The impact of COVID-19 on nurse staffing levels and healthcare- associated infections in medical institutions: A retrospective cohort study

doi:10.21203/rs.3.rs-4703027/v1

Background: In Korea, various policies had been introduced to improve the nursing shortage problem even before COVID-19, but there is still a shortage of nurses, and it is unclear how this, combined with the impact of infectious diseases, has affected staff nursing grades and healthcare-associated infections(HAIs). This study aimed to evaluate changes in nurse staffing levels in medical institutions in Korea and their impact on HAIs during the COVID-19 pandemic.

Methods: A total of 100,417 patients who were admitted to an intensive care unit(ICU) or general ward after a diagnosis or confirmation of COVID-19 from 2020 to 2022 were included in this study. To evaluate the effect of nurses on HAIs, nurse-to-bed(patient) ratio and fixed night shift nurses were considered as nurse factors. A HAI is defined as a patient with a diagnosed or confirmed COVID-19 infection more than seven days after admission or within seven days after discharge. To evaluate the association between nurse staffing levels and HAIs, survival analyses were performed using Cox proportional hazards models, adjusting for covariates.

Results: Of the patients admitted to an ICU or general ward, 4.5% and 12.2% had in-hospital COVID-19 infection, respectively. Survival analysis showed that HAIs increased as the number of patients per nurse increased for both general ward and ICU patients. Additionally, compared with medical institutions that do not operate fixed night shift nurses, HAIs increased as the proportion of night nurses increased, but decreased to less than 10%.

Conclusions: This study shows that securing nurses and operating an appropriate proportion of night nursing staff is important for infection control within medical institutions. In the event of an infectious disease outbreak, infection prevention activities through appropriate staffing are important, and healthcare-associated infections can be reduced by securing appropriate nurse staffing and maintaining an appropriate proportion of nurses on night shifts.

General Ward

Healthcare-Associated Infection

Intensive Care Unit

Nurse Staff

The coronavirus disease 2019 (COVID-19) outbreak raised public health challenges and brought unpredictable disruptions to healthcare systems. According to the World Health Organization, the number of deaths due to COVID-19 in 2020–2021 was 5.42 million, and the estimated excess deaths during that period were 14.83 million, which is 2.74 times the number of COVID-19-related deaths [1]. During the COVID-19 period, hospitalizations and procedures for non-COVID-19 patients decreased, and the time from symptom onset to treatment was delayed [2]. In addition, nurses' stress and burnout increased [3], and it has been reported that issues relating to the quality of care and missed care also increased [4, 5]. These results suggest that the COVID-19 outbreak may have reduced the quality of care and affected patient safety.

Despite increased awareness of infection prevention methods because of the COVID-19 outbreak [6], hospitals may still be a source of infection transmission, and healthcare-associated infections are a major health problem that continue to threaten patient safety [7, 8]. Findings on the impact of the COVID-19 outbreak on healthcare-associated infections are mixed, with some studies showing an increase in hospital-acquired bloodstream infections and multidrug-resistant bacteria [9, 10] and others showing a decrease [6, 11]. These results suggest that the impact of existing infection control efforts may have had a positive impact even during the COVID-19 outbreak, leading to a reduction in healthcare-associated infections, but overcrowding in medical institutions and a lack of protective equipment and medical staff may have had a negative impact [12, 13].

During the COVID-19 period, nosocomial COVID-19 infections were reported in medical settings, and transmission during hospitalization was reported not only among healthcare workers but also between patients [14, 15]. Previous studies have estimated that approximately 15% of patients experienced nosocomial transmission of COVID-19 during hospitalization [15], and when considering asymptomatic patients, unmeasured nosocomial infections are higher, suggesting that infection control may be necessary through screening of patients upon discharge [16]. Nurses are especially closely related to infection control, and inadequate infection control owing to a shortage of nurses can affect the spread of nosocomial infections among hospitalized patients [8, 17]. Although these results suggest the importance of nurses, the nursing shortage problem is still not resolved and appears to have worsened because of the COVID-19 pandemic.

The COVID-19 pandemic brought changes to the labor market and affected the movement of nurses as a result of an increased demand for temporary workers for infection control [18]. In the United States, the negative impact of infectious diseases led to an increase in nurses' intention to turnover; however, the number of travel nurses increased [19]. In Korea, the number of nurses in healthcare organizations increased from about 240,000 in 2021 to 254,000 in 2022 but it was still less than the Organisation for Economic Co-operation and Development’s average number of nurses per 1,000 population (2021: OECD: 9.2; Korea: 8.8) [20, 21]. Korea faces complex challenges owing to the impact of infectious diseases and the government's various nursing-related policies [20, 22]. Nurses tend to prefer large hospitals in terms of wages and working conditions [20, 23]. Larger hospitals have lower nurse-to-patient ratios, and the lower the nurse-to-patient ratio, the lower the turnover intention [20]. To respond to infectious diseases and the shortage of nurses, the government increased night-shift nurses’ compensation and expanded the number of hospitals that can receive incentives based on the fixed night-shift nurse. This is part of a policy to improve nurses’ working environments by paying additional fees to medical institutions for nurses' night shifts and refunding these costs to nurses. Medical institutions receive incentives based on the proportion of fixed night-shift nurses among all nurses, and more than 70% of the incentives must be used to pay nurses. These policies may affect the retention of nurses in medical institutions by providing them with more compensation, but the negative impact of infectious diseases is likely to offset that impact. However, there is insufficient evidence on the impact of changes in nurse staffing in medical institutions and nurse staffing on patients' health-associated infections during a pandemic.

The purpose of this study was to evaluate changes in hospital nurse staffing during the COVID-19 outbreak and its impact on patients' COVID-19 in-hospital infections. First, we evaluated changes in nursing grades at medical institutions during the COVID-19 outbreak. Next, to evaluate the effect of nurse staffing on patient outcomes, we evaluated the effects of nursing grades and the proportion of fixed night-shift nurses at medical institutions on health-associated infections for patients hospitalized in general wards and intensive care units (ICUs).

Database and data collection

This retrospective cohort study used data from the Korea Disease Control and Prevention Agency COVID-19 National Health Insurance Service cohort, which is linked to the Korea Disease Control and Prevention Agency and the National Health Insurance Service. The Korea Disease Control and Prevention Agency data provided general characteristics such as sex, age, date of diagnosis of confirmed COVID-19 patients, and COVID-19 vaccine data, and the National Health Insurance Service provided claims data, including patient information (age, sex, primary diagnosis, admission date, discharge date, etc.) and hospital information (number of beds, number of nurses, region, etc.). Data on confirmed COVID-19 cases from October 8, 2020, to October 29, 2022, can be linked with National Health Insurance Service data. In this study, data were extracted based on patients who had been hospitalized among patients who could be linked to the National Health Insurance Service with confirmed COVID-19 data. Based on this, a total of 1,387,345 patients were included in the baseline.

The inclusion criteria for this study were that patients had to have been hospitalized for COVID-19 and hospitalized at medical institutions. There were 591,155 hospitalized patients at baseline, of which 253,451 were diagnosed with COVID-19 based on the International Classification of Diseases codes (U071, U072) during hospitalization, or had COVID-19 onset dates confirmed before and after hospitalization in data from the Korea Disease Control and Prevention Agency. The exclusion criteria considered the characteristics of both the medical institutions and individuals. First, medical institutions with fewer than 30 beds, no nursing grades, or no nurses were excluded, and only patients admitted to hospitals, general hospitals, or tertiary hospitals were included. Second, patients under 18 years old, over 80 years old, with no income level, or with a length of stay of 0 days were excluded. Next, only patients hospitalized in adult ICUs or general wards were included. In this study, hospitalization for COVID-19 refers to patients diagnosed with COVID-19 seven days prior to hospitalization or who received a COVID-19 diagnosis during hospitalization. To consider potential healthcare-associated infections suggested in previous studies [16], patients who were not diagnosed with COVID-19 during hospitalization but were confirmed to have COVID-19 within seven days after discharge were also included. Further, because there is a possibility of healthcare-associated infections owing to factors other than nurses during long-term hospitalization [24], patients whose hospitalization period exceeded 31 days were excluded. Ultimately, 1,349 hospitals and 91,938 patients were included in this study.

Variables

The variable of interest in this study was nurse staffing. In Korea, ICUs are classified as 9th grade based on nurse-to-bed ratio, while general wards are classified as 7th grade based on nurse-to-patient ratio. This study classified each of these nursing grades into five categories: ICUs (nurse-to-bed ratio: < 0.5, < 0.77, < 1.1, < 1.5, ≥ 1.5); general wards (nurse-to-patient ratio: < 2.0, < 3.0, < 4.5, < 6.0, ≥ 6.0). The fixed night-shift nurse system is part of the flexible work system, where fixed-shift night nurses work eight hours a night, up to 14 days a month, and each nurse must handle no more than 25 patients. This policy was applied to hospitals excluding Seoul in April 2017, expanded to hospitals and general hospitals excluding Seoul in October 2019, and expanded to tertiary hospitals including Seoul from January 2022. The National Health Insurance Service provides incentives to medical institutions based on the proportion of fixed night-shift nurses among all nurses (< 10%, < 15%, < 20%, < 25%, ≥ 25%). In this study, institutions were classified into six categories, including institutions that do not operate fixed night-shift nurses. Additionally, the proportion of nursing assistants among all nurses was classified based on quartile (< 5%, < 15%, < 30%, ≥ 30%).

The outcome variable was in-hospital COVID-19 infection during hospitalization. In-hospital COVID-19 infection was defined as a person diagnosed with COVID-19 within seven days after hospitalization or confirmed with COVID-19 within seven days after discharge, referring to existing nosocomial infection definitions and previous studies [16]. Hospital characteristics included type of hospital (hospital, general hospital, tertiary hospital), region (capital area, metropolitan, and other), and number of beds (< 300, < 500, < 700, < 900, and ≥ 900). Patient characteristics included sex (female, male), major diagnosis (respiratory system [International Classification of Diseases code: J00-J99], malignant neoplasm[International Classification of Diseases code C00-C97], circulatory system [International Classification of Diseases code: I00-I99] and other), age (≤ 40, ≤ 55, ≤ 65, ≤ 75, > 75), Charlson comorbidity index, health insurance (Employee, Self-insured, Medicaid), income (low, low-moderate, moderate-high, high), and year of admission (2020, 2021, 2022). In addition, to consider patients’ movements, we evaluated whether the hospital and the patient’s residence were in the same location. We also considered the number of doses of COVID-19 vaccine before hospitalization. Finally, because infection rates can also potentially impact healthcare-associated infections, we included the COVID-19 incidence rate per 1,000 population by region by month.

Statistical analysis

The distribution of each categorical variable was examined by analyzing frequencies and percentages, and χ² tests were performed to examine associations with healthcare-associated infections. Either a t-test or analysis of variance was performed to compare the average values and standard deviations for continuous variables. Survival analysis using the Cox proportional hazards model was used to analyze the association between COVID-19 in-hospital infection and nurse staffing, adjusting for other covariates. In addition, to evaluate differences according to the timing of COVID-19 infection, nosocomial infections were evaluated during hospitalization (seven days after hospitalization) and after discharge (within seven days after discharge). All statistical analyses were performed using SAS (version 9.4; SAS Institute).

Table 1 shows the general characteristics of patients admitted to ICUs and general wards during the study period. Among patients hospitalized in ICUs, the nosocomial infection rate was 4.5% (n = 1,400), and among patients hospitalized in general wards, the nosocomial infection rate was 12.2% (n = 8,413). Neither the ICUs nor the general wards showed an increasing trend in COVID-19 healthcare-associated infections as the nurse-to-patients (or beds) ratio increased. However, when the proportion of fixed night-shift nurses among all nurses in medical institutions was high, healthcare-associated infections also tended to be high in general wards. In terms of on patient characteristics, COVID-19 in-hospital infections were high in patients hospitalized in regions other than their residential area (ICU: 5.2%; general ward: 15.1%) and patients diagnosed with malignant neoplasm (ICU: 12.5%; general ward: 18.6%) or circulatory diseases (ICU: 17.7%; general ward: 20.1%).

Table 1

General characteristics of participants (Unit: N/M, %/SD)
			ICU(n = 31,157)						General ward (n = 69,260)
			COVID-19 infection					P-value	COVID-19 infection				P-value
			Yes				No	P-value	Yes		No		P-value
Nurse to bed/patient ratio
	ICU	General ward
	< 0.5	< 2	806	(4.7)	16,525	(95.4)		< .0001	2,041	(14.9)	11,648	(85.1)	< .0001
	< 0.77	< 3	299	(5.1)	5,618	(95.0)			3,817	(12.5)	26,834	(87.6)
	< 1.1	< 4.5	121	(4.4)	2,636	(95.6)			895	(10.8)	7,430	(89.3)
	< 1.5	< 6	114	(4.3)	2,511	(95.7)			661	(9.4)	6,406	(90.7)
	≥ 1.5	≥ 6	60	(2.4)	2,467	(97.6)			999	(10.5)	8,529	(89.5)
Proportion of Night Shift Fixed Nurse(%)
	0		1,050	(4.4)	23,068	(95.7)		< .0001	6,311	(11.7)	47,536	(88.3)	< .0001
	< 10		313	(4.7)	6,318	(95.3)			1,711	(12.8)	11,619	(87.2)
	< 15		17	(6.9)	230	(93.1)			130	(16.0)	682	(84.0)
	< 20		14	(14.6)	82	(85.4)			130	(20.8)	496	(79.2)
	< 25		6	(9.2)	59	(90.8)			81	(19.6)	332	(80.4)
	≥ 25								50	(21.6)	182	(78.5)
Proportion of nursing assistant
	≤ 5		433	(4.3)	9,709	(95.7)		< .0001	1,710	(12.3)	12,196	(87.7)	< .0001
	≤ 15		574	(5.4)	10,003	(94.6)			2,576	(15.7)	13,878	(84.3)
	≤ 30		295	(3.9)	7,211	(96.1)			2,019	(12.0)	14,770	(88.0)
	> 30		98	(3.3)	2,834	(96.7)			2,108	(9.5)	20,003	(90.5)
Type of hospital
	Hospital		4	(1.1)	358	(98.9)		< .0001	2,095	(8.9)	21,374	(91.1)	< .0001
	General hospital		738	(4.1)	17,158	(95.9)			3,654	(12.6)	25,249	(87.4)
	Tertiary hospital		658	(5.1)	12,241	(94.9)			2,664	(15.8)	14,224	(84.2)
Bed
	≤ 100		-	(0.0)	4	(100.0)		< .0001	659	(7.6)	8,026	(92.4)	< .0001
	≤ 300		120	(1.7)	6,816	(98.3)			2,685	(10.5)	22,888	(89.5)
	≤ 700		511	(5.8)	8,322	(94.2)			2,023	(13.9)	12,580	(86.2)
	≤ 1,000		474	(5.6)	8,024	(94.4)			1,816	(16.0)	9,524	(84.0)
	> 1,000		295	(4.3)	6,591	(95.7)			1,230	(13.6)	7,829	(86.4)
Region
	Capital area		538	(3.1)	16,972	(96.9)		< .0001	2,143	(10.3)	18,573	(89.7)	< .0001
	Metropolitan		414	(5.3)	7,479	(94.8)			2,537	(15.1)	14,260	(84.9)
	Other		448	(7.8)	5,306	(92.2)			3,733	(11.8)	28,014	(88.2)
Hospitalization in residential area
	Yes		1,011	(4.3)	22,694	(95.7)		0.0006	6,304	(11.4)	49,010	(88.6)	< .0001
	No		389	(5.2)	7,063	(94.8)			2,109	(15.1)	11,837	(84.9)
Gender
	Male		916	(4.8)	18,046	(95.2)		0.0004	4,469	(12.8)	30,411	(87.2)	< .0001
	Female		484	(4.0)	11,711	(96.0)			3,944	(11.5)	30,436	(88.5)
Major diagnosis
	Respiratory system disease		90	(8.2)	1,002	(91.8)		< .0001	461	(8.9)	4,717	(91.1)	< .0001
	Malignant neoplasms		362	(12.5)	2,531	(87.5)			659	(18.6)	2,887	(81.4)
	Circulatory system disease		218	(17.7)	1,013	(82.3)			1,466	(20.1)	5,825	(79.9)
	Other		730	(2.8)	25,211	(97.2)			5,827	(10.9)	47,418	(89.1)
Number of COVID-19 vaccinations			2.41	± 1.27	1.55	± 1.46		< .0001	2.48	± 1.23	2.31	± 1.33	< .0001
Age
	≤ 40		50	(2.2)	2,239	(97.8)		< .0001	615	(7.4)	7,656	(92.6)	< .0001
	≤ 55		200	(4.5)	4,257	(95.5)			1,214	(11.2)	9,674	(88.9)
	≤ 65		297	(4.5)	6,238	(95.5)			1,922	(12.5)	13,416	(87.5)
	≤ 75		470	(4.5)	9,916	(95.5)			2,732	(13.2)	17,927	(86.8)
	> 75		383	(5.1)	7,107	(94.9)			1,930	(13.7)	12,174	(86.3)
CCI
	0		318	(3.0)	10,162	(97.0)		< .0001	2,953	(9.8)	27,269	(90.2)	< .0001
	1		292	(3.5)	8,036	(96.5)			2,061	(12.6)	14,344	(87.4)
	2		214	(4.0)	5,119	(96.0)			1,363	(13.4)	8,827	(86.6)
	≥ 3		576	(8.2)	6,440	(91.8)			2,036	(16.4)	10,407	(83.6)
Insurance
	Employee		682	(4.1)	15,935	(95.9)		0.0019	4,422	(11.6)	33,797	(88.4)	< .0001
	Self-insured		522	(4.9)	10,045	(95.1)			2,775	(12.5)	19,421	(87.5)
	Medicaid		196	(4.9)	3,777	(95.1)			1,216	(13.8)	7,629	(86.3)
Income
	Low		448	(4.6)	9,283	(95.4)		0.7523	2,812	(12.4)	19,842	(87.6)	0.0422
	Low-moderate		244	(4.6)	5,107	(95.4)			1,398	(11.6)	10,710	(88.5)
	Moderate-high		303	(4.6)	6,354	(95.5)			1,807	(11.9)	13,420	(88.1)
	High		405	(4.3)	9,013	(95.7)			2,396	(12.4)	16,875	(87.6)
Year of admission
	2020		12	(1.0)	1,236	(99.0)		< .0001	104	(4.0)	2,493	(96.0)	< .0001
	2021		73	(0.8)	9,006	(99.2)			461	(6.7)	6,413	(93.3)
	2022		1,315	(6.3)	19,515	(93.7)			7,848	(13.1)	51,941	(86.9)
Number of infected patients per 1,000 population			0.99	± 0.29	0.81	± 0.44		< .0001	0.93	± 0.38	0.88	± 0.43	< .0001
Total			1,400	(4.5)	29,757	(95.5)			8,413	(12.2)	60,847	(87.9)

Figure 1 shows the average number of nurses and nursing assistants by type of medical institution where COVID-19 patients were hospitalized. Hospitals showed a decline in both nurses and nursing assistants; general hospitals saw a decline in nurses, but there was no decline in nursing assistants. In contrast, both nurses and nursing assistants tended to increase in tertiary hospitals. Figure 2 shows the nursing grade of ICUs and general wards in tertiary hospitals and general hospitals.

In the case of general hospital ICUs, the proportion of hospitals with a nurse-to-bed ratio of less than 0.5 decreased from 24.7% in 2020 to 17% in 2022, while the nurse-to-bed ratio of more than 1.5 increased from 9.0% in 2020 to 11.5% in 2022. On the other hand, the nurse-to-bed ratio of less than 0.5 in the ICUs of tertiary hospitals increased from 82.9% in 2020 to 93.3% in 2022. In general wards, the number of general hospitals with a nurse-to-patient ratio of less than 3 increased from 69.8% in 2020 to 78.5% in 2022, and for tertiary hospitals, a nurse-to-patient ratio of less than 2 increased from 41.7% in 2020 to 68.9% in 2022 increased.

Table 2 shows the results of survival analysis on the impact of nurse staffing on COVID-19 hospital infection. In both the ICUs and general wards, COVID-19 nosocomial infections tended to increase as the nurse-to patients (or beds) ratio increased, and in the case of the ICUs, only cases where the nurse-to-bed ratio was less than 1.1 were statistically significant. Compared with medical institutions that do not operate fixed night-shift nurses, the number of COVID-19 infections decreased when the proportion of fixed night-shift nurses was less than 10% of all nurses in both ICUs (hazard ratio [HR]: 0.705, 95% confidence interval [CI]: 0.613–0.811) and general wards. In general wards, COVID-19 in-hospital infections increased when the proportion of night-shift nurses was more than 10% compared with hospitals that did not operate night-shift nurses. Additionally, COVID-19 in-hospital infections increased when patients lived in metropolitan cities or other regions, or were hospitalized in hospitals outside their residential areas.

Table 2

Results of survival analysis of the relationship between nurse staffing and COVID-19 infection
				ICU			General ward
				HR	95% CI		HR	95% CI
Nurse to bed/patient ratio
	ICU		General ward
	< 0.5		< 2	1.000	-	-	1.000	-	-
	< 0.77		< 3	1.192	1.014	1.401	1.287	1.170	1.415
	< 1.1		< 4.5	1.318	1.048	1.657	1.315	1.156	1.496
	< 1.5		< 6	1.088	0.843	1.403	1.253	1.086	1.445
	≥ 1.5		≥ 6	1.039	0.734	1.470	1.314	1.139	1.515
Proportion of Night Shift Fixed Nurse(%)
		0		1.000	-	-	1.000	-	-
		< 10		0.705	0.613	0.811	0.782	0.737	0.829
		< 15		1.264	0.757	2.111	1.223	1.023	1.461
		< 20		1.201	0.684	2.108	1.707	1.430	2.037
		< 25		1.165	0.510	2.658	1.476	1.180	1.847
		≥ 25					1.509	1.133	2.012
Proportion of nursing assistant
		≤ 5		1.000	-	-	1.000	-	-
		≤ 15		1.140	0.993	1.310	1.227	1.146	1.315
		≤ 30		1.071	0.876	1.309	1.242	1.137	1.357
		> 30		1.769	1.299	2.409	1.425	1.272	1.598
Type of hospital
		Hospital		0.628	0.225	1.756	0.600	0.521	0.692
		General hospital		0.851	0.700	1.034	0.760	0.676	0.853
		Tertiary hospital		1.000	-	-	1.000	-	-
Bed
		≤ 100					0.951	0.815	1.110
		≤ 300		0.526	0.387	0.715	0.888	0.784	1.006
		≤ 700		1.004	0.795	1.267	0.945	0.844	1.058
		≤ 1,000		1.004	0.856	1.176	1.003	0.927	1.084
		> 1,000		1.000	-	-	1.000	-	-
Region
		Capital area		1.000	-	-	1.000	-	-
		Metropolitan		1.306	1.133	1.506	1.272	1.195	1.355
		Other		1.435	1.208	1.704	1.034	0.965	1.108
Hospitalization in residential area
		Yes		1.000	-	-	1.000	-	-
		No		1.248	1.105	1.408	1.184	1.124	1.248
Gender
		Male		1.010	0.904	1.129	0.965	0.923	1.008
		Female		1.000	-	-	1.000	-	-
Major diagnosis
		Respiratory system disease		1.806	1.445	2.257	0.932	0.847	1.026
		Malignant neoplasms		2.562	2.236	2.935	1.440	1.323	1.567
		Circulatory system disease		3.646	3.111	4.272	1.716	1.613	1.826
		Other		1.000	-	-	1.000	-	-
Number of COVID-19 vaccinations				1.212	1.160	1.267	1.021	1.002	1.041
Age
		≤ 40		1.000	-	-	1.000	-	-
		≤ 55		1.290	0.944	1.762	0.966	0.876	1.065
		≤ 65		1.004	0.742	1.360	0.909	0.828	0.997
		≤ 75		0.843	0.627	1.134	0.874	0.798	0.956
		> 75		0.863	0.639	1.167	0.840	0.764	0.924
CCI
		0		1.000	-	-	1.000	-	-
		1		0.974	0.828	1.145	1.176	1.111	1.245
		2		0.906	0.758	1.082	1.173	1.098	1.252
		≥ 3		1.411	1.216	1.636	1.221	1.149	1.297
Insurance
		Employee		1.000	-	-	1.000	-	-
		Self-insured		1.154	1.029	1.295	0.993	0.947	1.042
		Medicaid		1.059	0.871	1.287	0.950	0.878	1.027
Income
		Low		0.922	0.787	1.081	0.931	0.873	0.993
		Low-moderate		1.037	0.883	1.217	0.944	0.883	1.010
		Moderate-high		0.971	0.836	1.128	0.963	0.906	1.025
		High		1.000	-	-	1.000	-	-
Year of admission
		2020		1.000	-	-	1.000	-	-
		2021		1.064	0.573	1.975	1.839	1.481	2.284
		2022		6.714	3.479	12.955	3.085	2.469	3.855
Number of infected patients per 1,000 population				0.718	0.539	0.957	0.832	0.758	0.914

Figure 3 shows the relationship between nurse staffing and COVID-19 nosocomial infection at the time of patient infection, at the time of hospitalization (seven days after hospitalization), and after discharge (within seven days after discharge). In ICUs, when the nurse-to-bed ratio was less than 0.77–1.1, COVID-19 nosocomial infection increased 1.689 times upon hospitalization, and as the nurse-to-bed ratio increased, infections within seven days after discharge tended to increase. The size of the effect of nurse staffing on COVID-19 infection was greatest when the nurse-to-bed ratio was less than 1.1–1.5 (after discharge; HR: 1.898, 95% CI: 1.130–3.188). In general wards, COVID-19 nosocomial infections increased as the number of patients per nurse upon hospitalization increased, and COVID-19 infections did not appear to increase after discharge as the nurse-to-patient ratio increased.

This study found that the number of nurses in the medical institutions included in the study decreased during the COVID-19 pandemic and that nurse staffing was associated with healthcare-associated infections. In particular, the number of nurses in medical institutions differed depending on the type of hospital, and while the number of nurses increased in tertiary hospitals, it decreased in general hospitals. As the number of patients in charge per nurse increased, nosocomial COVID-19 infections in hospitals increased, and the size of the effect appeared to vary depending on the time of infection (in-hospital or after discharge). These results suggest that infectious disease outbreaks may affect the movement of nurses, and that appropriate measures are needed to reduce infections within hospitals and improve the quality of care.

Previous studies have shown that infectious diseases have a negative effect on nurses' turnover intentions [25, 26], and the nursing shortage problem appears to have worsened because of infectious diseases. Among medical institutions where COVID-19 patients were hospitalized, both nursing assistants and nurses increased in tertiary hospitals, and the number of nursing assistants increased slightly in general hospitals. This phenomenon suggests that the negative impact of the pandemic may have influenced nurse retention in medical institutions, but may not be the only factor. The labor market has expanded as the number of temporary workers required for infection control has increased owing to the COVID-19 outbreak [18], which may affect the movement of nurses. The COVID-19 pandemic demanded more nurses, and this, combined with the government's incentive policy (incentives are provided as the nursing grade is higher or the proportion of fixed night-shift nurses increases), may have encouraged medical institutions to hire more nurses. Compensation is a major factor affecting nurse turnover [23], and considering that Korean nurses' wages are relatively low [27], about half that of specialists, the turnover of nurses may not be surprising. However, the wage gap between medical institutions and the low nurse-to-patient ratio at tertiary hospitals may have influenced nurses' preference for medical institutions [20, 28, 29], and as a result, the number of nurses may have increased only in tertiary hospitals.

This study also supports previous research showing that nurses are the most important healthcare workers for preventing healthcare-associated infections [8, 17, 30]. In ICUs, healthcare-associated infections increased 1.192 to 1.318 times when the number of beds per nurse was less than 0.5–1.1, and in general wards, when the nurse-to-patient ratio was 2 or more, the risk of healthcare-associated infections increased 1.253 to 1.315 times. In a pandemic, nurses face a variety of tasks in addition to their existing duties and must provide more nursing services to patients, so a shortage of nursing staff may affect infection control in hospitals [31]. However, it appears that an increase in the proportion of fixed night-shift nurses may have a somewhat negative impact on infection control. In both general wards and ICUs, there was a significant association with a decrease in healthcare-associated infections when the proportion of fixed night-shift nurses was less than 10%; contrastingly, when the number was more than 10%, the risk of infection actually increased. A plausible explanation for these results may be related to nursing staff shortages.

The fixed night nurse system, which was introduced to solve the problem of nursing shortages, provides incentives to medical institutions based on the proportion of fixed night-shift nurses. The system was first introduced in hospitals in 2017 and then applied to tertiary hospitals in 2022; most medical institutions with a fixed night-shift nurse proportion exceeding 10% in 2022 were hospitals (Supplementary Figure S1). Based on the general wards of hospitals included in this study, 34.2% of hospitals had more than six patients per nurse, which is a relative shortage of nurses compared with tertiary or general hospitals (Supplementary Figure S2). On the other hand, 80% of medical institutions with a proportion of fixed night nurses of less than 10% where healthcare-associated infections were reduced were general hospitals and tertiary general hospitals, and the number of patients per nurse was less than three. Expanding the flexible work system in hospitals with a shortage of nurses can have a negative impact on infection control [32], and these results suggest that hospitals with a shortage of nurses should expand the number of fixed night-shift nurses after securing a certain level of staffing.

Finally, the results of the subgroup analysis suggest that the magnitude of the effect on nurses' healthcare-associated infections in ICUs and general wards may be different. In the case of ICUs, as the number of beds per nurse increased, the impact on COVID-19 infection after discharge was greater, and in general wards, the higher the nurse-to-patient ratio, the greater the impact on healthcare-associated infections during hospitalization. During an infectious disease epidemic, healthcare workers can act as sources of infection to vulnerable patients, and asymptomatic infection or patients' lack of knowledge about infection prevention may contribute to nosocomial infections [33]. In particular, this may be affected by a shortage of nursing staff, and in general wards where the number of patients per nurse is relatively high, the greater the number of patients per nurse, the greater the impact on the risk of healthcare-associated infections upon hospitalization. On the other hand, the impact of infection after discharge from the ICU was found to be significant, suggesting the need for infection control through continuous follow-up of patients after discharge from the ICU.

Our findings support previous studies showing that more nurses are needed to manage healthcare-associated infections during infectious disease outbreaks[31, 32]. Government policies such as supporting compensation for nurses may be a way to attract more nurses, but this cannot be the only factor and other factors that may affect nurse retention in medical institutions must also be considered [20, 23]. In particular, nurses who work fixed night shifts can have a positive impact on nurses by applying a more flexible work system [34], but in medical institutions with a shortage of nurses, flexible work hours may have a negative impact in terms of nosocomial infection control and should be carefully considered.

Limitations

Our study has several limitations. First, because this study only included medical institutions with patients hospitalized with COVID-19, it did not include all medical institutions. However, as of 2022, almost all Korean general hospitals and tertiary hospitals are included, so it will be a meaningful result. Second, the data used in this study were data from the Korea Disease Control and Prevention Agency and National Health Insurance Service, and the definition of healthcare-associated infections was based on diagnosis date or diagnosis code, so the clinical characteristics of the patients could not be considered. Therefore, in this study, to exclude potential community infection, nosocomial infection was defined as a case that occurred more than seven days after hospitalization according to the existing nosocomial infection criteria. Third, because our data included and evaluated only the total number of nurses in medical institutions, we could not consider the turnover rate and recruitment of nurses. Therefore, additional research considering the turnover rate of nurses is needed. Nonetheless, our data will serve as evidence for the importance of nurses in infection control by presenting changes in nursing during COVID-19, including in many medical institutions, and the impact that nurses had on healthcare-associated infections. Additionally, this study suggests that the introduction of a certain level of flexible working hours can have a positive effect on infection control, and that medical institutions lacking nurses need to carefully expand their work systems.

During the COVID-19 outbreak, the number of nurses at medical institutions decreased, but the impact was different depending on the type of medical institution, and the gap in staffing appears to have actually widened depending on the type of medical institution. The increase in the number of patients per nurse was associated with an increase in healthcare-associated infections; in particular, nosocomial infections increased when the number of nurses applying the flexible working hours system exceeded a certain level among all nurses. In order to manage healthcare-associated infections in medical institutions, it is important to secure a sufficient number of nurses, and expanding the number of nurses applying flexible working hours in medical institutions will require careful review that considers the infection control aspect.

Ethics approval and consent to participate

This study used publicly available secondary data. Individual data were encrypted, and the data set did not allow for participant identification. According to the Bioethics and Safety Act, this study presented only a minimum risk to participants. This study was approved by the Institutional Review Board of the [blank for the review] (IRB number: MC23ZNSI0042).

Consent for publication

Not applicable

Availability of data and materials

The data that support the findings of this study are available in National Health Insurance Services at https://nhiss.nhis.or.kr/bd/ay/bdaya001iv.do. These data were derived from the following resources available in the public domain:

- National Health Insurance Services, https://nhiss.nhis.or.kr/bd/ay/bdaya001iv.do

Acknowledgements

This study used the database of the Korea Disease Control and Prevention Agency (KDCA) and the National Health Insurance Service (NHIS) for policy and academic research. The research number of this study is KDCA-NHIS-2023-1-749.

Conflict of interest none

Funding

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (NRF-2022R1C1C1002766). However, the funding sources did not intervene in study design and data interpretation.

Authors’ contributions

Seungju Kim led the design and conception of the study, performed the data analysis, and wrote the manuscript. Kyu-Tae Han contributed data analysis, interpretation of results, and wrote the manuscript. The authors have read and approved the final manuscript.

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No competing interests reported.

Supplementarymaterial.docx

The impact of COVID-19 on nurse staffing levels and healthcare- associated infections in medical institutions: A retrospective cohort study

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Abstract

Figures

Background

Materials and Methods

Database and data collection

Variables

Statistical analysis

Results

Discussion

Limitations

Conclusions

Declarations

References

Additional Declarations

Supplementary Files

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Version 1