The Impact of Nurse Staffing Levels and Nurse's Education on Patient
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Haegdorens et al. BMC Health Services Research (2019) 19:864 https://doi.org/10.1186/s12913-019-4688-7 RESEARCH ARTICLE Open Access The impact of nurse staffing levels and nurse’s education on patient mortality in medical and surgical wards: an observational multicentre study Filip Haegdorens1* , Peter Van Bogaert1, Koen De Meester1 and Koenraad G. Monsieurs2 Abstract Background: Growing evidence indicates that improved nurse staffing in acute hospitals is associated with lower hospital mortality. Current research is limited to studies using hospital level data or without proper adjustment for confounders which makes the translation to practice difficult. Method: In this observational study we analysed retrospectively the control group of a stepped wedge randomised controlled trial concerning 14 medical and 14 surgical wards in seven Belgian hospitals. All patients admitted to these wards during the control period were included in this study. Pregnant patients or children below 17 years of age were excluded. In all patients, we collected age, crude ward mortality, unexpected death, cardiac arrest with Cardiopulmonary Resuscitation (CPR), and unplanned admission to the Intensive Care Unit (ICU). A composite mortality measure was constructed including unexpected death and death up to 72 h after cardiac arrest with CPR or unplanned ICU admission. Every 4 months we obtained, from 30 consecutive patient admissions across all wards, the Charlson comorbidity index. The amount of nursing hours per patient days (NHPPD) were calculated every day for 15 days, once every 4 months. Data were aggregated to the ward level resulting in 68 estimates across wards and time. Linear mixed models were used since they are most appropriate in case of clustered and repeated measures data. Results: The unexpected death rate was 1.80 per 1000 patients. Up to 0.76 per 1000 patients died after CPR and 0.62 per 1000 patients died after unplanned admission to the ICU. The mean composite mortality was 3.18 per 1000 patients. The mean NHPPD and proportion of nurse Bachelor hours were respectively 2.48 and 0.59. We found a negative association between the nursing hours per patient day and the composite mortality rate adjusted for possible confounders (B = − 2.771, p = 0.002). The proportion of nurse Bachelor hours was negatively correlated with the composite mortality rate in the same analysis (B = − 8.845, p = 0.023). Using the regression equation, we calculated theoretically optimal NHPPDs. Conclusions: This study confirms the association between higher nurse staffing levels and lower patient mortality controlled for relevant confounders. Keywords: Mortality, Nurse staffing, Nurse education, Outcomes * Correspondence: [email protected] 1Centre for Research and Innovation in Care (CRIC), Department of Nursing and Midwifery Sciences, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Belgium Full list of author information is available at the end of the article © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Haegdorens et al. BMC Health Services Research (2019) 19:864 Page 2 of 9 Background hesitant to support a mandated ward-based minimum. Nurses represent the largest group of hospital workers Furthermore, hospital managers and nurse leaders con- and are responsible for the majority of patient care. In- tinue to struggle on a daily basis when allocating avail- vestigating the impact of their work environment and able nurses to hospital wards taking into account patient staffing on the quality of healthcare and patient safety is acuity and outcomes, nurse’s experience and education therefore crucial. There is a growing body of evidence level, ward workflow and financial factors [10]. It is rea- indicating that inadequate nurse staffing in acute care sonable to hypothesize that if there were more nurses hospitals is associated with adverse events such as available with an appropriate skill-mix, patient care patient falls, health-care related infections, medication would improve. However, the most important limitation errors and in-hospital mortality [1, 2]. Aiken et al. in current research is that the majority of studies investi- showed that improved nurse staffing and a higher pro- gating nurse staffing and patient outcomes use aggre- portion of nurses with a bachelor’s degree reduced the gated hospital level data making the translation to the likelihood of a hospitalised patient dying within 30 days ward level impossible. Additionally, it remains unclear of admission [3]. It has been hypothesised that adequate which methodology is appropriate when measuring nurse staffing influences the quality of patient surveil- nurse staffing and workload [13]. The objective of this lance because it allows nurses to spend more time in dir- study was to explore the relation between nurse staffing ect care. Insufficient staffing leads to the rationing of levels and patient mortality on medical and surgical time to care, which has an important impact on the wards considering nurse’s education level, team compos- occurrence of missed care [4]. This could be an explana- ition, patient’s age and comorbidity. tory factor linking nurse staffing levels and patient out- comes such as in-hospital death [5]. However, it is Methods unclear how nursing workload should be measured and Study design and participants how wards should be staffed to provide safe care. Ideally, This was an observational longitudinal study retro- hospital management aims for a balanced state between spectively analysing the control group of a stepped workload and the number of nurses staffed. Patient clas- wedge randomised controlled trial (SW-RCT) con- sification systems (PCSs) were developed to guide the cerning 14 medical and 14 surgical wards in seven allocation of hospital resources and are used by govern- Belgian hospitals [14].Intheoriginalstudy,weinves- mental organisations to determine hospital financing [6]. tigated the effect of a rapid response system on PCSs include objective and subjective measures of pa- patient outcomes. Therefore, we collected data on pa- tient needs and other care dimensions but are difficult tient morbidity and nurse staffing levels since we to measure and are insufficiently backed by evidence [7]. hypothesised that they could be important con- Nurse-to-Patient Ratios (NPRs) are defined as the pro- founders. All patients admitted to the study wards portion of nurses available per patient and are used to during the control period from October 2013 to distribute the available nursing staff across hospital January 2015 were included in this study. Pregnant wards [8]. However, NPRs do not take into account the patients or children below 17 years of age were ex- complexity of care or ward characteristics. NPRs esti- cluded because, in the SW-RCT, the intervention was mate the number of nurses needed considering the not suitable for these patients. Approval of the ethics amount of occupied beds on a specific ward. The nurs- committees of all local hospitals was obtained before- ing hours per patient day (NHPPD) method is a hand (registration number: B300201317835). This commonly used NPR which is calculated by dividing the study was carried out in seven hospitals geographic- available nursing hours by the number of admitted pa- ally spread throughout Belgium (Flanders, Brussels tients during a 24-h period. Policy makers have been and Wallonia). The SW-RCT study protocol, includ- using PCSs to estimate ward acuity and NPRs to deter- ing the approach to collecting data, was described in mine minimal nurse staffing levels for each ward [9]. To an earlier publication [14]. In the control group 34, date, it is not clear which NPR is suitable considering 267 patient admissions were included during four pe- patient acuity and clinical outcome targets [10]. Because riods of 4 months each. Because of the nature of the of the overwhelming evidence linking nurse staffing with stepped wedge design in the original study, wards and patient outcomes, there has been considerable academic hospitals had unequal sample sizes. discussion about ward based mandatory staffing levels [11]. Mandatory nurse staffing levels are in place in the Measures state of California (United States) and in Victoria and We collected data on two levels during the 16-month Queensland (Australia) [9, 12]. However, since no study period: the patient level and the ward level. Patient evidence-based nurse staffing guidelines exist to date, level data were collected in all admitted patients on the most governments and healthcare organisations are study wards. Ward level data were collected using a Haegdorens et al. BMC Health Services Research (2019) 19:864 Page 3 of 9 subsample of patients (comorbidity) and ward staff re- expressed in hours, were available for 15 days in each cords (all staffing measures). period (T0-T3). Nursing hours per patient day (NHPPD) were calculated for each of those 15 days per period by Outcomes dividing the total amount