Development of the CDISC Pediatrics User Guide: a CDISC and conect4children collaboration.

Introduction: The conect4children (c4c) project aims to facilitate efficient planning and delivery of paediatric clinical trials. One objective of c4c is data standardization and reuse. Interoperability and reusability of paediatric clinical trial data is challenging due to a lack of standardization. The Clinical Data Interchange Standards Consortium (CDISC) standards that are required or recommended for regulatory submissions in several countries lack paediatric specificity with limited awareness within academic institutions. To address this, c4c and CDISC collaborated to develop the Pediatrics User Guide (PUG) consisting of cross-cutting data items that are routinely collected in paediatric clinical trials, factoring in all paediatric age ranges. Methods and Results: The development of the PUG consisted of six stages. During the scoping phase, subtopics (each containing several clinically relevant concepts) were suggested and debated for inclusion in the PUG. Ninety concepts were selected for the modelling phase. Concept maps describing the Research Topic and representation procedure were developed for the 19 concepts that had no (or partial) previous modelling in CDISC. Next, metadata and implementation examples were developed for concepts. This was followed by a CDISC internal review and a public review. For both these review stages, the feedback comments were either implemented or rejected based on budget, timelines, expert review, and scope. The PUG was published on the CDISC website on February 23, 2023. Discussion: The PUG is a first step in bridging the lack of child specific CDISC standards, particularly within academia. Several academic and industrial partners were involved in the development of the PUG, and c4c has undertaken multiple steps to publicize the PUG within its academic partner organizations - in particular, the European Reference Networks (ERNs) that are developing registries and dictionaries in 24 disease areas. In the long term, continued use of the PUG in paediatric clinical trials will enable the pooling of data from multiple trials, which is particularly important for medical domains with small populations.

Use of mHealth tools to register birth outcomes in low-income and middle-income countries: a scoping review.

OBJECTIVE: Accurate reporting of birth outcomes in low-income and middle-income countries (LMICs) is essential. Mobile health (mHealth) tools have been proposed as a replacement for conventional paper-based registers. mHealth could provide timely data for individual facilities and health departments, as well as capture deliveries outside facilities. This scoping review evaluates which mHealth tools have been reported to birth outcomes in the delivering room in LMICs and documents their reported advantages and drawbacks. DESIGN: A scoping review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses and Joanna Briggs Institute guidelines for scoping reviews and the mHealth evidence reporting and assessment checklist for evaluating mHealth interventions. DATA SOURCES: PubMed, CINAHL and Global Health were searched for records until 3 February 2022 with no earliest date limit. ELIGIBILITY CRITERIA: Studies were included where healthcare workers used mHealth tools in LMICs to record birth outcomes. Exclusion criteria included mHealth not being used at the point of delivery, non-peer reviewed literature and studies not written in English. DATA EXTRACTION AND SYNTHESIS: Two independent reviewers screened studies and extracted data. Common themes among studies were identified. RESULTS: 640 records were screened, 21 of which met the inclusion criteria, describing 15 different mHealth tools. We identified six themes: (1) digital tools for labour monitoring (8 studies); (2) digital data collection of specific birth outcomes (3 studies); (3) digital technologies used in community settings (6 studies); (4) attitudes of healthcare workers (10 studies); (5) paper versus electronic data collection (3 studies) and (6) infrastructure, interoperability and sustainability (8 studies). CONCLUSION: Several mHealth technologies are reported to have the capability to record birth outcomes at delivery, but none were identified that were designed solely for that purpose. Use of digital delivery registers appears feasible and acceptable to healthcare workers, but definitive evaluations are lacking. Further assessment of the sustainability of technologies and their ability to integrate with existing health information systems is needed.

Embedding the Pillars of Quality in Health Information Technology Solutions Using "Integrated Patient Journey Mapping" (IPJM): Case Study.

BACKGROUND: Health information technology (HIT) and associated data analytics offer significant opportunities for tackling some of the more complex challenges currently facing the health care sector. However, to deliver robust health care service improvements, it is essential that HIT solutions be designed by parallelly considering the 3 core pillars of health care quality: clinical effectiveness, patient safety, and patient experience. This requires multidisciplinary teams to design interventions that both adhere to medical protocols and achieve the tripartite goals of effectiveness, safety, and experience. OBJECTIVE: In this paper, we present a design tool called Integrated Patient Journey Mapping (IPJM) that was developed to assist multidisciplinary teams in designing effective HIT solutions to address the 3 core pillars of health care quality. IPJM is intended to support the analysis of requirements as well as to promote empathy and the emergence of shared commitment and understanding among multidisciplinary teams. METHODS: A 6-month, in-depth case study was conducted to derive findings on the use of IPJM during Learning to Evaluate Blood Pressure at Home (LEANBH), a connected health project that developed an HIT solution for the perinatal health context. Data were collected from over 700 hours of participant observations and 10 semistructured interviews. RESULTS: The findings indicate that IPJM offered a constructive tool for multidisciplinary teams to work together in designing an HIT solution, through mapping the physical and emotional journey of patients for both the current service and the proposed connected health service. This allowed team members to consider the goals, tasks, constraints, and actors involved in the delivery of this journey and to capture requirements for the digital touchpoints of the connected health service. CONCLUSIONS: Overall, IPJM facilitates the design and implementation of complex HITs that require multidisciplinary participation.

Trajectories of the averaged abbreviated Vitalpac early warning score (AbEWS) and clinical course of 44,531 consecutive admissions hospitalized for acute medical illness.

BACKGROUND: It is not known how often, to what extent and over what time frame any early warning scores change, and what the implications of these changes are. SETTING: Thunder Bay Regional Health Sciences Center, Ontario, Canada. METHODS: The averaged vital signs measured over different time periods of 44,531 consecutive acutely ill medical admissions were determined and then combined to calculate the averaged abbreviated version of the Vitalpac early warning score (AbEWS) during each time period examined. RESULTS: 18% of all in-hospital deaths within 30 days are in patients with a low AbEWS on admission. Those admitted with a low AbEWS are more likely to increase their score and those admitted with a high score are more likely to lower it. Paradoxically, patients who have an averaged score over the first 6h in hospital that is lower than on admission have increased in-hospital mortality. Thereafter patients with an increase in the averaged score have almost twice the mortality of those with a decreased score. 4.7% of patients have a low averaged score on the day they die. CONCLUSION: AbEWS, without clinical judgment, cannot be used to detect those patients who do not need to be admitted to hospital or are suitable for discharge. A period of observation of at least 12h is required before the trajectory of AbEWS is of prognostic value, and any "improvement" that occurs before this time may be illusory.

Changes and their prognostic implications in the abbreviated Vitalpac™ early warning score (ViEWS) after admission to hospital of 18,853 acutely ill medical patients.

BACKGROUND: The best performing early warning score is Vitalpac™ Early Warning Score (ViEWS). However, it is not known how often, to what extent and over what time frame any early warning scores change, and what the implications of these changes are. SETTING: Thunder Bay Regional Health Sciences Center, Ontario, Canada. METHODS: The changes in the first three complete sets of the six variables required to retrospectively calculate the abbreviated version of ViEWS (that did not include mental status) after admission to hospital of 18,853 acutely ill medical patients, and their relationship to subsequent in-hospital mortality were examined. RESULTS: In the 10.4 SD 20.1 (median 5.0) hours between admission and the second recording the score changed in only 5.9% of patients and these changes were of no prognostic value. By the time of the third recording 34.9 SD 21.7 (median 30.0) hours after admission a change in score was clearly associated with a corresponding change in in-hospital mortality (e.g. for patients with an initial score of 5 an increase between the first and third recording of ≥4 points was associated with an increased mortality (OR 6.5 95% CI 2.3-15.9, p<0.00001), whereas a reduction of ≤-4 points was associated with a reduced mortality (OR 0.4 95% CI 0.2-0.9, p 0.03)). CONCLUSION: After a median interval of 30 h both the initial abbreviated ViEWS recording and subsequent changes in it both predict clinical outcome. It remains to be determined what interventions during this time frame will improve patient outcomes.

Changes and their prognostic implications in the abbreviated VitalPAC™ Early Warning Score (ViEWS) after admission to hospital of 18,827 surgical patients.

BACKGROUND: It is not known how often, to what extent and over what time frame any early warning scores change in surgical patients, and what the implications of these changes are. SETTING: Thunder Bay Regional Health Sciences Centre, Ontario, Canada. METHODS: The changes in the first three recordings of the abbreviated version of the VitalPAC™ Early Warning Score (ViEWS) after admission to hospital of 18,827 surgical patients, and their relationship to subsequent in-hospital mortality were examined. RESULTS: In the 2.0 SD 2.4h between admission and the second recording the score changed in 12.6% of patients. If the initial abbreviated ViEWS was ≤ 2 points (78% of all patients) the in-hospital mortality was 0.5%, and not significantly different in the 3.7% of patients that either increased or decreased their score. Patients who had an initial score ≥ 3 had a significantly higher overall in-hospital mortality (odds ratio 5.48, Chi-square 120.72, p<0.0001). Of these patients, those with a lower second score (42.3% of patients) had a significantly lower in-hospital mortality than those with an unchanged second score (i.e. 1.5% versus 3.3%, odds ratio 0.43, Chi-square 11.08, p<0.001). CONCLUSION: The abbreviated ViEWS score measured on admission identifies the majority of surgical patients who are at low risk of in-hospital death. Patients with an initial abbreviated ViEWS ≥ 3 who do not reduce their score within 2-3h of admission have a further significantly increased mortality.