = 30). In Study 2, eight expert semi-structured interviews were conducted with physicians to gain insights into potential facilitators and barriers Austrian physicians face when utilising personal EHR. Results: A wide range of barriers and facilitators were identified along the entire EHR usage spectrum, emerging on three different levels: the micro-level (individual level), the meso-level (level of the EHR system) and the macro-level (level of the health system). EHR literacy was identified as a booster to support EHR adherence. Health providers were identified as crucial gatekeepers with regard to EHR usage. Conclusion: The implications for mutual benefits arising out of EHR usage among the triad of health policymakers, providers and patients for both theory and practice are discussed. [ABSTRACT FROM AUTHOR]

Background: The health and well-being of children in the first 2000 days has a lasting effect on educational achievement and long-term chronic disease in later life. However, the lack of integration between high-quality data, analytic capacity and timely health improvement initiatives means practitioners, service leaders and policymakers cannot use data effectively to plan and evaluate early intervention services and monitor high-level health outcomes. Objective: Our exploratory study aimed to develop an in-depth understanding of the system and clinical requirements of a state-wide paediatric learning health system (LHS) that uses routinely collected data to not only identify where the inequities and variation in care are, but also to also inform service development and delivery where it is needed most. Method: Our approach included reviewing exemplars of how administrative data are used in Australia; consulting with clinical, policy and data stakeholders to determine their needs for a child health LHS; mapping the existing data points collected across the first 2000 days of a child's life and geospatially locating patterns of key indicators for child health needs. Results: Our study identified the indicators that are available and accessible to inform service delivery and demonstrated the potential of using routinely collected administrative data to identify the gap between health needs and service availability. Conclusion: We recommend improving data collection, accessibility and integration to establish a state-wide LHS, whereby there is a streamlined process for data cleaning, analysis and visualisation to help identify populations in need in a timely manner. [ABSTRACT FROM AUTHOR]

Background: Services data are an important source of information for policymakers and planners. In Australia, significant work has been undertaken to develop and implement collections of mental health services data. Given this level of investment, it is important that collected data are fit for purpose. Objective: This study aimed to: (1) identify existing national mandated and best endeavours collections of mental health services activity (e.g. occasions of service) and capacity (e.g. full-time equivalent staff) data in Australia; and (2) review the content of identified data collections to determine opportunities for data development. Method: A grey literature search was conducted to identify data collections. Where available, metadata and/or data were analysed. Results: Twenty data collections were identified. For services that received funding via multiple funding streams, data were often captured across several collections corresponding with each funder. There was significant variability in the content and format of collections. Unlike other service sectors, there is no national, mandated collection for psychosocial support services. Some collections have limited utility as they do not include key activity data; others do not include descriptive variables like service type. Workforce data are often not collected, and where data are collected, they are often not comprehensive. Conclusion: Findings are an important source of information for policymakers and planners who use services data to inform priorities. Implications: This study provides recommendations for data development, including mandating standardised reporting for psychosocial supports, filling workforce data gaps, streamlining data collections and including key missing data items in some collections. [ABSTRACT FROM AUTHOR]

Background: The implementation of emerging technologies has resulted in an increase of data breaches in healthcare organisations, especially during the COVID-19 pandemic. Health information and cybersecurity managers need to understand if, and to what extent, breach types and locations are associated with their organisation's business type. Objective: To investigate if breach type and breach location are associated with business type, and if so, investigate how these factors affect information systems and protected health information in for-profit versus non-profit organisations. Method: The quantitative study was performed using chi-square tests for association and post-hoc comparison of column proportions analysis on an archival data set of reported healthcare data breaches from 2020 to 2022. Data from the Department of Health and Human Services website was retrieved and each organisation classified as for-profit or non-profit. Results: For-profit organisations experienced a significantly higher number of breaches due to theft, and non-profit organisations experienced a significantly higher number of breaches due to unauthorised access. Furthermore, the number of breaches that occurred on laptops and paper/films was significantly higher in for-profit organisations. Conclusion: While the threat level of hacking techniques is the same in for-profit and non-profit organisations, certain breach types are more likely to occur within specific breach locations based on the organisation's business type. To protect the privacy and security of medical information, health information and cybersecurity managers need to align with industry-leading frameworks and controls to prevent specific breach types that occur in specific locations within their environments. [ABSTRACT FROM AUTHOR]

Background: Electronic medical records (EMRs) have been widely implemented in Australian hospitals. Their usability and design to support clinicians to effectively deliver and document care is essential, as is their impact on clinical workflow, safety and quality, communication, and collaboration across health systems. Perceptions of, and data about, usability of EMRs implemented in Australian hospitals are key to successful adoption. Objective: To explore perspectives of medical and nursing clinicians on EMR usability utilising free-text data collected in a survey. Method: Qualitative analysis of one free-text optional question included in a web-based survey. Respondents included medical and nursing/midwifery professionals in Australian hospitals (85 doctors and 27 nurses), who commented on the usability of the main EMR used. Results: Themes identified related to the status of EMR implementation, system design, human factors, safety and risk, system response time, and stability, alerts, and supporting the collaboration between healthcare sectors. Positive factors included ability to view information from any location; ease of medication documentation; and capacity to access diagnostic test results. Usability concerns included lack of intuitiveness; complexity; difficulties communicating with primary and other care sectors; and time taken to perform clinical tasks. Conclusion: If the benefits of EMRs are to be realised, there are good reasons to address the usability challenges identified by clinicians. Easy solutions that could improve the usability experience of hospital-based clinicians include resolving sign-on issues, use of templates, and more intelligent alerts and warnings to avoid errors. Implications: These essential improvements to the usability of the EMR, which are the foundation of the digital health system, will enable hospital clinicians to deliver safer and more effective health care. [ABSTRACT FROM AUTHOR]

Background: Clinician notes are structured in a variety of ways. This research pilot tested an innovative study design and explored the impact of note formats on diagnostic accuracy and documentation review time. Objective: To compare two formats for clinical documentation (narrative format vs. list of findings) on clinician diagnostic accuracy and documentation review time. Method: Participants diagnosed written clinical cases, half in narrative format, and half in list format. Diagnostic accuracy (defined as including correct case diagnosis among top three diagnoses) and time spent processing the case scenario were measured for each format. Generalised linear mixed regression models and bias-corrected bootstrap percentile confidence intervals for mean paired differences were used to analyse the primary research questions. Results: Odds of correctly diagnosing list format notes were 26% greater than with narrative notes. However, there is insufficient evidence that this difference is significant (75% CI 0.8–1.99). On average the list format notes required 85.6 more seconds to process and arrive at a diagnosis compared to narrative notes (95% CI -162.3, −2.77). Of cases where participants included the correct diagnosis, on average the list format notes required 94.17 more seconds compared to narrative notes (75% CI -195.9, −8.83). Conclusion: This study offers note format considerations for those interested in improving clinical documentation and suggests directions for future research. Balancing the priority of clinician preference with value of structured data may be necessary. Implications: This study provides a method and suggestive results for further investigation in usability of electronic documentation formats. [ABSTRACT FROM AUTHOR]

Background: Quantifying and dealing with lack of consistency in administrative databases (namely, under-coding) requires tracking patients longitudinally without compromising anonymity, which is often a challenging task. Objective: This study aimed to (i) assess and compare different hierarchical clustering methods on the identification of individual patients in an administrative database that does not easily allow tracking of episodes from the same patient; (ii) quantify the frequency of potential under-coding; and (iii) identify factors associated with such phenomena. Method: We analysed the Portuguese National Hospital Morbidity Dataset, an administrative database registering all hospitalisations occurring in Mainland Portugal between 2011–2015. We applied different approaches of hierarchical clustering methods (either isolated or combined with partitional clustering methods), to identify potential individual patients based on demographic variables and comorbidities. Diagnoses codes were grouped into the Charlson an Elixhauser comorbidity defined groups. The algorithm displaying the best performance was used to quantify potential under-coding. A generalised mixed model (GML) of binomial regression was applied to assess factors associated with such potential under-coding. Results: We observed that the hierarchical cluster analysis (HCA) + k-means clustering method with comorbidities grouped according to the Charlson defined groups was the algorithm displaying the best performance (with a Rand Index of 0.99997). We identified potential under-coding in all Charlson comorbidity groups, ranging from 3.5% (overall diabetes) to 27.7% (asthma). Overall, being male, having medical admission, dying during hospitalisation or being admitted at more specific and complex hospitals were associated with increased odds of potential under-coding. Discussion: We assessed several approaches to identify individual patients in an administrative database and, subsequently, by applying HCA + k-means algorithm, we tracked coding inconsistency and potentially improved data quality. We reported consistent potential under-coding in all defined groups of comorbidities and potential factors associated with such lack of completeness. Conclusion: Our proposed methodological framework could both enhance data quality and act as a reference for other studies relying on databases with similar problems. [ABSTRACT FROM AUTHOR]

Background: Healthcare data frequently lack the specificity level needed to achieve clinical and operational objectives such as optimising bed management. Pneumonia is a disease of importance as it accounts for more bed days than any other lung disease and has a varied aetiology. The condition has a range of SNOMED CT concepts with different levels of specificity. Objective: This study aimed to quantify the importance of the specificity of an SNOMED CT concept, against well-established predictors, for forecasting length of stay for pneumonia patients. Method: A retrospective data analysis was conducted of pneumonia admissions to a tertiary hospital between 2011 and 2021. For inclusion, the primary diagnosis was a subtype of bacterial or viral pneumonia, as identified by SNOMED CT concepts. Three linear mixed models were constructed. Model One included known predictors of length of stay. Model Two included the predictors in Model One and SNOMED CT concepts of lower specificity. Model Three included the Model Two predictors and the concepts with higher specificity. Model performances were compared. Results: Sex, ethnicity, deprivation rank and Charlson Comorbidity Index scores (age-adjusted) were meaningful predictors of length of stay in all models. Inclusion of lower specificity SNOMED CT concepts did not significantly improve performance (ΔR2 = 0.41%, p =.058). SNOMED CT concepts with higher specificity explained more variance than each of the individual predictors (ΔR2 = 4.31%, p <.001). Conclusion: SNOMED CT concepts with higher specificity explained more variance in length of stay than a range of well-studied predictors. Implications: Accurate and specific clinical documentation using SNOMED CT can improve predictive modelling and the generation of actionable insights. Resources should be dedicated to optimising and assuring clinical documentation quality at the point of recording. [ABSTRACT FROM AUTHOR]

Background: Patient online access to medical records is assumed to foster patient empowerment and advance patient-centred healthcare. Since July 2020, patients in the Netherlands have been legally entitled to electronically access their medical record in general practice. Experience from pioneering countries has shown that despite high patient interest, user rates often remain low. How to best support implementation depends on individual needs and expectations of patient populations, which are as yet unknown in the Dutch context. Objective: To understand Dutch patients' needs and expectations with regard to online access to their medical record in general practice. Method: Twenty participants completed semi-structured individual interviews via video or telephone call. Transcripts of interviews underwent template analysis combining deductive and inductive coding using Atlas.ti software. Results: Patients' needs and expectations ranged across three overlapping areas: (i) prerequisites for getting online access; (ii) using online access; and (iii) the impact on interaction with healthcare providers. Patients expected benefits from online access such as better overview, empowerment and improved communication with their general practitioner but identified needs regarding technological difficulties, data privacy and complex medical language in their record. Conclusion: The concerns and obstacles participants identified point towards the need for organisational changes in general practice, for example, adjusted documentation practices, and the key role of the general practitioner and staff in promoting and facilitating online access. Implications: Implementation strategies addressing needs identified in this study may help to unlock the full potential of online access to achieve desired outcomes of patient involvement and satisfaction. [ABSTRACT FROM AUTHOR]

Individuals from a variety of backgrounds are affected by the opioid crisis. To provide optimal care for individuals at risk of opioid overdose and prevent subsequent overdoses, a more targeted response that goes beyond the traditional taxonomical diagnosis approach to care management needs to be adopted. In previous works, Graph Machine Learning and Natural Language Processing methods were used to model the products for planning and evaluating the treatment of patients with complex issues. This study proposes a methodology of partitioning patients in the opioid overdose cohort into various communities based on their patterns of service utilization (PSUs) across the continuum of care using graph community detection and applying survival analysis to predict time-to-second overdose for each of the communities. The results demonstrated that the overdose cohort is not homogeneous with respect to the determinants of risk. Moreover, the risk for subsequent overdose was quantified: there is a 51% higher chance of experiencing a second overdose for a high-risk community compared to a low-risk community. The proposed method can inform a more efficient treatment heterogeneity approach for a cohort made of diverse individuals, such as the opioid overdose cohort. It can also guide targeted support for patients at risk of subsequent overdoses. [ABSTRACT FROM AUTHOR]

Objectives Health students’ ability to utilize technology effectively is vital for improving the quality of future healthcare services. Relevant digital health education must be comprehensively integrated into training programs, continuing professional development activities, and school curricula to keep them current. This study investigated the most effective digital health approaches to enhance health students’ cognitive, affective, and psychomotor skills, thereby preparing them for the workforce. Methods A literature review was conducted by searching for articles from 2013 to 2023 in PubMed, Science Direct, ERIC, and Scopus. The search used the PICO model, focusing on experimental studies and digital learning. Results The review identified 26 studies, categorizing digital education methods into platform-based (46.2%), tools-based (30.7%), and training-based approaches (23.1%). Participants included health students (57.7%), healthcare professionals (34.6%), and a combination of both (7.7%). The content materials primarily targeted curriculum objectives (65.4%) and clinical applications (34.6%). The outcomes, classified according to Bloom’s taxonomy, were divided into cognitive (84.6%), affective (76.9%), and psychomotor (46.1%) domains. Conclusions Digital health education benefits from a variety of approaches. A platform-based approach is recommended for delivering theoretical and methodological materials, a tools-based approach for simulations, and a training-based approach for practical skills to enhance the cognitive domain. Both platform-based and training-based approaches are advised to improve the affective and psychomotor dimensions of learning. This study underscores the importance of an integrated digital learning system in health educational institutions to prepare students for evolving health systems and to improve learning outcomes and skill transfer.

Background: Patient’s privacy protection is a challenging ethical issue. The complex situation of the COVID-19 pandemic was a probable predictor of breaching confidentiality. This study aimed to assess the viewpoints of COVID-19-confirmed patients, who were hospitalized, and their healthcare providers about the compliance of different aspects of patient’s privacy.Methods: This cross-sectional study included 3433 COVID-19-confirmed patients who were hospitalized in Kerman, between 2020 and 2021, and about 1228 related physicians, nurses, and paraclinical staff. Two separate validated researcher-made questionnaires were developed, each including subscales for physical, informational, and spatial privacy, as well as a satisfaction rate of privacy protection. The data were analyzed using SPSS software version 26, with independent samples t test, Mann-Whitney-U, Kruskal Wallis, and Multiple Linear Regression tests at a 95% confidence interval.Results: The mean percentages of the patients’ privacy scores in physical, spatial, and informational areas were significantly lower (P

Clinical documentation of patient visits has changed over the last 20 years, with the increasing use of electronic records causing a seismic shift in how notes are taken. Electronic note-taking aims at reducing the time taken to document a visit, and the introduction of dot phrases, or DotPhrases, in electronic medical records is a step toward reducing the time required to update patients' charts, which might allow doctors to spend more time with their patients. DotPhrases, abbreviated phrases used in the electronic medical record, help in the simplification of note-taking and the standardization of notes. They also allow for a more comprehensive note from physicians and ensure that no information is undocumented. On the contrary, however, excessive usage of DotPhrases can lead to an excessively long and cumbersome note. This can overwhelm physicians and lead to them missing crucial information that is buried somewhere in the notes. Although there is ample research studying the benefits of DotPhrases, adequate research must also be carried out to understand their shortcomings and disadvantages. This article aims to shed some light on use of DotPhrases and to outline their advantages and disadvantages affecting patient management and care. [ABSTRACT FROM AUTHOR]

Background: Providing care to persons with complex problems is inherently difficult due to several factors, including the impacts of proximal determinants of health, treatment response, the natural emergence of comorbidities, and service system capacity to provide timely required services. Providing visibility into the dynamics of patients' engagement can help to optimize care for patients with complex problems. Method: In a previous work, graph machine learning and NLP methods were used to model the products of service system dynamics as atemporal entities, using a data model that collapsed patient encounter events across time. In this paper, the order of events is put back into the data model to provide topological depictions of the dynamics that are embodied in patients' movement across a complex healthcare system. Result: The results show that directed graphs are well suited to the task of depicting the way that the diverse components of the system are functionally coupled—or remain disconnected—by patient journeys. Conclusion: By setting the resolution on the graph topology visualization, important characteristics can be highlighted, including highly prevalent repeating sequences of service events readily interpretable by clinical subject matter experts. Moreover, this methodology provides a first step in addressing the challenge of locating potential operational problems for patients with complex issues engaging with a complex healthcare service system. [ABSTRACT FROM AUTHOR]

Background: Optimizing care for patients with complex problems entails the integration of clinically appropriate problem-specific clinical protocols, and the optimization of service-system-encompassing clinical pathways. However, alignment of service system operations with Clinical Practice Guidelines (CPGs) is far more challenging than the time-bounded alignment of procedures with protocols. This is due to the challenge of identifying longitudinal patterns of service utilization in the cross-continuum data to assess adherence to the CPGs. Method: This paper proposes a new methodology for identifying patients' patterns of service utilization (PSUs) within sparse high-dimensional cross-continuum health datasets using graph community detection. Result: The result has shown that by using iterative graph community detections, and graph metrics combined with input from clinical and operational subject matter experts, it is possible to extract meaningful functionally integrated PSUs. Conclusions: This introduces the possibility of influencing the reorganization of some services to provide better care for patients with complex problems. Additionally, this introduces a novel analytical framework relying on patients' service pathways as a foundation to generate the basic entities required to evaluate conformance of interventions to cohort-specific clinical practice guidelines, which will be further explored in our future research. [ABSTRACT FROM AUTHOR]

Healthcare organizations have a contractual obligation to the public to address population-level inequities to health services access and shed light on them. Various studies have focused on achieving equitable access to healthcare services for vulnerable patients. However, these studies do not provide a nuanced perspective based on the local reality across the full continuum of care. In previous work, graph topology was used to provide visual depictions of the dynamics of patients' movement across a complex healthcare system. Using patients' encounters data represented as a graph, this study expands on previous work and proposes a methodology to identify and quantify cohort-specific disparities in accessing healthcare services across the continuum of care. The result has demonstrated that a more nuanced approach to assessing access-to-care disparity is doable using patients' patterns of service utilization from a longitudinal cross-continuum healthcare dataset. The proposed method can be used as part of a toolkit to support healthcare organizations that wish to structure their services to provide better care to their vulnerable populations based on the local realities. This provides a first step in addressing inequities for vulnerable patients in accessing healthcare services. However, additional steps need to be considered to fully address these inequities. [ABSTRACT FROM AUTHOR]

Healthcare organizations have a contractual obligation to the public to address population-level inequities to health services access and shed light on them. Various studies have focused on achieving equitable access to healthcare services for vulnerable patients. However, these studies do not provide a nuanced perspective based on the local reality across the full continuum of care. In previous work, graph topology was used to provide visual depictions of the dynamics of patients’ movement across a complex healthcare system. Using patients’ encounters data represented as a graph, this study expands on previous work and proposes a methodology to identify and quantify cohort-specific disparities in accessing healthcare services across the continuum of care. The result has demonstrated that a more nuanced approach to assessing access-to-care disparity is doable using patients’ patterns of service utilization from a longitudinal cross-continuum healthcare dataset. The proposed method can be used as part of a toolkit to support healthcare organizations that wish to structure their services to provide better care to their vulnerable populations based on the local realities. This provides a first step in addressing inequities for vulnerable patients in accessing healthcare services. However, additional steps need to be considered to fully address these inequities.

Background: Optimizing care for patients with complex problems entails the integration of clinically appropriate problem-specific clinical protocols, and the optimization of service-system-encompassing clinical pathways. However, alignment of service system operations with Clinical Practice Guidelines (CPGs) is far more challenging than the time-bounded alignment of procedures with protocols. This is due to the challenge of identifying longitudinal patterns of service utilization in the cross-continuum data to assess adherence to the CPGs. Method: This paper proposes a new methodology for identifying patients’ patterns of service utilization (PSUs) within sparse high-dimensional cross-continuum health datasets using graph community detection. Result: The result has shown that by using iterative graph community detections, and graph metrics combined with input from clinical and operational subject matter experts, it is possible to extract meaningful functionally integrated PSUs. Conclusions: This introduces the possibility of influencing the reorganization of some services to provide better care for patients with complex problems. Additionally, this introduces a novel analytical framework relying on patients’ service pathways as a foundation to generate the basic entities required to evaluate conformance of interventions to cohort-specific clinical practice guidelines, which will be further explored in our future research.

Background: Providing care to persons with complex problems is inherently difficult due to several factors, including the impacts of proximal determinants of health, treatment response, the natural emergence of comorbidities, and service system capacity to provide timely required services. Providing visibility into the dynamics of patients’ engagement can help to optimize care for patients with complex problems. Method: In a previous work, graph machine learning and NLP methods were used to model the products of service system dynamics as atemporal entities, using a data model that collapsed patient encounter events across time. In this paper, the order of events is put back into the data model to provide topological depictions of the dynamics that are embodied in patients’ movement across a complex healthcare system. Result: The results show that directed graphs are well suited to the task of depicting the way that the diverse components of the system are functionally coupled—or remain disconnected—by patient journeys. Conclusion: By setting the resolution on the graph topology visualization, important characteristics can be highlighted, including highly prevalent repeating sequences of service events readily interpretable by clinical subject matter experts. Moreover, this methodology provides a first step in addressing the challenge of locating potential operational problems for patients with complex issues engaging with a complex healthcare service system.

Abstract Background Effective communication and information delivery enhance doctor–patient relationships, improves adherence to treatment, reduces work burden, and supports decision-making. The study developed a head and neck cancer (HNC) communication platform to support effective delivery of information about HNC treatment and improve the doctor-patient relationship. Methods This study was structured in three main phases: 1) The requirement elicitation phase sought an understanding of the HNC treatment journey and service failure points (FPs) obtained through patient/medical staff interviews and observations, along with a review of the electronic health record system; 2) The development phase involved core needs analysis, solutions development through a co-creation workshop, and validation of the solutions through focus groups; and 3) the proposed HNC communication platform was integrated with the current treatment system, and the flow and mechanism of the interacting services were structured using a service blueprint (SB). Results Twenty-two service FPs identified through interviews and observations were consolidated into four core needs, and solutions were proposed to address each need: an HNC treatment journey map, cancer survivor stories, operation consent redesign with surgical illustrations, and a non-verbal communication toolkit. The communication platform was designed through the SB in terms of the stage at which the solution was applied and the actions and interactions of the service providers. Conclusions The developed platform has practical significance, reflecting a tangible service improvement for both patients and medical staff, making it applicable in hospital settings.

Abstract Background As the healthcare sector becomes increasingly reliant on technology, it is crucial for universities to offer bachelor’s degrees in health informatics (HI). HI professionals bridge the gap between IT and healthcare, ensuring that technology complements patient care and clinical workflows; they promote enhanced patient outcomes, support clinical research, and uphold data security and privacy standards. This study aims to evaluate accredited HI academic programs in Saudi Arabia. Methods This study employed a quantitative, descriptive, cross-sectional design utilising a self-reported electronic questionnaire consisting of predetermined items and response alternatives. Probability-stratified random sampling was also performed. Result The responses rates were 39% (n = 241) for students and 62% (n = 53) for faculty members. While the participants expressed different opinions regarding the eight variables being examined, the faculty members and students generally exhibited a strong level of consensus on many variables. A notable association was observed between facilities and various other characteristics, including student engagement, research activities, admission processes, and curriculum. Similarly, a notable correlation exists between student engagement and the curriculum in connection to research, attrition, the function of faculty members, and academic outcomes. Conclusion While faculty members and students hold similar views about the institution and its offerings, certain areas of divergence highlight the distinct perspectives and priorities of each group. The perception disparity between students and faculty in areas such as admission, faculty roles, and internships sheds light on areas of improvement and alignment for universities.

This article points out deficiencies in present-day definitions of public health surveillance, which include data collection, analysis, interpretation and dissemination, but not public health action. Controlling a public health problem of concern requires a public health response that goes beyond information dissemination. It is undesirable to have public health divided into data generation processes (public health surveillance) and data use processes (public health response), managed by two separate groups (surveillance experts and policy-makers). It is time to rethink the need to modernize the definition of public health surveillance, inspired by the authors’ enhanced Data, Information, Knowledge, Intelligence and Wisdom model. Our recommendations include expanding the scope of public health surveillance beyond information dissemination to comprise actionable knowledge (intelligence); mandating surveillance experts to assist policy-makers in making evidence-informed decisions; encouraging surveillance experts to become policy-makers; and incorporating public health literacy training – from data to knowledge to wisdom – into the curricula for all public health professionals. Work on modernizing the scope and definition of public health surveillance will be a good starting point.

Background: Medical certification of cause of death (MCCD) provides valuable data regarding disease burden in a community and for formulating health policy. Inaccurate MCCDs can significantly impair the precision of national health information. Objective: To evaluate the accuracy of cause of death certificates prepared at two tertiary cancer care hospitals in Northern India during the study period (May 2018 to December 2020). Method: A retrospective observational study at two tertiary cancer care hospitals in Varanasi, India, over a period of two and a half years. Medical records and cause of death certificates of all decedents were examined. Demographic characteristics, administrative details and cause of death data were collected using the WHO recommended death certificates. Accuracy of death certification was validated by electronic medical records and errors were graded. Results: A total of 778 deaths occurred in the two centres during the study period. Of these, only 30 (3.9%) certificates were error-free; 591 (75.9%) certificates had an inappropriate immediate cause of death; 231 (29.7%) certificates had incorrectly labelled modes of death as the immediate cause of death; and 585 (75.2%) certificates had an incorrect underlying cause of death. The majority of certificates were prepared by junior doctors and were significantly associated with higher certification errors. Conclusion: A high rate of errors was identified in death certification at the cancer care hospitals during the study period. Inaccurate MCCDs related to cancers can potentially influence cancer statistics and thereby affect policy making for cancer control. Implications: This study has identified the pressing need for appropriate interventions to improve quality of certification through training of doctors. [ABSTRACT FROM AUTHOR]

Background: The Australian hospital-acquired complication (HAC) policy was introduced to facilitate negative funding adjustments in Australian hospitals using ICD-10-AM codes. Objective: The aim of this study was to determine the positive predictive value (PPV) of the ICD-10-AM codes in the HAC framework to detect hospital-acquired pneumonia in patients with cancer and to describe any change in PPV before and after implementation of an electronic medical record (EMR) at our centre. Method: A retrospective case review of all coded pneumonia episodes at the Peter MacCallum Cancer Centre in Melbourne, Australia spanning two time periods (01 July 2015 to 30 June 2017 [pre-EMR period] and 01 September 2020 to 28 February 2021 [EMR period]) was performed to determine the proportion of events satisfying standardised surveillance definitions. Results: HAC-coded pneumonia occurred in 3.66% (n = 151) of 41,260 separations during the study period. Of the 151 coded pneumonia separations, 27 satisfied consensus surveillance criteria, corresponding to an overall PPV of 0.18 (95% CI: 0.12, 0.25). The PPV was approximately three times higher following EMR implementation (0.34 [95% CI: 0.19, 0.53] versus 0.13 [95% CI: 0.08, 0.21]; p =.013). Conclusion: The current HAC definition is a poor-to-moderate classifier for hospital-acquired pneumonia in patients with cancer and, therefore, may not accurately reflect hospital-level quality improvement. Implementation of an EMR did enhance case detection, and future refinements to administratively coded data in support of robust monitoring frameworks should focus on EMR systems. Implications: Although ICD-10-AM data are readily available in Australian healthcare settings, these data are not sufficient for monitoring and reporting of hospital-acquired pneumonia in haematology-oncology patients. [ABSTRACT FROM AUTHOR]

Objective: This article describes the first digital clinical information system tailored to support the operational needs of a forensic unit in Greece and to maintain its archives. Method: The development of our system was initiated towards the end of 2018, as a close collaboration between the Medical School of the University of Crete and the Forensic Medicine Unit of the University Hospital of Heraklion, Crete, where forensic pathologists assumed active roles during the specification and testing of the system. Results: The final prototype of the system was able to manage the life cycle of any forensic case by allowing users to create new records, assign them to forensic pathologists, upload reports, multimedia and any required files; mark the end of processing, issue certificates or appropriate legal documents, produce reports and generate statistics. For the first 4 years of digitised data (2017–2021), the system recorded 2936 forensic examinations categorised as 106 crime scene investigations, 259 external examinations, 912 autopsies, 102 post-mortem CT examinations, 804 histological examinations, 116 clinical examinations, 12 anthropological examinations and 625 embalmings. Conclusion: This research represents the first systematic effort to record forensic cases through a digital clinical information system in Greece, and to demonstrate its effectiveness, daily usability and vast potential for data extraction and for future research. [ABSTRACT FROM AUTHOR]

Background: The percentage of total body surface area (%TBSA) burned and burn depth provide valuable information on burn injury severity. Objective: This study investigated the concordance between The International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) codes and expert burn clinicians in assessing burn injury severity. Method: We conducted a retrospective population-based review of all patients who sustained a burn injury between July 1, 2009, and June 30, 2019, requiring admission into a specialist burn service across Australia and New Zealand. The %TBSA burned (including the percentage of full thickness burns) recorded by expert burn clinicians within the Burns Registry of Australia and New Zealand (BRANZ) were compared to ICD-10-AM coding. Results: 20,642 cases (71.5%) with ICD-10-AM code data were recorded. Overall, kappa scores (95% confidence interval [CI]) for burn size ranged from 0.64 (95% CI 0.63–0.66) to 0.86 (95% CI 0.78–0.94) indicating substantial to almost perfect agreement across all %TBSA groups. When stratified by depth, the lowest agreement was observed for < 10% TBSA and < 10% full thickness (kappa 0.03; 95% CI 0.02–0.04) and the highest agreement was observed for burns of ≥ 90% TBSA and ≥ 90% full thickness (kappa 0.72; 95% CI 0.58–0.85). Conclusion: Overall, there was substantial agreement between the BRANZ and ICD-10-AM coded data for %TBSA classification. When %TBSA classification was stratified by burn depth, greater agreement was observed for larger and deeper burns compared with smaller and superficial burns. Implications: Greater consistency in the classification of burns is needed. [ABSTRACT FROM AUTHOR]

Background: Historically, national programs for collecting stroke data in Australia required the use of multiple online tools. Clinicians were required to enter overlapping variables for the same patient in the different databases. From 2013 to 2016, the Australian Stroke Data Tool (AuSDaT) was built as an integrated data management solution. Objective: In this article, we have described the development, implementation, and evaluation phases of establishing the AuSDaT. Method: In the development phase, a governance structure with representatives from different data collection programs was established. Harmonisation of data variables, drawn from six programs used in hospitals for monitoring stroke care, was facilitated through creating a National Stroke Data Dictionary. The implementation phase involved a staged deployment for two national programs over 12 months. The evaluation included an online survey of people who had used the AuSDaT between March 2018 and May 2018. Results: By July 2016, data entered for an individual patient was, for the first time, shared between national programs. Overall, 119/422 users (90% female, 61% aged 30–49 years, 57% nurses) completed the online evaluation survey. The two most positive features reported about the AuSDaT were (i) accessibility of the system (including simultaneous user access), and (ii) the ability to download reports to benchmark local data against peer hospitals or national performance. More than three quarters of respondents (n = 92, 77%) reported overall satisfaction with the data collection tool. Conclusion: The AuSDaT reduces duplication and enables users from different national programs for stroke to enter standardised data into a single system. Implications: This example may assist others who seek to establish a harmonised data management solution for different disease areas where multiple programs of data collection exist. The importance of undertaking continuous evaluation of end-users to identify preferences and aspects of the tool that are not meeting current requirements were illustrated. We also highlighted the opportunities to increase interoperability, utility, and facilitate the exchange of accurate and meaningful data. [ABSTRACT FROM AUTHOR]

Background: Administrative data are used extensively for research purposes, but there remains limited information on the quality of these data for identifying comorbidities related to stroke. Objective: To compare the prevalence of comorbidities of stroke identified using International Classification Diseases, Australian Modification (ICD-10-AM) or Anatomical Therapeutic Chemical codes, with those from (i) self-reported data and (ii) published studies. Method: The cohort included patients with stroke or transient ischaemic attack admitted to hospitals (2012–2016; Victoria and Queensland) in the Australian Stroke Clinical Registry (N = 26,111). Data were linked with hospital and pharmaceutical datasets to ascertain comorbidities using published algorithms. The sensitivity, specificity, and positive predictive value of these comorbidities were compared with survey responses from 623 patients (reference standard). An indirect comparison was also performed with clinical data from published stroke studies. Results: The sensitivity of hospital ICD-10-AM data was poor for most comorbidities, except for diabetes (93.0%). Specificity was excellent for all comorbidities (87–96%), except for hypertension (70.5%). Compared to published stroke studies (3 clinical trials and 1 incidence study), the prevalence of diabetes and atrial fibrillation in our cohort was similar using ICD-10-AM codes, but lower for dyslipidaemia and anxiety/depression. Whereas in the pharmaceutical dispensing data, the sensitivity was excellent for dyslipidaemia (94%) and modest for anxiety/depression (77%). In the pharmaceutical data, specificity was modest for hypertension (78%) and anxiety or depression (76%), but specificity was poor for dyslipidaemia (19%) and heart disease (46%). Conclusion: Variation was observed in the reporting of comorbidities of stroke in administrative data, and consideration of multiple sources of data may be necessary for research. Further work is needed to improve coding and clinical documentation for reporting of comorbidities in administrative data. [ABSTRACT FROM AUTHOR]

Background: The professional identity and motivation of qualified health information managers (HIMs) is largely unexplored. Objectives: A larger study has investigated the motivators of HIMs in the construction of their professional identity and associated relationships to job satisfaction and engagement with their profession. The aims of this component of the study were to: (i) identify and analyse the characteristics of members of the profession who have different motivation profiles; (ii) obtain HIMs' perspectives on their professional identity; and (iii) measure correlation between HIMs' professional identity and different motivating factors. Method: A cross-sectional study design, with a convergent mixed-methods approach to data collection was employed. An online survey was administered to the 1985, 1995, 2005 and 2015 Australian health information management and medical record administration graduate cohorts from one university in Victoria. Results: Response rate: 72.7% (n = 72). There were no statistically significant correlations between the HIMs' motivation profile and professional identity. The HIMs were largely motivated by a need for achievement (striving for excellence) and continuous improvement; maintained high standards of work quality (95.8%); valued their work (94.4%) and work collaborations (84.7%); satisfactorily applied skills-knowledge (94%); demonstrated a very strong professional association (92% were proud to belong to the profession). Key factors in motivation that were consistently reported by members of all cohorts in the open-ended questions were as follows: intrinsic motivation; colleagues and teamwork; the variety of work performed; and contribution to the bigger picture. Overall, and notwithstanding between-cohort differences: 65.3% confidently directed others, 45.8% aspired to leadership and 38% actively networked. They related difficulty in explaining the profession to outsiders. Conclusion: There was no correlation between motivation profile and professional identity. Significantly, the HIMs demonstrated exceptionally strong positive professional identity, reflected particularly in pride in membership of the profession and their belief in the importance of their professional work. [ABSTRACT FROM AUTHOR]

Context: Access to real-time data that provide accurate and timely information about the status and extent of disease spread could assist management of the COVID-19 pandemic and inform decision-making. Aim: To demonstrate our experience with regard to implementation of technical and architectural infrastructure for a near real-time electronic health record-based surveillance system for COVID-19 in Iran. Method: This COVID-19 surveillance system was developed from hospital information and electronic health record (EHR) systems available in the study hospitals in conjunction with a set of open-source solutions; and designed to integrate data from multiple resources to provide near real-time access to COVID-19 patients' data, as well as a pool of health data for analytical and decision-making purposes. Outcomes: Using this surveillance system, we were able to monitor confirmed and suspected cases of COVID-19 in our population and to automatically notify stakeholders. Based on aggregated data collected, this surveillance system was able to facilitate many activities, such as resource allocation for hospitals, including managing bed allocations, providing and distributing equipment and funding, and setting up isolation centres. Conclusion: Electronic health record systems and an integrated data analytics infrastructure are effective tools to enable policymakers to make better decisions, and for epidemiologists to conduct improved analyses regarding COVID-19. Implications: Improved quality of clinical coding for better case finding, improved quality of health information in data sources, data-sharing agreements, and increased EHR coverage in the population can empower EHR-based COVID-19 surveillance systems. [ABSTRACT FROM AUTHOR]

Background: Sepsis is the world's leading cause of death and its detection from a range of data and coding sources, consistent with consensus clinical definition, is desirable. Objective: To evaluate the performance of three coding definitions (explicit, implicit, and newly proposed synchronous method) for sepsis derived from administrative data compared to a clinical reference standard. Method: Extraction of administrative coded data from Australian metropolitan teaching hospital with 25,000 annual overnight admissions compared to clinical review of medical records; 313 (27.9%) randomly selected adult multi-day stay hospital separations from 1,123 separations with acute infection during July 2019. Estimated prevalence and performance metrics, including positive (PPV) and negative predictive values (NPV), and area under the receiver operator characteristic curve (ROC). Results: Clinical prevalence of sepsis was estimated at 10.7 (95% CI = 10.3–11.3) per 100 separations, and mortality rate of 11.6 (95% CI = 10.3–13.0) per 100 sepsis separations. Explicit method for case detection had high PPV (93.2%) but low NPV (55.8%) compared to the standard implicit method (74.1 and 66.3%, respectively) and proposed synchronous method (80.4% and 80.0%) compared to a standard clinical case definition. ROC for each method: 0.618 (95% CI = 0.538–0.654), 0.698 (95% CI = 0.648–0.748), and 0.802 (95% CI = 0.757–0.846), respectively. Conclusion: In hospitalised Australian patients with community-onset sepsis, the explicit method for sepsis case detection underestimated prevalence. Implicit methods were consistent with consensus definition for sepsis, and proposed synchronous method had better performance. [ABSTRACT FROM AUTHOR]

Background: The International Classification of Diseases (ICD) is widely used by clinical coders worldwide for clinical coding morbidity data into administrative health databases. Accordingly, hospital data quality largely depends on the coders' skills acquired during ICD training, which varies greatly across countries. Objective: To characterise the current landscape of international ICD clinical coding training. Method: An online questionnaire was created to survey the 194 World Health Organization (WHO) member countries. Questions focused on the training provided to clinical coding professionals. The survey was distributed to potential participants who met specific criteria, and to organisations specialised in the topic, such as WHO Collaborating Centres, to be forwarded to their representatives. Responses were analysed using descriptive statistics. Results: Data from 47 respondents from 26 countries revealed disparities in all inquired topics. However, most participants reported clinical coders as the primary person assigning ICD codes. Although training was available in all countries, some did not mandate training qualifications, and those that did differed in type and duration of training, with college or university degree being most common. Clinical coding certificates most frequently entailed passing a certification exam. Most countries offered continuing training opportunities, and provided a range of support resources for clinical coders. Conclusion: Variability in clinical coder training could affect data collection worldwide, thus potentially hindering international comparability of health data. Implications: These findings could encourage countries to improve their resources and training programs available for clinical coders and will ultimately be valuable to the WHO for the standardisation of ICD training. [ABSTRACT FROM AUTHOR]

While the importance of Electronic Health Records (EHR) interoperability is widely recognised in the healthcare digitalisation context, its optimal governance structure remains controversial, requiring further research. Through the rapid literature review of 32 articles retrieved from PubMed and EBSCO, 47 distinct factors under ten categories were established. The three most cited factors in the reviewed 32 articles were “Robust inter-institutional connections, trust, and the technologies to ensure security”, “Legal adaptations to the evolving digitalisation needs”, and “Standardisation of terminologies and codes, and harmonised data structure”. This review contributes preliminary results for the ongoing research to optimise EHR interoperability governance. [ABSTRACT FROM AUTHOR]

Background: Effective communication and information delivery enhance doctor–patient relationships, improves adherence to treatment, reduces work burden, and supports decision-making. The study developed a head and neck cancer (HNC) communication platform to support effective delivery of information about HNC treatment and improve the doctor-patient relationship. Methods: This study was structured in three main phases: 1) The requirement elicitation phase sought an understanding of the HNC treatment journey and service failure points (FPs) obtained through patient/medical staff interviews and observations, along with a review of the electronic health record system; 2) The development phase involved core needs analysis, solutions development through a co-creation workshop, and validation of the solutions through focus groups; and 3) the proposed HNC communication platform was integrated with the current treatment system, and the flow and mechanism of the interacting services were structured using a service blueprint (SB). Results: Twenty-two service FPs identified through interviews and observations were consolidated into four core needs, and solutions were proposed to address each need: an HNC treatment journey map, cancer survivor stories, operation consent redesign with surgical illustrations, and a non-verbal communication toolkit. The communication platform was designed through the SB in terms of the stage at which the solution was applied and the actions and interactions of the service providers. Conclusions: The developed platform has practical significance, reflecting a tangible service improvement for both patients and medical staff, making it applicable in hospital settings. [ABSTRACT FROM AUTHOR]

Background: As the healthcare sector becomes increasingly reliant on technology, it is crucial for universities to offer bachelor's degrees in health informatics (HI). HI professionals bridge the gap between IT and healthcare, ensuring that technology complements patient care and clinical workflows; they promote enhanced patient outcomes, support clinical research, and uphold data security and privacy standards. This study aims to evaluate accredited HI academic programs in Saudi Arabia. Methods: This study employed a quantitative, descriptive, cross-sectional design utilising a self-reported electronic questionnaire consisting of predetermined items and response alternatives. Probability-stratified random sampling was also performed. Result: The responses rates were 39% (n = 241) for students and 62% (n = 53) for faculty members. While the participants expressed different opinions regarding the eight variables being examined, the faculty members and students generally exhibited a strong level of consensus on many variables. A notable association was observed between facilities and various other characteristics, including student engagement, research activities, admission processes, and curriculum. Similarly, a notable correlation exists between student engagement and the curriculum in connection to research, attrition, the function of faculty members, and academic outcomes. Conclusion: While faculty members and students hold similar views about the institution and its offerings, certain areas of divergence highlight the distinct perspectives and priorities of each group. The perception disparity between students and faculty in areas such as admission, faculty roles, and internships sheds light on areas of improvement and alignment for universities. [ABSTRACT FROM AUTHOR]

The benefits of research data sharing abound in the literature. However, some factors define how researchers and clinicians approach the challenges surrounding sharing human movement health research data. To describe the perceptions of human movement researchers and clinicians on the barriers and facilitators to research data sharing in Africa. A qualitative descriptive design with a purposive sampling method was used. In-depth interviews with human movement researchers and clinicians across Africa were conducted online via Microsoft Teams. Sixteen (n = 16) participants took part in this study. This sample size was representative of East, West, Northern, and Southern Africa. Efforts made to engage with participants in Central Africa were unsuccessful. Five themes emerged: 1) the researcher-clinician gap; 2) technological pros and cons in Africa; 3) cost matters; 4) bureaucracy and ethical factors; and 5) the unique African perspective. Mainly, barriers rather than facilitators to data sharing exist among African human movement researchers and clinicians. There needs to be a societal and psychological shift through reorientation to encourage data sharing among African human movement researchers and clinicians. [ABSTRACT FROM AUTHOR]

BACKGROUND Electronic health records (EHR) have become commonplace in medicine. A disconnect between developers and users while creating the interface often fails to create a product that captures clinical workflow, and issues become apparent with implementation. Optimization allows collaboration of clinicians and informaticists after implementation, but documentation of success has only been at the institutional level. METHODS A 4-month, department-wide EHR optimization was conducted with information technology (IT). Optimizations were developed from an intensive quality improvement process involving all levels of clinicians and clinical staff. The optimizations were then categorized as accommodations (department adjusted workflow to EHR), creations (IT developed new workflows within EHR), discoveries (department found workflows within EHR), and modifications (IT changed workflows within EHR). Departmental productivity, defined as number of visits, charges, and payments, was standardized to ratios prior to the COVID-19 pandemic and evaluated by Taylor’s change point analysis. Significant improvements were defined as shifts (change points), trends (5 or more consecutive values above/below the mean), and values outside 95% CIs. RESULTS The 124 optimizations were categorized as 43 accommodations, 13 creations, 54 discoveries, and 14 modifications. Productivity ratios of monthly charges (0.74 to 1.28) and payments (0.83 to 1.58) significantly improved with the optimization efforts. Monthly visit ratios increased (0.65 to 0.98) but did not change significantly. CONCLUSION Departmental collaboration with organizational IT for EHR optimization focused on detailed analysis of how workflows can impact productivity. Discovery optimization predominance indicates many solutions to EHR usability problems were already in the system. A large proportion of accommodation optimizations reinforced the need for better developer-user collaboration before implementation. [ABSTRACT FROM AUTHOR]

This study examines the factors influencing users’ intention to continue using mobile medical apps within the framework of the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Through a combination of questionnaire surveys and interviews, the research finds that doctor-patient trust, Performance Expectancy (PE), social influence, and facilitating conditions significantly impact users’ intention to utilize mobile medical apps. Furthermore, the study reveals the moderating effect of doctor-patient trust on social influence, indicating an increased trust level during the epidemic, attributed to positive media coverage, complimentary medical services, and risk-sharing initiatives. These results provide valuable insights for the field of internet healthcare, COVID-19 response strategies, health information management, and the advancement of digital health technologies, spotlighting the pivotal roles of trust, PE, and social influence in fostering sustained engagement with mobile health apps.

Objectives: Recognition of the cognitive status of patients is important so that care can be tailored accordingly. The objective of this integrative review was to report on the current practices that acute care hospitals use to identify people with cognitive impairment and how information about cognition is managed within the healthcare record as well as the approaches required and recommended by policies. Methods: Following Whittemore & Knafl’s five-step method, we systematically searched Medline, CINAHL, and Scopus databases and various grey literature sources. Articles relevant to the programs that have been implemented in acute care hospitals regarding the identification of cognitive impairment and management of cognition information were included. The Mixed Methods Appraisal Tool and AACODS (Authority, Accuracy, Coverage, Objectivity, Date, Significance) Checklist were used to evaluate the quality of the studies. Thematic analysis was used to present and synthesise results. This review was pre-registered on PROSPERO ( CRD42022343577). Results: Twenty-two primary studies and ten government/industry publications were included in the analysis. Findings included gaps between practice and policy. Although identification of cognitive impairment, transparency of cognition information, and interaction with patients, families, and carers (if appropriate) about this condition were highly valued at a policy level, sometimes in practice, cognitive assessments were informal, patient cognition information was not recorded, and interactions with patients, families, and carers were lacking. Discussion: By incorporating cognitive assessment, developing an integrated information management system using information technology, establishing relevant laws and regulations, providing education and training, and adopting a national approach, significant improvements can be made in the care provided to individuals with cognitive impairment.

Background Technology reduces the nursing workload, improve the quality care processes, patient’s safety, and avoid staff burnout. Innovative technologies are disrupting healthcare systems by improving the efficiency of processes and management. There is a discussion on the benefits, challenges, and barriers of these technologies and considering human factors of nursing management. The aim was to analyze the influence of technologies on the distribution of workload for nursing care management. Methods An integrative literature review was performed. Four databases were searched: Scopus, Scielo, PUBMED, and CINALH following PRISMA guidelines. Articles published from January 2016 to December 2020, published in English, Spanish and Portuguese were included. Studies were excluded when they were not original research, did not met the quality criteria or they did not answer the research questions. Quality appraisal was performed using the Crowe Critical Appraisal Tool version 1.4 (CCAT). Two reviewers independently examined the title and abstract for eligibility according to the inclusion and exclusion criteria. Results 2818 potentially relevant articles were found, but once the inclusion and exclusion criteria in the abstracts were analyzed, 177 remained for evaluation. After following the PRISMA Guidelines, 35 studies were included in the review. Three categories were identified: Nursing workload; Information technologies and technological means for management; Technology acceptance. Conclusions Technology has the potential to improve care management by estimating nurse workload in ICUs and non-critical units, but scientific evidence is more detailed in the former type of services. The literature provides insights about the factors that factors and the barriers that promote the technology acceptance and usability. We did not find studies comparing technologies and no scientific evidence proving improvements in care.

Objective: In the age of digital transformation, there is a need for a sustainable information management vision in health. Understanding the accumulation of health information management (HIM) knowledge from the past to the present and building a new vision to meet this need reveals the importance of understanding the available scientific knowledge. With this research, it is aimed to examine the scientific documents of the last 40 years of HIM literature with a holistic approach using science mapping techniques and to guide future research. Methods: This study used a bibliometric analysis method for science mapping. Co-citation and co-occurrence document analyses were performed on 630 academic publications selected from the Web of Science core collection (WoSCC) database using the keyword "Health Information Management" and inclusion criteria. The analyses were performed using the R-based software Bibliometrix (Version 4.0; K-Synth Srl), Python (Version 3.12.1; The Python Software Foundation), and Microsoft® Excel® 2016. Results: Co-occurrence analyses revealed the themes of personal health records, clinical coding and data quality, and health information management. The HIM theme consisted of five subthemes: "electronic records", "medical informatics", "e-health and telemedicine", "health education and awareness", and "health information systems (HISs)". As a result of the co-citation analysis, the prominent themes were technology acceptance, standardized clinical coding, the success of HISs, types of electronic records, people with HIM, health informatics used by consumers, e-health, e-mobile health technologies, and countries' frameworks and standards for HISs. Conclusions: This comprehensive bibliometric study shows that structured information can be helpful in understanding research trends in HIM. This study identified critical issues in HIM, identified meaningful themes, and explained the topic from a holistic perspective for all health system actors and stakeholders who want to work in the field of HIM. [ABSTRACT FROM AUTHOR]