The performed ANCOVA identified several relationships between medication errors and various components of the NMWCQ, KUHJSS, and RHCS instruments. The Outcomes variables (p< .001) and Requiring factors of work (p< .001) subareas of patient satisfaction and nurses’ job satisfaction, respectively, along with medication errors, were to be the most significantly affected by other factors.
Nurse managers’ various work duties influenced all aspects of patient satisfaction. One interesting finding was that an increase in most of NMWCQ subscales had a negative impact on different components of patient satisfaction. For example, the decision by a nurse manager to dedicate more time towards Organising, Work well-being, Work atmosphere, Financial management, Clinical nursing or Development of nursing care was found to decrease at least one subscale of patient satisfaction. However, it should be noted that most of these observed decreases were rather slight. In contrast, a nurse manager’s decision to focus more on Communication improved patient perceptions of Pain and apprehension. It is also important to note that more time spent in one area of a nurse manager’s job does not necessarily translate to an improvement in the quality of work. For example, the nurse manager’s overwhelming workload has been described in several recent studies. According to Steege et. al. (2017), fatigue among nurse managers decreases the quality of their work, and can impact decision-making (43). On the other hand, research by Labrague et al. (2018) suggests that – in some cases - more control over a job and a higher extent of responsibility lead to less occupational stress.
The performed ANCOVA also revealed that an increase in certain aspects of nurses’ job satisfaction, namely, Leadership, Requiring factors of work, Work environment, and Working welfare, were negatively correlated with patient satisfaction. This finding could also describe how nurse managers indirectly influence patient satisfaction. Nevertheless, an increase in other aspects of nurses’ job satisfaction, more specifically, Leadership, Requiring factors of work, Work environment, and Participation in decision-making, positively influenced patient assessments of Outcomes variables. This finding is similar to what was reported in a study by De Simone et al. (2018), i.e., patient satisfaction was positively correlated with nurses' job satisfaction, work engagement, self-eﬃcacy, self-regulation, and anticipation, but negatively correlated with nurses' turnover intentions. Another notable finding of our study was that an increase in medication errors negatively affected almost every component of patient satisfaction, including total patient satisfaction.
Moreover, six factors were shown to influence nurses’ job satisfaction. For example, a nurse manager’s decision to dedicate more time to Work well-being,Development of nursing care, and Communication decreased nurses’ job satisfaction to some extent. On the other hand, improved patient perceptions of Outcomesvariables increased nurses’ total job satisfaction, along with their ratings of the Leadership and Requiring factors of work components of job satisfaction. However, an increase in patients’ ratings of Cognition of physical needs decreased nurses’ Work well-being, while a lower number of nurses per nurse manager (n<40) strengthened nurses’ opinions of Leadership yet weakened their views of Working environment. Previous studies have found supporting and motivating staff to be a significant part of nurse managers’ work (8,9). Nurse managers can enhance staff well-being by encouraging staff to participate in planning, and can improve unit performance by being interested in nursing outcomes (5). Moreover, the quality of nurse management at the unit level affects care quality and nurses’ turnover intentions (11,20). Zaghini et al. (2020) found that nurses who are dissatisfied with leadership will have increased feelings of discomfort, which can lead to cynicism. Furthermore, nurses who perform counterproductive work feel more interpersonal strain, which can lead to patients feeling depersonalised and reporting lower levels of satisfaction with care. Karlsson et. al (2019) reported that nurses feel satisfied when they provide patient-centred care, while an excessive workload, interruptions, and incomplete work frustrates nurses. Moreover, nurses enjoy variability in their work, but would like to have control over their work. (20.)
According to prior research, nurse staffing affects patient outcomes (23,27), satisfaction (44), and safety (28). Gunawan et al. (2019) suggest that managers should be more proactive in the human resource management process, from recruitment to personnel appraisal. Moreover, Wong et al. (2013) have previously discussed how leaders influence certain human resource variables and, as such, a leader’s actions may be connected to patient care outcomes, the nurse-to-patient ratio, and number of overtime hours, along with staff expertise, turnover, and absenteeism. Unfortunately, managers at large hospitals are rarely involved in the recruitment process although the aspect of staffing has significant financial implications (45,46).
The most significant impacts in the performed ANCOVA were found for medication errors. There were large inter-hospital differences, as hospitals 1 and 2 had 16 and 23 times more medication errors, respectively, than hospital 3. In addition, units with a small number of nurses (n<40) per nurse manager showed almost 13 times less medication errors than units with more than 40 nurses per nurse manager. Furthermore, a nurse manager’s decision to dedicate more time to Work atmosphere and Planning and evaluation of activities noticeably increased medication errors, with these subareas showing unstandardized coefficients of more than 15 and eight, respectively. An increase in patient ratings of Human resources and Pain and apprehension noticeably decreased medication errors, showing unstandardized coefficients of approximately 30 and 40, respectively. Surprisingly, total patient satisfaction increased medication errors over 70 times, which could be explained by a safe clinical climate to report errors. Some of these factors have also been linked to medication errors in previous studies. Wong et al. (2013) found a strongly negative relationship between transformational leadership and the incidence of adverse events, especially medication errors. Accordingly, units with strong patient safety culture are characterised by organisational learning, continuous improvement, nonpunitive responses to errors, as well as feedback and open communication. Furthermore, these environments include an atmosphere in which employees feel safe to report medication errors, discuss them, and learn from previous mistakes. Accordingly, Hughes et al. (2019) promote the transactional leadership style as an approach that is conducive to reducing medication errors. However, it should be noted that nurse managers should consider contextual circumstances when choosing an appropriate leadership style.
The main limitation of the study was that only 28 units met the inclusion criteria. This small amount of units limited the choice of an appropriate analytic method. Therefore, structural equation modelling was excluded, with analysis of covariance chosen to investigate relationships between the variables (42). Nevertheless, 305 nurses and 651 patients participated in the study. In addition, we only studied patient satisfaction and nurses’ job satisfaction at the unit level. It would have been interesting to examine whether the hours each registered nurse spent per patient affected patient satisfaction or medication errors. However, we did examine how the number of nurses per nurse manager affects patient satisfaction, nurses’ job satisfaction, and medication errors. Hence, the study results provide clarity into the interactions between nurse managers’ work content, nurses’ job satisfaction, patient satisfaction, and medication errors.
The NMWCQ is a new instrument and, as such, needs to be tested more. It is also important to note that all of the questionnaires (NMWCQ, KUHJSS, and RHCS) are based on self-assessment, which can introduce a certain degree of bias as respondents tend to overestimate their own skills (47). However, several studies have reported that the KUHJSS and RHCS are reliable and valid instruments. Medication error data from the HaiPro register are based on nurses’ initiative to report medication errors. Therefore, it is impossible to know whether every medication error has been reported. However, it should be noted that HaiPro is the first adverse event reporting system that was introduced in Finland and is now widely used. To gain a representative picture of medication errors, we decided to collect medication error data over one year, whereas other data were collected over a time period of approximately one month.