In this section, the results of the CIIs are presented. Because the objective of the CIIs was to assess the actual risks for patients, the results in this section are presented for the actual causes (see section 3.4.4).
Summary of the data and data processing: OR CIIs
The original n of interviews = 20. The n of interviews used for analysis = 17 which means in this case that the n of discussed and analysed incidents = 17 (each interview yielded one incident). The data below relate to this number of 17 interviews/incidents. The n of causes = 98 of which the n of actual causes = 84 and the n of possible causes = 14. After classification of these causes according to the ECM—in which some causes were classified in more than one classification category—the n of actual causes = 96 and the n of all causes (i.e. both actual and possible) = 113. The n of recovery factors = 22 of which 14 were successful. The classified causes were used for comparison with the classified causes of the FMEA. For comparison with FMEA causes relating to the anaesthesia-operating part of the FMEA, the n of CIIs which relates to the anaesthesia-operating part of the CIIs = 13, the n of classified actual causes = 81, and the n of all the classified causes (i.e. both actual and possible) = 92. See also table 8.1 on page 256. The n of structural causes found = 20, see table 4.7 on page 112.
For reasons of reliability, the causes that were found by the CIIs were classified by the same persons who classified the causes of the FMEA and under the same conditions, see section 4.5. In order to determine to which classification category a cause could be assigned, the description Kanse [72] gave of the classification categories of the ECM was used and adapted by Van der Hoeff [151], see also appendix E. The classification results were examined by Van der Schaaf, researcher at the Eindhoven University of Technology (EUT), to validate the results. As a result of this, sixteen alterations were made in the classification categories of the causes in question.
The results of the classification of the causes of the CIIs are presented in figure 4.4 on the following page for the four main classification categories: technical failure, organisa- tional failure, human failure and X (i.e. unclassifiable).
The detailed classification results are given in figure 4.5 on the next page.
The causes and the recovery factors that were found by analysing the CIIs are pre- sented in two tables. The causes are presented in table 4.7 on page 112 and the recov- ery factors in table 4.8 on page 113. Both the causes and the recovery factors were
Technical failure: 6% Organisational failure: 36%
Human failure: 56%
X: 1%
Figure 4.4. Distribution of the classified OR CII causes per main classification category: n of CIIs = 17 and n of causes = 96. ‘X’ means unclassifiable.
Figure 4.5. Frequency distribution of classified OR CII causes per classification category: n of CIIs = 17 and n of causes = 96. The classification categories are explained in appendix E.
4.4 CIIs 111
anonymized and generalised because of the confidential nature of the CIIs.
Of the 22 recovery factors mentioned, 8 did not result in successful actual recovery.12 It turns out that recovery factors (read: remarks) were missed because of people’s failure to pay attention to each other. On the one hand, recovery factors should be taken ad- vantage of, and taking advantage of them should be encouraged; on the other hand, if a recovery remark was made, it was often ignored, even though the reluctance to make these recovery remarks was great. This reluctance was due to the gulf between doctors and employees.
All 17 incidents had one or more recovery factors. This emphasises the importance of an optimal use of these factors which may have a favourable effect on the outcome of an incident.
During the CIIs, information was collected that resulted in additional analysis. These research questions concerned:
1. Making FONA reports of incidents.
a) How many of the incidents were reported to the FONA committee?
Out of a total of 17 incidents that were analysed, 6 were also reported to the FONA committee.
b) What was the distribution of the incidents which were reported and those which were not reported to the FONA committee, if a distinction is made be- tween incidents with demonstrable temporary or permanent physical effects (accidents) on the one hand, and incidents with no demonstrable effects on patients (near accidents) on the other hand?
This question was answered although:
− It is difficult to determine whether or not an incident has effects on a patient, and what these effects are.
− It is difficult to determine the effects on patients indirectly via an inter- view.
In order to determine to what extent incident types were reported to the FONA committee, the number of FONA reports per incident type is pre- sented in table 4.9 on page 113.
The results in table 4.9 on page 113 were tested by means of the Fisher ex- act probability test13 which showed no difference between the distributions
12I.e. if attention had been paid to such a recovery remark, then the outcome of an incident—the top
event—would probably have been less serious for the patient.
13In this research, all data were tested using the SAS software version 6.12. For every test, the value for the
Table 4.7. Overview of the structural incident causes which were found using the CIIs in the OR.
Structural incident causes found using the CIIs
• On the anaesthesia list there is no specific space to report incidents • There is no uniformity of medicine stickers on ampoules and syringes • Doctors ignore remarks made by nurses
• There is no proper protocol that keeps everyone in the OR informed of which medicines are new and in which concentration they are available
• Filling in the different medical records before a patient is operated on is mandatory but is often
not performed
• Surgeon leaves the operating room too casually while the patient is being operated on
• Turning off the alarms during the induction phase and forgetting to turn them on again after- wards
• Inadvertent failure to make FONA reportsa
• Failing to take action about the dangerous situation of the ‘forgotten switch’b(this is(/these are)
one(/two) switch(es) which people forget to turn on/off: the respirator is then hand-operated in-
stead of in the ventilation state, and the patient is not insufflated)
• No involvement of anaesthesia assistants in the purchase of anaesthesia equipment
• Not calling in a surgeon outside one’s own discipline for assistance when faced with problems during an operation though the need for assistance is obvious
• Assigning patients to a certain discipline is based on which day of the week it happens to be and
not on the availability of a surgeon who is sufficiently competent to carry out the operation
• Although antibiotics should be supplied during operations, they were not • X-ray technician is not experienced enough
• Only one X-ray examination tube available in the OR • Equipment in the recovery is not uniform
• Because surgeons habitually blame the instrumentarium for setbacks during the operation, com- plaints about the instrumentarium are not always taken seriously by the operating assistant which results in defective instrumentarium continuing to be used. By not always taking the surgeon’s complaints seriously, the operating assistant prevents instruments from being unnecessarily re- placed only because of the surgeon’s irritation
• Mixing up the data of patients with the same name but different dates of birth
• Equipment in the ICU makes too much noise which leads to errors because people misunder- stand each other (NB: this cause relates to the ICU, of course)
• Failure to perform a check in a given situation because doing so would annoy a colleague because he has already checked
aBecause: − it was an error, and was not omitted on purpose; − it was not considered necessary; − no attention
was given to it; − it was considered the specialist’s job; − FONA was not considered an important issue (the (departmental) management did not consider this necessary); − after the operation, it was hoped that things would go all right: the complication did not emerge until later; − the incident was caused by equipment; − the incident was recognised in time, and it concerned a near accident.
4.4 CIIs 113
Table 4.8. Overview of the recovery factors which were found using the CIIs in the OR.
Recovery factors found using the CIIs
• Drawing attention to the fact that an injection is being given into artery instead of into vein • Patient is intubated by chance
• Drawing attention to patient being injected with painkiller rather than with sleep-inducing drug • The box containing the prothesis is opened by chance, and the prothesis appears to be unsterile • Patient’s thorax is open which made direct heart massage possible
• Heart-lung machine is connected • A report that a gauze is missing • Missing gauze is finally found
• Pre-oxygenate patient with 100% oxygen • Observing sallow face and blue lips • Observing blue lips
• Making remarks that method for inserting object into patient is wrong • Making remarks about not working in compliance with sterility requirements • Correct ideas about possible diagnosis
• Finding out by chance that patient does not wish to be operated on
• X-ray examination tube is accidentally already being used to position patient instead of when the patient is already under surgery: it turns out that X-ray examination tube is not working
• Finding out that alarm is off by checking the print-out of the time recorder
• During earlier operations, it had already been noticed that instruments were not working cor- rectly (but nothing was done about it)
• Putting medications ready so as to have them to hand
• Observing that patient’s medical record is incorrect: left and right turn out to have been switched round
• Observing that there is a mismatch between patient’s medical record and reality
• By accidentally putting a question to the patient, it is noticed that patient’s data have been mixed up
Table 4.9. The number of FONA reports per incident type discussed during the OR CIIs: n of discussed incidents which were classified as accidents = 11 (with n of causes = 73), n of incidents discussed which were classified as near accidents = 6 (with n of causes = 23), n of CIIs where a FONA report was made of the discussed incident = 6 (with n of causes = 46), n of CIIs where no FONA report was made of the discussed incident = 11 (with n of causes = 50).
Accident Near accident
No FONA report 6 5
Table 4.10. The number of FONA reports, and the number of FONA reports omitted, of incidents discussed by doctors and employees during the OR CIIs: n of CIIs where a FONA report was made of the incident discussed = 6 (with n of causes = 46), n of CIIs where no FONA report was made of the discussed incident = 11 (with n of causes = 50), n of doctors interviewed = 6 (with n of causes = 26), n of employees interviewed = 11 (with n of causes = 70).
FONA No FONA
Doctors 2 4
Employees 4 7
(p = 0.3334). Table 4.9 on the preceding page shows that the greater part of the accidents and near accidents were not reported to the FONA committee. c) Is there a difference between doctors and employees with regard to the num-
ber of FONA reports they make?
The results in table 4.10 were tested with the Fisher exact probability test (p = 1.0000), showing that, comparatively speaking, doctors and employees are equally bad at or remiss in reporting incidents to the FONA committee. d) What are the causes found by the FONA committee with regard to the inci-
dents which were both discussed during the CIIs and reported to the FONA committee?
The results of the 6 CIIs, the incidents of which were also reported to the FONA committee, were compared with the classification and conclusions of the FONA committee. For 4 of the 6 CIIs, FONA reports were found in the FONA archives; the remaining 2 were not found. This may mean that these incidents had never been reported to the FONA committee, although the interviewees said they had been. On the basis of the data on the FONA reporting forms, it was only partly possible to reconstruct the 4 incident de- scriptions. So, it is possible that the FONA committee drew the wrong con- clusions, also because there was often no consultation between the reporter(s) and the FONA committee. The distribution of the causes per main classifi- cation category of incidents with and without a FONA report, is presented in figure 4.6 on the facing page. The Fisher exact probability test was used to test the data of figure 4.6 on the next page. The test shows that there are no grounds for establishing a difference between the two distributions (p = 0.1457).
4.4 CIIs 115
Figure 4.6. Relative frequency distributions of the classified OR CII causes per main classification category in the case of incidents in which there was a FONA report and those in which there was no FONA report. In the case of a FONA reports, n of CIIs = 6 and n of causes = 46, and in the case of no FONA reports, n of CIIs = 11 and n of causes = 50. ‘X’ means unclassifiable.
Table 4.11. The number of accidents and near accidents discussed by doctors and employees during the OR CIIs: n of incidents discussed which were classified as accidents = 11 (with n of causes = 73), n of incidents discussed which were classified as near accidents = 6 (with n of causes = 23), n of doctors interviewed = 6 (with n of causes = 26), n of employees interviewed = 11 (with n of causes = 70).
Accidents Near accidents
Doctors 4 2
Employees 7 4
2. Incidents. The distribution of incidents in accidents and near accidents, and the reporting of different kinds of incidents by doctors and employees.
The results of reporting different kinds of incidents by doctors and employees are presented in table 4.11. The ratio of accidents and near accidents discussed during the CIIs is about the same for doctors and employees (Fisher exact probability test, p = 1.0000).
The distribution of incident causes in which there is an accident or a near accident, is presented in figure 4.7 on the next page. The Fisher exact probability test was used to test the data of figure 4.7 on the facing page. The test shows that there are no grounds for establishing a difference between the two distributions (p = 0.2934). 3. The effects of haste and fatigue.
The CIIs can be divided into incidents in which there was ‘fatigue’ and ‘no fatigue’, and into incidents in which there was ‘haste’ and ‘no haste’.
‘Haste’ is understood to refer to ‘emergency operation’. This was the case in three incidents which all occurred in the evening.
‘Fatigue’ is understood to refer to a situation in which an operation was still going on after four o’clock in the afternoon or was performed in the evening. In the case of all three incidents in which there was haste, fatigue also played a role too (i.e. in this case the emergency operations were performed in the evening, see above). The distributions of incident causes in which there is haste and fatigue are presented in figure 4.8 on page 118 and figure 4.9 on page 119. The Fisher exact probability test was used to test the data of figures 4.8 on page 118 and 4.9 on page 119. For figure 4.8 on page 118, the Fisher exact probability test shows that there are no grounds for establishing a difference between the two distributions (p = 0.2634).
4.4 CIIs 117
Figure 4.7. Relative frequency distributions of the classified OR CII causes per main classification category in the case of incidents which were classified as accidents and those which were classified as near accidents. In the case of accidents, n of CIIs = 11 and n of causes = 73, and in the case of near accidents, n of CIIs = 6 and n of causes = 23. ‘X’ means unclassifiable.
Figure 4.8. Relative frequency distributions of the classified OR CII causes per main classification category in the case of incidents in which there was haste and those in which there was no haste. In the case of haste, n of CIIs = 3 and n of causes = 25, and in the case of no haste, n of CIIs = 14 and n of causes = 71. ‘X’ means unclassifiable.
For figure 4.9 on the facing page, the Fisher exact probability test shows that there is a convincing difference between the two distributions (p = 0.0189), and cell chi- square shows no cell which contributes in a convincing manner to this difference. In this research, the value chosen to call a cell informative in the case of cell chi-square is 6¼ [129]. (Among statisticians, there is no unanimity about this value for the determination of informative cells. The value of 6¼ corresponds to a probability of 0.012 of calling a cell erroneously informative. Other values common among statisticians are 3.84, 4 and 9, so 6¼ is quite a safe value.)
4. Incidents discussed by doctors and employees.
Figure 4.10 on page 120 shows the distributions of causes of incidents discussed by doctors and employees. The Fisher exact test shows that there are no grounds for establishing a difference between the two distributions (p = 0.607).
4.4 CIIs 119
Figure 4.9. Relative frequency distributions of the classified OR CII causes per main classification category in the case of incidents in which there was fatigue and those in which there was no fatigue. In the case of fatigue, n of CIIs = 6 and n of causes = 56, and in the case of no fatigue, n of CIIs = 11 and n of causes = 40. ‘X’ means unclassifiable.
Figure 4.10. Relative frequency distributions of the classified OR CII causes per main classifica- tion category in the case of incidents which were discussed by doctors and which were discussed by employees. In the case of doctors, n of CIIs = 6 and n of causes = 26, and in the case of employees, n of CIIs = 11 and n of causes = 70. ‘X’ means unclassifiable.
4.4 CIIs 121
4.4.3 Conclusions and recommendations
Conclusions about the CIIs In the OR, human failure is the largest failure category, fol- lowed by organisational failure. The three classification categories in which most causes are classified are in descending order (from large to small): the organisational factor of ‘operating procedures’ (ECM: OP), the human behaviour factor of ‘planning’ (ECM: HR 5) and the organisational factor of ‘management priorities’ (ECM: OM) (see ap- pendix E for the ECM).
For the Fisher exact probability tests performed for the tables 4.9 on page 113, 4.10 on page 114 and 4.11 on page 116, it should be noted that a larger number of incidents—the number of 17 incidents is quite small—may lead to different test results.
Although the Fisher exact probability test shows no difference between the distribu- tions in table 4.9 on page 113, the data in table 4.9 give an indication that, in the case of the near accidents, the vast majority is not reported. This could be explained by the fact that, in accordance with hospital policy, doctors are requested to report accidents also to the FONA committee.
Table 4.10 on page 114 shows that the willingness to report incidents to the FONA committee is the same for doctors and employees.
The fact that only 6 of the 17 incidents were reported to the FONA committee (ta- ble 4.9 on page 113), may indicate that the number of FONA reports is not a good indi- cator of the real number of incidents in a department. However, in the FONA database only 4 of these 6 incidents reported to the FONA committee were to be found. It is possible that 2 interviewees were wrong and that only 4 (instead of 6) FONA reports were made of the 17 incidents. A comparison of the results of these 4 CIIs with the cor- responding 4 FONA reports, shows that it is not possible to get a clear and complete picture of an incident on the basis of the FONA report. This is because of the use of a