Prevalence, severity, and nature of preventable patient harm across medical care settings: systematic review and meta-analysis
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Objective: To systematically quantify the prevalence, severity, and nature of preventable patient harm across a range of medical settings globally. Design: Systematic review and meta-analysis. Data sources: Medline, PubMed, PsycINFO, Cinahl and Embase, WHOLIS, Google Scholar, and SIGLE from January 2000 to January 2019. The reference lists of eligible studies and other relevant systematic reviews were also searched. Review methods: Observational studies reporting preventable patient harm in medical care. The core outcomes were the prevalence, severity, and types of preventable patient harm reported as percentages and their 95% confidence intervals. Data extraction and critical appraisal were undertaken by two reviewers working independently. Random effects meta-analysis was employed followed by univariable and multivariable meta regression. Heterogeneity was quantified by using the I 2 statistic, and publication bias was evaluated. Results: Of the 7313 records identified, 70 studies involving 337 025 patients were included in the meta-analysis. The pooled prevalence for preventable patient harm was 6% (95% confidence interval 5% to 7%). A pooled proportion of 12% (9% to 15%) of preventable patient harm was severe or led to death. Incidents related to drugs (25%, 95% confidence interval 16% to 34%) and other treatments (24%, 21% to 30%) accounted for the largest proportion of preventable patient harm. Compared with general hospitals (where most evidence originated), preventable patient harm was more prevalent in advanced specialties (intensive care or surgery; regression coefficient b=0.07, 95% confidence interval 0.04 to 0.10). Conclusions: Around one in 20 patients are exposed to preventable harm in medical care. Although a focus on preventable patient harm has been encouraged by the international patient safety policy agenda, there are limited quality improvement practices specifically targeting incidents of preventable patient harm rather than overall patient harm (preventable and non-preventable). Developing and implementing evidence-based mitigation strategies specifically targeting preventable patient harm could lead to major service quality improvements in medical care which could also be more cost effective.
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Internationally, the pooled rate of hospital harm is 6% of patients across medical settings.
“Internationally, the pooled rate of hospital harm is 6% of patients across medical settings [36].”
From The hospital-to-home care transition experience of home care clients: an exploratory study using patient journey mapping (2023) · cites this paper as [36]
The Results report a pooled prevalence of 6% for preventable patient harm across medical care settings, not for all hospital harm. Table 1 gives 5% for preventable harm in hospitals specifically and 12% for overall harm across settings. (LLM, conf=0.90)
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Kennerly, D. A., Kudyakov, R., da Graca, B., Saldaña, M., Compton, J., Nicewander, D. A., & Gilder, R. E. (2014) · Health Services Research · doi:10.1111/1475-6773.12163 · Cited by 70 · see citing works
Hwang, J., Chin, H. J., & Chang, Y. (2013) · Journal of Evaluation in Clinical Practice · doi:10.1111/jep.12075 · Cited by 68 · see citing works
Lehmann, L. S., Puopolo, A. L., Shaykevich, S., & Brennan, T. A. (2005) · The American Journal of Medicine · doi:10.1016/j.amjmed.2005.01.012 · Cited by 68 · see citing works
Khalil, H., Bell, B., Chambers, H. P., et al. (2017) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd003942.pub3 · Cited by 67 · see citing works
Najjar, S., Hamdan, M., Euwema, M., et al. (2013) · International Journal for Quality in Health Care · doi:10.1093/intqhc/mzt066 · Cited by 62 · see citing works
Using prospective clinical surveillance to identify adverse events in hospital
Forster, A. J., Worthington, J. R., Hawken, S., Bourke, M., Rubens, F. D., Shojania, K., & van Walraven, C. (2011) · BMJ Quality & Safety · doi:10.1136/bmjqs.2010.048694 · Cited by 61 · see citing works
Preventable Adverse Events in Surgical Care in Sweden
Nilsson, L. M., Risberg, M. B., Montgomery, A. K., Sjödahl, R. I., Schildmeijer, K. G. I., & Rutberg, H. (2016) · Medicine · doi:10.1097/md.0000000000003047 · Cited by 59 · see citing works
Hignett, S. M., Lang, A. R., Pickup, L., Ives, C., Fray, M., McKeown, C., Tapley, S., Woodward, M., & Bowie, P. (2016) · Ergonomics · doi:10.1080/00140139.2016.1245446 · Cited by 58 · see citing works
Adverse events are common on the intensive care unit: results from a structured record review
Nilsson, L. M., Pihl, A., TÅGSJÖ, M., & Ericsson, E. (2012) · Acta Anaesthesiologica Scandinavica · doi:10.1111/j.1399-6576.2012.02711.x · Cited by 56 · see citing works
Advancing the research agenda for diagnostic error reduction
Zwaan, L., Schiff, G. D., & Singh, H. (2013) · BMJ Quality & Safety · doi:10.1136/bmjqs-2012-001624 · Cited by 56 · see citing works
Adverse events related to hospital care: a retrospective medical records review in a Swiss hospital
Halfon, P., Staines, A., & Burnand, B. (2017) · International Journal for Quality in Health Care · doi:10.1093/intqhc/mzx061 · Cited by 56 · see citing works
Adverse Events During Hospitalization: Results of a Patient Survey
Fowler, F. J., Epstein, A. M., Weingart, S. N., Annas, C. L., Bolcic‐Jankovic, D., Clarridge, B. R., Schneider, E. C., & Weissman, J. S. (2008) · The Joint Commission Journal on Quality and Patient Safety · doi:10.1016/s1553-7250(08)34073-2 · Cited by 50 · see citing works
Safer primary care for all: a global imperative
Sheikh, A., Panesar, S. S., Larizgoitia, I., Bates, D. W., & Donaldson, L. (2013) · The Lancet Global Health · doi:10.1016/s2214-109x(13)70030-5 · Cited by 50 · see citing works
Scale, nature, preventability and causes of adverse events in hospitalised older patients
Merten, H., Zegers, M., de Bruijne, M. C., & Wagner, C. (2012) · Age and Ageing · doi:10.1093/ageing/afs153 · Cited by 46 · see citing works
Nilsson, L. M., Risberg, M. B., Soop, M., Nylén, U., Ålenius, C., & Rutberg, H. (2018) · BMJ Open · doi:10.1136/bmjopen-2017-020833 · Cited by 44 · see citing works
Identifying and Addressing Preventable Process Errors in Trauma Care
Pucher, P., Aggarwal, R., Twaij, A., Batrick, N., Jenkins, M., & Darzi, A. (2013) · World Journal of Surgery · doi:10.1007/s00268-013-1917-9 · Cited by 42 · see citing works
Montserrat-Capella, D., Suarez, M. L. B., Ortíz, L., et al. (2015) · International Journal for Quality in Health Care · doi:10.1093/intqhc/mzu100 · Cited by 41 · see citing works
Detection of Adverse Events in a Scottish Hospital Using a Consensus-based Methodology
Williams, D. J., Olsen, S., Crichton, W., et al. (2008) · Scottish Medical Journal · doi:10.1258/rsmsmj.53.4.26 · Cited by 40 · see citing works
Suárez, C., Menéndez, M., Alonso, J., et al. (2014) · Journal of the American Geriatrics Society · doi:10.1111/jgs.12774 · Cited by 39 · see citing works
Citation classics in patient safety research: an invitation to contribute to an online bibliography
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Healthy Life-Years Lost and Excess Bed-Days Due to 6 Patient Safety Incidents
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Lipitz‐Snyderman, A., Pfister, D. G., Classen, D. C., Atoria, C. L., Killen, A. R., Epstein, A. S., Anderson, C. B., Fortier, E., & Weingart, S. N. (2017) · Cancer · doi:10.1002/cncr.30916 · Cited by 31 · see citing works
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The association between patient-reported incidents in hospitals and estimated rates of patient harm
Bjertnæs, Ø. A., Deilkas, E. T., Skudal, K. E., et al. (2014) · International Journal for Quality in Health Care · doi:10.1093/intqhc/mzu087 · Cited by 27 · see citing works
Patient safety and adverse events related with obstetric care
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The Ottawa Hospital Quality Incident Notification System for Capturing Adverse Events in Obstetrics
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Experience in adverse events detection in an emergency department: Incidence and outcome of events
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Frequency and Correlates of Adverse Events in a Respiratory Diseases Hospital in Mexico City
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The Incidence, Nature and Consequences of Adverse Events in Iranian Hospitals.
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Phipps, D. L., Jones, C. E. L., Parker, D., et al. (2018) · BMC Health Services Research · doi:10.1186/s12913-018-3607-7 · Cited by 12 · see citing works
Self-citationJob characteristics, well-being and risky behaviour amongst pharmacists
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Flagged first, then by citations
Research works printed but not linked: 1
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Cited by
Sorted by citations
Adverse Events in Hospitalized Pediatric Patients
Stockwell, D. C., Landrigan, C. P., Toomey, S. L., Loren, S. S., Jang, J., Quinn, J. A., Ashrafzadeh, S., Wang, M. J., Wu, M., Sharek, P. J., et al. (2018) · Pediatrics · doi:10.1542/peds.2017-3360 · Cited by 107 · see citing works
Saragosa, M., Nizzer, S., McKay, S., & Kuluski, K. (2023) · BMC Health Services Research · doi:10.1186/s12913-023-09899-2 · Cited by 31 · see citing works
“Interna-tionally, the pooled rate of hospital harm is 6% of patients across medical settings [36].”
BackgroundBrimhall, K. C., Tsai, C.-Y., Eckardt, R., Dionne, S., Yang, B., & Sharp, A. (2023) · Health Care Management Review · doi:10.1097/hmr.0000000000000358 · Cited by 22 · see citing works
Detecting clinical medication errors with AI enabled wearable cameras
Chan, J., Nsumba, S., Wortsman, M., Dave, A., Schmidt, L., Gollakota, S., & Michaelsen, K. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01295-2 · Cited by 18 · see citing works
Improving medication error classification using a reasoning large language model
Krifors, A., Beskow, T., Jonsson, M., Lindner, K.-J., Calås, J., Arwsbo, V., Sandström, K., & Norström, C. (2026) · JAMIA Open · doi:10.1093/jamiaopen/ooag004 · Cited by 5 · see citing works
Introduction to Drug Safety and Pharmacovigilance
Jose, J., Cox, A. R., & Bate, A. (2024) · Principles and Practice of Pharmacovigilance and Drug Safety · doi:10.1007/978-3-031-51089-2_1 · Cited by 3 · see citing works
- Authors
- Panagioti, M., Khan, K., Keers, R. N., Abuzour, A., Phipps, D., Kontopantelis, E., Bower, P., Campbell, S., Haneef, R., Avery, A. J., & Ashcroft, D. M.
- Affiliations
- University of Manchester (GB)
- Lancashire Teaching Hospitals NHS Foundation Trust (GB)
- University of Nottingham (GB)
- Corresponding author
- Panagioti, Maria
- ORCID
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2019-07-17
- Volume
- 366
- Pages
- l4185
- ISSN
- 1756-1833 (ISSN-L)
- 0959-8138
- PMC
- PMC6939648
- OpenAlex
- W2958795513
- Cited by
- 874
- References
- 129
- Citations by year
- 2026: 116 · 2025: 158 · 2024: 155 · 2023: 137 · 2022: 99 · 2021: 114 · 2020: 81 · 2019: 12 · 2018: 1
- FWCI
- 19.97
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- BMJ (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Repository@Nottingham (University of Nottingham) (publishedVersion, cc-by-nc)
- Research Explorer (The University of Manchester) (publishedVersion, cc-by-nc)
- Repository@Nottingham (University of Nottingham) (submittedVersion, cc-by-nc)
- Uppsala University Publications (Uppsala University) (submittedVersion, other-oa)
- HighWire Press Open Archive (submittedVersion)
- Funders
- National Institute for Health and Care Research (GMPSTRC-2012-1)
- NIHR Greater Manchester Patient Safety Translational Research Centre (GMPSTRC-2012-1)
- NIHR School for Primary Care Research
- Topics
- Health Sciences › Health Professions › Emergency Medical Services › Patient Safety and Medication Errors
- Health Sciences › Health Professions › Pharmacy › Medical Malpractice and Liability Issues
- Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
- Keywords
- preventable patient harm, patient safety, medical errors, drug-related harm, harm severity, hospital care, intensive care, surgical care, quality of care
- MeSH terms
- Cross-Sectional Studies, Humans, Retrospective Studies, Severity of Illness Index, Prevalence, Evidence-Based Practice, Quality Improvement, Patient Safety, Patient Harm, Observational Studies as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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