Can proactive support prevent unscheduled care? A controlled observational retrospective cohort study in cancer patients in Scotland.

INTRODUCTION: Preventative spend is a global health and social care strategy. Improving Cancer Journeys (ICJ) is a proactive, holistic, multidisciplinary project consistent with this agenda, currently being rolled out across Scotland and parts of UK. ICJ helps people with cancer access whatever support they need to mitigate their most pressing concerns. This study hypothesised that ICJ service users should subsequently use less unscheduled care than matched cohorts not using ICJ. METHODS: Retrospective observational cohort study using linked national datasets. N = 1,214 ICJ users in Glasgow were matched for age, sex, deprivation, cancer type, stage, and diagnosis year to two control groups: 1. Cancer patients from Glasgow before ICJ (pre-2014), 2. Cancer patients from rest of Scotland during study period (2014-2018). Cancer registrations were linked for 12-month baseline and study periods to: NHS24 calls, A&E admissions, inpatient hospital admissions, unscheduled care, number & cost of psychotropic prescriptions. Per-person mean service uses were compared between groups. RESULTS: There was a significant increase in NHS24 calls in the ICJ group (0.36 per person vs. -0.03 or 0.35), more and longer A&E attendances in ICJ (0.37 per person vs. 0.19 or 0.26; 2.19 h per person vs. 0.81-0.92 h), more and longer hospital admissions in ICJ (4.25 vs. 2.59 or 2.53; 12.05 days vs. 8.37 or 8.64), more care pathways involving more steps in ICJ (0.77 spells vs. 0.39 or 0.57; 1.88 steps vs. 1.56 or 1.21), more psychotropic drug prescriptions and higher costs in ICJ (1.88 prescription vs. 1.56 or 1.21; £9.51 vs. £9.57 or £6.95) in comparison to both control groups. DISCUSSION: ICJ users sourced significantly more unscheduled care than matched cohorts. These findings were consistent with much of the comparable literature examining the impact of non-health interventions on subsequent health spend. They also add to the growing evidence showing that ICJ reached its intended target, those with the greatest need. Together these findings raise the possibility that those choosing to use ICJ may also be self-identifying as a cohort of people more likely to use unscheduled care in future. This needs to be tested prospectively, because this understanding would be very helpful for health and social care planners in all countries where proactive holistic services exist.

Deductive Care Methodology: Describing and testing modes of care research.

OBJECTIVE: Define the modes of procedure of the Deductive Care Methodology (DCM) in the generation of knowledge about person's health care. METHODOLOGY: Design and test of the DCM modes based on three phases: mapping of the MDC, generation of models from this methodology and testing of the models through studies in a clinical context. RESULTS: The MDC presents five levels of abstraction with three modes broken down to 16 types. The modes are: Philosophical Mode to conceptualize and obtain generalities about reality, Mathematical Mode to operate with generalities, and Physical Mode to operationally verify, validating the results and the predictive capacity of the model. This MDC allows the creation of three models: Knowledge Model about Person Care, an ontology of care, Vulnerability Model about the person and Taxonomic Triangulation Model for knowledge management. All models generate products for computational knowledge management. In addition, the models are applied in teaching and generate research with more than a hundred participations in conferences and journals, of which five impact publications (from 2008 to 2022) classified in the categories of Nursing and Informatics are analysed. CONCLUSIONS: The MDC collects prior knowledge to work with certainties, evidence and applying inferences that do not depend on the number of cases or inductive designs. This research presents a formal structure of the MDC with an interdisciplinary orientation between Health Sciences and Computer Sciences.

Development of a communication platform for patients with head and neck cancer for effective information delivery and improvement of doctor-patient relationship: application of treatment journey-based service blueprint.

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.

Perceptions of students and faculty on NCAAA-accredited health informatics programs in Saudi Arabia: an evaluative study.

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.

Improving Anesthesia Start Time Documentation Through a Departmental Education Initiative at Yale New Haven Hospital, New Haven, United States.

Background Reimbursement for anesthetic services in the United States utilizes a formula that incorporates procedural and patient factors with total anesthesia time. According to the Centers for Medicare & Medicaid Services and the American Society of Anesthesiologists, the period of billable time starts when the anesthesia practitioner assumes care of the patient and may include transport to the operating room from the preoperative holding area. In this report on a quality improvement effort, we implemented a departmental education initiative aimed at improving the accuracy of anesthesia start-time documentation. Methods Utilizing de-identified, internal data on surgical procedures at Yale New Haven Hospital (YNHH), New Haven, United States, the difference between documented anesthesia start and patient in-room time was determined for all cases. Those with a difference between 0-1 minute were assumed "likely underbilled," and the total revenue lost for these cases was estimated using a weighted average of institutional reimbursement per unit of time. A monthly, department-wide educational email was then introduced to inform practitioners about the guidelines around start-time documentation, and the percentage of "likely underbilled" cases and lost revenue estimates trended over a one-year period. Results Baseline data in December 2020 showed that of the 6,877 total surgical cases requiring anesthesia at YNHH, 55.1% (N=3,790) had an anesthesia start to in-room time of 0-1 minute, which were considered "likely underbilled." The average start-to-in-room time for properly recorded cases (44.9%, N=3,087) was 4.42 minutes. The baseline revenue lost in December 2020 for underbilled cases was estimated at $52,302. Over the one-year quality improvement initiative, the proportion of underbilled cases showed a downward trend, decreasing to 29.2% of total cases by November 2021. The estimate of revenue lost due to underbilling also showed a downward trend, decreasing to $29,300 in November 2021. Conclusion This quality improvement study demonstrated that a relatively simple, department-wide educational email sent monthly correlated with an improvement in anesthesia start-time documentation accuracy and a reduction in estimated revenue lost to underbilling over a one-year period.

[Artificial intelligence in intensive care medicine]. / Künstliche Intelligenz in der Intensivmedizin.

The integration of artificial intelligence (AI) into intensive care medicine has made considerable progress in recent studies, particularly in the areas of predictive analytics, early detection of complications, and the development of decision support systems. The main challenges remain availability and quality of data, reduction of bias and the need for explainable results from algorithms and models. Methods to explain these systems are essential to increase trust, understanding, and ethical considerations among healthcare professionals and patients. Proper training of healthcare professionals in AI principles, terminology, ethical considerations, and practical application is crucial for the successful use of AI. Careful assessment of the impact of AI on patient autonomy and data protection is essential for its responsible use in intensive care medicine. A balance between ethical and practical considerations must be maintained to ensure patient-centered care while complying with data protection regulations. Synergistic collaboration between clinicians, AI engineers, and regulators is critical to realizing the full potential of AI in intensive care medicine and maximizing its positive impact on patient care. Future research and development efforts should focus on improving AI models for real-time predictions, increasing the accuracy and utility of AI-based closed-loop systems, and overcoming ethical, technical, and regulatory challenges, especially in generative AI systems.

Use of family planning information by primary healthcare clinic managers in South Africa.

BACKGROUND: Routine family planning data in South Africa are managed using a routine health information system, which facilitates data collection, storage, processing, presentation and dissemination. Healthcare providers generate data daily as they carry out their duties. The information generated should be used for planning and evaluating health program performance and policy development. OBJECTIVE: To explore the use of family planning information by primary healthcare (PHC) clinic managers in South Africa. METHOD: A qualitative descriptive exploratory study was carried out in 11 PHC clinics in Tshwane District. Individual semi-structured interviews were conducted with 11 clinic managers. The data were analysed using a thematic analysis approach. RESULTS: Managers used the information to disseminate performance and feedback, monitor the program's performance and make decisions to improve the family planning service. However, they experienced challenges that hampered the effective use of the information. CONCLUSION: The use of family planning information is critical for improving the performance of the program. The clinics need sufficient skilled healthcare providers who are able to provide comprehensive family planning and generate accurate and reliable information that can be used to improve the service. Collaboration between the private and public sectors is critical in monitoring the program's performance.

A framework for understanding an open scientific community using automated harvesting of public artifacts.

Background: The Observational Health Data Sciences and Informatics (OHDSI) community has emerged as a leader in observational research on real-world clinical data for promoting evidence for healthcare and decision-making. The community has seen rapid growth in publications, citations, and the number of authors. Components of its successful uptake have been attributed to an open science and collaborative culture for research and development. Investigating the adoption of OHDSI as a field of study provides an opportunity to understand how communities embrace new ideas, onboard new members, and enhance their impact. Objective: To track, study, and evaluate an open scientific community's growth and impact. Method: We present a modern architecture leveraging open application programming interfaces to capture publicly available data (PubMed, YouTube, and EHDEN) on open science activities (publication, teaching, and engagement). Results: Three interactive dashboard were implemented for each publicly available artifact (PubMed, YouTube, and EHDEN). Each dashboard provides longitudinal summary analysis and has a searchable table, which differs in the available features related to each public artifact. Conclusion: We discuss the insights enabled by our approach to monitor the growth and impact of the OHDSI community by capturing artifacts of learning, teaching, and creation. We share the implications for different users based on their functional needs. As other scientific networks adopt open-source frameworks, our framework serves as a model for tracking the growth of their community, driving the perception of their development, engaging their members, and attaining higher impact.

Public health surveillance and the data, information, knowledge, intelligence and wisdom paradigm.

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.

En este artículo se señalan las deficiencias de las definiciones actuales de la vigilancia de salud pública, que incluyen la recopilación, el análisis, la interpretación y la difusión de los datos, pero no las medidas de salud pública. El control de un problema de salud pública de interés exige una respuesta de salud pública que vaya más allá de la difusión de información. No es deseable que la salud pública esté dividida por un lado en procesos de generación de datos (vigilancia de salud pública) y por otro en procesos de uso de datos (respuesta de salud pública), gestionados por dos grupos diferentes (expertos en vigilancia y responsables de la formulación de políticas). Ha llegado el momento de replantear la necesidad de modernizar la definición de la vigilancia de salud pública tomando como referencia el modelo mejorado de Datos, Información, Conocimiento, Inteligencia y Sabiduría de los autores. Entre las recomendaciones que se proponen se encuentran las de ampliar el alcance de la vigilancia de salud pública más allá de la difusión de información para que incluya también el conocimiento aplicable (inteligencia); instar a los expertos en vigilancia a que presten ayuda a los responsables de la formulación de políticas en la toma de decisiones basadas en la evidencia; alentar a los expertos en vigilancia a que se conviertan en responsables de la formulación de políticas; e incorporar la formación en conocimientos básicos de salud pública (desde los datos hasta los conocimientos y la sabiduría) en los planes de estudio de todos los profesionales de la salud pública. Un buen punto de partida será trabajar en la modernización del alcance y la definición de la vigilancia de salud pública.

Este artigo aponta deficiências nas definições atuais de vigilância em saúde pública, que incluem coleta, análise, interpretação e disseminação de dados, mas não ações de saúde pública. O controle de um problema preocupante de saúde pública exige uma resposta de saúde pública que vá além da disseminação de informações. A saúde pública não deve ser dividida em processos de geração de dados (vigilância em saúde pública) e processos de uso de dados (resposta de saúde pública) gerenciados por dois grupos distintos (especialistas em vigilância e formuladores de políticas). É hora de repensar a necessidade de modernizar a definição de vigilância em saúde pública, inspirada no modelo aprimorado de Dados, Informações, Conhecimento, Inteligência e Sabedoria dos autores. Nossas recomendações incluem: expansão do escopo da vigilância em saúde pública para além da disseminação de informações, de modo a abranger conhecimentos acionáveis (inteligência); obrigatoriedade de que os especialistas em vigilância auxiliem os formuladores de políticas na tomada de decisões baseadas em evidências; incentivo para que os especialistas em vigilância se tornem formuladores de políticas; e incorporação de capacitação em letramento em saúde pública (partindo dos dados para o conhecimento e em seguida para a sabedoria) nos currículos de todos os profissionais de saúde pública. O trabalho de modernizar o escopo e a definição de vigilância em saúde pública será um bom ponto de partida.

Machine learning -based decision support framework for CBRN protection.

Detecting chemical, biological, radiological and nuclear (CBRN) incidents is a high priority task and has been a topic of intensive research for decades. Ongoing technological, data processing, and automation developments are opening up new potentials in CBRN protection, which has become a complex, interdisciplinary field of science. According to it, chemists, physicists, meteorologists, military experts, programmers, and data scientists are all involved in the research. The key to effectively enhancing CBRN defence capabilities is continuous and targeted development along a well-structured concept. Our study highlights the importance of predictive analytics by providing an overview of the main components of modern CBRN defence technologies, including a summary of the conceptual requirements for CBRN reconnaissance and decision support steps, and by presenting the role and recent opportunities of information management in these processes.

Identification and information management of cognitive impairment of patients in acute care hospitals: An integrative review.

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.

Assessing the performance of the family folder system for collecting community-based health information in Tigray Region, North Ethiopia: a capture-recapture study.

OBJECTIVES: To assess completeness and accuracy of the family folder in terms of capturing community-level health data. STUDY DESIGN: A capture-recapture method was applied in six randomly selected districts of Tigray Region, Ethiopia. PARTICIPANTS: Child health data, abstracted from randomly selected 24 073 family folders from 99 health posts, were compared with similar data recaptured through household survey and routine health information made by these health posts. PRIMARY AND SECONDARY OUTCOME MEASURES: Completeness and accuracy of the family folder data; and coverage selected child health indicators, respectively. RESULTS: Demographic data captured by the family folders and household survey were highly concordant, concordance correlation for total population, women 15-49 years age and under 5-year child were 0.97 (95% CI 0.94 to 0.99, p<0.001), 0.73 (95% CI 0.67 to 0.88) and 0.91 (95% CI 0.85 to 0.96), respectively. However, the live births, child health service indicators and child health events were more erratically reported in the three data sources. The concordance correlation among the three sources, for live births and neonatal deaths was 0.094 (95% CI -0.232 to 0.420) and 0.092 (95% CI -0.230 to 0.423) respectively, and for the other parameters were close to 0. CONCLUSION: The family folder system comprises a promising development. However, operational issues concerning the seamless capture and recording of events and merging community and facility data at the health centre level need improvement.

Impact of the Narcotics Information Management System on Opioid Use Among Outpatients With Musculoskeletal and Connective Tissue Disorders: Quasi-Experimental Study Using Interrupted Time Series.

BACKGROUND: Opioids have traditionally been used to manage acute or terminal pain. However, their prolonged use has the potential for abuse, misuse, and addiction. South Korea introduced a new health care IT system named the Narcotics Information Management System (NIMS) with the objective of managing all aspects of opioid use, including manufacturing, distribution, sales, disposal, etc. OBJECTIVE: This study aimed to assess the impact of NIMS on opioid use. METHODS: We conducted an analysis using national claims data from 45,582 patients diagnosed with musculoskeletal and connective tissue disorders between 2016 and 2020. Our approach included using an interrupted time-series analysis and constructing segmented regression models. Within these models, we considered the primary intervention to be the implementation of NIMS, while we treated the COVID-19 outbreak as the secondary event. To comprehensively assess inappropriate opioid use, we examined 4 key indicators, as established in previous studies: (1) the proportion of patients on high-dose opioid treatment, (2) the proportion of patients receiving opioid prescriptions from multiple providers, (3) the overlap rate of opioid prescriptions per patient, and (4) the naloxone use rate among opioid users. RESULTS: During the study period, there was a general trend of increasing opioid use. After the implementation of NIMS, significant increases were observed in the trend of the proportion of patients on high-dose opioid treatment (coefficient=0.0271; P=.01) and in the level of the proportion of patients receiving opioid prescriptions from multiple providers (coefficient=0.6252; P=.004). An abrupt decline was seen in the level of the naloxone use rate among opioid users (coefficient=-0.2968; P=.04). While these changes were statistically significant, their clinical significance appears to be minor. No significant changes were observed after both the implementation of NIMS and the COVID-19 outbreak. CONCLUSIONS: This study suggests that, in its current form, the NIMS may not have brought significant improvements to the identified indicators of opioid overuse and misuse. Additionally, the COVID-19 outbreak exhibited no significant influence on opioid use patterns. The absence of real-time monitoring feature within the NIMS could be a key contributing factor. Further exploration and enhancements are needed to maximize the NIMS' impact on curbing inappropriate opioid use.

What is the impact of artificial intelligence-based chatbots on infodemic management?

Artificial intelligence (AI) chatbots have the potential to revolutionize online health information-seeking behavior by delivering up-to-date information on a wide range of health topics. They generate personalized responses to user queries through their ability to process extensive amounts of text, analyze trends, and generate natural language responses. Chatbots can manage infodemic by debunking online health misinformation on a large scale. Nevertheless, system accuracy remains technically challenging. Chatbots require training on diverse and representative datasets, security to protect against malicious actors, and updates to keep up-to-date on scientific progress. Therefore, although AI chatbots hold significant potential in assisting infodemic management, it is essential to approach their outputs with caution due to their current limitations.

Optimization of Electronic Health Record Usability Through a Department-Led Quality Improvement Process.

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.Annals Early Access.

Analysis of Publications on Health Information Management Using the Science Mapping Method: A Holistic Perspective.

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.

Canada's Digital Health Workforce: The Role of Innovation, Research and Policy.

The rapid growth of digital health and use of technology has led to an increased demand for qualified professionals in the areas of health informatics (HI) and health information management (HIM). This is reflected by the growth in the number of educational programs and graduates in these areas. However, to develop a culture of digital health innovation in Canada, the role of research needs to be critically examined. In this paper we discuss some of these issues around the relation between research and innovation, and the development of an innovation culture in health informatics, health information management and digital health in Canada. Recommendations for facilitating this development in terms of funding, granting and policy are also explored.

Strengths and Obstacles of Health Informatics and Health Information Management Education and Professions in Hail City, Kingdom of Saudi Arabia: A Qualitative Study.

Health and higher education ministries in Saudi Arabia recognize the need for a highly qualified workforce specializing in health informatics and information management (HIIM). Therefore, KSA colleges and universities offer HIIM programs, health information systems, and health information technology. It is critical to investigate the HIIM professions and education in Hail City due to differences in these educational programs. This study examined HIIM professions and education in Hail City, Saudi Arabia, and provided strategies and recommendations. Based on a qualitative research approach, we interviewed 39 academicians, health informaticians, and other stakeholders in Hail City. The strengths, weaknesses, opportunities, threats (SWOT) framework was used to explore HIIM status and make recommendations. According to participants, HIIM Saudi professionals in Hail City have been growing and motivated, as have the university's undergraduate and postgraduate programs. Informants indicated several weaknesses, but many opportunities were found, including Saudi Vision 2030 and a new HIIM faculty at the University of Hail. According to our findings, relevant specialties control HIIM leadership while unspecialized academicians provide instruction. The extraordinary transmission of digital health in Saudi Arabia promises to enhance HIIM professions and education strengths and opportunities and reduce their weaknesses and threats.