The impact of eHealth on the quality and safety of health care: a systematic overview

Exploring the effectiveness of eHealth interventions in treating Post Intensive Care Syndrome (PICS) outcomes: a systematic review

BACKGROUND

It remains unclear how to optimise critical care rehabilitation to reduce the constellation of long-term physical, psychological and cognitive impairments known as Post Intensive Care Syndrome (PICS). Possible reasons for poor recovery include access to care and delayed treatment. eHealth could potentially aid in increasing access and providing consistent care remotely. Our review aimed to evaluate the effectiveness of eHealth interventions on PICS outcomes.

METHODS

Studies reporting eHealth interventions targeting Post Intensive Care Syndrome outcomes, published in Medline, CINAHL, PsycINFO, Embase, and Scopus from 30th January 2010 to 12th February 2024, were included in the review. Study eligibility was assessed by two reviewers with any disagreements discussed between them or resolved by a third reviewer. Study quality and risk of bias were assessed using the Mixed Method Appraisal Tool. Further to the identification of effective strategies, our review also aimed to clarify the timeline of recovery considered and the outcomes or domains targeted by the interventions.

RESULTS

Thirteen studies were included in our review. Study duration, eHealth intervention delivery format, and outcome measures varied considerably. No studies reported a theory of behavioural change and only one study was co-produced with patients or carers. Most studies were conducted in the early post-discharge phase (i.e., < 3 months) and had feasibility as a primary outcome. The cognitive domain was the least targeted and no intervention targeted all three domains. Interventions targeting the psychological domain suggest generally positive effects. However, results were underpowered and preliminary. Though all studies were concluded to be feasible, most studies did not assess acceptability. In studies that did assess acceptability, the main facilitators of acceptability were usability and perceived usefulness, and the main barrier was sensitivity to mental health and cognitive issues.

CONCLUSION

Our systematic review highlighted the promising contributions of eHealth with preliminary support for the feasibility of interventions in the early stages of post-critical care rehabilitation. Future research should focus on demonstrating effectiveness, acceptability, the cognitive domain, and multi-component interventions.

Evaluating Artificial Intelligence in Clinical Settings-Let Us Not Reinvent the Wheel

Given the requirement to minimize the risks and maximize the benefits of technology applications in health care provision, there is an urgent need to incorporate theory-informed health IT (HIT) evaluation frameworks into existing and emerging guidelines for the evaluation of artificial intelligence (AI). Such frameworks can help developers, implementers, and strategic decision makers to build on experience and the existing empirical evidence base. We provide a pragmatic conceptual overview of selected concrete examples of how existing theory-informed HIT evaluation frameworks may be used to inform the safe development and implementation of AI in health care settings. The list is not exhaustive and is intended to illustrate applications in line with various stakeholder requirements. Existing HIT evaluation frameworks can help to inform AI-based development and implementation by supporting developers and strategic decision makers in considering relevant technology, user, and organizational dimensions. This can facilitate the design of technologies, their implementation in user and organizational settings, and the sustainability and scalability of technologies.

Digital Maturity as a Predictor of Quality and Safety Outcomes in US Hospitals: Cross-Sectional Observational Study

BACKGROUND

This study demonstrates that digital maturity contributes to strengthened quality and safety performance outcomes in US hospitals. Advanced digital maturity is associated with more digitally enabled work environments with automated flow of data across information systems to enable clinicians and leaders to track quality and safety outcomes. This research illustrates that an advanced digitally enabled workforce is associated with strong safety leadership and culture and better patient health and safety outcomes.

OBJECTIVE

This study aimed to examine the relationship between digital maturity and quality and safety outcomes in US hospitals.

METHODS

The data sources were hospital safety letter grades as well as quality and safety scores on a continuous scale published by The Leapfrog Group. We used the digital maturity level (measured using the Electronic Medical Record Assessment Model [EMRAM]) of 1026 US hospitals. This was a cross-sectional, observational study. Logistic, linear, and Tweedie regression analyses were used to explore the relationships among The Leapfrog Group's Hospital Safety Grades, individual Leapfrog safety scores, and digital maturity levels classified as advanced or fully developed digital maturity (EMRAM levels 6 and 7) or underdeveloped maturity (EMRAM level 0). Digital maturity was a predictor while controlling for hospital characteristics including teaching status, urban or rural location, hospital size measured by number of beds, whether the hospital was a referral center, and type of hospital ownership as confounding variables. Hospitals were divided into the following 2 groups to compare safety and quality outcomes: hospitals that were digitally advanced and hospitals with underdeveloped digital maturity. Data from The Leapfrog Group's Hospital Safety Grades report published in spring 2019 were matched to the hospitals with completed EMRAM assessments in 2019. Hospital characteristics such as number of hospital beds were obtained from the CMS database.

RESULTS

The results revealed that the odds of achieving a higher Leapfrog Group Hospital Safety Grade was statistically significantly higher, by 3.25 times, for hospitals with advanced digital maturity (EMRAM maturity of 6 or 7; odds ratio 3.25, 95% CI 2.33-4.55).

CONCLUSIONS

Hospitals with advanced digital maturity had statistically significantly reduced infection rates, reduced adverse events, and improved surgical safety outcomes. The study findings suggest a significant difference in quality and safety outcomes among hospitals with advanced digital maturity compared with hospitals with underdeveloped digital maturity.

Comparative effectiveness of eHealth interventions on the exercise endurance and quality of life of patients with COPD: A systematic review and network meta-analysis

AIMS

To compare the effectiveness of different types of eHealth interventions in improving exercise endurance and quality of life in chronic obstructive pulmonary disease (COPD) patients.

BACKGROUND

COPD is a chronic airway disease characterized by persistent respiratory symptoms and airflow limitation. eHealth interventions have been accepted and recognized by healthcare professionals and COPD patients as an effective alternative to pulmonary rehabilitation. However, it is not clear which eHealth interventions are effective and preferred for exercise endurance and quality of life in COPD patients.

DESIGN

A systematic review and network meta-analysis based on PRISMA-NMA.

METHODS

We searched nine electronic databases to identify randomized controlled trials addressing the effect of eHealth interventions on the exercise endurance and quality of life of COPD patients from their inception to 30 October 2022. First, a random-effects model was chosen to conduct a traditional meta-analysis to directly investigate the efficacy of different eHealth interventions. Next, a network meta-analysis was performed to evaluate the relative efficacy of the eHealth interventions for COPD. The quality of the data was assessed using the Cochrane Risk of Bias tool.

RESULTS

Fifty-one studies containing six eHealth interventions (telemonitoring, application [APP], web-based interventions, phone calls, virtual reality and combined interventions [≥two types]) were included in the final analysis. Network meta-analysis showed that telemonitoring, APP, web-based interventions and combined interventions improved exercise endurance in COPD patients, with telemonitoring being the most effective. Web-based interventions and apps are effective in improving the quality of life, and web-based interventions are the most effective.

CONCLUSIONS

This study confirms that eHealth interventions can improve exercise endurance and quality of life in COPD patients. In the future, healthcare professionals can promote the use of telemedicine in COPD patients to enhance their exercise endurance and quality of life according to their individual needs.

RELEVANCE TO CLINICAL PRACTICE

This evidence suggests that eHealth interventions can improve exercise endurance and quality of life in COPD patients. Therefore, in the future, eHealth interventions could be used to maximize their effectiveness in improving exercise endurance and quality of life in COPD patients.

Digital Transformation in Thoracic Surgery: a survey among the European Society of Thoracic Surgeons

OBJECTIVES

Digital transformation has drastically changed the surgical sector, but few is known about its impact on thoracic surgical practice. The aim of this paper is to report the European Society of Thoracic Surgeons (ESTS) survey results, assessing the impact of and the need for Digital Transformation in Thoracic Surgery.

METHODS

A 23-item survey was designed by the ESTS Digital Transformation Working Group to assess the impact of and the need for Digital Transformation in Thoracic Surgery. All ESTS members (1668) were invited to complete the survey between 13 March and 21 May 2022 anonymously. Data analysis was descriptive calculating frequencies and percentages. Group comparison was done using chi-square test.

RESULTS

The response rate was 6.3%. Surgeons from 26 European countries participated of which more than 80% were based in academic hospitals. The impact of digital transformation was rated very important (43.8%) and fundamental (22.7%) in more than two-thirds of the cases, regardless of surgeons' age. None of the participants felt that digital transformation was of no importance and more than 85% had implemented digital platforms in their direct patient care. Almost 90% of the surgeons, currently not using digital platforms for training and education, would consider introducing them. About 70% were at least 'somewhat satisfied' with their current engagement in Digital Transformation in Thoracic Surgery.

CONCLUSIONS

Digital transformation seems to play a major role across European Thoracic Surgery departments in direct patient care, professional networking and surgical training. However, overall satisfaction with the current status of Digital Transformation in Thoracic Surgery was rather reserved, implying the need to increase the implementation of digital solutions in the latter.

Using process model to define the legislative framework of electronic prescription in the Czech Republic

Defining legislation for electronic prescription systems (EPS) is inherently challenging due to conflicting interests and requirements. The study aimed to develop a comprehensive EPS within the Czech healthcare framework, integrating legislative, process, and technical aspects to ensure security, user acceptability, and compliance with health regulations. A process modeling tool based on hierarchical state machines was employed to create a detailed process architecture for the EPS. Key participants, scenarios, and state transitions were identified and incorporated into a process model using the Craft.CASE based on the BORM methodology. The final process architecture model facilitated interdisciplinary communication and consensus-building among stakeholders, including healthcare professionals, IT specialists, and legislators. The model served as a foundation for the legislative framework and was included in the explanatory memorandum for the draft amendment to the Pharmaceuticals Act. The use of hierarchical state machines and process modeling tools in developing healthcare legislation effectively reduced misunderstandings and ensured precise implementation. This method can be applied to other complex legislative and system design projects, enhancing stakeholder communication and project success.

WhatsApp-based intervention in urban Colombia to support the prevention of arboviral diseases: a feasibility study

Arboviral diseases remain a significant health concern worldwide, with over half the world's population at risk for dengue alone. Without a vaccine or targeted treatment, the most effective strategy of prevention is vector management with community involvement. mHealth interventions, like WhatsApp, offer promising results for engaging communities and promoting healthier behaviors. This study explores the feasibility of integrating WhatsApp in vector control activities to improve arbovirus prevention in Colombia. A mixed-methods approach was employed to assess the WhatsApp-based intervention. WhatsApp messages were sent to 45 community women for 5 weeks to increase their knowledge and practices about dengue, Zika, and chikungunya. Pre-and-post surveys and focus group discussions were conducted in community settings to measure the feasibility and acceptability of this intervention. Chat reviews were done to assess the usability of users. A total of 1566 messages were exchanged in 45 WhatsApp chats. High acceptance and good usability (82% of users used the app for replying) were reported in this study. WhatsApp messages were perceived as short, clear, and enjoyable. Users liked the frequency, and design of messages. Pre- and post-surveys demonstrated improvements in the knowledge and practices of arboviral diseases. The intention to apply this knowledge in practice was reflected in a significant improvement, particularly in cleaning the laundry tank once a week (pre 62.1% to post 89.6%, p < 0.008). This study suggests that using WhatsApp as an additional tool could be a feasible, acceptable, and affordable strategy for improving the adoption of better practices in the prevention of arboviral diseases.

Energy landscape analysis and time-series clustering analysis of patient state multistability related to rheumatoid arthritis drug treatment: The KURAMA cohort study

Rheumatoid arthritis causes joint inflammation due to immune abnormalities, resulting in joint pain and swelling. In recent years, there have been considerable advancements in the treatment of this disease. However, only approximately 60% of patients achieve remission. Patients with multifactorial diseases shift between states from day to day. Patients may remain in a good or poor state with few or no transitions, or they may switch between states frequently. The visualization of time-dependent state transitions, based on the evaluation axis of stable/unstable states, may provide useful information for achieving rheumatoid arthritis treatment goals. Energy landscape analysis can be used to quantitatively determine the stability/instability of each state in terms of energy. Time-series clustering is another method used to classify transitions into different groups to identify potential patterns within a time-series dataset. The objective of this study was to utilize energy landscape analysis and time-series clustering to evaluate multidimensional time-series data in terms of multistability. We profiled each patient's state transitions during treatment using energy landscape analysis and time-series clustering. Energy landscape analysis divided state transitions into two patterns: "good stability leading to remission" and "poor stability leading to treatment dead-end." The number of patients whose disease status improved increased markedly until approximately 6 months after treatment initiation and then plateaued after 1 year. Time-series clustering grouped patients into three clusters: "toward good stability," "toward poor stability," and "unstable." Patients in the "unstable" cluster are considered to have clinical courses that are difficult to predict; therefore, these patients should be treated with more care. Early disease detection and treatment initiation are important. The evaluation of state multistability enables us to understand a patient's current state in the context of overall state transitions related to rheumatoid arthritis drug treatment and to predict future state transitions.

Use of Sequential Hot-Deck Imputation for Missing Health Care Systems Data for Population Health Research

Electronic medical record (EMR) data present many opportunities for population health research. The use of EMR data for population risk models can be impeded by the high proportion of missingness in key patient variables. Common approaches like complete case analysis and multiple imputation may not be appropriate for some population health initiatives that require a single, complete analytic data set. In this study, we demonstrate a sequential hot-deck imputation (HDI) procedure to address missingness in a set of cardiometabolic measures in an EMR data set. We assessed the performance of sequential HDI within the individual variables and a commonly used composite risk score. A data set of cardiometabolic measures based on EMR data from 2 large urban hospitals was used to create a benchmark data set with simulated missingness. Sequential HDI was applied, and the resulting data were used to calculate atherosclerotic cardiovascular disease risk scores. The performance of the imputation approach was assessed using a set of metrics to evaluate the distribution and validity of the imputed data. Of the 567,841 patients, 65% had at least 1 missing cardiometabolic measure. Sequential HDI resulted in the distribution of variables and risk scores that reflected those in the simulated data while retaining correlation. When stratified by age and sex, risk scores were plausible and captured patterns expected in the general population. The use of sequential HDI was shown to be a suitable approach to multivariate missingness in EMR data. Sequential HDI could benefit population health research by providing a straightforward, computationally nonintensive approach to missing EMR data that results in a single analytic data set.

Design and evaluation of a web-based electronic health record for amblyopia

Introduction

Amblyopia, or lazy eye, is a type of visual impairment in which the eyesight is not complete, even with the use of glasses. For the treatment of this disease, accurate and continuous examinations are needed. Nowadays, patient-centered care, by relying on web-based electronic records for amblyopia, has the potential to reduce treatment costs, increase the quality of care, and improve the safety and effectiveness of treatment. Therefore, the purpose of this study is to design and evaluate an Electronic Health Record (EHR) for patients with amblyopia.

Methods

The present study is applied developmental research. Using a Morgan table as a sampling tool, a straightforward random sampling technique selected 150 records from 1,500 records that were free of flaws. The design of the electronic version proceeded in a cascading manner so that after the design of each part, it was presented to the amblyopia experts, and if approved, the next part was designed. To design this EHR, the C# programming language and MySQL database were used. A system evaluation was performed by entering and recording patient information. For this purpose, the standard Questionnaire of User Interaction Satisfaction (QUIS), consisting of 18 questions, was used.

Results

According to the amblyopia EHR data elements, the data of physician and patient, examinations, website members, and members' roles were determined. After defining the fields and classes that explain the tables, the EHR was designed. The usability evaluation of the system showed that the mean selection of very good and good options by the users of EHRs was over 90%, indicating the patients' acceptance of web-based EHRs.

Conclusion

The design of an EHR for amblyopia is an effective step toward integrating and improving the information management of these patients. It will also enable the storage and retrieval of patients' information to reduce and facilitate the control of amblyopia complications.

Anxiety and Somatoform Syndromes Predict Transplant-Focused Internet Use in the Course of an Organ Transplantation

Background: e-Health interventions are increasing in the field of organ transplantations; however, the literature lacks evidence regarding needs, attitudes, and preferences of organ recipients and donors during the course of an organ transplantation. Methods: In a cross-sectional study, 70 subjects were assessed using self-rated and validated questionnaires, such as the PRIME MD Patient Health Questionnaire (PHQ-D) and the Essen Resource Inventory (ERI). Group differences and a multiple linear regression were also applied. Results: Organ recipients had significantly higher scores for depression (U = 245.00, z = -2.65, p = 0.008, Cohen's d = 0.32), somatoform (U = 224.50, z = -2.99, p = 0.003, Cohen's d = 0.37), and stress syndromes (U = 266.00, z = -2.25, p = 0.008, Cohen's d = 0.27). They also named the internet and apps as resources to find information regarding organ transplants (U = 177.50, z = -2.07, p = 0.017, Cohen's d = 0.28; Z = -2.308, p = 0.021) and preferred to use apps to monitor the physical condition (Z = -2.12, p = 0.034) significantly more than organ donors. Anxiety and somatoform syndromes were significant predictors to search for information regarding the transplant process (F[6,38] = 3.98, p < 0.001; R2 = 0.386). Conclusions: e-Health interventions are promising in accompanying the course of an organ transplant for patients to be informed and educated. Predominantly, potential organ recipients might benefit from apps to record physical parameters. However, anxiety syndromes might hinder patients from searching for information about the transplant process, while somatoform syndromes might enable patients who are searching for such information.

Insights from home parenteral nutrition infusion data

OBJECTIVE

Patients with chronic intestinal failure use home parenteral nutrition infusion support. Non-compliance of home parenteral nutrition treatment is well documented, especially if clinical resources are remote. Objective delivery data from Infusion Pump reports have the potential to support treatment progress and planning. The aim of this study was to report the efficacy and accuracy of the Eitan Insights digital health platform for home parenteral nutrition use (a platform providing data-driven insights from the pump-recorded data).

METHODS

A prospective, single-center observational study of 20 patients treated with home parenteral nutrition ≥3 d/wk was conducted over 2022. The patients recorded the pre- and postinfusion home parenteral nutrition bag weight, duration of infusion, and alarms. We compared manual records to the pump data. Repeated measures analysis of variance was used for statistical analysis.

RESULTS

A total of 45 data sets were collected, with no adverse events noted. In multiple comparisons between patient factors and descriptive statistics, there was no significant difference between manually recorded and pump-recorded data for volume infused (mean values of manual versus pump were 1707 ± 362 mL and 1708 ± 405 mL; P = 0.939) and infusion duration (mean values of manual versus pump iwere 9h 43 min ± 2.48 SD versus 9h 45 min ± 2.41 SD; P = 0.858).

CONCLUSION

The data collected by the digital platform accurately reflect patients' infusion data. This connected device has the potential to allow clinicians to be more informed and assess treatment trends and proactive resource planning through the Infusion Pump data insights.

Evaluation of three protocols for direct susceptibility testing for gram negative-Enterobacteriaceae from patient samples in Uganda with SMS reporting

In Uganda, the challenge of generating and timely reporting essential antimicrobial resistance (AMR) data has led to overreliance on empirical antibiotic therapy, exacerbating the AMR crisis. To address this issue, this study aimed to adapt a one-step AMR testing protocol alongside an SMS (Short Message Service) result relay system (SRRS), with the potential to reduce the turnaround time for AMR testing and result communication from 4 days or more to 1 day in Ugandan clinical microbiology laboratories. Out of the 377 samples examined, 54 isolates were obtained. Notably, E. coli (61%) and K. pneumoniae (33%) were the most frequently identified, majority testing positive for ESBL. Evaluation of three AMR testing protocols revealed varying sensitivity and specificity, with Protocol A (ChromID ESBL-based) demonstrating high sensitivity (100%) but no calculable specificity, Protocol B (ceftazidime-based) showing high sensitivity (100%) and relatively low specificity (7.1%), and Protocol C (cefotaxime-based) exhibiting high sensitivity (97.8%) but no calculable specificity. ESBL positivity strongly correlated with resistance to specific antibiotics, including cefotaxime, ampicillin, and aztreonam (100%), cefuroxime (96%), ceftriaxone (93%), and trimethoprim sulfamethoxazole (87%). The potential of integrating an SRRS underscored the crucial role this could have in enabling efficient healthcare communication in AMR management. This study underscores the substantial potential of the tested protocols for accurately detecting ESBL production in clinical samples, potentially, providing a critical foundation for predicting and reporting AMR patterns. Although considerations related to specificity warrant careful assessment before widespread clinical adoption.

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.

What are the determinants of older people adopting communicative e-health services: a meta-ethnography

BACKGROUND

Gradually, society has shifted more services online, with COVID-19 highlighting digital inequalities in access to services such as healthcare. Older adults can experience such digital inequalities, yet this group is also more likely to need medical appointments, compared to younger people. With the growing digitalisation of healthcare, it is increasingly important to understand how older people can best use communicative e-health services to interact with healthcare services. This is especially if older adults are to access, and actively interact with health professionals/clinicians due to their general health decline. This review aims to synthesise older adults' experiences and perceptions of communicative e-health services and, in turn, identify barriers and facilitators to using communicative e-health services.

METHODS

A meta-ethnography was conducted to qualitatively synthesise literature on older adults' experiences of using communicative e-health services. A systematic search, with terms relating to 'older adults', 'e-health', 'technology', and 'communication', was conducted on six international databases between January 2014 and May 2022. The search yielded a total of 10 empirical studies for synthesis.

RESULTS

The synthesis resulted in 10 themes that may impact older adults' perceptions and/or experiences of using communicative e-health services. These were: 1) health barriers, 2) support networks, 3) application interface/design, 4) digital literacy, 5) lack of awareness, 6) online security, 7) access to digital devices and the internet, 8) relationship with healthcare provider(s), 9) in-person preference and 10) convenience. These themes interlink with each other.

CONCLUSION

The findings suggest older adults' experiences and perceptions of communicative e-health services are generally negative, with many reporting various barriers to engaging with online services. However, many of these negative experiences are related to limited support networks and low digital literacy, along with complicated application interfaces. This supports previous literature identifying barriers and facilitators in which older adults experience general technology adoption and suggests a greater emphasis is needed on providing support networks to increase the adoption and usage of communicative e-health services.

Impact of the Lightwave Health Information Management Software on the Dimensions of Quality of Healthcare Data

OBJECTIVES

The use of technology in healthcare to manage patient records, guide diagnosis, and make referrals is termed electronic healthcare. An electronic health record system called Lightwave Health Information Management System (LHIMS) was implemented in 2018 at Cape Coast Teaching Hospital (CCTH). This study evaluated the impact of LHIMS on the quality of healthcare data at CCTH, focusing on the extent to which its use has enhanced the main dimensions of data quality.

METHODS

Structured questionnaires were administered to doctors at CCTH to enquire about their opinions about the present state of LHIMS as measured against the parameters of interest in this study, mainly the dimensions of quality healthcare data and the specific issues plaguing the system as reported by respondents.

RESULTS

Most doctors found LHIMS convenient to use, mainly because it made access to patient records easier and had to some extent improved the dimensions of quality healthcare data, except for comprehensiveness, at CCTH. Major challenges that impeded the smooth running of the system were erratic power supply, inadequate logistics and technological drive, and poor internet connectivity.

CONCLUSIONS

LHIMS must be upgraded to include more decision support systems and additional add-ons such as patients' radiological reports, and laboratory results must be readily available on LHIMS to make patient health data more comprehensive.

Improving safety claims in digital health interventions using the digital health assessment method

Objective

Establish a relationship between digital health intervention (DHI) and health system challenges (HSCs), as defined by the World Health Organization; within the context of hazard identification (HazID), leading to safety claims. To improve the justification of safety of DHIs and provide a standardised approach to hazard assessment through common terminology, ontology and simplification of safety claims. Articulation of results, to provide guidance for health strategy and regulatory/standards-based compliance.

Methods

We categorise and analyse hazards using a qualitative HazID study. This method utilises a synergy between simplicity of DHI intended use and the interaction from a multidisciplinary team (technologists and health informaticians) in the hazard analysis of the subject under assessment as an influencing factor. Although there are other methodologies available for hazard assessment. We examine the hazards identified and associated failures to articulate the improvements in the quality of safety claims.

Results

Applying the method provides the hazard assessment and helps generate the assurance case. Justification of safety is made and elicits confidence in safety claim. Controls to hazards contribute to meeting the HSC.

Conclusions

This method of hazard assessment, analysis and the use of ontologies (DHI & HSC) improves the justification of safety claim and evidence articulation.

Impact of coordination mechanisms based on information and communication technologies on cross-level clinical coordination: A scoping review

Background

Coordination mechanisms based on information and communication technologies (ICTs) are gaining attention, especially since the pandemic, due to their potential to improve communication between health professionals. However, their impact on cross-level clinical coordination remains unclear. The aim is to synthesize the evidence on the impact of ICT-based coordination mechanisms on clinical coordination between primary care and secondary care (SC) doctors and to identify knowledge gaps.

Methods

A scoping review was conducted by searching for original articles in six electronic databases and a manual search, with no restrictions regarding time, area, or methodology. Titles and abstracts were screened. Full texts of the selected articles were reviewed and analysed to assess the impact of each mechanism, according to the cross-level clinical coordination conceptual framework.

Results

Of the 6555 articles identified, 30 met the inclusion criteria. All had been conducted in high-income countries, most (n = 26) evaluated the impact of a single mechanism - asynchronous electronic consultations via electronic health records (EHR) - and were limited in terms of design and types and dimensions of cross-level clinical coordination analysed. The evaluation of electronic consultations showed positive impacts on the appropriateness of referrals and accessibility to SC, yet the qualitative studies also highlighted potential risks. Studies on other mechanisms were scarce (shared EHR, email consultations) or non-existent (videoconferencing, mobile applications).

Conclusions

Evidence of the impact of ICT-based mechanisms on clinical coordination between levels is limited. Rigorous evaluations are needed to inform policies and strategies for improving coordination between healthcare levels, thus contributing to high-quality, efficient healthcare.

Real-World Evaluation of an Automated Algorithm to Detect Patients With Potentially Undiagnosed Hypertension Among Patients With Routine Care in Hawai'i

BACKGROUND

This real-world evaluation considers an algorithm designed to detect patients with potentially undiagnosed hypertension, receiving routine care, in a large health system in Hawai'i. It quantifies patients identified as potentially undiagnosed with hypertension; summarizes the individual, clinical, and health system factors associated with undiagnosed hypertension; and examines if the COVID-19 pandemic affected detection.

METHODS AND RESULTS

We analyzed the electronic health records of patients treated across 6 clinics from 2018 to 2021. We calculated total patients with potentially undiagnosed hypertension and compared patients flagged for undiagnosed hypertension to those with diagnosed hypertension and to the full patient panel across individual characteristics, clinical and health system factors (eg, clinic of care), and timing. Modified Poisson regression was used to calculate crude and adjusted risk ratios. Among the eligible patients (N=13 364), 52.6% had been diagnosed with hypertension, 2.7% were flagged as potentially undiagnosed, and 44.6% had no evidence of hypertension. Factors associated with a higher risk of potentially undiagnosed hypertension included individual characteristics (ages 40-84 compared with 18-39 years), clinical (lack of diabetes diagnosis) and health system factors (clinic site and being a Medicaid versus a Medicare beneficiary), and timing (readings obtained after the COVID-19 Stay-At-Home Order in Hawai'i).

CONCLUSIONS

This evaluation provided evidence that a clinical algorithm implemented within a large health system's electronic health records could detect patients in need of follow-up to determine hypertension status, and it identified key individual characteristics, clinical and health system factors, and timing considerations that may contribute to undiagnosed hypertension among patients receiving routine care.

Evaluation of Digitalisation in Healthcare and the Quantification of the "Unmeasurable"

Evaluating healthcare digitalisation, where technology implementation and adoption transforms existing socio-organisational processes, presents various challenges for outcome assessments. Populations are diverse, interventions are complex and evolving over time, meaningful comparisons are difficult as outcomes vary between settings, and outcomes take a long time to materialise and stabilise. Digitalisation may also have unanticipated impacts. We here discuss the limitations of evaluating the digitalisation of healthcare, and describe how qualitative and quantitative approaches can complement each other to facilitate investment and implementation decisions. In doing so, we argue how existing approaches have focused on measuring what is easily measurable and elevating poorly chosen values to inform investment decisions. Limited attention has been paid to understanding processes that are not easily measured even though these can have significant implications for contextual transferability, sustainability and scale-up of interventions. We use what is commonly known as the McNamara Fallacy to structure our discussions. We conclude with recommendations on how we envisage the development of mixed methods approaches going forward in order to address shortcomings.

Development and validation of a case definition to estimate the prevalence and incidence of cirrhosis in pan-Canadian primary care databases

Aims

To develop and validate case definitions to identify patients with cirrhosis and alcohol-related cirrhosis using primary care electronic medical records (EMRs) and to estimate cirrhosis prevalence and incidence in pan-Canadian primary care databases, between 2011 and 2019.

Methods

A total of 689,301 adult patients were included with ≥1 visit to a primary care provider within the Canadian Primary Care Sentinel Study Network between January 1, 2017, and December 31, 2018. A subsample of 17,440 patients was used to validate the case definitions. Sensitivity, specificity, predictive values were calculated with their 95% CIs and then determined the population-level prevalence and incidence trends with the most accurate case definition.

Results

The most accurate case definition included: ≥1 health condition, billing, or encounter diagnosis for International Classification of Diseases, Ninth Revision codes 571.2, 571.5, 789.59, or 571. Sensitivity (84.6; 95% CI 83.1%-86.%), specificity (99.3; 95% CI 99.1%-99.4%), positive predictive values (94.8; 95% CI 93.9%-95.7%), and negative predictive values (97.5; 95% CI 97.3%-97.7%). Application of this definition to the overall population resulted in a crude prevalence estimate of (0.46%; 95% CI 0.45%-0.48%). Annual incidence of patients with a clinical diagnosis of cirrhosis nearly doubled between 2011 (0.05%; 95% CI 0.04%-0.06%) and 2019 to (0.09%; 95% CI 0.08%-0.09%).

Conclusions

The EMR-based case definition accurately captured patients diagnosed with cirrhosis in primary care. Future work to characterize patients with cirrhosis and their primary care experiences can support improvements in identification and management in primary care settings.

Adoption of Electronic Medical Records for Chronic Disease Care in Kenyan Refugee Camps: Quantitative and Qualitative Prospective Evaluation

Background

Noncommunicable disease (NCD) prevention and control in humanitarian emergencies is a well-recognized need, but there is little evidence to guide responses, leading to varying care delivery. The Sana.NCD mobile health (mHealth) app, initially developed in Lebanon, is the only known mHealth tool for NCD management designed to increase care quality and coverage for providers in humanitarian settings.

Objective

We evaluated a specialized mHealth app consisting of an abbreviated medical record for patients with hypertension or diabetes, adapted for a Kenyan refugee camp setting.

Methods

We tested an adapted version of the Sana.NCD app (diabetes and hypertension medical record) in an 11-month (May 2021 to March 2022) quantitative and qualitative prospective evaluation in Kenya's Hagadera refugee camp. Leveraging the rollout of a general electronic medical record (EMR) system in the Kakuma refugee camp, we compared a specialized NCD management app to a general EMR. We analyzed secondary data collected from the Sana.NCD app for 1539 patients, EMR data for 68 patients with NCD from Kakuma's surgical and outpatient departments, and key informant interviews that focused on Hagadera clinic staff perceptions of the Sana.NCD app.

Results

The Hagadera NCD clinic reported 18,801 consultations, 42.1% (n=7918) of which were reported in the NCD app. The Kakuma EMR reported 350,776 visits, of which 9385 (2.7%) were for NCDs (n=4264, 1.2% hypertension; n=2415, 0.7% diabetes). The completeness of reporting was used as a quality-of-care metric. Age, sex, prescribed medicines, random blood sugar, and smoking status were consistently reported in both the NCD app (>98%) and EMR (100%), whereas comorbidities, complications, hemoglobin A1c, and diet were rarely reported in either platform (≤7% NCD app; 0% EMR). The number of visits, BMI, physical activity, and next visit were frequently reported in the NCD app (≥99%) but not in the EMR (≤15%). In the NCD app, the completeness of reporting was high across the implementation period, with little meaningful change. Although not significantly changed during the study, elevated blood sugar (P=.82) and blood pressure (P=.12) were reported for sizable proportions of patients in the first (302/481, 62.8%, and 599/1094, 54.8%, respectively) and last (374/602, 62.1%, and 720/1395, 51.6%, respectively) study quarters. Providers were satisfied with the app, as it standardized patient information and made consultations easier. Providers also indicated that access to historic patient information was easier, benefiting NCD control and follow-up.

Conclusions

A specialized record for NCDs outperformed a more general record intended for use in all patients in terms of reporting completeness. This CommCare-based NCD app can easily be rolled out in similar humanitarian settings with minimal adaptation. However, the adaptation of technologies to the local context and use case is critical for uptake and ensuring that workflows and time burden do not outweigh the benefits of EMRs.

The promise of digital healthcare technologies

Digital health technologies have been in use for many years in a wide spectrum of healthcare scenarios. This narrative review outlines the current use and the future strategies and significance of digital health technologies in modern healthcare applications. It covers the current state of the scientific field (delineating major strengths, limitations, and applications) and envisions the future impact of relevant emerging key technologies. Furthermore, we attempt to provide recommendations for innovative approaches that would accelerate and benefit the research, translation and utilization of digital health technologies.

Mapping the Design Space of Technology-Based Solutions for Better Chronic Pain Care: Introducing the Pain Tech Landscape

OBJECTIVES

Technology has substantial potential to transform and extend care for persons with chronic pain, a burdensome and costly condition. To catalyze the development of impactful applications of technology in this space, we developed the Pain Tech Landscape (PTL) model, which integrates pain care needs with characteristics of technological solutions.

METHODS

Our interdisciplinary group representing experts in pain and human factors research developed PTL through iterative discussions. To demonstrate one potential use of the model, we apply data generated from a narrative review of selected pain and technology journals (2000-2020) in the form of heat map overlays, to reveal where pain tech research attention has focused to date.

RESULTS

The PTL comprises three two-dimensional planes, with pain care needs on each x axis (measurement to management) and technology applications on the y axes according to a) user agency (user- to system-driven), b) usage time frame (temporary to lifelong), and c) collaboration (single-user to collaborative). Heat maps show that existing applications reside primarily in the "user-driven/management" quadrant (e.g., self-care apps). Examples of less developed areas include artificial intelligence and Internet of Things (i.e., Internet-linked household objects), and collaborative/social tools for pain management.

CONCLUSIONS

Collaborative development between the pain and tech fields in early developmental stages using the PTL as a common language could yield impactful solutions for chronic pain management. The PTL could also be used to track developments in the field over time. We encourage periodic reassessment and refinement of the PTL model, which can also be adapted to other chronic conditions.

Can Natural Language Processing and Artificial Intelligence Automate The Generation of Billing Codes From Operative Note Dictations?

STUDY DESIGN

Retrospective Cohort Study.

OBJECTIVES

Using natural language processing (NLP) in combination with machine learning on standard operative notes may allow for efficient billing, maximization of collections, and minimization of coder error. This study was conducted as a pilot study to determine if a machine learning algorithm can accurately identify billing Current Procedural Terminology (CPT) codes on patient operative notes.

METHODS

This was a retrospective analysis of operative notes from patients who underwent elective spine surgery by a single senior surgeon from 9/2015 to 1/2020. Algorithm performance was measured by performing receiver operating characteristic (ROC) analysis, calculating the area under the ROC curve (AUC) and the area under the precision-recall curve (AUPRC). A deep learning NLP algorithm and a Random Forest algorithm were both trained and tested on operative notes to predict CPT codes. CPT codes generated by the billing department were compared to those generated by our model.

RESULTS

The random forest machine learning model had an AUC of .94 and an AUPRC of .85. The deep learning model had a final AUC of .72 and an AUPRC of .44. The random forest model had a weighted average, class-by-class accuracy of 87%. The LSTM deep learning model had a weighted average, class-by-class accuracy 0f 59%.

CONCLUSIONS

Combining natural language processing with machine learning is a valid approach for automatic generation of CPT billing codes. The random forest machine learning model outperformed the LSTM deep learning model in this case. These models can be used by orthopedic or neurosurgery departments to allow for efficient billing.

Changing the paradigm in health and care services: modern value chains using open innovation for the creation of new digital health solutions

Digital Health is a subject of extensive discourse when considering its current and future significance. This significance arises from a convergence of various factors, including the escalating capabilities and cost-effectiveness of computing and communication technology, coupled with the mounting demands and challenges faced by healthcare systems. The integration of health and technology, when studied collectively with the purpose of addressing tangible real-world issues, holds the potential to generate substantial outcomes that greatly influence the provision of clinical and social care, thereby enhancing the overall well-being of both individuals and populations. In this sense, in this paper we propose a collaborative approach, using Open Innovation, where the most relevant stakeholders-health and care professionals, citizens and companies-work together to develop and validate innovative digital solutions for health and care. We have called this approach of value co-creation the Collaborative Ecosystem, and we focus specifically on the potential development of the Regional Ecosystem for Collaborative Innovation in Digital Health and Care, and the envisioned implications of its implementation in economic and social dimensions.

Evaluating the costs and consequences of computerized clinical decision support systems in hospitals: a scoping review and recommendations for future practice

OBJECTIVE

Sustainable investment in computerized decision support systems (CDSS) requires robust evaluation of their economic impacts compared with current clinical workflows. We reviewed current approaches used to evaluate the costs and consequences of CDSS in hospital settings and presented recommendations to improve the generalizability of future evaluations.

MATERIALS AND METHODS

A scoping review of peer-reviewed research articles published since 2010. Searches were completed in the PubMed, Ovid Medline, Embase, and Scopus databases (last searched February 14, 2023). All studies reported the costs and consequences of a CDSS-based intervention compared with current hospital workflows. Findings were summarized using narrative synthesis. Individual studies were further appraised against the Consolidated Health Economic Evaluation and Reporting (CHEERS) 2022 checklist.

RESULTS

Twenty-nine studies published since 2010 were included. Studies evaluated CDSS for adverse event surveillance (5 studies), antimicrobial stewardship (4 studies), blood product management (8 studies), laboratory testing (7 studies), and medication safety (5 studies). All studies evaluated costs from a hospital perspective but varied based on the valuation of resources affected by CDSS implementation, and the measurement of consequences. We recommend future studies follow guidance from the CHEERS checklist; use study designs that adjust for confounders; consider both the costs of CDSS implementation and adherence; evaluate consequences that are directly or indirectly affected by CDSS-initiated behavior change; examine the impacts of uncertainty and differences in outcomes across patient subgroups.

DISCUSSION AND CONCLUSION

Improving consistency in the conduct and reporting of evaluations will enable detailed comparisons between promising initiatives, and their subsequent uptake by decision-makers.

Evaluation of an Electronic Care and Rehabilitation Planning Tool With Stroke Survivors With Aphasia: Usability Study

BACKGROUND

Patients with chronic illnesses with physical and cognitive disabilities, particularly stroke survivors with aphasia, are often not involved in design and evaluation processes. As a consequence, existing eHealth services often do not meet the needs of this group of patients, which has resulted in a digital divide.

OBJECTIVE

The aim of this study was to examine the effectiveness and user satisfaction of an electronic care and rehabilitation planning tool from the perspective of stroke survivors with aphasia. This would help us gain knowledge on how such a tool would need to be adapted for these patients for further development.

METHODS

Usability tests were conducted with 9 postdischarge stroke survivors with aphasia. Effectiveness was measured using task-based tests, and user satisfaction was studied through qualitative interviews at the end of each test. All tests were audio recorded, and each test lasted approximately 1 hour. The data were analyzed using qualitative content analysis. As the tool can be used by stroke survivors either independently or with some support from their next of kin or care professionals, the research group decided to divide the participants into 2 groups. Group 1 did not receive any support during the tests, and group 2 received some minor support from the moderator.

RESULTS

The results showed that the care and rehabilitation planning tool was not effective for stroke survivors with aphasia, as many participants in group 1 did not accomplish the tasks successfully. Despite several usability problems and challenges in using the tool because of patients' disabilities, the participants were positive toward using the tool and found it useful for their care and rehabilitation journey.

CONCLUSIONS

There is a need to involve patients with chronic illnesses more in the design and evaluation processes of health information systems and eHealth services. eHealth services and health information systems designed for this group of patients should be more adaptable and flexible to provide them with appropriate functionalities and features, meet their needs, and be useful and easy to use. In addition, the design and evaluation processes should be adapted, considering the challenges of this patient group.

Digital Health Data Quality Issues: Systematic Review

BACKGROUND

The promise of digital health is principally dependent on the ability to electronically capture data that can be analyzed to improve decision-making. However, the ability to effectively harness data has proven elusive, largely because of the quality of the data captured. Despite the importance of data quality (DQ), an agreed-upon DQ taxonomy evades literature. When consolidated frameworks are developed, the dimensions are often fragmented, without consideration of the interrelationships among the dimensions or their resultant impact.

OBJECTIVE

The aim of this study was to develop a consolidated digital health DQ dimension and outcome (DQ-DO) framework to provide insights into 3 research questions: What are the dimensions of digital health DQ? How are the dimensions of digital health DQ related? and What are the impacts of digital health DQ?

METHODS

Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a developmental systematic literature review was conducted of peer-reviewed literature focusing on digital health DQ in predominately hospital settings. A total of 227 relevant articles were retrieved and inductively analyzed to identify digital health DQ dimensions and outcomes. The inductive analysis was performed through open coding, constant comparison, and card sorting with subject matter experts to identify digital health DQ dimensions and digital health DQ outcomes. Subsequently, a computer-assisted analysis was performed and verified by DQ experts to identify the interrelationships among the DQ dimensions and relationships between DQ dimensions and outcomes. The analysis resulted in the development of the DQ-DO framework.

RESULTS

The digital health DQ-DO framework consists of 6 dimensions of DQ, namely accessibility, accuracy, completeness, consistency, contextual validity, and currency; interrelationships among the dimensions of digital health DQ, with consistency being the most influential dimension impacting all other digital health DQ dimensions; 5 digital health DQ outcomes, namely clinical, clinician, research-related, business process, and organizational outcomes; and relationships between the digital health DQ dimensions and DQ outcomes, with the consistency and accessibility dimensions impacting all DQ outcomes.

CONCLUSIONS

The DQ-DO framework developed in this study demonstrates the complexity of digital health DQ and the necessity for reducing digital health DQ issues. The framework further provides health care executives with holistic insights into DQ issues and resultant outcomes, which can help them prioritize which DQ-related problems to tackle first.

Time Utilization Among Immunization Clinics Using an Electronic Immunization Registry (Part 2): Time and Motion Study of Modified User Workflows

BACKGROUND

Digital health interventions have the potential to improve the provision of health care services through digitized data collection and management. Low- and middle-income countries are beginning to introduce electronic immunization registries (EIRs) into their routine immunization services to better capture and store childhood vaccination information. Especially in Africa, where 25% of children remain unimmunized or underimmunized, technologies that can help identify children due for a vaccination are particularly important for improving vaccination coverage. However, an improved understanding of the effectiveness of these systems is needed to develop and deploy sustainable EIRs in low- and middle-income countries.

OBJECTIVE

We conducted an interventional pretest-posttest design study that sought to improve time efficiency through workflow modifications in Kenyan immunization clinics. Our aim was to describe how activity times differed after introducing workflow modifications that could potentially reduce the time needed to perform routine data entry activities. Our intent was to demonstrate changes in efficiency when moving from the existing dual-data entry workflow to a future paperless workflow by health facility size and experience length of health care workers (HCWs).

METHODS

We tested how 3 workflow modifications would affect time utilization among HCWs using the EIR at the point of care compared with baseline immunization clinic workflows. Our outcome of interest was the time taken to complete individual activities and a patient's total time in the clinic where we compared the time spent during the baseline workflow with that during the modified workflow. We used a standardized tool to observe and document the immunization clinic workflow. To estimate differences in time utilization, we used bivariate analyses and fit multivariate linear mixed-effects models.

RESULTS

Our study found that for HCWs using an EIR, the introduction of modified workflows decreased the amount of time needed to provide services to children seen in the immunization clinic. With a baseline mean time of 10 minutes spent per child, this decreased by about 3 minutes when the preparation modification was introduced and almost 5 minutes for the paperless and combined modifications. Results pertaining to the EIR's performance and ability to connect to the internet were particularly insightful about potential causes of delays.

CONCLUSIONS

We were able to conduct a concise clinical simulation exercise by introducing modified workflows and estimating their impact on time utilization in immunization clinics using an EIR. We found that the paperless workflow provided the largest time savings when delivering services, although this was threatened by poor EIR performance and internet connectivity. This study demonstrated that not only should digital health interventions be built and adapted for particular use cases but existing user workflows also need to adapt to new technology.

Integration of a Digital Health Intervention Into Immunization Clinic Workflows in Kenya: Qualitative, Realist Evaluation of Technology Usability

BACKGROUND

In an effort to increase vaccination coverage in low-resource settings, digital tools have been introduced to better track immunization records, improve data management practices, and provide improved access to vaccination coverage data for decision-making. Despite the potential of these electronic systems to improve the provision of health services, few digital health interventions have been institutionalized at scale in low- and middle-income countries.

OBJECTIVE

In this paper, we aimed to describe how health care workers in Kenya had integrated an electronic immunization registry into their immunization clinic workflows and to use these findings to inform the development of a refined program theory on the registry's usability.

METHODS

Informed by realist methodology, we developed a program theory to explain usability of the electronic immunization registry. We designed a qualitative study based on our theory to describe the barriers and facilitators influencing data entry and use. Qualitative data were collected through semistructured interviews with users and workflow observations of immunization clinic sessions. Our findings were summarized by context-mechanism-outcome relationships formed after analyzing our key themes across interviews and workflow observations. Using these relationships, we were able to identify common rules for future implementers.

RESULTS

Across the 12 facilities included in our study, 19 health care workers were interviewed, and 58 workflow sessions were observed. The common rules developed from our qualitative findings are as follows: rule 1-ensure that the users complete training to build familiarity with the system, understand the value of the system and data, and know where to find support; rule 2-confirm that the system captures all data needed for users to provide routine health care services and is easy to navigate; rule 3-identify work-arounds for poor network, system performance, and too few staff or resources; and rule 4-make users aware of expected changes to their workflow, and how these changes might differ over time and by facility size or number of patients. Upon study completion, we revised the program theory to reflect the importance of the goals and workflows of electronic immunization registries aligning with reality.

CONCLUSIONS

We created a deeper understanding of the underlying mechanisms for usability of the registry. We found that the electronic immunization registry had high acceptability among users; however, there were numerous barriers to using the system, even under ideal conditions, causing a misalignment between the system and the reality of the users' workflows and their environment. Human-centered design and human-factors methods can assist during pilot stages to better align systems with users' needs and again after scale-up to ensure that interventions are suitable for all user settings.

Improving Implementation of an Electronic Prescription System for COVID-19 Vaccination in the Czech Republic: Process Modeling Approach

BACKGROUND

It is very difficult to find a consensus that will be accepted by most players when creating health care legislation. The Czech electronic prescription system was launched in 2011 and new functions were introduced in 2018. To ensure that these functions will not conflict with any other existing law, a process modeling tool based on the patent "Method and system for automated requirements modeling" was used successfully in the Czech Republic for the first time.

OBJECTIVE

The aim of this project was to develop another successful application of process modeling to add COVID-19 vaccination records to the existing electronic prescription system.

METHODS

The method employed was based on the mathematical theory of hierarchical state diagrams and process models. In the first step, sketches that record the results of informal discussions, interviews, meetings, and workshops were prepared. Subsequently, the architecture containing the main participants and their high-level interactions was drafted. Finally, detailed process diagrams were drawn. Each semiresult was discussed with all involved team members and stakeholders to incorporate all comments. By repeating this procedure, individual topics were gradually resolved and the areas of discussion were narrowed down until reaching complete agreement.

RESULTS

This method proved to be faster, clearer, and significantly simpler than other methods. Owing to the use of graphic tools and symbols, the risk of errors, inaccuracies, and misunderstandings was significantly reduced. The outcome was used as an annex to the bill in the legislative process. One of the main benefits of this approach is gaining a higher level of understanding for all parties involved (ie, legislators, the medical community, patient organizations, and information technology professionals). The process architecture model in a form of a graphic scheme has proven to be a valuable communication platform and facilitated negotiation between stakeholders. Moreover, this model helped to avoid several inconsistencies that appeared during workshops and discussions. Our method worked successfully even when participants were from different knowledge areas.

CONCLUSIONS

The vaccination record process model was drafted in 3 weeks and it took a total of 2 months to pass the bill. In comparison, the initial introduction of the electronic prescription system using conventional legislative methods took over 1 year, involving immediate creation of a text with legislative intent, followed by paragraph-by-section wording of the legislation that was commented on directly. These steps are repeated over and over, as any change in any part of the text has to be checked and rechecked within the entire document. Compared with conventional methods, we have shown that using our method for the process of modification of legislation related to such a complex issue as the integration of COVID-19 vaccination into an electronic prescription model significantly simplifies the preparation of a legislative standard.

Developing Usability Guidelines for mHealth Applications (UGmHA)

Mobile health (mHealth) is a branch of electronic health (eHealth) technology that provides healthcare services using smartphones and wearable devices. However, most mHealth applications were developed without applying mHealth specialized usability guidelines. Although many researchers have used various guidelines to design and evaluate mHealth applications, these guidelines have certain limitations. First, some of them are general guidelines. Second, others are specified for mHealth applications; however, they only cover a few features of mHealth applications. Third, some of them did not consider accessibility needs for the elderly and people with special needs. Therefore, this paper proposes a new set of usability guidelines for mHealth applications (UGmHA) based on Quinones et al.’s formal methodology, which consists of seven stages starting from the Exploratory stage and ending with the Refining stage. What distinguishes these proposed guidelines is that they are easy to follow, consider the feature of accessibility for the elderly and people with special needs and cover different features of mHealth applications. In order to validate UGmHA, an experiment was conducted on two applications in Saudi Arabia using UGmHA versus other well-known usability guidelines to discover usability issues. The experimental results show that the UGmHA discovered more usability issues than did the other guidelines.

Machine learning-driven clinical decision support system for concept-based searching: a field trial in a Norwegian hospital

BACKGROUND

Natural language processing (NLP) based clinical decision support systems (CDSSs) have demonstrated the ability to extract vital information from patient electronic health records (EHRs) to facilitate important decision support tasks. While obtaining accurate, medical domain interpretable results is crucial, it is demanding because real-world EHRs contain many inconsistencies and inaccuracies. Further, testing of such machine learning-based systems in clinical practice has received limited attention and are yet to be accepted by clinicians for regular use.

METHODS

We present our results from the evaluation of an NLP-driven CDSS developed and implemented in a Norwegian Hospital. The system incorporates unsupervised and supervised machine learning combined with rule-based algorithms for clinical concept-based searching to identify and classify allergies of concern for anesthesia and intensive care. The system also implements a semi-supervised machine learning approach to automatically annotate medical concepts in the narrative.

RESULTS

Evaluation of system adoption was performed by a mixed methods approach applying The Unified Theory of Acceptance and Use of Technology (UTAUT) as a theoretical lens. Most of the respondents demonstrated a high degree of system acceptance and expressed a positive attitude towards the system in general and intention to use the system in the future. Increased detection of patient allergies, and thus improved quality of practice and patient safety during surgery or ICU stays, was perceived as the most important advantage of the system.

CONCLUSIONS

Our combined machine learning and rule-based approach benefits system performance, efficiency, and interpretability. The results demonstrate that the proposed CDSS increases detection of patient allergies, and that the system received high-level acceptance by the clinicians using it. Useful recommendations for further system improvements and implementation initiatives are reducing the quantity of alarms, expansion of the system to include more clinical concepts, closer EHR system integration, and more workstations available at point of care.

Bibliometric analysis on the adoption of artificial intelligence applications in the e-health sector

Artificial Intelligent (AI) applications in e-health have evolved considerably in the last 25 years. To track the current research progress in this field, there is a need to analyze the most recent trend of adopting AI applications in e-health. This bibliometric analysis study covers AI applications in e-health. It differs from the existing literature review as the journal articles are obtained from the Scopus database from its beginning to late 2021 (25 years), which depicts the most recent trend of AI in e-health. The bibliometric analysis is employed to find the statistical and quantitative analysis of available literature of a specific field of study for a particular period. An extensive global literature review is performed to identify the significant research area, authors, or their relationship through published articles. It also provides the researchers with an overview of the work evolution of specific research fields. The study's main contribution highlights the essential authors, journals, institutes, keywords, and states in developing the AI field in e-health.

New Frontiers of Natural Language Processing in Surgery

The vast and ever-growing volume of electronic health records (EHR) have generated a wealth of information-rich data. Traditional, non-machine learning data extraction techniques are error-prone and laborious, hindering the analytical potential of these massive data sources. Equipped with natural language processing (NLP) tools, surgeons are better able to automate, and customize their review to investigate and implement surgical solutions. We identify current perioperative applications of NLP algorithms as well as research limitations and future avenues to outline the impact and potential of this technology for progressing surgical innovation.

Compas-Y: A mixed methods pilot evaluation of a mobile self-compassion training for people with newly diagnosed cancer

Objective

Compas-Y is a compassionate mind training app that was co-designed to be fully adapted to mobile technology and to people with newly diagnosed cancer. This study aimed to evaluate the use, appreciation and impact of the app.

Methods

Seventy-one people with cancer who created an app account were included (38% breast cancer, 72% diagnosed <4 months ago, 76% received chemotherapy). Participants had very high baseline scores of self-compassion. In a convergent mixed methods design, back-end log-data (n = 71), pre-post surveys (n = 34) and semi-structured interviews (n = 23) collected for >8 weeks and were concurrently analysed using joint displays.

Results

About half of the participants (45%) used 4 of the 6 modules. Compas-Y was highly appreciated, with all content considered relevant and a source of support. Experienced benefits related to improved mental health. Particularly, we found significant changes in anxiety, but not in depression or well-being. In the interviews, people reported experiencing more rest and more positive emotions due to using the app. Process benefits included significant reductions in self-criticism (inadequate self and self-blame), but not self-compassion. In the interviews, people reported improved self-compassion and less self-criticism, more self-awareness, recognition and support, and improved emotion regulation and coping. The surveys did not capture the full range of outcomes that participants reported in the interviews.

Conclusions

Compas-Y is a highly appreciated mobile intervention that supported users in aspects of their mental health. Findings are discussed in terms of reach and adherence, app functionalities, co-design and tailoring of cancer-related and compassion-based eHealth.

Optimising the educational value of indirect patient care

INTRODUCTION

Indirect patient care activities (IPCA) such as documentation, reviewing investigations and filling out forms require an increasing amount of physician time. While an essential part of patient care, rising rates of IPCA work correspond with increases in physician burnout and job dissatisfaction. It is not known how best to prepare residents in IPCA-heavy specialties (e.g. family medicine) for this aspect of their career. This study investigates how educators and residency programmes can optimise IPCA work during residency to best prepare residents for future practice.

METHODS

Using Constructivist Grounded Theory, we conducted focus groups and individual interviews with 42 clinicians (19 family medicine residents, 16 family physicians in the first 5 years of practice and 7 family physician educators). All participants were connected to one family medicine residency programme. We analysed interview data iteratively, using a staged approach to constant comparative analysis.

RESULTS

While residents, early career physicians and educators perceived the educational value of IPCAs differently, they all reported IPCAs as a necessary weight that family physicians carry throughout their career. Some residents described IPCAs as a burden, creating inequities in workload and interfering with other learning and personal opportunities. In contrast, educators conceptualised IPCAs as an opportunity to build and develop the skills required to carry the weight of IPCAs throughout their career. We make specific recommendations for helping residents recognise this educational opportunity, such as clarifying expectations, navigating equity, understanding purpose and maintaining consistency when teaching IPCAs.

CONCLUSION

IPCAs are a key competency for many medical residents but require explicit pedagogical attention. If the educational opportunities are not made explicit, residents may miss the opportunity to develop strategies for practice management, professional boundaries, and administrative efficiencies.

Measurement Properties of Remotely or Self-Administered Lower Extremity Mobility Performance Measures in Adults: A Systematic Review

OBJECTIVE

For individuals who face barriers to care assessment, there is a need for remote administration or self-administration of physical performance measures that assess mobility to determine current functional status and to monitor and predict future changes in functional status. The primary purpose of this review is to evaluate the available measurement properties of scores for remotely or self-administered lower extremity mobility performance measures in adults. This review also outlines the test procedures and population suitability of these measures.

METHODS

Data sources were Ovid MEDLINE, Ovid Embase, EBSCOhost CINAHL, Ovid AMED, and Cochrane CENTRAL-which were searched from inception to January 26, 2021-and the reference lists of relevant studies. Two individuals independently screened studies that assessed at least 1 prespecified measurement property of scores for a remote and/or self-administered lower extremity physical performance measure assessing mobility in an adult population. Two individuals independently extracted data on study characteristics, measurement properties, feasibility, and interpretability using piloted extraction forms. The COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) Risk of Bias tool was used to assess methodological quality. Data were qualitatively summarized, and results were compared against COSMIN's criteria for good measurement properties. Level of evidence was determined using COSMIN's modified GRADE approach.

RESULTS

Fourteen studies detailing 19 outcome measures were included. Many studies displayed "sufficient" measurement properties based on COSMIN's criteria; however, risk of bias for most of the included studies was rated adequate or doubtful.

CONCLUSION

Clinicians and researchers can consider the measurement properties of scores and feasibility of different approaches presented in this review when determining how to assess or monitor mobility in adult populations.

IMPACT

Assessing mobility via remote or self-administered physical performance measures in adult populations appears to be feasible using a variety of methods including simple tools (chair, stopwatch), videoconferencing, and smartphone applications. This strategy may be particularly valuable for self-management of chronic conditions and decreasing barriers to accessing care.

An exploration of expectations and perceptions of practicing physicians on the implementation of computerized clinical decision support systems using a Qsort approach

BACKGROUND

There is increasing interest in incorporating clinical decision support (CDS) into electronic healthcare records (EHR). Successful implementation of CDS systems depends on acceptance of them by healthcare workers. We used a mix of quantitative and qualitative methods starting from Qsort methodology to explore expectations and perceptions of practicing physicians on the use of CDS incorporated in EHR.

METHODS

The study was performed in a large tertiary care academic hospital. We used a mixed approach with a Q-sort based classification of pre-defined reactions to clinical case vignettes combined with a thinking-aloud approach, taking into account COREQ recommendations The open source software of Ken-Q Analysis version 1.0.6. was used for the quantitative analysis, using principal components and a Varimax rotation. For the qualitative analysis, a thematic analysis based on the four main themes was performed based on the audiotapes and field notes.

RESULTS

Thirty physicians were interviewed (7 in training, 8 junior staff and 15 senior staff; 16 females). Nearly all respondents were strongly averse towards interruptive messages, especially when these also were obstructive. Obstructive interruption was considered to be acceptable only when it increases safety, is adjustable to user expertise level and/or allows deviations when the end-user explains why a deviation is desirable in the case at issue. Transparency was deemed an essential feature, which seems to boil down to providing sufficient clarification on the factors underlying the recommendations of the CDS, so that these can be compared against the physicians' existing knowledge, beliefs and convictions.

CONCLUSION

Avoidance of disruptive workflows and transparency of the underlying decision processes are important points to consider when developing CDS systems incorporated in EHR.

eHealth Literacy in German Skin Cancer Patients

The global incidence of skin cancer has steadily increased in recent years, and malignant melanoma still has one of the fastest-growing incidence rates among all malignant tumors in the western world. Thus, newly diagnosed patients have an increased need for health information concerning their disease. Using a standardized questionnaire, our study aims to investigate our patients’ primary sources of health-related information as well as their self-proclaimed eHealth literacy. We received 714 questionnaires. Regardless of age, the primary source of information was the treating dermato-oncologist, followed by the treating general practitioner and the Internet. However, with increasing age, the usage of the Internet decreased. Hence, younger participants were better equipped to find health-related information while using the Internet. Additionally, comprehending health-related information and gaining medical knowledge was significantly increased in better-educated participants. Overall, our study shows that with increased use of eHealth services, accessing web-based information increased, correlating with a better eHealth literacy of our patients. eHealth technologies are increasingly becoming more prevalent as a primary source of information in our modern health care system. Thus, it is crucial to educate cancer patients in eHealth literacy to make autonomous, informed decisions and gain more confidence in dealing with their disease.

The association between stress attributed to information systems and the experience of workplace aggression: a cross-sectional survey study among Finnish physicians

Background

Physicians commonly suffer from workplace aggression and its negative consequences. Previous studies have shown that stressors such as job demands increase the risk of inappropriate treatment at workplace. Poorly functioning, and constantly changing information systems form a major work stressor for physicians. The current study examined the association between physicians’ stress attributed to information systems (SAIS) and their experiences of workplace aggression. Workplace aggression covered physical and non-physical aggression, perpetrated by coworkers, patients, patient’s relatives, or supervisors.

Methods

A cross-sectional survey study was conducted. The participants included 2786 physicians (67.4% women) who were sampled randomly from the registry of Finnish Medical Association, which covers almost all of the Finnish physician population. First, bivariate associations were studied among participant characteristics, SAIS and workplace aggression. Logistic regression analysis was then used to further determine how SAIS was associated with the likelihood of experiencing different types of aggression.

Results

Higher levels of SAIS were associated with higher likelihood of aggression with regard to all types of aggression, except non-physical aggression perpetrated by patients or relatives. The demographic factors (work-sector, gender, age) did not have a noticeable influence on the association between SAIS and aggression.

Conclusions

The present results build on previous evidence on the prevalence of SAIS and its negative effects on healthcare workers. Since SAIS may increase the risk of experiencing aggression, it is possible that SAIS also endangers the wellbeing of physicians and thereby the quality of patient care. Resourcing time and training during introduction of a new IS could alleviate time pressure and thus stress attributed to managing new information systems. The role of organizational climate and general workload in arousing SAIS and aggression should be examined in future studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08116-w.

Addressing the Challenges of Electronic Health Records Using Blockchain and IPFS

Electronic Health Records (EHR) are the healthcare sector's core digital strategy meant to improve the quality of care provided to patients. Despite the benefits afforded by this digital transformation initiative, adoption among healthcare organizations has been slower than desired. The sheer volume and sensitive nature of patient records compel these organizations to exercise a healthy amount of caution in implementing EHR. Cyberattacks have also increased the risks associated with non-optimal EHR implementations. An influx of high-profile data breaches has plagued the sector during the COVID-19 pandemic, which put the spotlight on EHR cybersecurity. One objective of this research project is to aid the acceleration of EHR adoption. Another objective is to ensure the robustness of the system to resist malicious attacks. For the former, a systematic review was used to unearth all the possible causes why the adoption of EHR has been anemic. In this paper, sixty-five existing proposed EHR solutions were analyzed and it was found that there are fourteen major challenges that need to be addressed to reduce friction and risk for health organizations. These were privacy, security, confidentiality, interoperability, access control, scalability, authentication, accessibility, availability, data storage, data ownership, data validity, data integrity, and ease of use. We propose EHRChain, a new framework that tackles all the listed challenges simultaneously to address the first objective while also being designed to achieve the second objective. It is enabled by dual-blockchains based on Hyperledger Sawtooth to allow patient data decentralization via a consortium blockchain and IPFS for distributed data storage.

Attitudes and Perceptions of Health Leaders for the Quality Enhancement of Workforce in Saudi Arabia

BACKGROUND AND AIM

Besides the unique exposure and experience of health leaders in facing challenges and overcoming them, and the relatively fewer articles relating to the perception of health leaders in workforce quality enhancement, health leadership plays a crucial role in redirecting the workforce, increasing job satisfaction, professional development, and burnout prevention. Thus, this study aimed to understand the current healthcare workforce quality and future expectations from the attitudes and perceptions of health leaders.

METHODS

A qualitative research was carried out using semi-structured interviews consisting of 24 different questions. Participants of the study were healthcare leaders from different backgrounds and governmental institutions. All interviews were recorded, transcribed, and then analyzed using thematic analysis via the N-Vivo program.

RESULTS

Eleven participants were involved in the study, with one female and ten males. A thematic analysis and N-Vivo program yielded 5 main themes: (1) workforce competency, (2) health transformation, (3) leadership, (4) workforce planning, and (5) healthcare quality, with 22 emerging sub-themes. Moreover, participants responded with different attitudes and perceptions.

CONCLUSION

Health leaders are satisfied with the current direction of workforce competency and planning, yet fragmentation of the system and poor accessibility may need further enhancement. Furthermore, misutilization of services and the uncertainty of the future and talent pool are potential barriers for capability building. Moreover, with the existing gap in the workforce, health leaders believe that privatization and corporatization may have a positive effect. Aside from that, Saudization with the current plan of having a minimum standard of accepting non-Saudis in certain areas might benefit in maintaining competition and enriching experience. However, catching up with further research in healthcare quality in Saudi Arabia is needed because of the ongoing health transformation.

eHealth Tools That Assess and Track Health and Well-being in Children and Young People: Systematic Review

Background

eHealth tools that assess and track health outcomes in children or young people are an emerging type of technology that has the potential to reform health service delivery and facilitate integrated, interdisciplinary care.

Objective

The aim of this review is to summarize eHealth tools that have assessed and tracked health in children or young people to provide greater clarity around the populations and settings in which they have been used, characteristics of digital devices (eg, health domains, respondents, presence of tracking, and connection to care), primary outcomes, and risks and challenges of implementation.

Methods

A search was conducted in PsycINFO, PubMed or MEDLINE, and Embase in April 2020. Studies were included if they evaluated a digital device whose primary purpose was to assess and track health, focused on children or young people (birth to the age of 24 years), reported original research, and were published in peer-reviewed journals in English.

Results

A total of 39 papers were included in this review. The sample sizes ranged from 7 to 149,329 participants (median 163, mean 5155). More studies were conducted in urban (18/39, 46%) regions than in rural (3/39, 8%) regions or a combination of urban and rural areas (8/39, 21%). Devices were implemented in three main settings: outpatient health clinics (12/39, 31%), hospitals (14/39, 36%), community outreach (10/39, 26%), or a combination of these settings (3/39, 8%). Mental and general health were the most common health domains assessed, with a single study assessing multiple health domains. Just under half of the devices tracked children’s health over time (16/39, 41%), and two-thirds (25/39, 64%) connected children or young people to clinical care. It was more common for information to be collected from a single informant (ie, the child or young person, trained health worker, clinician, and parent or caregiver) than from multiple informants. The health of children or young people was assessed as a primary or secondary outcome in 36% (14/39) of studies; however, only 3% (1/39) of studies assessed whether using the digital tool improved the health of users. Most papers reported early phase research (formative or process evaluations), with fewer outcome evaluations and only 3 randomized controlled trials. Identified challenges or risks were related to accessibility, clinical utility and safety, uptake, data quality, user interface or design aspects of the device, language proficiency or literacy, sociocultural barriers, and privacy or confidentiality concerns; ways to address these barriers were not thoroughly explored.

Conclusions

eHealth tools that assess and track health in children or young people have the potential to enhance health service delivery; however, a strong evidence base validating the clinical utility, efficacy, and safety of tools is lacking, and more thorough investigation is needed to address the risks and challenges of using these emerging technologies in clinical care. At present, there is greater potential for the tools to facilitate multi-informant, multidomain assessments and longitudinally track health over time and room for further implementation in rural or remote regions and community settings around the world.

"Many roads lead to Rome and the Artificial Intelligence only shows me one road": an interview study on physician attitudes regarding the implementation of computerised clinical decision support systems

Research regarding the drivers of acceptance of clinical decision support systems (CDSS) by physicians is still rather limited. The literature that does exist, however, tends to focus on problems regarding the user-friendliness of CDSS. We have performed a thematic analysis of 24 interviews with physicians concerning specific clinical case vignettes, in order to explore their underlying opinions and attitudes regarding the introduction of CDSS in clinical practice, to allow a more in-depth analysis of factors underlying (non-)acceptance of CDSS. We identified three general themes from the results. First, 'the perceived role of the AI', including items referring to the tasks that may properly be assigned to the CDSS according to the respondents. Second, 'the perceived role of the physician', referring to the aspects of clinical practice that were seen as being fundamentally 'human' or non-automatable. Third, 'concerns regarding AI', including items referring to more general issues that were raised by the respondents regarding the introduction of CDSS in general and/or in clinical medicine in particular. Apart from the overall concerns expressed by the respondents regarding user-friendliness, we will explain how our results indicate that our respondents were primarily occupied by distinguishing between parts of their job that should be automated and aspects that should be kept in human hands. We refer to this distinction as 'the division of clinical labor.' This division is not based on knowledge regarding AI or medicine, but rather on which parts of a physician's job were seen by the respondents as being central to who they are as physicians and as human beings. Often the respondents' view that certain core parts of their job ought to be shielded from automation was closely linked to claims concerning the uniqueness of medicine as a domain. Finally, although almost all respondents claimed that they highly value their final responsibility, a closer investigation of this concept suggests that their view of 'final responsibility' was not that demanding after all.

The Current and Future Role of Technology in Respiratory Care

Over the past few decades, technology and improvements in artificial intelligence have dramatically changed major sectors of our day-to-day lives, including the field of healthcare. E-health includes a wide range of subdomains, such as wearables, smart-inhalers, portable electronic spirometers, digital stethoscopes, and clinical decision support systems. E-health has been consistently shown to enhance the quality of care, improve adherence to therapy, and allow early detection of worsening in chronic pulmonary diseases. The present review addresses the current and potential future role of major e-health tools and approaches in respiratory medicine, with the aim of providing readers with trustful and updated evidence to increase their awareness of the topic, and to allow them to optimally benefit from the latest innovation technology. Collected literature evidence shows that the potential of technology tools in respiratory medicine mainly relies on three fundamental interactions: between clinicians, between clinician and patient, and between patient and health technology. However, it would be desirable to establish widely agreed and adopted standards for conducting trials and reporting results in this area, as well as to take into proper consideration potentially relevant pitfalls related to privacy protection and compliance with regulatory procedures.

Artificial intelligence and the future of midwifery: What do midwives think about artificial intelligence? A qualitative study

The evidence on how AI will make a revolution is insufficient. Our aim was to investigate opinions of midwives on the future of AI and midwifery. Semi-structured interviews were done with 18 midwives in Turkey. Themes were identified: expectations included the advantages and conditional acceptance of robotic technology, prejudices reflected perceived shortcomings, lack of human competencies, and trust issues. Concerns included midwifery care and concerns about her future. Midwives were overwhelmingly skeptical about the replacement of human capabilities by AI and found the technology's potential limited.