Abstract

Objective

To assess organizational culture in neonatal intensive care units (NICUs) in Japan.

Design

Cross-sectional survey of organizational culture.

Setting

Forty NICUs across Japan.

Participants

Physicians and nurses who worked in NICUs (n = 2006).

Main Outcome Measures

The Competing Values Framework (CVF) was used to assess the organizational culture of the study population. The 20-item CVF was divided into four culture archetypes: Group, Developmental, Hierarchical and Rational. We calculated geometric means (gmean) and 95% bootstrap confidence intervals of the individual dimensions by unit and occupation. The median number of staff, beds, physicians’ work hours and work engagement were also calculated to examine the differences by culture archetypes.

Results

Group (gmean = 34.6) and Hierarchical (gmean = 31.7) culture archetypes were higher than Developmental (gmean = 16.3) and Rational (gmean = 17.4) among physicians as a whole. Hierarchical (gmean = 36.3) was the highest followed by Group (gmean = 25.8), Developmental (gmean = 16.3) and Rational (gmean = 21.7) among nurses as a whole. Units with dominant Hierarchical culture had a slightly higher number of physicians (median = 7) than dominant Group culture (median = 6). Units with dominant Group culture had a higher number of beds (median = 12) than dominant Hierarchical culture (median = 9) among physicians. Nurses from units with a dominant Group culture (median = 2.8) had slightly higher work engagement compared with those in units with a dominant Hierarchical culture (median = 2.6).

Conclusions

Our findings revealed that organizational culture in NICUs varies depending on occupation and group size. Group and Hierarchical cultures predominated in Japanese NICUs. Assessing organizational culture will provide insights into the perceptions of unit values to improve quality of care.

Introduction

Organizational culture is described as the reflection of values, dominant leadership styles, the language and symbols, the procedures and routines, and the definitions of success that make an organization unique [1]. The most common definition of organizational culture is that by Schien [2], who describes it as ‘a pattern of shared basic assumptions that a group has learned as it solved its problems of external adaptation and internal integration, that has worked well enough to be considered valid and therefore, to be taught to new members as the correct way to perceive, think and feel in relation to those problems’. The study of organizational culture began in the 1980s, and understanding organizational culture has become an essential approach to implementing strategic management in the business field. Similarly, organizational culture in the healthcare industry has also been drawing much attention since the late 1990s, as it has been recognized as an important contributor to healthcare quality and performance. Organizational values and beliefs often focus on quality of care and patient safety, and there is strong evidence of these values in most healthcare organizations [3]. Notably, organizational culture has been shown to have an impact on job satisfaction [46], employee turnover [7], patient satisfaction [5, 8], quality improvement [9], guideline adherence [10] and performance outcomes [11].

Studies have suggested that a cooperative culture is associated with improved patient outcomes in neonatal intensive care, such as a decrease in mortality of preterm infants [12] and higher safety performance [13]. Conversely, there is an argument that the interpretation of results should be done with a degree of caution due to methodological weakness [14, 15]. Considering that organizational culture in healthcare may be a critical indicator of quality improvement, measuring organizational culture is increasingly needed for organizations to identify enhancements and barriers to implementing quality improvement. A number of instruments have been developed to measure organizational culture and have been used in several studies to assess organizational culture in healthcare [1619]. For example, the Competing Values Framework (CVF) is commonly used in the healthcare setting [2023]. To date, however, no studies, including but not limited to healthcare settings, have taken into account the nature of fixed choice (ipsative data) of the CVF scales [6, 8, 9, 20, 2225].

While Japan is a country with one of the lowest infant mortality rates in the world, practice variations and disparities in the morbidity and mortality of very low birth weight infants have been found among neonatal intensive care units (NICUs) [26]. There are multiple clinical and nonclinical factors behind these variations and disparities among facilities, and organizational culture might differ depending on practice performance. Differences in organizational culture in the context of quality improvement of NICUs have not yet been investigated in Japan. This study, therefore, analyzed ipsative data with the view to assess the organizational culture of NICUs in Japan.

Methods

Sample and data

We used baseline data from a self-administered questionnaire for physicians and nurses at 40 NICUs across Japan that participated in the Improvement of NICU Practice and Team Approach Cluster randomized controlled trial (INTACT) [27]. INTACT aimed to improve the outcomes of very low birth weight infants by conducting a multifaceted intervention, which consisted of (i) comprehensive feedback of facility profiles, (ii) on-site educational workshops, (iii) assistance in the development and implementation of action plans and (iv) audits of the status of action plans to provide advice. Questionnaires were distributed to 345 physicians and 1800 nurses. The unlinked anonymous survey was conducted from December 2011 to March 2012.

Ethical consideration

Participation in the study was voluntary and written consent was obtained from each participant. Anonymity and confidentiality of data was assured to all participants. Ethical approval was obtained on 15 July 2011 from the independent review board of INTACT (UMIN000007064), which has its administrative office located at Tokyo Women's Medical University. This study was also approved by the Ethics Committee of Kyoto University Graduate School and Faculty of Medicine on 28 March 2014.

Instrument

Competing Values Framework

The original CVF instrument comprised 16 items validated by Quinn and Spreizer [28]. We used a modified 20-item version from the Quality Improvement Implementation Survey created by Shortell [9] for use in the hospital environment, and included the CVF scales adapted from Zammuto and Krakowe [29]. Shortell's 20-item version is divided into four organizational culture archetypes, measuring over five organizational dimensions: facility character, cohesion, managers, emphasis and facility rewards. The four organizational culture archetypes are referred to as Group, Developmental, Hierarchical and Rational. Group culture focuses on norms and values associated with affiliation, teamwork and participation. This archetype has an internal focus and emphasizes flexibility. Developmental culture focuses on risk-taking innovation and change. This has an external focus and emphasizes flexibility. Hierarchical culture reflects the values and norms associated with bureaucracy. This has an internal focus and emphasizes control. Rational culture focuses on efficiency, productivity and achievement. This archetype has an external focus and emphasizes control. There are two versions of the instrument, Likert scales and ipsative scales. Quinn and Spreizer found that both versions of the instrument conformed to the CVF, and items among the four subscales correlated as predicted in the model [28]. Cronbach Alphas on CVF Likert scales were 0.76–0.90 for Group culture; 0.77–0.86 for Development culture; 0.62–0.70 for Hierarchical culture; and 0.71–0.80 for Rational culture [3032]. In the present study, we used ipsative scales in which respondents allocated 100 points among four items of each cultural dimension according to how well each item described the organization relative to the other items.

Utrecht Work Engagement Scale Japan (UWES-J)

Work engagement was measured using the Japanese 9-item (α = 0.92) short version of the Utrecht Work Engagement Scale Japan [33]. The three sub-dimensions of vigor, dedication and absorption were each represented by three items (e.g. ‘At my job, I feel strong and vigorous’; ‘I am enthusiastic about my job’; and ‘I feel happy when I work intensely’). Respondents rate how often they experience these positive work-related states, using a 7-point scale from 1 = ‘never’ to 7 = ‘always/every day’.

Translation process

The 20-item CVF instrument was translated into Japanese from English by a professional translator, and then back translated by a different translator. To maintain quality control, the back translation was shared with Dr. Stephen M. Shortell, Principal Investigator of the original study [8]. After two authors (H.S. and R.M.) assessed the expressions used in the Japanese CVF, a pretest was performed on 30 physicians and 124 nurses from three pre-intervention facilities that participated in INTACT. The pretest was performed to see whether the Japanese CVF would be appropriate and easily understood. Based on the results of the pretest, the translation was modified and finalized.

Ipsative scales

Ipsative data are scale scores for respondents that always add to the same total [34]. Because the measurement approach requires respondents to allocate a fixed number of points among four culture archetypes, the number of points a respondent assigns to one type of culture affects the number of points he or she assigns to the other types of culture [8]. In these kinds of fixed scales, items are grouped in item sets, and respondents must compare options instead of selecting the most desirable alternative, as is the case with normative scores such as Likert-type scales [35].

Because of the holistic nature of organizational culture, the quadrants (Group, Developmental, Hierarchical and Rational) of CVF scales are interdependent [36]. The ipsative scales maintain the quadrants’ interdependence [28]. Thus, ipsative scales are suitable for use when correlating cases and undertaking Q factor analysis [37]. Considering this feature, ipsative scales are not appropriate for correlations-based analysis such as factor analysis and regression [28].

Statistical analysis

We excluded data from analysis if there was a missing value on any variable in the CVF instrument and if the sum of each subscale was not 100 points. We calculated means and confidence intervals (CIs) of the individual dimensions by hospital and occupation. Hospitals were classified according to the founder. We also calculated median number of staff, beds, physicians’ work hours and work engagement to investigate the differences by hospital types and culture archetypes.

The analysis of ipsative data, however, is problematic because standard statistical analyses yield biased results [35]. Van Eijnattan et al. [35] proposed an alternative statistical method to take into account the ipsative nature of the CVF: the closed part-wise geometric mean, the nonparametric bootstrap 95% CIs and envelopes. Construction of 95% bootstrap CIs is described as follows: (i) extract nonparametric samples from the data, (ii) compute collective dimensional profiles (CDP) for each of the bootstrap samples with the closed part-wise geometric means, (iii) compute the Aitchison distance [38] for each bootstrap CDP, (iv) delete the CDP pertaining to the 5% largest Aitchison distance and (v) determine the upper and lower bounds of each CI based on the highest and lowest values for each component of the remaining 95% of the bootstrap mean CDPs. The suggested approach satisfies basic statistical requirements for the analysis of ipsative data: scale invariance, permutation variance and subcompositional coherence [35]. This approach can correctly compute and compare organizational culture profiles within the same organization. On the other hand, Van Eijnattan et al. argued that the problem of drawing inter-organization contrasts in ipsative scales still remains uncertain. Thus, we can only interpret our results as a relative comparison between organizations. We did not test psychometric property of the scales in this study because correlation-based analysis and factor analysis are not suitable to ipsative data, as explained above. Although there are some statistical limitations on ipsative scales, we gave priority over its merits and applied this method to analyze our data in this study.

All statistical analyses were undertaken in R-software package ‘compositions’ [3941] and SPSS version 21.0 (IBM Corporation, USA). The syntax of R program was obtained from Van Eijnattan [35].

Results

Description of sample

A total of 2006 questionnaires were completed by 316 physicians (response rate = 92%) and 1690 nurses (response rate = 94%). The high response rate was achieved due to the provision of feedback results to each NICU. After excluding missing values and values scored with the same numbers, the final data for analysis were 1758, including 289 physicians and 1469 nurses. The 289 physicians consisted of 56 (19.4%) managerial doctors, 206 (71.3%) doctors, 23 (8.0%) residents and 4 (1.4%) unknown. The 1469 nurses consisted of 124 (8.4%) managerial nurses, 1324 (90.1%) nurses, 3 (0.2%) assistant nurses and 18 (1.2%) unknown. The highest number of years of practice in their own unit was 1–2 years for nurses and less than 1 year for physicians (Table 1).

Table 1

Characteristics of NICUs and their staff

N%
Neonatal intensive care units40100
Facility type
 Public2460.0
 Private1025.0
 Other615.0
Number of beds in unit
 6–91742.5
 10–131127.5
 14–1737.5
 18–21717.5
 >2225.0
Staff1736100
 Head physician563.3
 Staff physician22913.2
 Head nurse1247.1
 Staff nurse132776.4
Years of working experience
 Less than 1 year36721.1
 1–2 years38522.2
 3–4 years36621.1
 5–9 years38322.1
 More than 10 years23513.5
N%
Neonatal intensive care units40100
Facility type
 Public2460.0
 Private1025.0
 Other615.0
Number of beds in unit
 6–91742.5
 10–131127.5
 14–1737.5
 18–21717.5
 >2225.0
Staff1736100
 Head physician563.3
 Staff physician22913.2
 Head nurse1247.1
 Staff nurse132776.4
Years of working experience
 Less than 1 year36721.1
 1–2 years38522.2
 3–4 years36621.1
 5–9 years38322.1
 More than 10 years23513.5
Table 1

Characteristics of NICUs and their staff

N%
Neonatal intensive care units40100
Facility type
 Public2460.0
 Private1025.0
 Other615.0
Number of beds in unit
 6–91742.5
 10–131127.5
 14–1737.5
 18–21717.5
 >2225.0
Staff1736100
 Head physician563.3
 Staff physician22913.2
 Head nurse1247.1
 Staff nurse132776.4
Years of working experience
 Less than 1 year36721.1
 1–2 years38522.2
 3–4 years36621.1
 5–9 years38322.1
 More than 10 years23513.5
N%
Neonatal intensive care units40100
Facility type
 Public2460.0
 Private1025.0
 Other615.0
Number of beds in unit
 6–91742.5
 10–131127.5
 14–1737.5
 18–21717.5
 >2225.0
Staff1736100
 Head physician563.3
 Staff physician22913.2
 Head nurse1247.1
 Staff nurse132776.4
Years of working experience
 Less than 1 year36721.1
 1–2 years38522.2
 3–4 years36621.1
 5–9 years38322.1
 More than 10 years23513.5

Means and CIs of culture archetypes

The hospitals consisted of one Red Cross hospital, 10 university hospitals, 13 private hospitals, 10 public hospitals and 6 national hospitals. Among 40 NICUs, Hierarchical culture was the dominant culture in 35 units and Group culture was dominant in 5 units (Table 2). Figure 1 shows the organizational culture profile of all 40 units. Hierarchical was stronger than other culture types. With regard to the culture archetypes of physicians by units, 23 units had a higher emphasis on Group and Hierarchical, 12 units had a higher emphasis on Group, 4 units had a higher emphasis on Hierarchical and 1 unit had a higher emphasis on Rational and Hierarchical. The smaller units with mostly less than 10 respondents had wide CIs. For example, the highest gmean fell within the range of the other dimensions, or the minimum score of one dimension was close to the maximum score of another dimension. Therefore, more than one dominant culture was present in those small units. This was not the case among total units and nurses because of the large number of respondents. Figure 2 shows the organizational culture profile for the total physician sample. Group (gmean = 34.6) and Hierarchical (gmean = 31.7) archetypes were both higher than Developmental (gmean = 16.3) and Rational (gmean = 17.4). In terms of nurses’ organizational culture, 34 units placed a higher emphasis on Hierarchical, 5 units had a higher emphasis on Group and 1 unit had a higher emphasis on Developmental. Figure 3 shows the organizational culture profile for the total nurse sample. Hierarchical (gmean = 36.3) was the highest, followed by Group (gmean = 25.8), Developmental (gmean = 16.3) and Rational (gmean = 21.7).

Table 2

Culture archetype means, 95% CI in units (total)

UnitHospital typesNo. of bedsNo. of staff (respondents)Culture archetypes
GroupDevelopmentalRationalHierarchical
Mean95% CIMean95% CIMean95% CIMean95% CI
Overall (40 units)175827.126.3–27.916.415.9–16.821.020.4–21.535.534.6–36.4
13123327.020.5–34.914.011.1–16.718.415.5–21.840.532.4–48.9
2594527.422.6–33.214.011.0–17.119.717.1–22.938.932.7–45.3
34308023.921.1–27.020.418.2–22.322.319.9–24.433.429.8–37.1
4393726.122.2–30.316.013.6–18.819.917.7–21.937.933.4–43.0
54124919.415.8–23.612.610.1–15.319.816.6–22.848.242.1–54.4
62217020.316.8–24.013.911.3–16.522.219.5–25.843.638.0–49.3
7462628.223.7–33.519.516.2–23.022.119.2–25.930.125.9–35.4
8592522.817.8–28.814.611.1–18.916.712.3–20.346.037.6–54.8
93124427.722.8–32.715.813.3–18.521.418.1–24.735.129.8–40.8
102244531.026.5–35.416.914.3–19.520.617.9–23.731.426.9–36.2
11193831.927.6–36.317.014.4–20.120.618.3–22.830.526.3–35.2
12293726.321.7–31.316.814.0–19.522.519.1–26.034.429.2–40.1
13394428.724.1–33.416.313.9–19.119.817.1–22.335.230.0–40.7
143124325.822.3–29.516.914.7–19.721.218.5–24.036.132.0–40.7
153113525.419.6–32.412.99.7–16.622.418.1–27.439.432.3–47.1
162124826.421.9–31.516.413.5–19.420.917.6–23.836.330.3–42.3
174216528.124.4–32.219.516.9–22.622.019.0–24.930.426.9–34.6
182154228.323.7–34.018.315.1–21.420.817.4–24.032.627.1–38.6
19262424.819.7–30.815.011.4–18.819.915.8–24.140.333.2–47.5
205156323.519.5–27.816.113.6–19.120.017.5–22.540.535.3–46.0
215123625.621.3–30.417.013.9–20.221.117.1–24.736.330.8–41.5
222124325.522.1–29.117.214.7–19.722.819.8–25.834.630.4–38.9
23592728.923.6–34.417.114.1–20.920.217.2–24.033.828.4–40.0
24492137.631.9–43.420.917.5–24.017.815.0–21.223.819.8–28.3
253187630.226.5–34.017.515.4–19.819.517.4–22.032.828.9–36.9
264217229.526.1–33.122.420.1–24.923.320.5–26.224.821.6–28.0
274184930.625.8–35.317.815.2–20.519.916.8–23.131.727.1–36.8
28363131.025.5–37.215.813.1–19.218.115.0–21.535.028.2–42.1
294123629.023.4–35.121.117.8–24.723.319.9–27.626.721.9–32.2
30563533.730.3–37.319.417.0–21.921.519.0–23.925.422.5–28.5
31392630.825.6–36.315.512.6–18.820.417.6–24.133.327.7–38.9
322123727.723.3–32.916.413.1–19.922.318.0–26.133.727.9–40.0
334215425.722.1–29.721.719.0–24.425.422.2–28.527.323.6–31.5
342186522.318.7–26.316.113.3–18.825.322.–28.736.331.6–41.2
35394321.017.1–25.512.49.6–15.322.319.3–25.244.337.6–51.6
36394331.425.9–37.516.613.7–19.519.216.0–23.032.827.0–39.2
37393823.319.2–27.716.513.–19.922.419.4–25.537.832.8–43.7
384124730.026.3–34.318.816.6–21.120.918.0–23.730.326.2–34.2
39293027.123.1–31.318.515.4–21.924.021.0–27.530.426.3–34.9
403155627.924.9–30.917.715.7–19.921.819.8–23.732.629.7–35.8
UnitHospital typesNo. of bedsNo. of staff (respondents)Culture archetypes
GroupDevelopmentalRationalHierarchical
Mean95% CIMean95% CIMean95% CIMean95% CI
Overall (40 units)175827.126.3–27.916.415.9–16.821.020.4–21.535.534.6–36.4
13123327.020.5–34.914.011.1–16.718.415.5–21.840.532.4–48.9
2594527.422.6–33.214.011.0–17.119.717.1–22.938.932.7–45.3
34308023.921.1–27.020.418.2–22.322.319.9–24.433.429.8–37.1
4393726.122.2–30.316.013.6–18.819.917.7–21.937.933.4–43.0
54124919.415.8–23.612.610.1–15.319.816.6–22.848.242.1–54.4
62217020.316.8–24.013.911.3–16.522.219.5–25.843.638.0–49.3
7462628.223.7–33.519.516.2–23.022.119.2–25.930.125.9–35.4
8592522.817.8–28.814.611.1–18.916.712.3–20.346.037.6–54.8
93124427.722.8–32.715.813.3–18.521.418.1–24.735.129.8–40.8
102244531.026.5–35.416.914.3–19.520.617.9–23.731.426.9–36.2
11193831.927.6–36.317.014.4–20.120.618.3–22.830.526.3–35.2
12293726.321.7–31.316.814.0–19.522.519.1–26.034.429.2–40.1
13394428.724.1–33.416.313.9–19.119.817.1–22.335.230.0–40.7
143124325.822.3–29.516.914.7–19.721.218.5–24.036.132.0–40.7
153113525.419.6–32.412.99.7–16.622.418.1–27.439.432.3–47.1
162124826.421.9–31.516.413.5–19.420.917.6–23.836.330.3–42.3
174216528.124.4–32.219.516.9–22.622.019.0–24.930.426.9–34.6
182154228.323.7–34.018.315.1–21.420.817.4–24.032.627.1–38.6
19262424.819.7–30.815.011.4–18.819.915.8–24.140.333.2–47.5
205156323.519.5–27.816.113.6–19.120.017.5–22.540.535.3–46.0
215123625.621.3–30.417.013.9–20.221.117.1–24.736.330.8–41.5
222124325.522.1–29.117.214.7–19.722.819.8–25.834.630.4–38.9
23592728.923.6–34.417.114.1–20.920.217.2–24.033.828.4–40.0
24492137.631.9–43.420.917.5–24.017.815.0–21.223.819.8–28.3
253187630.226.5–34.017.515.4–19.819.517.4–22.032.828.9–36.9
264217229.526.1–33.122.420.1–24.923.320.5–26.224.821.6–28.0
274184930.625.8–35.317.815.2–20.519.916.8–23.131.727.1–36.8
28363131.025.5–37.215.813.1–19.218.115.0–21.535.028.2–42.1
294123629.023.4–35.121.117.8–24.723.319.9–27.626.721.9–32.2
30563533.730.3–37.319.417.0–21.921.519.0–23.925.422.5–28.5
31392630.825.6–36.315.512.6–18.820.417.6–24.133.327.7–38.9
322123727.723.3–32.916.413.1–19.922.318.0–26.133.727.9–40.0
334215425.722.1–29.721.719.0–24.425.422.2–28.527.323.6–31.5
342186522.318.7–26.316.113.3–18.825.322.–28.736.331.6–41.2
35394321.017.1–25.512.49.6–15.322.319.3–25.244.337.6–51.6
36394331.425.9–37.516.613.7–19.519.216.0–23.032.827.0–39.2
37393823.319.2–27.716.513.–19.922.419.4–25.537.832.8–43.7
384124730.026.3–34.318.816.6–21.120.918.0–23.730.326.2–34.2
39293027.123.1–31.318.515.4–21.924.021.0–27.530.426.3–34.9
403155627.924.9–30.917.715.7–19.921.819.8–23.732.629.7–35.8

1: Red Cross hospitals, 2: University hospitals, 3: Private hospitals, 4: Public hospitals, 5: National hospitals.

Mean: closed part-wise geometric means, 95 % CI: 95 % bootstrap confidence envelopes.

Bold values indicate the highest culture archetypes in each hospital.

Table 2

Culture archetype means, 95% CI in units (total)

UnitHospital typesNo. of bedsNo. of staff (respondents)Culture archetypes
GroupDevelopmentalRationalHierarchical
Mean95% CIMean95% CIMean95% CIMean95% CI
Overall (40 units)175827.126.3–27.916.415.9–16.821.020.4–21.535.534.6–36.4
13123327.020.5–34.914.011.1–16.718.415.5–21.840.532.4–48.9
2594527.422.6–33.214.011.0–17.119.717.1–22.938.932.7–45.3
34308023.921.1–27.020.418.2–22.322.319.9–24.433.429.8–37.1
4393726.122.2–30.316.013.6–18.819.917.7–21.937.933.4–43.0
54124919.415.8–23.612.610.1–15.319.816.6–22.848.242.1–54.4
62217020.316.8–24.013.911.3–16.522.219.5–25.843.638.0–49.3
7462628.223.7–33.519.516.2–23.022.119.2–25.930.125.9–35.4
8592522.817.8–28.814.611.1–18.916.712.3–20.346.037.6–54.8
93124427.722.8–32.715.813.3–18.521.418.1–24.735.129.8–40.8
102244531.026.5–35.416.914.3–19.520.617.9–23.731.426.9–36.2
11193831.927.6–36.317.014.4–20.120.618.3–22.830.526.3–35.2
12293726.321.7–31.316.814.0–19.522.519.1–26.034.429.2–40.1
13394428.724.1–33.416.313.9–19.119.817.1–22.335.230.0–40.7
143124325.822.3–29.516.914.7–19.721.218.5–24.036.132.0–40.7
153113525.419.6–32.412.99.7–16.622.418.1–27.439.432.3–47.1
162124826.421.9–31.516.413.5–19.420.917.6–23.836.330.3–42.3
174216528.124.4–32.219.516.9–22.622.019.0–24.930.426.9–34.6
182154228.323.7–34.018.315.1–21.420.817.4–24.032.627.1–38.6
19262424.819.7–30.815.011.4–18.819.915.8–24.140.333.2–47.5
205156323.519.5–27.816.113.6–19.120.017.5–22.540.535.3–46.0
215123625.621.3–30.417.013.9–20.221.117.1–24.736.330.8–41.5
222124325.522.1–29.117.214.7–19.722.819.8–25.834.630.4–38.9
23592728.923.6–34.417.114.1–20.920.217.2–24.033.828.4–40.0
24492137.631.9–43.420.917.5–24.017.815.0–21.223.819.8–28.3
253187630.226.5–34.017.515.4–19.819.517.4–22.032.828.9–36.9
264217229.526.1–33.122.420.1–24.923.320.5–26.224.821.6–28.0
274184930.625.8–35.317.815.2–20.519.916.8–23.131.727.1–36.8
28363131.025.5–37.215.813.1–19.218.115.0–21.535.028.2–42.1
294123629.023.4–35.121.117.8–24.723.319.9–27.626.721.9–32.2
30563533.730.3–37.319.417.0–21.921.519.0–23.925.422.5–28.5
31392630.825.6–36.315.512.6–18.820.417.6–24.133.327.7–38.9
322123727.723.3–32.916.413.1–19.922.318.0–26.133.727.9–40.0
334215425.722.1–29.721.719.0–24.425.422.2–28.527.323.6–31.5
342186522.318.7–26.316.113.3–18.825.322.–28.736.331.6–41.2
35394321.017.1–25.512.49.6–15.322.319.3–25.244.337.6–51.6
36394331.425.9–37.516.613.7–19.519.216.0–23.032.827.0–39.2
37393823.319.2–27.716.513.–19.922.419.4–25.537.832.8–43.7
384124730.026.3–34.318.816.6–21.120.918.0–23.730.326.2–34.2
39293027.123.1–31.318.515.4–21.924.021.0–27.530.426.3–34.9
403155627.924.9–30.917.715.7–19.921.819.8–23.732.629.7–35.8
UnitHospital typesNo. of bedsNo. of staff (respondents)Culture archetypes
GroupDevelopmentalRationalHierarchical
Mean95% CIMean95% CIMean95% CIMean95% CI
Overall (40 units)175827.126.3–27.916.415.9–16.821.020.4–21.535.534.6–36.4
13123327.020.5–34.914.011.1–16.718.415.5–21.840.532.4–48.9
2594527.422.6–33.214.011.0–17.119.717.1–22.938.932.7–45.3
34308023.921.1–27.020.418.2–22.322.319.9–24.433.429.8–37.1
4393726.122.2–30.316.013.6–18.819.917.7–21.937.933.4–43.0
54124919.415.8–23.612.610.1–15.319.816.6–22.848.242.1–54.4
62217020.316.8–24.013.911.3–16.522.219.5–25.843.638.0–49.3
7462628.223.7–33.519.516.2–23.022.119.2–25.930.125.9–35.4
8592522.817.8–28.814.611.1–18.916.712.3–20.346.037.6–54.8
93124427.722.8–32.715.813.3–18.521.418.1–24.735.129.8–40.8
102244531.026.5–35.416.914.3–19.520.617.9–23.731.426.9–36.2
11193831.927.6–36.317.014.4–20.120.618.3–22.830.526.3–35.2
12293726.321.7–31.316.814.0–19.522.519.1–26.034.429.2–40.1
13394428.724.1–33.416.313.9–19.119.817.1–22.335.230.0–40.7
143124325.822.3–29.516.914.7–19.721.218.5–24.036.132.0–40.7
153113525.419.6–32.412.99.7–16.622.418.1–27.439.432.3–47.1
162124826.421.9–31.516.413.5–19.420.917.6–23.836.330.3–42.3
174216528.124.4–32.219.516.9–22.622.019.0–24.930.426.9–34.6
182154228.323.7–34.018.315.1–21.420.817.4–24.032.627.1–38.6
19262424.819.7–30.815.011.4–18.819.915.8–24.140.333.2–47.5
205156323.519.5–27.816.113.6–19.120.017.5–22.540.535.3–46.0
215123625.621.3–30.417.013.9–20.221.117.1–24.736.330.8–41.5
222124325.522.1–29.117.214.7–19.722.819.8–25.834.630.4–38.9
23592728.923.6–34.417.114.1–20.920.217.2–24.033.828.4–40.0
24492137.631.9–43.420.917.5–24.017.815.0–21.223.819.8–28.3
253187630.226.5–34.017.515.4–19.819.517.4–22.032.828.9–36.9
264217229.526.1–33.122.420.1–24.923.320.5–26.224.821.6–28.0
274184930.625.8–35.317.815.2–20.519.916.8–23.131.727.1–36.8
28363131.025.5–37.215.813.1–19.218.115.0–21.535.028.2–42.1
294123629.023.4–35.121.117.8–24.723.319.9–27.626.721.9–32.2
30563533.730.3–37.319.417.0–21.921.519.0–23.925.422.5–28.5
31392630.825.6–36.315.512.6–18.820.417.6–24.133.327.7–38.9
322123727.723.3–32.916.413.1–19.922.318.0–26.133.727.9–40.0
334215425.722.1–29.721.719.0–24.425.422.2–28.527.323.6–31.5
342186522.318.7–26.316.113.3–18.825.322.–28.736.331.6–41.2
35394321.017.1–25.512.49.6–15.322.319.3–25.244.337.6–51.6
36394331.425.9–37.516.613.7–19.519.216.0–23.032.827.0–39.2
37393823.319.2–27.716.513.–19.922.419.4–25.537.832.8–43.7
384124730.026.3–34.318.816.6–21.120.918.0–23.730.326.2–34.2
39293027.123.1–31.318.515.4–21.924.021.0–27.530.426.3–34.9
403155627.924.9–30.917.715.7–19.921.819.8–23.732.629.7–35.8

1: Red Cross hospitals, 2: University hospitals, 3: Private hospitals, 4: Public hospitals, 5: National hospitals.

Mean: closed part-wise geometric means, 95 % CI: 95 % bootstrap confidence envelopes.

Bold values indicate the highest culture archetypes in each hospital.

Organizational culture profile for total sample (N = 1758); closed part-wise geometric means and 95% bootstrap confidence envelopes.
Figure 1

Organizational culture profile for total sample (N = 1758); closed part-wise geometric means and 95% bootstrap confidence envelopes.

Organizational culture profile for total physician sample (N = 289); closed part-wise geometric means and 95% bootstrap confidence envelopes.
Figure 2

Organizational culture profile for total physician sample (N = 289); closed part-wise geometric means and 95% bootstrap confidence envelopes.

Organizational culture profile for total nurse sample (N = 1469); closed part-wise geometric means and 95% bootstrap confidence envelopes.
Figure 3

Organizational culture profile for total nurse sample (N = 1469); closed part-wise geometric means and 95% bootstrap confidence envelopes.

Association between culture archetypes and organizational/individual factors

Units with a dominant Hierarchical culture had a slightly higher median number of physicians (median = 7, minimum = 4, max = 14) than dominant Group culture (median = 6, minimum = 3, max = 12) among physicians. Units with a dominant Group culture had a higher median number of beds (median = 12, minimum = 6, max = 21) than dominant Hierarchical culture (median = 9, minimum = 6, max = 30). There were no differences in work hours per week (Group median = 70.9, Hierarchical median = 71.0) and work engagement (Group median = 3.4, Hierarchical median = 3.3). Among units with dominant Hierarchical culture among nurses, public hospitals had a higher number of nursing staff (median = 40.5, minimum = 21, max = 68) than other hospitals (university hospitals: median = 37.0, minimum = 18, max = 61; private hospitals: median = 36.0, minimum = 21, max = 65; national hospitals: median = 30.0, minimum = 21, max = 57). Nurses’ work engagement was slightly higher in units with dominant Group culture (median = 2.8, minimum = 2.5, max = 3.3) than units with dominant Hierarchical culture (median = 2.6, minimum = 2.1, max = 3.0). There was no difference in the number of beds depending on dominant culture archetypes (Group: median = 12, minimum = 6, max = 24, Hierarchical: median = 12, minimum = 6, max = 30).

Discussion

This is the first study to assess organizational cultures in a large number of NICUs in Japan. We analyzed ipsative data of the CVF by taking into account its nature. Our findings revealed that dominant culture varied according to occupation. Group and Hierarchical cultures were both strong among physicians, while Hierarchical culture was stronger among nurses. The high Hierarchical culture scores had a positive association with the number of physicians. Nurses were likely to experience greater work engagement when working in units that emphasized Group values.

Physicians identified strongly with cultures emphasizing cohesiveness (group) and rules (hierarchical), which is partially consistent with previous findings that showed Canadian physicians working in NICUs gave their units a significantly higher hierarchical culture score. Mahl et. al argued that this can be explained by the uniquely specialized setting of the level III NICU, which manages the care of extremely premature or critically ill babies and so is generally a more protocol-focused setting with standardization of practice (Hierarchical) [23]. Teamwork is also highly important in life-threatening and time-critical situations such as the NICU, where a team requires clear communication and collaborative actions to avoid needless morbidity and mortality [42, 43]. This feature is clearly related to the other dominant culture (Group) of physicians.

Previous research in adult patients reported that points were equally distributed to four culture archetypes when assessing nurse culture in medical/surgical units [44]. In a survey on nursing staff of 11 dementia units in 11 Dutch nursing homes, 56% of nursing staff scored highest on Group culture, 28% scored highest on Hierarchical, 9% scored highest on Developmental and 7% scored highest on Rational culture [45]. In contrast, we found that nurses placed high value on Hierarchical culture. This result is most likely due to the characteristics of hospital nurses belonging to a nursing department. Nursing departments, particularly in Japan, expect nurses to carry out various management roles, which differ from other departments where nursing activities take place [46]. In addition, group size may influence culture. One report showed that large hospitals with subspecialty services tended to be more hierarchical than smaller hospitals [47].

In this study, Hierarchical culture was dominant in most units overall. This result may be influenced by the high value that nurses place on this culture archetype, yet this is inconsistent with Canadian surveys in which 34 NICUs placed a higher emphasis on Developmental culture [48]. Regarding the association between Group culture and work engagement in nurses, a collaborative work environment of trust and unity might have influenced their motivation. This is consistent with previous findings that group culture values are positively related to job involvement and job satisfaction [4, 24]. On the other hand, according to Shimazu [33], work engagement and burnout may be considered opposite in the sense that they represent a positive (work engagement) and a negative (burnout) aspect of health-related well-being. If work engagement is assumed to be negatively related to burnout, nurses working in units with dominant Hierarchical culture may be more likely to burnout. It is important to take into account individual factors from both positive and negative aspects to explore the implementation of quality management and activities in different culture types.

There are few limitations in this study. The generalizability of our findings is unknown since we studied only NICUs that participated in the randomized controlled trial. Additionally, although the instrument has been adopted to measure culture in healthcare organizations, it has not been confirmed whether the dimensions are relevant to the Japanese context until it is examined qualitatively how health professionals perceive their organization.

Nonetheless, our results demonstrated a variation in perceived values across different units and occupations. It has been suggested that allowance must be made among professional groups such as nurses or physicians for the co-existence of multiple and heterogeneous values inside health organizations [49]. The inconsistency of cultural perceptions among different occupations has been observed in previous research on safety culture in Japan [50]. Although members in an organization belong to the same team, it is important to collect data from all members, and to understand the similarity and difference of cultures by positions or occupations. The importance of variety of respondents has also been suggested by authors, who concluded that the type of organizational culture was not associated with the development of quality management in a multi-country survey that measured organizational culture among only senior managers in European hospitals [51]. Identifying the strengths and weaknesses of organizational culture before initiating quality of care in practice is particularly useful for managers who struggle to improve patient outcomes. Otherwise, the implementations may become counterproductive. Strategy implementation for improving quality of care must differ by the type of organizational culture.

Conclusion

Our findings showed that organizational culture in NICUs varies depending on occupational group and team size. Group and Hierarchical cultures predominate among physicians, while Hierarchical culture is dominant among nurses. Units with strong cohesion and a participatory environment seem to achieve greater work engagement among nurses. Assessing organizational culture will provide insights into quality improvement strategies in healthcare.

Authors’ contributions

H.S. administered the survey, acquired the data, performed the statistical analysis and prepared the draft. N.Y. provided supervision of the study design, the data analysis and interpretation. R.M. supervised the design of the study. T.Ni. and S.K. managed the whole research processes. T.Na. supervised the data analysis and critically revised the manuscript for important intellectual content. All authors were involved in critical commentary and approved the final version of the manuscript.

Acknowledgments

The authors are deeply appreciative of the methodological supervision provided by Dr. Frans M. van Eijnatten (Eindhoven University of Technology, Netherlands). In addition to thanking all physicians and nurses who generously participated in this study, we would like to acknowledge the contribution of the research head office, Dr. Atsushi Uchiyama and Dr. Hideko Mitsuhashi (Tokyo Women's Medical University, Japan). We would also like to thank Dr. Julian Tang and Ms. Emma Barber of the Department of Education for Clinical Research, National Center for Child Health and Development, for proofreading and editing this manuscript.

Funding

This study was supported by Health and Labour Sciences Research Grants in FY2012 (H23-Iryo · Shitei-008) funded by the Ministry of Health, Labour and Welfare, Japan. The funder had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

1

Cameron
KS
,
Quinn
RE
.
Diagnosing and Changing Organizational Culture: Based on the Competing Values Framework
.
New Jersey, USA
:
John Wiley & Sons
,
2006
.

2

Schein
EH
.
Organizational Culture and Leadership
;
Vol. 2
.
New Jersey, USA
:
John Wiley & Sons
,
2010
.

3

Barbera
KM
.
The Oxford Handbook of Organizational Climate and Culture
.
Oxford, UK
:
Oxford University Press
,
2014
.

4

Brazil
K
,
Wakefield
DB
,
Cloutier
MM
et al. .
Organizational culture predicts job satisfaction and perceived clinical effectiveness in pediatric primary care practices
.
Health Care Manage Rev
2010
;
35
:
365
71
.

5

Mallak
LA
,
Lyth
DM
,
Olson
SD
et al. .
Culture, the built environment and healthcare organizational performance
.
Manage Serv Qual
2003
;
13
:
27
38
.

6

Zazzali
JL
,
Alexander
JA
,
Shortell
SM
et al. .
Organizational culture and physician satisfaction with dimensions of group practice
.
Health Serv Res
2007
;
42
:
1150
76
.

7

Mohr
DC
,
Young
GJ
,
Burgess
JF
Jr
.
Employee turnover and operational performance: the moderating effect of group‐oriented organisational culture
.
Hum Resour Manage J
2012
;
22
:
216
33
.

8

Meterko
M
,
Mohr
DC
,
Young
GJ
.
Teamwork culture and patient satisfaction in hospitals
.
Med Care
2004
;
42
:
492
8
.

9

Shortell
SM
,
O'Brien
JL
,
Carman
JM
et al. .
Assessing the impact of continuous quality improvement/total quality management: concept versus implementation
.
Health Serv Res
1995
;
30
:
377
.

10

Ukawa
N
,
Tanaka
M
,
Morishima
T
et al. .
Organizational culture affecting quality of care: guideline adherence in perioperative antibiotic use
.
Int J Qual Health Care
2015
;
27
:
37
45
.

11

Jacobs
R
,
Mannion
R
,
Davies
HT
et al. .
The relationship between organizational culture and performance in acute hospitals
.
Soc Sci Med
2013
;
76
:
115
25
.

12

Nembhard
IM
,
Tucker
AL
.
Deliberate learning to improve performance in dynamic service settings: evidence from hospital intensive care units
.
Organ Sci
2011
;
22
:
907
22
.

13

Profit
J
,
Etchegaray
J
,
Petersen
LA
et al. .
The safety attitudes questionnaire as a tool for benchmarking safety culture in the NICU
.
Arch Dis Child Fetal Neonatal Ed
2012
;
97
:
F127
F32
.

14

Scott
T
,
Mannion
R
,
Marshall
M
et al. .
Does organisational culture influence health care performance? A review of the evidence
.
J Health Serv Res Policy
2003
;
8
:
105
17
.

15

Mannion
R
,
Davies
H
,
Marshall
M
.
Cultural characteristics of ‘high’ and ‘low’ performing hospitals
.
J Health Organ Manag
2005
;
19
:
431
9
.

16

Scott
T
,
Mannion
R
,
Davies
H
et al. .
The quantitative measurement of organizational culture in health care: a review of the available instruments
.
Health Serv Res
2003
;
38
:
923
45
.

17

Jung
T
,
Scott
T
,
Davies
HTO
et al. .
Instruments for the exploration of organisational cultur
.
2007
, Working paper, Aavailable at http://www.scothub.org/culture/instruments.html.

18

Kimberly
J
,
Cook
JM
.
Organizational measurement and the implementation of innovations in mental health services
.
Adm Policy Ment Health
2008
;
35
:
11
20
.

19

Mannion
R
,
Davies
H
,
Scott
T
et al. . Measuring and assessing organizational culture in the NHS (OC1)
2008
. London, UK: National Co-ordinating Centre for National Institute for Health Research Service Delivery and Organisation Programme (NCCSDO).

20

Gifford
BD
,
Zammuto
RF
,
Goodman
EA
.
The relationship between hospital unit culture and nurses’ quality of work life
.
J Healthc Manag
2001
;
47
:
13
25
. discussion-6.

21

Wakefield
BJ
,
Blegen
MA
,
Uden-Holman
T
et al. .
Organizational culture, continuous quality improvement, and medication administration error reporting
.
Am J Med Qual
2001
;
16
:
128
34
.

22

Strasser
DC
,
Smits
SJ
,
Falconer
JA
et al. .
The influence of hospital culture on rehabilitation team functioning in VA hospitals
.
J Rehabil Res Dev
2002
;
39
:
115
26
.

23

Mahl
S
,
Lee
SK
,
Baker
GR
et al. .
The association of organizational culture and quality improvement implementation with neonatal outcomes in the NICU
.
J Pediatr Health Care
2015
;
29
:
435
41
.

24

Goodman
EA
,
Zammuto
RF
,
Gifford
BD
.
The Competing Values Framework: understanding the impact of organizational culture on the quality of work life
.
Organ Dev J
2001
;
19
:
58
68
.

25

Scammon
DL
,
Tabler
J
,
Brunisholz
K
et al. .
Organizational culture associated with provider satisfaction
.
J Am Board Fam Med
2014
;
27
:
219
28
.

26

Kusuda
S
,
Fujimura
M
,
Sakuma
I
et al. .
Morbidity and mortality of infants with very low birth weight in Japan: center variation
.
Pediatrics
2006
;
118
:
e1130
e8
.

27

Improvement of NICU Practice and Team Approach Cluster randomized controlled trial (INTACT) (in Japanese): http://www.nicu-intact.org/about-research.html (10 September 2015, date last accessed).

28

Quinn
RE
,
Spreitzer
GM
.
The Psychometrics of the Competing Values Culture Instrument and an Analysis of the Impact of Organizational Culture on Quality of Life
.
Bingley, UK
:
Emerald
,
1991
.

29

Zammuto
RF
,
Krakower
JY
.
Quantitative and Qualitative Studies of Organizational Culture
.
Bingley, UK
:
JAI Press Inc
,
1991
.

30

Henri
J-F
.
Organizational culture and performance measurement systems
.
Account Organ Soc
2006
;
31
:
77
103
.

31

Helfrich
CD
,
Li
Y-F
,
Mohr
DC
et al. .
Assessing an organizational culture instrument based on the Competing Values Framework: exploratory and confirmatory factor analyses
.
Implement Sci
2007
;
2
:
1
14
.

32

Heritage
B
,
Pollock
C
,
Roberts
L
.
Validation of the organizational culture assessment instrument
.
PLoS One
2014
;
9
:
e92879
.

33

Shimazu
A
,
Schaufeli
W
,
Kosugi
S
et al. .
Work engagement in Japan: validation of the Japanese version of the Utrecht Work Engagement Scale
.
Appl Psychol
2008
;
57
:
510
23
.

34

Baron
H
.
Strengths and limitations of ipsative measurement
.
J Occup Organ Psychol
1996
;
69
:
49
56
.

35

van Eijnatten
FM
,
van der Ark
LA
,
Holloway
SS
.
Ipsative measurement and the analysis of organizational values: an alternative approach for data analysis
.
Qual Quant
2015
;
49
:
559
79
.

36

Zammuto
RF
.
Organizational adaptation: some implications of organizaitonal ecology for strategic choice [1]
.
J Manag. Stud
1988
;
25
:
105
20
.

37

Guilford
JP
.
When not to factor analyze
.
Psychol Bull
1952
;
49
:
26
.

38

Aitchison
J
. The statistical analysis of compositional data.
London, UK
:
Chapman and Hall
,
1986
,
416
pp.

39

van den Boogaart
KG
. Using the Rpackage ‘compositions’: http://www.stat.boogaart.de/compositions/ (11 August 2015, date last accessed).

40

van den Boogaart
KG
,
Tolosana
R
,
Bren
M
.
Compositions: Compositional Data Analysis
.
R package version 1.30-1
,
2013
. Available at http://CRAN.R-project.org/package=compositions.

41

van den Boogaart
KG
,
Tolosana-Delgado
R
.
‘Compositions’: a unified R package to analyze compositional data
.
Comput Geosci
2008
;
34
:
320
38
.

42

Clarke
SP
,
Aiken
LH
.
Failure to rescue: needless deaths are prime examples of the need for more nurses at the bedside
.
Am J Nurs
2003
;
103
:
42
7
.

43

Richardson
J
,
West
MA
,
Cuthbertson
BH
.
Team working in intensive care: current evidence and future endeavors
.
Curr Opin Crit Care
2010
;
16
:
643
8
.

44

Jones
KR
,
DeBaca
V
,
Yarbrough
M
.
Organizational culture assessment before and after implementing patient-focused care
.
Nurs Econ
1997
;
15
:
73
81
.

45

Van Beek
A
,
Gerritsen
D
.
The relationship between organizational culture of nursing staff and quality of care for residents with dementia: questionnaire surveys and systematic observations in nursing homes
.
Int J Nurs Stud
2010
;
47
:
1274
82
.

46

Ryuko
K
,
Kazuoki
K
,
Yukari
M
.
A discussion on the characteristics of organizational structure and operation of the Hospital Nursing Department
.
Bull Toyohashi Sozo Univ
2010
;
14
:
79
93
.

47

Carman
JM
,
Shortell
SM
,
Foster
RW
et al. .
Keys for successful implementation of total quality management in hospitals
.
Health Care Manage Rev
2010
;
35
:
283
93
.

48

Baker
GR
,
King
H
,
MacDonald
JL
et al. .
Using organizational assessment surveys for improvement in neonatal intensive care
.
Pediatrics
2003
;
111
:
e419
e25
.

49

Ancarani
A
,
Di Mauro
C
,
Giammanco
MD
.
How are organisational climate models and patient satisfaction related? A competing value framework approach
.
Soc Sci Med
2009
;
69
:
1813
8
.

50

Kobuse
H
,
Morishima
T
,
Tanaka
M
et al. .
Visualizing variations in organizational safety culture across an inter‐hospital multifaceted workforce
.
J Eval Clin Pract
2014
;
20
:
273
80
.

51

Wagner
C
,
Mannion
R
,
Hammer
A
et al. .
The associations between organizational culture, organizational structure and quality management in European hospitals
.
Int J Qual Health Care
2014
;
26
:
1
7
.

This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact [email protected]