Écart de mobilité : estimation des seuils de mobilité requis pour maîtriser le SRAS-CoV-2 au Canada

CONTEXTE:

Les interventions non pharmacologiques demeurent le principal moyen de maîtriser le coronavirus du syndrome respiratoire aigu sévère 2 (SRAS-CoV-2) d’ici à ce que la couverture vaccinale soit suffisante pour donner lieu à une immunité collective. Nous avons utilisé des données de mobilité anonymisées de téléphones intelligents afin de quantifier le niveau de mobilité requis pour maîtriser le SRAS-CoV-2 (c.-à-d., seuil de mobilité), et la différence par rapport au niveau de mobilité observé (c.-à-d., écart de mobilité).

MÉTHODES:

Nous avons procédé à une analyse de séries chronologiques sur l’incidence hebdomadaire du SRAS-CoV-2 au Canada entre le 15 mars 2020 et le 6 mars 2021. Le paramètre mesuré était le taux de croissance hebdomadaire, défini comme le rapport entre les cas d’une semaine donnée et ceux de la semaine précédente. Nous avons mesuré les effets du temps moyen passé hors domicile au cours des 3 semaines précédentes à l’aide d’un modèle de régression log-normal, en tenant compte de la province, de la semaine et de la température moyenne. Nous avons calculé le seuil de mobilité et l’écart de mobilité pour le SRAS-CoV-2.

RÉSULTATS:

Au cours des 51 semaines de l’étude, en tout, 888 751 personnes ont contracté le SRAS-CoV-2. Chaque augmentation de 10 % de l’écart de mobilité a été associée à une augmentation de 25 % du taux de croissance des cas hebdomadaires de SRAS-CoV-2 (rapport 1,25, intervalle de confiance à 95 % 1,20–1,29). Comparativement à la mobilité prépandémique de référence de 100 %, le seuil de mobilité a été plus élevé au cours de l’été (69 %, écart interquartile [EI] 67 %–70 %), et a chuté à 54 % pendant l’hiver 2021 (EI 52 %–55 %); un écart de mobilité a été observé au Canada entre juillet 2020 et la dernière semaine de décembre 2020.

INTERPRÉTATION:

La mobilité permet de prédire avec fiabilité et constance la croissance des cas hebdomadaires et il faut maintenir des niveaux faibles de mobilité pour maîtriser le SRAS-CoV-2 jusqu’à la fin du printemps 2021. Les données de mobilité anonymisées des téléphones intelligents peuvent servir à guider le relâchement ou le resserrement des mesures de distanciation physique provinciales et régionales.

The endonasal patient reference tracker: a novel solution for accurate noninvasive electromagnetic neuronavigation

OBJECTIVE

Electromagnetic (EM) navigation provides the advantages of continuous guidance and tip-tracking of instruments. The current solutions for patient reference trackers are suboptimal, as they are either invasively screwed to the bone or less accurate if attached to the skin. The authors present a novel EM reference method with the tracker rigidly but not invasively positioned inside the nasal cavity.

METHODS

The nasal tracker (NT) consists of the EM coil array of the AxiEM tracker plugged into a nasal tamponade, which is then inserted into the inferior nasal meatus. Initially, a proof-of-concept study was performed on two cadaveric skull bases. The stability of the NT was assessed in simulated surgical situations, for example, prone, supine, and lateral patient positioning and skin traction. A deviation ≤ 2 mm was judged sufficiently accurate for clinical trial. Thus, a feasibility study was performed in the clinical setting. Positional changes of the NT and a standard skin-adhesive tracker (ST) relative to a ground-truth reference tracker were recorded throughout routine surgical procedures. The accuracy of the NT and ST was compared at different stages of surgery.

RESULTS

Ex vivo, the NT proved to be highly stable in all simulated surgical situations (median deviation 0.4 mm, range 0.0-2.0 mm). In 13 routine clinical cases, the NT was significantly more stable than the ST (median deviation at procedure end 1.3 mm, range 0.5-3.0 mm vs 4.0 mm, range 1.2-11.2 mm, p = 0.002). The loss of accuracy of the ST was highest during draping and flap fixation.

CONCLUSIONS

Application of the EM endonasal patient tracker was found to be feasible with high procedural stability ex vivo as well as in the clinical setting. This innovation combines the advantages of high precision and noninvasiveness and may, in the future, enhance EM navigation for neurosurgery.

Holographic patient tracking after bed movement for augmented reality neuronavigation using a head-mounted display

BACKGROUND

Holographic neuronavigation has several potential advantages compared to conventional neuronavigation systems. We present the first report of a holographic neuronavigation system with patient-to-image registration and patient tracking with a reference array using an augmented reality head-mounted display (AR-HMD).

METHODS

Three patients undergoing an intracranial neurosurgical procedure were included in this pilot study. The relevant anatomy was first segmented in 3D and then uploaded as holographic scene in our custom neuronavigation software. Registration was performed using point-based matching using anatomical landmarks. We measured the fiducial registration error (FRE) as the outcome measure for registration accuracy. A custom-made reference array with QR codes was integrated in the neurosurgical setup and used for patient tracking after bed movement.

RESULTS

Six registrations were performed with a mean FRE of 8.5 mm. Patient tracking was achieved with no visual difference between the registration before and after movement.

CONCLUSIONS

This first report shows a proof of principle of intraoperative patient tracking using a standalone holographic neuronavigation system. The navigation accuracy should be further optimized to be clinically applicable. However, it is likely that this technology will be incorporated in future neurosurgical workflows because the system improves spatial anatomical understanding for the surgeon.

COVID-19 CG enables SARS-CoV-2 mutation and lineage tracking by locations and dates of interest

COVID-19 CG (covidcg.org) is an open resource for tracking SARS-CoV-2 single-nucleotide variations (SNVs), lineages, and clades using the virus genomes on the GISAID database while filtering by location, date, gene, and mutation of interest. COVID-19 CG provides significant time, labor, and cost-saving utility to projects on SARS-CoV-2 transmission, evolution, diagnostics, therapeutics, vaccines, and intervention tracking. Here, we describe case studies in which users can interrogate (1) SNVs in the SARS-CoV-2 spike receptor binding domain (RBD) across different geographical regions to inform the design and testing of therapeutics, (2) SNVs that may impact the sensitivity of commonly used diagnostic primers, and (3) the emergence of a dominant lineage harboring an S477N RBD mutation in Australia in 2020. To accelerate COVID-19 efforts, COVID-19 CG will be upgraded with new features for users to rapidly pinpoint mutations as the virus evolves throughout the pandemic and in response to therapeutic and public health interventions.

Patient Identification Techniques - Approaches, Implications, and Findings

OBJECTIVES

To identify current patient identification techniques and approaches used worldwide in today's healthcare environment. To identify challenges associated with improper patient identification.

METHODS

A literature review of relevant peer-reviewed and grey literature published from January 2015 to October 2019 was conducted to inform the paper. The focus was on: 1) patient identification techniques and 2) unintended consequences and ramifications of unresolved patient identification issues.

RESULTS

The literature review showed six common patient identification techniques implemented worldwide ranging from unique patient identifiers, algorithmic approaches, referential matching software, biometrics, radio frequency identification device (RFID) systems, and hybrid models. The review revealed three themes associated with unresolved patient identification: 1) treatment, care delivery, and patient safety errors, 2) cost and resource considerations, and 3) data sharing and interoperability challenges.

CONCLUSIONS

Errors in patient identification have implications for patient care and safety, payment, as well as data sharing and interoperability. Different patient identification techniques ranging from unique patient identifiers and algorithms to hybrid models have been implemented worldwide. However, no current patient identification techniques have resulted in a 100% match rate. Optimizing algorithmic matching through data standardization and referential matching software should be studied further to identify opportunities to enhance patient identification techniques and approaches. Further efforts to improve patient identity management include adoption of patients' photos at registration, naming conventions, and standardized processes for recording patients' demographic data attributes.

MRLIHT: Mobile RFID-based Localization for Indoor Human Tracking

Radio Frequency Identification (RFID) technology has been widely used in indoor location tracking, especially serving human beings, due to its advantage of low cost, non-contact communication, resistance to hostile environments and so forth. Over the years, many indoor location tracking methods have been proposed. However, tracking mobile RFID readers in real-time has been a daunting task, especially for achieving high localization accuracy. In this paper, we propose a new Mobile RFID (M-RFID)-based Localization approach for Indoor Human Tracking, named MRLIHT. Based on the M-RFID model where RFID readers are equipped on the moving objects (human beings) and RFID tags are fixed deployed in the monitoring area, MRLIHT implements the real-time indoor location tracking effectively and economically. First, based on the readings of multiple tags detected by an RFID reader simultaneously, MRLIHT generates the response regions of tags to the reader. Next, MRLIHT determines the potential location region of the reader where two algorithms are devised. Finally, MRLIHT estimates the location of the reader by dividing the potential location region of the reader into finer-grained grids. The experimental results demonstrate that the proposed MRLIHT performs well in both accuracy and scalability.

Unique health identifiers for universal health coverage

Identifying everyone residing in a country, especially the poor, is an indispensable part of pursuing universal health coverage (UHC). Having information on an individuals' financial protection is also imperative for measuring the progress of UHC. This paper examines different ways of instituting a system of unique health identifiers that can lead toward achieving UHC, particularly in relation to utilizing universal civil registration and national unique identification number systems. Civil registration is a fundamental function of the government that establishes a legal identity for individuals and enables them to access essential public services. National unique identification numbers assigned at birth registration can further link their vital event information with data collected in different sectors, including in finance and health. Some countries use the national unique identification number as the unique health identifier, such as is done in South Korea and Thailand. In other countries, a unique health identifier is created in addition to the national unique identification number, but the two numbers are linked; Slovenia offers an example of this arrangement. The advantages and disadvantages of the system types are discussed in the paper. In either approach, linking the health system with the civil registration and national identity management systems contributed to advancing effective and efficient UHC programs in those countries.

The Relationship between Health Information Technology Laboratory Tracking Systems and Hospital Financial Performance and Quality

The objective of this study is to explore the relationship between hospitals Health Information Technology (HIT), and financial and quality performance. The study merged the 2017 Centers for Medicare & Medicaid Services (CMS) Healthcare Cost Report Information System, American Hospital Association Annual Survey, and two CMS Hospital Compare datasets. A total of 3002 hospitals were analyzed using multivariate analysis. We found that hospitals with laboratory tracking systems reported better financial performance on five financial performance measures. Policymakers should consider developing policies that facilitate exploration and adoption of various hospital HIT capabilities that measurably improves hospital quality of care.

Improving patient identification in an ophthalmology clinic using name alerts

OBJECTIVE

To develop a standardized process for reviewing daily patient lists and identifying potential risks of misidentification. Our goal was to develop a proactive approach to identify and eliminate risks of patient misidentification.

METHODS

Assessment of current patient identification practices took place over a period of 4 weeks. Using a process map, a patient survey was developed to determine the encounter points when patient identification was confirmed. This information was used to develop a standardized protocol for review of daily appointment lists.

RESULTS

Review of daily appointment lists was completed to identify potential similar/same name risks. A standardized manual process of chart review, flagging, and tracking was developed.

CONCLUSIONS

The name alert process resulted in a simple manual process for identifying which patients have a higher name risk and allowed care providers to take preventative action to decrease potential risk of incorrect diagnostic testing, procedure, or medication administration.

The Development of an RFID Solution to Facilitate the Traceability of Patient and Pharmaceutical Data

One of the principal objectives of hospitals is to increase the quality of care of the patient. This is even more of a priority in Day Hospitals where certain medication requires special attention, from its preparation in the Pharmacy service to its delivery to the patient in the Day Hospital. In the case of expensive medicines, nursing staff have to comply with very detailed instructions in their administration to the patient (name of medicine, route, dosage, schedule, previous medication, conditions of conservation, etc.). This work focuses on the development of a multi-faceted hub application to facilitate the traceability of mixed intravenous medication from the beginning to the end of the process of prescription-validation-dosing-preparation-administration (PVD-PA) and be available to all health professionals involved: doctors, pharmacists, and the nursing staff of the Hospital Pharmacy and Day Hospital.

An Indoor Wayfinding System Based on Geometric Features Aided Graph SLAM for the Visually Impaired

This paper presents a 6-degree of freedom (DOF) pose estimation (PE) method and an indoor wayfinding system based on the method for the visually impaired. The PE method involves two-graph simultaneous localization and mapping (SLAM) processes to reduce the accumulative pose error of the device. In the first step, the floor plane is extracted from the 3-D camera's point cloud and added as a landmark node into the graph for 6-DOF SLAM to reduce roll, pitch, and Z errors. In the second step, the wall lines are extracted and incorporated into the graph for 3-DOF SLAM to reduce X , Y , and yaw errors. The method reduces the 6-DOF pose error and results in more accurate pose with less computational time than the state-of-the-art planar SLAM methods. Based on the PE method, a wayfinding system is developed for navigating a visually impaired person in an indoor environment. The system uses the estimated pose and floor plan to locate the device user in a building and guides the user by announcing the points of interest and navigational commands through a speech interface. Experimental results validate the effectiveness of the PE method and demonstrate that the system may substantially ease an indoor navigation task.

Patient identification and tube labelling - a call for harmonisation

Venous blood sampling (phlebotomy) is the most common invasive procedure performed in patient care. Guidelines on the correct practice of phlebotomy are available, including the H3-A6 guideline issued by the Clinical Laboratory Standards Institute (CLSI). As the quality of practices and procedures related to venous blood sample collection in European countries was unknown, the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group for the Preanalytical Phase conducted an observational study in 12 European countries. The study demonstrated that the level of compliance of phlebotomy procedures with the CLSI H3-A6 guideline was unacceptably low, and that patient identification and tube labelling are amongst the most critical steps in need of immediate attention and improvement. The process of patient identification and tube labelling is an essential safety barrier to prevent patient identity mix-up. Therefore, the EFLM Working Group aims to encourage and support worldwide harmonisation of patient identification and tube labelling procedures in order to reduce the risk of preanalytical errors and improve patient safety. With this Position paper we wish to raise awareness and provide recommendations for proper patient and sample identification procedures.

Evaluation of a Tracking System for Patients and Mixed Intravenous Medication Based on RFID Technology

At present, one of the primary concerns of healthcare professionals is how to increase the safety and quality of the care that patients receive during their stay in hospital. This is particularly important in the administration of expensive and high-risk medicines with which it is fundamental to minimize the possibility of adverse events in the process of prescription-validation-preparation/dosage-dispensation-administration of intravenous mixes. This work is a detailed analysis of the evaluation, carried out by the health personnel involved in the Radiofrequency Identification (RFID) system developed in the Day Hospital and Pharmacy services of the Complejo Hospitalario Universitario A Coruña (CHUAC). The RFID system is evaluated by analyzing surveys completed by said health personnel, since their questions represent the key indicators of the patient care process (safety, cost, adequacy with the clinical practice). This work allows us to conclude, among other things, that the system tracks the patients satisfactorily and that its cost, though high, is justified in the context of the project context (use of dangerous and costly medication).

Detecting Bipolar Depression From Geographic Location Data

Objective

This paper aims to identify periods of depression using geolocation movements recorded from mobile phones in a prospective community study of individuals with bipolar disorder (BD).

Methods

Anonymized geographic location recordings from 22 BD participants and 14 healthy controls (HC) were collected over 3 months. Participants reported their depressive symptomatology using a weekly questionnaire (QIDS-SR₁₆). Recorded location data were preprocessed by detecting and removing imprecise data points and features were extracted to assess the level and regularity of geographic movements of the participant. A subset of features were selected using a wrapper feature selection method and presented to 1) a linear regression model and a quadratic generalized linear model with a logistic link function for questionnaire score estimation; and 2) a quadratic discriminant analysis classifier for depression detection in BD participants based on their questionnaire responses.

Results

HC participants did not report depressive symptoms and their features showed similar distributions to nondepressed BD participants. Questionnaire score estimation using geolocation-derived features from BD participants demonstrated an optimal mean absolute error rate of 3.73, while depression detection demonstrated an optimal (median ± IQR) F₁ score of 0.857 ± 0.022 using five features (classification accuracy: 0.849 ± 0.016; sensitivity: 0.839 ± 0.014; specificity: 0.872 ± 0.047).

Conclusion

These results demonstrate a strong link between geographic movements and depression in bipolar disorder.

Significance

To our knowledge, this is the first community study of passively recorded objective markers of depression in bipolar disorder of this scale. The techniques could help individuals monitor their depression and enable healthcare providers to detect those in need of care or treatment.

Getting It Right for Patient Safety: Specimen Collection Process Improvement From Operating Room to Pathology

OBJECTIVES

Specimen labeling defects within the perioperative environment are a known patient safety risk that carries the potential for adverse outcomes. These outcomes are a result of errors that occur when unsuspecting providers operate within poorly designed processes with little control over the specimen collection context. Many costly outcomes resulting from labeling errors may include patient harm, inappropriate treatments, lengthy investigations, corrective actions, and, at times, legal action.

METHODS

This improvement initiative to identify and reduce the risk of specimen labeling defects includes the application of a disciplined Lean problem-solving approach with the engagement of employees who actually perform the work.

RESULTS

By listening to the voice of our internal customers, we collectively redesigned the workflow by collaboratively linking work teams of the operating room and Pathology Department of Henry Ford Hospital, Detroit, over a 2-year period.

CONCLUSIONS

We illustrate successful interventions achieved by Lean process management by streamlining, standardizing, and mistake proofing the processes and eliminating waste and inefficiency through systematic problem solving.

Automatic Detection and Notification of “Wrong Patient—Wrong Location” Errors in the Operating Room

When procedures and processes to assure patient location based on human performance do not work as expected, patients are brought incrementally closer to a possible “wrong patient—wrong procedure” error. We developed a system for automated patient location monitoring and management. Realtime data from an active infrared/radio frequency identification tracking system provides patient location data that are robust and can be compared with an “expected process” model to automatically flag wrong-location events as soon as they occur. The system also generates messages that are automatically sent to process managers via the hospital paging system, thus creating an active alerting function to annunciate errors. We deployed the system to detect and annunciate “patientin-wrong-OR” events. The system detected all “ wrongoperating room (OR)” events, and all “wrong-OR” locations were correctly assigned within 0.50 ± 0.28 minutes (mean ± SD). This corresponded to the measured latency of the tracking system. All wrong-OR events were correctly annunciated via the paging function. This experiment demonstrates that current technology can automatically collect sufficient data to remotely monitor patient flow through a hospital, provide decision support based on predefined rules, and automatically notify stakeholders of errors.

Auto Identification Technology and Its Impact on Patient Safety in the Operating Room of the Future

Automatic identification technologies, such as bar coding and radio frequency identification, are ubiquitous in everyday life but virtually nonexistent in the operating room. User expectations, based on everyday experience with automatic identification technologies, have generated much anticipation that these systems will improve readiness, workflow, and safety in the operating room, with minimal training requirements. We report, in narrative form, a multi-year experience with various automatic identification technologies in the Operating Room of the Future Project at Massachusetts General Hospital. In each case, the additional human labor required to make these `labor-saving' technologies function in the medical environment has proved to be their undoing. We conclude that while automatic identification technologies show promise, significant barriers to realizing their potential still exist. Nevertheless, overcoming these obstacles is necessary if the vision of an operating room of the future in which all processes are monitored, controlled, and optimized is to be achieved.

Piloting the European Unified Patient Identity Management (EUPID) Concept to Facilitate Secondary Use of Neuroblastoma Data from Clinical Trials and Biobanking

Data from two contexts, i.e. the European Unresectable Neuroblastoma (EUNB) clinical trial and results from comparative genomic hybridisation (CGH) analyses from corresponding tumour samples shall be provided to existing repositories for secondary use. Utilizing the European Unified Patient IDentity Management (EUPID) as developed in the course of the ENCCA project, the following processes were applied to the data: standardization (providing interoperability), pseudonymization (generating distinct but linkable pseudonyms for both contexts), and linking both data sources. The applied procedures resulted in a joined dataset that did not contain any identifiers that would allow to backtrack the records to either data sources. This provided a high degree of privacy to the involved patients as required by data protection regulations, without preventing proper analysis.

Tracking the take - Using patient flow data to improve AMU performance and safety

AIMS

To create a system to co-ordinate the medical take, bed management and track patient flow. To use the system to continuously audit against Society for Acute Medicine Quality Indicators. To use the data to model patient flow and optimise working patterns to improve waiting times.

METHOD

An online whiteboard and underlying database system were designed, tested and implemented. Data from this system were used to audit against SAM Quality Indicators and then analysed to optimise both trainee and consultant working patterns.

RESULTS

The online whiteboard proved effective and popular as a working tool. Data collection improved using the electronic system. Optimising junior doctor working patterns to match demand led to a reduction of average waiting time to see a doctor from 190 minutes to 71 minutes (p < 0.0001), and a reduction in the proportion of patients waiting over 4 hours from 40% to 10% (p > 0.0001). Optimising consultant working patterns did not produced significant changes in waiting times.

CONCLUSIONS

The online whiteboard improved day-to-day working and data collection, when compared to the previous paper-based system. Better data facilitated analysis of working patterns leading to a significant improvement in patient waiting times.

Human factors engineering approaches to patient identification armband design

The task of patient identification is performed many times each day by nurses and other members of the care team. Armbands are used for both direct verification and barcode scanning during patient identification. Armbands and information layout are critical to reducing patient identification errors and dangerous workarounds. We report the effort at two large, integrated healthcare systems that employed human factors engineering approaches to the information layout design of new patient identification armbands. The different methods used illustrate potential pathways to obtain standardized armbands across healthcare systems that incorporate human factors principles. By extension, how the designs have been adopted provides examples of how to incorporate human factors engineering into key clinical processes.