Using patient flow simulation to improve access at a multidisciplinary sleep centre.

The lack of timely access to diagnosis and treatment for sleep disorders is well described, but little attention has been paid to understanding how multiple system constraints contribute to long waiting times. The objectives of this study were to identify system constraints leading to long waiting times at a multidisciplinary sleep centre, and to use patient flow simulation modelling to test solutions that could improve access. Discrete-event simulation models of patient flow were constructed using historical data from 150 patients referred to the sleep centre, and used to both examine reasons for access delays and to test alternative system configurations that were predicted by administrators to reduce waiting times. Four possible solutions were modelled and compared with baseline, including addition of capacity to different areas at the sleep centre and elimination of prioritization by urgency. Within the model, adding physician capacity improved time from patient referral to initial physician appointment, but worsened time from polysomnography requisition to test completion, and had no effect on time from patient referral to treatment initiation. Adding respiratory therapist did not improve model performance compared with baseline. Eliminating triage prioritization worsened time to physician assessment and treatment initiation for urgent patients without improving waiting times overall. This study demonstrates that discrete-event simulation can identify multiple constraints in access-limited healthcare systems and allow suggested solutions to be tested before implementation. The model of this sleep centre predicted that investments in capacity expansion proposed by administrators would not reduce the time to a clinically meaningful patient outcome.

The costs of developing, implementing, and operating a safety learning system in community practice.

BACKGROUND: The cost of implementing safety systems in primary care has not been examined. One type of safety system is a safety learning system (SLS). An SLS has 2 components: a reporting that monitors patient safety incidents and a learning component that facilitated the development and implementation of improvement strategies. It is important to understand the costs of an SLS to determine if the improvement program is financially sustainable. OBJECTIVE: To determine the costs of the development, implementation, and operation of the community-based SLS. METHODS: Nineteen participating family physician clinics in Calgary, Alberta, were included (15 urban and 4 rural) consisting of 47 physicians, 53 office staff, 18 nurses, and 6 clinic managers. Costs of the SLS were determined by the ingredient method using micro-costing. The costs were divided into 3 stages: development, implementation, and operational. Development costs were processes required to create and initiate the SLS. Implementation costs were accrued as a result of establishing, running, and refining the SLS. Finally, operational costs were those related to maintaining the SLS. Costs were further broken down into fixed, marginal, and in kind; this approach will allow policy and decision makers to apply the appropriate costs to their own settings. RESULTS: The total development, implementation, and operational costs for the SLS in Canadian dollars were $77,011, $19,941, and $166,727, respectively, with a total cost of $263,679 over approximately a 4-year period. During this time, 270 incident reports were submitted, and 54 improvement cycles were implemented. CONCLUSIONS: The results provide quantitative data, which could be useful to legislators, policy makers, and other private and public sector payers of patient safety programs in determining the overall sustainability of an SLS.