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BACKGROUND There is currently no consensus on the impact of a higher co-author scale (the number of authors) on paper citation. No studies have comprehensively explored the interaction effects of co-author scale and paper characteristics on paper citations. OBJECTIVE We aimed to determine the interaction effects between co-author scale and paper characteristics on paper citations in medical informatics. METHODS A total of 34,399 papers were included in this study. Highly-cited papers were identified among the top 10% of all published papers in the current year. Logistic regression analyses were conducted to estimate the associations between co-author scale and paper citation. RESULTS We found that higher co-author scale was significantly associated with highly-cited papers. Significant independent risk factors were identified using multivariate analysis. A subgroup analysis showed that higher co-author scale significantly increased the probability of a paper becoming highly-cited if it was published in the past 9-14 years (OR = 1.24; 95% CI: 1.03 –1.50), has 20-30 references (OR = 1.38; 95% CI: 1.13 –1.70), was a funded paper (OR = 1.30; 95% CI: 1.11 –1.52), was published in a European journal (OR = 1.22; 95% CI: 1.06 –1.40), or was published in multi-disciplinary (≥5) journals (OR = 1.70; 95% CI: 1.38 –2.08). CONCLUSIONS Our study demonstrated that there was a statistically significant interaction effect between co-author scale and paper characteristics on paper citation in medical informatics. These results provide further empirical evidence on the association between co-author scale, paper characteristics, and paper citation, and provide suggestions for researchers who are launching new projects.

BACKGROUND Emergency department (ED) providers are important collaborators in preventing falls for older adults because they are often the first healthcare providers to see a patient after a fall and because at-home falls are often preceded by previous ED visits. Previous work has shown that ED referrals to falls interventions can reduce the risk of an at-home fall by 38%. Screening patients at risk for a fall can be time-consuming and difficult to implement in the ED setting. Machine learning (ML) and clinical decision support (CDS) offer the potential of automating the screening process. However, it remains unclear whether automation of screening and referrals can reduce the risk of future falls among older patients. OBJECTIVE The goal of this paper to is describe a research protocol for evaluating effectiveness of an automated screening and referral intervention. These findings will inform ongoing discussions about the use of machine learning and artificial intelligence to augment medical decision making. METHODS To assess effectiveness of our program for patients receiving the falls risk intervention, our primary analysis will be to obtain referral completion rate at three different EDs. We use a quasi-experimental design known as a sharp regression discontinuity with regards to intent-to-treat, since the intervention is administered to patients whose risk score falls above some threshold. A conditional logistic regression model will be built to describe six-month fall risk at each site as a function of the intervention, patient demographics, and risk score. The odds ratio of return visit for fall and its 95% confidence interval will be estimated comparing those that identified as high risk by the ML-based CDS (ML-CDS) and those who were not but had a similar risk profile. RESULTS The ML-CDS tool under study has been implemented at two of the three EDs in our study. As of April 2023, a total of 1326 patient encounters have been flagged for providers, and 339 unique patients have been referred to the mobility and falls clinic. To date, 45 (15%) patients have scheduled an appointment with the clinic. CONCLUSIONS This study seeks to quantify the impact of an ML-CDS intervention on patient behavior and outcomes. Our end-to-end dataset allows for a more meaningful analysis of patient outcomes than other studies focused on interim outcomes, and our multi-site implementation plan will demonstrate applicability to a broad population and possibility to adapt intervention to other emergency departments and achieve similar results. Our statistical methodology, regression discontinuity design, allows for causal inference from observational data and staggered implementation strategy allows for the identification of secular trends that could affect causal association and mitigate as necessary. CLINICALTRIAL This observational quasi-experiment is registered with clinicaltrials.gov as NCT05810064

BACKGROUND Computer-aided detection used in screening and diagnostic cognitive impairment becomes increasingly the focus of attention, which allows objective, ecologically valid, and convenient assessment. Among that, sensor technology based on digital devices is potential method for detection. v OBJECTIVE The aim of this study was to develop and validate a novel trail-making test (TMT) based on a mixing of paper and electronic devices. METHODS In this research, a community-dwelling sample of older adults (n = 297) was included, classified as cognitively normal control (NC, n = 100), diagnosed with mild cognitive impairment (MCI, n = 98) or Alzheimer's disease (AD, n = 99). We used an electromagnetic tablet to record each participant's hand-painted strokes. Meanwhile, a sheet of A4 paper was placed on top of the tablet to keep the traditional interaction style for subjects who are not familiar or comfortable with electronic devices, e.g., touchscreen. In this way, all participants were instructed to perform the TMT-square and circle (TMT-S&C). Furthermore, we developed an efficient and interpretable cognitive impairment screening model to automated analyse cognitive impairment level, which was dependent on demographic, time-related, pressure-related, jerk-related, and template-related features. Among that, the novel template-based features were based on vector quantization (VQ) algorithm. Firstly, the model singled out a candidate trajectory as the standard answer (template) from the normal group. Then the distance between the recorded trajectories and the reference was computed as the important evaluation index. To verify the effectiveness of our method, we compared the performance of well-trained machine learning model using the extracted evaluation index with conventional demographic characters and time related features. In addition, the well-trained model also was validated on follow-ups’ data (NC: 38, MCI: 32, and AD: 22). RESULTS We compared five candidate machine learning methods, screened out the random forest as the ideal model with the best performance (Accuracy: 0.777 for NC vs. MCI, 0.929 for NC vs. AD, and 0.805 for AD vs. MCI). Meanwhile, the well-trained classifier achieved better performance than the conventional assessment method and high stability and accuracy on follow-ups’ data. CONCLUSIONS The study demonstrated that the mixing of paper and electronic TMT produced more reliable and valid data for evaluating subjects' cognitive impairment compared with conventional paper-based assessment. CLINICALTRIAL The study was approved by Medical Ethics Committee of Shanghai Tongji Hospital (ChiCTR2000039550)

Background The National Cancer Institute Informatics Technology for Cancer Research (ITCR) program provides a series of funding mechanisms to create an ecosystem of open-source software (OSS) that serves the needs of cancer research. As the ITCR ecosystem substantially grows, it faces the challenge of the long-term sustainability of the software being developed by ITCR grantees. To address this challenge, the ITCR sustainability and industry partnership working group (SIP-WG) was convened in 2019. Objective The charter of the SIP-WG is to investigate options to enhance the long-term sustainability of the OSS being developed by ITCR, in part by developing a collection of business model archetypes that can serve as sustainability plans for ITCR OSS development initiatives. The working group assembled models from the ITCR program, from other studies, and from the engagement of its extensive network of relationships with other organizations (eg, Chan Zuckerberg Initiative, Open Source Initiative, and Software Sustainability Institute) in support of this objective. Methods This paper reviews the existing sustainability models and describes 10 OSS use cases disseminated by the SIP-WG and others, including 3D Slicer, Bioconductor, Cytoscape, Globus, i2b2 (Informatics for Integrating Biology and the Bedside) and tranSMART, Insight Toolkit, Linux, Observational Health Data Sciences and Informatics tools, R, and REDCap (Research Electronic Data Capture), in 10 sustainability aspects: governance, documentation, code quality, support, ecosystem collaboration, security, legal, finance, marketing, and dependency hygiene. Results Information available to the public reveals that all 10 OSS have effective governance, comprehensive documentation, high code quality, reliable dependency hygiene, strong user and developer support, and active marketing. These OSS include a variety of licensing models (eg, general public license version 2, general public license version 3, Berkeley Software Distribution, and Apache 3) and financial models (eg, federal research funding, industry and membership support, and commercial support). However, detailed information on ecosystem collaboration and security is not publicly provided by most OSS. Conclusions We recommend 6 essential attributes for research software: alignment with unmet scientific needs, a dedicated development team, a vibrant user community, a feasible licensing model, a sustainable financial model, and effective product management. We also stress important actions to be considered in future ITCR activities that involve the discussion of the sustainability and licensing models for ITCR OSS, the establishment of a central library, the allocation of consulting resources to code quality control, ecosystem collaboration, security, and dependency hygiene.

Background High-frequency patient-reported outcome (PRO) assessments are used to measure patients' symptoms after surgery for surgical research; however, the quality of those longitudinal PRO data has seldom been discussed. Objective The aim of this study was to determine data quality-influencing factors and to profile error trajectories of data longitudinally collected via paper-and-pencil (P&P) or web-based assessment (electronic PRO [ePRO]) after thoracic surgery. Methods We extracted longitudinal PRO data with 678 patients scheduled for lung surgery from an observational study (n=512) and a randomized clinical trial (n=166) on the evaluation of different perioperative care strategies. PROs were assessed by the MD Anderson Symptom Inventory Lung Cancer Module and single-item Quality of Life Scale before surgery and then daily after surgery until discharge or up to 14 days of hospitalization. Patient compliance and data error were identified and compared between P&P and ePRO. Generalized estimating equations model and 2-piecewise model were used to describe trajectories of error incidence over time and to identify the risk factors. Results Among 678 patients, 629 with at least 2 PRO assessments, 440 completed 3347 P&P assessments and 189 completed 1291 ePRO assessments. In total, 49.4% of patients had at least one error, including (1) missing items (64.69%, 1070/1654), (2) modifications without signatures (27.99%, 463/1654), (3) selection of multiple options (3.02%, 50/1654), (4) missing patient signatures (2.54%, 42/1654), (5) missing researcher signatures (1.45%, 24/1654), and (6) missing completion dates (0.30%, 5/1654). Patients who completed ePRO had fewer errors than those who completed P&P assessments (ePRO: 30.2% [57/189] vs. P&P: 57.7% [254/440]; P Conclusions It is possible to improve data quality of longitudinally collected PRO through ePRO, compared with P&P. However, ePRO-related sampling bias needs to be considered when designing clinical research using longitudinal PROs as major outcomes.

Background Display signage is ubiquitous and essential in hospitals to serve several clerical, operational, and clinical functions, including displaying notices, providing directions, and presenting clinical information. These functions improve efficiency and patient engagement, reduce errors, and enhance the continuity of care. Over time, signage has evolved from analog approaches such as whiteboards and handwritten notices to digital displays such as liquid crystal displays, light emitting diodes, and, now, electronic ink displays. Electronic ink displays are paper-like displays that are not backlit and show content by aligning microencapsulated color beads in response to an applied electric current. Power is only required to generate content and not to retain it. These displays are very readable, with low eye strain; minimize the emission of blue light; require minimal power; and can be driven by several data sources, ranging from virtual servers to electronic health record systems. These attributes make adapting electronic ink displays to hospitals an ideal use case. Objective In this paper, we aimed to outline the use of signage and displays in hospitals with a focus on electronic ink displays. We aimed to assess the advantages and limitations of using these displays in hospitals and outline the various public-facing and patient-facing applications of electronic ink displays. Finally, we aimed to discuss the technological considerations and an implementation framework that must be followed when adopting and deploying electronic ink displays. Methods The public-facing applications of electronic ink displays include signage and way-finders, timetables for shared workspaces, and noticeboards and bulletin boards. The clinical display applications may be smaller form factors such as door signs or bedside cards. The larger, ≥40-inch form factors may be used within patient rooms or at clinical command centers as a digital whiteboard to display general information, patient and clinician information, and care plans. In all these applications, such displays could replace analog whiteboards, noticeboards, and even other digital screens. Results We are conducting pilot research projects to delineate best use cases and practices in adopting electronic ink displays in clinical settings. This will entail liaising with key stakeholders, gathering objective logistical and feasibility data, and, ultimately, quantifying and describing the effect on clinical care and patient satisfaction. Conclusions There are several use cases in a clinical setting that may lend themselves perfectly to electronic ink display use. The main considerations to be studied in this adoption are network connectivity, content management, privacy and security robustness, and detailed comparison with existing modalities. Electronic ink displays offer a superior opportunity to future-proof existing practices. There is a need for theoretical considerations and real-world testing to determine if the advantages outweigh the limitations of electronic ink displays.

UNSTRUCTURED Crowding and its main causes, exit block and boarding, continue to threaten the quality and safety of ED care. Most interventions to reduce crowding have not been comprehensive or system solutions, only focusing on part of the care procession and not directly effecting boarding reduction. This position paper proposes that the complexities of the emergency department (ED) crowding problem can be optimally addressed by applying a systems approach to crowding through predictive modeling. Using predictive models to identify patients who are at risk of being admitted could be used to remove the exit block that causes boarding by initiating the complex and time-consuming bed management process earlier in the care continuum, shortening the time patients wait in the ED for an inpatient bed assignment. Thus, this, in turn, reduces exit block, boarding, and subsequently crowding.

Background Colorectal cancer screening by fecal occult blood testing has been an important public health test and shown to reduce colorectal cancer–related mortality. However, the low participation rate in colorectal cancer screening by the general public remains a problematic public health issue. This fact could be attributed to the complex and unpleasant operation of the screening tool. Objective This study aimed to validate a novel toilet paper–based point-of-care test (ie, JustWipe) as a public health instrument to detect fecal occult blood and provide detailed results from the evaluation of the analytic characteristics in the clinical validation. Methods The mechanism of fecal specimen collection by the toilet-paper device was verified with repeatability and reproducibility tests. We also evaluated the analytical characteristics of the test reagents. For clinical validation, we conducted comparisons between JustWipe and other fecal occult blood tests. The first comparison was between JustWipe and typical fecal occult blood testing in a central laboratory setting with 70 fecal specimens from the hospital. For the second comparison, a total of 58 volunteers were recruited, and JustWipe was compared with the commercially available Hemoccult SENSA in a point-of-care setting. Results Adequate amounts of fecal specimens were collected using the toilet-paper device with small day-to-day and person-to-person variations. The limit of detection of the test reagent was evaluated to be 3.75 µg of hemoglobin per milliliter of reagent. Moreover, the test reagent also showed high repeatability (100%) on different days and high reproducibility (>96%) among different users. The overall agreement between JustWipe and a typical fecal occult blood test in a central laboratory setting was 82.9%. In the setting of point-of-care tests, the overall agreement between JustWipe and Hemoccult SENSA was 89.7%. Moreover, the usability questionnaire showed that the novel test tool had high scores in operation friendliness (87.3/100), ease of reading results (97.4/100), and information usefulness (96.1/100). Conclusions We developed and validated a toilet paper–based fecal occult blood test for use as a point-of-care test for the rapid (in 60 seconds) and easy testing of fecal occult blood. These favorable characteristics render it a promising tool for colorectal cancer screening as a public health instrument.

BACKGROUND Study participants and patients often perceive (long) questionnaires as burdensome. In addition, paper-based questionnaires are prone to errors such as (unintentionally) skipping questions or filling in a wrong type of answer. With the emergence of mobile questionnaire applications, such errors can be prevented. OBJECTIVE The objective of the present study was to validate an innovative way to measure quality of life using a mobile application (mobile app), based on the EQ-5D-5L questionnaire. This validation study compared the EQ-5D-5L questionnaire requested by a mobile app to the gold standard, a paper-based version of the EQ-5D-5L. METHODS The study was designed as a randomized, cross-over, and open study. Each participant received a digital version of the EQ-5D-5L questionnaire requested via a mobile app and the EQ-5D-5L paper-based questionnaire sent by postal mail. In the mobile app participants received, spread over five consecutive days, one question in the morning and one question in the afternoon and all questions were asked twice (at timepoint 1 (App T1) and timepoint 2 (App T2)). Primary outcomes were the correlations between the answers (scores) of each EQ-5D-5L question requested via the mobile app compared with the paper-based questionnaire to assess convergent validity. RESULTS In total 255 participants (healthy at own discretion), of which 117 men and 138 women in the age range of 18 – 64 years, completed the study. All questions showed a high correlation (0.64 - 0.92) for the paper-based EQ-5D-5L questionnaire versus the mobile app-based questions at App T1 and App T2. The scores and their variance remain similar over questionnaires, indicating no clear difference in answer tendency. Also, the correlation between the two app-based questionnaires was high (>0.73), illustrating a high test-retest reliability, and a reliable replacement for the paper-based questionnaire. CONCLUSIONS The present study indicates that the mobile app is a valid tool for measuring quality of life and is as reliable as the paper-based version of the EQ-5D-5L, while reducing response burden.

BACKGROUND Back pain is a common and costly problem, with negative impacts on both individuals and the healthcare system. Rural, remote, and Indigenous populations are at greater risk of experiencing back pain compared to urban and non-Indigenous populations. Potential barriers to health care access among Canadians with chronic back pain (CBP) have been identified; however, no known study has used lived experiences of people with CBP to drive the selection, analysis, and interpretation of variables most meaningful to patients. OBJECTIVE 1) Engage with rural, remote, and urban Indigenous and non-Indigenous patients, health care providers, and health system decision makers to explore lived experiences of attempting to access health care among people with CBP in Saskatchewan, Canada; 2) Co-create meaningful indicators of CBP care access and effectiveness; 3) Identify program and policy recommendations to overcome access barriers to CBP care. METHODS Phase 1) One-on-one interviews with 30 people with current or past CBP and 10 health care providers residing or practicing in rural, remote, or urban Saskatchewan communities will be conducted. We will recruit Indigenous (10) and non-Indigenous (20) rural, remote and urban people. Phase 2) Findings from the interviews will inform development of a population-based telephone survey focused on access to health care barriers and facilitators among rural, remote and urban people; this survey will be administered to 383 residents with CBP across Saskatchewan. Phase 3) Phase 1 & 2 findings will be presented to provincial and national policy makers, health system decision makers, health care providers, rural, remote, and urban people with CBP and their communities, and other knowledge users at an interactive end-of-project knowledge translation event. A World Café method will be used to facilitate interactive dialogue designed to catalyse future patient-oriented research and pathways to improve access to CBP care. Patient engagement: People with lived experience of CBP, including Indigenous and non-Indigenous people from rural, remote, and urban communities (i.e. ‘patient partners’) are equal members of the research team for this patient-oriented project. Patient partners are engaged throughout the entire research process and will provide unique knowledge from the patient perspective to ensure more comprehensive collection of data, while shaping culturally appropriate messages and identifying target audiences and methods of sharing findings to knowledge users. RESULTS Participant recruitment began in January 2021. Final results are anticipated in late 2022. CONCLUSIONS This study will privilege CBP patient experiences to better understand current health care use and potential access challenges and facilitators among rural, remote, and urban people living with CBP in Saskatchewan. Our study aims to inform the development of comprehensive measures that will be sensitive to geographical location and relevant to culturally diverse people with CBP, ultimately leading to enhanced access to more patient-centred care for CBP.