Pandemic impacts on healthcare utilisation: a systematic review
Bibliographic record
Abstract
Abstract Objectives To determine the extent and nature of changes in utilisation of healthcare services during COVID-19 pandemic. Design Systematic review Eligibility Eligible studies compared utilisation of services during COVID-19 pandemic to at least one comparable period in prior years. Services included visits, admissions, diagnostics, and therapeutics. Studies were excluded if from single-centres or studied only COVID-19 patients. Data sources PubMed, Embase, Cochrane COVID-19 Study Register, and pre-prints were searched, without language restrictions, until August 10, using detailed searches with key concepts including COVID-19, health services and impact. Data analysis Risk of bias was assessed by adapting ROBINS-I and Cochrane Effective Practice and Organization of Care tool. Results were analysed using descriptive statistics, graphical figures, and narrative synthesis. Outcome measures Primary outcome was change in service utilisation between pre-pandemic and pandemic periods. Secondary outcome was the change in proportions of users of healthcare services with milder or more severe illness (e.g. triage scores). Results 3097 unique references were identified, and 81 studies across 20 countries included, reporting on >11 million services pre-pandemic and 6.9 million during pandemic. For the primary outcome, there were 143 estimates of changes, with a median 37% reduction in services overall (interquartile range −51% to −20%), comprising median reductions for visits of 42%(−53% to −32%), admissions, 28%(−40% to −17%), diagnostics, 31%(−53% to −24%), and for therapeutics, 30%(−57% to −19%). Among 35 studies reporting secondary outcomes, there were 60 estimates, with 27(45%) reporting larger reductions in utilisation among people with a milder spectrum of illness, and 33 (55%) reporting no change. Conclusions Healthcare utilisation decreased by about a third during the pandemic, with considerable variation, and with greater reductions among people with less severe illness. While addressing unmet need remains a priority, studies of health impacts of reductions may help health-systems prioritise higher-value care in the post-pandemic recovery. Funding, Study registration No funding was required. PROSPERO: CRD42020203729 Strengths and limitations of this study – The review is the first broad synthesis of global studies of pandemic related changes in utilisation across all categories of healthcare services. – The review provides novel findings informing design of future studies of pandemic-related changes in utilisation and its impacts. – Limitations include the possibility of publication bias and the potential of our eligibility criteria to exclude important data sources such as studies in single-centres and unpublished datasets from health systems. – Heterogenous designs and settings precluding meta-analysis.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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".