Table 1: Sociodemographic characteristic of COVID-19 infection among healthcare
workers in Kedah (N=1679)
Variables N (%)
Age group 1154 (68.7)
<40 years
40 years 525 (31.3)
Gender
Male 537 (32.0)
Female 1142 (68.0)
Ethnicity
Malay 1495 (89.0)
Non-Malay 184 (11.0)
Comorbid
Yes 264 (15.7)
No 1415 (84.3)
Job Category
Doctor 291 (17.3)
Nurses 618 (36.8)
Assistant Medical Officer 113 (6.7)
Pharmacy 39 (2.3)
Dentistry 55 (3.3)
Allied Health 75 (4.5)
Support service 406 (24.2)
Administrative staff 82 (4.9)
Workplace setting
Hospital setting 1258 (74.9)
Non-hospital setting 421 (25.1)
Reason of screening
Contact with family member or friend 469 (27.9)
Contact with patient/ work colleague 489 (29.1)
Symptomatic screening 616 (36.7)
Targeted screening* 105 (6.3)
Managing COVID-19
Yes 134 (8.0)
No 1545 (92.0)
Completed vaccine
Yes 1311 (78.1)
No 368 (21.9)
Symptomatic
Yes 1261 (75.1)
No 418 (24.9)
CT value (n=1515)
<30 1095 (72.3)
30 420 (27.7)
*e.g. mass screening, pre placement, pre-admission, living at PKPD area
a Fisher exact was performed due to some cells contain less than 5
294
Table 2: Comparison of healthcare associated and non-healthcare associated
COVID-19 infection among healthcare workers in Kedah (N=1679)
Variables Non healthcare- Healthcare- p-value
associated associated 0.007
Age group (n=1125) 0.099
<40 years (n=554) 0.018
749 (64.9) 0.005
40 years 376 (71.6) 405 (35.1) 0.001
Gender 149 (28.4)
345 (64.3) 0.009
Male 780 (68.3) 192 (35.7) <0.001a
Female 362 (31.7)
Ethnicity 1016 (68.0) 0.594
Malay 109 (59.2) 479 (32.0) <0.001
Non-Malay 75 (40.8) <0.001
Comorbid 210 (74.2) <0.001
Yes 915 (65.5) 73 (25.8)
No 481 (34.5)
Job Category 166 (57.0)
Doctor 424 (68.6) 125 (43.0)
Nurses 76 (67.3) 194 (31.4)
Assistant Medical Officer 24 (61.5) 37 (32.7)
Pharmacy 43 (78.2) 15 (38.5)
Dentistry 60 (80.0) 12 (21.8)
Allied Health 275 (67.7) 15 (20.0)
Support service 57 (69.5) 131 (32.3)
Administrative staff 25 (30.5)
Workplace setting 821 (65.3)
Hospital setting 304 (72.2) 437 (34.7)
Non-hospital setting 117(27.8)
Reason of screening 464 (98.9)
Contact with family member 5(1.1)
or friend 4 (0.8)
Contact with patient/ work 485 (99.2)
colleague 611 (99.2)
Symptomatic screening 46 (43.8) 5 (0.8)
Targeted screening* 59 (56.2)
Managing COVID-19 87 (64.9)
Yes 1038 (67.2) 47 (35.1)
No 507 (32.8)
Completed vaccine 913 (69.6)
Yes 212 (57.6) 398 (30.4)
No 156 (42.4)
Symptomatic 947 (75.1)
Yes 178 (42.6) 314 (24.9)
No 240 (57.4)
CT value (n=1515) 837 (76.4)
<30 204(48.6) 258(23.6)
216 (51.4)
30
295
Table 3: Clinical presentation of the COVID-19 cases (N=1679)
Variables Number Percentage
Type of Symptoms 631 37.6
Fever 618 36.8
Runny Nose 587 35.0
Cough 476 28.3
Sore throat 208 12.4
Headache 184 11.0
Anosmia 136 8.1
Myalgia/Arthralgia 56 3.3
Ageusia 35 2.1
Diarrhea 19 1.1
Shortness of breath 40 2.4
Others 418 24.9
Asymptomatic
418 24.9
Category COVID-19 1255 74.7
Category I 0.1
Category II 1 0.2
Category III 4 0.1
Category IV 1
Category V 87.2
1464 11.3
Treatment Centre 189 1.5
Home Quarantine 26
Hospital 99.9
PKRC 1678 0.1
Recovery 1
Recovered
Died
DISCUSSION
The study aim to compare the characteristics of healthcare associated and non-
healthcare associated COVID-19 infection among HCWs in Kedah and to describe
the clinical characteristics. In this study, the prevalence of healthcare-associated
COVID-19 infection among HCW was 33%. Crude analysis showed significant
differences (p-value <0.05) with the healthcare-associated infection were age group
of less than 40 years, Non-Malay, no comorbid, job category, working at a hospital
setting, incomplete vaccination, asymptomatic and level of CT-value of more than
30.
First, our result showed cases who work in hospital settings were significantly higher
in the healthcare–associated infection group. The enclosed and crowded working
environment at the hospital setting such as air-conditioning ward, on-call room and
296
pantry could be the contributing factors as compared to working at a health clinic
which was more open and naturally ventilated (Tan-Loh & Mun Keong Cheong,
2021). Based on the study finding, strengthening infection prevention and control
measures such as wearing appropriate PPE, disinfection, sterilization and good
ventilation is important in preventing healthcare-associated transmission.
Second, our result also showed not vaccinated or incomplete vaccination was
significantly higher in the healthcare –associated infection group. It has been well
established COVID-19 vaccination play a critical role in reducing COVID-19
transmission and disease severity (CDC., 2021) . Hence, it is very important to
ensure high vaccination coverage among healthcare workers who are the front liner
in combating COVID-19 infection.
Third, asymptomatic cases were significantly higher in the healthcare-associated
infection group. A meta-analysis by Ma et al reported the pooled percentage of
asymptomatic infections among confirmed COVID-19 cases in the community was
40.5% (Ma et al., 2021). The percentage was even higher at 47.53% among nursing
home residents and staff. The high percentage of asymptomatic infections
emphasises the potential transmission risk of asymptomatic infections. Our study
confirmed the finding that asymptomatic HCW was a factor associated with the
transmission of COVID-19 at healthcare setting.
Fourth, the risk factor for healthcare-associated infection was a Ct value more than
30. A cycle threshold value represented the number of nucleic acid amplification
cycles that occurred before a specimen containing the target material generates a
signal greater than the predetermined positivity threshold. Generally, the higher the
Ct value the lower the quantity of viral load present in the sample. Ct value of more
than 30 was usually considered a high Ct value and low viral load. The high Ct value
also may indicate the exposure was old and the virus isolation was later as compared
to the symptom onset. Singanayagam et al reported in the first week of symptom
onset, the geometric mean (GM) of Ct value were 28.18 and in the second week
(days 8 to 14), GM Ct was 30.65 and after 14 days, GM Ct was 31.60
(Singanayagam et al., 2020). Therefore, risk assessment and contact tracing should
be conducted as early as possible for early screening and isolation to prevent
healthcare transmission.
Our study reported, HCWs suffering from COVID-19 had mild symptoms and
favorable outcomes. This could be due to the majority of cases being at younger
age group, with no comorbid and high vaccination coverage.
297
Based on the study findings, we would like to recommend a good surveillance
system for early testing, reporting, isolating, and vaccination as they remain the key
strategies in protecting HCW and ensuring continuity of the health system. We also
would like to recommend instilling public health practices such as wearing
appropriate PPE, social distancing, and practicing new norms to reduce the disease
transmission in the workplace.
This study has limitations. First, there is a possibility that the source of the infection
of healthcare-associated infection is community-acquired and vice versa. This
classification bias was minimized by ensuring a thorough investigation was
conducted to identify the source of infection. Second, some important variables were
not included in this study such as compliance to appropriate PPE and ever received
training on infection control. Third, the analysis of this study is limited to bivariate
analysis, hence further multivariate analysis is required to determine the predictors
for healthcare-associated COVID-19 infection among HCW.
CONCLUSION
The study reported that 33% of the COVID-19 cases among HCW in Kedah were
classified as healthcare-associated. We found factors significantly higher in
healthcare-associated infection were age group less than 40 years, Non-Malay, no-
comorbid, among doctor and pharmacy, working at a hospital setting, incomplete
vaccine, asymptomatic and CT value more than 30 as compared to the non-
healthcare associated group. The identified factors will help to plan for control
measures to prevent healthcare-associated transmission. The study also found
HCWs with COVID-19 had mild symptoms and favorable outcomes.
ACKNOWLEDGEMENT
The authors would like to thank the Director General of Health Malaysia for his
permission to publish this article and Kedah State Health Department for the
administrative support.
REFERENCES
CDC (2021) COVID-19 Vaccines are Effective. Available at:
https://www.cdc.gov/coronavirus/2019-
ncov/vaccines/effectiveness/index.html
Hashim, J. H., Adman, M. A., Hashim, Z., Mohd Radi, M. F. and Kwan, S. C. (2021)
‘COVID-19 Epidemic in Malaysia: Epidemic Progression, Challenges, and
298
Response’, Frontiers in Public Health. Frontiers Media S.A., 9, p. 247. doi:
10.3389/FPUBH.2021.560592/BIBTEX
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., … Cao, B. (2020). Clinical
features of patients infected with 2019 novel coronavirus in Wuhan, China.
The Lancet, 395(10223), 497–506. http://doi.org/10.1016/S0140-
6736(20)30183-5
Ma, Q., Liu, J., Liu, Q., Kang, L., Liu, R., Jing, W., … Liu, M. (2021). Global
Percentage of Asymptomatic SARS-CoV-2 Infections Among the Tested
Population and Individuals With Confirmed COVID-19 Diagnosis: A
Systematic Review and Meta-analysis. JAMA Network Open, 4(12), 1–18.
http://doi.org/10.1001/jamanetworkopen.2021.37257
Ministry of Health Malaysia. (2021). COVID-19 Management Guidelines in Malaysia
No.5 / 2020, 1–3.
Singanayagam, A., Patel, M., Charlett, A., Bernal, J. L., Saliba, V., Ellis, J., … Gopal,
R. (2020). Duration of infectiousness and correlation with RT-PCR cycle
threshold values in cases of COVID-19, England, January to May 2020.
Eurosurveillance, 25(32), 1–5. http://doi.org/10.2807/1560-
7917.ES.2020.25.32.2001483
Tan-Loh, J., & Mun Keong Cheong, B. (2021). A descriptive analysis of clinical
characteristics of COVID-19 among healthcare workers in a district specialist
hospital. Medical Journal of Malaysia, 76(1), 24–28.
Wong, L. Y., Tan, A. L., Leo, Y. S., Lee, V. J. M., & Toh, M. P. H. S. (2020).
Healthcare workers in Singapore infected with COVID-19: 23 January-17
April 2020. Influenza and Other Respiratory Viruses, 00(August), 1–9.
http://doi.org/10.1111/irv.12803
299
WILLINGNESS TO PAY (WTP) FOR SALIVA TEST KIT AMONG
HEALTHCARE WORKERS IN KEDAH
Rosidah Omar1, Nur Haryanie Haron1
1Occupational and Environmental Health Unit, Kedah State Health Department
*Corresponding author: Rosidah Omar, [email protected]
ABSTRACT
Background: Saliva test kit is an important screening tool for early identification.
However, the willingness-to-pay (WTP) for the testing kit remains unclear. The
objectives of this study is to identify the willingness to pay for the saliva test kit and
to identify attitude and practice and financing mechanism preference for the saliva
test kit.
Methodology: A cross sectional study was conducted among HCW in Kedah on
13th October 2021. The WTP were obtain through an open and closed-ended
questionnaire via online Google form.
Results: The study found WTP for saliva test kit was RM6.75 or USD 1.59 which is
lower as compared to selling price of RM19 at the time of study. The study found
four factors influencing on the WTP for saliva test kit include female, tertiary
education, professional group and household income >RM5000 (p-value <0.005).
Majority of the respondents believed that individuals did not need to pay out of pocket
for saliva test (60.2%). Instead, respondents prefer employers (64.1%), government
(67.4%) and health insurance (70.4%) to pay fully for the saliva test kit.
Conclusion: The study results helped decision-maker to decide on policy of saliva
testing among HCW. This study findings could also facilitate government to set
appropriate market price to ensure the affordability and accessibility of the saliva test
kit.
Keyword: Willingness to Pay, saliva test kit, COVID-19, self-test, financial COVID-
19, healthcare worker
300
INTRODUCTION
The Coronavirus disease 2019 (COVID-19) pandemic has caused significant
morbidity and mortality in the world. As of 23rd December 2021, 277,520,342 cases
and 5,393,232 death has been reported globally (“Worldometer,” 2021). Many
countries practicing movement control order as a strategy to curb the pandemic.
However, further movement control order is irrelevant due to its impacts on social
and economic sectors. Other than vaccination, early identification and rapid isolation
remain key strategies to curb the pandemic relies on the presence of adequate
testing capacity.
With the opening of more economic sectors, schools and, educational institutions, it
is essential for people to self-test periodically. The COVID-19 saliva test kit entered
the Malaysian market at the end of July 2021 and is available at retail pharmacies
and private health clinics for a price unit of RM39.90 (Dzafri, 2021). The price was
further reduced and a new ceiling price of the saliva test kit was announced by the
Ministry of Domestic Trade and Consumer Affairs and fixed at RM19.90 starting 5th
November 2021 (Veena Babulal, 2021).The saliva test kit was used as a self-
administered screening test and positive test result required further confirmation
using RT-PCR according to the Ministry of Health guidelines at that time. The test
results should be self-reported into the MySejahtera application (Ministry of Health
Malaysia, 2021)
Healthcare workers are the front liner in combating COVID-19. According to the
Ministry of Health, 1.2% of healthcare worker (HCW) under the MOH have been
infected with COVID-19 during the pandemic period (Ministry of Health Malaysia,
2021). Early identification is important to prevent healthcare-associated infection of
COVID-19. Therefore, rapid saliva testing is an essential screening tool for HCW for
early identification. Currently, the Ministry of Health supplies the saliva test kit for
HCW however it is a one-off supply limited for the purpose of outbreak management
involving health facilities. Other than work-related purposes, HCW are required to
buy the saliva test kit themselves.
The willingness to pay (WTP) for the testing kit is still not clear. Hence the objectives
of this study are to identify the willingness to pay for the saliva test kit among HCW
in Kedah and to identify attitude, practice and financing mechanism preference for
the saliva test kit.
301
METHODOLOGY
This is a cross sectional study and was conducted among HCW in Kedah on 13th
October 2021.The study used convenience sampling and the sample size was 621
HCW. A questionnaire was developed based on previous studies assessing on
willingness to pay and was distributed via online medium using Google form (Azzeri,
Laziz, Ithnin, & Jaafar, 2021; Wang et al., 2021).
The study variables include: 1) Sociodemographic characteristics; 2) Attitude and
practice for saliva test kit 3) Financing mechanism preference 4) Willingness to pay
for saliva test kit. Payment scale and open-ended method were used to collect the
value for WTP. For the payment scale, respondent was asked to answer how much
they are willing to pay for one test starting with “RM5”, “RM10”, “RM15”, “RM20”,
“RM25”, “RM30”, “RM35”, “RM40”, “willing to pay at any price”. The price range was
set to cover private market prices on saliva test kit in the market. As for the open
ended question, respondent was asked to report WTP by themselves.
Descriptive analysis was used to describe the sociodemographic characteristic.
Results for continuous data were presented as median and IQR for skewed data.
Mann-Whitney test was done to establish association between exposure variable
and outcome variable. We conducted a multivariate Tobit regression to identify
factors influencing the WTP with coefficient, standard errors (SE) and p-value
reported. Level of significant was set at 0.05. Data was analyzed using STATA
RESULTS
Respondent Characteristics
Table 1 shows the sociodemographic characteristic of the study participants for the
WTP survey. Overall, the survey included 621 respondents from all over health
facilities in Kedah. Majority of the participants were female (68.3%), Malay (90.5%),
married (78.9%), tertiary education (81.6%), support group (68.4%), permanent
worker (86.8%). About 31 (5%) had side income and 9 (1.5%) received financial
aids.
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Table 1: Sociodemographic characteristics of study participants (N=621)
Variable Frequency Percentage
Gender
Male 197 31.7
Female 424 68.3
Ethnicity
Non-malay 59 9.5
Malay 562 90.5
Marital status
Single 131 21.1
Married 490 78.9
Education
Primary/Secondary 114 18.4
Tertiary 507 81.6
Job Category
Support group 425 68.4
Professional 196 31.6
Employment status 82 13.2
Contract 539 86.8
Permanent
Chronic Illness
No 541 87.1
Yes 80 12.9
Side income
No 590 95.0
Yes 31 5.0
Financial aid 612 98.5
No
Yes 9 1.5
Willingness to pay for saliva test kit
Table 2 presents the distribution of WTP by the close ended and open ended for
saliva test kit. For closed ended question, the mean (SD) WTP recorded values was
RM7.66 (RM4.76). Meanwhile for open ended question recorded lower mean WTP
values at RM6.75 (RM5.39). Both open-ended and close-ended question revealed
median WTP for saliva test kit was RM5 (IQR=RM5)
Table 2: Distribution of WTP for saliva test kit Mean SD Median IQR
Variable
Willingness to pay for 1 test (close ended RM7.66 4.76 RM5 RM5
question, n=614) RM6.75 5.39 RM5 RM5
Willingness to pay for 1 test (open ended
question, n=621)
Normality testing was conducted to determine the distribution of WTP values. Since
the distribution were skewed, Mann-Whitney test was implied to determine the
association between sociodemographic characteristic and WTP values. Table 3
303
shows distribution of HCW’s mean willingness to pay by sociodemographic
characteristic. For open ended question, significant higher mean WTP were
recorded among females, HCW with tertiary education, professional group and
household income of more than RM5000 per month (p value <0.05).
Table 3: Distribution of HCW’s mean WTP by sociodemographic characteristic (N=621)
Variable Mean WTP (RM) P value
Gender 5.87 0.0010
Male 7.58 0.3635
Female 0.1813
7.26 0.0921
Ethnicity 7.02 0.0488
Non-malay 0.0001
Malay 8.20 0.5090
6.73 0.2980
Marital status 0.5579
Single 7.64 0.4222
Married 6.76 0.9822
0.0002
Workplace 6.09
Hospital 7.25
Non-hospital
6.30
Education 8.63
Primary/Secondary
Tertiary 7.63
6.95
Job Category
Support group 6.67
Professional 7.35
Employment status 7.13
Contract 6.475
Permanent
5.77
Length of services 7.11
<10 years
10 years 7.05
6.11
Chronic Illness
No 6.41
Yes 7.91
Side income
No
Yes
Financial aid
No
Yes
Monthly Household income
<RM5000
RM5000
304
Perception and attitude
Tables 4 shows the attitude and practice about saliva test kit. During the survey,
majority of the respondents answered they will do saliva test before travelling for
work purpose (483, 77.8%), before travelling for social visit (483, 77.8%), after come
back from travelling (495, 79.7%), before attending meeting or training involving
more than 50 participants (449, 72.3%), before attending meeting or training involved
participants from other districts or states (465, 74.9%), being symptomatic (586,
94.4%) and being a close contact (580, 93.4%)
Table 4: Attitude and practice about saliva test kit (N=621)
Variables Frequency Percentage
483 77.8
I will do saliva test before travelling for work purposes Yes 138 22.2
483 77.8
No 138 22.2
495 79.7
I will do saliva test before travelling for social visit Yes 126 20.3
449 72.3
No
172 26.7
I will do saliva test after come back from travelling Yes 465 74.9
No 156 25.1
586 94.4
I will do saliva test before attending meeting or training Yes 35 5.6
580 93.4
involving more than 50 participants 41 6.6
No
I will do saliva test before attending meeting or training Yes
involve participants from other districts or states
No
I will do saliva test if symptomatic Yes
No
I will do saliva test if I am a close contact Yes
No
Financing preference for saliva test kit
Table 5 presents respondent’s financing mechanism preference for saliva test kit.
Majority of the respondents believed that individuals did not need to pay out of pocket
for saliva test (374, 60.2%). Meanwhile 142 respondnets or 22.8% believed
individual need to pay a portion for the saliva test and only 105 or 17.0% believed
individuals need to pay fully. In contrast, respondents believe employers (399,
64.2%), government (418, 67.3%) and health insurance (438, 70.5%) need to pay
fully for the saliva test kit.
305
Table 5: Financing mechanism preference for saliva test kit Frequency Percentage
Variables 374 60.2
Individuals need to pay out of pocket No
for saliva test 142 22.8
Yes, pay for a 105 17.0
portion 95 15.3
Yes, pay fully 127 20.5
Employers need to pay for saliva test No
Yes, pay for a 399 64.2
portion 69 11.1
Yes, pay fully
Governments need to pay for saliva No 134 21.6
test
Yes, pay for a 418 67.3
portion 103 16.6
Yes, pay fully
Health insurance needs to pay for No 80 12.9
saliva test
Yes, pay for a 438 70.5
portion
Yes, pay fully
DISCUSSIONS
The aims of this study is to identify the willingness of HCW in Kedah to pay for the
saliva test kit. In this study, we found WTP for a saliva test kit was RM6.75 or USD
1.59 (the price year 2022). This is lower as compared to the selling price of RM19.90
or USD 4.54 (the price year 2022) at the time of the study. The WTP was also lower
than a previous study conducted in Kenya which reported a mean WTP for saliva
test kit value of USD 5.59 (Kazungu et al., 2021). The difference could be due to
different populations being studied where private pharmacy clients tend to pay out-
of-pocket payments to get the medical test kit or medication. Meanwhile, this study
was conducted among public HCW where normally their treatment cost was fully
subsidized by the government. Hence the willingness to pay might be lower
compared to the private pharmacy client.
The study found four factors influencing the WTP for saliva test kits include females,
tertiary education, professional group and household income >RM5000. Females
had higher WTP as compared to males could be due to they are more health-
conscious, and have higher health literacy (Lee, Lee, & Kim, 2015). The Professional
groups were willing to pay more for saliva test kits as compared to support groups
could be due to they had higher education and monthly income. It is consistent with
the previous finding that reported education and income factors were the main
factors influencing WTP (Noor Aizuddin, Sulong, & Aljunid, 2012; Wang et al., 2021).
306
The study showed awareness on indication to do the saliva test was excellent where
majority thought they should get tested before or after traveling, attending crowd
meeting, symptomatic or being a close contact. Although the awareness was very
good, surprisingly the majority of respondents (60.2%) were not willing to pay out-
of-pocket for the saliva test kit. Since they are not willing to pay, the respondent
stated it’s the government, employers, and insurance company’s responsibility to
pay for the saliva test kit.
At the moment, MOH HCW in Kedah were encouraged to do saliva tests before or
after traveling and attending crowd meetings for the work purposes. To facilitate this,
the test kit was available at the nearest health clinics and hospitals using the one-off
supply subsidized by the Ministry of Health. Should the subsidized discontinuation,
the cost of the saliva test kit might need to be incurred by the out-of-pocket payment.
Therefore, this study finding could also facilitate the government to set appropriate
market prices to ensure the affordability and accessibility of the saliva test kit.
This study is not without limitations. First, this study was conducted among
healthcare workers in Kedah, the findings may not be generalized to other
populations or other states in Malaysia. Second, bidding method is more accurate
method to determine WTP (Azzeri et al., 2021). In this bidding method, respondents
were asked on WTP with prices increased or decreased depending on the answers
given.
CONCLUSION
The study reported WTP for saliva test kits among HCW in Kedah was RM6.75 or
USD 1.59. Factors influencing WTP include females, tertiary education, professional
group, and household income. The awareness on indication to do the saliva test was
excellent, nonetheless the majority of respondents were not willing to pay out of
pocket for the saliva test kit and stating its government, employers and insurance
company’s responsibility. The study results helped the decision-maker to decide on
policy of saliva testing among HCW. This study finding could also facilitate the
government to set appropriate market prices to ensure the affordability and
accessibility of the saliva test kit.
ACKNOWLEDGEMENT
The authors would like to thank the Director General of Health Malaysia for his
permission to publish this article We would also like to thank the Kedah State Health
Department for the administrative support.
307
REFERENCES
Azzeri, A., Laziz, N. A. A., Ithnin, M., & Jaafar, H. (2021). Ability to Pay and
Willingness to Pay for Covid-19 Vaccination: Are we Ready? Malaysian
Journal of Public Health Medicine, 21(1), 347–355.
http://doi.org/10.37268/MJPHM/VOL.21/NO.1/ART.1006
Dzafri, R. (2021, July 20). Malaysia approves two RM39.90 Covid-19 self-test kits,
here’s what you need to know. Retrieved from
https://malaysia.news.yahoo.com/malaysia-approves-two-rm39-90-
032852008.html
Kazungu, J., Mumbi, A., Kilimo, P., Vernon, J., Barasa, E., & Mugo, P. (2021).
Level and determinants of willingness to pay for rapid COVID-19 testing
delivered through private retail pharmacies in Kenya.
Lee, H. Y., Lee, J., & Kim, N. K. (2015). Gender Differences in Health Literacy
Among Korean Adults: Do Women Have a Higher Level of Health Literacy
Than Men? American Journal of Men’s Health.
http://doi.org/10.1177/1557988314545485
Ministry of Health Malaysia. (2021). COVID-19 Management Guidelines in
Malaysia No.5 / 2020, 1–3.
Noor Aizuddin, A., Sulong, S., & Aljunid, S. M. (2012). Factors influencing
willingness to pay for healthcare. BMC Public Health, 12(S2), 2458.
http://doi.org/10.1186/1471-2458-12-s2-a37
Veena Babulal. (2021). Ceiling price of Covid-19 self-test kits fixed at RM19.90
from Sunday. New Straits Times. Kuala Lumpur.
Wang, J., Lyu, Y., Zhang, H., Jing, R., Lai, X., Feng, H., … Fang, H. (2021).
Willingness to pay and financing preferences for COVID-19 vaccination in
China. Vaccine, 39(14), 1968–1976.
http://doi.org/10.1016/j.vaccine.2021.02.060
Worldometer. (2021). Retrieved December 23, 2021, from
https://www.worldometers.info/coronavirus/
308
ISLAND HEALTH: PREVALENCE OF COVID-19 INFECTION
AMONG HEALTHCARE WORKERS IN LANGKAWI DISTRICT
Dr Muhammad Suhaili Bin Muhammad Shueib1, Dr Fahrulshima Binti
Saliholdin1, Siti Nur Asma Binti Zakaria1, Reena Rohayu Binti Romainor1, Dr
Nurulaini Binti Abdullah1
1Langkawi District Health Office
Corresponding author: Dr Nurulaini Binti Abdullah, Family Medicine Specialist, Langkawi District
Health Office, 013-3631644 (Tel)
ABSTRACT
Background: Healthcare Workers (HCWs) are the frontliner in combating COVID-
19 and they were at high risk of contracting the disease. Understanding COVID-19
infection among HCWs is important to plan for the outbreak management and control
measures to ensure the safety of our frontliner. The study aims to determine the
prevalence and to describe the sociodemographic and clinical characteristics of
COVID-19 infection among HCW in Langkawi.
Methodology: This is a retrospective cross-sectional. The study used data collected
from 1st January 2021 until 31st December 2021. We reported the prevalence of
COVID-19 infection among HCW at Pejabat Kesihatan Daerah Langkawi and
Hospital Sultanah Maliha and study variables included sociodemographic and
clinical characteristics of the cases.
Results: Overall, 67 or 6.73% of total HCW in Langkawi District was infected with
COVID-19 in 2021. The majority of the cases were Malay (94%), female (79%), age
group 30-39 years (46%), no comorbid (97%), working in Hospital Sultanah Maliha
(64%), and from the non-professional group (82%). With regards to clinical
characteristics, all cases were diagnosed with Category 2, out of which 96% were
treated under home quarantine and only three (4%) required hospital admission. The
cases had favorable outcomes where all were fully recovered.
Conclusion: HCWs represent a critical component in fighting against the COVID-
19 pandemic and they are at high risk of contracting the infection. A good
surveillance system in testing, contact tracing, isolating, and strengthening infection
and preventive control measures are the key strategies in combating COVID-19
infection.
Keyword: COVID-19, Healthcare Worker, Prevalence, Langkawi District.
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INTRODUCTION
The first case of coronavirus disease 2019 (COVID-19) caused by severe acute
respiratory syndrome coronavirus 2 (SARS-CoV-2) was documented in Wuhan,
China, in December 2019 (Huang et al., 2020). The COVID-19 had spread fast
worldwide which posed threats to global health. World Health Organization (WHO)
had declared the outbreak as a pandemic on 11 March 2020. Multiple interventions
were planned and carried out to contain this pandemic such as social distancing,
wearing a facemask, and even city lockdown. However, these varying degree of
implementation that had been planned has not effectively stopped the spread of
COVID-19 as the cases are continually being reported worldwide. As in Malaysia, to
contain the spread, Malaysia implemented the first, Movement Control Order (MCO)
beginning on 18 March 2020 until 12 May 2020. This Movement Control Order
implementation was continued and being executed accordingly based on the
number of cases reported.
During this pandemic, in Malaysia, until 3rd January 2022, a total of confirmed cases
reported are 2 757 044 cases with 39 733 active cases (Ministery of Health
Malaysia., 2022). Healthcare workers (HCW) are undoubtedly among the most high
risk group to get infected. In the past outbreak, on 23 April 2020, a total of 325 HCW
under the Ministry of Health was reported with confirmed positive cases. They carry
a high risk of infection due to daily exposure to management COVID-19 patients and
also potential infection from the community. Based on the report, 70% of them were
infected through community transmission and not while handling patients.
Langkawi District is one of the famous tourist destinations in Malaysia. As the city of
tourism, the health agency is responsible for preventing the spread of COVID-19 in
this area in order to help and maintain Langkawi as the main tourist attraction even
in this pandemic period. HCW was assigned several new roles and tasks to ensure
Langkawi District remain safe for the local citizen and tourists such as COVID-19
sampling center, COVID-19 Assessment Center, COVID-19 Quarantine Center and
Special ward or Intensive Care for COVID-19 patients. These lead to new exposure
for each HCWs to the COVID-19 infection. Even though, HCW were trained on the
COVID-19 infection preventive control, the risk of contracting the disease was high
at workplace and also from the community. Understanding the prevalence of
COVID-19 infection among HCW in Langkawi District is indispensable for the
planning of prevention and control measures. Hence, the objective of this study is to
determine the prevalence of COVID-19 infection among HCWs in Langkawi District
and to describe the sociodemographic and clinical characteristics of the cases.
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METHODOLOGY
This was a cross-sectional study. Study populations were HCW of Langkawi District
Health Office and Hospital Sultanah Maliha infected with COVID-19 infection in 2021
including permanent and contract posts. The study period was from 1st January 2021
until 31st December 2021. We used universal sampling where we included all
positive cases among HCW in Langkawi during the period of inclusion. Study
variables included sociodemographic characteristics such as ethnicity, gender, age
group, place of work (Hospital Sultanah Maliha or Langkawi District Health Office),
and job category. We also measured the clinical characteristics such as comorbidity,
COVID-19 category, place of treatment and disease outcome.
Data Collection and Analysis
The data was extracted from Langkawi District Health Office COVID-19 Crisis
Preparedness and Response Centre (CPRC). It is based on numbers of reported
confirmed positive COVID-19 cases among HCWs for the period of 1st January 2021
until 31st December 2021. The information on sociodemographic and clinical
characteristics was gathered from the standard investigation form from the
occupational health unit. The data were analyzed descriptively using Microsoft Excel
version 2020
RESULTS
Sociodemographic Characteristic
In 2021, there was a total of 996 HCW in Langkawi District in Hospital Sultanah
Maliha and Langkawi District Health Office including permanent and contract posts.
There were 67 HCW being reported confirmed positive COVID-19 cases in 2021.
This represents 6.73% of HCW being diagnosed with COVID -19 in Langkawi District
in 2021.
Table 1 shows the sociodemographic and clinical characteristics of the cases. Out
of 67 HCW positive COVID-19 cases, majority were Malay with 63 cases (94%).
While Chinese and Indian reported 2 cases respectively. By gender, there were 53
(79%) females being reported confirmed positive cases while only 14 (21%) males
being reported. It is also shown that the majority of the cases were from the age
group 30 – 39 years old with 31 cases (46%), followed by age between 20 – 29
years old with 24 cases (36%), 40 – 49 years old with 10 cases (15%) and 50 – 59
years old with 2 cases (3%). Also, 43 or 64% of the cases working in Hospital
Sultanah Maliha, while 24 (36%) were from Langkawi District Health Office staff.
Findings also showed the majority of the cases were from “Kumpulan Sokongan 1
and 2” or non-professional such as nurses, medical assistants, laboratory assistants,
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and others with 55 (82%) cases. While Professional groups such as medical officers
only constituted 12 or 18% of total cases. The majority of the cases (97%) have no
comorbid. Only two cases had underlying Diabetes Mellitus. With regards to clinical
characteristics, all cases were diagnosed with Category 2, out of which 64 or 96%
were treated under home quarantine and only three (4%) required hospital
admission. The cases had favorable outcomes where all were fully recovered.
Table 1: Sociodemographic and Clinical characteristics of COVID-19 infection
among HCW in Langkawi (N=67)
Characteristics Malay N (%)
Ethnicity Chinese
Indian 63 (94%)
Gender 2 (3%)
Age Group Female 2 (3%)
Male
Place of Work 53 (79%)
20 – 29 14 (21%)
Job category 30 – 39
Comorbidity 40 – 49 24 (36%)
COVID-19 50 – 59 31(46%)
Categories 10 (15%)
Hospital Sultanah Maliha 2 (3%)
Place of treatment Langkawi District Health
Office 43 (64%)
Recovery 24 (36%)
Professional
Non-Profesional 12 (18%)
Diabetes Mellitus 55 (82%)
No Comorbid
2 (3%)
Category 1 65 (97%)
Category 2
Category 3 0 (0%)
Category 4 67 (100%)
Category 5
0 (0%)
Home quarantine 0 (0%)
Quarantine and Low Risk 0 (0%)
Treatment Center (PKRC)
Hospital Admission 64 (96%)
Fully recover 0 (0%)
3 (4%)
67 (100%)
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DISCUSSIONS
The study aims to describe the prevalence, sociodemographic and clinical
characteristics of COVID-19 infection among HCW in Langkawi. The study found the
prevalence of COVID-19 infection among HCW was 6.73%. The prevalence is lower
than the study reported by Nienhaus and Hod (2020) where they reported
prevalence of COVID-19 infection among HCW in Malaysia was 9.1% (Nienhaus &
Hod, 2020). The difference could be due study by Nienhaus and Hod reported
prevalence based on total HCW who has been tested. Meanwhile, in this study, we
measured prevalence based on total HCW working in Langkawi, as data on HCW
who has been screened was limited. It should be noted that, even though the number
was lower, the prevalence should be given attention since the risk of contracting and
spreading the disease to their family member, work colleagues and patients are high.
The risk was described in multiple studies such as in a prospective cohort study done
by Pandemic Epidemiology Consortium in their study of the Risk of COVID-19
among front-line HCW and the general community (Nguyen et al., 2020). The large-
scale study was conducted in the United Kingdom (UK) and United State of America
(USA) among 2035395 community individuals and 99795 frontline healthcare
workers and stated 5545 incident reports of a positive COVID-19 test over 34 435
272 person-days. The study concluded frontline healthcare workers were at
increased risk for reporting a positive COVID-19 test as compared to the general
community(Nguyen et al., 2020).
With regards to sociodemographic characteristics, we found the majority of the cases
were among Malay and females. This was corresponding to demographic data of
HCW in Langkawi where the majority were from these two groups. Also, most of the
cases were in the young age group of 30 – 39 years old, followed by age of 20 – 29
years old. This could be due to the majority of HCW in the Langkawi District being
within this age group. Other than that, in this age group, they were highly mobile,
hence the risk of contracting the disease from the community was higher. Identifying
the high risk age group is important as the Center for Disease Control and Prevention
(CDC), stated the risk of developing complications of COVID-19 was higher in the
elder age group where they might need hospitalization, intensive care, or a ventilator.
This study showed the majority of the cases were working in hospital settings. This
could be due to long working hours, crowded or enclosed environments in hospital
settings increasing the risk of contracting the infection as compared to the more open
and airy environment in the health clinic setting. Our study also showed high cases
among a non-professional group such as nurses, assistant medical officers, support
services and others. The finding was consistent with other studies that reported high
risk occupational categories such as nursing staff and support service (Eyre et al.,
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2020). This could be due to these groups of occupation they tend to have close
physical contact with patients, perform aerosol-generating procedures, and work
with patients who may be extremely ill and infectious.
The study also found the majority of the cases were without comorbid. This could be
due to the majority of cases being in the young age group. It is important to identify
comorbidity since a person with underlying medical conditions were at a greater risk
of contracting COVID-19 such as diabetes, cardiovascular, or lung disease. They
were not only at a higher risk of developing severe illness but were also at an
increased risk of death if they become ill.With regards to clinical characteristics, our
study reported the majority of the cases were mild where all were categorized as
category 2 of COVID-19 infection and recovered. This could be due to the majority
of the cases being in the young age group, no comorbid and having been vaccinated.
Since they had mild disease, most of them required outpatient treatment and were
put under home quarantine. Only three cases required hospital admission since they
were pregnant and further monitoring and assessment of the mother and baby was
required.
CONCLUSION
HCWs represent a critical component in fighting against the COVID-19 pandemic
and they were at heightened risk of infection. This study reported the prevalence of
COVID-19 among HCW in Langkawi was 6.73%. We also reported higher
prevalence among the young age group, no comorbid, non-professional group, and
working in the hospital setting. The identified high risk group of contracting COVID-
19 should inform policymakers to plan for a targeted intervention program to prevent
COVID-19 infection among HCW. A good surveillance system in testing, contact
tracing, isolating, and strengthening infection and preventive control measures were
the key strategies to curb the pandemic of COVID-19.
ACKNOWLEDGEMENT
The authors would like to express gratitude to all team members involved in this
study. Also, Langkawi Health District Office and Hospital Sultanah Maliha in assisting
the data collection for completion of this study. The authors would also like to thank
the Director General of Health Malaysia for his permission to publish this article.
314
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from 1 January 2021 – 31 December 2021, Langkawi District Health Office.
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Available online: https://covidnow.moh.gov.my/cases. (Accessed on 3 January
2022).
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Jangkitan Penyakit Coronavirus 2019 (COVID-19) di Malaysia. Putrajaya: Ministry
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Malaysia. International Journal of Environmental Research and Public Health,
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Available online: https://covid19.who.int/. (Accessed on 3 January 2022)
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“BURNOUT” DALAM KALANGAN PETUGAS KESIHATAN
PEJABAT KESIHATAN DAERAH (PKD) DAN IBU PEJABAT
JABATAN KESIHATAN NEGERI (IPJKN) KEDAH SEMASA
PANDEMIK COVID-19
Juliana M.Lazim1, Azrin Isa1, M.Shafuden Othman1, Ooli Gunalan Manickam2,
Mohd Husrul Ari Husin3
1Unit Psikologi Kaunseling, Jabatan Kesihatan Negeri Kedah
2Bahagian Pengurusan, Jabatan Kesihatan Negeri Kedah
3Unit Kawalan Penyakit Tidak Berjangkit, Jabatan Kesihatan Negeri Kedah
*Corresponding author: Juliana Ikhzawati Mohamed Lazim, [email protected],
ABSTRAK
Latar belakang: Burnout ditakrifkan sebagai satu sindrom yang berkaitan dengan
persekitaran kerja berisiko dan stress yang tidak diuruskan dengan baik. Ianya
melibatkan perasaan dalaman dan menjejaskan keupayaan mental yang seterusnya
diterjemahkan melalui kemerosotan prestasi dan kemahiran tugas seseorang.
Kajian berdasarkan soal-selidik ini dilaksanakan untuk mengenal-pasti burnout
dengan menggunakan Copenhagen Burnout Inventory dalam kalangan petugas
kesihatan Pejabat Kesihatan Daerah di Negeri Kedah dan mengesyorkan langkah-
langkah yang harus diambil bagi mengatasinya.
Keputusan: Seramai 2150 petugas kesihatan terlibat dalam kajian ini yang
melibatkan 557 petugas kesihatan lelaki dan 1593 petugas kesihatan perempuan.
Daripada dapatan kajian mendapati 31% petugas kesihatan mengalami burnout
berkait peribadi, 18% burnout berkait kerja dan 9.8% burnout berkait pesakit.
Beberapa faktor yang dikaitkan dengan burnout adalah kumpulan umur petugas,
jantina, dan daerah.
Kesimpulan: Terdapat hubung-kait rapat kejadian burnout semasa Pandemik
Covid-19 dengan petugas kesihatan. Burnout berkait peribadi adalah lebih tinggi
berbanding kerja dan pesakit. Tiada perbezaan ketara dalam kalangan petugas
kesihatan perempuan dan lelaki berkaitan burnout. Petugas kesihatan berumur
kurang 40 tahun mengalami burnout yang lebih ketara berbanding kumpulan umur
melebihi 40 tahun. Manakala daerah Kuala Muda dan Kulim mencatatkan kadar burnout
paling tinggidalam kalangan petugas kesihatan di negeri Kedah. Kajian mencadangkan
agar pihak pengurusan perlu mengambil langkah-langkah bagi meningkatkan
suasana persekitaran kerja yang baik dan kondusif bagi mengurangkan burnout
dalam kalangan petugas kesihatan.
Kata Kunci: Burnout, Copenhagen Burnout Inventory, Covid-19
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PENGENALAN
Pada penghujung Disember 2019, peningkatan bilangan pesakit pneumoniadengan
sebab jangkitan yang tidak diketahui ditemui di Wuhan, China. Virus penyebab
kemudiannya dikenal pasti sebagai sindrom pernafasan akut teruk Coronavirus 2
(SARS-CoV-2), dan pneumonia novel ini dipanggil penyakit Coronavirus 2019
(COVID-19). Ia serta- merta menjadi ancaman kesihatan global kepada orang
awam, walaupun dalam tempoh inkubasi. Dengan peningkatan kes yang mendadak
dilaporkan di luar China, Pertubuhan Kesihatan Sedunia (WHO)mengisytiharkan
wabak COVID-19 sebagai pandemik pada 11 Mac 2020 (Wu, J.T, et al., 2020).
Pandemik COVID-19, telah menunjukkan tahap kebimbangan yang lebih tinggi
dalam kalangan petugas kesihatan China berbanding dengan populasi umum (Pan,
R., et al.,2020). Sejumlah 42.5% daripada petugas kesihatan Thailand dikenal pasti
mempunyai sekurang-kurangnya simptom kebimbangan ringan (Apisarnthanarak,
A., et al, 2020). Satu lagi kajian mendedahkan bahawa 64.7%, 51.6%, dan 41.2%
daripada petugas kesihatan Turki masing-masing menunjukkan simptom
kemurungan, kebimbangan, dan tekanan (Eibay, R.Y.,et al., 2020).
Burnout tidak sinonim dengan keletihan, tekanan, atau kemurungan dan diketahui
memberi kesan kepada profesion seperti petugas kesihatan. Kekurangan tenaga
atau keletihan emosi, emosi negatif yang berkaitan dengan pekerjaan seseorang,
dan mengurangkan kecekapan professional adalah tergolong dalam kategori
burnout (Roslan, N.S., et al, 2021). Penyelidikan terdahulu telah mengaitkan
burnout kepada pelbagai kesan seperti penjagaan kendiri dan pesakit,
pengurangan tahap profesionalisme, empati , keselamatan pesakit, kerja
berpasukan dan peningkatankadar medical errors and attritions (Syahirah, M. et
al.,2020). Kebiasaaan burnout yang tinggi telah dikenal-pasti dalam kalangan
petugas kesihatan pasca bencana alam, namunterdapat juga kajian yang turut
menyatakan ‘burnout’ berlaku dalam suasana pandemik (Roslan, N.S., et al,
2021). ‘Burnout’ boleh disebabkan oleh beban kerja yang meningkat dan
kekurangan tenaga kerja,termasuk konflik nilai, dan kaitan ini telah berkembang
luas lagi semasa COVID-19 (West, C.P., et al., 2018). Burnout juga boleh
berpunca daripada pengorbanan besar yang tidak seimbang dan kepuasan yang
rendah, menjadikan petugas kesihatan yang paling berdedikasi berasa terdedah
kepada burnout, terutamanya dalam masa pandemik (Iacovides, A., et al., 2003).
Walaupun beberapa kajian menjelaskan prevalans kemurungan, kebimbangan
dan tekanan, tetapi kurang diketahui tentangburnout petugas kesihatan (WHO,
2020). ‘Burnout’ boleh ditakrifkan sebagai sindrom akibat tekanan keterlaluan di
tempat kerja yang tidak berjaya diuruskan. Oleh itu, berdasarkan keterangan di
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atas, kajian ini dijalankan untuk melihat isu yang melibatkan burnout. Pengkaji
berhasrat untuk mengenal-pasti burnout dalam kalangan petugas kesihatan
Pejabat Kesihatan Daerah Negeri Kedah. Burnout akan dikategorikandalam tiga
dimensi iaitu burnout-peribadi, burnout-kerja dan burnout-hubungan dengan
pesakit.
OBJEKTIF KAJIAN
Dalam kajian ini, pengkaji ingin mengenalpasti burnout berkait peribadi, burnout
berkait kerja dan burnout berkait pesakit dalam kalangan petugas kesihatan
Pejabat Kesihatan Daerah Negeri Kedah. Pengkaji juga ingin mengenalpasti
dimensi tertinggi burnout. Hasil dapatan kajian ini penting untuk merancang
program pencegahan yang merangkumi aspek kesihatan mental petugas
kesihatan Pejabat Kesihatan Daerah Negeri Kedah.
KEPENTINGAN KAJIAN
Tekanan dalam hidup dan kerja akan memberikan kesan terhadap kesihatan dan
kesejahteraan hidup seseorang individu. Persekitaran kerja yang berisiko dan
bahaya akan menyebabkan petugas kesihatan seperti pegawai perubatan dan
jururawat mengalami tekanan atau stress dan seterusnya memberikan kesan
terhadap kesihatan diri seperti burnout. Kualiti dan prestasi kerja juga akan
terkesan jika petugas kesihatan mengalami burnout. Semua lapisan petugas
kesihatan adalah terdedah dengan burnout dan ianya akan menjejaskan kualiti
hidup, risiko mengidapi penyakit dan kesan negatif terhadap kesihatan mental atau
psikologi. Penglibatan dan usaha-usaha dalam menangani Covid-19 di Malaysia
ternyata memerlukan kajian yang dapat menterjemahkan masalah psikologi dan
kelaziman ‘burnout’ yang dihadapi oleh petugas kesihatan agar dapat dikenal-pasti
dan seterusnya mengambil langkah atau pendekatan yang sesuai.
METODOLOGI
Kajian dijalankan dengan menggunakan borang soal selidik dalam bentuk ‘Google
Form’ antara 2 Ogos 2021 sehingga 5 Oktober 2021 dengan memuatkan pautan
inventori ‘Copenhagen Burnout Inventory’ melalui laman web rasmi Jabatan
Kesihatan Negeri Kedah. Copenhagen Burnout Inventory (CBI) ialah soal selidik
yang ditadbir sendiri yang dibangunkan oleh Kristensen et al. yang memfokuskan
kepada tiga dimensi: burnout peribadi, burnout berkaitan kerja dan burnout
berkaitan pesakit. Ia mengandungi 19 item, dan respons kepada item ini dinilai
pada skala dalam peratusan iaitu ‘sentiasa’ (100%), kerapkali (75%), kadang-
kadang (35%), jarang-jarang (25%) dan tidak pernah (0%). Jumlah peratus untuk
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setiap dimensi dipuratakan untuk mendapatkan purata markah. Purata markah 35%
dan ke atas menunjukkan berlakunya burnout bagi dimensi tersebut dan purata
markah di bawah 35% menunjukkan tidak burnout. CBI mempunyai
kebolehpercayaan dan kesahan yang memuaskan menurut Kristensen TS et al.
(2005). Data yang diperolehi dianalisa secara kuantitatif dengan menggunakan
SPSS versi 20 (IBM Corp., Ar monk, NY, USA). Kaedah statistik deskriptif digunakan
untuk memeriksa prevalans burnout peribadi, burnout kerja dan burnout berkaitan
pesakit. Analisa chi-square digunakan untuk mencari hubungan yang signifikan
antara setiap pembolehubah tidak bersandar ((jantina, umur dan daerah) dan
dimensi burnout . Data yang diperolehi disimpan dalam Google Form dan hanya
seorang sahaja penyelidik yang mempunyai akses kepada data-data tersebut.
DAPATAN
Sampel Demografi
Sejumlah 2204 petugas kesihatan di pejabat-pejabat kesihatan daerah danklinik
kesihatan seluruh negeri Kedah telah menjawab borang soal selidik dalam talian,
dengan kadar tindak balas 99.9%. Pengkaji telah mengeluarkan lima puluh empat
sampel kerana maklumat tidak lengkap menjadikanjumlah sampel 2150 petugas
kesihatan.
Analisa Kajian
Jadual 1 menunjukkan ciri-ciri demografi petugas kesihatan yang terlibat dalam
kajian (n=2150). Majoriti responden adalah perempuan (74.1%), berumur 22-40
tahun (69.1%) dan dari daerah Kota Setar (16.9%) diikuti Kubang Pasu (12.7%)
dan Bandar Baharu (9.7%).
Prevalans keseluruhan burnout berkait peribadi, kerja dan pesakit di dalam sampel
ini masing-masing adalah 31%, 18% dan 10%. Jadual 2 menunjukkan ciri-ciri
‘Burnout’ semasa COVID 19. Di kalangan petugas yang mempunyai burnout
peribadi, prevalens paling tinggi adalah dikalangan petugas perempuan (74.9%),
petugas berumur 22-40 tahun (76.5%) dan dari daerah Kota Setar (16.1%).
Walaubagaimanapun, analisa chi-square menunjukkan terdapat perbezaan
signifikan yang menunjukkan burnout peribadi adalah lebih tinggi dikalangan
responden yang berumur 22-40 tahun, dari daerah Kuala Muda, Kulim, Kubang
Pasu, Pendang, Baling dan Langkawi (p <0.001) berbanding petugas yang tiada
burnout peribadi.
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Jadual 1: Ciri-ciri demografi petugas kesihatan yang terlibat dalam kajian (n=2150)
Ciri-ciri demografi n(%)
Jantina 557 (25.9)
1593 (74.1)
Lelaki
1485 (69.1)
Perempuan 665 (30.9)
Umur
22 – 40
41 – 59
Daerah 363 (16.9)
Kota Setar 130 (6.0)
Kuala Muda 196 (9.1)
Kulim 272 (12.7)
Kubang Pasu 197 (9.2)
Padang Terap 150 (7.0)
Pendang 177 (8.2)
Baling 108 (5.0)
Sik 188 (8.7)
Yan 208 (9.7)
Bandar Baharu 161 (7.5)
Langkawi
Jadual 2 juga menunjukkan untuk burnout berkait kerja, majoriti kes adalah
dikalangan petugas perempuan (72%), berumur 22-40 tahun (80.6%) dan dari
daerah Kota Setar (19.7%). Analisa chi-square menunjukkan terdapat perbezaan
signifikan yang menunjukkan burnout berkait kerja adalah lebih tinggi untuk ciri umur
22-40 tahun (p<0.001) dan dari daerah Kota Setar, Kuala Muda, Kulim, Kubang
Pasu, Pendang, Baling, Sik dan Langkawi ( p <0.001) berbanding yang tiada
burnout berkait kerja. Sementara itu, untuk burnout berkait pesakit, prevalens paling
tinggi juga adalah dikalangan petugas perempuan (68.2%), berumur 22-40 tahun
(77.7%) dan daerah Kota Setar (19%). Analisa chi-square menunjukkan terdapat
perbezaan signifikan yang menunjukkan burnout berkait pesakit adalah lebih tinggi
untuk ciri umur 22-40 tahun (p<0.001) dan daerah Kota Setar, Kuala Muda, Kulim,
Pendang dan Baling ( p <0.001) berbanding yang tidak mempunyai burnout berkait
kerja.
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Jadual 2: Prevalans ‘Burnout’ Semasa COVID 19 Berdasarkan Ciri-Ciri Petugas
Kesihatan PKD. (n=2150)
Burnout Berkait p-value Burnout Berkait p- Burnout p-
Peribadi Kerja value Berkait Pesakit value
n (%) n (%) n (%)
Ya Tidak Ya Tidak Ya Tidak
Jantina 0.237 0.583 0.021
Lelaki 167 389 (26.2) 108 448 (25.4) 67 489
(25.1) (28.0) (31.8) (25.2)
Perempuan 498 1096(73.8) 278 1316(74.6) 144 1450
(74.9) (72.0) (68.2) (74.8)
Umur <0.001 < 0.109
0.001
22 – 40 509 976 (65.7) 311 1174(66.5) 164 1321
(76.5) (80.6) (77.7) (68.1)
41 – 59 156 509 (34.3) 75 590 (33.5) 47 618
(23.5) (19.4) (22.3) (31.9)
Daerah < 0.001 <0.001 <
0.001
Kota Setar 107 264 (17.8) 76 295 (16.7) 40 331
(16.1) (19.7) (19.0) (17.1)
K. Muda 59 71 (4.8) 35 95 (5.4) 16 114
(8.9) (9.1) (7.6) (5.9)
Kulim 70 126 (8.5) 43 153 (8.7) 27 169
(10.5) (11.1) (12.8) (8.7)
K. Pasu 86 187 (12.6) 52 221 (12.5) 24 249
(12.9) (13.5) (11.4) (12.8)
Pdg Terap 58 140 (9.4) 32 166 (9.4) 14 184
(8.7) (8.3) (6.6) (9.5)
Pendang 50 100 (6.7) 32 118 (6.7) 23 127
(7.5) (8.3) (10.9) (6.5)
Baling 63 115 (7.7) 39 139 (7.9) 20 158
(9.5) (8.3) (9.5) (8.1)
Sik 25 83 (5.6) 13 95 (5.4) 8 100
(3.8) (3.4) (3.8) (5.2)
Yan 42 146 (9.8) 12 176 (10.0) 10 178
(6.3) (3.1) (4.7) (9.2)
B. Baharu 49 161 (10.8) 22 188 (10.7) 19 191
(7.4) (5.7) (9.0) (9.9)
Langkawi 56 92 (6.2) 30 118 (6.7) 10 138
(8.4) (7.8) (4.7) (7.1)
Keseluruhan 665 1485(69) 386 1764(82) 211 1939
(31) (18) (10) (90)
321
PERBINCANGAN
i ) Umur
Kajian ini mendapati petugas kesihatan yang berumur kurang daripada 40 tahun
lebih cenderung mengalami burnout berbanding petugas kesihatan yang berumur
lebih dari 40 tahun. Kajian ini selari dengan dapatan kajian oleh Maslach, C. et al.,
2001 dan didapati selari dengan kajian yang dilakukan di United Kingdom,
Sepanyol, Turki dan Jepun (Roslan N. S., et al., 2021).
ii) Daerah
Daerah Kota setar, Kuala Muda, Kulim, Baling dan Kubang Pasu mencatatkan
kadar burnout yang tinggidalam kalangan petugas kesihatan. Daerah-daerah ini
adalah antara daerah yang mempunyai populasi penduduk yang tinggi dan pada
masa data ini diperolehi (Ogos hinggaNovember 2021) jumlah kes COVID 19 harian
di daerah- daerah ini mencatatkan jumlah yang tertinggi dalam negeri Kedah
(https://covidnow.moh.gov.my/cases/kdh). Ini turut menyokong kajian sebelum ini
yang menyatakan beban kerja yang meningkat dan kekurangan tenaga kerja
menyumbang kepada burnout (West, C.P et al, 2018)..
iii) Peribadi
Kajian ini juga mendapati burnout berkait peribadi lebih tinggi berbanding kerja dan
pesakit. Ini disokong oleh kajian Jves J., et al. (2009) dan Goulia, P., et al.
(2010) yang menyatakan faktor utama menyumbang kepada burnout dalam
kalangan petugas adalah kebimbangan tentang kesihatan diri dan keluarga.
iv) Kerja
Kajian ini mendapati 18% petugas kesihatan mengalami burnout berkait kerja dan
dapatan ini disokong oleh kajian Roslan N. S., et al, 2021 yang menyatakan
bahawa jadual tugasan yang lama dan tidak dapat dijangka menyebabkan burnout
yang tinggi dalamkalangan petugas kesihatan sepanjang pandemik apabila tidak
dapatmenguruskan penjagaan anak-anak. Dapatan ini turut disokong oleh Liu, X.,
et al. (2020) menyatakan bahawa waktu bekerja yang panjang, beban kerja yang
tinggi dan shif malam yang banyak, menyumbang kepada burnout dalam kalangan
petugas kesihatan. Waktu bekerja yang panjang juga menyumbang konflik
kepada keluarga kerana kesuntukan masa bersama keluarga. Kekurangan
personal protection equipment (PPE), ventilator, katil pesakit dan juga kakitangan
menambahburuk tekanan yang dialami oleh petugas kesihatan yang
mengakibatkan burnout (Rashid S, 2021). Stigma dilabel pembawa virus kepada
orang ramai menambah tekanandan mempercepatkan keadaan burnout (Sultana
A., et al. 2020).
322
SYOR DAN CADANGAN
Berdasarkan kajian ini, pengkaji dapat mengemukakan langkah-langkahintervensi
mengurangkan burnout dalam kalangan petugas kesihatan kepada tiga peringkat
iaitu peringkat individu, organisasi dan budaya seperti di Jadual 3. Bagi langkah
untuk memberi impak di tahap individu, pihak PTJ boleh menyelia petugas dengan
membahagikan petugas dalam kelompok- kelompok kecil. Dalam kelompok
tersebut petugas dilatih untuk kemahiran penjagaan mental dan fizikal , pengurusan
stres dan kemahiran komunikasi. Di samping pembelajaran psiko-pendidikan,
aktiviti fizikal turut diterapkan, seperti senaman relaksasi dan diet seimbang dalam
pemakanan. Sleep hygiene juga diajar supaya petugas lebih mengambil berat akan
perkara ini. Isu sokongan dari keluarga juga perlu dititikberatkan.
Seterusnya, untuk intervensi di peringkat organisasi, penetapan had kehadiran
bertugas perlu dilaksanakan demi mengekalkan konsistensi penyampaian tugasan.
Dengan ini petugas juga perlu dibimbing untuk merancang cuti rehat dengan
sebaiknya. Pihak atasan atau penyeliaan perlu melibatkan semua petugas dalam
urusan keputusan organisasi. Ini bertujuan untuk mengurangkan perselisihan faham
atau konflik dalam pasukan. Organisasi juga perlu mewujudkan satu pasukan
pelbagai disiplin untuk bantuan psikososial profesional kepada petugas kesihatan.
Ganjaran atau sebarang bentuk penghargaan dan sokongan yang praktikal seperti
penjagaan anak-anak, warga emas dan penjagaan haiwan petugas juga boleh
diwujudkan.
Dalam konteks budaya pula, pendedahan kepada perubahan yang radikal dalam
budaya kerja perlu diperkenalkan agar petugas berada dalam kesiapsiagaan
menghadapi ancaman tersebut. Persekitaran kerja tanpa prejudis akan
membantu mempersiapkan pasukan untuk menghadapi insiden, kecemasan,
bencana, cabaran dan rundingcara. Persekitaran kerja yang kondusif ini akan
mengelakkan daripada berlakunya mencari kesalahanpihak lain dalam tugasan.
Walaupun langkah-langkah tersebut yang disyorkan dalam jadual melibatkan
pegawai perubatan namum boleh diaplikasikan kepada semua skimperkhidmatan
petugas kesihatan dalam menangani burnout. Intervensi Kaunseling melalui
penggunaan teknologi digital seperti telefon bimbit, apps dan internet juga dapat
mengurangkan burnout dan meningkatkan kesihatan mental dalam kalangan
petugas kesihatan. Penggunaan teknologi juga dapat menggelakkan perjumpaan
bersemuka dengan pesakitCovid-19 dan perkhidmatan boleh dilakukan tanpa risiko
yang tinggi.
323
Jadual 3 : Syor dan Cadangan Mengurangkan Burnout Dalam Kalangan Petugas
Kesihatan kepada 3 Impak.
TAHAP IMPAK SYOR DAN CADANGAN
Individu Pembahagian dan penyeliaan kelompok kecil
Organisasi Pembelajaran pengurusan stres
Budaya Latihan penjagaan kendiri dan kemahiran komunikasi
Penekanan kepada aktiviti fizikal, teknik relaksasi, diet
seimbang, “sleep hygiene”, sokongan keluarga dan
kelompok perbincangan kecil
Limitasi waktu bertugas dan sistem syif yang adil
Penglibatan semua petugas dalam keputusan
organisasi
Penubuhan pasukan pelbagai disiplin untuk sokongan
psikososial
Sokongan yang praktikal bagi penjagaan kanak-kanak,
warga emas dan haiwan peliharaan petugas.
Pendedahan kepada perubahan yang radikal.
Persekitaran kerja tanpa prejudis
KESIMPULAN
Kajian ini mendapati prevalans keseluruhan burnout berkait peribadi, kerja dan
pesakit di dalam sampel ini masing-masing adalah 31%, 18% dan 10%. Prevalens
bagi burnout peribadi dan burnout berkait kerja adalah tinggi dikalangan petugas
perempuan dan kategori umur petugas 22-40 tahun. Kajian ini juga mendapati
burnout petugas kesihatan Daerah Kuala Muda dan Kulim mencatatkan kadar
burnout yang paling tinggi berbanding daerah-daerah lain di negeri Kedah.
PENGHARGAAN
Pengarang ingin menucapkan setinggi-tinggi penghargaan kepada Ketua Pengarah
Kesihatan kerana kebenaran menerbitkan artikel ini.
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325
SISTEM GAS PERUBATAN DALAM MENANGANI PANDEMIK
COVID-19: KEJAYAAN JURUTERA OPERASI HOSPITAL
Norman O.1, Mohamad Hafiz M.D.1, Ir. Abdullah A.1, Muhammad Suffian S.,
Muhammad Syauki Y.1, Badrul Hisham M.2, Nurjanatul Naim A.S.2, Edgenta
Mediserve Sdn. Bhd.3
1Bahagian Kejuruteraan, Jabatan Kesihatan Negeri Kedah
2Unit Kejuruteraan Operasi Hospital, Hospital Kulim
3Syarikat Konsesi Hospital
________________________________________________________________________
ABSTRAK
Hospital Kulim dibina pada tahun 1994 dengan kapasiti 320 katil. Peningkatan kes
COVID-19 menyebabkan wad rawatan pesakit diubahfungsi kepada wad COVID-
19. Kemasukan bilangan pesakit COVID-19 yang tinggi di Hospital Kulim telah
memberi tekanan hebat kepada sistem kejuruteraan di Hospital Kulim khususnya
pada Sistem Perpaipan Gas Perubatan Oksigen. Hal ini menjadikan kadar
penggunakan gas perubatan oksigen melebihi had rekabentuk menyebabkan
tekanan gas perubatan oksigen tidak stabil dan menurun ke paras minima. Isu dan
cabaran bagi Sistem Perpaipan Gas Perubatan Oksigen adalah bagi memastikan
tekanan gas perubatan oksigen kekal stabil pada tekanan minimum 3.9 bar sehingga
4.0 bar di terminal unit outlet wad-wad hospital. Seterusnya, peningkatan bilangan
pesakit COVID-19 ini juga memaksa pembukaan wad COVID yang mana telah
menyebabkan keperluan penggunaan gas perubatan oksigen melebihi had
rekabentuk. Cadangan pengasingan penggunaan gas perubatan oksigen di
kawasan kurang penggunaan gas perubatan oksigen seperti Klinik Pakar 4, Klinik
Pakar 5 dan Unit Radiologi, penghentian penggunaan twin-flowmeter di wad-wad,
pembukaan wad COVID secara berasingan dengan menggunakan silinder gas
perubatan oksigen individu kepada pesakit dan kerja-kerja naiktaraf pressure
regulator serta pressure safety valve di loji utama gas perubatan oksigen telah
dilaksanakan sehingga tekanan gas perubatan oksigen kembali stabil.
326
PENGENALAN
Sistem Perpaipan Gas Perubatan Oksigen sedia ada di Hospital Kulim adalah
direkabentuk secara sistem berpusat dilengkapi dengan loji utama tangki gas
perubatan oksigen berkapasiti 20,000 liter cecair perubatan oksigen sebagai primary
system dan sistem automatic manifold gas perubatan oksigen sebagai secondary
system seperti di Rajah 1. Fungsi Sistem Perpaipan Gas Perubatan Oksigen di
Hospital Kulim ini adalah direkabentuk untuk memberi bekalan gas perubatan
oksigen kepada pesakit di hospital.
Rajah 1: Sistem tangki utama gas perubatan oksigen (primary system) dan sistem
automatic manifold gas perubatan oksigen (secondary system)
ISU DAN CABARAN
Tekanan Gas Perubatan Oksigen Rendah Di Hospital Kulim
Pada 2 Ogos 2021 jam 8.00 pagi, insiden penurunan tekanan gas perubatan oksigen
di Wad 3 (wad COVID) berlaku di Hospital Kulim pada kategori “low pressure”.
Pasukan Jurutera daripada Bahagian Kejuruteraan, JKN Kedah bersama syarikat
konsesi, Edgenta Mediserve Sdn. Bhd. telah bergegas dengan segera ke Hospital
Kulim sejurus menerima aduan bagi mengenalpasti punca berlakunya tekanan
rendah pada bekalan gas perubatan oksigen berpusat.
Pasukan Jurutera telah menjalankan pemeriksaan secara menyeluruh pada bacaan
tekanan gas perubatan oksigen di loji tangki utama gas perubatan oksigen, di wad-
wad termasuk wad COVID dan juga di Unit Kecemasan dan Trauma, Hospital Kulim.
Bacaan tekanan paling rendah yang direkodkan adalah di Wad 3 (wad COVID)
Hospital Kulim iaitu 3.3 bar dengan kapasiti penggunaan gas perubatan oksigen
327
seramai 25 orang pesakit manakala Unit Kecemasan dan Trauma termasuk khemah
COVID sementara pula bacaan direkodkan ialah 3.4 bar dengan kapasiti
penggunaan gas perubatan oksigen seramai 66 orang. Pecahan data pengunaan
gas perubatan oksigen di Wad 3 (wad COVID) dan Unit Kecemasan dan Trauma
adalah seperti di Jadual 1 dan Jadual 2.
Jadual 1: Maklumat Penggunaan Gas Perubatan Oksigen di Wad 3 (wad COVID),
Hospital Kulim
Bil Pesakit Jenis Pengunaan Kapasiti Pengunaan Jumlah Kapasiti
3 Per Pesakit Pengunaan
High Flow Nasal (semasa)
Cannula
35 l/min 105 l/min
10 Venturi Mask 15 l/min 150 l/min
6 High Flow Mask 15 l/min 90 l/min
4 Non-Invasive 15 l/min 60 l/min
Ventilator
2 Nasal Prong 3 l/min 6 l/min
Jumlah 411 l/min
Rujukan : l/min - liter per minit
Jadual 2: Maklumat Penggunaan Gas Perubatan Oksigen di Unit Kecemasan dan
Trauma, Hospital Kulim
Lokasi Jenis Bil Pesakit Kapasiti Jumlah Kapasiti
Pengunaan Pengunaan pengunaan
per pesakit
Green Zone , Nasal Prong 2 3 l/min 6 l/min
Yellow Zone Face Mask 2 10 l/min 20 l/min
dan Red Zone
(Non-COVID Nasal Prong 44 3 l/min 132 l/min
Patient)
Khemah
COVID Non-Invasive 1 15 l/min 15 l/min
Sementara Ventilator
(punca bekalan High Flow Mask 6 15 l/min 90 l/min
gas perubatan Venturi Mask 1 10 l/min 10 l/min
oksigen Face Mask 10 10 l/min 100 l/min
daripada
Decon Room) JUMLAH 373 l/min
Rujukan : l/min - liter per minit
328
Pengiraan anggaran kapasiti di Wad 3 (wad COVID) dan Unit Kecemasan dan
Trauma ditentukan mengikut formula seperti berikut:
= ( ) ×
Jadual 3 menunjukkan peratus kadar penggunaan gas perubatan oksigen bagi Wad
3 (wad COVID) dan Unit Kecemasan dan Trauma, Hospital Kulim seperti berikut:
Jadual 3: Maklumat Peratus Perbandingan Pengguna Gas Perubatan Oksigen di Wad 3
dan Unit Kecemasan dan Trauma, Hospital Kulim
Lokasi Bilangan Kadar Aliran Kapasiti Penggunaan Peratus
Wad 3 (wad Terminal Rekabentuk Rekabentuk Semasa Penggunaan
COVID
Unit (l/min) (l/min) (l/min) (%)
Outlet 411
10 200 205
20
COVID)
Unit
Kecemasan 18 10 180 373 207
dan Trauma
Ini menunjukkan bahawa sebanyak 205 % penggunaan gas perubatan di Wad 3
(wad Covid) dan sebanyak 207 % penggunaan gas perubatan oksigen di Unit
Kecemasan dan Trauma adalah melebihi anggaran kapasiti rekabentuk sistem gas
perubatan oksigen. Ia sekaligus menjadi faktor utama berlakunya ketidakstabilan
serta penurunan tekanan gas perubatan oksigen.
Tindakan Menstabilkan Tekanan Gas Perubatan Oksigen
Pasukan Jurutera meneruskan tindakan bagi menstabilkan semula tekanan gas
perubatan oksigen di Hospital Kulim dengan mengambil langkah-langkah berikut:
a) Kerja-kerja pelarasan tekanan pada pressure regulator oleh orang kompeten
gas perubatan dengan seliaan pasukan Jurutera bagi memastikan pelarasan
tetapan dibuat pada paras maksimum pressure regulator boleh beroperasi.
Walaubagaimanapun, bacaan tekanan gas perubatan oksigen terbaru
selepas dilaraskan tidak mencapai tahap tekanan yang diperlukan. Maka
pelarasan paling maksimum terpaksa dilakukan. Namun, pressure safety
relief valve telah berfungsi disebabkan tekanan melebihi paras normal
operasi yang dibenarkan.
b) Pasukan jurutera telah mengenalpasti kawasan penggunaan gas perubatan
oksigen yang rendah iaitu Jabatan Radiologi, Klinik Pakar 4 dan Klinik Pakar
329
5. Maka, gas perubatan oksigen di lokasi tersebut diasingkan serta merta
dengan menggunakan sistem sandaran sementara silinder gas perubatan
oksigen seperti di Rajah 2.
Rajah 2: Sistem sandaran sementara Gas Perubatan Oksigen yang dipasang
di Jabatan Radiologi, Klinik Pakar 4 dan Klinik Pakar 5
c) Penggunaan twin flowmeter di terminal unit outlet bagi kegunaan pesakit di
wad-wad dihentikan serta merta bagi mengurangkan risiko penurunan
tekanan gas perubatan oksigen yang ketara. Pasukan Jurutera telah
mengeluarkan panduan had kapasiti penggunaan gas perubatan oksigen
setiap wad bagi mengikut anggaran rekabentuk sistem gas perubatan
oksigen.
d) Pasukan Jurutera turut mengenalpasti bahawa sistem pepasangan gas
perubatan oksigen di khemah COVID sementara tidak mematuhi garis
panduan standard sistem pepasangan gas perubatan. Oleh demikian, satu
arahan dikeluarkan bagi menghentikan penggunaannya dan diganti dengan
sistem silinder gas perubatan oksigen beroperasi secara individu kepada
pesakit lengkap dengan bracket keselamatan. Sebanyak 30 unit silinder gas
perubatan oksigen lengkap dengan bracket berjaya dipasang dengan di
dalam khemah COVID sementara. Dalam situasi kritikal dalam pengendalian
330
pesakit COVID-19, pemantauan penggunaan silinder gas perubatan oksigen
secara berterusan dan penukaran silinder gas perubatan oksigen kerap
dilaksanakan oleh pihak hospital serta syarikat konsesi secara bersama.
e) Selain itu, bagi memastikan bekalan gas perubatan oksigen berterusan,
pasukan Jurutera telah memohon pihak pengurusan hospital dan farmasi
hospital untuk membuat pesanan bekalan silinder gas perubatan oksigen
sebanyak 200 unit silinder gas perubatan oksigen, namun dimaklumkan pihak
pembekal tidak dapat memberikan silinder gas perubatan oksigen pada masa
yang ditetapkan.
f) Sebagai menjamin tekanan gas perubatan oksigen dan keselamatan,
pasukan Jurutera membuat keputusan untuk menaiktaraf pressure regulator
dan pressure safety relief valve di loji utama gas perubatan oksigen.
Bahagian Kejuruteraan JKN Kedah telah berhubung dengan pihak Bahagian
Perkhidmatan Kejuruteraan, KKM bagi mendapatkan peruntukan kecemasan
supaya peruntukan dan kerja naiktaraf dapat diluluskan dengan segera.
Kerja-kerja naiktaraf pemasangan pressure regulator dan safety relief valve
berjaya diselesaikan pada 4 Ogos 2021.
KEJAYAAN KEJURUTERAAN
Tekanan Gas Perubatan Terkawal
Pada 4 Ogos 2021 pasukan Jurutera meneruskan pemantauan terhadap bacaan
tekanan gas perubatan oksigen di keseluruhan hospital. Kerja-kerja naiktaraf
pemasangan pressure regulator dan pressure safety relief valve dilaksanakan oleh
pihak Specialist Vendor dan selesai sepenuhnya pada jam 6.00 petang. Pasukan
Jurutera mengarahan kepada pihak pengurusan hospital untuk menyemak dan
membuat imbangan kapasiti penggunaan gas perubatan oksigen kepada setiap
wad berdasarkan pengiraan rekabentuk oleh pasukan Jurutera.
Bacaan tekanan gas perubatan oksigen direkodkan setiap wad telah stabil dengan
julat bacaan yang dibenarkan iaitu 3.9 bar sehingga 4.0 bar. Pemantauan diteruskan
selama 24 jam dan mendapati bacaan tekanan gas perubatan oksigen tidak
berubah. Tekanan gas perubatan Hospital Kulim telah kembali stabil sepenuhnya
pada 5 Ogos 2021.
331
IMPLIKASI KEJAYAAN
Penyelesaian jangka panjang bagi isu tekanan gas perubatan oksigen :
a) Kerja-kerja penambahan kapasiti tangki gas perubatan oksigen dengan
membuat tapak tangki baharu dan sewaan tangki gas perubatan oksigen
berkapasiti 20,000 liter cecair gas perubatan menjadikan keseluruhan
kapasiti 40,000 liter gas perubatan oksigen.
b) Kerja-kerja menaiktaraf sistem perpaipan gas perubatan oksigen utama
daripada bersaiz 28 mm diameter kepada 35 mm diameter untuk ke Wad 3,
Wad 4, Wad 7 dan Wad 8.
c) Kerja-kerja penambahan kontena sistem automatic manifold gas perubatan
oksigen lengkap dengan 30 terminal unit outlet di khemah COVID sementara
Unit Kecemasan dan Trauma, Hospital Kulim.
Kesemua penyelesaian jangka panjang ini telah dilaksanakan dan siap sepenuhnya
pada bulan September 2021 dibawah peruntukan khas darurat.
PENGHARGAAN
Penulis ingin mengucapkan setinggi-tinggi penghargaan kepada Ketua Pengarah
Kesihatan kerana kebenaran untuk menerbitkan artikel ini
RUJUKAN
Health Technical Memorandum 02-01 : Medical Gas Pipeline Systems Part A:
Design, Installation, Validation and Verification, The Stationary Office,
London, 2007.
Health Technical Memorandum 02-01 : Medical Gas Pipeline Systems Part B:
Design, Installation, Validation and Verification, The Stationary Office,
London, 2007.
Malaysia Standard (MS2675) - Medical gas system s - Part 1: Code of Practice for
The Design, Installation, Validation and Verification
332
PATIENT SAFETY CULTURE AND ITS DETERMINANTS AMONG
HEALTHCARE PROFESSIONALS AT A CLUSTER HOSPITAL IN
KEDAH.
Siti Norhani Mazrah Khalid1, Aniza Ismail2,
1Hospital Sultanah Bahiyah, Alor Setar
2Hospital Canselor Tuanku Muhriz UKM, Department of Community Health, Cheras.
Abstract
Introduction: Patient safety culture has been identified as a key component of patient safety
in health-related organizations. Thus, this study aimed to assess the level of patient safety
culture among healthcare professionals at a cluster hospital in Kedah and to determine the
predictive factors of positive patient safety culture.
Methods: This cross-sectional study was conducted at a cluster hospital comprising
one state and two district hospitals in Northern Kedah. The safety culture was
assessed using the Safety Attitude Questionnaire (SAQ), which is a validated
questionnaire. Using proportionate stratified random sampling, 1814 respondents
were recruited, and we used the independent t-test, Pearson chi-square test, and
multiple logistic regression analysis for data assessment.
Results: Only 23.9% of the respondents had positive patient-safety culture levels (SAQ
score ≥ 75%); the overall mean score was 67.82 ± 10.53. The job satisfaction dimension
had the highest percentage of positive responses (67.0%), with a mean score of 76.54 ±
17.77. The factors associated with positive patient-safety culture were age (odds ratio (OR)
1.03, p < 0.001), gender (OR 1.67, p = 0.001), education level (OR 2.51, p < 0.001), work
station (OR 2.02, p < 0.001), participation in patient safety training (OR 1.64, p = 0.007),
good perception of the incident reporting system (OR 1.71, p = 0.038), and a non-blaming
(OR 1.36, p = 0.013) and instructive (OR 3.31, p = 0.007) incident reporting system.
Conclusions: Healthcare professionals at the cluster hospital showed unsatisfactory
patient-safety culture levels. Most of the respondents appreciated their jobs, despite
experiencing dissatisfaction with their working conditions. The priority for changes should
involve systematic interventions to focus on patient safety training, address the blame
culture, improve communication, exchange information about errors, and improve working
conditions.
Keywords: patient safety culture; patient safety; safety attitude questionnaire; cluster
hospital
333
INTRODUCTION
The healthcare system is extremely complex, wherein healthcare delivery is founded
on patient safety. Patient safety entails avoiding preventable harm to patients during
the health care process and reducing the risk of unnecessary injury associated with
health care to an acceptable minimum. The World Health Organization (WHO)
reports that approximately 1 in 10 patients are harmed while receiving health care,
and approximately 43 million patient safety incidents occur annually (Organization,
2019). Little can be accomplished if a patient feels, or is, unsafe when receiving
medical treatment at healthcare facilities (Ulrich & Kear, 2014). Thus, ensuring
patient safety requires tremendous efforts from every member of a healthcare team.
The patient safety movement hit a milestone after the Institute of Medicine (IOM)
(Kohn, Corrigan, & Donaldson, 2000). Since then, patient safety has been at the
forefront of health care. In Malaysia, for example, the Ministry of Health (MOH)
formed the Patient Safety Council of Malaysia in January 2003 to ensure that people
receive safe health care. Malaysia Patient Safety Goals were then introduced on
June 24, 2013, outlining 13 essential areas in patient safety, with specific goals and
targets. Since then, multiple programs and efforts have been organized at both
national and state levels to improve the awareness of healthcare staff regarding
patient safety.
In the interest of patient safety, numerous studies have examined the causes of
medical errors. Over the years, health care organizations’ approaches to errors have
shifted from person-centered to system-centered. The system-centered approach
focuses on working conditions, rather than individual mistakes.(Van, Boer,
Akerboom, & Hudson, 2010) Further, the WHO Patient Safety Methods and
Measures Working Group identified the need to understand a range of human factors
such as managerial, team, and individual characteristics that influence healthcare
staff behavior concerning patient safety. A WHO report identified safety culture as
one of the 10 key human factors relevant to patient safety (Organization, 2009).
Safety culture or attitude influences the typical behaviors of workers in a particular
ward or unit. It affects patient safety as it determines the accepted practices within
an organization. Thus, evaluating the safety attitude and understanding the
components and influencers of safety culture is important to develop strategies for
creating a culture committed to providing patients with the safest possible care.
Furthermore, reported patient-safety-related incidents have increased over the
years. In England, the number of patient-safety-related incidents reported to the
National Reporting and Learning System in 2018 increased by 3.5%.(NHS
334
Improvement, 2018) In Malaysia, patient-safety-related incidents such as medication
errors, transfusion errors, and patient falls have increased since 2014 (Bakar, Bakar,
& Nahar, 2017). An outpatient geriatric pharmacy reported 20 cases of medication
errors daily, costing approximately RM111 924 per year. This increasing trend in
medical errors raises concern, as it indicates that our healthcare facilities may not
be safe for patients. It also has the potential to lead to medico-legal repercussions,
which would tarnish the reputation of the MOH and create a financial burden on the
patients and the ministry.
The present study was conducted at a cluster hospital in the state of Kedah,
Malaysia. A cluster hospital is defined as a group of hospitals in the same
geographical location within a state that collaborates and operates as one
organization; it is a MOH Malaysia initiative aimed at transforming healthcare service
delivery in the country. Additionally, it has been recognized as a Government
Transformation Program, a high-impact initiative by the Public Service Department,
and one of the top 10 priorities of the MOH Plan of Action (2016–2020). The objective
of the cluster hospital is to optimize resource utilization. The hospitals collaborate
and have an aligned flow of patients and services. A typical cluster hospital consists
of a lead hospital (LH), usually a state hospital or major specialist hospital.
Meanwhile, non-LHs (NLH) are usually the district non-specialist hospitals that
provide specialist services based on the cluster hospital concept.
Thus, this study’s main objective was to assess the baseline level and mean score
of every domain of patient-safety culture among healthcare professionals at a cluster
hospital. It identified the determinants associated with patient-safety culture and
developed a model for the predictive factors of positive patient-safety culture.
METHODS
Study design and sampling
This cross-sectional study was conducted at a cluster hospital consisting of a state
hospital and two district hospitals in Northern Kedah. As all three hospitals are public,
they implement similar patient-safety practices and policies. Data were collected
from December 2019 to February 2020. All doctors, pharmacists, nurses, and
assistant medical officers (AMO) who were involved directly with patient care
processes and who had been working at the hospitals for at least four weeks were
included in the study. Those who worked in management and who was on a long
leave were excluded from the study.
The samples were selected through proportionate stratified random sampling to
ensure that, throughout the population, the sample size selected from each subgroup
was proportional to the size of that subgroup. The same sampling method was used
335
to determine how many representatives from each professional category would be
selected. The sample size required, which was calculated using StatCalc Epi Info
7.2, was 778, at a 95% confidence interval (CI) and with 80% power. However,
considering a dropout rate of 20%, the final sample size required was 934.
Measures
One of the ubiquitously used tools for measuring patient-safety culture in healthcare
is the Safety Attitude Questionnaire (SAQ), which has been adapted for various
clinical settings such as intensive care units, general inpatient settings, emergency
services, operation theatres, and pharmacies. Here, we used both English and
Malay versions of the SAQ. The Malay version has been validated in the Malaysian
healthcare setting,(Samsuri, Lin, & Fahrni, 2015) with good construct validity and
internal consistency (Kar & Hamid, 2013).
The SAQ comprises 36 items for assessing six safety culture domains: teamwork
climate (items 1–6), safety climate (items 7–13), job satisfaction (items 15–19),
stress recognition (items 20–23), perceptions of management (items 24–28), and
working conditions (items 29–32). Items 14 and 33–36 are not among the
abovementioned scales. All items are closed-ended questions, and respondents are
required to indicate their agreement level on a 5-point Likert scale ranging from 1
(disagree strongly) to 5 (agree strongly). The respondents’ demographic information
such as age, gender, race, profession, education level, current working hospital and
unit, length of service, and working hours per week were obtained as well.
Information on patient safety training and the incident reporting system in the
organization was also added to the questionnaire to assess the factors affecting
patient-safety culture levels among healthcare professionals.
Data were analyzed using IBM SPSS Statistics version 21, and the respondents’
demographic characteristics and patient-safety culture level were determined using
univariate analysis. Before the analysis, three negatively worded items (items 2, 11,
and 36) in the SAQ were reversed. Each item’s score was calculated by converting
the 5-point Likert scale into a 100-point scale: 1 = 0, 2 = 25, 3 = 50, 4 = 75, and 5 =
100. Each item’s score within the same dimension was summed and divided by the
number of items available for that dimension to obtain a score of 0–100. If a
respondent’s mean score was ≥75, they had a positive safety culture for a given
dimension. The respondent’s overall score for the patient-safety culture level was
calculated using the same method.
The differences between two independent groups of normally distributed numerical
data were analyzed using an independent t-test; the association between two sets
of categorical data was examined using Pearson’s chi-square test for independence.
336
Multiple logistic regression was used to examine the association between risk factors
and two outcome categories. All probability values were 2-sided, and a level of
significance of <0.05 (p < 0.05) was considered statistically significant. Finally, the
model fitness was tested using the Hosmer-Lemeshow test and classification table.
Ethical issues/statement
This study received ethics approval from the Universiti Kebangsaan Malaysia (UKM)
Ethics Committee and the MOH Medical Research Etiquette Committee (MREC).
Respondents were informed about the background and aim of the study and the
confidentiality of the data submitted in the questionnaire, and their consent was
obtained before answering the questionnaire.
Patient and Public Involvement
Patients or the public were not involved in the design, conduct, reporting, or
dissemination plans of our research.
RESULTS
After 2000 questionnaires were distributed to the healthcare professionals who met
the inclusion criteria, 1814 completed questionnaires were returned, resulting in an
overall response rate of 90.7%.
Descriptive analysis
Demographic Characteristics
Table 1 shows the respondents’ general demographic characteristics. Most
respondents were female and Malay, with a mean age of 34.29 years. The majority
were from the non-doctor group, diploma holders and had been working at their
current departments or units for approximately five years. Most respondents (95.6%)
agreed that patient safety training was available at their organization, and 81% had
attended such programs at least once. More than half the respondents felt that the
incident reporting system was punitive.
337
Table 1: Demographic characteristics of the respondents Overall
Demographic characteristics
Frequency Percent
Age; mean (SD), median
Gender (n=1800) (%)
Male 34.29 (7.223), 33.00
Female
373 20.7
Race 1427 79.3
Malay
Non-Malay 1567 87.1
233 12.9
Profession
Doctor 479 26.6
Non-doctors 1321 73.4
Education level 1189 66.1
Diploma 611 33.9
Degree and above
1532 85.1
Current working hospital 268 14.9
Lead Hospital
Non-Lead Hospital 549 30.5
589 32.7
Location of work/ department 662 36.8
Medical based 63.65 (61.266), 48.00
Surgical based
Others 1258 69.9
542 30.1
Length of service; mean (SD), median
Working hours per week 1720 95.6
80 4.4
≤ 48 hours
> 48 hours 1458 81
Availability of training on patient safety 342 19
Yes
No 1619 89.9
Participation in patient safety program or training 181 10.1
Yes
No 1128 62.7
The overall perception of the incident reporting system 672 37.3
Good
Poor 1707 94.8
The incident reporting system is punitive 93 5.2
Yes
No 1750 97.2
Learned something from the incidence reported (Instructive incident 50 2.8
reporting system)
Yes
No
Will report patient safety incidents to the higher authority
Yes
No
338
Patient Safety Culture Level
The patient-safety culture levels among the respondents are shown in Table 2.
Overall, less than a quarter of the respondents (23.9%) had a positive patient-safety
culture. Notably, more than half of the respondents had a negative attitude toward
most of the dimensions tested, except for job satisfaction. NLH respondents had a
higher percentage of positive responses for the overall patient safety culture,
compared to LH respondents.
Table 2: Patient safety culture levels among healthcare professionals
Patient Safety Culture Overall LH NLH
Level Frequen Perce Frequen Perce Frequen Perce
cy nt (%) cy nt (%) cy nt (%)
(n=1800) (n=1532) (n=268)
Teamwork Climate
Negative 1133 62.9 975 63.6 158 59.0
Positive 667 37.1 557 36.4 110 41.0
Safety Climate
Negative 1149 63.8 1000 65.3 149 55.6
Positive 651 36.2 532 34.7 119 44.4
Job Satisfaction
Negative 594 33.0 518 33.8 76 28.4
Positive 1206 67.0 1014 66.2 192 71.6
Stress Recognition
Negative 1049 58.3 864 56.4 185 69.0
Positive 751 41.7 668 43.6 83 31.0
Perceptions of
Management
Negative 1279 71.1 1099 71.7 180 67.2
Positive 521 28.9 433 28.3 88 32.8
Working Conditions
Negative 1389 77.2 1165 76.0 224 83.6
Positive 411 22.8 367 24.0 44 16.4
Overall Safety Culture
Negative 1370 76.1 1179 77.0 191 71.3
Positive 430 23.9 353 23.0 77 28.7
The mean scores for each patient-safety culture dimension are presented in Table
3. The cluster hospital’s overall mean score was 67.82, and the LH and NLH had
comparable mean scores. The job satisfaction dimension had the highest mean
score (76.54), followed by safety climate (69.36), teamwork climate (69.18),
perception of management (64.87), stress recognition (62.80), and working condition
339
(62.27). The NLH had higher mean scores than the LH for most dimensions, except
for stress recognition and working condition.
Table 3: Mean scores of patient safety culture by dimension
Patient Overall LH NLH
Safety Mean (SD) Positive Mean Positive Mean (SD) Positive
Culture respons (SD) respons respons
Domains e (≥75)
e (≥75) e (≥75)
(%) (%) (%)
Teamwork 69.18 37.1 69.03 36.4 70.08 41.0
climate (12.83) (12.84 (12.75)
)
Safety 69.36 36.2 69.03 34.7 71.25 44.4
(13.17)
climate (12.55) (12.42
)
Job 76.54 67.0 76.27 66.2 78.10 71.6
(16.96)
satisfaction (17.77) (17.90
)
Stress 62.80 41.7 63.70 43.6 57.65 31.0
(25.58)
recognition (24.68) (24.41
)
Perception 64.87 28.9 64.68 28.3 65.93 32.8
(16.13)
of (16.24) (16.26
managemen )
t
Working 62.27 22.8 62.57 24.0 60.56 16.4
(11.97) 28.7
condition (12.64) (12.73
67.90
) (10.54)
Overall 67.82 23.9 67.80 23.0
safety (10.53) (10.53
culture )
Bivariate Analysis
Table 4 shows the result of the analysis to determine the associated factors for the
patient safety culture among healthcare professionals in a cluster hospital. Overall,
a significant association was noted between patient safety culture level and race (p
= 0.004), profession (p < 0.05), education level (p < 0.001), current working hospital
(p = 0.044), current department or unit (p < 0.001), and working hours per week (p
= 0.0001). There was also a significant association between patient safety culture
level and patient safety-related questions.
340
Table 4: Factors associated with patient safety culture
Variable Patient safety culture
Negative Positive p-value
< 0.05
n (%) n (%) 0.693
0.004
Age: Median (IQR) 32 (10.0) 35 (11.0) < 0.05
< 0.001
Gender 0.044
< 0.001
Male 281 (75.3) 92 (24.7) 0.069
0.0001
Female 1089 (76.3) 338 (23.7) 0.0004
< 0.05
Race
< 0.05
Malay 1175 (75.0) 392 (25.0) 0.692
Non-Malay 195 (83.7) 38 (16.3) 0.0001
Profession 0.019
Doctor 405 (84.6) 74 (15.4)
Non-doctors 965 (73.1) 356 (26.9)
Education level
Diploma 843 (70.9) 346 (29.1)
Degree and above 527 (86.3) 84 (13.7)
Current working hospital
LH 1179 (77.0) 353 (23.0)
NLH 191 (71.3) 77 (28.7)
Location of work/ department
Medical 406 (74.0) 143 (26.0)
Surgical 411 (69.8) 178 (30.2)
Others 553 (83.5) 109 (16.5)
Length of service; Median (IQR) 48.00 (85.0) 50.50 (91.0)
Working hours per week 926 (73.6) 332 (26.4)
≤ 48 hours
> 48 hours 444 (81.9) 98 (18.1)
Availability of training on patient safety
Yes 1296 (75.3) 424 (24.7)
No 74 (92.5) 6 (7.5)
Participation in patient safety program or training
Yes 1074 (73.7) 384 (26.3)
No 296 (86.5) 46 (13.5)
The overall perception of the incident reporting
system
Good 1209 (74.7) 410 (25.3)
Poor 161 (89.0) 20 (11.0)
The incident reporting system is punitive
Yes 862 (76.4) 266 (23.6)
No 508 (75.6) 164 (24.4)
Learned something from the incidence reported
(Instructive incident reporting system)
Yes 1283 (75.2) 424 (24.8)
No 87 (93.5) 6 (6.5)
Will report patient safety incidents to the higher
authority
Yes 1325 (75.7) 425 (24.3)
No 45 (90.0) 5 (10.0)
341
Multivariate analysis
Multiple logistic regression was conducted to identify a model of the predictive
factors that are associated with a positive patient-safety culture (Table 5). The
factors included in the model that were significantly associated with positive patient-
safety culture were age, gender, education level, working department/unit,
participation in patient safety training, good perception of incident reporting and
learning systems, and non-blaming and instructive incident reporting systems in the
organization. The model fitness was tested using the Hosmer-Lemeshow test (p =
0.788) and the classification table (76.5%). Nagelkerke’s R2 showed that this logistic
model explained 11.4% of the variation in the outcome variable.
Table 5: Multiple logistic regression Wald Overall safety culture p-value
Variable 13.046 Adj. OR (95% CI) < 0.001
11.896 1.03 (1.02, 1.05) 0.001
Age; median (IQR)
Gender 35.547 1.67 (1.25, 2.24) < 0.001
1.00
Male 7.136 < 0.001
Female 23.059 2.51 (1.85, 3.34)
Education level 1.00 0.007
Diploma
Degree and above 1.49 (1.11, 2.00)
Location of work/ department 2.02 (1.51, 2.68)
Medical based 1.00
Surgical based
Others 7.321 1.64 (1.15, 2.34)
Participation in patient safety 1.00
program or training
Yes 0.038
No
The overall perception of the 4.303 1.71 (1.03, 2.83)
incident reporting system 1.00
Good
Poor 0.013
The incident reporting system is
punitive 6.107 1.00
Yes 1.36 (1.07, 1.73)
No
Learned something from the 0.007
incidence reported (Instructive
incident reporting system) 7.405 3.31 (1.40, 7.85)
Yes 1.00
No
342
DISCUSSION
The response rate of the present study is 90.7%; thus, it is considered good and
positive compared with that of previous local studies that used the same instrument,
which was 58.0–83%.(A. Ismail, Hamid, & Sulong, 2020; Krishnasamy, Tan, &
Zakaria, 2019; Samsuri et al., 2015; Sarifulnizam et al., 2019) Further, other local
studies have used tools other than the SAQ, and recorded lower response rates (i.e.
78–81%), compared to that of the present study.(Alex, Chin, Sharlyn, Priscilla, &
Josephine, 2019; L. Ismail & Yunus, 2015) Furthermore, the response rate in our
study was higher compared to international benchmarking data in the US, UK, and
New Zealand, which was 65.7–72.2%,(John B Sexton et al., 2006) and other studies
conducted across the world.(Cui et al., 2017; Lee et al., 2010; Patel & Wu, 2016;
Zakari, 2011) The greater response rate in our study may be potential because this
is the first study on patient safety conducted in our cluster hospital community;
therefore, most departments were interested in participating. The high response rate
could also be an obvious indication of employee commitment and dedication to
quality issues, all of which signify responsible conduct. Further, the administered
questionnaire has positive features, which makes it more user-friendly, compared to
other tools. Among those features are self-administered questionnaires with clear
terms and a limited number of items that only require a short time for respondents to
complete.
At our cluster hospital, the respondents lacked a patient safety culture, far below the
international benchmarking standard, which is appropriately 60% (John B Sexton et
al., 2006) and that of other previous international studies (Brasaite, Kaunonen,
Martinkenas, & Suominen, 2016; Cheng, Yen, & Lee, 2019; Elsous et al., 2016; Lee
et al., 2010; Zimmermann et al., 2013). However, compared to previous local
studies, we recorded a higher percentage of positive responses than Sarifulnizam et
al. (2019) and comparable responses to Samsuri et al. (2015). We noted that the
NLH had a greater proportion of respondents with a positive patient-safety culture.
This finding correlates with Samsuri et al. (2015), who found that respondents in
smaller institutions had a more positive safety culture than those working in
hospitals. Other studies have also stated that smaller institutions tend to have a
better safety culture compared to large institutions (El-Jardali, Dimassi, Jamal,
Jaafar, & Hemadeh, 2011). The reason could be that small institutions, such as NLH,
have more similar environments and smaller work communities, whereby workers
are more likely to hold and share the same climate. Only the job satisfaction
dimension had a high percentage of positive responses (>60%), similar to other
previous local studies (A. Ismail et al., 2020; Sarifulnizam et al., 2019). The other
five dimensions showed low positive responses, between 22% and 41%.
343
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