Background: All aspects of the heath care sector are being asked to account for their performance. This poses unique challenges for local public health units with their traditional focus on population health and their emphasis on disease prevention, health promotion and protection. Reliance on measures of health status provides an imprecise and partial picture of the performance of a health unit. In 2004 the provincial Institute for Clinical Evaluative Sciences based in Ontario, Canada introduced a public-health specific balanced scorecard framework. We present the conceptual deliberations and decisions undertaken by a health unit while adopting the framework.
Background: The science of syndromic surveillance is still very much in its infancy. While a number of syndromic surveillance systems are being evaluated in the US, very few have had success thus far in predicting an infectious disease event. Furthermore, to date, the majority of syndromic surveillance systems have been based primarily in emergency department settings, with varying levels of enhancement from other data sources. While research has been done on the value of telephone helplines on health care use and patient satisfaction, very few projects have looked at using a telephone helpline as a source of data for syndromic surveillance, and none have been attempted in Canada. The notable exception to this statement has been in the UK where research using the national NHS Direct system as a syndromic surveillance tool has been conducted.
Background: Little is known about inter-facility patient transfers in populations. In 2003, detailed information about inter-facility patient transfers began to be systematically collected in Ontario. Methodology: The authors undertook a descriptive examination of inter-facility patient transfers using a newly created population-based information system. Results: Approximately 1,000 inter-facility patient transfers occur in Ontario each day, and every day and a half, the total distance travelled for these transfers equals the distance around the earth' s circumference. The annual cost for patient transfers is approximately $283 million. Most common were routine and non-urgent inter-facility patient transfers. Eighty-five thousand patients (24.3% of transferred patients) were transported between healthcare facilities for dialysis appointments, appointments with physicians and return trips home. Patients with circulatory conditions were the most commonly transferred diagnostic group. Although 70% of all transfers were within 25 kilometres, some were for longer distances: for example, those involving pregnant women and newborn babies required travelling a median distance of 40.3 kilometres for continued care. Cardiac patients (54,000 patient transfers per year) travelled a median of 24.2 kilometres to reach a catheterization lab for treatment and further investigation. There was considerable lateral movement between academic health sciences centres (AHSCs). Over 16,000 patients per year (4.7% of all transfers) were transferred from one AHSC to another, predominantly for cardiac care. Discussion: Patients in Ontario are often transferred between healthcare facilities. Most transfers are for routine, non-life-threatening reasons, using the Emergency Medical Services (EMS) system. This practice diverts resources from more emergent requests. Although patient transportation is a necessary part of any healthcare system, the results of this study highlight the current demands on a system that was not intended for the volume of inter-facility patient transfers it is supporting. These results call into question the use of sophisticated, highly trained, expensive patient transfer resources to provide routine medical services in Ontario.
IntroductionDigital health, the use of apps, text-messaging, and online interventions, can revolutionize healthcare and make care more equitable. Currently, digital health interventions are often not designed for those who could benefit most and may have unintended consequences. In this paper, we explain how privacy vulnerabilities and power imbalances, including racism and sexism, continue to influence health app design and research. We provide guidelines for researchers to design, report and evaluate digital health studies to maximize social justice in health.MethodsFrom September 2020 to April 2021, we held five discussion and brainstorming sessions with researchers, students, and community partners to develop the guide and the key questions. We additionally conducted an informal literature review, invited experts to review our guide, and identified examples from our own digital health study and other studies.ResultsWe identified five overarching topics with key questions and subquestions to guide researchers in designing or evaluating a digital health research study. The overarching topics are: 1. Equitable distribution; 2. Equitable design; 3. Privacy and data return; 4. Stereotype and bias; 5. Structural racism.ConclusionWe provide a guide with five key topics and questions for social justice digital health research. Encouraging researchers and practitioners to ask these questions will help to spark a transformation in digital health toward more equitable and ethical research. Future work needs to determine if the quality of studies can improve when researchers use this guide.
Background: The Provincial Transfer Authorization Centre (PTAC) was established as a part of the emergency response in Ontario, Canada to the Severe Acute Respiratory Syndrome (SARS) outbreak in 2003. Prior to 2003, data relating to inter-facility patient transfers were not collected in a systematic manner. Then, in an emergency setting, a comprehensive database with a complex data collection process was established. For the first time in Ontario, population-based data for patient movement between healthcare facilities for a population of twelve million are available. The PTAC database stores all patient transfer data in a large database. There are few population-based patient transfer databases and the PTAC database is believed to be the largest example to house this novel dataset. A patient transfer database has also never been validated. This paper presents the validation of the PTAC database.
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