ArticlePatient safety in surgery2022
Patient safety assurance in the age of defensive medicine: a review.
Article in Patient safety in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Confronting medical grifting: Fraudulent and unproven products and interventions in apheresis, transfusion and biotherapies.British journal of haematology · 2025Review
- The experience of an innovative interdisciplinary model of primary care delivery in changing organizational dynamics: a grounded theory study.Primary health care research & development · 2025Article
- Low-value practices in primary care: a cross-sectional study comparing data between males and females in Spain.BMJ open · 2024Observational
- Delayed intestinal obstruction from an unintentionally retained surgical gauze in a 24-year old woman two years after caesarean section: a case report.Patient safety in surgery · 2023Article
- COVID-19 pandemic: ethical issues and recommendations for emergency triage.Frontiers in public health · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The definition of defensive medicine has evolved over time given various permutations and combinations. The underlying meaning, however, has persisted in its relevance towards two classifications, positive and negative defensive medicine. Positive defensive medicine is specific to overutilization, excessive testing, over-diagnosing, and overtreatment. Negative defensive medicine, on the contrary, is specific to avoiding, referring, or transferring high risk patients. Given the above bifurcation, the present research analyzes defensive medicine in the landscape of medical errors. In its specificity to medical errors, we consider the cognitive taxonomies of medical errors contextual to execution and evaluation slips and mistakes. We, thereafter, illustrate how the above taxonomy interclasps with five classifications of medical errors. These classifications are those that involve medical errors of operative, drug-related, diagnostic, procedure-related, and other types. This analytical review illustrates the nodular frameworks of defensive medicine. As furtherance of our analysis, this review deciphers the above nodular interconnectedness to these error taxonomies in a cascading stepwise sequential manner. This paper was designed to elaborate and to stress repeatedly that practicing defensive medicine entails onerous implications to physicians, administrators, the healthcare system, and to patients. Practicing defensive medicine, thereby, is far from adhering to those optimal healthcare practices that support quality of care metrics/milestones, and patient safety measures. As an independent standalone concept, defensive medicine is observed to align with the taxonomies of medical errors based on this paper's diagrammatic and analytical inference.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.