Cleven, Anne Katharina Winter, Robert Wortmann, Felix Mettler, Tobias
Year of Publication:
[Journal:] Business Research [ISSN:] 2198-2627 [Volume:] 7 [Issue:] 2 [Publisher:] Springer [Place:] Heidelberg [Year:] 2014 [Pages:] 191-216
In order to improve transparency and stabilise health care costs, several countries have decided to reform their healthcare system on the basis of diagnosis-related groups (DRG). DRGs are not only used for classifying medical treatments, but also for case-based reimbursement, hence induce active competition among hospitals, forcing them to become more efficient and effective. In consequence, hospitals are investing considerably in process orientation and management. However, to date there is neither a consensus on what capabilities hospitals need to acquire for becoming process-oriented, nor a general agreement on the sequence of development stages they have to traverse. To this end, this study proposes an empirically grounded conceptualisation of process management capabilities and presents a staged capability maturity model algorithmically derived on the basis of empirical data from 129 acute somatic hospitals in Switzerland. The five capability maturity levels start with 'encouragement of process orientation' (level 1), 'case-by-case handling' (level 2), and 'defined processes' (level 3). Ultimately, hospitals can reach the levels 'occasional corrective action' (level 4) and 'closed loop improvement' (level 5). The empirically derived model reveals why existing, generic capability maturity models for process management are not applicable in the hospitals context: their comparatively high complexity on the one hand and their strong focus on topics like an adequate IT integration and process automation on the other make them inadequate for solving the problems felt in the hospital sector, which are primarily of cultural and structural nature. We deem the proposed capability maturity model capable to overcome these shortcomings.
Health care management Process management Maturity model Design science research