Abstract
Aims
To report on the engagement of Swiss nursing homes and of nurses in expanded roles in quality improvement.
Design
A cross‐sectional study (2018–2019).
Methods
Survey data from a sample of 115 Swiss nursing homes and 104 nurses in expanded roles. Descriptive statistics were used.
Results
Most participating nursing homes reported carrying several quality improvement activities (median of eight out of 10 activities surveyed) but some were only engaged in five activities or less. Nursing homes working with nurses in expanded roles (n = 83) showed greater engagement in quality improvement than those working with none. Nurses with more advanced qualifications (Bachelor's or Master's degree) engaged more in quality improvement than nurses with standard training. Specifically, higher educated nurses were more involved in data‐focused activities. Using nurses in expanded roles can be a way forward for nursing homes seeking to actively carry out quality improvement in their facilities.
Conclusion
Although a large proportion of nurses in expanded roles surveyed were implementing quality activities, their level of engagement depended on their educational level. Our findings support the principle that higher level competencies are a key aspect of data‐based quality improvement in nursing homes. However, as Advance Practice Registered Nurses will remain difficult to recruit in nursing homes, using nurses in expanded roles might contribute to quality improvement.
Keywords: advanced practice nursing, nurses, nursing homes, quality improvement, quality of health care
What does this paper contribute to the wider global clinical community?
Nursing homes working with higher educated nurses in expanded roles are more engaged in quality improvement than nursing homes working without such nurses
Registered nurses in expanded roles—Registered Nurses with experience and broader responsibilities than regular nurses—substantially contribute to quality improvement in nursing homes
1. BACKGROUND
Quality of care issues have long been a concern for nursing homes (NHs). Now, as growing numbers of people with complex geriatric needs deepen a global healthcare worker shortage, NHs are facing increased challenges to provide high quality of care (OECD/European Union, 2013). To meet these challenges, implementing quality improvement is key: it can help NHs identify problems, initiate improvement cycles and evaluate outcomes (Johannessen et al., 2020; OECD/European Union, 2013; Rantz et al., 2012). Quality improvement activities include, for example, monitoring, benchmarking and assessing data, evaluating processes, identifying opportunities for improvement, implementing new approaches to care, and assessing changes in processes or outcomes. Various publications have reported on specific NH quality improvement interventions or projects (Chadborn et al., 2020; Toles et al., 2021). However, as highlighted by previous research, the extent to which NHs are engaged in quality improvement activities as part of their daily practice has rarely been investigated (Bakerjian & Zisberg, 2013; Lee & Wendling, 2004; Ree et al., 2019; Toles et al., 2021) despite legal requirements in some countries (e.g. US) to conduct quality improvement and the growing importance of the topic in a post‐pandemic setting (National Academies of Sciences & Medicine, 2022).
Implementing quality improvement activities requires competencies outside the range held by the majority of NH staff members. Quality improvement can be carried out by a range of professionals and is often implemented by interprofessional teams, but this paper focuses particularly on the contribution of nurses to NH quality improvement. Over the last 20 years, advanced practice Registered Nurses (APRNs) —nurses with advanced skills and knowledge—have been increasingly employed for the development of NH quality (Maier et al., 2017). They can work as either nurse practitioners (NPs) or clinical nurse specialists (CNS), depending on their roles and training, and can positively impact resident outcomes (Morilla‐Herrera et al., 2016; Rantz et al., 2018). Despite high demand for APRN expertise in NHs, their limited numbers have prevented their broad introduction in most European countries, including Switzerland. As an intermediate step, many countries have been working with Registered Nurses in expanded roles (RNXs), referring to Registered Nurses with any additional qualification to take up an expanded role (Basinska, 2021). RNXs have varied educational profiles (e.g. Bachelor, Master), but have to hold qualifications corresponding at minima to a level 5 from the European Qualification Framework (EQF) (Europass European Union) or from the International Standard Classification of Education (ISCED) (UNESCO). They also take on equally varied roles (e.g. clinical, educational) beyond those of regular Registered Nurses (RNs). RNXs can function as mentors and innovators and be particularly well‐suited to perform quality improvement tasks—for instance, by promoting a culture of safety, coaching staff or operationalizing quality‐related data (Basinska, 2021; Bakerjian & Zisberg, 2013). While some studies have reported on RNXs' roles in quality improvement interventions (Zúñiga, 2022; Santosaputri et al., 2019), their specific involvement in implementing NHs self‐administered quality programs has not been investigated.
We used elements of the Quality Assurance and Performance Improvement (QAPI) program as a theoretical foundation to describe NHs' engagement in quality improvement in general and the engagement of RNXs in particular. QAPI is used as a theoretical basis for quality‐oriented changes and aims to guide NHs in assessing quality and in implementing quality improvement programs to ensure the provision of high‐quality care. It is based on 5 elements: (1) Design and Scope; (2) Governance and Leadership; (3) Feedback, Data Systems and Monitoring; (4) Performance Improvement Projects; and (5) Systematic Analysis and Systemic Action. Full descriptions of these elements can be found elsewhere (Centers for Medicare & Medicaid Services, 2012).
This study had two aims: (1) to report on the overall engagement in quality improvement activities in Swiss NHs, exploring differences based on whether they work with an RNX; and (2) to report on RNXs' engagement in NHs in quality improvement activities, exploring differences based on educational level.
2. METHODS
2.1. Study design
This is an original study using data collected as part of the Swiss Nursing Homes Human Resources Project (SHURP) 2018, a cross†sectional, multi†centre study in Swiss NHs.
2.2. Setting and sample
We recruited a convenience sample of 118 NHs from the French and German‐speaking parts of Switzerland. We recruited NHs that had participated in the first [Swiss Nursing Homes Human Ressources Project] (2013–2015) (Schwendimann, 2014) and who agreed to participate in the present study, and randomly selected NHs, NHs recruited via NH associations collaborating with the research team, and NHs that asked to be included. Recruitment lasted between December 2017 and March 2019. Inclusion criteria were for residential facilities providing 24 h social and medical services to older people to be recognized as NHs by their regional authorities. Individuals were included in the sample if they were RNs with an expertise in long‐term NH care (e.g. have a continuous education degree) who in collaboration with the NH upper management, have responsibilities regarding practice development, support interprofessional collaboration and/or coach and support care staff. Furthermore, RNXs had to have worked a minimum of 20% as a RNX for at least a month in one of the NHs of the sample to be included.
2.3. Data collection
Between September 2018 and October 2019, we collected facility and RNX survey data from the participating NHs. Two questionnaires were used to collect data: (1) a facility questionnaire, and (2) a RNX questionnaire. Each participating NH received a paper facility questionnaire which could be filled out within 2 months by the NH manager or by any other person in the NH knowledgeable about the subjects addressed in the questionnaire. If the NH indicated working with an RNX, we sent a separate questionnaire to the RNX. The completed questionnaires were returned to the research team via pre‐stamped envelopes. Data plausibility was checked by the research team.
2.4. Variables and measurements
2.4.1. Nursing home survey
NH managers filled out the facility questionnaire, providing data on facility characteristics (e.g. number of beds, ownership, medical organization). NH managers indicated whether the NH was working with an RNX—and if yes, how many, what was the highest education level and highest continuous education degree of the RNXs, and what were their roles (e.g. clinical, leadership). We assessed the following continuous education degrees for RNXs: Master of Advanced Studies (MAS) equivalent to 60 European Credit Transfer and Accumulation System (ECTS) credits; Diploma of Advanced Studies (DAS) equivalent to 30–59 credits; and Certificate of Advanced Studies (CAS), equivalent to 10–29 credits. All variables are displayed in Table 1. Investigator‐developed questions were used to ask NH managers about 10 quality improvement activities and whether each activity had taken place in their NH over the last 2 years (yes/no questions, see Table 2). We used the QAPI framework to organize these activities; its elements are described in details elsewhere (Centers for Medicare & Medicaid Services, 2012).
TABLE 1.
Nursing homes and RNXs characteristics.
| Nursing homes' characteristics (n = 115) | n (%) | Missing n (%) |
|---|---|---|
| Size | ||
| Large (100 beds and more) | 35 (30.4) | 0 (0.0) |
| Medium (51–99 beds) | 54 (47.0) | |
| Small (50 beds and less) | 26 (22.6) | |
| Legal status | ||
| Public | 54 (47.0) | 0 (0.0) |
| Private | 61 (53.0) | |
| Medical organization: working with… | ||
| In‐house physician only | 12 (10.5) | 1 (0.9) |
| In‐house physician caring for ≥80% of residents, and with residents' general practitioners | 22 (19.3) | |
| In‐house physician caring for <80% of residents, and with residents' general practitioners | 23 (20.2) | |
| Residents' general practitioners only | 57 (50.0) | |
| Responsible person(s) for quality assurance and improvement a | ||
| Director of nursing | 89 (77.4) | 0 (0.0) |
| Nursing home manager | 87 (75.6) | |
| Nurse expert | 50 (43.5) | |
| Nursing quality assurance manager | 48 (41.7) | |
| Another person | 30 (26.9) | |
| No specific person | 1 (0.9) | |
| Nursing homes working with a RNX (n = 83) | 83 (72.2) | 0 (0.0) |
| Highest educational level of the RNX b | ||
| Diploma of Nursing | 27 (33.3) | 2 (2.4) |
| Bachelor's degree in Nursing | 28 (34.6) | |
| Master's degree in Nursing | 21 (25.9) | |
| Other/Could not be attributed | 5 (6.2) | |
| Highest continuous education of the RNX b | ||
| CAS | 22 (30.1) | 10 (12.0) |
| DAS | 8 (11.0) | |
| MAS | 31 (42.5) | |
| None of these degrees | 12 (16.4) | |
| Main role(s) of the RNX a | ||
| Clinical | 69 (83.1) | 0 (0.0) |
| Leadership | 40 (48.2) | |
| Education | 54 (65.1) | |
| Research/Innovation | 31 (35.6) | |
| RNXs' self‐reported characteristics (n = 104) | ||
| Female gender (n, %) | 92 (90.2) | 2 (1.9) |
| Age (n, %) | ||
| ≤30 years | 14 (13.6) | 1 (1.0) |
| 31–40 years | 25 (24.3) | |
| 41–50 years | 19 (18.4) | |
| >51 years | 45 (43.7) | |
| Work experience (mean in years, SD) | ||
| As a nurse in NHs | 6.8 (6.8) | 2 (1.9) |
| As a RNX in NHs | 5.3 (4.9) | 0 (0.0) |
| As a RNX in your current facility | 4.2 (4.0) | 0 (0.0) |
| Highest educational level (n, %) | ||
| Diploma of Nursing | 48 (48.0) | 4 (3.8) |
| Bachelor's degree in Nursing | 35 (35.0) | |
| Master's degree in Nursing | 17 (17.0) | |
| Continuous education degree held (n, %) a | ||
| CAS | 42 (49.4) | 19 (18.3) |
| DAS | 7 (8.2) | |
| MAS | 20 (23.5) | |
| None | 28 (32.9) | |
| Work percentage as RNX (%, SD) | 61.4 (27.4) | 104 (0.0) |
Abbreviations: CAS, Certificate of Advanced Studies; DAS, Diploma of Advanced Studies; GP, General Practitioner, MAS, Master of Advanced Studies; NH, Nursing Home; RNX, Nurses in expanded roles.
Multiple answers possible.
If NHs were working with multiple RNX, they indicated the educational level of the RNX holding the highest educational degree.
TABLE 2.
Quality improvement activities conducted in the facility in the last 2 years, stratified by the presence of a RNX and RNXs' educational level, and organized according to the Quality Assurance and Performance Improvement (QAPI) elements.
| Quality improvement activities conducted in the facility in the last 2 years: % yes | Overall (n = 115 NHs) n (%) | NHs without a RNX (n = 32) n (%) | NHs with a RNX diploma (n = 27) n (%) | NHs with a RNX Bachelor (n = 28) n (%) | NHs with a RNX Master (n = 21) n (%) | SMD | p‐value |
|---|---|---|---|---|---|---|---|
| Governance and Leadership | |||||||
| Treating residents or their relatives' complaints | 85 (73.9) | 20 (62.5) | 22 (81.5) | 24 (85.7) | 12 (57.1) | 0.40 | 0.06 |
| Carrying a staff's satisfaction survey | 81 (70.4) | 20 (62.5) | 21 (77.8) | 23 (82.1) | 13 (61.9) | 0.29 | 0.23 |
| Carrying a residents' satisfaction survey | 66 (57.4) | 21 (65.6) | 14 (51.9) | 17 (60.7) | 10 (47.6) | 0.21 | 0.54 |
| Handling reported errors (e.g. CIRS) | 61 (53.0) | 8 (25.0) | 15 (55.6) | 16 (57.1) | 17 (81.0) | 0.64 | <0.01 |
| Feedback, data systems and monitoring | |||||||
| Giving feedback to teams on the NH's quality of care results (e.g. with key numbers) | 99 (86.1) | 24 (75.0) | 23 (85.2) | 26 (92.9) | 20 (95.2) | 0.34 | 0.12 |
| Setting quality aims for the NH or for specific units | 92 (80.0) | 25 (78.1) | 18 (66.7) | 25 (89.3) | 18 (85.7) | 0.32 | 0.18 |
| Using quality indicators | 90 (78.9) | 20 (62.5) | 20 (74.1) | 24 (88.9) | 20 (95.2) | 0.50 | 0.02 |
| Conducting an internal audit | 81 (70.4) | 21 (65.6) | 15 (55.6) | 23 (82.1) | 17 (81.0) | 0.36 | 0.10 |
| Comparing quality aims with results from the NH or from specific units | 77 (67.0) | 17 (53.1) | 19 (70.4) | 24 (85.7) | 14 (66.7) | 0.39 | 0.06 |
| Performance improvement projects | |||||||
| Implementing a quality improvement or practice development project or program | 81 (70.4) | 21 (65.6) | 15 (55.6) | 23 (82.1) | 19 (90.5) | 0.49 | 0.03 |
| Number of activities done (0–10) (median) | 8 | 6.5 | 7 | 9 | 7 | ||
Note: Total n for educational level stratification is 76 because n = 7 NHs provided information about RNXs' educational level that could not be attributed to one of the three educational groups. Items are ordered in each category from the highest proportion to the lowest. All items had no missing values except for the item “Using quality indicators” which had n = 1 (0.8%) missing value.
Abbreviations: CIRS, Critical Incident Reporting System; NH, Nursing Home; RNX, Nurses in expended roles; SMD, Standardized mean difference.
2.4.2. Nurses in expanded roles survey
RNXs answered the RNX questionnaire. RNXs' survey included questions regarding basic socio‐demographic information (e.g. gender, educational background, work percentage, see Table 1) and questions about their own involvement in 17 quality improvement activities (e.g. organizing satisfaction surveys, performing benchmarking, interpreting results of quality indicators) (yes/no questions, see Table 3), and about quality improvement methods used (e.g. Plan‐Do‐Study‐Act (PDSA) cycle) (see Table 4). The QAPI framework was used to organize the activities.
TABLE 3.
Quality improvement activities implemented by RNXs, stratified by educational level and organized according to the Quality Assurance and Performance Improvement (QAPI) elements.
| Quality improvement activities implemented by RNXs in their current nursing home: % yes | Overall (n = 104 RNXs) n (%) | Missing n (%) | Diploma (n = 48) n (%) | Bachelor (n = 35) n (%) | Master (n = 17) n (%) | SMD | p‐value |
|---|---|---|---|---|---|---|---|
| Governance and leadership | |||||||
| Handling complaints from residents or their relatives | 75 (72.1) | 0 (0.0) | 32 (66.7) | 27 (77.1) | 13 (76.5) | 0.16 | 0.52 |
| Handling reported errors (e.g. CIRS) | 50 (48.5) | 1 (1.0) | 19 (39.6) | 20 (58.8) | 9 (52.9) | 0.26 | 0.21 |
| Organizing/conducting surveys on residents' satisfaction | 39 (37.5) | 0 (0.0) | 17 (35.4) | 16 (45.7) | 4 (23.5) | 0.32 | 0.28 |
| Organizing/conducting surveys on staff's satisfaction | 34 (32.7) | 0 (0.0) | 17 (35.4) | 13 (37.1) | 1 (5.9) | 0.55 | 0.05 |
| Feedback, data systems and monitoring | |||||||
| Setting quality goals for the NH or for specific units | 80 (76.9) | 0 (0.0) | 34 (70.8) | 28 (80.0) | 15 (88.2) | 0.29 | 0.30 |
| Giving feedback to the team about the quality of care provided by the NH (e.g. key figures) | 77 (74.0) | 0 (0.0) | 34 (70.8) | 25 (71.4) | 15 (88.2) | 0.29 | 0.34 |
| Comparing the results of the NH or of specific units with set quality goals | 70 (67.3) | 0 (0.0) | 27 (56.2) | 25 (71.4) | 15 (88.2) | 0.50 | 0.04 |
| Interpreting results of quality surveys (e.g. on quality indicators) | 68 (66.0) | 1 (1.0) | 25 (53.2) | 26 (74.3) | 14 (82.4) | 0.43 | 0.04 |
| Preparing or performing an internal benchmarking/quality follow‐up (i.e. comparing the results of the units within the NH/tracking the results over time) | 61 (59.2) | 1 (1.0) | 18 (37.5) | 26 (74.3) | 14 (82.4) | 0.66 | <0.01 |
| Preparing or performing an external benchmarking (i.e. comparing own NH's results with other NHs' results) | 44 (42.3) | 0 (0.0) | 13 (27.1) | 21 (60.0) | 8 (47.1) | 0.46 | 0.01 |
| Developing diagrams or graphs to display results of quality surveys | 42 (40.4) | 0 (0.0) | 14 (29.2) | 18 (51.4) | 9 (52.9) | 0.33 | 0.07 |
| Performance improvement projects | |||||||
| Implementing an intervention, a program or a quality improvement project | 93 (90.3) | 1 (1.0) | 41 (87.2) | 32 (91.4) | 16 (94.1) | 0.16 | 0.67 |
| PDSA: see Table 4 | |||||||
| Clinical teaching | 91 (87.5) | 0 (0.0) | 44 (91.7) | 30 (85.7) | 14 (82.4) | 0.19 | 0.52 |
| Offering modules/education to the team given by the RNX | 82 (80.4) | 2 (1.9) | 37 (80.4) | 28 (80.0) | 14 (82.4) | 0.04 | 0.98 |
| Offering modules/education to the team organized by the RNX (e.g. by inviting external speakers) | 64 (62.7) | 2 (1.9) | 22 (47.8) | 26 (74.3) | 13 (76.5) | 0.41 | 0.02 |
| Systematic analysis and systematic action | |||||||
| RCA and FMEA: see Table 4 | |||||||
| Leading or conducting case reviews | 82 (78.8) | 0 (0.0) | 34 (70.8) | 30 (85.7) | 15 (88.2) | 0.29 | 0.15 |
| Participating in the strategic planning of the NH | 63 (61.2) | 1 (1.0) | 23 (48.9) | 26 (74.3) | 10 (58.8) | 0.36 | 0.07 |
Note: No educational level could be attributed to n = 4 RNXs.
Abbreviations: CIRS, Critical Incident Reporting System; FMEA, Failure modes and effects analysis; NH, Nursing Home; PDSA, Plan‐Do‐Study‐Act cycle; RCA, Root cause analysis; RNXs, Nurses in expanded roles; SMD; Standardized mean difference.
TABLE 4.
Quality improvement methods used by RNXs in their nursing home.
| Methods used for quality improvement by RNXs in their current nursing home: % yes | Overall (n = 104 RNX) n (%) | Missing n (%) | Diploma (n = 48) n (%) | Bachelor (n = 35) n (%) | Master (n = 17) n (%) | SMD | p‐value |
|---|---|---|---|---|---|---|---|
| Root cause analysis | 58 (58.6) | 5 (4.8) | 24 (52.2) | 21 (63.6) | 12 (75.0) | 0.32 | 0.24 |
| Plan‐Do‐Study‐Act cycle | 42 (42.9) | 6 (5.8) | 13 (27.7) | 17. (54.8) | 11 (68.8) | 0.59 | 0.01 |
| Total quality management, Continuous quality improvement | 29 (29.6) | 6 (5.8) | 13 (27.7) | 11 (34.4) | 4 (26.7) | 0.11 | 0.78 |
| Lean production system, Lean management | 18 (18.8) | 8 (7.7) | 6 (13.0) | 7 (23.3) | 4 (25.0) | 0.21 | 0.40 |
| Failure modes and effects analysis | 4 (4.1) | 7 (6.7) | 2 (4.3) | 2 (6.2) | 0 (0.0) | 0.25 | 0.62 |
| Six sigma / DMAIC | 2 (2.1) | 8 (7.7) | 0 (0.0) | 2 (6.5) | 0 (0.0) | 0.25 | 0.13 |
Note: No educational level could be attributed to n = 4 RNXs. For all of the items, an option to answer “Planned” was given to respondents and was attributed to “No” for this analysis. Items are ordered from the highest proportion of agreement to the lowest.
Abbreviations: CQI, Continuous quality improvement; DMAIC, Define, Measure, Analyse. Improve and Control; FMEA, Failure modes and effects analysis; PDSA, Plan‐Do‐Study‐Act cycle; RCA, Root cause analysis; RNXs, Nurses in expended roles; SMD, Standardized mean difference; TQM, Total quality management.
2.5. Data analysis
We used R version 1.4.1106 for the data analysis. We used descriptive statistics (e.g. frequencies, range, standard deviations (SDs), means, medians) to describe the study sample. At the facility level, we stratified results of NH engagement in quality improvement activities according to whether the NH was employing at least one RNX and the highest educational level of the employed RNXs. At the RNX level, we stratified RNX involvement in quality improvement activities based on their educational level. P‐values and standardized mean differences (SMDs) were computed to describe between‐group differences. The SMD is equivalent to Cohen's D and indicates an effect size, with 0.2–0.5 considered small, >0.5–0.8 medium and >0.8 large (Nakagawa & Cuthill, 2007). There were few missing values, that is, maximum 3.8% of missing values, except for questions about the level of continuous education of nurses (max. 18.3%) and quality improvement methods (max. 7.7%). Missing values were deleted pairwise. Missing values are reported per item in the Tables.
2.6. Ethical considerations
NH management provided written participation consent prior to the start of the study. Participation in the study was voluntary for both NH managers and RNXs. Informed consent was implied by the return of the completed questionnaire to the study team. Respondents could not be identified based on the data collected, but could be linked to the corresponding NH identification number. An ethics waiver ([BASEC Nr Req‐2018‐00420]) was obtained from the responsible Swiss ethics committee (i.e. the Northwest and Central Switzerland ethics committee).
3. RESULTS
The final sample consisted of 115 NHs (response rate: 100%) and 104 RNXs (response rate: 89.7%) from 62 of the 83 NHs which employed RNXs. Figure 1 shows the flowchart for inclusion of participants.
FIGURE 1.
Flowchart of included participants.
3.1. Nursing homes survey.
The characteristics of the NHs are reported in Table 1. The majority of NHs were of medium size (47%, n = 54) and 53% were privately owned (n = 61). For around a third of NHs (33.3%, n = 27), the highest degree held by the RNX employed was a Diploma of Nursing, and 25.9% of NHs employed a RNX with a Masters' degree. NH managers reported that most RNX employed had a clinical role (83.1%, n = 69) or an education role (65.1%, n = 54); few RNXs had a research or innovation‐focused role (35.6%, n = 31). A total of 83 NHs (72.2%) reported employing at least one RNX, of which 33 (39.8%) reported employing two or more (mean: 2.2). A larger proportion of the larger NHs were working with a RNX (82.9%, n = 29) in comparison to medium NHs (72.2%, n = 39) and to small NHs (57.7%, n = 15). A larger proportion of public NHs were working with at least one RNX (77.8%, n = 42) in comparison to privately owned ones (67.2%, n = 41). A total of 84.5% (n = 49) of the NHs working with at least one in‐house physician were also working with RNXs in comparison to 59.6% (n = 34) of the NHs working exclusively with residents' own general practitioners.
NH management indicated that their NHs were involved in a median of eight quality improvement activities (see Table 2). 27.8% (n = 32) of NHs were engaged in five or fewer of these activities; only two (1.7%) reported not being involved in any. The activities most often implemented were giving feedback to the care teams on the facility's quality of care results (86.1%), setting quality aims for the facility or for specific units of the facility (80.0%) and using quality indicators (78.9%). The two activities least done by NHs were carrying a residents' satisfaction survey (57.4%) and handling reported errors (53.0%).
NHs working with RNXs were engaged in a higher total number of activities (median: 8) than those not working with RNXs (median: 6.5). A larger proportion of NHs working with RNXs were engaged in all but one activity (carrying out resident satisfaction surveys). NH involvement in quality improvement also differed based on RNXs' educational levels: the group whose RNXs held a Diploma of Nursing were the group least involved in quality activities. Effect sizes between groups ranged from small (e.g. carrying a residents' satisfaction survey, SMD: 0.21) to medium (e.g. handling reported errors, SMD: 0.64).
3.2. Nurses in expanded roles survey
A total of 90.2% (n = 92) of RNXs were female, the majority (43.7%, n = 45) were over 51 years of age and had a mean of 5.3 years of experience as a RNX working in a NH. Almost half of the respondents (48%) had a Diploma of Nursing, 35% a Bachelor's degree and 17% a Master's degree (see Table 1). RNXs' reported involvement in quality improvement is summarized in Table 3. Overall, the activities most done were implementing an intervention, program or a quality improvement project (90.3%), clinical teaching (87.5%) and offering education to the team (80.4%). Activities least done included conducting surveys on staff (32.7%) or residents' satisfaction (37.5%). Depending on the activities, there were no differences between the groups (e.g. RNX offering education to the team, SMD: 0.04), small effect sizes (e.g. giving feedback to the team about quality, SMD: 0.29) and medium effect sizes (e.g. performing an internal benchmarking, SMD: 0.66).
RNXs reported participating in a median of 12 of the 17 activities surveyed, with differences according to RNXs' educational levels (Diploma: 10 vs. Master/Bachelor: 13). RNXs with higher educational levels reported greater involvement in quality activities; and with one exception—clinical teaching—all surveyed activities were performed by larger proportions of nurses with Bachelors' or Masters' degrees. Specifically, almost all tasks relating to “Feedback, Data Systems and Monitoring” are performed most by Master‐educated RNXs and least by Diploma‐educated RNXs. Table 4 presents RNXs' self‐reported use of quality improvement methods. Those most commonly employed were the Root Cause Analysis (RCA) (58.6%), the PDSA cycle (42.9%) and the Total Quality Management (TQM) and/or Continuous Quality Improvement (CQI) methods (29.6%). RNXs with Master's degrees indicated using the RCA and PDSA the most, followed by RNXs with Bachelors' degrees, and then by those with Diplomas of Nursing.
4. DISCUSSION
In this study, we describe the engagement of 115 Swiss NHs and 104 RNXs in quality improvement activities. The majority of NHs reported implementing several quality improvement activities; and the group working with RNXs (n = 83) were more engaged in such activities than those not working with RNXs. Nurses with more advanced qualifications—with a Bachelor's or a Master's degree—participated more in quality improvement activities and used more quality improvement methods than nurses with standard training (Diploma of Nursing).
In our sample, a median of 8 of the 10 activities surveyed were reported in the facilities within the past two years, covering several dimensions of the QAPI (Centers for Medicare & Medicaid Services, 2012). Very little research exists about what NHs are really implementing in terms of quality improvement in their facilities. When (Lee & Wendling, 2004) surveyed Kansas' NHs about the extent of their quality improvement program, they concluded that few NHs had systematic quality improvement programs in place. More recently, Davila et al. (2021) found that the majority of NH directors reported carrying out “data‐focused strategies” to improve quality outcomes. However, methodological differences make comparisons with our data difficult. While the majority of Swiss NHs leaders reported carrying data‐focused quality work, we do not know the scope of these activities, or how adequately or effectively data were used to make decisions and lead changes. Indeed, other research shows that NH quality improvement efforts are often not integrated within structured or comprehensive systems or processes of implementation (Vaughn et al., 2019; Woo et al., 2017), are often not part of an overall management vision (Lee & Wendling, 2004), and that institutionalizing quality and safety efforts within “wider organisational policies, procedures and norms” remains difficult (Dixon‐Woods et al., 2012). More specifically, the literature has shown that data‐based quality improvement remains largely a challenge in the NH sector (Devi et al., 2021; Rantz et al., 2012; Sales et al., 2012).
Within our sample, 72.2% of NHs indicated working with RNXs. We found that these NHs were more invested in quality work than those that did not employ RNXs. Previous research postulated that factors such as an operational quality and safety system, positive leadership and an organizational culture open to innovation and change were important to develop, integrate and sustain quality improvement efforts (Johannessen et al., 2020; Ree et al., 2019). The employment of RNXs can be a sign of such factors, and of a willingness to invest in care quality, geriatric expertise and quality improvement (Basinska, 2021; Vaughn et al., 2019). This is relevant as the hiring of various types of staff has been recently recommended as a way to enhance the available expertise in US NHs, which is a priority in the long‐term care sector (National Academies of Sciences & Medicine, 2022).
Little information exists on the contribution of nurses to NH quality improvement, but engaging nurses in quality improvement has been deemed valuable (Burhans & Alligood, 2010) and integrating their perceptions on quality improvement, as qualified front‐line care delivery staff responsible to directly perform some of these processes, is an important part of successful quality improvement, and critical to both patient safety and healthcare effectiveness (Navacchi & Lockwood, 2020; Oestberg, 2012). In our sample, RNXs employed by Swiss NHs had diverse educational backgrounds, training and experience, and varied in how they were involved in quality activities. RNXs with Bachelors' or Masters' degrees were more involved in most quality improvement activities. Specifically, higher educated RNXs tend to be more involved in data‐focused tasks. Likewise, the proportion of RNXs who reported working with RCA and PDSA increased with educational level. This suggests that nurses with advanced qualifications are more prepared to work with data than those with standard training. This is supported by several studies that have concluded that RNs without advanced training lack adequate knowledge, skills and tools needed for quality improvement (e.g. to use flowcharts, quality improvement methods, or tools to measure performance and variation, Kovner et al., 2010; Sherwood & Drenkard, 2007). Still, other evidence suggests that institutional barriers or lack of interest limit RNXs participation in quality improvement. For NH managers interested in hiring an RNX specifically to perform quality improvement work, a more educated nurse (e.g. one who is Master‐educated or with a specific training) might bring desirable quality improvement skills and offer nurses an interesting career pathway (Kovner et al., 2010). Financial and institutional barriers to the education, recognition and hiring of such nurses (e.g. legislative and regulatory frameworks restricting scope of practices, required supervision, health insurance reimbursements issues, attractiveness and salaries in geriatric settings) are present in Switzerland as in other countries. As such, given the difficulties involved in recruiting highly qualified nurses and the need for these competencies within NHs (National Academies of Sciences & Medicine, 2022), in‐house training of less qualified nurses might also be an avenue worth exploring.
4.1. Strengths and limitations of the work
The current study has certain strengths, such as a relatively large sample size and strong response rates. Conversely, certain limitations mean that our results must be assessed with caution. First, despite the large sample size, a number of our group comparisons involved small group sizes (<30). Second, we used a convenience sample, meaning there could be a selection bias, limited our results' generalizability. Particularly, we hypothesize that, as high‐performing NH leaders tend to have the interest, availability and resources to participate in research, our results might be biased towards those with greater involvement in quality improvement than the average NH. As not all employed RNXs participated in the survey, non‐responder bias is also a possibility. Additionally, we used self‐reported survey data, which can be a source of bias (e.g. socially acceptable answers). Furthermore, while we asked whether specific activities had been carried out, a positive answer does not mean that the activity was provided either fully or correctly. Finally, this study's cross‐sectional design does not allow for causal inferences.
4.2. Recommendations for further research
Other research designs (qualitative, longitudinal, or based on observations) might be useful to investigate the current and possible contribution of RNXs to quality improvement and resident outcomes in a NH setting. Most research is not able to link quality improvement activities to (improved) resident outcomes, but this needs to be further investigated as this has major implications regarding these activities' relevance in NHs.
5. CONCLUSION
Quality improvement programs help NHs face increasing quality of care challenges. While the majority of this study's NHs were actively engaged in quality improvement activities—which is a positive finding—we do not know the extent, frequency and institutionalization of such activities, and international comparison is difficult. Furthermore, for a large proportion of the participating NHs, greater investments in quality improvement appear needed. Our findings support the principle that higher level competencies are a key aspect of data‐based quality improvement in NHs. A large proportion of RNXs surveyed were implementing quality activities, but their levels of engagement depended on their educational level: overall, those with Bachelors' or Masters' degrees showed more involvement in quality improvement. As APRNs will likely remain difficult to recruit in NHs, using RNXs instead might contribute to quality improvement. However, many RNXs might require further education (e.g. continuous education, in‐house training) to build the competencies necessary to implement quality improvement. NHs should train RNXs with competency profiles that complement their facility existing competencies and their in‐house possibilities to distribute quality improvement tasks.
CONFLICT OF INTEREST STATEMENT
There is no conflict of interest to declare for any of the named authors above.
NO PATIENT OR PUBLIC CONTRIBUTION
Not applicable in this study.
ACKNOWLEDGEMENTS
The Swiss Nursing Home Human Resources Project 2018 (SHURP 2018) study was funded via participation fees paid by the participating nursing homes. The authors are grateful for the nursing homes and the nurses in expanded roles' participation in the study. We also thank all members of the SHURP 2018 team for their support and Chris Shultis for English editing the manuscript.
The authors have checked to make sure that our submission conforms as applicable to the Journal's statistical guidelines described here. There is a statistician on the author team: Michael SIMON. The author(s) affirm that the methods used in the data analyses are suitably applied to their data within their study design and context, and the statistical findings have been implemented and interpreted correctly. The authors agree to take responsibility for ensuring that the choice of statistical approach is appropriate and is conducted and interpreted correctly as a condition to submit to the Journal. State which of the following main statistical methods/approaches were used: Frequently used statistical methods (descriptive, graphical methods, parametric & nonparametric tests, linear & logistic regression).
Favez, L. , Simon, M. , Serdaly, C. , & Zúñiga, F. (2023). Expanded role of nurses in Swiss nursing homes and their engagement in quality improvement: A cross‐sectional study. Nursing Open, 10, 5356–5365. 10.1002/nop2.1773
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.