In this controlled, randomized intervention study, we analysed whether physicians working conditions in surgical and medical departments of a hospital can be improved through a participatory work re-design intervention. We additionally explored related improvements of physician performance, as reflected by patient judgments regarding the quality of patient care. The study shows that for several prevalent problems in the physician’s hospital working environment, solutions can be found and successfully implemented. Overall, the study results indicate positive effects of the intervention on conflicts in role and tasks demands, colleague support, and quality of cooperation with patients relatives. At the end of the intervention, patients of the ID rated the organization of patient care more favourably than patients in the CD.
An intervention to change hospital physician working conditions is subject to complex influences, which are only partly under the control of the researchers . Additional information is needed to shed more light on process-related factors [16, 17, 20]. Therefore, supplementary interviews with involved physicians served to identify important procedural aspects to enhance opportunities for transferring results into practice and guide further research [16, 20, 35]. The interviews revealed that the hospital physicians rated the intervention process positively.
Although differences between ID and CD regarding study outcomes mostly attained only marginal significance (p < 0.1) and effect sizes were rather small, obtained results are plausible with regard to the implemented changes in work design and consistent with one another. The fact that improvements were observed from two independent perspectives (physicians and patients) increases the validity of our results and, thus, supports the usefulness of similar interventions in organizational development projects. In line with previous research findings, it appears overly optimistic to expect consistent and enduring positive effects of a single organizational intervention, which was limited in scope [16, 20]. However, even small changes of specific stressful working conditions (such as reduced interruptions and conflicting demands, improved coordination, and support among teams) may be beneficial in the long run.
Study’s strengths and limitations
To our best knowledge, this is the first controlled intervention study with the aim of improving working conditions and quality of care of hospital physicians by applying a participatory change process. Conducting such a study proves to be highly challenging, given the complexities and dynamics of hospital settings. It is therefore no surprise that only few studies have addressed this topic so far . By applying cluster randomization, measuring the core variables with standardized, validated scales, and testing intervention effects with established statistical methods, we were able to demonstrate the feasibility, scientific relevance, and potential practical usefulness of this approach [29, 36]. A second strength concerns the inclusion of a large number of patient evaluations of physician performance. This is rarely done, despite the obvious importance of the consumer perspective in health care. The combination of data from two stakeholder groups strengthens the validity and robustness of our findings. Third, our additional qualitative information enriches outcome data with process-related details and thus contributes to an in-depth interpretation of observed changes in attitudes and behaviours [17, 37].
There are several limitations to this study. Firstly, the restriction to one single hospital setting limits the generalization of the results as well as the applicability of the implemented organizational changes and effects beyond this hospital. There is, however, reason to assume that the identified core dynamics are similar in other hospitals of this type, given the commonalities of tasks and similar overarching organizational constraints. Furthermore, an additional investigation of a larger sample of German hospital physicians revealed a high degree of concordance with our physician-based findings . Secondly, the number of physicians included was relatively small, thus compromising the statistical power. It was not possible to reduce the regular turnover of physicians during the intervention, given the constraints of their training careers and rotating schedules. In ID, 2 to 3 physicians regularly took part in actual intervention meetings, and subsequently discussed or informed their colleagues about problems, solutions and implementation status (usually during routine departmental meetings). Thus, we cannot estimate to what extent the individual physicians were exposed to the intervention (i.e., dose delivered). This is particularly relevant since physicians who may have felt little involvement in the intervention initiatives may have reported unchanged working conditions .
Although physicians were not explicitly informed about study hypotheses in detail, the broader objective to improve working conditions was communicated openly. Since it is not feasible to blind employees in a participatory intervention, bias may occur if participants respond differently with regard to study objectives. For example, positive developments may have been more salient in the ID than in the CD. Conversely, announcing the intention to improve working conditions may also have led to expectancy effects, resulting in a more critical response tendency in the ID. Further, in the CD, both lower response tendencies due to the relative deprivation compared to the ID as well as more optimistic ratings based on psychological compensation processes are theoretically plausible. Overall, while we cannot rule out effects of the unavoidable lack of blinding, there is no clear indication that these would necessarily inflate the observed differences in change between study groups.
Furthermore, the observed positive intervention pattern in patients’ reports supports our findings, because patients were completely blind to the design of the intervention and as such were not able to respond according to the study objectives.
In our statistical analysis of intervention effects, we treated time and group affiliation as independent factors, since the number of physicians that participated in both waves was low (N = 9, respectively). To account for potential bias due to repeated measurement, future intervention studies should seek to recruit larger samples to allow robust statistical analyses, e.g. mixed-model design ANOVA. To address potential bias due to the repeated participation of physicians at baseline and follow-up, we conducted an in-depth analysis for this particular subgroup (cf. Additional file 1: Table S1). Furthermore, while differing medical specialties make ‘contamination’ (i.e., personnel changes) between the ID and CD unlikely, we cannot definitely exclude such an effect.
A third limitation concerns the scope of the intervention applied. We restricted the measures to distinct organizational changes at the level of single departments. This restriction precludes changes depending on higher-level decision making. In highly complex, multifaceted organizations such as hospitals, some problems, e.g. concerning personnel resources allocation or other broader organizational practices, need to be addressed at higher organizational levels. Although the inclusion of the steering committee aimed to address this issue, the effectiveness of some changes implemented at the departmental level was weakened due to this limitation (e.g., lack of momentum). Likewise, while focusing on structural measures, our approach did not target individual-level behavioural changes. It is possible that by combining organization-based interventions with person-based interventions, stronger effects may have been observed [17, 18, 39]. Yet, it is also possible that our intervention strategy may produce more robust effects in the longer run, and that the observation period of potential changes was too short [16, 40].
Two less tangible limitations relate to unmeasured effects evolving from cluster-randomization and to potential bias in the patient survey. Randomizing departments instead of individuals introduces the risk of neglecting variations in organizational culture and leadership style which may influence the implementation. Concerning the patient samples, we observed similar participation rates at study entry, but a considerably lower participation rate in the CD at follow-up. Due to confidentiality regulations we were not able to check for detailed patient characteristics that may shed light on a potential response bias . Overall, no clear biasing tendency can be derived from the reduced survey participation of patients in the CD at follow-up, which could be based on selection effects related to either low or high satisfaction with the delivered quality of care. Additionally, while we cannot exclude that few patients were included in both measurement waves; this poses a limited risk for bias due to the rather large sample sizes.