Administrative burden in primary care
Bibliographic record
Abstract
OBJECTIVE: Administrative burden contributes to the current primary care crisis. This critical review of the literature explores how primary care administrative burden is discussed, including how it is defined and what drivers and solutions have been identified. DATA SOURCES: A systematic search of MEDLINE and CINAHL electronic databases for peer-reviewed original research articles, literature reviews, and commentaries that discuss administrative burden in the context of primary care or primary health care. STUDY SELECTION: Searches identified 321 articles in MEDLINE and 109 in CINAHL, resulting in a total of 351 articles after duplicates were removed. Based on title and abstract screening, 228 articles were retained for full-text screening; 136 were ultimately included in the analysis. SYNTHESIS: Most articles focused on perspectives of physicians (72.8%), followed by those of other primary care clinicians (14.7%) and patients (12.5%). Few articles explicitly defined administrative burden (n=6), although most illustrated the concept with examples. One relevant definition of administrative burden distinguishes compliance, learning, and psychological costs. This definition was proposed in the context of people interacting with bureaucracies generally, but these categories are also relevant to primary care specifically. Primary care administrative burdens most often included compliance costs (forms and information management), but learning costs (finding information, navigating processes, and adapting to and implementing new technology) and psychological costs (stress and burnout) were also discussed in the literature. Identified drivers of administrative burden included health system requirements, technological tools available to do administrative work, and complexity of patients or patient populations. Technology and task shifting were discussed as both drivers of administrative burden and solutions to administrative workload. CONCLUSION: Examples of administrative burden in primary care underscore that this work often supports central functions of continuity and coordination of care. Attention often focuses on compliance costs, but learning costs (eg, finding information and learning new technology) and psychological costs must not be overlooked. That technology and task shifting can function as both drivers of and solutions to administrative burden highlights why this issue is challenging to address. Solutions should consider costs broadly and evaluate implications from multiple perspectives, including those of patients and caregivers.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".