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The association between hospital overcrowding and mortality among patients admitted via Western Australian emergency departments

Peter C Sprivulis, Julie-Ann Da Silva, Ian G Jacobs, George A Jelinek and Amanda R L Frazer
Med J Aust 2006; 184 (5): 208-212. || doi: 10.5694/j.1326-5377.2006.tb00203.x
Published online: 6 March 2006

Abstract

Objective: To examine the relationship between hospital and emergency department (ED) occupancy, as indicators of hospital overcrowding, and mortality after emergency admission.

Design: Retrospective analysis of 62 495 probabilistically linked emergency hospital admissions and death records.

Setting: Three tertiary metropolitan hospitals between July 2000 and June 2003.

Participants: All patients 18 years or older whose first ED attendance resulted in hospital admission during the study period.

Main outcome measures: Deaths on days 2, 7 and 30 were evaluated against an Overcrowding Hazard Scale based on hospital and ED occupancy, after adjusting for age, diagnosis, referral source, urgency and mode of transport to hospital.

Results: There was a linear relationship between the Overcrowding Hazard Scale and deaths on Day 7 (r = 0.98; 95% CI, 0.79–1.00). An Overcrowding Hazard Scale > 2 was associated with an increased Day 2, Day 7 and Day 30 hazard ratio for death of 1.3 (95% CI, 1.1–1.6), 1.3 (95% CI, 1.2–1.5) and 1.2 (95% CI, 1.1–1.3), respectively. Deaths at 30 days associated with an Overcrowding Hazard Scale > 2 compared with one of < 3 were undifferentiated with respect to age, diagnosis, urgency, transport mode, referral source or hospital length of stay, but had longer ED durations of stay (risk ratio per hour of ED stay, 1.1; 95% CI, 1.1–1.1; P < 0.001) and longer physician waiting times (risk ratio per hour of ED wait, 1.2; 95% CI, 1.1–1.3; P = 0.01).

Conclusions: Hospital and ED overcrowding is associated with increased mortality. The Overcrowding Hazard Scale may be used to assess the hazard associated with hospital and ED overcrowding. Reducing overcrowding may improve outcomes for patients requiring emergency hospital admission.

Emergency department (ED) overcrowding is common in North America, the United Kingdom and Australasia.1-3 Overcrowding results in ambulance diversion and impaired ED responsiveness.2,4,5

Inpatient bed “access block” is the principal cause of ED overcrowding.1,4,6 Access block is defined as the proportion of ED patients requiring admission whose total time within the ED exceeds 8 hours.7 Access block is correlated with total hospital inpatient bed occupancy of 90% or more, as measured by a midnight bed census.7-9 A target occupancy of 85% has been suggested as a balance between unused bed capacity and efficient inpatient flow.8,10

Some studies have identified a relationship between high occupancy, access block and adverse patient outcomes, as measured by inpatient length of stay, hospital readmission or reattendance for emergency care.11-13

Our study examines whether high hospital occupancy and ED access block is also associated with increased patient mortality.

Methods
Statistical analysis

The Statistical Package for the Social Sciences (SPSS, Version 12.0, Chicago, Ill, USA) was used for the analysis.

Results
Sample characteristics

There were 62 495 first emergency admissions and 3084 deaths by the Day 30 censoring date. The admission characteristics, grouped by hospital occupancy, are summarised in Box 2. Higher hospital occupancy was associated with a slightly higher proportion of elderly, female, illness admissions, and was more likely during weekdays and during winter. However, the hospital occupancy groupings were undifferentiated with respect to the proportion of physician-referred admissions, ambulance-transported admissions, triage urgency, or length of hospital stay.18

Hospital occupancy and mortality

Box 2 shows a positive relationship between level of hospital occupancy and death by days 2, 7 and 30 after index ED attendance, with a relative increase in mortality by Day 7 of 18% (95% CI, 0.5%–38%) for hospital occupancy of 90%–99% and 46% (95% CI, 14%–85%) for hospital occupancy of 100% or more.

Box 3 illustrates the 7-day survival stratified by hospital occupancy, adjusted for age, mode of transport, diagnosis (ICD-10-CM), triage urgency and referral source. In comparison with < 90% occupancy, the 7-day hazard ratio for 90%–99% hospital occupancy was 1.2 (95% CI, 1.1–1.3; P = 0.02), and for 100% hospital occupancy it was 1.3 (95% CI, 1.1–1.6; P = 0.001). Initially significant univariate associations between mortality and winter season, month of year, individual day of week and time of day were rendered non-significant after adjustment for the above variables. Adjustment for hospital attended (including use of an interaction term “hospital × occupancy”) or length of hospital stay did not significantly change the hazard associated with hospital occupancy.

The Overcrowding Hazard Scale and mortality

Box 4 presents the 7-day hazard ratios associated with the Overcrowding Hazard Scale, using an identical model to that used for Box 3, but with the Overcrowding Hazard Scale substituted for hospital occupancy. A linear relationship between the Overcrowding Hazard Scale and 7-day mortality hazard was demonstrated (r = 0.98; 95% CI, 0.79–1.00; P = 0.001), indicating that an Overcrowding Hazard Scale score > 2 (defining “overcrowded conditions”) is associated with increased patient mortality.

Box 5 presents the hazard ratios associated with overcrowded conditions and the other factors associated with Day 7 deaths, and Box 6 presents the deaths associated with overcrowded conditions, censoring survival at 2, 7 and 30 days: 2.3 deaths per 1000 emergency admissions were associated with overcrowded conditions by Day 30 (95% CI, 1.2–3.2), or an estimated 120 deaths (95% CI, 60–170) among the 53 025 tertiary hospital emergency admissions (including non-index admissions) in Perth in 2003.

Discussion
Understanding the relationship between overcrowding and patient harm

Our study did not examine the mechanisms by which overcrowding is associated with increased mortality. Examination of delays in the initiation of time-critical care, such as the administration of antibiotics in sepsis, may be a fruitful line of enquiry.19 The longer physician waiting times and ED durations of stay among patients in our study who experienced overcrowded conditions and died may be acting as proxies for delays in the initiation of care. The presence of patients experiencing access block is strongly correlated with longer physician waiting times in EDs in both metropolitan Perth (r = 0.86) and internationally.4,6

Human error theory predicts that errors occur more often when systems are stressed by constraining resources; such as when a hospital is overcrowded.20 Overcrowding is often associated with placing inpatients on an incorrect ward (eg, medical patients placed on surgical wards) where staff may be less familiar with standard service guidelines for care of the patient’s condition or the clinical cues associated with potential adverse events. Such patient “outlying” may be a mediator of the association between overcrowding and increased mortality.

Given the association between the Overcrowding Hazard Scale and increased mortality, we suggest that the scale could be used to monitor the hazard associated with overcrowding in real-time. An Overcrowding Hazard Scale score > 2 may be considered prima facie evidence of an increased Day 7 mortality hazard.8

Solutions to overcrowding

Hospital overcrowding is a complex phenomenon. The prevalence of overcrowding may rise in health services in developed economies as age-related demand for hospital services grows over the next 10–15 years.21 In addition, economic incentives tend to favour high occupancy.21 Solutions may include the realignment of incentives that favour high levels of hospital occupancy at the expense of emergency access. Other solutions may include strategies that reduce waste, misuse and overuse of health services, and improved chronic disease management to reduce hospital bed demand.22 In addition, better matching of bed supply with predictable emergency demand and optimisation of hospital inpatient flow are required.22-24

Conclusion

Hospital and ED overcrowding is associated with increased mortality. The Overcrowding Hazard Scale may be used to assess the mortality hazard to patients associated with hospital and ED overcrowding. Reducing overcrowding may improve outcomes for patients requiring emergency hospital admission.

2 Characteristics of emergency hospital admissions grouped by hospital occupancy

Occupancy < 90%


Occupancy 90%–99%


Occupancy ≥ 100%


Sample characteristic

n (%)
or mean  

95% CI

n (%)
or mean  

95% CI

n (%)
or mean  

95% CI

P


Sex (% female)

7 464
(45.0%)

44.3%–45.8%

19 023
(47.5%)

47.0%–48.0%

2 959
(50.6%)

49.3%–51.9%

0.05

Age (% ≥ 50 years)

9 969
(60.1%)

59.4%–60.9%

25 805
(64.4%)

63.9%–64.9%

4 220
(72.1%)

71.0%–73.3%

< 0.001

Diagnosis (% injury)

4 130
(24.9%)

24.3%–25.6%

9 453
(23.6%)

23.2%–24.0%

1 343
(23.0%)

21.9%–24.0%

< 0.001

Shift (% 08:00–15:59 hours)

7 148
(43.1%)

42.4%–43.9%

18 123
(45.2%)

44.7%–45.7%

2 902
(49.6%)

48.3%–50.9%

0.12

Day (% Mon–Fri)

10 287
(62.0%)

61.3%–62.8%

30 043
(75.0%)

74.6%–75.4%

5 110
(87.4%)

86.5%–88.2%

< 0.001

Winter attendance (% Jun–Sep)

1 776
(10.7%)

10.2%–11.2%

16 192
(40.4%)

39.9%–40.9%

4 614
(78.9%)

77.8%–79.9%

< 0.001

Referral source (% physician-referred)

5 543
(33.4%)

32.7%–34.2%

13 603
(34.0%)

33.5%–34.4%

2 129
(36.4%)

35.2%–37.6%

0.36

Transport to emergency (% ambulance)

8 141
(49.1%)

48.3%–49.9%

20 653
(51.5%)

51.1%–52.0%

3 212
(54.9%)

53.6%–56.2%

0.09

Triage urgency (% resuscitation cases)

662
(4.0%)

3.7%–4.3%

1 546
(3.9%)

3.7%–4.0%

251
(4.3%)

3.8%–4.8%

0.27

Mean length of stay

6.60

6.44–6.76

6.72

6.61–6.83

6.76

6.49–7.04

> 0.2*

Mean length of stay, weighted for deaths

6.84

6.67–7.00

6.99

6.88–7.10

7.09

6.82–7.36

> 0.1*

Day 2 deaths (%)

179
(1.1%)

0.9%–1.2%

532
(1.3%)

1.2%–1.4%

91
(1.6%)

1.2%–1.9%

0.06

Day 7 deaths (%)

375
(2.3%)

2.0%–2.5%

1 065
(2.7%)

2.5%–2.8%

193
(3.3%)

2.8%–3.8%

0.002

Day 30 deaths (%)

725
(4.4%)

4.1%–4.7%

2 001
(5.0%)

4.8%–5.2%

358
(6.1%)

5.5%–6.7%

0.001

Total (% of 62 495 admissions)

16 579
(26.5%)

40 067
(64.1%)

5 849
(9.4%)


* For all between-group tests.

Received 24 May 2005, accepted 21 November 2005

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