Who responds to longer wait times? The effects of predicted emergency wait times on the health and volume of patients who present for care.

Healthcare is often free at the point-of-care so that price does not deter patients. However, the dis-utility from waiting for care that often occurs could also lead to deterrence. I investigate responses in the volume and types of patients that demand emergency care when predicted waiting times quasi-randomly change. I leverage a discontinuity to compare emergency sites with similar predicted wait times but with different apparent wait times displayed to patients. I use impulse response functions estimated by local projections to estimate effects of predicted wait times on patient demand for care. An additional thirty minutes of predicted wait time results in 15% fewer waiting patients at urgent cares and 2% fewer waiting patients at emergency departments within three hours of display. Patients that stop using emergency care are also triaged as healthier. However, at very high predicted wait times, there are reductions in demand for all patients including sicker patients.

Effects of extending residencies on the supply and quality of family medicine practitioners; difference-in-differences evidence from the implementation of mandatory family medicine residencies in Canada.

I examine the impacts of extending residency training programs on the supply and quality of physicians practicing primary care. I leverage mandated extended residency lengths for primary care practitioners that were rolled out over 20 years in Canada on a province-by-province basis. I compare these primary care specialties to other specialties that did not change residency length (first difference) before and after the policy implementation (second difference) to assess how physician supply evolved in response. To examine quality outcomes, I use a set of scraped data and repeat this difference-in-differences identification strategy for complaints resulting in censure against physicians in Ontario. I find declines in the number of primary care providers by 5% for up to 9 years after the policy change. These changes are particularly pronounced in new graduates and younger physicians, suggesting that the policy change dissuaded these physicians from entering primary care residencies. I find no impacts on quality of physicians as measured by public censure of physicians. This suggests that extending primary care training caused declines in physician supply without improvement in the quality of these physicians. This has implications for current plans to extend residency training programs.

Measuring nursing movements using real time tracking data at the Royal Wolverhampton Hospital Trust.

BACKGROUND: Real time location systems (RTLS) are increasingly used in healthcare with applications that include contract tracing and staffing. However, their potential to provide organizational insights requires staff compliance with the system. MATERIALS AND METHODS: Our goal is to assess how many nurses are using the RTLS correctly (i.e. complying to the system). We collect RTLS data on the movements of nurses at the Royal Wolverhampton NHS Trust. We identify the number of RTLS active nurses and compare it to what expected from the nurses' rotas. RESULTS: We find that a significant number of nurses appear not to be active from the RTLS data. For approximately 15% of the active users, RTLS records below 10 movements per day. Nevertheless, most of the active users have daily RTLS times consistent with the average shift length. CONCLUSION: Applications of RTLS data may need to account for imperfect compliance of staff to the system.

The feasibility and validity of using a real time location system (RTLS) to measure bedside contact time.

Background: The association between the nurse-to-patient ratio and patient outcomes has been extensively investigated. Real time location systems have the potential capability of measuring the actual amount of bedside contact patients receive. Aims: This study aimed to determine the feasibility and accuracy of real time location systems as a measure of the amount of contact time that nurses spent in the patients' bed space. Methods: An exploratory, observational, feasibility study was designed to compare the accuracy of data collection between manual observation performed by a researcher and real time location systems data capture capability. Four nurses participated in the study, which took place in 2019 on two hospital wards. They were observed by a researcher while carrying out their work activities for a total of 230 minutes. The amount of time the nurses spent in the patients' bed space was recorded in 10-minute blocks of time and the real time location systems data were extracted for the same nurse at the time of observation. Data were then analysed for the level of agreement between the observed and the real time location systems measured data, descriptively and graphically using a kernel density and a scatter plot. Results: The difference (in minutes) between researcher observed and real time location systems measured data for the 23, 10-minute observation blocks ranged from zero (complete agreement) to 5 minutes. The mean difference between the researcher observed and real time location systems time in the patients' bed space was one minute (10% of the time). On average, real time location systems measured time in the bed space was longer than the researcher observed time. Conclusions: There were good levels of agreement between researcher observation and real time location systems data of the time nurses spend at the bedside. This study confirms that it is feasible to use real time location systems as an accurate measure of the amount of time nurses spend at the patients' bedside.

How Are Patient Order and Shift Timing Associated with Imaging Choices in the Emergency Department? Evidence From Niagara Health Administrative Data.

STUDY OBJECTIVE: We assessed whether the timing and order of patients over emergency shifts are associated with receiving diagnostic imaging in the emergency department and characterized whether changes in imaging are associated with changes in patients returning to the ED. METHODS: In this retrospective study, we used multivariate and instrumental variable regressions to examine how the timing and order of patients are associated with the use of diagnostic imaging. Outcomes include whether a patient receives a radiograph, a computed tomography (CT) scan, an ultrasound, and 7-day bouncebacks to the ED. The variables of interest are time and order during a physician's shift in which a patient is seen. RESULTS: A total of 841,683 ED visits were examined from an administrative database of all ED visits to Niagara Health. Relative to the first patient, the probability of receiving a radiograph, CT, and ultrasound decreases by 6.4%, 9.1%, and 3.8% if a patient is the 15th patient seen during a shift. Relative to the first minute, the probability of receiving a radiograph, CT, or ultrasound increases by 1.9%, 2.7%, and 1.1% if a patient is seen in the 180th minute. Seven-day bounceback rates are not consistently associated with patient order or timing in a shift and imaging orders. CONCLUSION: Imaging in the ED is associated with shift length and especially patient order, suggesting that physicians make different imaging decisions over the course of their shifts. Additional imaging does not translate into reductions in subsequent bouncebacks to the hospital.

A Population-Based Susceptible, Infected, Recovered Simulation Model of the Spread of Influenza-Like-Illness in the Homeless versus Non-Homeless Population.

PURPOSE: To examine the prevalence and characteristics of influenza-like illness (ILI) related presentations among people experiencing homelessness compared to the general population as well as to use the Susceptible, Infected, Recovered (SIR) simulation model parameters ß and γ to model infectious interactivity, recovery rate, and population-level basic reproduction number (R0). METHODS: Using administrative health data from emergency department (ED) visits in the province of Ontario, Canada from 2010 to 2017, an SIR model was used to calculate the R0 for ILI in both the general population and the population of homeless individuals. RESULTS: From 2010 to 2017, a total of 17,056 homeless and 85,553 non-homeless individuals presented with an ILI to an ED in Ontario. The estimated infectious interactivity (ß) was lower while the recovery rate (γ) was longer for infected people experiencing homelessness. CONCLUSIONS: Our results suggest that infections of ILI will result in more secondary cases in the homeless population compared to the homed population. This evaluation of the dynamics of ILI spread in the homeless population provides insight into how illnesses such as COVID-19 may be much more infectious in this population compared to the homed population.

Exploring Changes in Patient Safety Incidents During the COVID-19 Pandemic in a Canadian Regional Hospital System: A Retrospective Time Series Analysis.

OBJECTIVES: The COVID-19 pandemic has placed unprecedented strain on healthcare systems and may have consequential impacts on patient safety incidents (PSIs). The primary objective of this study was to examine the impact of the COVID-19 pandemic on PSIs reported in Niagara Health. METHODS: Flexible Farrington models were used to retrospectively detect weeks from January to September 2020 where PSI counts were significantly above expected counts. Incident counts were adjusted to weekly inpatient-days. Outcomes included overall incident numbers, incidents by category, and incidents by ward type. RESULTS: The overall number of PSIs across Niagara Health did not increase during the first wave of the COVID-19 pandemic. However, significant increases in falls were observed, suggesting that other types of incidents decreased. Falls increased by 75% from February to March 2020, coinciding with the onset of the first wave of the pandemic. Further investigation by unit type revealed that the number of falls increased specifically on internal medicine and complex continuing care wards. CONCLUSIONS: Despite no observed changes in overall number, significant composition shifts in PSIs occurred during the first wave of the COVID-19 pandemic, with increased falls on internal medicine and complex continuing care wards. Possible explanations include restrictions on patient visitation, reduced patient contact/supervision, and/or personal protective equipment requirements. Providers should maintain a particularly high vigilance for patient falls during pandemic outbreaks, and hospitals should consider targeting resources to higher-risk locations. The results of this study reinforce the need for ongoing pandemic PSI monitoring and rapidly adaptive responses to new patient safety concerns.

Do Patients Respond to Posted Emergency Department Wait Times: Time-Series Evidence From the Implementation of a Wait Time Publication System in Hamilton, Canada.

STUDY OBJECTIVE: One proposed solution to prolonged emergency department (ED) wait times is a publicly available website that displays estimated ED wait times. This could provide information to patients so that they may choose sites with low wait times, which has the potential to smooth the overall wait times in EDs across a health system. We describe the effect of a novel city-wide ED wait time website on patient volume distributions throughout the city of Hamilton, Ontario, Canada. METHODS: We compared the number of new patients arriving every 15 minutes during 2 separate time periods-before and after a publicly viewable wait time website was made available. For each ED site, the effect of the posted wait time was measured by assessing its association with the total number of patient arrivals in the subsequent hour at the same site and at all other sites in Hamilton. RESULTS: Linear models showed clinically modest changes in patient volumes when wait times changed. However, nonlinear models showed that a 60-minute increase in wait time at a site was associated with 10% fewer patients presenting over the next hour. Larger negative associations were observed at community hospitals and urgent care centers. Increases in wait times at a given site were also associated with increased patient volumes at other sites in the system. CONCLUSION: After the implementation of a public wait time website, elevated wait times led to fewer patients at the same site but more patient visits at other sites. This may be consistent with the wait time tracker inducing patients to avoid sites with high wait times and instead visit alternate sites in Hamilton, but only when wait times were very high.

Hard-to-Reach Populations and Administrative Health Data: A Serial Cross-sectional Study and Application of Data to Improve Interventions for People Experiencing Homelessness.

BACKGROUND: Intervention studies with vulnerable groups in the emergency department (ED) suffer from lower quality and an absence of administrative health data. We used administrative health data to identify and describe people experiencing homelessness who access EDs, characterize patterns of ED use relative to the general population, and apply findings to inform the design of a peer support program. METHODS: We conducted a serial cross-sectional study using administrative health data to examine ED use by people experiencing homelessness and nonhomeless individuals in the Niagara region of Ontario, Canada from April 1, 2010 to March 31, 2018. Outcomes included number of visits; unique patients; group proportions of Canadian Triage and Acuity Scale (CTAS) scores; time spent in emergency; and time to see an MD. Descriptive statistics were generated with t tests for point estimates and a Mann-Whitney U test for distributional measures. RESULTS: We included 1,486,699 ED visits. The number of unique people experiencing homelessness ranged from 91 in 2010 to 344 in 2017, trending higher over the study period compared with nonhomeless patients. Rate of visits increased from 1.7 to 2.8 per person. People experiencing homelessness presented later with higher overall acuity compared with the general population. Time in the ED and time to see an MD were greater among people experiencing homelessness. CONCLUSIONS: People experiencing homelessness demonstrate increasing visits, worse health, and longer time in the ED when compared with the general population, which may be a burden on both patients and the health care system.

Characterizing people experiencing homelessness and trends in homelessness using population-level emergency department visit data in Ontario, Canada.

BACKGROUND: Data on people experiencing homelessness often come from time- and labour-intensive cross-sectional counts and surveys from selected samples. This study uses comprehensive administrative health data from emergency department (ED) visits to enumerate people experiencing homelessness and characterize demographic and geographic trends in the province of Ontario, Canada, from 2010 to 2017. DATA AND METHODS: People experiencing homelessness were identified by their postal code, designated as "XX." Outcomes included the number of people experiencing homelessness stratified by year and week, gender and age plotted annually, the location of each ED visit, and composition changes in demographics and geographic distribution. RESULTS: Over seven years, 39,408 individuals were identified as experiencing homelessness. The number of ED visits increased over the study period in all of Ontario. The average peak in the number of visits occurred annually in September, with the fewest visits in January. Rises in overall homelessness were secondary to increases in working-age homelessness. ED presentations were concentrated in urban centres. The total proportion of patients experiencing homelessness became less concentrated in Toronto, decreasing from 60% to 40% over the study period, with a shift toward EDs outside the city. DISCUSSION: This study shows that administrative health data can provide comprehensive information on demographics and other characteristics analyzed over time. Surveillance can be conducted cost-effectively, and changes can be tracked in real time to allow for services to be coordinated and implemented in a time-sensitive manner.

Is herpes zoster vaccination likely to be cost-effective in Canada?

OBJECTIVES: To synthesize the current literature detailing the cost-effectiveness of the herpes zoster (HZ) vaccine, and to provide Canadian policy-makers with cost-effectiveness measurements in a Canadian context. METHODS: This article builds on an existing systematic review of the HZ vaccine that offers a quality assessment of 11 recent articles. We first replicated this study, and then two assessors reviewed the articles and extracted information on vaccine effectiveness, cost of HZ, other modelling assumptions and QALY estimates. Then we transformed the results into a format useful for Canadian policy decisions. Results expressed in different currencies from different years were converted into 2012 Canadian dollars using Bank of Canada exchange rates and a Consumer Price Index deflator. Modelling assumptions that varied between studies were synthesized. We tabled the results for comparability. SYNTHESIS: The Szucs systematic review presented a thorough methodological assessment of the relevant literature. However, the various studies presented results in a variety of currencies, and based their analyses on disparate methodological assumptions. Most of the current literature uses Markov chain models to estimate HZ prevalence. Cost assumptions, discount rate assumptions, assumptions about vaccine efficacy and waning and epidemiological assumptions drove variation in the outcomes. This article transforms the results into a table easily understood by policy-makers. CONCLUSION: The majority of the current literature shows that HZ vaccination is cost-effective at the price of $100,000 per QALY. Few studies showed that vaccination cost-effectiveness was higher than this threshold, and only under conservative assumptions. Cost-effectiveness was sensitive to vaccine price and discount rate.