Smart hospital: achieving interoperability and raw data collection from medical devices in clinical routine.

Introduction: Today, modern technology is used to diagnose and treat cardiovascular disease. These medical devices provide exact measures and raw data such as imaging data or biosignals. So far, the Broad Integration of These Health Data into Hospital Information Technology Structures-Especially in Germany-is Lacking, and if data integration takes place, only non-Evaluable Findings are Usually Integrated into the Hospital Information Technology Structures. A Comprehensive Integration of raw Data and Structured Medical Information has not yet Been Established. The aim of this project was to design and implement an interoperable database (cardio-vascular-information-system, CVIS) for the automated integration of al medical device data (parameters and raw data) in cardio-vascular medicine. Methods: The CVIS serves as a data integration and preparation system at the interface between the various devices and the hospital IT infrastructure. In our project, we were able to establish a database with integration of proprietary device interfaces, which could be integrated into the electronic health record (EHR) with various HL7 and web interfaces. Results: In the period between 1.7.2020 and 30.6.2022, the data integrated into this database were evaluated. During this time, 114,858 patients were automatically included in the database and medical data of 50,295 of them were entered. For technical examinations, more than 4.5 million readings (an average of 28.5 per examination) and 684,696 image data and raw signals (28,935 ECG files, 655,761 structured reports, 91,113 x-ray objects, 559,648 ultrasound objects in 54 different examination types, 5,000 endoscopy objects) were integrated into the database. Over 10.2 million bidirectional HL7 messages (approximately 14,000/day) were successfully processed. 98,458 documents were transferred to the central document management system, 55,154 materials (average 7.77 per order) were recorded and stored in the database, 21,196 diagnoses and 50,353 services/OPS were recorded and transferred. On average, 3.3 examinations per patient were recorded; in addition, there are an average of 13 laboratory examinations. Discussion: Fully automated data integration from medical devices including the raw data is feasible and already creates a comprehensive database for multimodal modern analysis approaches in a short time. This is the basis for national and international projects by extracting research data using FHIR.

Assessing the impact of real-time random safety audits through full propensity score matching on reliable data from the clinical information system.

BACKGROUND: Evidence-based care processes are not always applied at the bedside in critically ill patients. Numerous studies have assessed the impact of checklists and related strategies on the process of care and patient outcomes. We aimed to evaluate the effects of real-time random safety audits on process-of-care and outcome variables in critical care patients. METHODS: This prospective study used data from the clinical information system to evaluate the impact of real-time random safety audits targeting 32 safety measures in two intensive care units during a 9-month period. We compared endpoints between patients attended with safety audits and those not attended with safety audits. The primary endpoint was mortality, measured by Cox hazard regression after full propensity-score matching. Secondary endpoints were the impact on adherence to process-of-care measures and on quality indicators. RESULTS: We included 871 patients; 228 of these were attended in ≥ 1 real-time random safety audits. Safety audits were carried out on 390 patient-days; most improvements in the process of care were observed in safety measures related to mechanical ventilation, renal function and therapies, nutrition, and clinical information system. Although the group of patients attended in safety audits had more severe disease at ICU admission [APACHE II score 21 (16-27) vs. 20 (15-25), p = 0.023]; included a higher proportion of surgical patients [37.3 % vs. 26.4 %, p = 0.003] and a higher proportion of mechanically ventilated patients [72.8 % vs. 40.3 %, p < 0.001]; averaged more days on mechanical ventilation, central venous catheter, and urinary catheter; and had a longer ICU stay [12.5 (5.5-23.3) vs. 2.9 (1.7-5.9), p < 0.001], ICU mortality did not differ significantly between groups (19.3 % vs. 18.8 % in the group without safety rounds). After full propensity-score matching, Cox hazard regression analysis showed real-time random safety audits were associated with a lower risk of mortality throughout the ICU stay (HR 0.31; 95 %CI 0.20-0.47). CONCLUSIONS: Real-time random safety audits are associated with a reduction in the risk of ICU mortality. Exploiting data from the clinical information system is useful in assessing the impact of them on the care process, quality indicators, and mortality.

Healthcare-Associated-Infections: preliminary results from a real-time reporting system of an Italian neurologic research hospital.

Background: Healthcare-Associated-Infections are a critical concern in healthcare settings, posing serious threats to patient safety and causing significant morbidity, mortality, and financial strain. This study aims to calculate healthcare-associated-infections trends in the hospital setting through an automatic reporting system. Study design: The study is a descriptive analysis of automatically generated trends of an innovative digital tool based on existing hospital information flows. Methods: An algorithm was developed within a Clinical Information System to create a suite of quality indicators for monitoring healthcare-associated-infections trends. The algorithm used criteria related to admission, laboratory tests and antimicrobial administrations. A descriptive analysis was conducted for patients aged 18 or older, admitted to a neurological or to a neuro-rehabilitation department of a neurologic hospital from 2019 to 2022. Results: The results showed fluctuations in healthcare-associated-infections prevalence from 2.9% to 5.6% and hospital infec-tions prevalence from 4.5% to 10.9%, with notable increases in 2020 and 2021. The majority (70.3%) of healthcare associated infections identified by the tool were confirmed to be potentially hospital-acquired, according to the European Centre of Disease Prevention and Control's definition. Discussion and Conclusions: The study posits the algorithm as a vital tool for automatically monitoring hospital infections, providing valuable preliminary results for improving care quality and guiding the infections' prevention and control strategies, with plans to benchmark the algorithm against a gold standard in the future.

The Impact and Usability of the eRIC System in the ICU - A Qualitative Study.

The Intensive Care Unit (ICU) is an information-intense environment where more patient data points are recorded than in other wards. The electronic Record for Intensive Care (eRIC) is an ICU information system that integrates patient data every minute from multiple systems. Once implemented across New South Wales (NSW), eRIC will be one of the largest system-wide ICU clinical information systems in the world. This study explored experiences with the use of eRIC by ICU clinicians at an Australian metropolitan teaching hospital. Semi-structured, in-depth interviews relating to physician electronic test management processes were conducted with 11 ICU clinicians and one clinical information system manager was observed in their use of the system. The introduction of eRIC resulted in an additional patient record, which was perceived to hold implications for workflow and patient safety. Study findings are valuable for informing implementation as the rollout of eRIC continues.

HeNeCOn: An ontology for integrative research in Head and Neck cancer.

BACKGROUND: Head and Neck Cancer (HNC) has a high incidence and prevalence in the worldwide population. The broad terminology associated with these diseases and their multimodality treatments generates large amounts of heterogeneous clinical data, which motivates the construction of a high-quality harmonization model to standardize this multi-source clinical data in terms of format and semantics. The use of ontologies and semantic techniques is a well-known approach to face this challenge. OBJECTIVE: This work aims to provide a clinically reliable data model for HNC processes during all phases of the disease: prognosis, treatment, and follow-up. Therefore, we built the first ontology specifically focused on the HNC domain, named HeNeCOn (Head and Neck Cancer Ontology). METHODS: First, an annotated dataset was established to provide a formal reference description of HNC. Then, 170 clinical variables were organized into a taxonomy, and later expanded and mapped to formalize and integrate multiple databases into the HeNeCOn ontology. The outcomes of this iterative process were reviewed and validated by clinicians and statisticians. RESULTS: HeNeCOn is an ontology consisting of 502 classes, a taxonomy with a hierarchical structure, semantic definitions of 283 medical terms and detailed relations between them, which can be used as a tool for information extraction and knowledge management. CONCLUSION: HeNeCOn is a reusable, extendible and standardized ontology which establishes a reference data model for terminology structure and standard definitions in the Head and Neck Cancer domain. This ontology allows handling both current and newly generated knowledge in Head and Neck cancer research, by means of data linking and mapping with other public ontologies.

Design and implementation of an automatic nursing assessment system based on CDSS technology.

BACKGROUND: Various quantitative and quality assessment tools are currently used in nursing to evaluate a patient's physiological, psychological, and socioeconomic status. The results play important roles in evaluating the efficiency of healthcare, improving the treatment plans, and lowing relevant clinical risks. However, the manual process of the assessment imposes a substantial burden and can lead to errors in digitalization. To fill these gaps, we proposed an automatic nursing assessment system based on clinical decision support system (CDSS). The framework underlying the CDSS included experts, evaluation criteria, and voting roles for selecting electronic assessment sheets over paper ones. METHODS: We developed the framework based on an expert voting flow to choose electronic assessment sheets. The CDSS was constructed based on a nursing process workflow model. A multilayer architecture with independent modules was used. The performance of the proposed system was evaluated by comparing the adverse events' incidence and the average time for regular daily assessment before and after the implementation. RESULTS: After implementation of the system, the adverse nursing events' incidence decreased significantly from 0.43 % to 0.37 % in the first year and further to 0.27 % in the second year (p-value: 0.04). Meanwhile, the median time for regular daily assessments further decreased from 63 s to 51 s. CONCLUSIONS: The automatic assessment system helps to reduce nurses' workload and the incidence of adverse nursing events.

Using the PharmCAT tool for Pharmacogenetic clinical decision support.

Here, we will provide our insights into the usage of PharmCAT as part of a pharmacogenetic clinical decision support pipeline, which addresses the challenges in mapping clinical dosing guidelines to variants to be extracted from genetic datasets. After a general outline of pharmacogenetics, we describe some features of PharmCAT and how we integrated it into a pharmacogenetic clinical decision support system within a clinical information system. We conclude with promising developments regarding future PharmCAT releases.

End-users' perspectives on factors affecting implementation and utilization of the Iranian electronic health record system: a qualitative study in a developing country.

BACKGROUND: As one of the most important information technologies for storing, managing, and exchanging health information, the electronic health record (EHR) plays a major role in the health system. However, these systems in developing countries have been associated with multidimensional issues. The purpose of the present study was the assessment of nonclinical end-users' points of view on the implementation and utilization of the Iranian electronic health record system. METHODS: This was a large qualitative study conducted in 2021 for 7 months from February to August. In this study, data were collected through in-depth semi-structured interviews with 70 non-clinical end-users in 22 public and six private hospitals of West Azerbaijan province in Iran. To analyze the data, the thematic analysis method was used. RESULTS: The study results indicated that technical, human, cultural, managerial, and financial readiness are the most important factors affecting the implementation of EHRs in Iran. Among the mentioned factors, technical and human readiness were emphasized more by the users. Also, technical, organizational, human, and managerial factors were identified as factors influencing EHRs utilization, and technical and organizational factors had a stronger role in the system utilization. CONCLUSIONS: According to the results, several factors influence EHR implementation and adequate utilization in Iran. To achieve the predetermined goals of this system, implementation issues and problems of using the system should be considered and solved.

Design and Evaluation of an Intensive Care Unit Dashboard Built in Response to the COVID-19 Pandemic: Semistructured Interview Study.

BACKGROUND: Dashboards and interactive displays are becoming increasingly prevalent in most health care settings and have the potential to streamline access to information, consolidate disparate data sources and deliver new insights. Our research focuses on intensive care units (ICUs) which are heavily instrumented, critical care environments that generate vast amounts of data and frequently require individualized support for each patient. Consequently, clinicians experience a high cognitive load, which can translate to suboptimal performance. The global COVID-19 pandemic exacerbated this problem by generating a large number of additional hospitalizations, which necessitated a new tool that would help manage ICUs' census. In a previous study, we interviewed clinicians at the University Hospitals Bristol and Weston National Health Service Foundation Trust to capture the requirements for bespoke dashboards that would alleviate this problem. OBJECTIVE: This study aims to design, implement, and evaluate an ICU dashboard to allow for monitoring of the high volume of patients in need of critical care, particularly tailored to high-demand situations, such as those seen during the COVID-19 pandemic. METHODS: Building upon the previously gathered requirements, we developed a dashboard, integrated it within the ICU of a National Health Service trust, and allowed all staff to access our tool. For evaluation purposes, participants were recruited and interviewed following a 25-day period during which they were able to use the dashboard clinically. The semistructured interviews followed a topic guide aimed at capturing the usability of the dashboard, supplemented with additional questions asked post hoc to probe themes established during the interview. Interview transcripts were analyzed using a thematic analysis framework that combined inductive and deductive approaches and integrated the Technology Acceptance Model. RESULTS: A total of 10 participants with 4 different roles in the ICU (6 consultants, 2 junior doctors, 1 nurse, and 1 advanced clinical practitioner) participated in the interviews. Our analysis generated 4 key topics that prevailed across the data: our dashboard met the usability requirements of the participants and was found useful and intuitive; participants perceived that it impacted their delivery of patient care by improving the access to the information and better equipping them to do their job; the tool was used in a variety of ways and for different reasons and tasks; and there were barriers to integration of our dashboard into practice, including familiarity with existing systems, which stifled the adoption of our tool. CONCLUSIONS: Our findings show that the perceived utility of the dashboard had a positive impact on the clinicians' workflows in the ICU. Improving access to information translated into more efficient patient care and transformed some of the existing processes. The introduction of our tool was met with positive reception, but its integration during the COVID-19 pandemic limited its adoption into practice.

Quorum-based model learning on a blockchain hierarchical clinical research network using smart contracts.

BACKGROUND: Collaborative privacy-preserving modeling across several healthcare institutions allows for the construction of more generalizable predictive models while protecting patient privacy. OBJECTIVE: We aim at addressing the site availability issue on a hierarchical network by designing an immutable/transparent/source-verifiable quorum mechanism. METHODS: We developed an approach to combine a hierarchical learning algorithm, a novel Proof-of-Quorum (PoQ) consensus protocol, and a design of blockchain smart contracts. We constructed QuorumChain as an example and evaluated the scenarios of site-unavailability during the initialization and/or iteration phases of the modeling process on three healthcare/genomic datasets. RESULTS: When one or more sites would become unavailable, HierarchicalChain could not function, whereas QuorumChain improved predictive correctness significantly (the full Area Under the receiver operating characteristic Curve, or AUC, improved from 0.068 to 0.441, all with p-values < 0.001). CONCLUSION: By constructing a quorum to continue the modeling process, QuorumChain possesses the capability to tackle the situation of sites being unavailable. It inherits the capability of learning on network-of-networks, improves learning continuity, and provides data/software immutability, transparency, and provenance, which can be important in expediting clinical research.

Secondary use of data extracted from a clinical information system to assess the adherence of tidal volume and its impact on outcomes.

OBJECTIVES: To extract data from clinical information systems to automatically calculate high-resolution quality indicators to assess adherence to recommendations for low tidal volume. DESIGN: We devised two indicators: the percentage of time under mechanical ventilation with excessive tidal volume (>8mL/kg predicted body weight) and the percentage of patients who received appropriate tidal volume (≤8mL/kg PBW) at least 80% of the time under mechanical ventilation. We developed an algorithm to automatically calculate these indicators from clinical information system data and analyzed associations between them and patients' characteristics and outcomes. SETTINGS: This study has been carried out in our 30-bed polyvalent intensive care unit between January 1, 2014 and November 30, 2019. PATIENTS: All patients admitted to intensive care unit ventilated >72h were included. INTERVENTION: Use data collected automatically from the clinical information systems to assess adherence to tidal volume recommendations and its outcomes. MAIN VARIABLES OF INTEREST: Mechanical ventilation days, ICU length of stay and mortality. RESULTS: Of all admitted patients, 340 met the inclusion criteria. Median percentage of time under mechanical ventilation with excessive tidal volume was 70% (23%-93%); only 22.3% of patients received appropriate tidal volume at least 80% of the time. Receiving appropriate tidal volume was associated with shorter duration of mechanical ventilation and intensive care unit stay. Patients receiving appropriate tidal volume were mostly male, younger, taller, and less severely ill. Adjusted intensive care unit mortality did not differ according to percentage of time with excessive tidal volume or to receiving appropriate tidal volume at least 80% of the time. CONCLUSIONS: Automatic calculation of process-of-care indicators from clinical information systems high-resolution data can provide an accurate and continuous measure of adherence to recommendations. Adherence to tidal volume recommendations was associated with shorter duration of mechanical ventilation and intensive care unit stay.

Secondary use of data extracted from a clinical information system to assess the adherence of tidal volume and its impact on outcomes / Uso secundario de los datos del Sistema de Información Clínica para evaluar la adherencia a las guías de práctica clínica respecto al volumen tidal y su impacto en los resultados

Objectives To extract data from clinical information systems to automatically calculate high-resolution quality indicators to assess adherence to recommendations for low tidal volume. Design We devised two indicators: the percentage of time under mechanical ventilation with excessive tidal volume (>8mL/kg predicted body weight) and the percentage of patients who received appropriate tidal volume (≤8mL/kg PBW) at least 80% of the time under mechanical ventilation. We developed an algorithm to automatically calculate these indicators from clinical information system data and analyzed associations between them and patients’ characteristics and outcomes. Settings This study has been carried out in our 30-bed polyvalent intensive care unit between January 1, 2014 and November 30, 2019. Patients All patients admitted to intensive care unit ventilated >72h were included. Intervention Use data collected automatically from the clinical information systems to assess adherence to tidal volume recommendations and its outcomes. Main variables of interest Mechanical ventilation days, ICU length of stay and mortality. Results Of all admitted patients, 340 met the inclusion criteria. Median percentage of time under mechanical ventilation with excessive tidal volume was 70% (23%–93%); only 22.3% of patients received appropriate tidal volume at least 80% of the time. Receiving appropriate tidal volume was associated with shorter duration of mechanical ventilation and intensive care unit stay. Patients receiving appropriate tidal volume were mostly male, younger, taller, and less severely ill. Adjusted intensive care unit mortality did not differ according to percentage of time with excessive tidal volume or to receiving appropriate tidal volume at least 80% of the time (AU)

Objetivos Extraer los datos del Sistema de Información Clínica para calcular automáticamente indicadores de calidad de alta resolución para evaluar la adherencia a las recomendaciones sobre el volumen tidal. Diseño Ideamos 2 indicadores: el porcentaje de tiempo en ventilación mecánica con volumen tidal excesivo (>8mL/kg peso ideal) y el porcentaje de pacientes con volumen tidal apropiado (≤8mL/kg peso ideal) al menos el 80% del tiempo en ventilación mecánica. Desarrollamos un algoritmo para calcular automáticamente dichos indicadores con los datos del Sistema de Información Clínica y analizamos su asociación con las características de los pacientes y su evolución. Ambiente El estudio se llevó a cabo en una unidad de cuidados intensivos polivalente de 30 camas desde el 1 enero 2014 hasta el 20 noviembre 2019. Pacientes Se incluyeron en el estudio todos los pacientes ingresados en la unidad de cuidados intensivos conectados a ventilación mecánica>72h. Intervención Usar los datos recogidos automáticamente desde el Sistema de Información Clínica para evaluar la adherencia a las recomendaciones del volumen tidal y sus resultados. Principales variables de interés Días de ventilación mecánica, días de estancia en la unidad de cuidados intensivos y mortalidad. Resultados De todos los pacientes ingresados, 340 cumplieron los criterios de inclusión. El tiempo medio de ventilación mecánica con volumen tidal excesivo fue 70% (23-93%); solo el 22,3% de los pacientes recibió un volumen tidal apropiado al menos el 80% del tiempo. Recibir un volumen tidal apropiado se asoció con menos días de ventilación mecánica y de estancia en la unidad de cuidados intensivos. Los pacientes que recibieron un volumen tidal apropiado fueron más frecuentemente hombres, más jóvenes, más altos y menos graves (AU)

The Reduction in Medical Errors on Implementing an Intensive Care Information System in a Setting Where a Hospital Electronic Medical Record System is Already in Use: Retrospective Analysis.

BACKGROUND: Although the various advantages of clinical information systems in intensive care units (ICUs), such as intensive care information systems (ICISs), have been reported, their role in preventing medical errors remains unclear. OBJECTIVE: This study aimed to investigate the changes in the incidence and type of errors in the ICU before and after ICIS implementation in a setting where a hospital electronic medical record system is already in use. METHODS: An ICIS was introduced to the general ICU of a university hospital. After a step-by-step implementation lasting 3 months, the ICIS was used for all patients starting from April 2019. We performed a retrospective analysis of the errors in the ICU during the 6-month period before and after ICIS implementation by using data from an incident reporting system, and the number, incidence rate, type, and patient outcome level of errors were determined. RESULTS: From April 2018 to September 2018, 755 patients were admitted to the ICU, and 719 patients were admitted from April 2019 to September 2019. The number of errors was 153 in the 2018 study period and 71 in the 2019 study period. The error incidence rates in 2018 and 2019 were 54.1 (95% CI 45.9-63.4) and 27.3 (95% CI 21.3-34.4) events per 1000 patient-days, respectively (P<.001). During both periods, there were no significant changes in the composition of the types of errors (P=.16), and the most common type of error was medication error. CONCLUSIONS: ICIS implementation was temporally associated with a 50% reduction in the number and incidence rate of errors in the ICU. Although the most common type of error was medication error in both study periods, ICIS implementation significantly reduced the number and incidence rate of medication errors. TRIAL REGISTRATION: University Hospital Medical Information Network Clinical Trials Registry UMIN000041471; https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000047345.

Development of a comprehensive database for research on foetal acidosis.

OBJECTIVE: To develop a research database for mother-and-child clinical and laboratory data and digital foetal heart rate (FHR) recordings. METHODS: The Base Bien Naître (BBN) database was derived from a single-centre health data warehouse. It contains exhaustive data on all parturients with a singleton pregnancy, a vaginal or caesarean delivery in labour with a cephalic presentation after at least 37 weeks of amenorrhea, and a live birth between February 1st, 2011, and December 31st, 2018. On arrival in the delivery room, the FHR was recorded digitally for at least 30 min. A cord blood sample was always taken in order to obtain arterial pH (pHa). More than 6,000 recordings were analyzed visually for the risk of foetal acidosis and classified into five groups (according to the French College of Gynaecologists and Obstetricians (CNGOF) classification) or three groups (according to the International Federation of Gynaecology and Obstetrics (FIGO) classification). RESULTS: Of the 16,089 files in the health data warehouse, 11,026 were complete and met the BBN's inclusion criteria. The FHR digital recordings were of good quality, with low signal loss (median [interquartile range]: 7.0% [4.3;10.9]) and a median recording time of 304 min [190;438]). In 3.7% of the children, the pHa was below 7.10. We selected a subset of 6115 records with good-quality FHR recordings over 120 min and reliable cord blood gas data: 692 (11.3%) had at least a significant risk of acidosis (according to the CNGOF classification), and 1638 (26.8%) were at least suspicious (according to the FIGO classification). CONCLUSION: The BBN database has been designed as a searchable tool with data reuse. It currently contains over 11,000 records with comprehensive data.

Digital Leadership: Attributes of Modern Healthcare Leaders.

Background Living in the current digital era requires widespread adoption of information technology in the modern healthcare industry. Objective The current research aimed to study key attributes and behaviors related to successful leaders' need to achieve the vision and ensure successful health IT adoption. Methods A Delphi technique with three rounds was employed and guided by structured questions. Part of the study was conducted online due to COVID-19 guidelines on distancing norms and lockdown in some areas. The answers of the participants were evaluated on a five-point Likert scale. Results The findings showed that similar leadership qualities are required in the healthcare sector as well as other sectors. For digital innovations in the rapidly changing healthcare space, leaders need to play a more proactive role, be visionary and dynamic, and should lead by example to take the organization to the next level. Conclusions Leaders need to come out of their comfort zone, understand the fast-evolving scenario where outstanding leadership qualities are essential to prove their mettle, outshine others, and create a strong foundation for the adoption of modern, efficient, customized digital technology in the fast-growing healthcare sector.

Development and implementation of a clinical information system-based protocol to improve nurse satisfaction of end-of-life care in a single intensive care unit.

BACKGROUND: Patients treated in Australian intensive care units (ICUs) have an overall mortality rate of 5.05%. This is due to the critical nature of their disease, the increasing proportion of patients with multiple comorbidities, and advanced age. This has made treating patients during the end of life an integral part of intensive care practice and requires a high quality of care. With the increased use of electronic clinical information systems, a standardised protocol encompassing end-of-life care may provide an efficient method for documentation, communication, and timely delivery of comfort care. OBJECTIVE: The aim of the study was to determine if an electronic clinical information system-based end-of-life care protocol improved nurses' satisfaction with the practice of end-of-life care for patients in the ICU. DESIGN: This is a prospective single-centre observational study. SETTING: The study was carried out at a 20-bed cardiothoracic and general ICU between 2015 and 2017. PARTICIPANTS: The study participants were ICU nurses. INTERVENTION: Electronic clinical information-based end-of-life care protocol was used in the study. OUTCOME: The primary outcome was nurse satisfaction obtained by a survey. RESULTS: The number of respondents for the before survey and after survey was 58 (29%) and 64 (32%), respectively. There was a significant difference between the before survey and the after survey with regard to feeling comfortable in transitioning from curative treatment (median = 2 [interquartile range {IQR} = 2, 3] vs 3 [IQR = 2, 3], p = 0.03), feeling involved in the decision to move from curative treatment to end-of-life care (median = 2 [IQR = 2, 2] vs 2 [IQR 2, 3], p = 0.049), and feeling religious beliefs/rituals should be respected during the end-of-life process (median = 4 [IQR = 3, 4] vs. 4 [IQR = 4, 4], p = 0.02). There were some practices that had a low satisfaction rate on both the before survey and after survey. However, a high proportion of nurses were satisfied with many of the end-of-life care practices. CONCLUSION: The nurses were highly satisfied with many aspects of end-of-life care practices in this unit. The use of an electronic clinical information system-based protocol improved nurse satisfaction and perception of quality of end-of-life care practices for three survey questions.

[Design and Implementation of Multifunctional Interactive Electronic Bedside Card System for Inpatients Based on Internet of Things Technology].

This research is based on data from clinical information systems such as HIS, EMR, LIS, etc, based on the functions of the traditional paper bedside card, relying on wired network technology, using the Internet of Things technology to design and develop a multi-functional intelligent interactive electronic bedside card system for inpatients. The functional framework of the system is introduced and discussed in detail, and the design is carried out from several aspects of system architecture, network architecture, software architecture, database and software system. The results show that the system has stable performance and can ensure the real-time and accuracy of medical information. The implementation of the system can fully meet the needs of clinical first-line ward management, reduce the workload of nursing staff, improve work efficiency, and reduce the possibility of medical accidents. At the same time, it can facilitate patients to see their own health information, improve patient experience. It has important guiding significance for the development of ward management and hospital information construction.

[Design and Implementation of Multifunctional Interactive Electronic Bedside Card System for Inpatients Based on Internet of Things Technology].

This research is based on data from clinical information systems such as HIS, EMR, LIS, etc, based on the functions of the traditional paper bedside card, relying on wired network technology, using the Internet of Things technology to design and develop a multi-functional intelligent interactive electronic bedside card system for inpatients. The functional framework of the system is introduced and discussed in detail, and the design is carried out from several aspects of system architecture, network architecture, software architecture, database and software system. The results show that the system has stable performance and can ensure the real-time and accuracy of medical information. The implementation of the system can fully meet the needs of clinical first-line ward management, reduce the workload of nursing staff, improve work efficiency, and reduce the possibility of medical accidents. At the same time, it can facilitate patients to see their own health information, improve patient experience. It has important guiding significance for the development of ward management and hospital information construction.

Change in Glycemic Control for Patients Enrolled in a Membership-Based Primary Care Program: Longitudinal Observational Study.

BACKGROUND: Both primary care practices based on the chronic care model (CCM) and digital therapeutics have been shown to improve the care of patients with diabetes. OBJECTIVE: The aim of this observational study was to examine the change in diabetes control for patients enrolled in a membership-based primary care service that is based on the CCM. METHODS: Using a diabetes registry, we analyzed the change in glycated hemoglobin (HbA1c) for patients with uncontrolled diabetes mellitus (initial HbA1c≥9%). All patients had access to a technology-enhanced primary care practice built on the CCM. RESULTS: The registry included 621 patients diagnosed with uncontrolled diabetes. All patients had at least two HbA1c measurements, with the average time between the first and last measurement of 1.2 years (SD 0.4). The average starting value of HbA1c was 10.7, which decreased to 8.7, corresponding to a reduction of 2.03 (P<.001). Secondary analyses showed statistically significant reductions in total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. CONCLUSIONS: Patients with initially uncontrolled diabetes who undergo care in a technology-enhanced primary care practice based on the CCM have long-term clinically meaningful reductions in HbA1c.

Patient Empowerment During the COVID-19 Pandemic by Ensuring Safe and Fast Communication of Test Results: Implementation and Performance of a Tracking System.

BACKGROUND: Overcoming the COVID-19 crisis requires new ideas and strategies for online communication of personal medical information and patient empowerment. Rapid testing of a large number of subjects is essential for monitoring and delaying the spread of SARS-CoV-2 in order to mitigate the pandemic's consequences. People who do not know that they are infected may not stay in quarantine and, thus, risk infecting others. Unfortunately, the massive number of COVID-19 tests performed is challenging for both laboratories and the units that conduct throat swabs and communicate the results. OBJECTIVE: The goal of this study was to reduce the communication burden for health care professionals. We developed a secure and easy-to-use tracking system to report COVID-19 test results online that is simple to understand for the tested subjects as soon as these results become available. Instead of personal calls, the system updates the status and the results of the tests automatically. This aims to reduce the delay when informing testees about their results and, consequently, to slow down the virus spread. METHODS: The application in this study draws on an existing tracking tool. With this open-source and browser-based online tracking system, we aim to minimize the time required to inform the tested person and the testing units (eg, hospitals or the public health care system). The system can be integrated into the clinical workflow with very modest effort and avoids excessive load to telephone hotlines. RESULTS: The test statuses and results are published on a secured webpage, enabling regular status checks by patients; status checks are performed without the use of smartphones, which has some importance, as smartphone usage diminishes with age. Stress tests and statistics show the performance of our software. CTest is currently running at two university hospitals in Germany-University Hospital Ulm and University Hospital Tübingen-with thousands of tests being performed each week. Results show a mean number of 10 (SD 2.8) views per testee. CONCLUSIONS: CTest runs independently of existing infrastructures, aims at straightforward integration, and aims for the safe transmission of information. The system is easy to use for testees. QR (Quick Response) code links allow for quick access to the test results. The mean number of views per entry indicates a reduced amount of time for both health care professionals and testees. The system is quite generic and can be extended and adapted to other communication tasks.