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Surge Capacity Dynamics at a
COVID-19 Designated Hospital
in Malaysia
Kuan Pei Xuan1,2, Kuldip Kaur Prem Singh3, Law Kian Boon1, Mohd Aizuddin Abdul Rahman1,2,
Mohan Dass Pathmanathan1,2, Wong Xin Ci1, Kalaiarasu M. Peariasamy1,2, Goh Pik Pin1
1 Digital Health Research and Innovation, Institute for Clinical Research, Malaysia
2 Clinical Research Centre, Hospital Sungai Buloh, Malaysia
3 Director Office, Hospital Sungai Buloh, Malaysia
NMRR-20-1646-559741
Outline
▪Background
▪Introduction
▪Methodology
▪Results
▪Discussion
▪Conclusion
▪Acknowledgement
2
Background
1 Chopra, V. et al. (2020) ‘How Should U . S . Hospitals Prepare for Coronavirus Disease 2019 (COVID-19 )?’, Ann Intern Med. Available at: https://doi.org/10.7326/M20-0907.Ann Intern Med. Available at:
https://doi.org/10.7326/M20-0907.
2 Hick, J. L. et al. (2020) ‘Duty to Plan: Health Care, Crisis Standards of Care, and Novel Coronavirus SARS-CoV-2’, NAM Perspectives. doi: 10.31478/202003b.
3 Hospital Sungai Buloh [Internet]. 2020. Available from: https://hsgbuloh.moh.gov.my/index.php/ms/mengenai-kami/latar-belakang
4 Ministry of Health Malaysia (2020) Latest Updates on COVID-19, Ministry of Health, Malaysia. Available at: http://www.moh.gov.my/index.php/pages/view/2019-ncov-wuhan.
Building surge capacity for anticipated admission of COVID-19
patients is a critical part of hospital preparedness strategy 1,2
Hospital Sungai Buloh (HSgB)
▪ Designated COVID-19 hospital 3,4
▪ Multi-disciplinary specialty hospital pre-COVID 3
▪ Beds capacity management to meet admissions
3
Introduction
▪Modelling is useful to test preparedness decisions
▪Aims were to analyse:
i. Predicted daily bed requirement
ii. Actual hospital COVID-19 related admissions
iii. Compare trend with national COVID-19 disease dynamics
4
Methodology
▪Observational study design
▪COVID-19 daily admissions* recorded from Jan to May
2020
▪Bed utilisation compared with national daily new COVID-
19 cases
▪Correlation between bed capacity and demand calculated
against COVID-19 transmission dynamics
*Active admissions at HSgB= COVID-19 RT-PCR confirmed patients and Person Under Investigation (PUI) 5
Results
Description Total
Total number of COVID-19 cases (National) N= 7819
Total number of active cases (HSgB)
i) COVID-19
ii) PUI
Bed capacity
i) Pre-COVID
ii) During COVID
N= 5760
2474 (43.0%)
3286 (57.0%)
620
2069
Table 1: Total COVID-19 Cases in Malaysia, Active Cases and Bed Capacity in HSgB (up to May 2020)
6
Table 2: Demographic Characteristics of COVID-19 and PUI Cases Admitted to HSgB
COVID-19 (N=2474) PUI (N=3286)
Total n (%) n (%)
Age, median (min, max) 34.0 (0, 94.5) 30.8 (0, 96.4)
Age groups
≤ 10 73 (3.1) 339 (10.3)
11 – 20 249 (10.4) 234 (7.1)
21 – 30 662 (27.8) 924 (28.1)
31 – 40 454 (19.0) 690 (21.0)
41 – 50 289 (12.1) 287 (8.7)
51 – 60 304 (12.8) 233 (7.1)
61 – 70 198 (8.3) 191 (5.8)
≥ 71 155 (6.5) 388 (11.8)
Gender
Female 764 (30.9) 1802 (54.8)
Male 1710 (69.1) 1484 (45.2)
Nationality
Malaysian 1709 (71.7) 2967 (90.3)
Non-Malaysian 675 (28.3) 319 (9.7)
7
Fig. 1: Daily Trends of Active Cases in HSgB and COVID-19 Cases in Malaysia 8
Fig. 2: Active Cases Admitted to HSgB vs. Active COVID-19 Cases at National Level
▪ During the
Movement
Control Orders
(MCO), 10-20%
of COVID-19
cases were
admitted to
HSgB on
average
9
Fig. 3 (A): Correlation Between Active Cases Admitted to HSgB and COVID-19
Cases at National Level
▪ A two-phase
relationship was
found between
active cases
admitted to HSgB
and COVID-19
cases at the
national level
A) Correlation Between Active Cases (HSgB) and COVID-19 Cases (National)
10
Fig. 3 (B): Graph of Active Cases Admitted to HSgB Against COVID-19 Cases at
National Level Before MCO
▪ The first phase
occurred from end-
Feb to mid-March
2020, and can be
accurately modelled
using a logarithmic
function, with
r=0.982
11
Fig. 3 (C): Graph of Active Cases Admitted to HSgB Against COVID-19 Cases at
National Level During MCO
▪ The relationship
changed from
logarithmic to linear
during the second
phase
▪ There was high
correlation (r=0.998)
between national
cumulative COVID-19
cases and hospital
admission
12
Fig. 4: Bed Availability and Activation vs. Active Cases Admitted to HSgB
▪ Bed
capacity
and bed
activation
were
planned
ahead of
time
13
Discussion
▪The trend reflected COVID-19 daily cases detected from
contact tracing and screening strategies
▪Sudden surge of local transmissions occurring from mass
religious gathering
▪Traveling bans, Movement Control Orders (MCO) and
public health measures were implemented in response to
surge dynamics
14
Conclusion
▪Hospital bed capacity was suitably expanded to time for
the surge of COVID-19 admissions
▪Daily national COVID-19 cases provide a guide for hospital
preparedness decisions through modelling system
▪The modelling approach should take into consideration
for the surge in disease dynamics
15
Acknowledgement
▪We thank the Director General of Health Malaysia
for his permission to present this research
16
Thank you
17

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Surge Capacity Dynamics at a COVID-19 Designated Hospital in Malaysia

  • 1. ▪XX Surge Capacity Dynamics at a COVID-19 Designated Hospital in Malaysia Kuan Pei Xuan1,2, Kuldip Kaur Prem Singh3, Law Kian Boon1, Mohd Aizuddin Abdul Rahman1,2, Mohan Dass Pathmanathan1,2, Wong Xin Ci1, Kalaiarasu M. Peariasamy1,2, Goh Pik Pin1 1 Digital Health Research and Innovation, Institute for Clinical Research, Malaysia 2 Clinical Research Centre, Hospital Sungai Buloh, Malaysia 3 Director Office, Hospital Sungai Buloh, Malaysia NMRR-20-1646-559741
  • 3. Background 1 Chopra, V. et al. (2020) ‘How Should U . S . Hospitals Prepare for Coronavirus Disease 2019 (COVID-19 )?’, Ann Intern Med. Available at: https://doi.org/10.7326/M20-0907.Ann Intern Med. Available at: https://doi.org/10.7326/M20-0907. 2 Hick, J. L. et al. (2020) ‘Duty to Plan: Health Care, Crisis Standards of Care, and Novel Coronavirus SARS-CoV-2’, NAM Perspectives. doi: 10.31478/202003b. 3 Hospital Sungai Buloh [Internet]. 2020. Available from: https://hsgbuloh.moh.gov.my/index.php/ms/mengenai-kami/latar-belakang 4 Ministry of Health Malaysia (2020) Latest Updates on COVID-19, Ministry of Health, Malaysia. Available at: http://www.moh.gov.my/index.php/pages/view/2019-ncov-wuhan. Building surge capacity for anticipated admission of COVID-19 patients is a critical part of hospital preparedness strategy 1,2 Hospital Sungai Buloh (HSgB) ▪ Designated COVID-19 hospital 3,4 ▪ Multi-disciplinary specialty hospital pre-COVID 3 ▪ Beds capacity management to meet admissions 3
  • 4. Introduction ▪Modelling is useful to test preparedness decisions ▪Aims were to analyse: i. Predicted daily bed requirement ii. Actual hospital COVID-19 related admissions iii. Compare trend with national COVID-19 disease dynamics 4
  • 5. Methodology ▪Observational study design ▪COVID-19 daily admissions* recorded from Jan to May 2020 ▪Bed utilisation compared with national daily new COVID- 19 cases ▪Correlation between bed capacity and demand calculated against COVID-19 transmission dynamics *Active admissions at HSgB= COVID-19 RT-PCR confirmed patients and Person Under Investigation (PUI) 5
  • 6. Results Description Total Total number of COVID-19 cases (National) N= 7819 Total number of active cases (HSgB) i) COVID-19 ii) PUI Bed capacity i) Pre-COVID ii) During COVID N= 5760 2474 (43.0%) 3286 (57.0%) 620 2069 Table 1: Total COVID-19 Cases in Malaysia, Active Cases and Bed Capacity in HSgB (up to May 2020) 6
  • 7. Table 2: Demographic Characteristics of COVID-19 and PUI Cases Admitted to HSgB COVID-19 (N=2474) PUI (N=3286) Total n (%) n (%) Age, median (min, max) 34.0 (0, 94.5) 30.8 (0, 96.4) Age groups ≤ 10 73 (3.1) 339 (10.3) 11 – 20 249 (10.4) 234 (7.1) 21 – 30 662 (27.8) 924 (28.1) 31 – 40 454 (19.0) 690 (21.0) 41 – 50 289 (12.1) 287 (8.7) 51 – 60 304 (12.8) 233 (7.1) 61 – 70 198 (8.3) 191 (5.8) ≥ 71 155 (6.5) 388 (11.8) Gender Female 764 (30.9) 1802 (54.8) Male 1710 (69.1) 1484 (45.2) Nationality Malaysian 1709 (71.7) 2967 (90.3) Non-Malaysian 675 (28.3) 319 (9.7) 7
  • 8. Fig. 1: Daily Trends of Active Cases in HSgB and COVID-19 Cases in Malaysia 8
  • 9. Fig. 2: Active Cases Admitted to HSgB vs. Active COVID-19 Cases at National Level ▪ During the Movement Control Orders (MCO), 10-20% of COVID-19 cases were admitted to HSgB on average 9
  • 10. Fig. 3 (A): Correlation Between Active Cases Admitted to HSgB and COVID-19 Cases at National Level ▪ A two-phase relationship was found between active cases admitted to HSgB and COVID-19 cases at the national level A) Correlation Between Active Cases (HSgB) and COVID-19 Cases (National) 10
  • 11. Fig. 3 (B): Graph of Active Cases Admitted to HSgB Against COVID-19 Cases at National Level Before MCO ▪ The first phase occurred from end- Feb to mid-March 2020, and can be accurately modelled using a logarithmic function, with r=0.982 11
  • 12. Fig. 3 (C): Graph of Active Cases Admitted to HSgB Against COVID-19 Cases at National Level During MCO ▪ The relationship changed from logarithmic to linear during the second phase ▪ There was high correlation (r=0.998) between national cumulative COVID-19 cases and hospital admission 12
  • 13. Fig. 4: Bed Availability and Activation vs. Active Cases Admitted to HSgB ▪ Bed capacity and bed activation were planned ahead of time 13
  • 14. Discussion ▪The trend reflected COVID-19 daily cases detected from contact tracing and screening strategies ▪Sudden surge of local transmissions occurring from mass religious gathering ▪Traveling bans, Movement Control Orders (MCO) and public health measures were implemented in response to surge dynamics 14
  • 15. Conclusion ▪Hospital bed capacity was suitably expanded to time for the surge of COVID-19 admissions ▪Daily national COVID-19 cases provide a guide for hospital preparedness decisions through modelling system ▪The modelling approach should take into consideration for the surge in disease dynamics 15
  • 16. Acknowledgement ▪We thank the Director General of Health Malaysia for his permission to present this research 16