Improving transitions of care at hospital discharge--implications for pediatric hospitalists and primary care providers.

Delays, omissions, and inaccuracy of discharge information are common at hospital discharge and put patients at risk for adverse outcomes. We assembled an interdisciplinary team of stakeholders to evaluate our current discharge process between hospitalists and primary care providers (PCPs). We used a fishbone diagram to identify potential causes of suboptimal discharge communication to PCPs. Opportunities for improvement (leverage points) to achieve optimal transfer of discharge information were identified using tally sheets and Pareto charts. Quality improvement strategies consisted of training and implementation of a new discharge process including: (1) enhanced PCP identification at discharge, (2) use of an electronic discharge order and instruction system, and (3) autofaxing discharge information to PCPs. The new discharge process's impact was evaluated on 2,530 hospitalist patient discharges over a 34-week period by measuring: (1) successful transfer of discharge information (proportion of discharge information sheets successfully faxed to PCPs), (2) timeliness (proportion of sheets faxed within 2 days of discharge), and (3) content (presence of key clinical elements in discharge sheets). Postintervention, success, and timeliness of discharge information transfer between pediatric hospitalists and PCPs significantly improved while content remained high.

Enhancing an existing clinical information system to improve study recruitment and census gathering efficiency.

Information technology can improve healthcare efficiency. We developed and implemented a simple and inexpensive tool, the "Automated Case Finding and Alerting System" (ACAS), using data from an existing clinical information system to facilitate identification of potentially eligible patients for clinical trials and patient encounters for billing purposes. We validated the ACAS by calculating the level of agreement in patient identification with data generated from manual identification methods. There was substantial agreement between the two methods both for clinical trial (kappa:0.84) and billing (kappa:0.97). Automated identification occurred instantaneously vs. about 2 hours/day for clinical trial and 1 hour 10 minutes/day for billing, and was inexpensive ($98.95, one time fee) compared to manual identification ($1,200/month for clinical trial and $670/month for billing). Automated identification was more efficient and cost-effective than manual identification methods. Repurposing clinical information beyond their traditional use has the potential to improve efficiency and decrease healthcare cost.