The epidemiology and healthcare costs of community-acquired pneumonia in Ontario, Canada: a population-based cohort study
Bibliographic record
Abstract
The aim of the present study was to determine incidence-based short- and long-term healthcare costs attributable to community-acquired pneumonia (CAP) from the healthcare payer perspective in Ontario, Canada. We conducted a retrospective population-based matched cohort study of residents in Ontario, Canada using health administrative data. We identified subjects with an incident episode of CAP (exposed subjects) between 1 January 2012 and 31 December 2014. The index date of each episode was based on the first inpatient or outpatient claim for pneumonia. Exposed subjects were matched without replacement to unexposed subjects from the general population using hard and propensity score matching on age, sex, income quintile, rural residence, comorbidities, and healthcare costs prior to index date. Attributable costs represented the mean difference in costs between the exposed subjects and their matched pairs. We identified 692,090 subjects with at least one episode of CAP between 1 January 2012 and 31 December 2014. Adults aged 65 years and older had the highest annual incidence rate of 50.1 episodes per 1,000 person-years, while adults aged 18–64 years and children (aged 0–17) had incidence rates of 12.9 and 24.7 episodes per 1,000 person-years, respectively. The majority of episodes involved care exclusively in the outpatient setting (92.6%), with most of these episodes involving a single physician visit. The mean attributable costs were $1,595 (95% CI: $1,572–$1,616) per outpatient CAP episode and $12,576 (95% CI: $12.392–$12,761) per inpatient CAP episode. Attributable costs were significantly higher for adult subjects and those with time spent in the intensive care unit. Alternative case definitions yielded different results, although demonstrated the same overall trends across groups. CAP is associated with substantially increased acute and long-term healthcare costs compared to unexposed subjects. This study highlights the burden of CAP in both the inpatient and outpatient setting, and will serve to inform strategic healthcare planning for future interventions and healthcare programs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".