Primary care is usually the first point of contact for patients with the health system. This makes it ideal for detecting the first clinical or even sub-clinical effects of ambient temperatures and an excellent place for prevention and intervention in many cases.
This is a time-stratified case-crossover study that uses aggregated healthcare data from Clalit health systems and regional daily environmental data. This advanced study design was recently used to analyze associations between temperature and various aggregate outcomes, as it combines advantages from the two traditional methods of time series analyses and individual-level case-crossover studies. In short, this design uses the daily variability of the absolute incidence of the selected outcome (e.g., number of visits) and the relevant exposure to examine the associations between them. The study period is stratified into non-overlapping strata, defined as week-of-day, within-month, and year. Each calendar day during the study period is compared to all other days in its stratum so that weekday, season, and time trends are controlled as part of the study design. Another advantage of this design is its ability to ignore days without any events, making it useful also for less common outcomes. For non-event data, such as numeric lab results, statistical measures of their daily distribution will be analyzed instead of count data, as described below.
This analytic approach uses the entire population’s data without requiring informed consent or active cooperation from patients. Moreover, this design is not susceptible to confounding by individual characteristics. Using aggregate data simplifies privacy issues and eases institutional review board (IRB) permissions and data extraction processes. It also minimizes research costs since the data used is already collected routinely. Ethical permission will be sought from Clalit.