Treated versus self-reported prevalence of chronic pain and costs of patients’ health services utilization: a population-based study of health administrative databases
Bibliographic record
Abstract
ObjectivesTo compare treated to self-reported prevalence of chronic pain (CP) and to estimate health services utilization (HSU) costs of patients treated for CP in Alberta, Canada.MethodsPatients treated for CP were identified by the physician billing codes of health services for CP from the practitioner claims database in fiscal year 2021/22. The treated prevalence of CP (number of these patients divided by the population) was compared to the self-reported prevalence of CP previously estimated (doi:10.1371/journal.pone.0272638). Costs of patients’ HSU included costs for general practitioner (GP), specialist, inpatient, emergency department, outpatient clinic services, and prescription drugs.ResultsThe treated prevalence of CP was 6.0% (4.4% among males and 7.8% among females) which was 30% to 41% of the self-reported prevalence. The highest treated prevalence (7.2%) was found in the age group of 18–64 years, followed by age groups of >64 years (7.0%) and <18 years (2.1%). The average cost per patient per year was $5096 ($5878 for males and $4652 for females), of which hospitalizations accounted for 65.0%, outpatient clinic visits 16.4%, ED visits 9.5%, prescription drugs 4.7%, GP visits 3.9%, and specialist visits 0.4%. The total cost of patients with CP for the health system was $1.37 billion (∼7% of total health expenditure), of which males accounted for 41.7% and females for 58.3%.DiscussionOur findings suggest that the economic burden of CP is considerable and that many people with self-reported CP do not use the public healthcare services. This can be multifactorial, including lack of availability and accessibility of publicly funded services, people’s lack of awareness of available services, lower utilization due to COVID-19 pandemic, and reliance on self-management, private services, and alternative treatments. Further studies are warranted to inform future policies and health system initiatives aiming to reduce the burden of CP and improve lives of people living with it.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".