“Can nurse work environment influence readmission risk?” – a systematic review

Figures & data

Figure 1 Flow diagram for article selection.

Table 1 Characteristics of reviewed studies

Source	Country	Objectives	Research design	Study sites	Study period	Study population	Sample size
Bobay et al, 2011^Citation27	USA	To investigate the relationship between unit-level nurse staffing and post-discharge utilization (readmission and ED visit) and the related cost benefit	Cross-sectional observational	4 hospitals	January 2007– June 2007	Adult patients (18 years or older) admitted to medical, surgical, or medical–surgical units	1,660 patients
Diya et al, 2012^Citation36	Belgium	To study the relationship between nurse staffing and patient readmission to ICU and/or OT	Retrospective observational	28 hospitals	2003	Adult cardiac patients (20–85 years) admitted for a coronary artery bypass graft or heart valve procedure	9,054 patients
Evans and Kim, 2006^Citation28	USA	To assess whether lower hospital staff levels cause readmission and other adverse outcomes	Retrospective observational	491 hospitals	1996–2000	Adult patients (18 years or older) admitted to medical or surgical units	9,912,889 admissions
Joynt and Jha, 2011^Citation29	USA	To evaluate the role of hospital nurse staffing and other hospital characteristics in predicting readmission	Cross-sectional observational	4,091 hospitals	2006–2007	Medicare patients with HF	905,764 discharges
McHugh and Ma, 2013^Citation30	USA	To determine the relationship between hospital nursing, nurse work environment, nurse staffing levels, and nurse education, and 30-day readmissions among Medicare patients with HF, AMI, and pneumonia	Cross-sectional observational	412 hospitals	2005–2006	Medicare patients with HF, AMI, and pneumonia	324,042 patients (134,695 HF patients, 60,837 AMI patients, 128,510 pneumonia patients)
McHugh et al, 2013^Citation31	USA	To examine the relationship between registered nurse staffing levels and hospital performance in the HRRP	Cross-sectional observational	2,826 hospitals	2013	Hospitals under the HRRP	2,826 hospitals
Murphy et al, 2011^Citation35	Canada	To investigate the relationships between patient length of stay in hospital, exposure to nursing care, readmission rates, patient satisfaction levels, and patient health status	Cross-sectional observational	122 hospitals	2001	Hospitals with HF readmissions	122 hospitals
Stamp et al, 2014^Citation32	USA	To identify predictors for excess HF readmissions in California, New York, and Massachusetts	Cross-sectional observational	577 hospitals	July 2008– June 2011	Hospitals with CMS HF patients	577 hospitals
Tubbs-Cooley et al, 2013^Citation33	USA	To examine the relationship between staffing ratios and all-cause readmission among children admitted for common medical and surgical conditions	Cross-sectional observational	225 hospitals	2005–2006	Pediatric medical and surgical patients (1–17 years)	90,459 patients
Weiss et al, 2011^Citation34	USA	To determine the direct and indirect effect of nursing unit staffing structure on post-discharge utilization of readmissions and ED visits within 30 days and the related cost benefit	Prospective observational	4 hospitals	January– June 2008	Adult medical and surgical patients (18 years or older)	1,892 patients

Abbreviations: AMI, acute myocardial infarction; CMS, Centers for Medicare and Medicaid Services; ED, emergency department; HF, heart failure; HRRP, hospital readmission reduction program; ICU, intensive care unit; OT, operative theater.

Table 2 Summary of measures of variables of interest and results

Author	Environment measure	Readmission measure	Results	Statistical significance	Mean quality score
Bobay et al, 2011^Citation27	Unit level: Nurse staffing – RN and non-RN hours per patient day (both non-overtime hours and overtime hours)	Patient level: Unplanned/related 30-day readmissions	No significant relationship was identified between staffing and readmission. Cost analysis indicated a cost savings for payers when nurse staffing is higher	−	20
Diya et al, 2012^Citation36	Unit level: Nurse staffing – nursing hours per patient day	Patient level: Readmission into ICU/OR during one hospital stay	Significant relationship was identified. Higher staffing was associated with less readmissions, and this relationship decreased when patients’ severity of illness increased	+	21
Evans and Kim, 2006^Citation28	Hospital level: Nurse staffing – the number of unexpected admissions to a hospital over the next 2 days (also called effective staffing ratio)	Patient level: 7-day and 30-day readmission	Significant relationships were identified in some but not all models/subsamples. Nurse staffing impacted (measured as unexpected surge of admissions) on patients’ probabilities of readmission	±	21
Joynt and Jha, 2011^Citation29	Hospital level: Nurse staffing – full-time equivalent nurses per 1,000 patient days	Patient level: CMS 30-day all cause readmission for HF	Significant relationship was identified. Patients discharged from hospitals with the lowest quartile of staffing levels had higher likelihood of being readmitted within 30 days of discharge than those from hospitals in highest quartile of staffing levels (29.6% versus 26.4%, P<0.001)	+	22
McHugh and Ma, 2013^Citation30	Hospital level: Nurse work environment – measured by the PES-NWI Nurse staffing – average patient-to-nurse ratio	Patient level: CMS 30-day all cause readmission	Significant relationship was identified. Patients cared for in a hospital with a good versus poor work environment had 7% lower odds for HF, 6% lower odds for AMI, and 10% lower for pneumonia. Each additional patient per nurse was associated with a 7% higher odds of 30-day readmissions for HF patients, 6% for pneumonia patients, and 9% for AMI patients	+	22
McHugh et al, 2013^Citation31	Hospital level: Nurse staffing – registered nurse hours per adjusted patient day	Hospital level: CMS hospital 30-day excess readmission ratio	Significant relationship was identified. Hospitals with higher nurse staffing had 25% lower odds of being penalized	+	22
Murphy et al, 2011^Citation35	Hospital level: Nurse staffing – registered nurse hours per patient day	Hospital level: Hospital 30-day readmission rate	No significant relationship was identified between staffing and readmission	−	17
Stamp et al, 2014^Citation32	Hospital level: Nurse staffing – total nursing staff full-time equivalent hours per patient day/total facility personnel full-time equivalent hours per patient day	Hospital level: CMS 30-day risk standardized excess readmission ratio	Significant relationship was identified. HF readmission ratio was decreased by 0.093 for each increase in the ratio of nursing staff full-time equivalent hours per patient day to the total facility personnel full-time equivalent hours per patient day	+	21
Tubbs-Cooley et al, 2013^Citation33	Hospital level: Nurse staffing – patient-to-nurse staffing ratios	Patient level: 14-day and 30-day patient readmission	Significant relationship was identified. Each one patient increase per pediatric nurse led to a 11% increase in the odds of readmission for medical children and a 48% increase in the odds of readmission for surgical children within 15–30 days of discharge, but not readmissions within 14 days	+	22
Weiss et al, 2011^Citation34	Unit level measures: Nurse staffing – RN and non-RN hours per patient day (both non-overtime hours and overtime hours)	Patient level: Unplanned and related 30-day readmission	Significant relationship was identified. One SD increase in RN non-overtime staffing was directly associated with a 4.4% reduction in the likelihood of 30-day readmission; better nurse staffing (increase in RN non-overtime staffing and/or decrease in RN overtime staffing) resulted in cost to hospitals and savings to payers	+	22

Notes: − represents not statistically significant; + represents statistically significant; ± represents statistically significant in some models.

Abbreviations: AMI, acute myocardial infarction; CMS, Centers for Medicare and Medicaid Services; HF, heart failure; ICU, intensive care unit; OR, operative room; PES-NWI, Practice Environment Scale of Nursing Work Index; RN, registered nurse; SD, standard deviation.

Bobay K, Yakusheva O, Weiss M. Outcomes and cost analysis of the impact of unit-level nurse staffing on post-discharge utilization. Nurs Econ. 2011;29(2):69–78, 87.

 Web of Science ®Google Scholar

Diya L, Van den Heede K, Sermeus W, Lesaffre E. The relationship between in-hospital mortality, readmission into the intensive care nursing unit and/or operating theatre, and nurse staffing levels. J Adv Nurs. 2012;68(5):1073–1081.

 Web of Science ®Google Scholar

Evans WN, Kim B. Patient outcomes when hospitals experience a surge in admissions. J Health Econ. 2006;25(2):365–388.

 Web of Science ®Google Scholar

Joynt KE, Jha AK. Who has higher readmission rates for heart failure, and why? Implications for efforts to improve care using financial incentives. Circ Cardiovasc Qual Outcomes. 2011;4(1):53–59.

 PubMed Web of Science ®Google Scholar

McHugh MD, Ma C. Hospital nursing and 30-day readmissions among Medicare patients with heart failure, acute myocardial infarction, and pneumonia. Med Care. 2013;51(1):52–59.

 Web of Science ®Google Scholar

McHugh MD, Berez J, Small DS. Hospitals with higher nurse staffing had lower odds of readmissions penalties than hospitals with lower staffing. Health Aff (Millwood). 2013;32(10):1740–1747.

 Web of Science ®Google Scholar

Murphy GT, Birch S, O’Brien Pallas L, Kephart G, MacKenzie A. Nursing inputs and outcomes of hospital care: an empirical analysis of Ontario’s acute-care hospitals. Can J Nurs Res. 2011;43(1):126–146.

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Stamp KD, Flanagan J, Gregas M, Shindul-Rothschild J. Predictors of excess heart failure readmissions: implications for nursing practice. J Nurs Care Qual. 2014;29(2):115–123.

 Web of Science ®Google Scholar

Tubbs-Cooley HL, Cimiotti JP, Silber JH, Sloane DM, Aiken LH. An observational study of nurse staffing ratios and hospital readmission among children admitted for common conditions. BMJ Qual Saf. 2013;22(9):735–742.

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Weiss ME, Yakusheva O, Bobay KL. Quality and cost analysis of nurse staffing, discharge preparation, and postdischarge utilization. Health Serv Res. 2011;46(5):1473–1494.

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