Using balanced metrics and mixed methods to better understand QI interventions.

To cite: Kaboli PJ, Mosher HJ. BMJ Qual Saf Published Online First: [please include Day Month Year] doi:10.1136/bmjqs-2014002829 Improving quality while maintaining or reducing costs requires balancing competing demands to bring value to healthcare. High-value reporting of quality improvement (QI) initiatives similarly requires balancing descriptions of improvements achieved with assessments of potential costs and unintended consequences. Using balanced QI metrics allows simultaneous measurement of intended improvements (eg, reduced length of stay (LOS)) and of processes or outcomes that might worsen as a result of a given intervention (eg, mortality, hospital readmission). In their initiative to improve the efficiency of inpatient care without compromising safety at a large teaching hospital in Edmonton, Alberta in Canada, McAlister et al report balanced measures, use a methodologically evaluative QI design, and describe the local contextual factors that influenced their success, thus creating generalisable knowledge. Their intervention bundles a number of plausible improvements on inpatient units: daily interdisciplinary care rounds, geographical cohorting of patients—that is, placing general medicine patients and their doctors at one place in the hospital, strategies to optimise care transitions (eg, medication reconciliation) and use of best practice through care maps, order sets and decision support tools. Many would regard these changes as components of high-quality inpatient care and appropriate to all patients. In reality, limited evidence supports these interventions individually and the magnitude of their benefits (at least on their own) is probably not large. Hence, the reason for a multifaceted or bundled intervention—we do not know which component will generate important improvements, and, it is possible all are needed. Some components may even have synergistic effects. Such bundled interventions will be increasingly important to deal with highly complex healthcare problems, which typically have no single ‘magic bullet’ solution. On the one hand, a bundled approach aims at the QI target quickly (as opposed to testing each component in turn or trying different combinations of possibly synergistic components). On the other hand, the price often paid for the bundled approach (the proverbial kitchen sink approach—‘we threw everything at the problem except the kitchen sink’) is that the active ingredients remain unclear. Recognising this problem, McAlister et al incorporated a mixed-methods approach in their attempt to identify the most effective elements. Their focus groups attributed the benefits achieved largely to two of the changes. The first was geographical cohorting of patients: the intervention resulted in 97% of admissions going to general internal medicine wards from a baseline rate of 53%. The second was daily interdisciplinary discharge rounds occurring 5 days a week from a baseline rate of once weekly. Thus, the report by McAlister et al is noteworthy for the robust controlled evaluation that showed a reduced LOS attributable to their inpatient care transformation initiative, and also for isolating the likely ‘active ingredients’ in their intervention. Geographical cohorting of patients deserves further discussion. This innovation appeals to healthcare teams for many reasons, including improved communication and relationship building when working with a smaller group of individuals, and reducing the inefficiencies of walking to multiple physically separated units. Although there is little empirical evidence that geographical cohorting improves efficiency, the focus groups thought it did. However, this apparently simple change is far from straightforward to introduce owing to difficulty in managing bed flow. Administrators recognise EDITORIAL