5 annotated bibliographies #1 As much as we try to prevent them, medication errors happen everyday. It is especially common in skilled nursing facilities because many of them still use paper charts for medication administration or documentation and do not have access to the newer technology that other medical facilities do. According to a study performed in 2014, medication distribution technology has been proven to be effective in automatically detecting medication errors so that nurses can have more of an opportunity to focus on their patients. Working on a long-term care unit, most of my time is spent passing medications and doing treatments since I have 19 residents to tend to. Depending on how “smooth” the night goes, I sometimes do not get a chance to spend that extra time with my residents as I would like to. This medication distribution technology includes a mobile medication dispensing cart for long-term care units. The medications would be pre-packed for each patient by the pharmacy and able to be dispensed when needed. This would allow nurses to provide more one-on-one time with their patients while also increasing the prevention of medication errors. It also will help to lighten the nurses’ workload. Research shows that these mobile medication cart have been successful. Medication error rates decreased from 2.9% to 0.6% (Baril, Gascon & Brouillette, 2014). Reference Baril, C., Gascon, V., & Brouillette, C. (2014). Impact of technological innovation on a nursing home performance and on the medication-use process safety. ​Journal of Medical Systems​, ​38​(3), 1–12. https://library.neit.edu:2404/10.1007/s10916-014-0022-4 #2 Adverse drug effects due to medication errors are estimated to cost the United States $2 billion every year. After reviewing patient reports and reviewing charts, it was discovered that 44% of these occur after the prescription was written. These errors were found to be from registered nurses, licensed practical nurses and pharmacy technicians. Therefore, the problem comes from administration of the medication. However, these numbers only account for the errors that are actually reported. It is the more serious and harmful errors that are recorded, probably because they are harder to hide. The Health Care Finance Administration of the United States made it standard for hospitals and skilled nursing facilities to have no more than 5% of medication error rates a year. In a study conducted in 2014, researchers decided to put a hold on reviewing incident reports and patient charts. Instead, they decided to directly observe medication administration over 20 different hospitals or skilled nursing facilities. Other methods included: attending medical rounds to see if a medication error had occurred, interviewing health care workers to see if they would report anything, testing patients urine to see if they had any unauthorized medications in their system, and comparing .

1. 5 annotated bibliographies
#1
As much as we try to prevent them, medication errors happen
everyday. It is especially
common in skilled nursing facilities because many of them still
use paper charts for
medication administration or documentation and do not have
access to the newer
technology that other medical facilities do.
According to a study performed in 2014, medication distribution
technology has been
proven to be effective in automatically detecting medication
errors so that nurses can
have more of an opportunity to focus on their patients. Working
on a long-term care unit,
most of my time is spent passing medications and doing
treatments since I have 19
residents to tend to. Depending on how “smooth” the night goes,
I sometimes do not get
a chance to spend that extra time with my residents as I would
like to. This medication
distribution technology includes a mobile medication dispensing
cart for long-term care
units. The medications would be pre-packed for each patient by
the pharmacy and able
to be dispensed when needed. This would allow nurses to
provide more one-on-one
time with their patients while also increasing the prevention of
medication errors. It also
will help to lighten the nurses’ workload. Research shows that

2. these mobile medication
cart have been successful. Medication error rates decreased
from 2.9% to 0.6% (Baril,
Gascon & Brouillette, 2014).
Reference
Baril, C., Gascon, V., & Brouillette, C. (2014). Impact of
technological innovation on a
nursing home performance and on the medication-use process
safety. Journal of
Medical Systems, 38(3), 1–12.
https://library.neit.edu:2404/10.1007/s10916-014-0022-4
#2
Adverse drug effects due to medication errors are estimated to
cost the United States
$2 billion every year. After reviewing patient reports and
reviewing charts, it was
discovered that 44% of these occur after the prescription was
written. These errors were
found to be from registered nurses, licensed practical nurses and
pharmacy technicians.
Therefore, the problem comes from administration of the
medication. However, these
numbers only account for the errors that are actually reported. It
is the more serious and
harmful errors that are recorded, probably because they are
harder to hide. The Health
Care Finance Administration of the United States made it

3. standard for hospitals and
skilled nursing facilities to have no more than 5% of medication
error rates a year.
In a study conducted in 2014, researchers decided to put a hold
on reviewing incident
reports and patient charts. Instead, they decided to directly
observe medication
administration over 20 different hospitals or skilled nursing
facilities. Other methods
included: attending medical rounds to see if a medication error
had occurred,
interviewing health care workers to see if they would report
anything, testing patients
urine to see if they had any unauthorized medications in their
system, and comparing
medication administration records with the physician’s order
(Flynn, Barker, Pepper,
Bates & Mikeal, 2014). I think these methods are effective in
detecting medication errors
as well as having the healthcare workers realize how often these
errors actually do
occur and that they should always perform their tasks as if they
are always being
directly observed.
Reference
Flynn, E.A., Barker, K.N., Pepper, G.A., Bates, D.W., &
Mikeal, R.L., (2014).
Comparison of methods for detecting medication errors in 36
hospitals and
skilled-nursing facilities. American Journal of Health-System
Pharmacy, 59(5), 436–446.
Retrieved from

4. http://library.neit.edu:2084/login.aspx?direct=true&db=ccm&A
N=106538546&site=ehost
-live
#3
Medical errors are a result of a few different causes. We have
learned in this week’s
reading that these can be caused by technical errors,
organizational errors and human
errors. Technical errors are caused by an error in the computer
system or a malfunction
in equipment being used. Organizational error is when an
intervention is not thoroughly
planned, or not planned at all. It can also be caused by poor
communication within the
treatment team. Human errors occur when a person carries out
an intervention without
double checking if it is appropriate for the patient or if they are
even using the proper
intervention. It is vital to catch the medical error before or as
soon as it happens, so that
the steps can be taken to avoid adverse effects from occurring,
or if they already have,
from getting worse.
In a 2015 study, a design was produced to report medical errors
through an online
system. Once the medical error is reported, the online system
identifies the cause and
the damage resulting from the medical error. It is completely
anonymous so healthcare

5. providers do not have to be hesitant to use the system. After
identifying the cause and
damage of the medical error, the system provides feedback. The
system recommends
ways to prevent the error from reoccurring as well as providing
guidelines on how to
prevent them (Jeddi & Atoof, 2015). This will be a great asset if
introduced in all medical
facilities.
Reference
Jeddi, F. R., & Atoof, F. (2015). Improving patients’ care
through electronic medical
error reporting system. Health, Spirituality & Medical Ethics
Journal, 2(2), 22–29.
Retrieved from
http://library.neit.edu:2084/login.aspx?direct=true&db=ccm&A
N=108335172&site=ehost
-live
#4
When a person hears that a medical error has occurred, they
automatically think of the
worst case scenario. They are concerned for the patient’s safety
and they begin to think
of the quality of healthcare of the facility that they chose.
Between 1985 and 2005, over
21,000 medical errors were reported in the United States and
3% of them were pediatric
cases. In a 2018 study, the target participants were parents with
children between the
ages 3 to 6. The objective was to determine how parents felt

6. about medical errors and if
they have every experienced one when it came to their child.
More than half of those
surveyed stated that the medical errors were caused by
physicians. 21% reported that
nurses made the medical error, 6% stated it was both the
physicians and the nurses,
and 21% blamed other members of the healthcare team. As far
as the source of the
issues, participants reported that they were related to a shortage
of nurses, exhaustion
from working long hours, physicians not making enough time
for their patients, and lack
of teamwork and communication. More than half of the parents
involved in the study
believed that they were also responsible for the errors that
occurred. They believe they
should be aware of what is going on so that they can identify if
something is going
wrong (Bektas & Yardimci, 2018). Involvement of patients and
their friends or family in
medical treatment is helpful in preventing medical errors.
Reference
Bektas, I., & Yardimci, F. (2018). What do parents think of
medical errors? International
Journal of Caring Sciences, 379–385. Retrieved from
http://library.neit.edu:2084/login.aspx?direct=true&db=ccm&A
N=129399275&site=ehost
-live

7. #5
Medical errors have been ranked third on the Center for Disease
Control’s (CDC) list of
common causes of death, following heart disease and cancer.
Patient safety is always
the ultimate goal but it can also be a major challenge for
healthcare systems across the
world. One factor that has been found to contribute to these
errors are poor
communications systems. Electronic medical records (EMR)
were developed to make it
easier for healthcare providers to communicate, but they have
not been perfected to
solve these communication issues. It is believed that better data
collection systems
would help to measure each problem contributing to medical
errors so that data can be
collected in order to detect a pattern.
In a 2014 study, data was collected from eleven countries,
regarding patient-reported
medical errors. However, it is important to keep in mind that
many patients suffer from
adverse effects after they are already discharged so it is hard to
include them in the
data. Many patients see more than one physician in different
facilities so the risks of
medical errors increase because not all specialists communicate
effectively regarding
their patient’s plan of care (Schwappach, 2014) . Patients along
with their family
members, or whoever else accompanies them to their
appointments, are the only ones
actually present during every appointment, treatment and
consultation, etcetera. It is not

8. always guaranteed that they can remember everything that they
are told or that goes on
within an appointment. Better communication techniques should
be placed so that each
healthcare provider a patient sees is on the same page.
Reference
Schwappach, D. L. B. (2014). Risk factors for patient-reported
medical errors in eleven
countries. Health Expectations, 17(3), 321–331.
https://library.neit.edu:2404/10.1111/j.1369-7625.2011.00755.x
Risk factors for patient-reported medical errors in
eleven countries
David L. B. Schwappach MPH PhD*�
*Scientific Head, Swiss Patient Safety Foundation, Zuerich,
Switzerland and �Institute of Social and Preventive Medicine
(ISPM),
Senior lecturer, University of Bern, Bern, Switzerland
Correspondence
David L. B. Schwappach MPH, PhD
Swiss Patient Safety Foundation
Asylstr. 77, 8032 Zuerich
Switzerland

9. E-mail: [email protected]
patientensicherheit.ch
Accepted for publication
12 October 2011
Keywords: medical errors,
patient-reported outcomes,
safety, survey
Abstract
Objectives The aim of this study was to identify common risk
factors for patient-reported medical errors across countries. In
country-level analyses, differences in risks associated with error
between health care systems were investigated. The joint effects
of
risks on error-reporting probability were modelled for
hypothetical
patients with different health care utilization patterns.
Design Data from the Commonwealth Fund�s 2010
lnternational
Survey of the General Public�s Views of their Health Care
System�s
Performance in 11 Countries.
Setting Representative population samples of 11 countries were

10. surveyed (total sample = 19 738 adults). Utilization of health
care,
coordination of care problems and reported errors were
assessed.
Regression analyses were conducted to identify risk factors for
patients� reports of medical, medication and laboratory errors
across
countries and in country-specific models.
Results Error was reported by 11.2% of patients but with
marked
differences between countries (range: 5.4–17.0%). Poor
coordination
of care was reported by 27.3%. The risk of patient-reported
error
was determined mainly by health care utilization: Emergency
care
(OR = 1.7, P < 0.001), hospitalization (OR = 1.6, P < 0.001)
and the number of providers involved (OR three doctors = 2.0,
P < 0.001) are important predictors. Poor care coordination is
the
single most important risk factor for reporting error (OR = 3.9,
P < 0.001). Country-specific models yielded common and
country-

11. specific predictors for self-reported error. For high utilizers of
care,
the probability that errors are reported rises up to P = 0.68.
Conclusions Safety remains a global challenge affecting many
patients throughout the world. Large variability exists in the
frequency of patient-reported error across countries. To learn
from
others� errors is not only essential within countries but may
also
prove a promising strategy internationally.
doi: 10.1111/j.1369-7625.2011.00755.x
� 2012 John Wiley & Sons Ltd
Health Expectations, 17, pp.321–331 321
Introduction
Patient safety remains a major challenge for
health care systems worldwide.
1
A recent chart
review study conducted in the Netherlands
reports the incidence of one or more adverse

12. events as 5.7% of all hospital admissions of
which 40% were deemed preventable.
2
In Swe-
den, the incidence of adverse events was 12.3%
of hospital admissions with 70% being judged as
preventable.
3
Similar data have been reported
for several countries recently, including the
United States, New Zealand, Canada and oth-
ers.
4–7
On the basis of these studies, it can be
concluded that approximately one of thousand
hospital patients dies as a result from prevent-
able adverse events. Many patients suffer from
adverse events after discharge and are therefore
not identified in record-based studies.
8
Less research has been conducted in the out-

13. patient care setting but the available studies
suggest that patients are at considerable risk as
well. In particular, preventable adverse drug
events are frequent among patients in outpatient
care.
9,10
Gurwitz et al.
11
report an overall rate of
adverse drug events among older patients in the
ambulatory setting of 50.1 ⁄ 1000 person-years,
of which 28% were considered preventable.
Studies based on staff members� incident reports
in the United Kingdom yielded an error report
rate of 75 ⁄ 1000 patient contacts in outpatient
care.
12
In a similar study in the United States,
errors and preventable adverse events were
reported after 24% of outpatient visits.
13
In

14. Australia, the incidence of error reported to an
anonymous reporting system by general practi-
tioners was 0.24% per patient seen per year.
14
These setting-specific studies are valuable and
important to identify and understand specific
threats, e.g. hospital care or outpatient drug
therapy. However, the frequency and harm of
error is then investigated in isolation for specific
health care sectors, settings or even therapies or
treatments (e.g. medical errors in in-patient
cancer treatment). But many patients utilize
several types of health care in different settings,
and the associated risks accumulate or even
exponentiate because of coordination and com-
munication failures among different providers.
To assess patients� total risk, longitudinal
observation of patient cohorts would be possible
in theory but is methodologically challenging

15. and has not yet been undertaken to the author�s
knowledge. Another methodological approach
to the accumulated likelihood of error is the
survey of citizens or patients. As patients are the
only individuals physically present during every
treatment and consultation, they carry with
them important contextualized information in
particular with relation to transition between
different settings.
15,16
Surveying patients about
their experience of medical error across specific
types of health care consumed, e.g. hospital care,
can help to identify risk factors for error along
the care continuum and relative to specific
patient-level factors and the amount and type of
health care utilized.
In addition, such patient surveys of error
experience conducted in a multinational design

16. can inform health policy about common risk
factors across countries and those specific to
different health care systems. For example, some
countries may perform better in ensuring safe
transition and coordination of inpatient and
outpatient care than others. The main aim of
this analysis was the identification of risk factors
for patient-reported medical errors across sev-
eral countries. Country-level analyses were
conducted to investigate differences in risks
associated with error between different health
care systems. To evaluate the joint effects of the
identified risk factors, the probability that
hypothetical patients with different personal and
health-related profiles and health care utilization
patterns would report error in their care was
modelled.
Methods

17. Design
This analysis is based on data from �The Com-
monwealth Fund�s 2010 lnternational Survey of
the General Public�s Views of their Health Care
System�s Performance in 11 Countries�, which
was conducted in Australia, Canada, France,
Risk factors for patient-reported medical errors, D L B
Schwappach
� 2012 John Wiley & Sons Ltd
Health Expectations, 17, pp.321–331
322
Germany, the Netherlands, New Zealand, Nor-
way, Sweden, Switzerland, the United Kingdom
and the United States in 2010 [details are avail-
able at http://www.commonwealthfund.org/
Content/Surveys/2010/Nov/2010-International-
Survey.aspx]. Computer-assisted telephone
interviews were conducted with nationally rep-
resentative samples of adults aged 18 and above
in each of these countries. Samples were drawn

18. from residential phone number lists, random
number lists or random digit dialing. National
samples differ in the extent to which cell lines
were included. The interviewee in each house-
hold was selected at random based on the most
recent birthday in most countries. All sample
records were called eight times or more before
being abandoned as unusable. The interviews
were conducted by professional interviewing
staff and took on average 18–21 min across
countries. Response rates varied from 13% in
Norway to 54% in Switzerland.
Survey
The Commonwealth Fund�s 2010 lnternational
Survey assessed public confidence in the health
care system including access to care, cost and
quality of care. Methods and results of earlier
versions of the survey have been published pre-
viously.

19. 17–19
For the purpose of this analysis, the following
items relating to medical error experience are of
particular relevance: whether respondents were
ever been given the wrong medication or wrong
dose by a doctor, nurse, hospital or pharmacist in
the past 2 years (referred to as �medication error�
hereinafter); whether there was a time in the past
2 years the responder thought a medical mistake
was made in her treatment or care (referred to as
�medical error� hereinafter); whether the
responder has been given incorrect results for a
diagnostic or laboratory test in the past 2 years
(referred to as �lab error� hereinafter). The
response categories were yes, no, not sure and
decline to answer. Participants that reported any
of the above errors were also asked whether the
error occurred while they were hospitalized (yes,
in the hospital, no, not sure, decline to answer).
Participants were also asked several questions

20. related to demographics, their health and utili-
zation of health care services. Responses to three
items that asked for experience of poor coordi-
nation of care in the past 2 years were also
included in the analysis: whether subjects
reported (i) test results or medical records were
unavailable at the time of a scheduled appoint-
ment; (ii) receiving conflicting information from
different providers; (iii) doctors ordered medical
tests that had already been performed.
Data analysis
Raw survey data were weighted for age, sex,
education and region according to the most
recent national census to reflect demographic
distributions. To dichotomize data for analysis,
�not sure� and �decline to answer� responses were
recoded to missing.
An aggregate measure was computed that

21. captures experience of any of the specific error
items. We report descriptive analysis for all
individual error items and the aggregate measure
per country. To identify potential predictors,
several demographic, health-related and heath
care utilization variables were tested for their
individual association with error experience in
bivariate analyses: age, gender, education,
income (relative to national averages), general
health status, presence of chronic conditions
(out of a specified list of conditions), having a
regular doctor, number of doctors seen in the
past 12 months, specialist care in the past
2 years, elective surgery in the past 2 years,
hospital stay in the past 2 years, emergency care
use in the past 2 years, medical tests (laboratory,
X-ray, etc.) in the past 2 years and current reg-
ular use of prescription drugs. Responses to

22. three coordination of care items were used to
compute an indicator variable indicating expe-
rience of none vs. any of these three events. All
individual variables that were significantly
associated with error experience in bivariate
analyses at the 0.1 level were entered into the
logistic regression model. Logistic regression
was conducted for the aggregate measure, i.e.
report of �any error�, and for each of the
Risk factors for patient-reported medical errors, D L B
Schwappach
� 2012 John Wiley & Sons Ltd
Health Expectations, 17, pp.321–331
323
individual error items as dependent variables.
Multicollinearity of the predictor variables was
assessed using the variance inflation factor
(VIF). VIFs > 10 were inspected, and multi-

23. collinear variables were omitted from the mod-
els. Model fit was assessed using the Archer–
Lemeshow goodness-of-fit statistic, a F-adjusted
mean residual goodness-of-fit test under com-
plex sampling.
20
To evaluate the joint effects of
the identified risk factors across all countries, we
predicted the probability that hypothetical sub-
jects (patients A–F) with different personal and
health-related profiles and health care utilization
patterns would report any error in their care. We
also conducted country-specific analyses for
three countries (United States, United Kingdom
and Germany) that represent prototypes of
health care system organization, i.e. market-
driven, public and social insurance-based health
care systems. Country-specific analyses were
conducted using logistic hierarchical backward

24. selection with the aggregate measure as outcome
variable. This approach was selected because of
the limited size of the country-specific samples.
Hierarchical stepwise regression differs to com-
mon stepwise regression in that potential pre-
dictors are grouped and ordered based on
theory. The sequence in which groups are tested
is not arbitrary. Guided by theoretical consid-
erations, predictors were tested in the following
blocks and sequences for each of the three
country-specific models: (gender) (age) (income,
education) (poor health, number of chronic
conditions) (specialist care, number of doctors
seen) (number of prescriptions drugs) (emer-
gency care) (surgery, hospital) (coordination of
care). Beginning with the first grouping (i.e.
gender), the effect of each block was tested
backwards and the entire block discarded if non-

25. significant. Significant blocks were included as a
whole. Data were analysed using the software
package STATASTATA v11.2.
21
Results
Interviews were completed with 19 738 adults
aged 18 and above. Sample characteristics are
provided in Table 1. Self-reported error in
health care was common in all countries but
with marked differences even within European
countries (Table 2). For example, only 2.2% of
responders in the United Kingdom but 8.6% of
French participants reported a medication error
in the past 2 years. Overall, one of ten citizens
self-reported a medical or medication error
during the last 2 years. 18.8% of responders
across countries reported that the last error in
their care occurred in hospital, but this fraction

26. varied considerably between countries and
ranged from 12.3% in Sweden to 31.3% in
Switzerland (P < 0.001). Across countries, the
Table 1 Sample characteristics, weighted data (n = 19 738)
Characteristic n (%) of participants
Country
Australia 3552 (18.0)
Canada 3302 (16.7)
France 1402 (7.1)
Germany 1005 (5.1)
Netherlands 1001 (5.1)
Norway 1058 (5.4)
New Zealand 1000 (5.1)
Sweden 2100 (10.6)
Switzerland 1306 (6.6)
United Kingdom 1511 (7.7)
United States 2501 (12.7)
Female gender 11 537 (51.5)

27. Age, mean 48.4 years
18–29 years 2212 (17.6)
30–49 years 6467 (36.9)
50–64 years 5632 (24.6)
65 years and above 5427 (20.9)
Education (recoded from nation-specific response codes)
High school or less 9984 (58.4)
Some college 4266 (21.4)
College graduate or higher 5150 (20.3)
Income (relative to national averages)
Much below average 3275 (17.1)
Somewhat below average 3412 (18.9)
Average 4854 (26.9)
Somewhat above average 4441 (24.6)
Much above average 2365 (12.5)
Self-rated health
Excellent ⁄ very good 10 522 (53.9)
Good 6262 (31.5)
Fair ⁄ poor 2876 (14.6)

28. Chronic conditions
None 7429 (42.0)
1 condition 5137 (26.0)
2 or more conditions 7119 (32.0)
Risk factors for patient-reported medical errors, D L B
Schwappach
� 2012 John Wiley & Sons Ltd
Health Expectations, 17, pp.321–331
324
fraction of respondents that reported experience
of two different types of error was 2.5%, and
0.5% reported all three types of errors. Poor
coordination of care was also common in all
countries: 10.9% reported that test results or
medical records were not available, 19.6% per-
ceived to have received conflicting information
by care providers and 10.5% reported that tests
were ordered although they had been performed

29. before. A quarter of citizens (27.3%) reported
any of these coordination problems in the past
2 years.
A number of variables were associated with
patient-reported error in bivariate analysis
(Fig. 1). Across all countries, health status and
health care utilization variables were associated
with all three types of self-reported errors (and
the aggregate measure) with different levels of
strength. Associations between demographic
variables and errors were less systematic: Higher
age was inversely related to all types of reported
errors, except medication errors. Female gender
was associated with medical error, medication
error and the aggregate measure, but not the
Table 2 Frequency of self-reported errors by country, weighted
data
Country
Medical error

30. n (%)
Medication
error n (%)
Either medical
or medication
error n (%)
Laboratory
error* n (%)
Either medical,
medication or
laboratory error
(aggregate
measure) n (%)
Australia 282 (8.3) 155 (4.5) 350 (10.1) 69 (2.4) 395 (11.4)
Canada 212 (7.7) 179 (6.0) 322 (10.9) 106 (4.1) 372 (12.2)
France 87 (5.9) 110 (8.6) 157 (11.6) 39 (2.8) 178 (12.5)
Germany 54 (5.9) 20 (2.2) 64 (7.0) 12 (1.7) 73 (7.8)
Netherlands 52 (4.8) 45 (4.5) 82 (7.8) 25 (3.0) 97 (9.3)

31. Norway 101 (10.8) 79 (8.1) 147 (15.7) 29 (3.4) 161 (17.0)
New Zealand 59 (5.6) 39 (4.6) 82 (8.3) 19 (2.4) 92 (9.0)
Sweden 118 (6.1) 92 (4.9) 173 (8.9) 26 (1.9) 184 (9.5)
Switzerland 81 (8.0) 61 (5.3) 123 (11.4) 31 (3.2) 136 (11.9)
United Kingdom 39 (3.2) 25 (2.2) 55 (4.7) 21 (2.6) 66 (5.4)
United States 204 (9.7) 150 (6.4) 295 (12.9) 83 (5.0) 331 (14.3)
*Based on those that reported blood test, X-rays or other tests
in the past 2 years.
***
**
***
***
***
***
***
***
***
***

32. ***
***
***
***
***
Age > 65 years
Female gender
Education, high school or less
Income much below average
Poor self−rated health
1 chronic cond.
2 or more chronic cond.
Regular doctor
Specialist care
1−2 doctors
3 or more doctors
Elective surgery
Inpatient stay
Emergency care
1 prescription drug
2 or more prescription drugs
Poor care coordination
0 1 2 3 4 5 6 7 8

33. Odds ratio
Figure 1 Bivariate (unadjusted) asso-
ciations between demographic, health
and health care utilization variables
and experience of any error (aggregate
measure), weighted data. Stars indi-
cate significant associations
(*P < 0.05; **P < 0.01;
***P < 0.01).
Risk factors for patient-reported medical errors, D L B
Schwappach
� 2012 John Wiley & Sons Ltd
Health Expectations, 17, pp.321–331
325
subset of laboratory errors. Low income was
associated with all types of reported errors,
again except laboratory errors. Education was
only weakly associated with reporting medical

34. error.
Results of the regression model for all 11
countries and three country-specific models are
presented in Table 3. All VIFs were <2.0 indi-
cating no substantial multicollinearity. The
Archer–Lemeshow goodness-of-fit statistic did
not indicate any overall model departure from
the observed data. Across countries, the risk of
patient-reported error is determined mainly by
health care utilization. Emergency care, hospi-
talization and the number of providers involved
are among the most important predictors.
Having seen three or more doctors doubles the
risk for reporting any error when other factors
are controlled for, e.g. health status and use of
prescription drugs. Experience of poor care
coordination is the single most important risk
factor, associated with a four-fold increase in

35. reporting error. Responders with chronic con-
ditions and poor health are at considerably
higher risk for reporting errors in their care,
even after adjusting for a large variety of health
care utilization. After controlling for health and
health care utilization, patients younger than
65 years were nearly twice as likely to report any
medical error.
The joint influence of the risk factors on the
probability that patients report error in their
care is substantial (illustrated in Fig. 2). For
example, the differences between hypothetical
patients B and F (chronic conditions, emergency
care, prescription drugs, number of doctors seen,
specialist care and coordination of care prob-
lems) account for a 14-fold increase in proba-
bility of reporting error, keeping younger age,
low income, poor self-reported health, hospital

36. stay and surgery constant (pB = 0.049,
pF = 0.679, P < 0.001).
Three country-specific models yield common
and country-specific predictors for self-reported
error. Poor coordination of care experiences was
the strongest predictor for patient-reported error
in all three countries. Hospital care in the past
2 years was associated with reporting error in
the United Kingdom and Germany, but not in
the United States. On the contrary, poor health,
specialist care and emergency care increase the
likelihood of self-reported error in the United
States, but not in the United Kingdom and
Germany. Use of prescription drugs was a sig-
nificant predictor only in the United Kingdom.
Having a much below average income was a
strong predictor for reporting error experience
in Germany.

37. Discussion
This study reports new data on patients� per-
ceptions of error in 11 countries and identified a
number of important risk factors. Overall, one
of ten surveyed patients reported either medical,
medication or laboratory errors in their care but
this risk varies markedly by a factor of 3 across
countries (5.4% in the United Kingdom and
17.0% in Norway). Several factors may help to
explain this finding: Different health care sys-
tems may in fact perform better in preventing
errors and can thus deem to be safer. However,
observed differences between countries may also
stem from differences in patients� likelihood to
identify and report error, rather than differences
in true incidences. While evidence shows that
patients� reports of adverse events are often in
well concordance with other detection methods,
e.g. record review, it is unclear whether this
degree of concordance is similar across coun-

38. tries.
22–25
For example, safety in health care may
be an issue of high public awareness in some
countries and largely unrecognized in others. As
a result, patients may be more or less vigilant
and educated about safety and have different
abilities or motivation to detect errors. �Medical
error� may also be defined differently in diverse
cultural contexts. In addition, patients� reports
of errors are likely to be affected by official
standards and cultural norms among health care
workers on how openly to communicate errors
towards patients. Thus, patients� reports of error
do not only reflect incidence of error but are also
�contaminated� by identification and reporting
biases. Reporting effects rather than differences
in frequency may also help to explain why
Risk factors for patient-reported medical errors, D L B
Schwappach
� 2012 John Wiley & Sons Ltd
Health Expectations, 17, pp.321–331

39. 326
T
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40. c
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41. .
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42. o
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(m
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43. e
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1
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44. n
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-s
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45. U
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(h
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46. h
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)
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47. n
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48. O
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88. .9
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Risk factors for patient-reported medical errors, D L B
Schwappach
� 2012 John Wiley & Sons Ltd
Health Expectations, 17, pp.321–331
327
younger patients were systematically more likely
to report errors compared to respondents aged
65 and above, a finding that has been reported in
the previous studies. For example, in a recent
survey study among Swiss hospital patients, the
likelihood for reporting adverse events during
hospital stay decreased significantly with higher
age by a comparable magnitude.
26
Younger
patients may be more aware of safety problems

89. and less reluctant to report these.
Across 11 countries, our data clearly show
that risk of self-reported error increases steadily
with the amount and categories of health care
consumed. However, across countries, patients
with poor health and low income are at
increased risk even after adjusting for various
health care utilization-related variables. It is not
surprising that poor care coordination experi-
ence is the most important single risk factor for
reporting errors across countries and in our
country-specific analyses. Unavailable records,
conflicting information and repetition of tests
can signal, cause or coincide with safety events
and can themselves be regarded as �error�, even if
they may not cause harm. Thus, it seems likely
that an unknown fraction of responders had the
same event in mind when reporting coordination
of care problems and error. This would lead to

90. an overestimation of the association of coordi-
nation of care problems with error. Indeed,
Rathert et al.
27
recently reported from a quali-
tative study that patients seem to share a
broader interpretation of safety compared with
health professionals and often include commu-
nication and coordination failures. Our country-
level analyses reveal that the risk associated with
different health care services varies considerably
between countries. This strengthens the
assumption that systems differ in their abilities
to manage specific threats for patient safety.
This view is also supported by the large variance
observed in reported occurrence of error. Hos-
pital-associated error was much more frequent
in some countries (e.g. Switzerland) compared to

91. the cross-national average. These results may
reflect differences between countries in how care
is organized. For example, access to specialist
outpatient care is far more restrictive in some
countries compared to others.
While our results clearly indicate that various
types of health care consumed increase the risk
of error, the relative magnitude of predictor
variables should be compared with care. As with
all surveys, health care utilization had to be
operationalized for measurement and this oper-
ationalization may interact with specific forms
of care organizations and is thus important for
interpretation: For example, a single hospital
stay is longer and patients are exposed to risk
(and error identification) simply for a longer
0
.0
0

92. .2
0
.4
0
.6
0
.8
1
.0
P
ro
b
a
b
ili
ty
o
f
p
a
tie
n
t−
re

93. p
o
rt
e
d
e
rr
o
r
A B C D E F
Hypothetical patients
Figure 2 Predicted probability for patient-reported error
(aggregate measure) across 11 countries for six hypothetical
patients (A–F), weighted data. Six hypothetical patients (A–F)
were modelled with the following characteristics: Patient A:
Aged >65 years, average income, good self-reported health,
two or more chronic conditions, emergency care, no hospital
or surgery, two or more prescription drugs, one or two
doctors, no specialist, no coordination of care problems.
Patient B: Aged <65 years, much below average income,

94. poor self-reported health, no chronic conditions, no emer-
gency care, hospital stay and surgery, no prescription drugs,
no doctors seen, no specialist, no coordination of care
problems. Patient C: Aged <65 years, average income, poor
self-reported health, one chronic condition, no emergency
care, hospital stay, no surgery, one prescription drug, one or
two doctors, specialist, no coordination of care problems.
Patient D: Aged >65 years, much below average income,
poor self-reported health, no chronic conditions, emergency
care, hospital stay and surgery, no prescription drugs, one or
two doctors, no specialist, poor coordination of care. Patient
E: Aged <65 years, average income, good self-reported
health, one chronic condition, no emergency care, no hospital
stay or surgery, two or more prescription drugs, three or
more doctors, specialist, poor coordination of care. Patient F:
Aged <65 years, much below average income, poor self-
reported health, two or more chronic conditions, emergency
care, hospital stay and surgery, two or more prescription

95. drugs, three or more doctors, specialist, poor coordination
of care.
Risk factors for patient-reported medical errors, D L B
Schwappach
� 2012 John Wiley & Sons Ltd
Health Expectations, 17, pp.321–331
328
duration as compared to a short outpatient
consultation. The number of doctors seen does
reflect the increasing need for coordination, but
not necessarily treatment intensity. Thus, for
countries that restrict access to the number of
providers involved, treatment intensity per pro-
vider may be more important.
This study has some limitations: First, the
samples for each of 11 countries have been
drawn and weighted to be representative for
each individual country.

96. The sample sizes did not allow more extensive
analyses of country-level data, e.g. selection of
predictors based on bivariate analyses or
including the same predictors in all country-
specific models irrespective of their significance.
In addition, the reasons for and potential effects
of the very different survey response rates
remain unclear. For example, Norway had the
lowest response rate (13%) and the highest
fraction of patients that reported any error in
their care (17%). It seems likely that individuals
that experienced error were more likely to par-
ticipate than others. Second, we used an aggre-
gate measure of error as outcome variable in
regression analyses. Distinct associations with
specific types of errors, i.e. medication or labo-
ratory errors, may thus have gone undetected.
Finally, owing to the nature of the data, we

97. cannot demonstrate causal or temporal rela-
tionship between health care utilization and
error. While responders were asked to consider
the past 2 years in most of the questions, we do
not know whether health care was utilized
before or after the reported events occurred and
how they are connected.
Despite these limitations, the results of this
study are alarming. Our modelling of hypo-
thetical patients shows that for high utilizers of
health care that unify multiple risk factors it is
nearly rule rather than exception that errors
occur. Patients who utilize various types of
health care in different settings accumulate a
high risk of errors, which is largely underesti-
mated in isolated setting-specific adverse event
studies. Despite the associated health-related
harm, the common experience of error in these

98. populations may also cause considerable loss of
trust in the health care system as a whole.
Medical error is communized with poor coor-
dination of care experiences, and obviously,
health care systems fail to overcome risks asso-
ciated with the segmentation of health care. This
is also indicated by the fact that having a regular
doctor had no substantial protecting effects on
patient safety. These results emphasize that
patient safety remains a global challenge affect-
ing many patients throughout the world. How-
ever, large variability exists in the frequency of
patient-reported error across countries. Taking
the opportunity to learn from others� errors is
not only essential within individual institutions
or systems but may also prove a promising
strategy internationally.
Ethics approval
Ethics approval was not necessary for this study.

99. Acknowledgements
The author thanks the Commonwealth Fund for
permission to analyse the data. The support by
Markus Weber (Swiss Federal Office of Public
Health, BAG) is highly appreciated. Three
anonymous referees are acknowledged for their
thorough comments on an earlier draft. The
contents are the sole responsibility of the author
and do not represent the views of the Com-
monwealth Fund or local agencies of the par-
ticipating countries.
Competing interests
None.
Funding
The author obtained no funding for this partic-
ular research. Core funding for the �Common-
wealth Fund�s 2010 lnternational Survey of the
General Public�s Views of their Health Care
System�s Performance in Eleven Countries� was
by the Commonwealth Fund with co-funding

100. from the following organizations: the Australian
Commission on Safety and Quality in Health
Risk factors for patient-reported medical errors, D L B
Schwappach
� 2012 John Wiley & Sons Ltd
Health Expectations, 17, pp.321–331
329
Care; the Ontario Health Quality Council; the
Health Council of Canada; the Quebec Health
Commission; La Haute Autorité de Santé; the
Caisse Nationale d�Assurance Maladie Ces
Travailleurs Salaries; the German lnstitute for
Quality and Efficiency in Health Care; the Dutch
Ministry of Health, Welfare and Sport; the Sci-
entific lnstitute for Quality of Healthcare, Rad-
boud University Nijmegen; the Norwegian
Knowledge Centre for the Health Services; the
Health Foundation; the Swedish Ministry of

101. Health and Social Affairs; the Swiss Federal
Office of Public Health.
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International Journal of Caring Sciences

108. January-April 2018 Volume 11 | Issue 1| Page 379
www.internationaljournalofcaringsciences.org
Original Article
What Do Parents Think of Medical Errors?
Ilknur Bektas
Dokuz Eylul University, Faculty of Nursing, Department of
Pediatric Nursing , Izmir, Turkey
Figen Yardimci
Ege University, Faculty of Nursing, Department of Pediatric
Nursing, Izmir, Turkey
Correspondence: Ilknur Bektas, Dokuz Eylul University,
Faculty of Nursing, Department of Pediatric
Nursing, Inciralti, Izmir, Turkey E-mail: [email protected]
Abstract
Background: In its reports on “medical errors” and “patient
safety and health care quality”, the Institute of
Medicine dealt with two significant problems in health care
environments.
Objective or Aims: The purpose of study is to identify the views
of parents with children aged three to six
years old concerning medical errors.
Methodology: The sample was comprised of 301 parents. 9.3%
of parent encountered a medical error. The data
for the study were collected through “the Descriptive Form for
Parents” and “The Parents’ Perceptions of
Medical Errors Form.” The scenarios for the study were

109. prepared in reference to the medical errors on which the
Third Specialized Board of the Council of Forensic Science had
expressed an opinion and to other scenarios
whose validity had already been tested in other similar studies.
Results: Case 1 was viewed as an example of a medical error by
91.7% of the parents. Out of these parents,
77.9% considered it as a severe/serious error. As for Case 2,
95% of the participants viewed it as an example of
a medical error.
Conclusions: Parents who considered a case as an example of a
medical error were more likely to desire
disclosure and reporting.
Keywords: Medical errors; parents; perceptions.
Introduction
In its reports on “medical errors” and “patient
safety and health care quality”, the Institute of
Medicine dealt with two significant problems in
health care environments. According to the
reports, 98.000 people die of medical errors in
the USA every year (IOM, 1999).
It is essential to ensure patient safety in health
care systems, which are becoming increasingly
complicated and equipped with technological
devices. Individuals are under greater threat in
such health care systems. Accordingly, greater
and greater importance is attached to patient
safety (Cirpi et al., 2009; Gokdogan and Yorgun,
2010; Hakverdioglu Yont, 2011).
The Physician Insurers Association reported that

110. there were 214226 reports of medical errors in
the USA between 1985 and 2005, and 2.97% of
these reports were pediatric cases (as cited in
Carroll et al., 2006). The rate of medical errors
among discharged children was discovered to
range from 1.81% to 2.96% in the USA (Slomin,
LaFleur, Ahmed and Joseph, 2003). In Turkey, a
total of 1458 files were submitted to the High
Council of Health between 2000 and 2006, and
378 of them (25%) were pediatric cases (Ozkaya,
2008). All these suggest that children constitute
an important group to be taken into consideration
in terms of medical errors and patient safety both
in Turkey and other nations.
Programs on patient safety in health care services
often neglect the patient perspective. This is in
sharp contrast to the fact that active roles of
patients in health care services should be
recognized and supported. The reason for this is
that patients play a key role in achieving accurate
diagnosis, deciding on the treatment, choosing a
safe and experienced service provider, providing
and monitoring accurate treatment, identifying
negative occurrences, and taking necessary
actions. The “To Err is Human” report by the
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Institute of Medicine (IOM, 1999) suggests that

111. patients should be acknowledged as active
participants of medical care processes and a
member of the health care team (IOM, 1999).
The identification of parental views of medical
errors will hopefully be useful for ensuring
cooperation with patients, something that we
have to do, and enabling patients, who are often
neglected, to participate in the process.
Methodology
Population and sample
The study was designed as a descriptive and
cross-sectional one. The sample was comprised
of 301 parents whose children attended four
different kindergartens run by the District
Directorate for National Education. Sample size
was calculated according to pilot study. By the
pilot study, the sample size needed was at least
84 student/parent for power analysis with a Type
II error 0.20 and 0.01 level of significance.
Instruments
The data for the study were collected through
“the Descriptive Form for Parents” and “The
Parents’ Perceptions of Medical Errors Form.”
The former was focused on identifying certain
socio-demographics for the participants, namely
age, occupation, social security, number of
children, previous hospitalization record, and
previous medical error record). The latter was
composed in reference to the literature in order to
reveal parents’ views of medical errors. The form
contained two cases, which were followed by 14

112. questions. It was translated from English to
Turkish by two language experts, and the
Turkish version of the form was revised by the
researchers.
Before it was finalized, the Turkish version was
submitted to a Turkish language expert. To make
the form more reliable, the Turkish version was
submitted to another language expert, who had
never seen the form previously, to be translated
again.
The scenarios for the study were prepared in
reference to the medical errors on which the
Third Specialized Board of the Council of
Forensic Science had expressed an opinion and
to other scenarios whose validity had already
been tested in other similar studies. The level of
severity was not specified by the researchers;
instead, the participants were presented with
cases that might involve medical errors so as to
identify whether they considered them as
medical errors and how severe they thought they
were.
Expert judgment was received before the form
that contained the cases and relevant questions
was administered to the participants. The content
validity of the form was assessed by eight
experts. According to Lawshe’s table, minimum
fit criterion is 0.78 for eight reviewers.
The instrument had a content validity ratio
(CVR) of 0.91, a value higher than the one
specified in Lawshe’s table, which suggested that

113. there was advanced fit among the experts (Alpar,
2010; Sencan, 2005).
Pilot Test
The form was administered to 20 randomly
chosen parents, who were from the schools
included in the present study but not in its
sample. Positive feedback by these parents
suggested that the form could be administered to
the sample.
The Parents’ Perceptions of Medical Errors
Form : The form contained two scenarios and 14
questions. The first three questions were as to
whether the participants viewed the case as a
medical error, how severe they thought the
medical error was, and by whom they would like
to be informed about the error. The remaining
questions were grouped under three headings,
namely disclosure, reporting, and legal actions.
Each question could be answered by one of the
three following options: I agree (3), neutral (2),
and I disagree (1). Cronbach’s alpha values were
0.79 and 0.86 for the first and second scenarios
respectively.
Ethics
The permission for the study was granted by the
Scientific Ethics Committee. In addition, written
consent was obtained from the Provincial
Directorate for National Education while verbal
consent was obtained from school principals and
parents.

114. Statistical Analysis
The data were analyzed through percentages,
Mann-Whitney U test, Kruskal Wallis Analysis,
Mann-Whitney U test with Bonferroni
correction, independent samples t-test with
Bonferroni correction, and Multiple Regression
analysis.
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Results
Slightly more than half of the participants
(52.4%) reported that medical errors were mostly
committed by physicians, 20.8% by nurses, 5.6%
by both physicians and nurses, and 21.2% by
other members of health care staff.
As for the cause of the medical error, 9.7% of the
participants noted that medical errors resulted
from the inadequate number of nurses, 15.9%
from exhaustion and stress caused by long
working hours, 21.6% from communication
disorders, 13.6% from lack of team work, 15.9%
from the complicated nature of health care
services, and 23.3% from the inability of
physicians to allocate enough time to patients.
More than a quarter of the participants (27.2%)

115. reported that parents should file a lawsuit against
the member of the health care staff responsible
for the medical error whereas 19.6% of them said
that the health care institution should be taken to
the court. Another 10% believed that other
actions should be taken. Whereas 35.2% of the
participants believed that those subject to the
medical error should file a lawsuit against both
the member of the health care staff and the health
care institution, 2.3% of them noted that they
should not only file a lawsuit against the member
of the health care staff and the health care
institution but also take other actions.
As for what patients could do in terms of safety,
5.6% of the parents reported that patients could
absolutely protect themselves against medical
errors while 36.2% thought that they could
slightly protect themselves against such errors. In
addition, 17.9% of the participants believed that
parents could protect themselves against medical
errors. Whereas 31.9% of the participants
reported that parents could not protect
themselves against medical errors, 8.3% of them
believed that parents could definitely not protect
themselves.
Twenty-nine percent of the parents reported that
they much relied on their own knowledge and
awareness to get protected from medical errors
whereas 67.4% reported their slight reliance on
their knowledge and awareness in this respect.
On the other hand, 10.6% of them did not rely on
their own knowledge and awareness to get
protected against medical errors.

116. Findings on Case 1
Table 1. The Results of the Multiple Regression Analysis of the
Variables in the Parents’
Viewing Case 1 as an Example of a Medical Error
B Standard
Error
Standard
Beta (β)
t p
Constant 0.963 0.384 2.509 0.017
Parental Role 0.294 0.093 0.575 3.178 0.003
Age 0.018 0.005 0.539 3.600 0.001
Educational Status 0.030 0.032 0.149 0.949 0.349
Occupational Status 0.135 0.072 0.323 1.863 0.071
Social Security 0.060 0.078 0.111 0.770 0.446
Number of Children 0.016 0.052 0.042 0.304 0.763
Length of Hospitalization
for Child
0.032 0.038 0.140 0.852 0.400
Number of Times of
Hospitalization

117. 0.013 0.042 0.050 0.318 0.753
Type of Hospital 0.003 0.037 0.014 0.092 0.927
Previous Medical Error
Record
0.078 0.097 0.108 0.810 0.423
R=0.661 R2=0.437 F= 2.540 p= 0.017 DW Coefficient=
2.5 (1.5-2.5)
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While 91.7% of the participants viewed the
scenario in Case 1 as an example of a medical
error, the remaining 8.3% did not. Whereas the
mean score of the former group in the desire for
disclosure was 14.33 ± 1.17, the latter group had
a mean score of 13.08 ± 3.26. The discrepancy
between the former and latter groups in their
mean scores was not statistically significant
(p=0.079). As for the desire for reporting, the
mean score of the former group was 5.91 ± 0.44
whereas the latter group had a mean score of
5.28 ± 1.48. The discrepancy between the former
and latter groups in terms of their mean scores in
the desire for reporting was statistically highly

118. significant (p=0.000). Regarding the desire for
legal actions, the mean score of the former group
was 12.70 ± 2.01whereas the latter group had a
mean score of 10.12 ± 3.16. The discrepancy
between the former and latter groups in terms of
their mean scores in the desire for reporting was
statistically highly significant (p=0.000).
The results of the regression analysis indicated
that the variables involved in the study were
(R2=0.437) in an intermediately significant
interaction with viewing Case 1 as an example of
a medical error (F= 2.540, p= 0.017). These
variables could account for only 43.7% of
viewing Case 1 as an example of a medical error.
According to the standardized regression
coefficient (β), the independent variables had an
influence on viewing Case 1 as an example of a
medical error in the following order of
importance: the parental role of the respondent
(i.e. mother or father), the age of the respondent,
the occupational status of the respondent, the
educational status of the respondent, the length
of hospitalization for the child, social security,
previous medical error record for the parent, the
number of times of hospitalization, the number
of children, and the type of hospital. On the other
hand, the results of the t-test demonstrated that
the parental role of the respondent (i.e. mother or
father) (p=0.003) and the age of the respondent
(p=0.001) had a significant influence on viewing
Case 1 as an example of a medical error.
Table 2. The Results of the Multiple Regression Analysis of the

119. Variables in Parents’ Viewing
Case 2 as an Example of a Medical Error
B Standard
Error
Standard
Beta (β)
t p
Constant 0.519 0.431 1.205 0.236
Parental Role (i.e. mother
or father)
0.006 0.104 0.011 0.057 0.955
Age 0.003 0.006 0.088 0.524 0.604
Educational Status 0.042 0.035 0.210 1.193 0.241
Occupational Status 0.086 0.081 0.206 1.057 0.298
Social Security 0.038 0.088 0.069 0.429 0.671
Number of Children 0.046 0.058 0.122 0.789 0.435
Length of Hospitalization
for Child
0.05 .043 0.231 1.253 0.218
Number of Times of
Hospitalization

120. 0.051 0.047 0.192 1.085 0.285
Type of Hospital 0.058 0.041 0.243 1.421 0.164
Previous Medical Error
Record
0.014 0.109 0.020 0.131 0.896
R=0.539 R2=0.29 F= 1.337 p= 0.245 DW Coefficient=
1.913 (1.5-2.5)
Findings on Case 2
While 95% of the participants viewed the
scenario in Case 2 as an example of a medical
error, 3.7% did not. The remaining 1.3% left the
question unanswered. Whereas the mean score of
the former group in the desire for disclosure was
14.54 ± 1.08, the latter group had a mean score
of 13.27 ± 3.03. The discrepancy between the
former and latter groups in their mean scores was
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statistically significant (p=0.019). As for the
desire for reporting, the mean score of the former
group was 5.92 ± 0.49 whereas the latter group
had a mean score of 5.36 ± 1.28. The

121. discrepancy between the former and latter groups
in terms of their mean scores in the desire for
reporting was statistically highly significant
(p=0.000). As for the desire for legal actions, the
mean score of the former group was 13.45 ± 1.82
whereas the latter group had a mean score of
12.00 ± 3.77. The discrepancy between the
former and latter groups in terms of their mean
scores in the desire for legal actions was not
statistically significant (p=0.316).
The results of the regression analysis indicated
that the variables involved in the study were
(R2=0.29) in a low and insignificant interaction
with viewing Case 2 as an example of a medical
error (F= 1.337, p= 0.245). These variables could
account for only 29% of viewing Case 2 as an
example of a medical error. According to the
standardized regression coefficient (β), the
independent variables had an influence on
viewing Case 2 as an example of a medical error
in the following order of importance: the type of
hospital, the length of hospitalization for the
child, the educational status of the respondent,
the occupational status of the respondent, the
number of times of hospitalization, the number
of children, the age of the respondent, social
security, previous medical error record for the
parent, and the parental role of the respondent
(i.e. mother or father). On the other hand, the
results of the t-test demonstrated that none of the
variables had a significant influence on viewing
Case 2 as an example of a medical error.
Discussion

122. In the present study, only a small percentage of
the parents (9.3%) reported encountering medical
errors in the clinic. When compared to other
similar studies (Hobgood et al., 2005; Mazor et
al., 2010; Matlow et al., 2010), the ratio is
smaller, which might be attributed to the fact that
the sample for the present study was from
outside hospitals and that the parents stayed at
hospitals for a relatively shorter time.
According to the parents, medical errors were
mostly committed by physicians (52.4%), nurses
(20.8%), and other health care staff (21.2%)
respectively. Ozkaya (2008) reported that nearly
half of the files submitted to the Third
Specialized Board of the Council of Forensic
Science were about medical errors committed by
physicians and that nurses were responsible for
only 6.7% of these errors. The reason for the
discrepancy might be that the public views
physicians as the person with sole responsibility
for treatment and nurses as only the implementer
of commands given by physicians.
The participants attributed medical errors to
different causes, namely the inadequate number
of nurses (9.7%), exhaustion and stress caused by
long working hours (15.9%), communication
disorders (21.6%), lack of team work (13.6%),
the complicated nature of health care services
(15.9%), and the inability of physicians to
allocate enough time to patients (23.3%). The
finding is quite similar to those of other similar
studies (Hogbood et al., 2005; Mazor et al.,
2010; and Matlow et al., 2010).

123. Almost all of the parents (96%) believed that
parents/patients should be informed about and
apologized for medical errors. Similarly, studies
in the literature have revealed that parents are of
the opinion that they should be informed about
and apologized for medical errors (Hobgood et
al., 2005; Mazor et al., 2010; Matlow et al.,
2010).
The great majority of the participants in the
present study stressed that in case of medical
errors parents should file a lawsuit against both
the person committing the error and the
institution, and they demanded that institutions
should take legal actions. The finding is
supported by the 10% increase in the number of
lawsuits against nurses in recent years (Zincirci,
2010).
More than half of the parents (56.5%) believed
that parents were also responsible for preventing
medical errors. A review of literature suggests
parents think that parents, along with children,
are also responsible for the prevention of medical
errors (Hobgood et al., 2005; Mazor et al., 2010;
Matlow et al., 2010).
In the present study, 89.3% of the parents relied
on their own knowledge and awareness to
prevent medical errors. Similarly, Clarke et al.
(2005) concluded from their study that parents
believe they can prevent medical errors by being
careful with the treatment of their children.
Likewise, the IOM (2003) stresses that
involvement of patients and their

124. friends/relatives in treatment and care is a
significant step in the prevention of medical
errors.
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Case 1 and Case 2 were considered as an
example of a medical error by 91.7% and 95% of
the participants respectively. Actually, both cases
were an example of a medical error, though at
different levels of severity, and almost all of the
participants viewed the cases as an example of a
medical error. The finding is similar to that of
Hobgood et al. (2005), who observed that 99% of
parents accurately viewed the scenarios they
were presented with as examples of medical
errors. The finding of the present study suggests
that parents are knowledgeable about medical
errors, though at varying degrees; therefore, a
significant decrease is likely to be achieved in
the number of medical errors if parents are
informed about and enabled to participate in the
treatment and care of their children, as
recommended by the IOM (2003).
The results of the regression analysis indicated
that the variables involved in the study were
(R2=0.437) in an intermediately significant
interaction with viewing Case 1 as an example of
a medical error (F= 2.540, p= 0.017). These
variables could account for only 43.7% of

125. viewing Case 1 as an example of a medical error.
According to the standardized regression
coefficient (β), the independent variables had an
influence on viewing Case 1 as an example of a
medical error in the following order of
importance: the parental role of the respondent
(i.e. mother or father), the age of the respondent,
the occupational status of the respondent, the
educational status of the respondent, the length
of hospitalization for the child, social security,
previous medical error record for the parent, the
number of times of hospitalization, the number
of children, and the type of hospital. On the other
hand, the results of the t-test demonstrated that
only the parental role of the respondent (i.e.
mother or father) (p=0.003) and the age of the
respondent (p=0.001) had a significant influence
on viewing Case 1 as an example of a medical
error. As for Case 2, the results of the regression
analysis indicated that the variables involved in
the study were (R2=0.29) in a low and
insignificant interaction with viewing Case 2 as
an example of a medical error (F= 1.337, p=
0.245) (Table 2). These variables could account
for only 29% of viewing Case 2 as an example of
a medical error. On the other hand, the results of
the t-test demonstrated that none of the variables
had a significant influence on viewing Case 2 as
an example of a medical error. Several studies
have found, unlike the present study, that the
parental role and age of the parent do not affect
the way medical errors are perceived (Hobgood
et al., 2005; Mazor et al., 2010; Matlow et al.,
2010). The reason for the contradiction between
the findings might be that it is often mothers who

126. are responsible for child care in the Turkish
culture and fathers exhibit an insufficient level of
interest in their children. For both of the cases,
the parents had considerably high scores in the
desire for disclosure, legal actions, and reporting.
Likewise, it is reported in the literature that
parents have a high desire especially for
disclosure, punishment for the person or
institution committing the error, and reporting
with the purpose of preventing the error from
being committed again (Hogbood et al., 2005;
Mazor et al., 2010; Matlow et al., 2010).
Whereas there was not a significant difference
(p=0.079) in the mean scores concerning the
desire for disclosure between the parents who
viewed Case 1 as an example of a medical error
and those who did not, there was a significant
difference (p=0.019) in this respect between the
parents who viewed Case 2 as an example of a
medical error and those who did not. In similar
other studies, parents who considered a case as
not an example of a medical error or an example
of a slight medical error were observed to tend to
have lower levels of desire for disclosure
whereas those who considered a case as an
example of a medical error had higher levels of
desire for disclosure (Hobgood et al., 2005;
Mazor et al., 2010; Matlow et al., 2010).
Just as there was not a significant difference
(p=0.000) in the mean scores concerning the
desire for reporting between the parents who
viewed Case 1 as an example of a medical error
and those who did not, there was not a significant
difference (p=0.000) in this respect between the

127. parents who viewed Case 2 as an example of a
medical error (5.92±0.49) and those who did not.
Similarly, Hobgood et al. (2005), Mazor et al.
(2010) and Matlow et al. (2010) observed that
parents who considered a case as an example of a
medical error had a higher level of desire for
reporting.
Whereas there was a statistically highly
significant difference (p=0.000) in the mean
scores concerning the desire for legal actions in
case of medical errors between the parents who
viewed Case 1 as an example of a medical error
and those who did not, there was not a
statistically significant difference (p=0.316) in
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this respect between the parents who viewed
Case 2 as an example of a medical error and
those who did not. Likewise, other similar
studies in the literature have found that parents
who view a case as an example of a medical
error tend to have higher levels of desire for legal
actions (Hobgood et al., 2005; Mazor et al.,
2010; Matlow et al., 2010). In other words, the
finding on Case 2 is different from those in the
literature. The discrepancy might be owing to
two reasons. Firstly, there were a small number
of parents who did not consider the case as an
example of a medical error. Secondly, even those

128. parents who did not consider the case as an
example of a medical error might have thought
that legal actions should be taken in case of
medical errors.
Conclusion and implications
Half of parents hold physicians responsible for
medical errors, and almost all of them are of the
opinion that patients should be informed about
and apologized for medical errors. The great
majority of parents accurately view cases as
examples of medical errors. Considering that the
present study is the first in Turkey to attempt to
measure parents’ perceptions of medical errors, it
is recommended that the study should be
replicated in different regions and on different
samples. In addition, further studies could
attempt to replicate the present study on parents
staying at hospitals so that factors in parents’
perceptions of medical errors can be fully
identified.
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131. Health, Spirituality and Medical Ethics - Vol.2, No.2, Summer
2015
Improving Patients' Care through Electronic Medical Error
Reporting System
Fatemeh Rangraz Jeddi1*, Fatemeh Atoof2
1 Associate professor of Health Information Management.
Kashan University of Medical Sciences, Kashan, Iran
2 PhD Student. Tehran University of Medical Sciences. Tehran,
Iran
[email protected] mail:-E. Fatemeh Rangraz Jeddihould be
addressed SCorrespondence: *

132. Abstract
Background and Objectives: Medical errors are unintentional
acts that take place due to the
negligence or lead to undesirable consequences in medical
practice. The purpose of this study was
to design a conceptual model for medical error reporting
system.
Methods: This applied descriptive cross-sectional research
employed Delphi method carried out
from 2012 to 2013. The study population was medical and
paramedical personnel of health workers
and paramedical personnel of hospitals, deputy of treatment,
faculty members of Kashan University
of Medical Sciences in addition to the internet and library
resources. Sample size included 30 expert
individuals in the field of medical errors. The one-stage
stratified sampling procedure was used.
The items with opposition ranging 0 to 25 were confirmed and
those exceeding 50 were rejected
whereas the items with the opposition 25 to 50 were reevaluated
in the second session. This process
continued for three times and the items that failed to be
approved were eliminated in the model.

133. Results: Based on the results of this research, repeated
informing about and reporting operation
at on-line bases that have access to the incidence of error
detected on time, identifying cause and
damage due to the incidence reported confidential and
anonymously immediately after the
occurrence is necessary. Analysis of data quantitatively and
qualitatively by using computer
software is needed. Classifying the errors reports based on
feedback provision according to the
cause of error is needed. In addition, confidential report and
possible manual retrieval were
suggested
Conclusion: It is essential to determine the means of reporting
and items in the reporting form including
time, cause and damage of medical error, media of reporting and
method of recording and analysis.
Keywords: design, informing, medical error, reporting,system.
Original Article Health, Spirituality
and Medical Ethics. 2015;2(2):22-29
Please Cite This Article As: Rangraz Jeddi F, Atoof F.
Improving Patients' Care through

134. Electronic Medical Error Reporting System. Health, Spirituality
and Medical Ethics. 2015;2(2):22-
29.
Health standards are a set of procedures and acts
to ensure the regaining of patient's health. They
are logical acts and well-defined goals that are
mandatory to be followed by the practitioners
based on the condition and the accessible
facilities (1). The occurrence of medical errors
in extensive professions such as medical settings
is not unusual and the medical professionals
are always seeking means by which to avoid
Introduction
edical errors are unintentional acts that
occur due to the negligence or carelessness
which fail to lead to a desirable consequence in
medical practice. A medical error is defined as
the action made or decision taken in a health-

135. care setting that does not conform to the health
standards set in the field.
M
Improving Patients' Care through Electronic Medical Error
Health, Spirituality and Medical Ethics - Vol.2, No.2, Summer
2015
or reduce them. Since many cases of medical
errors are not reported, estimating an
approximate rate is very difficult (2). According
to the results of a research, 195000 deaths take
place every year due to medical errors (3).
The main cause of many medical errors is the
insufficient access to information at the time of
decision making and poor communication
among the caring team that usually work in

136. manually operating systems. Sedghiani has
indicated that one of the items in regard to the
evaluation of hospital is the inclusion of error
report form, its analysis and the result of such
report on the delivery of services (4). There are
many ways for reducing medical errors and
increasing the safety of patients (5). One of
them is discovering the errors through
employing a reporting system (6). A health care
system will benefit from discovering a medical
error only when there is a comprehensive
program and proper mechanism for analyzing
the condition under which the error took place
and then implement appropriate measure to
prevent its recurrence (7). Such a management
system requires understanding of the causes of
errors and introducing plans to prevent them
before they lead to harmful occurrences; a

137. system that will propose strategies and
guidelines to avoid the likely errors and dangers
that may occur in future.
Error reporting systems employ efficient
methods for eliminating errors in a health care
system. Error reporting may be committed
voluntarily or involuntarily. The voluntary
method of error reporting is done by physicians
and personnel within the medical centers who
are directly in contact with patients either para-
clinically or clinically. The involuntary
reporting is carried out according to the
assignment and duties defined by the health care
and medical service system (8). The result of
researches have indicated that systems that
employ voluntary and involuntary error
reporting method are more efficient and more
errors are reported by physicians so that that the

138. rate of reporting increases 20 times (10). The
importance of error reporting system is such that
many medical centers conduct error reporting
through their computer systems (11, 12).
A successful error reporting system must be
confidential and non-punitive. The analysis of
errors and reporting their explanation must be
performed by expert personnel who understand
the clinical cares and causes of error systems.
The report must be available on time. It must
rely on and emphasize the processes instead of
individuals; it must be capable of responding
appropriately to the needs of the system; employ
proper media and be accessible to the public. In
designing the medical error reporting system, it
is important to focus on systems, processes and
services instead of individuals. The system must
be able to provide the appropriate responses to

139. the beneficiary organization; it must be easy to
learn and use and release its result in a suitable
medium and be accessible to the public.
The design of medical error reporting system
must focus on important issues such as the
reporting of events, ease of using computer
technology and even web, evaluation of
effectiveness, and capability of executive
system review of goals, and obstacles in the use
of reporting system, procedures for
classification and reporting errors (8, 13. 14).
The purpose of this research was to design a
conceptual model for medical error reporting
system that has the capability of reducing the
medical errors and facilitating management
affairs.
Methods:
This applied descriptive cross-sectional

140. research employed Delphi technique between
2012 to 2013. The study population was medical
and paramedical personnel. Sample size
included 30 expert individuals in the field of
medical errors. The means of determining
sample size was the one- stage stratified
sampling procedure. The experts were selected
from 5 categories including 3 physicians
(faculty members), 17 nurses, 2 midwifes, 7
paramedics and one manager. The selection was
based on the proportion of every profession.
The inclusion-exclusion criteria were based on
the involvement of the experts in the occurrence
of medical errors, who were working in the
offices of clinical governance or members of the
committees’ accreditation assessment of the
hospitals. The questionnaire was based on the

141. Rangraz Jeddi F, et al
Health, Spirituality and Medical Ethics - Vol.2, No.2, Summer
2015
library resources aligned with the research
objectives. The validity of the questionnaire
was confirmed through face and content
validity and question items were corrected
based upon opinions of 3 experts. To calculate
the reliability of the questionnaire, split-half
method was used and alpha level equal to 0.76
was calculated. The first draft of the
questionnaire was presented to the experts.
The item with opposition ranging 0 to 25 was
confirmed and those exceeding 50 were
rejected whereas the items with the opposition
between 25 to 50 were put forward to the next
step and reevaluated in the second session.
This process continued for three times and the

142. items that failed to be approved were
eliminated in the model.
Results
The result of analysis of data indicated that
informing the personnel about the reporting
medical error is a necessity. The main
components of the system are: a) recording the
event, b) analyzing and c) feedback and
reporting the result (figure 1).
In regard to the informing of reporting medical
error, the results showed that the highest
frequency of agreement among the expert in the
first stage of reporting was the written
informing form 29 (96.7%). In addition, written
informing method by matrons and educational
supervisor was deemed necessary while the use
of poster and brusher was suggested (table 1).
Data analysis also showed that implementing an

143. involuntary rule for recording the medical error
Table 1. Frequency Distribution of Expert Opinion regarding
the Informing System
Opinion
Item
agree
Frequency
(percent)
disagree
frequency
(percent)
No opinion
frequency
(percent)
First stage
result
Second
stage result

144. Third
stage
result
method
verbal 10 (33.3) 9 (30) 11 (36.7) reassessment remove *
written 24 (80) 1 (3.3) 5 (16.7) confirm * *
Person in
charge
matron 15 (50) 5 (16.7) 10 (33.3) reassessment confirm *
Educational
supervisor
18 (60) 2 (6.7) 10 (33.3) confirm * *
media
Internet 9 (30) 12 (40) 9 (30) reassessment remove *
journal 10 (33.3) 10 (33.3) 10 (33.3) reassessment reassessment
remove
booklet 12 (40) 8 (26.7) 10 (33.3) reassessment reassessment
remove
brochure 15 (50) 7 (23.3) 8 (26.7) confirm * *
poster 14 (46.7) 11 (36.7) 5 (16.7) reassessment confirm *

145. television 8 (26.7) 13 (43.3) 9 (30) remove * *
satellite 2 (6.7) 16 (50.3) 12 (40) remove * *
characteristics
Repeated
informing
22 (73.3) 6 (20) 2 (6.7) confirm * *
Overall
reporting in
hospital
29 (96.7) 1 (3.3) 0 (0) confirm * *
* did not enter at this stage
Improving Patients' Care through Electronic Medical Error
Health, Spirituality and Medical Ethics - Vol.2, No.2, Summer
2015
while keeping the reporter animosity and the
report confidentially immediately after the
incidence is desirable. In addition, rewarding

146. the reporter in addition to having a simple and
comprehensible method appropriate for the
objectives to improve the care and services of
health care were confirmed. Moreover,
recording the time of incidence, cause and harm
inflicted and the title of the person committing
the error were also suggested. The result of
analysis showed that using electronic and on-
line media was necessary. According to experts'
beliefs, the medical errors must be analyzed and
the cause be identified.
In their opinion, quantitative and qualitative
analysis using software, statisticians' and
experts' views on medical errors is
indispensable. All the experts (30, 100%) in the
first stage suggested the need to analyze the
medical errors. The lowest frequency of
agreement was about the necessity to perform

147. analysis by the medical record expert (14,
46.7%). The highest frequency of agreement
among experts in the first stage was verbal
feedback (29, 96.7%) (table 3).
With regard to the feedback provision and
effectiveness of reporting the result of analysis
of medical errors for reducing the errors, the
need for classification based on the type of error
and maintaining the confidentiality was
emphasized by the experts (table 4).
Discussion:
A medical system of reporting the medical
errors demonstrates the performance and
capability of the hospitals or other health care
centers for presenting the cares based on the
safety standards (15-18). Despite the fact that
voluntary reporting of medical errors leads to
under reporting of the real cases of errors which

148. in turn is considered as weakness in the system
(19), nowadays such an act plays an important
role in reporting the errors and increasing the
safety of patient on one hand and on the other
hand leads to the development and improvement
of the system to reduce medical errors. For these
purposes, different methods of medical error
reporting are used in many countries (20-21).
The results of the present research showed that
repeated error reporting, particularly, written
Table 2. Frequency Distribution of Expert Opinions about the
Recording of the Events
Third
stage
result
Second
stage
result
First stage

149. result
No opinion
frequency
(percent)
Disagree
Frequency
(percent)
Agree
frequency
(percent)
Opinion
Item
* * remove 4 (13.3) 14 (46.7) 12 (40) Arbitrary recording the
error
R
eco
rd
in
g
M

150. eth
o
d
confirm reassessment reassessment 9 (30) 5 (16.7) 16 (50.3)
Compulsory reporting the error
* confirm reassessment 9 (30) 6 (20) 5 (16.7) Animosity of the
reporter of error
* * remove 9 (30) 13 (43.3) 8 (26.7) Known reporter of error
* confirm reassessment 5 (16.7) 3 (10) 22 (73.3)
Confidentiality of the error
recorded
confirm
reassessm
ent
reassessment 5 (16.7) 7 (23.3) 18 (60)
Recording the error by the
committer
* * confirm 4 (13.3) 0 (0) 26 (86.7)
Recording immediately after the
incidence
confirm reassessment reassessment 11(36.7) 2 (6.7) 17 (56.7)
Rewarding the error recorder C
h

151. aracteristic o
f
reco
rd
in
g
th
e
ev
en
ts
* * remove 9 (30) 18 (60) 3 (10) Punishing the error recorder
* * confirm 1 (3.3) 1 (3.3) 28 (93.3) Plain design
* * confirm 1 (3.3) 1 (3.3) 28 (93.3) Clear design
* * confirm 0(0) 0 (0) 30 (100) Comprehendible design
* * confirm 0 (0) 0 (0) 30 (100)
In line with the goals of care and
control
* * confirm 0 (0) 2 (6.7) 28 (93.3) Recording the time of error
A
t least o
f

152. elem
en
ts
*
reassessm
ent
reassessment 4 (13.3) 4 (13.3) 22 (73.3)
Recording the responsibility of
the reported
* * confirm 0 (0) 0 (0) 30 (100) Recording the cause
* * Confirm 0 (0) 1 (3.3) 29 (96.7) Recording the damage due to
error
* confirm Reassessment 3 (10) 6 (20) 21 (70) Internet m
ed
ia
* * confirm 4 (13.3) 10 (33.3) 16 (50.3) electronic
* * confirm 2 (6.7) 5 (16.7) 23 (76.7) Hospital information
system
Rangraz Jeddi F, et al

153. Health, Spirituality and Medical Ethics - Vol.2, No.2, Summer
2015
ones by the matrons and educational supervisors
is necessary. While the use of posters and
brochures are also suggested for this purpose .
Jerico suggested the use of educational
intervention program to increase the incidence
of medical error reports (22). The result of a
study conducted in an educational hospital
indicated that 54.8 percent of the physicians
knew the method of reporting medical errors
and only 39.5 percent of them were familiar
with what errors need to be reported (23). In
another study, 98 percent of the health workers
were aware of the reporting system while 25
percent knew how to use these reports (24).
Mcneil et al. reported that 71 percent of the
medical workers were familiar with the system

154. of error reporting (25). White et al. indicated
that only 31 percent of the intern and resident
students received instruction about how to
complete an error reporting form (26). All these
evidence show that reporting the medical errors
is necessary and must be consistently
performed.
The present research emphasized that recording
the errors has to be obligatory, anonymous and
confidential. It should also be done immediately
after the incidence along with rewarding the
reporter. Simple and comprehensible design,
recording the time and cause of the harm in
addition to the status of person committing the
error were confirmed as the minimum measures
of recording .
This is similar to the results of investigators that
claimed the medical error reports must be

155. confidential with no punishment consequences
and unrelated to the authorities exercising
punishing act in addition to being simple and
comprehensible and provide the opportunity to
report the incidence (7, 8, 17, 27, 28). These
systems need to be designed in a way that
maintains the identity of the reporter
anonymously and keeps the records
confidentially (27, 29). In addition, the
information related to the incident should
include the cause of error, the harm inflicted and
the reason for the occurrence (8, 27). Some of
studies in this regard suggest other information
such as the date of incidence and reception of
report, ward of the hospital where the event took
place and the severity of incident is recorded
Table 3. Frequency Distribution of Expert Opinion about the
Analysis of Medical Errors

156. Opinion
Item
Agree
Number (%)
Disagree
Number (%)
No opinion
Number (%)
Result of first stage
Need to analyze 29 (96.7) 1 (3.3) 0 (0) confirm
Cases examined
cause 30 (100) 0 (0) 0 (0) confirm
Reason of recurrence 29 (96.7) 0 (0) 1 (3.3) confirm
Type of analysis
quantitative 19 (63.3) 4 (13.3) 7 (23.3) confirm
qualitative 26 (86.7) 1 (3.3) 3 (10) confirm
analyzer
Statistical software 21 (70) 3 (10) 6 (20) confirm
statistician 17 (56.7) 4 (13.3) 9 (30) confirm
Medical record expert 14 (46.7) 6 (20) 10 (33.3) remove
Hospital's matron 16 (53.3) 5 (16.7) 9 (30) confirm

157. Expert of medical error 29 (96.7) 0 (0) 1 (3.3) confirm
* did not have second and third stage
Table 4. Frequency Distribution of Expert Opinion about the
Feedback and Reporting the Result of Analysis of Medical
Errors
Opinion
Item
Agree
Number (%)
Disagree
Number (%)
No opinion
Number (%)
Result of
first stage
Goal
Error reduction 27 (90) 2 (6.7) 1 (3.3) confirm
Classifying errors 27 (90) 0 (0) 3 (10) confirm
Method of maintaining
confidential 24 (80) 1 (3.3) 5 (16.7) confirm
Non-confidential 4 (13.3) 18 (60) 8 (26.7) remove
Retrieval method