Health Information Technology in Healthcare Quality and Patient Safety: Literature Review

Machine learning and artificial intelligence within pediatric autoimmune diseases: applications, challenges, future perspective

INTRODUCTION

Autoimmune disorders affect 4.5% to 9.4% of children, significantly reducing their quality of life. The diagnosis and prognosis of autoimmune diseases are uncertain because of the variety of onset and development. Machine learning can identify clinically relevant patterns from vast amounts of data. Hence, its introduction has been beneficial in the diagnosis and management of patients.

AREAS COVERED

This narrative review was conducted through searching various electronic databases, including PubMed, Scopus, and Web of Science. This study thoroughly explores the current knowledge and identifies the remaining gaps in the applications of machine learning specifically in the context of pediatric autoimmune and related diseases.

EXPERT OPINION

Machine learning algorithms have the potential to completely change how pediatric autoimmune disorders are identified, treated, and managed. Machine learning can assist physicians in making more precise and fast judgments, identifying new biomarkers and therapeutic targets, and personalizing treatment strategies for each patient by utilizing massive datasets and powerful analytics.

Development and Validation of SafeHIT: An Instrument to Assess the Self-Reported Safe Use of Health Information Technology

BACKGROUND

Implementing health information technology (HIT) may cause unintended consequences and safety risks when incorrectly designed and used. Yet, the tools to assess self-reported safe use of HIT are not well established.

OBJECTIVE

This study aims to develop and validate SafeHIT, an instrument to assess self-reported safe use of HIT among health care practitioners.

METHODS

Systematic literature review and a semistructured interview with 31 experts were adopted to generate SafeHIT instrument items. In total, 450 physicians from various departments at three Malaysian public hospitals participated in the questionnaire survey to validate SafeHIT. Exploratory factor analysis and confirmatory factor analysis (CFA) were undertaken to explore the items that best represent a specific construct and to confirm the reliability and validity of the SafeHIT, respectively.

RESULTS

The final SafeHIT consisted of 14 constructs and 58 items in total. The result of the CFA confirmed that all constructs demonstrated adequate convergent and discriminant validity.

CONCLUSION

A reliable and valid theoretically underpinned measure of determinants of safe HIT use behavior has been developed. Understanding external factors that influence safe HIT use is useful for developing targeted interventions that favor the quality and safety of health care.

Complex implementation mechanisms in primary care: do physicians' beliefs about the effectiveness of innovation play a mediating role? Applying a realist inquiry and structural equation modeling approach in a formative evaluation study

BACKGROUND

The adoption of digital health technologies can improve the quality of care for polypharmacy patients, if the underlying complex implementation mechanisms are better understood. Context effects play a critical role in relation to implementation mechanisms. In primary care research, evidence on the effects of context in the adoption of digital innovation for polypharmacy management is lacking.

STUDY AIM

This study aims to identify contextual factors relevant to physician behavior and how they might mediate the adoption process.

METHODS

The physicians who participated in this formative evaluation study (n = 218) were part of the intervention group in a cluster-randomized controlled trial (AdAM). The intervention group implemented a digital innovation for clinical decision making in polypharmacy. A three-step methodological approach was used: (1) a realist inquiry approach, which involves the description of a context-mechanism-outcome configuration for the primary care setting; (2) a belief elicitation approach, which involves qualitative content analysis and the development of a quantitative latent contextualized scale; and (3) a mediation analysis using structural equation modeling (SEM) based on quantitative survey data from physicians to assess the mediating role of the contextualized scale (n = 179).

RESULTS

The key dimensions of a (1) context-mechanism-outcome model were mapped and refined. A (2) latent construct of the physicians' innovation beliefs related to the effectiveness of polypharmacy management practices was identified. Innovation beliefs play a (3) mediating role between the organizational readiness to implement change (p < 0.01) and the desired behavioral intent of physicians to adopt digital innovation (p < 0.01; R² = 0.645). Our contextualized model estimated significant mediation, with a relative size of 38% for the mediation effect. Overall, the model demonstrated good fit indices (CFI = 0.985, RMSEA = 0.034).

CONCLUSION

Physician adoption is directly affected by the readiness of primary care organizations for the implementation of change. In addition, the mediation analysis revealed that this relationship is indirectly influenced by primary care physicians' beliefs regarding the effectiveness of digital innovation. Both individual physician beliefs and practice organizational capacity could be equally prioritized in developing implementation strategies. The methodological approach used is suitable for the evaluation of complex implementation mechanisms. It has been proven to be an advantageous approach for formative evaluation.

TRIAL REGISTRATION

NCT03430336 . First registration: 12/02/2018.

CLINICALTRIALS

gov.

Development of the information quality scale for health information supply chain type 2 diabetes mellitus management using exploratory factor analysis

Background

Research on the quality scale of the healthcare supply chain is still limited. This study aimed to assess the information quality of the supply chain model with a focus on construct validity. Studies related to information quality measurement generally focus on measuring the dimensions of the completeness of medical records and consumer perspectives. We intended to assess the scale based on doctors needed as care coordinators on type 2 diabetes mellitus or the Non-Insulin-Dependent-Diabetes-Mellitus (NIDDM) program in primary healthcare.

Methods

Sixty-four primary healthcare doctors with an age range of 24-51 years were involved in this research. The scale obtained was formed from the assessment of the point of view of a panel of experts through the content validity index (CVI). The exploratory factor analysis (EFA) method was used to explore the scale of information quality in the information supply chain model for the NIDDM chronic disease management program.

Result

The data analysis results indicated three main factors that affected the quality of the information supply chain model of NIDDM, namely accessibility, safety, and efficiency of information related to NIDDM. The results of the validity and reliability of the data showed that the scale used in this research was valid and reliable with a Cronbach alpha coefficient of 0.861.

Conclusion

The scale developed in this research could be used to explore the quality of the information supply chain of NIDDM management in primary healthcare. Each item on the scale could explain the variables according to their respective groups.

Using automated methods to detect safety problems with health information technology: a scoping review

OBJECTIVE

To summarize the research literature evaluating automated methods for early detection of safety problems with health information technology (HIT).

MATERIALS AND METHODS

We searched bibliographic databases including MEDLINE, ACM Digital, Embase, CINAHL Complete, PsycINFO, and Web of Science from January 2010 to June 2021 for studies evaluating the performance of automated methods to detect HIT problems. HIT problems were reviewed using an existing classification for safety concerns. Automated methods were categorized into rule-based, statistical, and machine learning methods, and their performance in detecting HIT problems was assessed. The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses extension for Scoping Reviews statement.

RESULTS

Of the 45 studies identified, the majority (n = 27, 60%) focused on detecting use errors involving electronic health records and order entry systems. Machine learning (n = 22) and statistical modeling (n = 17) were the most common methods. Unsupervised learning was used to detect use errors in laboratory test results, prescriptions, and patient records while supervised learning was used to detect technical errors arising from hardware or software issues. Statistical modeling was used to detect use errors, unauthorized access, and clinical decision support system malfunctions while rule-based methods primarily focused on use errors.

CONCLUSIONS

A wide variety of rule-based, statistical, and machine learning methods have been applied to automate the detection of safety problems with HIT. Many opportunities remain to systematically study their application and effectiveness in real-world settings.

The Role of Access Type and Age Group in the Breadth of Use of Patient Portals: Observational Study

BACKGROUND

Health care delivery and patient satisfaction are improved when patients engage with their medical information through patient portals. Despite their wide availability and multiple functionalities, patient portals and their functionalities are still underused.

OBJECTIVE

We seek to understand factors that lead to patient engagement through multiple portal functionalities. We provide recommendations that could lead to higher patients' usage of their portals.

METHODS

Using data from the Health Information National Trends Survey 5, Cycle 3 (N=2093), we performed descriptive statistics and used a chi-square test to analyze the association between the demographic variables and the use of mobile health apps for accessing medical records. We further fitted a generalized linear model to examine the association between access type and the use of portal functionalities. We further examined the moderation effects of age groups on the impact of access type on portal usage.

RESULTS

Our results show that accessing personal health records using a mobile health app is positively associated with greater patient usage of access capabilities (β=.52; P<.001), patient-provider interaction capabilities (β=.24, P=.006), and patient-personal health information interaction capabilities (β=.23, P=.009). Patients are more likely to interact with their records and their providers when accessing their electronic medical records using a mobile health app. The impacts of mobile health app usage fade with age for tasks consisting of viewing, downloading, and transmitting medical results to a third party (β=-.43, P=.005), but not for those involving patient-provider interaction (β=.05, P=.76) or patient-personal health information interaction (β=-.15, P=.19).

CONCLUSIONS

These findings provide insights on how to increase engagement with diverse portal functionalities for different age groups and thus improve health care delivery and patient satisfaction.

Nurse-led consultations reinforced with eHealth technology: a qualitative study of the experiences of patients with gynecological cancer

BACKGROUND

During the last decade, the health care profession has moved toward personalized care and has focused on the diversity of survivorship needs after initial cancer treatment. Health care providers encourage empowering patients to participate actively in their own health management and survivorship. Consequently, we developed and piloted a new follow-up model for patients at a Norwegian hospital, referred to as the Lifestyle and Empowerment Techniques in Survivorship of Gynecologic Oncology (LETSGO) model. Using LETSGO, a dedicated nurse replaces the physician in every second follow-up consultation, providing patients who have undergone cancer treatment with self-management techniques that are reinforced with eHealth technology via a specially designed app. Encouraging behavioral change and evaluating the late effects of treatment and recurrence symptoms are central components of self-management techniques. In addition, the app encourages physical activity and positive lifestyle changes, helps identify recurrence-related symptoms, and provides reminders of activity goals. This study aims to investigate experiences with nurse-led consultations supported by eHealth technology among the patients who piloted the LETSGO intervention.

METHODS

Semi-structured qualitative interviews were conducted to analyze the participants' experiences with the LETSGO intervention after six to seven months.

RESULTS

The participants in the LETSGO pilot felt safe and well cared for. They thought the nurse was less busy than the doctors appear to be, which made it easy for them to share any cancer-related challenges. Many participants reported increased empowerment and confidence in recognizing symptoms of cancer recurrence, and participants who used the app regularly were motivated to increase their physical activity levels. However, the participants also experienced some limitations and technical errors with the app.

CONCLUSIONS

Generally, the participants positively received the nurse-led consultations and eHealth technology, but an intervention study is required for further evaluation. In addition, the reported technical app errors should be resolved and tested prior to eHealth application implementation. Regardless, this study may be useful in planning personalized survivorship care studies.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT03453788 . Registration March 5, 2018.

Advancing Pharmacogenomics from Single-Gene to Preemptive Testing

Pharmacogenomic testing can be an effective tool to enhance medication safety and efficacy. Pharmacogenomically actionable medications are widely used, and approximately 90-95% of individuals have an actionable genotype for at least one pharmacogene. For pharmacogenomic testing to have the greatest impact on medication safety and clinical care, genetic information should be made available at the time of prescribing (preemptive testing). However, the use of preemptive pharmacogenomic testing is associated with some logistical concerns, such as consistent reimbursement, processes for reporting preemptive results over an individual's lifetime, and result portability. Lessons can be learned from institutions that have implemented preemptive pharmacogenomic testing. In this review, we discuss the rationale and best practices for implementing pharmacogenomics preemptively.

An inter-method comparison of four Human Reliability Assessment models

This paper presents a comparison of four common Human Reliability Assessment (HRA) models through a scoping literature review and sensitivity analysis. The scoping literature review identified 72 relevant studies which formed the basis of the comparison. Studies reported the four selected models have similarities in terms of the sector of origin, applied sectors, output calculation, and a lack of clear guidelines on Performance Influencing Factors (PIFs) selection and risk level allocation. The studied models have differences in the number and type of PIF inputs and Human Error Probability (HEP) calculation procedures. The One Factor At a Time (OFAT) and "combined" sensitivity analysis were conducted to examine the HRA models' responses to systematic risk level changes when each of 8 matching PIFs were systematically set to "high" and then "low" levels individually and simultaneously. The OFAT analysis showed coefficients of variation (CV) in HEP varying from 9% for skills/training up to 94% for work procedure when the PIFs are assigned to a "low" risk level individually. The combined analysis showed the median HEP value close to 97% and 1% when PIFs are assigned to" high" and "low" risk levels respectively. Although the selected HRA models were reported to be validated in high-risk domains there was no study found that validated these models in low-risk domains such as manual order picking, or manual assembly lines. The HRA models examined here are disconnected from specific system design elements which can inhibit design improvement efforts. The study outcome suggests the need for clear guidelines for PIFs selection and risk level allocation. Future research should address both the connection of error assessment to the design of the system and the features of new HRA models that affect its reliability and validity in a variety of industrial contexts.

Computerized Clinical Decision Support Systems for the Early Detection of Sepsis Among Adult Inpatients: Scoping Review

Background

Sepsis is a significant cause of morbidity and mortality worldwide. Early detection of sepsis followed promptly by treatment initiation improves patient outcomes and saves lives. Hospitals are increasingly using computerized clinical decision support (CCDS) systems for the rapid identification of adult patients with sepsis.

Objective

This scoping review aims to systematically describe studies reporting on the use and evaluation of CCDS systems for the early detection of adult inpatients with sepsis.

Methods

The protocol for this scoping review was previously published. A total of 10 electronic databases (MEDLINE, Embase, CINAHL, the Cochrane database, LILACS [Latin American and Caribbean Health Sciences Literature], Scopus, Web of Science, OpenGrey, ClinicalTrials.gov, and PQDT [ProQuest Dissertations and Theses]) were comprehensively searched using terms for sepsis, CCDS, and detection to identify relevant studies. Title, abstract, and full-text screening were performed by 2 independent reviewers using predefined eligibility criteria. Data charting was performed by 1 reviewer with a second reviewer checking a random sample of studies. Any disagreements were discussed with input from a third reviewer. In this review, we present the results for adult inpatients, including studies that do not specify patient age.

Results

A search of the electronic databases retrieved 12,139 studies following duplicate removal. We identified 124 studies for inclusion after title, abstract, full-text screening, and hand searching were complete. Nearly all studies (121/124, 97.6%) were published after 2009. Half of the studies were journal articles (65/124, 52.4%), and the remainder were conference abstracts (54/124, 43.5%) and theses (5/124, 4%). Most studies used a single cohort (54/124, 43.5%) or before-after (42/124, 33.9%) approach. Across all 124 included studies, patient outcomes were the most frequently reported outcomes (107/124, 86.3%), followed by sepsis treatment and management (75/124, 60.5%), CCDS usability (14/124, 11.3%), and cost outcomes (9/124, 7.3%). For sepsis identification, the systemic inflammatory response syndrome criteria were the most commonly used, alone (50/124, 40.3%), combined with organ dysfunction (28/124, 22.6%), or combined with other criteria (23/124, 18.5%). Over half of the CCDS systems (68/124, 54.8%) were implemented alongside other sepsis-related interventions.

Conclusions

The current body of literature investigating the implementation of CCDS systems for the early detection of adult inpatients with sepsis is extremely diverse. There is substantial variability in study design, CCDS criteria and characteristics, and outcomes measured across the identified literature. Future research on CCDS system usability, cost, and impact on sepsis morbidity is needed.

International Registered Report Identifier (IRRID)

RR2-10.2196/24899

Information Technology Ambidexterity, Digital Dynamic Capability, and Knowledge Processes as Enablers of Patient Agility: Empirical Study

BACKGROUND

There is a limited understanding of information technology's (IT) role as an enabler of patient agility and the department's ability to respond to patients' needs and wishes adequately.

OBJECTIVE

This study aims to contribute to the insights of the validity of the hypothesized relationship among IT resources, practices and capabilities, and hospital departments' knowledge processes, and the department's ability to adequately sense and respond to patient needs and wishes (ie, patient agility).

METHODS

This study conveniently sampled data from 107 clinical hospital departments in the Netherlands and used structural equation modeling for model assessment.

RESULTS

IT ambidexterity positively enhanced the development of a digital dynamic capability (β=.69; t4999=13.43; P<.001). Likewise, IT ambidexterity also positively impacted the hospital department's knowledge processes (β=.32; t4999=2.85; P=.005). Both digital dynamic capability (β=.36; t4999=3.95; P<.001) and knowledge processes positively influenced patient agility (β=.33; t4999=3.23; P=.001).

CONCLUSIONS

IT ambidexterity promotes taking advantage of IT resources and experiments to reshape patient services and enhance patient agility.

Dentists as Primary Care Providers: Expert Opinion on Predoctoral Competencies

Dentistry and medicine traditionally practice as separate professions despite sharing goals for optimal patient health. Many US residents experience both poor oral and general health, with difficulty accessing care. More efficient collaboration between these professions could enhance health. The COVID-19 pandemic disclosed further disparities while underscoring concerns that physician supply is inadequate for population needs. Hence, enhancing healthcare provider education to better meet the public's health needs is critical. The proposed titles “Oral Physician” or “Oral Health Primary Care Provider” (OP-PCP) acknowledge dentist's capacity to diagnose and manage diseases of the orofacial complex and provide some basic primary healthcare. The US Surgeon General's National Prevention Council and others recommend such models. Medical and dental education already overlap considerably, thus it is plausible that dental graduates could be trained as OP-PCPs to provide primary healthcare such as basic screening and preventive services within existing dental education standards. In 2018, 23 dental and medical educators participated in an expert-opinion elicitation process to review educational competencies for this model. They demonstrated consensus on educational expansion and agreed that the proposed OP-PCP model could work within existing US Commission on Dental Accreditation (CODA) standards for predoctoral education. However, there were broader opinions on scope of practice details. Existing CODA standards could allow interested dental programs to educate OP-PCPs as a highly-skilled workforce assisting with care of medically-complex patients and to helping to reduce health disparities. Next steps include broader stakeholder discussion of OC-PCP competencies and applied studies including patient outcome assessments.

Factors of quality of care and their association with smartphone based PHR adoption in South Korean hospitals

BACKGROUND

Healthcare organizations have begun to adopt personal health records (PHR) systems to engage patients, but little is known about factors associated with the adoption of PHR systems at an organizational level. The objective of this study is to investigate factors associated with healthcare organizations' adoption of PHR systems in South Korea.

METHODS

The units of analysis were hospitals with more than 100 beds. Study data of 313 hospitals were collected from May 1 to June 30, 2020. The PHR adoption status for each hospital was collected from PHR vendors and online searches. Adoption was then confirmed by downloading the hospital's PHR app and the PHR app was examined to ascertain its available functions. One major outcome variable was PHR adoption status at hospital level. Data were analysed by logistic regressions using SAS 9.4 version.

RESULTS

Out of 313 hospitals, 103 (32.9%) hospitals adopted PHR systems. The nurse-patient ratio was significantly associated with PHR adoption (OR 0.758; 0.624 to 0.920, p = 0.005). The number of health information management staff was associated with PHR adoption (OR 1.622; 1.228 to 2.141, p = 0.001). The number of CTs was positively associated with PHR adoption (OR 5.346; 1.962 to 14.568, p = 0.001). Among the hospital characteristics, the number of beds was significantly related with PHR adoption in the model of standard of nursing care (OR 1.003; 1.001 to 1.005, p < 0.001), HIM staff (OR 1.004; 1.002 to 1.006, p < 0.001), and technological infrastructure (OR 1.050; 1.003 to 1.006, p < 0.001).

CONCLUSIONS

One-third of study hospitals had adopted PHR systems. Standard of nursing care as well as information technology infrastructure in terms of human resources for health information management and advanced technologies were significantly associated with adoption of PHR systems. A favourable environment for adopting new technologies in general may be associated with the adoption and use of PHR systems.

Information Security Awareness and Behaviors of Health Care Professionals at Public Health Care Facilities

OBJECTIVES

This study investigated information security behaviors of professionals working in the public health sector to guide policymakers toward focusing their investments in infrastructure and training on the most vulnerable segments. We sought to answer the following questions: (1) Are certain professional demographics more vulnerable to cybersecurity threats? (2) Do professionals in different institution types (i.e., hospitals vs. primary care clinics) exhibit different cybersecurity behaviors? (3) Can Internet usage behaviors by professionals be indicative of their cybersecurity awareness and the risk they introduce?

METHODS

A cross-sectional, anonymous, paper-based survey was distributed among professionals working in public health care organizations in Kuwait. Data were collected about each professional's role, experience, work environment, cybersecurity practices, and understanding to calculate a cybersecurity score which indicates their level of compliance to good cybersecurity practices. We also asked about respondents' internet usage and used K-means cluster analysis to segment respondents into three groups based on their internet activities at work. Ordinary least squares regression assessed the association between the collected independent variables in question on the overall cybersecurity behavior.

RESULTS

A total of 453/700 (64%) were responded to the survey. The results indicated that professionals with more work experience demonstrated higher compliance with good cybersecurity practices. Interestingly, nurses demonstrate higher cybersecurity aptitude relative to physicians. Professionals that were less inclined to use the internet for personal use during their work demonstrated higher cybersecurity aptitude.

CONCLUSION

Our findings provide some guidance regarding how to target health care professional training to mitigate cybersecurity risks. There is a need for ensuring that physicians receive adequate cybersecurity training, despite the opportunity costs and other issues competing for their attention. Additionally, classifying professionals based on their internet browsing patterns may identify individuals vulnerable to cybersecurity incidents better than more discrete indicators such as age or gender.

Measuring the Interactions Between Health Demand, Informatics Supply, and Technological Applications in Digital Medical Innovation for China: Content Mapping and Analysis

BACKGROUND

There were 2 major incentives introduced by the Chinese government to promote medical informatics in 2009 and 2016. As new drugs are the major source of medical innovation, informatics-related concepts and techniques are a major source of digital medical innovation. However, it is unclear whether the research efforts of medical informatics in China have met the health needs, such as disease management and population health.

OBJECTIVE

We proposed an approach to mapping the interplay between different knowledge entities by using the tree structure of Medical Subject Headings (MeSH) to gain insights into the interactions between informatics supply, health demand, and technological applications in digital medical innovation in China.

METHODS

All terms under the MeSH tree parent node "Diseases [C]" or node "Health [N01.400]" or "Public Health [N06.850]" were labelled as H. All terms under the node "Information Science [L]" were labelled as I, and all terms under node "Analytical, Diagnostic and Therapeutic Techniques, and Equipment [E]" were labelled as T. The H-I-T interactions can be measured by using their co-occurrences in a given publication.

RESULTS

The H-I-T interactions in China are showing significant growth and a more concentrated interplay were observed. Computing methodologies, informatics, and communications media (such as social media and the internet) constitute the majority of I-related concepts and techniques used for resolving the health promotion and diseases management problems in China. Generally there is a positive correlation between the burden and informatics research efforts for diseases in China. We think it is not contradictory that informatics research should be focused on the greatest burden of diseases or where it can have the most impact. Artificial intelligence is a competing field of medical informatics research in China, with a notable focus on diagnostic deep learning algorithms for medical imaging.

CONCLUSIONS

It is suggested that technological transfers, namely the functionality to be realized by medical/health informatics (eg, diagnosis, therapeutics, surgical procedures, laboratory testing techniques, and equipment and supplies) should be strengthened. Research on natural language processing and electronic health records should also be strengthened to improve the real-world applications of health information technologies and big data in the future.

Machine Learning Classification of Inflammatory Bowel Disease in Children Based on a Large Real-World Pediatric Cohort CEDATA-GPGE® Registry

Introduction: The rising incidence of pediatric inflammatory bowel diseases (PIBD) facilitates the need for new methods of improving diagnosis latency, quality of care and documentation. Machine learning models have shown to be applicable to classifying PIBD when using histological data or extensive serology. This study aims to evaluate the performance of algorithms based on promptly available data more suited to clinical applications.

Methods: Data of inflammatory locations of the bowels from initial and follow-up visitations is extracted from the CEDATA-GPGE registry and two follow-up sets are split off containing only input from 2017 and 2018. Pre-processing excludes patients in remission and encodes the categorical data numerically. For classification of PIBD diagnosis, a support vector machine (SVM), a random forest algorithm (RF), extreme gradient boosting (XGBoost), a dense neural network (DNN) and a convolutional neural network (CNN) are employed. As best performer, a convolutional neural network is further improved using grid optimization.

Results: The achieved accuracy of the optimized neural network reaches up to 90.57% on data inserted into the registry in 2018. Less performant methods reach 88.78% for the DNN down to 83.94% for the XGBoost. The accuracy of prediction for the 2018 follow-up dataset is higher than those for older datasets. Neural networks yield a higher standard deviation with 3.45 for the CNN compared to 0.83–0.86 of the support vector machine and ensemble methods.

Discussion: The displayed accuracy of the convolutional neural network proofs the viability of machine learning classification in PIBD diagnostics using only timely available data.

A systematic review of healthcare professionals' core competency instruments

While technical and profession-specific competencies are paramount in the delivery of healthcare services, the cross-cutting core competencies of healthcare professionals play an important role in healthcare transformation, innovation, and the integration of roles. This systematic review describes the characteristics and psychometric properties of existing instruments for assessing healthcare professionals' core competencies in clinical settings. It was guided by the JBI methodology and used the COSMIN checklist (Mokkink et al., User manual, 2018, 78, 1) to evaluate the methodological quality of the included studies. A database search (CINAHL, Scopus, and PubMed) and additional manual search were undertaken for peer-reviewed papers with abstracts, published in English between 2008 and 2019. The search identified nine studies that were included in the synthesis demonstrating core competencies in professionalism, ethical and legal issues, research and evidence-based practice, personal and professional development, teamwork and collaboration, leadership and management, and patient-centered care. Few instruments addressed competencies in quality improvement, safety, communication, or health information technology. The findings demonstrate the reviewed tools' validity and reliability and pave the way for a comprehensive evaluation and assessment of core competencies into clinical practice.

Unpacking Prevalence and Dichotomy in Quick Sequential Organ Failure Assessment and Systemic Inflammatory Response Syndrome Parameters: Observational Data-Driven Approach Backed by Sepsis Pathophysiology

BACKGROUND

Considering morbidity, mortality, and annual treatment costs, the dramatic rise in the incidence of sepsis and septic shock among intensive care unit (ICU) admissions in US hospitals is an increasing concern. Recent changes in the sepsis definition (sepsis-3), based on the quick Sequential Organ Failure Assessment (qSOFA), have motivated the international medical informatics research community to investigate score recalculation and information retrieval, and to study the intersection between sepsis-3 and the previous definition (sepsis-2) based on systemic inflammatory response syndrome (SIRS) parameters.

OBJECTIVE

The objective of this study was three-fold. First, we aimed to unpack the most prevalent criterion for sepsis (for both sepsis-3 and sepsis-2 predictors). Second, we intended to determine the most prevalent sepsis scenario in the ICU among 4 possible scenarios for qSOFA and 11 possible scenarios for SIRS. Third, we investigated the multicollinearity or dichotomy among qSOFA and SIRS predictors.

METHODS

This observational study was conducted according to the most recent update of Medical Information Mart for Intensive Care (MIMIC-III, Version 1.4), the critical care database developed by MIT. The qSOFA (sepsis-3) and SIRS (sepsis-2) parameters were analyzed for patients admitted to critical care units from 2001 to 2012 in Beth Israel Deaconess Medical Center (Boston, MA, USA) to determine the prevalence and underlying relation between these parameters among patients undergoing sepsis screening. We adopted a multiblind Delphi method to seek a rationale for decisions in several stages of the research design regarding handling missing data and outlier values, statistical imputations and biases, and generalizability of the study.

RESULTS

Altered mental status in the Glasgow Coma Scale (59.28%, 38,854/65,545 observations) was the most prevalent sepsis-3 (qSOFA) criterion and the white blood cell count (53.12%, 17,163/32,311 observations) was the most prevalent sepsis-2 (SIRS) criterion confronted in the ICU. In addition, the two-factored sepsis criterion of high respiratory rate (≥22 breaths/minute) and altered mental status (28.19%, among four possible qSOFA scenarios besides no sepsis) was the most prevalent sepsis-3 (qSOFA) scenario, and the three-factored sepsis criterion of tachypnea, high heart rate, and high white blood cell count (12.32%, among 11 possible scenarios besides no sepsis) was the most prevalent sepsis-2 (SIRS) scenario in the ICU. Moreover, the absolute Pearson correlation coefficients were not significant, thereby nullifying the likelihood of any linear correlation among the critical parameters and assuring the lack of multicollinearity between the parameters. Although this further bolsters evidence for their dichotomy, the absence of multicollinearity cannot guarantee that two random variables are statistically independent.

CONCLUSIONS

Quantifying the prevalence of the qSOFA criteria of sepsis-3 in comparison with the SIRS criteria of sepsis-2, and understanding the underlying dichotomy among these parameters provides significant inferences for sepsis treatment initiatives in the ICU and informing hospital resource allocation. These data-driven results further offer design implications for multiparameter intelligent sepsis prediction in the ICU.

Mutual-Aid Mobile App for Emergency Care: Feasibility Study

BACKGROUND

Improving the quality of patient care through the use of mobile devices is one of the hot topics in the health care field. In unwanted situations like an accident, ambulances and rescuers often require a certain amount of time to arrive at the scene. Providing immediate cardiopulmonary resuscitation (CPR) to patients might improve survival.

OBJECTIVE

The primary objective of this study was to evaluate the feasibility of an emergency and mutual-aid app model in Taiwan and to provide a reference for government policy.

METHODS

A structured questionnaire was developed as a research tool. All questionnaires were designed according to the technology acceptance model, and a Likert scale was used to measure the degree of agreement or disagreement. Moreover, in-depth interviews were conducted with six experts from medical, legal, and mobile app departments. Each expert was interviewed once to discuss feasible countermeasures and suggestions. Statistical Package for the Social Sciences (SPSS version 19; IBM Corp, Armonk, New York) was used to perform all statistical analyses, including descriptive statistics, independent sample t-tests, variance analysis, and Pearson correlation analysis.

RESULTS

We conducted this study between October 20, 2017, and November 10, 2017, at the Taipei Medical University Hospital. Questionnaires were distributed to medical personnel, visiting guests, family members, and volunteers. A total of 113 valid questionnaires were finally obtained after the exclusion of incomplete questionnaires. Cronbach α values for self-efficacy (perceived ease of use), use attitude (perceived usefulness), and use willingness and frequency were above .85, meeting the criterion of greater than .70. We observed that the reliability of each subquestion was acceptable and the values for use attitude (perceive usefulness) and use willingness and frequency were more than .90.

CONCLUSIONS

The findings suggest that perceived ease of use and perceived usefulness of the app model affect use willingness. However, perceived usefulness had an intermediary influence on use willingness. Experts in law, medical, and technology fields consider that an emergency and mutual-aid model can be implemented in Taiwan. Along with the development of an emergency and mutual-aid app model, we recommend an increase in the number of automated external defibrillators per region and promotion of correct knowledge about CPR in order to decrease morbidity and mortality.

Advancing laboratory medicine in hospitals through health information exchange: a survey of specialist physicians in Canada

BACKGROUND

Laboratory testing occupies a prominent place in health care. Information technology systems have the potential to empower laboratory experts and to enhance the interpretation of test results in order to better support physicians in their quest for better and safer patient care. This study sought to develop a better understanding of which laboratory information exchange (LIE) systems and features specialist physicians are using in hospital settings to consult their patients' laboratory test results, and what benefit they derive from such use.

METHODS

As part of a broader research program on the use of health information exchange systems for laboratory medicine in Quebec, Canada, this study was designed as on online survey. Our sample is composed of 566 specialist physicians working in hospital settings, out of the 1512 physicians who responded to the survey (response rate of 17%). Respondents are representative of the targeted population of specialist physicians in terms of gender, age and hospital location.

RESULTS

We first observed that 80% of the surveyed physicians used the province-wide interoperable electronic health records (iEHR) system and 93% used a laboratory results viewer (LRV) to consult laboratory test results and most (72%) use both systems to retrieve lab results. Next, our findings reveal important differences in the capabilities available in each type of system and in the use of these capabilities. Third, there are differences in the nature of the perceived benefits obtained from the use of each of these two systems. Last, the extent of use of an LRV is strongly influenced by the IT artefact itself (i.e., the hospital's LRV available capabilities) while the use of the provincial iEHR system is influenced by its organizational context (i.e. the hospital's size and location).

CONCLUSIONS

The main contribution of this study lies in its insights into the role played by context in shaping physicians' choices about which laboratory information exchange systems to adopt and which features to use, and the different perceptions they have about benefits arising from such use. One related implication for practice is that success of LIE initiatives should not be solely assessed with basic usage statistics.

PROTOTYPE FOR MONITORING INCIDENTS IN THE HEALTH SERVICES: INNOVATION FOR PATIENT SAFETY

ABSTRACT Objective: to describe the participatory process of building a prototype to support the development of an information management system for notification, investigation and monitoring of health incidents. Method: a methodological research study on technology development, carried out in two stages: 1) documentary analysis of primary and secondary sources related to forms and legislation on incident notification systems, from September to October 2018; 2) deliberative dialog in two sessions, with 12 managers and coordinators of the Quality and Patient Safety Center of public hospitals in the Federal District, held in November 2018. In the deliberative session there was a presentation of the prototype and discussion of its applicability and functionality for the development of an information system for risk management in the health services. Results: creation and prototyping of a tool with 4 (four) screens representing the systematic flow of data. Screen 1: Simplified notification for patients and companions. Screen 2: Notification for the health professional. Screen 3: Investigation of the event and action plan. Screen 4: Intervention and monitoring by means of indicators. Conclusion: this is a tool capable of integrating actions to reduce the occurrence of incidents based on the identification and timely intervention on the risk factors. It can be used as a facilitating basis for the development or improvement of new instruments for risk management in the health services.

The emerging literature for the triad of health informatics, healthcare quality and safety, and healthcare simulation

The areas of health informatics, healthcare quality and safety, and healthcare simulation are often thought of as separate domains. The purpose of this position paper is to report on the interdependence that is emerging as an important triad across the healthcare/health system continuum. A qualitative review of 24 studies suggests the interdependence of health informatics, healthcare quality and safety, and healthcare simulation reaches much broader than traditional utilisation of simulation. We suggest ways that organisations can take advantage of the interdependence of this triad across a broader variety of healthcare environments, including teamwork, communication, and complex system relationships. In conclusion, the reviewed 24 studies suggest that the research in the triad focuses on simulation education and computerised simulation, and when coupled with health informatics, bears greater strength on quality improvement or patient safety.

Networked information technologies and patient safety: a protocol for a realist synthesis

BACKGROUND

There is a widespread belief that information technologies will improve diagnosis, treatment and care. Evidence about their effectiveness in health care is, however, mixed. It is not clear why this is the case, given the remarkable advances in hardware and software over the last 20 years. This review focuses on interoperable information technologies, which governments are currently advocating and funding. These link organisations across a health economy, with a view to enabling health and care professionals to coordinate their work with one another and to access patient data wherever it is stored. Given the mixed evidence about information technologies in general, and current policies and funding, there is a need to establish the value of investments in this class of system. The aim of this review is to establish how, why and in what circumstances interoperable systems affect patient safety.

METHODS

A realist synthesis will be undertaken, to understand how and why inter-organisational systems reduce patients' clinical risks, or fail to do so. The review will follow the steps in most published realist syntheses, including (1) clarifying the scope of the review and identifying candidate programme and mid-range theories to evaluate, (2) searching for evidence, (3) appraising primary studies in terms of their rigour and relevance and extracting evidence, (4) synthesising evidence, (5) identifying recommendations, based on assessment of the extent to which findings can be generalised to other settings.

DISCUSSION

The findings of this realist synthesis will shed light on how and why an important class of systems, that span organisations in a health economy, will contribute to changes in patients' clinical risks. We anticipate that the findings will be generalizable, in two ways. First, a refined mid-range theory will contribute to our understanding of the underlying mechanisms that, for a range of information technologies, lead to changes in clinical practices and hence patients' risks (or not). Second, many governments are funding and implementing cross-organisational IT networks. The findings can inform policies on their design and implementation.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42017073004.

Key Issues in the Development of an Evidence-Based Stratified Surgical Patient Safety Improvement Information System: Experience From a Multicenter Surgical Safety Program

Surgery is still far from being completely safe and reliable. Surgical safety has, therefore, been the focus of considerable attention over the last few decades, and there are a growing number of national drives to improve it. There are also a number of large surgical complication reporting systems and system-based interventions, both of which have made remarkable progress in the past two decades. These systems, however, have either mainly focused on reporting complications and played a limited role in guiding practice or have provided nonselective interventions to all patients, perhaps imposing unnecessary burdens on frontline medical staff. We have, therefore, developed an evidence-based stratified surgical safety information system based on a multicenter surgical safety improvement program. This study discusses some critical issues in the process of developing this information system, including (1) decisions about data gathering, (2) establishing and sharing knowledge, (3) developing functions for the system, (4) system implementation, and (5) evaluation and continuous improvement. Using examples drawn from the surgical safety improvement program, we have shown how this type of system can be fitted into day-to-day clinical practice and how it can guide medical practice by incorporating inherent patient-related risk and providing tailored interventions for patients with different levels of risk. We concluded that multidisciplinary collaboration, involving experts in health care (including senior staff in surgery, nursing, and anesthesia), data science, health care management, and health information technology, can help build an evidence-based stratified surgical patient safety improvement system. This can provide an information-intensified surgical safety learning platform and, therefore, benefit surgical patients by delivering tailored interventions and an integrated workflow.

Long-term effects of an e-learning course on patient safety: A controlled longitudinal study with medical students

Background

To improve patient safety, educational interventions on all system levels, including medical school are necessary. Sound theoretical knowledge on elements influencing patient safety (such as error management or team work) is the basis for behavioral changes of health care professionals.

Methods

A controlled, quasi-experimental study with repeated measures was deployed. The intervention group participated in a mandatory e-learning course on patient safety (ELPAS) between October 2016 and December 2016. The control group did not receive any didactic session on patient safety. In both groups we measured technical knowledge and attitudes towards patient safety before the intervention (T0), directly after the intervention (T1) and one year after the intervention (T2). Participants were 309 third-year medical students in the intervention group and 154 first- and second-year medical students in the control group.

Results

Technical knowledge in the intervention group (but not the control group) improved significantly after the intervention and remained high after one year (F(2, 84) = 13.506, p < .001, η² = .243). Students of the intervention group felt better prepared for safe patient practice, even one year after the intervention F(2, 85) = 6.743, p < .002, η² = .137). There was no sustainable significant effect on attitudes towards patient safety.

Conclusion

This study shows, that eLearning interventions can produce significant long-term effects on patient safety knowledge, however, the study did not show long-term effects on attitudes towards patient safety. Our study implies two potential developments for future research: e-learning might be used in combination with face-to-face sessions, or more intensive (in terms of frequency and duration) e-learning sessions may be needed to achieve lasting changes in attitude.

Man vs machine in emergency medicine - a study on the effects of manual and automatic vital sign documentation on data quality and perceived workload, using observational paired sample data and questionnaires

BACKGROUND

Emergency medicine is characterized by a high patient flow where timely decisions are essential. Clinical decision support systems have the potential to assist in such decisions but will be dependent on the data quality in electronic health records which often is inadequate. This study explores the effect of automated documentation of vital signs on data quality and workload.

METHODS

An observational study of 200 vital sign measurements was performed to evaluate the effects of manual vs automatic documentation on data quality. Data collection using questionnaires was performed to compare the workload on wards using manual or automatic documentation.

RESULTS

In the automated documentation time to documentation was reduced by 6.1 min (0.6 min vs 7.7 min, p <  0.05) and completeness increased (98% vs 95%, p <  0.05). Regarding workflow temporal demands were lower in the automatic documentation workflow compared to the manual group (50 vs 23, p <  0.05). The same was true for frustration level (64 vs 33, p <  0.05). The experienced reduction in temporal demands was in line with the anticipated, whereas the experienced reduction in frustration was lower than the anticipated (27 vs 54, p < 0.05).

DISCUSSION

The study shows that automatic documentation will improve the currency and the completeness of vital sign data in the Electronic Health Record while reducing workload regarding temporal demands and experienced frustration. The study also shows that these findings are in line with staff anticipations but indicates that the anticipations on the reduction of frustration may be exaggerated among the staff. The open-ended answers indicate that frustration focus will change from double documentation of vital signs to technical aspects of the automatic documentation system.