An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study.

BACKGROUND: A coordinated care system helps provide timely access to treatment for suspected acute stroke. In Northwestern Ontario (NWO), Canada, communities are widespread with several hospitals offering various diagnostic equipment and services. Thus, resources are limited, and health care providers must often transfer patients with stroke to different hospital locations to ensure the most appropriate care access within recommended time frames. However, health care providers frequently situated temporarily (locum) in NWO or providing care remotely from other areas of Ontario may lack sufficient information and experience in the region to access care for a patient with a time-sensitive condition. Suboptimal decision-making may lead to multiple transfers before definitive stroke care is obtained, resulting in poor outcomes and additional health care system costs. OBJECTIVE: We aimed to develop a tool to inform and assist NWO health care providers in determining the best transfer options for patients with stroke to provide the most efficient care access. We aimed to develop an app using a comprehensive geomapping navigation and estimation system based on machine learning algorithms. This app uses key stroke-related timelines including the last time the patient was known to be well, patient location, treatment options, and imaging availability at different health care facilities. METHODS: Using historical data (2008-2020), an accurate prediction model using machine learning methods was developed and incorporated into a mobile app. These data contained parameters regarding air (Ornge) and land medical transport (3 services), which were preprocessed and cleaned. For cases in which Ornge air services and land ambulance medical transport were both involved in a patient transport process, data were merged and time intervals of the transport journey were determined. The data were distributed for training (35%), testing (35%), and validation (30%) of the prediction model. RESULTS: In total, 70,623 records were collected in the data set from Ornge and land medical transport services to develop a prediction model. Various learning models were analyzed; all learning models perform better than the simple average of all points in predicting output variables. The decision tree model provided more accurate results than the other models. The decision tree model performed remarkably well, with the values from testing, validation, and the model within a close range. This model was used to develop the "NWO Navigate Stroke" system. The system provides accurate results and demonstrates that a mobile app can be a significant tool for health care providers navigating stroke care in NWO, potentially impacting patient care and outcomes. CONCLUSIONS: The NWO Navigate Stroke system uses a data-driven, reliable, accurate prediction model while considering all variations and is simultaneously linked to all required acute stroke management pathways and tools. It was tested using historical data, and the next step will to involve usability testing with end users.

Impact of a Remote Patient Monitoring Platform on Outcomes Following a Total Hip or Knee Arthroplasty.

Background: The coronavirus pandemic highlighted the need for remote patient monitoring to deliver and provide access to patient care and education. A mobile-based app providing interactive tools for patient education and monitoring was piloted at Thunder Bay Regional Health Sciences Centre (TBRHSC) in November 2020. We aimed to examine the platform's impact on postoperative length of stay, hospital readmissions, and emergency department (ED) visits 60 days postsurgery in total hip and knee arthroplasty patients in Northwestern Ontario. Methods: Data were assessed from patients undergoing primary total hip or knee arthroplasties at TBRHSC from March 1, 2020, to February 28, 2022. Patients were divided into 2 cohorts based on enrollment with the mobile-based app (SeamlessMD). Statistical differences in outcomes were determined using Mann-Whitney or χ2 tests. An odds ratio was calculated for ED visits. Results: Patients enrolled in the mobile-based app had statistically lower length of stay (U = 7779.0, P < .001) and fewer ED visits (χ2 (1,212) = 5.570, P = .018) than patients not enrolled in the program. Patients not enrolled had 2.31 times greater odds of visiting the ED postsurgery (odds ratio = 0.432, 95% confidence interval = 0.213-0.877, P = .022). There were no statistical differences found in readmission rates. Conclusions: The implementation of the mobile-based app at TBRHSC showed its potential value as a tool to reduce costs in the healthcare system and improve patient outcomes. Consequentially, more formal studies are required to elucidate the magnitude of this effect.

Comparison of a validated decision-support tool to a standard of care triage system for knee osteoarthritis assessment: a proof-of-concept study.

BACKGROUND: Patients with knee osteoarthritis (OA) in northwestern Ontario are referred by their primary care provider (PCP) to a centralized assessment clinic for evaluation by an advanced practice physiotherapist (APP) to determine if they will require surgical management. However, many patients are found to not require surgical management, resulting in delays for patients who do. A decision-support tool was developed to address this issue and to guide treatment options by determining the need for surgical or nonsurgical approaches. METHODS: We used a proof-of-concept method to assess the use of the decision-support tool in northwestern Ontario. Data from 100 consecutive patients assessed for knee OA management were collected from the Thunder Bay centralized assessment clinic. Two levels of agreement analyses (calculated using Cohen κ statistic) were performed, between the APP assessment decision (surgical or non-surgical) and the decision-support tool recommendation, and between the surgeon's decision (surgical or non-surgical) and the decision-support tool recommendation. RESULTS: We found a near-perfect agreement (κ = 0.870, n = 65) between the APP decision and the decision-support tool recommendation, when controlled for patient preference. There was a substantial level of agreement (κ = 0.618, n = 72) between the decision-support tool recommendation and the surgeon's decision. CONCLUSION: The decision-support tool recommendation showed considerable agreement with the decisions of the APP and surgeon indicating that it could be a valuable tool to guide PCPs caring for patients with knee OA. The applicability of a decision-support tool in northwestern Ontario displayed promising results, but further research is needed to examine the feasibility in a primary care setting.

Clinical and laboratory characteristics of patients presenting to a tertiary care center emergency department with invasive group A streptococcal infections.

OBJECTIVES: The aim of this study was to describe the clinical and laboratory characteristics of invasive group A streptococcal infections in a geographic area that sees a high volume of cases. METHODS: We conducted a health records review of consecutive patients presenting to the Thunder Bay Regional Health Sciences Centre Emergency Department (ED) in 2016-2017 with a diagnosis of invasive group A streptococcal infection using ICD-10 codes. Patient demographics, host characteristics, triage vital signs, laboratory values, culture sites, and disposition were described using univariate and bivariate statistics. RESULTS: Forty-four adult cases were identified over 2 years, with a median age of 44 years (interquartile range, 35-52). The most prevalent risk factors were diabetes mellitus (45%), current or previous alcohol abuse (39%), and current or previous intravenous drug use (34%). The two most abnormal triage vitals signs were a heart rate ≥ 100 beats per minute in 32 (73%) cases and a respiratory rate ≥ 20 breaths per minute in 27 (63%) cases. The temperature was ≥ 38°C in only 14 (32%) of cases. The C-reactive protein (CRP) was always elevated when measured, and greater than 150 mg/L in 20 (71%) of cases. One-third of patients had an ED visit in the preceding 7 days before the diagnosis of invasive group A Streptococcus. CONCLUSIONS: Invasive group A streptococcal infections often present insidiously in adult patients with mild tachycardia and tachypnea at triage. The CRP was the most consistently abnormal laboratory investigation.

Pulmonary ultrashort echo time 19F MR imaging with inhaled fluorinated gas mixtures in healthy volunteers: feasibility.

PURPOSE: To perform static breath-hold fluorine 19 ((19)F) three-dimensional (3D) ultrashort echo time (UTE) magnetic resonance (MR) imaging of the lungs in healthy volunteers by using a mixture of 79% perfluoropropane (PFP) and 21% O2. MATERIALS AND METHODS: This study protocol was approved by the local research ethics board and by Health Canada. All volunteers provided written informed consent. Ten healthy volunteers underwent MR imaging at 3.0 T. Fluorine 19 3D UTE MR images were acquired during a 15-second breath hold according to one of two breathing protocols: protocol A, a 1-L inhalation of a mixture of 79% PFP and 21% O2, and protocol B, continuous breathing from a 5-L bag of a mixture of 79% PFP and 21% O2 followed by a 1-L inhalation of the same PFP-O2 mixture from a separate bag and a subsequent breath hold. The signal-to-noise ratio (SNR) was measured in the three most central image sections and was compared between breathing protocols by using an unpaired t test. RESULTS: Overall, the SNR was significantly greater for breathing protocol B (continuous breathing) than for breathing protocol A (single breath) (P = .018). The mean SNRs were 18 ± 6 (standard deviation) and 32 ± 6 for images acquired by using breathing protocols A and B, respectively. Breathing protocol B improves SNR by "washing out" the air from the lungs and increasing the PFP concentration prior to (19)F imaging. CONCLUSION: This study demonstrates the feasibility of (19)F 3D UTE static breath-hold MR imaging of human lungs with inert fluorinated gases.

Synthesis, characterization and Stat3 inhibitory properties of the prototypical platinum(IV) anticancer drug, [PtCl3(NO2)(NH3)2] (CPA-7).

This paper describes a reinvestigation of the literature concerning the synthesis and structural characterization of the platinum(IV)-based anticancer drug known as CPA-7 and believed to be the compound fac-[PtCl3(NO2)(NH 3)2]. CPA-7 has previously been extensively investigated for its ability to control tumor cell growth by inhibition of Stat3 signaling, but very little information is available concerning its synthesis or spectroscopic properties. A reproducible synthetic route is shown to produce an active material which is characterized by IR and (1)H, (14)N, (15)N, and (195)Pt NMR spectroscopy, and single crystal X-ray crystallography. The freshly prepared drug is obtained as a single isomer which may in fact be fac- or mer-[PtCl3(NO2)(NH3)2], but recrystallization resulted in a disordered crystal containing approximately equal amounts of the two geometric isomers.