Pfaff et al. BMC Health Services Research (2021) 21:70 https://doi.org/10.1186/s12913-020-06053-0 RESEARCH ARTICLE Open Access Social determinants of the impact of hospital management boards on quality management: a study of 109 European hospitals using a parsonian approach Holger Pfaff1* , Antje Hammer1, Marta Ballester2,3,4, Kristina Schubin1, Michael Swora1 and Rosa Sunol2,3,4 Abstract Background: The consolidated framework for implementation research states that personal leadership matters in quality management implementation. However, it remains to be answered which characteristics of plural leadership in hospital management boards make them impactful. The present study focuses on social determinants of implementation power of hospital boards using Talcott Parsons’ sociological concept of adaptation, goal attainment, integration, and latency (AGIL), focusing on the G (goal attainment) and I (integration) factors of this concept. The study aims to test the hypothesis that hospitals with management boards that are oriented toward the quality goal (G) and socially integrated (I) (GI boards) are better at implementing quality management than hospitals with boards lacking these characteristics (non-GI boards). Methods: A cross-sectional mixed-method design was used for data collection in 109 randomly selected hospitals in seven European countries. Data is based on the study “Deepening our understanding of quality improvement in Europe” (DUQUE). We used responses from (a) hospitals’ chief executive officers to measure the variable social integration and the variable quality orientation of the board and (b) responses from quality managers to measure the degree of implementation of the quality management system. We developed the GI index measuring the combination of goal-orientation and integration. A multiple linear regression analysis was performed. Results: Hospitals with management boards that are quality oriented and socially integrated (GI boards) had significantly higher scores on the quality management system index than hospitals with boards scoring low on these features, when controlled for several context factors. Conclusions: Our findings suggest that the implementation power of hospital management boards is higher if there is a sense of unity and purpose within the boards. Thus, to improve quality management, it could be worthwhile to increase boards’ social capital and to increase time designated for quality management in board meetings. Keywords: Quality management, Implementation power, Leadership, Hospital management board, Social capital, Top management team, Consolidated framework for implementation research * Correspondence: holger.pfaff@uk-koeln.de 1 Institute for Medical Sociology, Health Services Research and Rehabilitation Science, Faculty of Human Science, Faculty of Medicine, University of Cologne, Eupener Strasse 129, 50933 Cologne, Germany Full list of author information is available at the end of the article © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. 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BMC Health Services Research (2021) 21:70 Page 2 of 7 Background Based on the GI model of system performance [9, 10], The consolidated framework for implementation research we define the GI factor as follows: The GI factor is given (CFIR) states that personal leadership is an important con- in a group if two conditions are met: (1) strong actions textual determinant for the implementation of quality of the group to attain specific goals (G factor) and (2) a management [1, 2]. However, leadership may be plural [3], high degree of social integration within the group (I fac- as is the case in hospital management boards (HMBs). It tor). Top management teams with the GI factor have a remains to be answered which features of plural leader- sense of unity and purpose, which makes them impact- ship increase the power of a HMB to implement quality ful. Therefore, our hypothesis is that HMBs, which com- management throughout the hospital. bine high goal attainment with regard to quality (G) and Research on success characteristics of HMBs provides high social integration within the board (I) (GI boards) insights into the importance of the structural character- have greater implementation power than HMBs with istics of HMBs. These studies often examine the direct low integration and low quality goal orientation (non-GI relationship between HMBs and health care quality [4– boards). 7], disregarding the mechanisms that transform the pol- itical will of plural leaders into positive health care out- comes. The implementation of quality management Methods systems in the hospitals can potentially mediate between We used data from the multicenter cross-sectional study HMBs and patient care quality. The CFIR underscores “Deepening our understanding of quality improvement the importance of leadership for implementation. We in Europe” (DUQuE) [11]. DUQuE fulfilled the ethical aim to improve this hypothesis by connecting it with so- requirements for research projects as described in the cial theory. Frameworks for implementation research, seventh framework of EU Directorate-General Research. such as CFIR, focus on variables rather than theories; Ethics approval was granted through the Bioethical however, we are convinced that we have to use theories Committee of the Department of Health of the Govern- to explain how these variables function. Thus, we ment of Catalonia, Spain. Data collection in each coun- propose a framework-plus-theory approach in quality re- try complied with confidentiality requirements according search. The CFIR states that leadership commitment is to the national legislation or standards of practice of that essential for the implementation of innovations and country. evidence-based practices [2]. We specify this hypothesis Patient records and other information was anonymized using the well-established sociological concept of AGIL and de-identified prior to analysis. The inclusion criteria by Talcott Parsons [8]. for hospitals were as follows: (a) having 120 beds or The AGIL scheme [8] assumes that social systems more, (b) delivering care for four medical conditions – – such as HMBs – have to fulfill four central func- acute myocardial infection, stroke, hip fracture, and de- tions to survive and be productive: adaptation (A), livery and (c) having a HMB with at least 2 but no more goal attainment (G), integration (I), and latency (L). than 25 board members. The exclusion criterion was Because the function “goal attainment” is closely missing data in the variables used in the regression ana- linked to the CFIR notion of leadership commitment, lysis. An analysis of the missing data showed only minor we focus on the factor goal attainment (G factor). differences between the sample obtained after applying However, our assumption is that the HMBs’ plural only the inclusion criteria (N = 152) and the sample ob- leadership commitment alone is not sufficient to exert tained after applying the exclusion criterion as well (N = power and influence from the top level (HMB) to the 109). There were no or only minor differences in the middle and lower levels of hospital management to distribution of the following variables: public hospitals fully implement a hospital-wide quality management (full sample: 82.9% vs. missing-data-free sample: 82.6%), system. Additionally, HMBs need a certain sense of social capital (mean: 3.27 vs. 3.25), quality orientation unity and agreement within the top management (mean: 3.86 vs. 3.94), and GI index (GI hospitals: 29.5% team. Therefore, based on the AGIL concept, we add vs. 30.3%). There were differences regarding hospital size the factor social integration (I factor) to the G factor. (hospitals with more than 500 beds: 45.4% vs. 51.3%) Social integration makes a group of leaders act like a and small differences regarding teaching status (40.1% single leader, making plural leadership a united lead- vs. 42.2%). Data collection was performed in 109 ran- ership. The integration factor is advantageous because domly selected hospitals in the Czech Republic, France, it allows HMBs to speak with one voice, reach bal- Germany, Poland, Portugal, Spain, and Turkey. In the anced and mature decisions, and communicate the present study, we used the responses of the hospitals’ committed decisions via committed board members chief executive officers (CEOs) and quality managers ob- to the stakeholders they represent (e.g., physicians, tained through web-based questionnaires. Data were col- nurses, and administrators). lected between May 2011 and February 2012. Pfaff et al. BMC Health Services Research (2021) 21:70 Page 3 of 7 Items used in the questionnaire were either newly de- hospital management board” [15] as a proxy for social veloped in English (e.g. quality management system integration of the board. It was derived from a validated index) or translated from existing measures into English scale called social capital of healthcare organizations (e.g. social capital scale) or adapted. The final question- from employees’ perspective (SOCAPO-E), which has naire has been translated into seven languages following been used in previous studies [16, 17]. For this study, a standard protocol for a forward–backward translation the six items of this scale were adapted in order to meas- process supervised by local country coordinators [12, ure social capital among hospital management board 13]. We used a 46-item quality management system members (SOCAPO-B). The scale consists of six items index as the dependent variable measuring the degree of (Cronbach’s alpha: 0.91) measuring the amount of unity implementation of quality management systems in hos- and agreement, common values, mutual trust, mutual pitals from the perspective of the quality managers. This helpfulness, “we” feeling, and good social climate in the index was the sum of scores on the following nine sub- HMBs. The scale reflects central features of the commu- scales: quality policy documents (three items), quality nal aspects of social capital [17–19]. We used a 4-point monitoring by the board (five items), training of profes- Likert scale from “strongly disagree” (1) to “strongly sionals (nine items), formal protocols for infection con- agree” (4). To construct the dichotomous variable “inte- trol (five items), formal protocols for medication and gration index”, which separates HMBs scoring high in patient handling (four items), analyzing performance of social capital (1) from those scoring low (0). Again, we care processes (eight items), analyzing performance of used the upper tercile split and not the median split professionals (three items), analyzing feedback and pa- method based on the assumption that for having ad- tient experiences (three items), and evaluating results equate implementation power, a quite high amount of (six items). Eight of the nine subscales of this index had unity and cohesion within HMBs is needed. sufficient reliability (Cronbach’s alpha: 0.70–0.88), Based on the goal–integration model [9; 10] we devel- whereas one subscale – analyzing feedback and patient oped a GI index by adding both dichotomous variables, experiences – did not. To ensure content validity, we de- resulting in an index with three values: 0 (HBM with cided to include this subscale in the quality management low quality goal orientation and low social capital), 1 system index as well. For details, see Wagner et al. [12]. (HBM low in one of these two variables), and 2 (HBM We used the averaged composite score for the nine sub- high in both variables). Thus, we did not differentiate scales ranging from 0 to 27 points. between the other two combinations – HMB with high To measure the first component of the GI index – the quality goal orientation but without high social capital G factor – we built the index “hospital board quality and HMB without high quality goal orientation but with goal orientation” as a surrogate variable. Based on the high social capital – because both combinations are con- empirical work of Botje and colleagues concerning qual- sidered equivalent in promoting collective action. We ity orientation of hospital management boards [14] we used board size, ownership, hospital size, teaching status measured the goal attainment index by asking the CEOs of hospital, and country as control variables. For the (a) to assess how frequently quality performance was an multivariate analysis, we used multiple linear regression item on the executive board’s agenda during the last year with a restricted and a full model using IBM SPSS (never [1], in a few meetings [2], in most meetings [3], STATISTICS version 26. or in every meeting [4]) and (b) to assess what percent- age of the hospital (management) board’s meeting time Results was typically spent on issues of quality performance Sample characteristics and descriptive statistics (10% or less [1], 11–20% [2], 21–30% [3], 31–40% [4], The dataset included in this analysis contained only hos- and greater than 40% [5]). This index was built by add- pitals with complete data on all variables used in the ing the answers of these two questions. On the basis of multiple regression model (N = 109). The sample in- this index, we then constructed a dichotomous variable cluded seven countries (see Table 1); 82.6% were public using the tercile split method, creating a binary variable: hospitals, and 42.2% were teaching hospitals. Approxi- low quality orientation (low and medium tercile [0]) and mately 11% of the hospitals had less than 200 beds; high quality orientation (upper tercile [1]). We used the 37.6% had 200–500 beds; 33.9% had 501–1000 beds; and upper tercile split method and not the median split 17.4% had more than 1000 beds. The average number of method based on the assumption that it is necessary to HMB members in our sample was 7.6 (SD = 4.1). The have a strong goal orientation in the HMBs to have an mean of the social capital scale – as one component of impact on the followers across different management the GI index – was 3.3 (SD = 0.61), measured on a scale levels. ranging from 1 to 4. The dichotomization of this scale To measure the second component of the GI index – using an upper tercile split showed that 64.2% and 35.8% the I factor – we used the scale “social capital within the of the hospitals, respectively, had low and high HMB Pfaff et al. BMC Health Services Research (2021) 21:70 Page 4 of 7 Table 1 Percentage of the hospitals in European countries (explained variance: 27,6%; p < 0.001), the introduction participating in DUQUE used in the analysis (N = 109) of the GI factor into the equation led to a significant in- N % crease of 5,7% in explained variance (p < 0.05); the full Country Czech Republic 19 17.4 model explained 33% of the variance in the quality man- France 17 15.6 agement system index. Hospitals with boards high in the GI index had significantly better scores on the quality Germany 7 6.4 management system index than hospitals with boards Poland 17 15.6 low in quality goal orientation and in social capital (ref- Portugal 19 17.4 erence group: non-GI-board hospitals; p < 0.01). The re- Spain 19 17.4 sults also showed that hospitals that meet only one of Turkey 11 10.1 both impact requirements – HMB quality goal orienta- Total 109 100.0 tion or HMB social capital – have an advantage over hospitals that fulfill none of the two requirements, but this advantage was not significant. We conducted regres- social capital. The mean of the hospital board quality sion diagnostics by checking the assumptions of linear- goal orientation index – the other component of the GI ity, variance homogeneity and normally distributed index – was 3.9 (SD = 1.61), measured on a scale ranging errors by means of scatter- and QQ-plots of the stan- from 0 to 7. The dichotomization of this scale using an dardized residuals, which proved to be well-behaved. upper tercile split indicated that 58.7% and 41.3% of the Furthermore, there were no signs of multicollinearity as hospitals, respectively, showed low and high HMB qual- measured by the condition index. ity goal orientation. The creation of the goal–integration index led to three GI levels, with 40.4% of the HMBs (N = 44) on the lowest level, 42.2% (N = 46) on the mid- Discussion dle level, and 17.4% (N = 19) on the highest level (see Implementation of quality management systems in hos- Table 2). Moreover, the average mean of the outcome pitals is one of the central tasks in quality and safety. Ac- variable quality management system index was 19.3 cording to the CFIR, one way to promote this is using (SD = 4.6) on a scale ranging from 0 to 27. leadership commitment [2]. In the case of HMBs, leader- ship is plural leadership. The present study aimed to in- Regression analyses vestigate which conditions foster the implementation Checking for outliers with Cook’s distance proved to be power of plural leadership. To answer this question, we negative, indicating no outliers. The results of the linear considered the HMB as a social system and used Par- regression analysis (see Table 3) indicate a significant as- sons’ social system theory. sociation between the boards’ GI index and the quality On the basis of Parsons’ sociological concept of AGIL, management system index. Compared with the re- we proposed that the combination of goal attainment stricted model containing the control variables (G) and social integration (I) – the GI factor – is a social precondition for any collective endeavor such as the im- plementation of a hospital-wide quality management Table 2 Goal–integration (GI) index (N = 109) system. In general, our empirical results support the hy- Characteristic of Hospital Management Board (HMB) N % pothesis that, in European hospitals, quality manage- Quality goal orientation of HMB (G index) ment strategies are fully implemented more often if the 0 – HMB low in quality goal orientation 64 58.7 hospitals are managed by hospital boards with a high GI 1 – HMB high in quality goal orientation 45 41.3 factor. After adjusting for various potential confounding Total 109 100 variables, hospitals with GI boards showed a higher Social capital of HMB (I index) score on the quality management system index than hospitals led by non-GI boards. Hypothetically, this 0 – HMB low in social capital 70 64.2 means that hospitals could realize an absolute improve- 1 – HMB high in social capital 39 35.8 ment of 3.3 points on the 27-point quality management Total 109 100 system index (11% improvement) if there is strong em- GI index phasis on quality performance and a sense of unity 0 – HMB low in social capital and quality goal orientation 44 40.4 within the HMBs. There was no significant increase 1 – HMB low in social capital OR quality goal orientation 46 42.2 compared with the reference group (low GI-board hos- pital) if the HMB either had quality orientation only (G) 2 – HMB high in social capital and quality goal orientation 19 17.4 or a sense of unity only (I). Therefore, having a board Total 109 100 with only one of these success factors does not seem Pfaff et al. BMC Health Services Research (2021) 21:70 Page 5 of 7 Table 3 Regression analysis with quality management system index as dependent variable (N = 109) Regression coefficient p-value CI (95%) Regression coefficient p-value CI (95%) Step 1: Restricted model Step 2: Full model (Constant) 20.8 0.000 16.3; 25.2 20.6 0.000 16.3; 25.0 Control variables Czech Republic (1) 1.7 0.38 -2.1; 5.6 0.7 0.70 -3.1; 4.5 France (1) -1.1 0.61 -5.5; 3.2 -2.0 0.36 -6.3; 2.3 Poland (1) 2.6 0.33 -2.6; 7.7 1.7 0.52 -3.5; 6.8 Portugal (1) -1.0 0.63 -5.2; 3.1 -1.9 0.37 -6.0; 2.2 Spain (1) -2.3 0.34 -7.1; 2.5 -3.3 0.16 -8.1; 1.4 Turkey (1) 4.2 0.08 -0.5; 8.9 2.3 0.35 -2.5; 7.1 Number of board members -0,03 0.84 -0.3; 0.3 -0.014 0.92 -0.3; 0.3 Number of beds between 200 and 500 (2) -1.0 0.54 -4.2; 2.2 -2.2 0.19 -5.4; 1.1 Number of beds between 501 and 1000 (2) -0.5 0.79 -3.9; 3.0 -1.5 0.40 -4.9; 2.0 Number of beds more than 1000 (2) -0.8 0.69 -4.7; 3.1 -1.5 0.44 -5.4; 2.4 Teaching Hospital -1.8 0.29 -5.3; 1.6 -1.8 0.29 -5.2; 1.5 Public Hospital -0.2 0.88 -3.0; 2.6 0.6 0.68 -2.2; 3.3 GI Index GI index: middle (3) 1.6 0.08 -0.2; 3.4 GI index: high (3) 3.3 0.007 0.9; 5.7 ΔR2 0.276 0.001 0.057 0.022 R2 0.276 0.001 0.333 0.000 (1) Dummy variable: reference category: Germany (2) Dummy variable: reference category: number of beds lower than 200 (3) Dummy variable: reference category: GI index = low sufficient. The possible explanations for this finding implementation power stems from the social contagion need to be explored. effect of committed groups. Social contagion describes Our results correspond with the upper echelons theory the diffusion of emotions, cognitions, attitudes, or be- [20]. This theory states that certain characteristics of top haviors in groups, networks, and organizations [24]. management teams influence the decision making of the Studies showed that leaders’ mood and passion [25] as top team itself as well as the decisions and behaviors of well as their commitment towards a certain goal (e.g., others outside the team, especially employees in the quality goal) are contagious to the followers [26, 27]. organization [20]. Furthermore, the implementation power is based on the Thus, we have two types of HMB impact: (a) an in- unity of the group. This unity bundles together the indi- ward impact and (b) an outward impact. One inward im- vidual energies of the board members forming a cohe- pact is that HMBs with a high degree of social sive top management team with high social energy that integration can make quick collective decisions owing to can be used to influence people (I: integration). Add- shared values and a common will to reach agreement itionally, the implementation power stems from the role [21]. The other inward impact is that socially integrated model function of a quality-oriented HMB. Quality- HMBs are able to integrate different cultures and stake- striving boards are an inspiring example for attaining holders within the HMB through group-bonding pro- quality goals throughout the hospital on all hierarchical cesses, leading to more culturally balanced decisions and levels (G: goal attainment). The Ohio model of leader- less social conflicts within HMBs. Shared leadership ship further supports this informal power perspective studies support this perspective [22, 23]. [28]. The Ohio model states that successful leadership An important outward impact of an integrated and combines two dimensions: (a) consideration (fostering the committed HMB is its power to influence the lower quality of the social relationships between leaders and hierarchical levels and its power to implement innova- followers) and (b) initiating structure (the degree to which tions on these levels. This implementation power de- a leader is oriented toward goal attainment) [29]. The first pends on the formal power of the HMB to make dimension relates to the I factor in the AGIL concept, and decisions and to lead the hospital. Moreover, this the second dimension relates to the G factor. Pfaff et al. BMC Health Services Research (2021) 21:70 Page 6 of 7 Implementation power is important for transferring items used might differ across national cultures and quality practices to all hospital levels because the imple- regulatory environments. mentation of quality-oriented structures and processes affects employees with vested interests and involves acti- Conclusions vating resources controlled by other managers [30]. Em- To the best of our knowledge, this is the first large-scale pirical results suggest that “in order to have effective study that explored two possible social determinants of strategy implementation processes (…) top management the impact of hospital boards on quality management: teams first need to minimize within-team fragmentation quality goal orientation (G factor) and social integration pressures to achieve integration” [31]. Therefore, (I factor). Due to the limitations of this study, we have strengthening the social capital of HMBs by improving to be careful with conclusions. However, we can state the team climate is important to foster the implementa- that this study could be regarded as a hypothesis gener- tion power of the board. ating study. Hence, the present study improves the con- solidated framework for implementation research by generating the hypothesis that shared commitment to- Strengths and limitations wards quality performance combined with social integra- The presented data are based on a cross-national, tion within HMBs could possibly increase the power of mixed-method study in seven European countries. We the HMBs to implement quality management systems mostly used validated scales. Moreover, we used differ- within the hospital. Regarding future research, longitu- ent sources of data for the GI index (CEO questionnaire) dinal studies are required to further examine the and for the quality management system index (quality relationship between HMB characteristics and imple- manager questionnaire) to diminish the risk of common mentation of quality management systems. Regarding method variance bias [32]. However, the present ana- quality management practices, results indicate tentatively lyses have certain limitations that are worth mentioning. that two practical measures could strengthen the imple- First, the study is based on a cross-sectional design and mentation of evidence-based quality in hospitals: (1) fos- does not allow us to draw causal conclusions. Future tering the social capital in HMBs using team studies should strive for longitudinal designs. Second, development and (2) reserving time to discuss quality on social capital, quality goal orientation, and quality man- the agenda of the board meetings. agement system are self-reported measures based on the questionnaires answered by the CEOs and quality man- Abbreviations CFIR: Consolidated Framework for Implementation Research; GI: Goal– agers. These variables are not based on objective mea- Integration; DUQUE: Deepening our Understanding of Quality improvement surements (e.g. observations), which would be an in Europe; CEOs: Chief Executive Officers; HMBs: Hospital Management additional goal for future studies. Therefore, they repre- Boards; AGIL: Adaptation, Goal attainment, Integration, Latency; SD: Standard Deviation; CI: Confidence Interval sent the perception of these professionals, which should be considered when interpreting the results. Third, the Acknowledgements two-item index “hospital management board quality goal We thank the experts, country coordinators and participating hospitals of the orientation” is not a validated measure yet. However, DUQuE project for their valuable advice on the measurement instruments, and the respondents for their effort and time to fill in the questionnaires. this index is based on quality management research and has been developed and used in a previous study as a re- Authors' contributions liable, fact-based measure [14]. By dichotomizing this HP contributed to funding acquisition, conceptualization, project administration, methodology, investigation, software, data curation, formal index, we additionally facilitated the robustness of the analysis, original draft preparation, reviewing, and editing. AH contributed to measure. Fourth, one could criticize the key informant project administration, investigation, data curation, and formal analysis. MB approach used; we chose this approach owing to its contributed to conceptualization, reviewing, and editing. KS contributed to formal analysis, reviewing, and editing. MS contributed to methodology and practicability. Nevertheless, the use of key informants is formal analysis. RS contributed to funding acquisition, project administration, common practice in business research and health ser- supervision, conceptualization, validation, reviewing, and editing. The vices research. Fifth, despite high response rates, our re- author(s) read and approved the final manuscript. sults are restricted to 109 hospitals because of missing Funding values in the quality management system index. Further This work was supported by the European Commission’s Seventh Framework analysis showed no significant differences between the Program FP7/2007–2013 [ec.europa.eu/index_en.htm] under the grant original sample and the analyzed sample of 109 hospi- agreement number 241822. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. tals. Sixth, we considered most potential confounders, Open Access funding enabled and organized by Projekt DEAL. but uncontrolled confounding cannot be completely eliminated. Seventh, despite our efforts to use a validated Availability of data and materials The datasets used and/or analyzed during the present study are available approach for backward-forward translation [13], we can- upon reasonable request. Please send your request to Rosa Sunol not fully rule out the possibility that the meaning of the (rsunol@fadq.org; ORCID: 0000-0003-1902-833X). Pfaff et al. BMC Health Services Research (2021) 21:70 Page 7 of 7 Ethics approval and consent to participate 17. Ansmann L, Hower KI, Wirtz MA, et al. Measuring social capital of healthcare This was a secondary data analysis of the DUQUE data. 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