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The 2019 novel coronavirus (COVID-19) pandemic created an immediate need to enhance current efforts to reduce transfers of nursing home (NH) residents to acute care. Long-Term Care Plus (LTC+), a collaborative care program developed and implemented during the COVID-19 pandemic, aimed to enhance care in the NH setting while also decreasing unnecessary acute care transfers. Using a hub-and-spoke model, LTC+ was implemented in six hospitals serving as central hubs to 54 geographically associated NHs with 9,574 beds in Toronto, Canada. LTC+ provided to NHs with the following: 1) virtual general internal medicine (GIM) consultations; 2) nursing navigator support; 3) rapid access to laboratory and diagnostic imaging services; and 4) educational resources. From April 2020 to June 2021, LTC+ provided 381 GIM consultations that addressed abnormal bloodwork (15%), cardiac problems (13%) and unexplained fever (11%) as the most common reasons for consultation. Sixty-five nurse navigator calls addressed requests for non-GIM specialist consultations (34%), wound care assessments (14%) and system navigation (12%). One hundred and seventy-seven (46%; 95% CI 41-52%) consults addressed care concerns sufficiently to avoid the need for acute care transfer. All 36 primary care physicians who consulted the LTC+ program reported strong satisfaction with the advice provided. Early results demonstrate the feasibility and acceptability of an integrated care model that enhances care delivery for NH residents where they reside and has the potential to positively impact the long-term care sector by ensuring equitable and timely access to care for people living in NHs. It represents an important step towards health system integration that values the expertise within the long-term care sector., Early impact of the implementation of a novel collaborative care program in nursing homes demonstrates feasibility in enhancing care, decreasing unnecessary acute care transfers, and building connections across sectors.

Background Multiplex polymerase chain reaction (PCR) panels allow for rapid detection or exclusion of pathogens causing meningitis and encephalitis (ME). The clinical impact of rapid multiplex PCR ME panel results on the duration of empiric antibiotic therapy is not well characterized. Methods We performed a retrospective prepost study at our institution that evaluated the clinical impact of a multiplex PCR ME panel among adults with suspected bacterial meningitis who received empiric antibiotic therapy and underwent lumbar puncture in the emergency department. The primary outcome was the duration of empiric antibiotic therapy. Results The positive pathogen detection rates were similar between pre- and post-multiplex PCR ME panel periods (17.5%, 24 of 137 vs 20.3%, 14 of 69, respectively). The median duration of empiric antibiotic therapy was significantly reduced in the post-multiplex PCR ME panel period compared with the pre-multiplex PCR ME panel period (34.7 vs 12.3 hours, P = .01). At any point in time, 46% more patients in the post-multiplex PCR ME panel period had empiric antibiotic therapy discontinued or de-escalated compared with the pre-multiplex PCR ME panel period (sex- and immunosuppressant use-adjusted hazard ratio 1.46, P = .01). The median hospital length of stay was shorter in the post-multiplex PCR ME panel period (3 vs 4 days, P = .03). Conclusions The implementation of the multiplex PCR ME panel for bacterial meningitis reduced the duration of empiric antibiotic therapy and possibly hospital length of stay compared with traditional microbiological testing methods., In this pre-post study, implementation of a multiplex polymerase chain reaction panel testing for agents of meningitis significantly reduced the duration of empiric antibiotic therapy, time to targeted therapy, and hospital length of stay compared with traditional microbiological testing methods.

Background Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality and leads to frequent hospital admissions and emergency department (ED) visits. COPD exacerbations are an important patient outcome, and reducing their frequency would result in significant cost savings. Remote monitoring and self-monitoring could both help patients manage their symptoms and reduce the frequency of exacerbations, but they have different resource implications and have not been directly compared. Objective This study aims to compare the effectiveness of implementing a technology-enabled self-monitoring program versus a technology-enabled remote monitoring program in patients with COPD compared with a standard care group. Methods We conducted a 3-arm randomized controlled trial evaluating the effectiveness of a remote monitoring and a self-monitoring program relative to standard care. Patients with COPD were recruited from outpatient clinics and a pulmonary rehabilitation program. Patients in both interventions used a Bluetooth-enabled device kit to monitor oxygen saturation, blood pressure, temperature, weight, and symptoms, but only patients in the remote monitoring group were monitored by a respiratory therapist. All patients were assessed at baseline and at 3 and 6 months after program initiation. Outcomes included self-management skills, as measured by the Partners in Health (PIH) Scale; patient symptoms measured with the St George’s Respiratory Questionnaire (SGRQ); and the Bristol COPD Knowledge Questionnaire (BCKQ). Patients were also asked to self-report on health system use, and data on health use were collected from the hospital. Results A total of 122 patients participated in the study: 40 in the standard care, 41 in the self-monitoring, and 41 in the remote monitoring groups. Although all 3 groups improved in PIH scores, BCKQ scores, and SGRQ impact scores, there were no significant differences among any of the groups. No effects were observed on the SGRQ activity or symptom scores or on hospitalizations, ED visits, or clinic visits. Conclusions Despite regular use of the technology, patients with COPD assigned to remote monitoring or self-monitoring did not have any improvement in patient outcomes such as self-management skills, knowledge, or symptoms, or in health care use compared with each other or with a standard care group. This may be owing to low health care use at baseline, the lack of structured educational components in the intervention groups, and the lack of integration of the action plan with the technology. Trial Registration ClinicalTrials.gov NCT03741855; https://clinicaltrials.gov/ct2/show/ NCT03741855

Background Health systems are increasingly looking toward the private sector to provide digital solutions to address health care demands. Innovation in digital health is largely driven by small- and medium-sized enterprises (SMEs), yet these companies experience significant barriers to entry, especially in public health systems. Complex and fragmented care models, alongside a myriad of relevant stakeholders (eg, purchasers, providers, and producers of health care products), make developing value propositions for digital solutions highly challenging. Objective This study aims to identify areas for health system improvement to promote the integration of innovative digital health technologies developed by SMEs. Methods This paper qualitatively analyzes a series of case studies to identify health system barriers faced by SMEs developing digital health technologies in Canada and proposed solutions to encourage a more innovative ecosystem. The Women’s College Hospital Institute for Health System Solutions and Virtual Care established a consultation program for SMEs to help them increase their innovation capacity and take their ideas to market. The consultation involved the SME filling out an onboarding form and review of this information by an expert advisory committee using guided considerations, leading to a recommendation report provided to the SME. This paper reports on the characteristics of 25 SMEs who completed the program and qualitatively analyzed their recommendation reports to identify common barriers to digital health innovation. Results A total of 2 central themes were identified, each with 3 subthemes. First, a common barrier to system integration was the lack of formal evaluation, with SMEs having limited resources and opportunities to conduct such an evaluation. Second, the health system’s current structure does not create incentives for clinicians to use digital technologies, which threatens the sustainability of SMEs’ business models. SMEs faced significant challenges in engaging users and payers from the public system due to perverse economic incentives. Physicians are compensated by in-person visits, which actively works against the goals of many digital health solutions of keeping patients out of clinics and hospitals. Conclusions There is a significant disconnect between the economic incentives that drive clinical behaviors and the use of digital technologies that would benefit patients’ well-being. To encourage the use of digital health technologies, publicly funded health systems need to dedicate funding for the evaluation of digital solutions and streamlined pathways for clinical integration.

Background Chronic obstructive pulmonary disease (COPD) is the third leading cause of mortality worldwide. Reducing the number of COPD exacerbations is an important patient outcome and a major cost-saving approach. Both technology-enabled self-monitoring (SM) and remote monitoring (RM) programs have the potential to reduce exacerbations, but they have not been directly compared with each other. As RM is a more resource-intensive strategy, it is important to understand whether it is more effective than SM. Objective The objective of this study is to evaluate the impact of SM and RM on self-management behaviors, COPD disease knowledge, and respiratory status relative to standard care (SC). Methods This was a 3-arm open-label randomized controlled trial comparing SM, RM, and SC completed in an outpatient COPD clinic in a community hospital. Patients in the SM and RM groups recorded their vital signs (oxygen, blood pressure, temperature, and weight) and symptoms with the Cloud DX platform every day and were provided with a COPD action plan. Patients in the RM group also received access to a respiratory therapist (RT). The RT monitored their vital signs intermittently and contacted them when their vitals varied outside of predetermined thresholds. The RT also contacted patients once a week irrespective of their vital signs or symptoms. All patients were randomized to 1 of the 3 groups and assessed at baseline and 3 and 6 months after program initiation. The primary outcome was the Partners in Health scale, which measures self-management skills. Secondary outcomes included the St. George's Respiratory Questionnaire, Bristol COPD Knowledge Questionnaire, COPD Assessment Test, and modified-Medical Research Council Breathlessness Scale. Patients were also asked to self-report on health system usage. Results A total of 122 patients participated in the study, 40 in the SC, 41 in the SM, and 41 in the RM groups. Out of those patients, 7 in the SC, 5 in the SM, and 6 in the RM groups did not complete the study. There were no significant differences in the rates of study completion among the groups (P=.80). Conclusions Both SM and RM have shown promise in reducing acute care utilization and exacerbation frequencies. As far as we are aware, no studies to date have directly compared technology-enabled self-management with RM programs in COPD patients. We believe that this study will be an important contribution to the literature. Trial Registration ClinicalTrials.gov NCT03741855; https://clinicaltrials.gov/ct2/show/NCT03741855 International Registered Report Identifier (IRRID) DERR1-10.2196/13920

Sickle cell disease (SCD) is a major public health priority throughout much of the world, affecting millions of people. In many regions, particularly those in resource-limited settings, SCD is not consistently diagnosed. In Africa, where the majority of SCD patients reside, more than 50% of the 0.2-0.3 million children born with SCD each year will die from it; many of these deaths are in fact preventable with correct diagnosis and treatment. Here we present a deep learning framework which can perform automatic screening of sickle cells in blood smears using a smartphone microscope. This framework uses two distinct, complementary deep neural networks. The first neural network enhances and standardizes the blood smear images captured by the smartphone microscope, spatially and spectrally matching the image quality of a laboratory-grade benchtop microscope. The second network acts on the output of the first image enhancement neural network and is used to perform the semantic segmentation between healthy and sickle cells within a blood smear. These segmented images are then used to rapidly determine the SCD diagnosis per patient. We blindly tested this mobile sickle cell detection method using blood smears from 96 unique patients (including 32 SCD patients) that were imaged by our smartphone microscope, and achieved ~98% accuracy, with an area-under-the-curve (AUC) of 0.998. With its high accuracy, this mobile and cost-effective method has the potential to be used as a screening tool for SCD and other blood cell disorders in resource-limited settings., Comment: 30 pages, 5 figures