Evaluating medical students’ ability to identify and report errors: finding gaps in patient safety education

Figures & data

Table 1. Basic characteristics of medical errors reported by students

	Categories	Frequency (%)
Subject making the medical error	Other(s)	644 (67.6%)
	Intern(s)/Resident(s)	171 (26.6%)
	Health professional(s)*	166 (25.8%)
	Attending staff	109 (16.9%)
	Nurse(s)/Paramedical(s)	99 (15.4%)
	Patient(s)/Family(ies)	84 (13.0%)
	Teammate(s)	33 (5.1%)
	Hospital worker(s)	14 (2.2%)
	Others	8 (1.2%)
	N/A	18 (2.8%)
	Myself	248 (26.1%)
	Myself and	60 (6.3%)
	Teammate(s)	26 (43.3%)
	Intern(s)/Resident(s)	23 (38.3%)
	Attending staff	15 (25.0%)
	Nurse(s)/Paramedical(s)	7 (11.7%)
	Health professional(s)*	6 (10.0%)
	Patient(s)/Family(ies)	3 (5.0%)
Place where the error occurred^†	Ward	385 (40.4%)
	Out-patient clinic	144 (15.1%)
	Operating room	113 (11.9%)
`	Emergency room	84 (8.8%)
	Intensive care unit	54 (5.7%)
	Delivery room	7 (0.7%)
	Laboratory/Procedure room	3 (0.3%)
	Others	79 (8.3%)
	N/A	91 (9.6%)

Abbreviations: N/A = not available.

Notes: *If the report documented that the error was made by some other health professionals but did not specify their working position in the hospital, we included them in this category.^†Several reports described more than one subject who committed the error or the place where the error occurred. Therefore, the total number of each category may exceed that of the reports, which is 952.

Table 2. Types of errors reported by students*

Error types		Total (n = 952)	Myself involved (n = 308)	Others (n = 644)	p value^†
Infection related errors*		176 (18.5%)	69 (22.4%)	107 (16.6%)	p = 0.031
Hand washing/sanitizing		101 (57.4%)	45 (65.2%)	56 (52.3%)
Wearing protective equipment		60 (34.1%)	23 (33.3%)	37 (34.6%)
Discarding biohazard waste		11 (6.3%)	1 (1.4%)	10 (9.3%)
Others		20 (11.4%)	8 (11.6%)	12 (11.2%)
Sterilisation of personal equipment		11 (55.0%)	6 (75.0%)	5 (41.7%)
In-hospital infection		4 (20.0%)	0 (0%)	4 (33.3%)
Contamination events at ward		3 (15.0%)	0 (0%)	3 (25.0%)
Cleaning doctor’s gown		2 (10.0%)	2 (25%)	0 (0%)
Errors in invasive procedures*		192 (20.2%)	72 (23.3%)	120 (18.6%)	p = 0.088
Wrong patient, wrong site		60 (31.3%)	22 (30.6%)	38 (31.7%)
Violation of aseptic procedures		58 (30.2%)	39 (54.2%)	19 (15.8%)
Procedure-related complications		19 (9.9%)	2 (2.8%)	17 (14.2%)
Others		56 (29.2%)	10 (13.9%)	46 (38.3%)
Procedure failure		20 (35.7%)	4 (40.0%)	16 (34.8%)
Errors during the procedure		10 (17.9%)	0 (0%)	10 (21.7%)
Delayed operation		9 (16.1%)	1 (10.0%)	8 (17.4%)
Injury to health workers		5 (8.9%)	0 (0%)	5 (10.9%)
Wrong gauze count		4 (7.1%)	1 (10.0%)	3 (6.5%)
Improper skills		3 (5.4%)	2 (20.0%)	1 (2.2%)
Improper preparation		2 (3.6%)	0 (0%)	2 (4.4%)
Failed anesthesia		2 (3.6%)	0 (0%)	2 (4.4%)
Unsafe environment		2 (3.6%)	2 (20.0%)	0 (0%)
Medication error*		74 (7.8%)	1 (0.3%)	73 (11.3%)	p < 0.001^¶
In prescription		42 (56.8%)	1 (100%)	41(56.2%)
In giving medication		27 (36.5%)	0 (0%)	27 (37.0%)
In monitoring		5 (6.8%)	0 (0%)	5 (6.8%)
Others		1 (1.4%)	0 (0%)	1 (1.4%)
Errors in engaging with patients		328 (34.5%)	100 (32.5%)	228 (35.4%)	p = 0.372
Patient care and management^‡	97 (29.6%)		19 (19.0%)	78 (34.2%)
Informed consent	60 (18.3%)		24 (24.0%)	36 (15.8%)
Spills of patient information	57 (17.4%)		26 (26.0%)	31 (13.6%)
Treatment non-compliance	55 (16.8%)		4 (4.0%)	51 (22.4%)
Miscommunication	27 (8.2%)		16 (16.0%)	11 (4.8%)
Not protecting patient privacy	13 (3.9%)		6 (6.0%)	7 (3.1%)
Others	19 (5.8%)		5 (5.0%)	14 (6.1%)
Others	196 (20.6%)		68 (22.1%)	128 (19.9%)	p = 0.432
Delayed process	50 (25.5%)		12 (17.6%)	38 (29.7%)
Errors in the treatment process	22 (11.2%)		7 (10.3%)	15 (11.7%)
Errors in medical recording	21 (10.7%)		12 (17.6%)	9 (7.0%)
Errors in teamwork	21 (10.7%)		8 (11.8%)	13 (10.2%)
Error in diagnosis	13 (6.6%)		8 (11.8%)	5 (3.9%)
Safety error in a hospital facility	12 (6.1%)		3 (4.4%)	9 (7.0%)
Fall-related injury	11 (5.6%)		0 (0%)	11 (8.6%)
Errors in team communication	9 (4.6%)		4 (5.9%)	5 (3.9%)
Errors in patient isolation	7 (3.6%)		0 (0%)	7 (5.5%)
Restrain injury	5 (2.6%)		2 (3.0%)	3 (2.3%)
Providing wrong information to the patient	5 (2.6%)		0 (0%)	5 (3.9%)
Unnecessary examinations	5 (2.6%)		0 (0%)	5 (3.9%)
Transfusion error	1 (0.5%)		0 (0%)	1 (0.8%)
Needlestick injury	1 (0.5%)		0 (0%)	1 (0.8%)
Others	13 (6.6%)		6 (8.9%)	7 (5.5%)

*Several reports were documenting two or more types of error. Therefore, the sum of sub-categories exceeded each category’s total number of reports and error counts.^†Statistical analyses by Chi-square test.^‡This included every situation where patient complained, regardless of who contributed to their misunderstanding or how it started.^¶Statistical analysis by Fisher’s exact test.

Table 3. Root cause analyses of reported errors by students

Variables	Total (n = 952)	Myself involved (n = 308)	Others (n = 644)	p-value*
Quality of root causes presented				p < 0.001^‡
Non-systematic, unorganised, irrelevant, less than 3 causes presented	208 (21.8%)	45 (14.6%)	163 (25.3%)
Unorganised, but more than 3 causes presented	25 (2.7%)	10 (3.2%)	15 (2.3%)
Systematic, classifiable causes, less than 3 causes presented	223 (23.4%)	89 (28.9%)	134 (20.8%)
Systematic, well-classified, relevant, more than 3 causes presented	496 (52.1%)	164 (53.2%)	332 (51.6%)
Blaming tendency
Blaming the individual committing the error	148 (15.5%)	13 (4.2%)	135 (20.9%)	p < 0.001
Considering system failure	740 (77.7%)	214 (69.5%)	526 (81.7%)	p < 0.001
Types of root causes presented in reports^†
Rules	764 (80.3%)	240 (77.9%)	524 (81.4%)	p = 0.212
Fatigue, scheduling, and training	735 (77.2%)	267 (86.7%)	468 (72.7%)	p < 0.001
Communication	653 (68.6%)	159 (51.6%)	494 (76.7%)	p < 0.001
Safeguard, environment, and equipment	51 (5.4%)	10 (3.2%)	41 (6.4%)	p = 0.046
Information technology	42 (4.4%)	11 (3.6%)	31 (4.8%)	p = 0.334
Others	28 (2.9%)	12 (3.9%)	16 (2.5%)	p = 0.228

*Statistical analyses by Chi-square test.^†Classification of root causes was performed according to the VA National Center for Patient Safety RCA tools. Each report included more than one root cause. Therefore, the total count of root causes exceeded the total number of reports (n = 952).^‡In the statistical analysis, the quality of the suggestions was sorted into two categories: non-systematic unorganised and systematic, classified causes, and then compared using the Chi-square test.

Table 4. Students’ improvement plans for behavioural changes

Variables	Total (n = 952)	Myself involved (n = 308)	Others (n = 644)	p-value*
Quality of the suggestion Non-systematic, unorganised, irrelevant, less than 3 suggestions presented Unorganised, but more than 3 suggestions presented Systematic, classifiable causes, less than 3 suggestions presented Systematic, well-classified, relevant, specific, more than 3 suggestions presented, motivated Categories of suggested plans	412 (43.3%) 365 (38.3%) 31 (3.3%) 144 (15.1%)	124 (40.3%) 161 (52.3%) 3 (0.9%) 20 (6.5%)	288 (44.7%) 204 (31.7%) 28 (4.4%) 124 (19.3%)	p < 0.001^†
Individual level	875 (91.9%)	298 (96.7%)	577 (89.6%)	p < 0.001
Team level	851 (89.4%)	274 (88.9%)	577 (89.6%)	p = 0.766
Patient level	246 (25.8%)	58 (18.8%)	188 (29.2%)	p < 0.001

*Statistical analyses by Chi-square test.^†Statistical analysis by Chi-square test. In the statistical analysis, the quality of the suggestions was sorted into two categories: non-systematic unorganised and systematic, classified suggestions, and then compared.