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Journal of Peking University (Health Sciences) ›› 2025, Vol. 57 ›› Issue (3): 529-536. doi: 10.19723/j.issn.1671-167X.2025.03.017

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Healthcare institution resilience and the influencing factors during infectious disease outbreaks

Yaqun FU1,2, Jiawei ZHANG1, Bing HAN3, Quan WANG1, Zheng ZHU1, Zhijie NIE1, Yiyang TAN1, Qing LIU4, Xiaoguang LI5, Jing GUO1, Rongmeng JIANG3, Li YANG1,2,*()   

  1. 1. Department of Health Policy and Management, Peking University School of Public Health, Beijing 100191, China
    2. Beijing Institute for Health Development, Peking University, Beijing 100191, China
    3. Clinical and Research Center of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100102, China
    4. Second Outpatient Section, Peking University Third Hospital, Beijing 100096, China
    5. Department of Infectious Diseases, Peking University Third Hospital, Beijing 100191, China
  • Received:2025-02-08 Online:2025-06-18 Published:2025-06-13
  • Contact: Li YANG
  • Supported by:
    the National Natural Science Foundation of China(72174010); Beijing Municipal Natural Science Foundation(M22033); the Capital Health Research and Development of Special Fund(2021-1G-4091)

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Abstract:

Objective: To analyze the association between healthcare workers mental health, institutional supplies and facilities, inter-organizational coordination during infectious disease outbreaks, and the healthcare institution resilience. Methods: An online questionnaire survey was conducted among the healthcare workforce from 146 institutions in Beijing from January 13, 2023 to February 9, 2023, and a total of 1 434 eligible respondents were included. The sample comprised 408 responses from tertiary hospitals, 117 from secondary hospitals, and 909 from primary care institutions. The resilience indicator for healthcare institutions was defined as the degree to which medical services met patient demands, with influencing factors including physical factors, such as material shortages and facility space adaptation or expansion, organizational factors such as information sharing and patient referral, and psychological factors were evaluated using job satisfaction (extrinsic satisfaction, intrinsic satisfaction), burnout (emotional exhaustion, depersonalization, reduced personal accomplishment), and depression status. Ordered multiclassification Logistic regression was used to examine the impact of various factors on the degree to which healthcare services met patient needs; additionally, demographic factors that might influence institutional resilience were controlled. Results: During the emergency response phase, 93% of hospitals maintained the capacity to meet patient needs, though tertiary hospitals demonstrated significantly higher rates of service inadequacy (21.05%). Material shortages were reported across all institutions, with tertiary hospitals experiencing more frequent multi-item shortages. Inter-institutional collaboration patterns revealed substantial variation: 87.50% of primary care facilities, 42.86% of secondary hospitals, and 31.58% of tertiary hospitals. Healthcare workers across all levels reported mild depressive symptoms and moderate-to-severe burnout levels. Regression analysis showed high satisfaction (overall satisfaction β=0.04, extrinsic satisfaction β=0.06, and intrinsic satisfaction β=0.08), low degree of job burnout (emotional exhaustion β=-0.04, depersonalization β=-0.07 and reduced personal accomplishment β=0.01), low degree of depression (β=-0.06) were significantly associated with higher healthcare institution resilience. In addition, material shortages were significantly associated with lower resilience, and renovation and expansion of treatment spaces, and information sharing, were all associated with higher resilience. Demographic factors (age, gender, marital status, educational background, etc.) had no significant impact on resilience. Conclusion: Mental health status significantly influences healthcare institution resilience. As human resources constitute the core asset of healthcare institutions, strategic optimization of workforce allocation and psychological support interventions can effectively strengthen resilience. Moreover, healthcare institution resilience is positively impacted by orderly material supply chains, timely resource distribution, and adaptive reconfiguration of clinical spaces. Finally, facilitating information sharing also enhances institutional resilience.

Key words: Healthcare institution resilience, Psychological factors, Organizational factors, Physical factors, Ordered multiclassification Logistic regression

CLC Number: 

  • R197

Table 1

Definition and description of variables"

Variable type Variable name Code
Dependent variable
  Service level Whether service can meet patient’s needs Y
Independent variable
  Psychological resilience Job satisfaction (overall) X1
  Job satisfaction (extrinsic satisfaction)
  Job satisfaction (intrinsic satisfaction)
Burnout (emotional exhaustion)
Burnout (depersonalization)
Burnout (reduced personal accomplishment)
Depression
  Organizational resilience Convenient access to patient history X2
Patient referrals X3
  Physical resilience Shortages of drugs, equipment and protective materials X4
Space renovation and expansion X5
  Demographic characteristics and hospital level Gender X6
Age X7
Marital status X8
Job category X9
Highest education level X10
  Other Hospital level X11

Table 2

Basic characteristics of participants"

Items Tertiary hospital (n=408) Secondary hospital (n=117) Primary hospital (n=909)
Age/years, ${\bar x}$±s 35.58±8.28 37.62±9.58 39.73±8.91
Gender, n(%)
  Male 65 (15.93) 32 (27.35) 285 (31.35)
  Female 343 (84.07) 85 (72.65) 624 (68.65)
Job category, n(%)
  Doctor 192 (47.06) 62 (52.99) 594 (65.35)
  Nurse 210 (51.47) 54 (46.15) 101 (11.11)
  Other 6 (1.47) 1 (0.85) 214 (23.54)
Highest education level, n(%)
  Junior college and below 73 (17.89) 31 (26.50) 184 (20.24)
  College degree 200 (49.02) 71 (60.68) 612 (67.33)
  Master’s degree and above 135 (33.09) 15 (12.82) 113 (12.43)
Marital status, n(%)
  Married 286 (70.10) 89 (76.07) 756 (83.17)
  Unmarried 114 (27.94) 25 (21.37) 117 (12.87)
  Other 8 (1.96) 3 (2.56) 36 (3.96)

Table 3

Basic characteristics of hospitals"

Items Tertiary hospital(n=19) Secondary hospital(n=7) Primary hospital(n=120)
Level of service provision, n(%)
  Unable to meet patients’ needs 4(21.05) 0(0.00) 6(5.00)
  Basically meet patients’ needs 11(57.90) 6(85.71) 61(50.83)
  Fully meet patients’ needs 4(21.05) 1(14.29) 53(44.17)
Shortage situation, n(%)
  Only drugs 8(42.11) 7(63.64) 75(62.50)
  Only medical devices 2(10.52) - -
  Drugs, medical devices and medical protective supplies 9(47.37) 4(36.36) 45(37.50)
Setting of fever clinics, ±s
  Number of regular consulting rooms 3.37 ±1.07 3.00 ±1.29 -
  Number of consulting rooms during the peak of outbreak 3.54 ±1.61 3.57 ±2.07 -
Expansion and renovation of areas, n(%) - - 80(66.67)
Cross-institutional cooperation，n(%)
  Conduct referrals 6(31.58) 3(42.86) 105(87.50)
  Convenient access to patients’ previous medical records 12(63.16) 5(71.57) 103(85.83)

Table 4

Evaluation of reliability and validity of the research scale"

Scale Cronbach α KMO
Minnesota job satisfaction scale (MSQ) 0.975 3 0.968 3
Job burnout scale (MBI-GS) 0.908 4 0.932 5
Patient health questionnaire-9 (PHQ-9) 0.945 1 0.927 6

Table 5

Satisfaction, burnout and depression of different healthcare workforce"

Variables Doctors (n=848) Nurses (n=365) Other (n=221) P value
Job satisfaction, ${\bar x}$±s 75.95±13.72 76.64±15.25 76.43±14.87 0.723
  Extrinsic satisfaction 46.07±8.18 46.64±9.05 46.21±8.97 0.562
  Intrinsic satisfaction 29.88±5.75 29.99±6.45 30.22±6.11 0.754
Job burnout, ${\bar x}$±s
  Emotional exhaustion 24.01±12.89 22.57±13.83 21.93±15.05 0.059
  Depersonalization 6.93±6.37 7.60±7.07 7.15±7.54 0.284
  Reduced personal accomplishment 30.82±10.21 28.97±11.89 26.86±13.06 < 0.001
Depression, ${\bar x}$±s 7.70±5.82 8.01±6.12 7.32±6.06 0.390

Table 6

Factors associated with healthcare services' responsiveness to patient needs"

Items Model 1 β(95%CI) Model 2 β(95%CI) Model 3 β(95%CI) Model 4 β(95%CI) Model 5 β(95%CI) Model 6 β(95%CI) Model 7 β(95%CI)
Psychological factors - - - - - - -
Job satisfaction 0.04*** (0.03, 0.04) - - - - - -
  Extrinsic - 0.06*** (0.04, 0.08) - - - - -
  Intrinsic - - 0.08*** (0.06, 0.10) - - - -
Burnout
  Emotional exhaustion - - - -0.04*** (-0.05, -0.03) - - -
  Depersonalization - - - - -0.07*** (-0.08, -0.05) - -
  Reduced personal accomplishment - - - - - 0.01** (0.00, 0.02) -
Depression - - - - - - -0.06*** (-0.09, -0.04)
Organizational factors
  Convenient access to patient history 0.22 (-0.05, 0.50) 0.22 (-0.05, 0.50) 0.23 (-0.05, 0.50) 0.27* (-0, 0.55) 0.28** (0.00, 0.56) 0.30** (0.02, 0.57) 0.28** (0.01, 0.55)
  Patient referrals 0.17 (-0.10, 0.43) 0.17 (-0.09, 0.44) 0.17 (-0.10, 0.43) 0.2 (-0.06, 0.47) 0.2 (-0.06, 0.47) 0.24* (-0.02, 0.50) 0.25* (-0.01, 0.51)
Physical factors
  Shortages of drugs, equipment and protective materials -0.25** (-0.49, -0.00) -0.26** (-0.51, -0.02) -0.23* (-0.48, 0.01) -0.2 (-0.45, 0.05) -0.24* (-0.49, 0.00) -0.27** (-0.51, -0.03) -0.22* (-0.46, 0.03)
  Space renovation and expansion 0.1 (-0.21, 0.41) 0.11 (-0.20, 0.42) 0.11 (-0.20, 0.42) 0.31** (0.00, 0.62) 0.25 (-0.06, 0.56) 0.23 (-0.08, 0.54) 0.22 (-0.09, 0.53)
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