Adrian Zai

J Am Med Inform Assoc. 2009;16:516-523. DOI 10.1197/jamia.M2977.

Objective: The authors previously implemented an electronic heart failure registry at a large academic hospital to identify heart failure patients and to connect these patients with appropriate discharge services. Despite significant improvements in patient identification and connection rates, time to connection remained high, with an average delay of 3.2 days from the time patients were admitted to the time connections were made. Our objective for this current study was to determine the most effective solution to minimize time to connection.

Design: We used a queuing theory model to simulate 3 different potential solutions to decrease the delay from patient identification to connection with discharge services.

Measurements: The measures included average rate at which patients were being connected to the post discharge heart failure services program, average number of patients in line, and average patient waiting time.

Results: Using queuing theory model simulations, we were able to estimate for our current system the minimum rate at which patients need to be connected (262 patients/mo), the ideal patient arrival rate (174 patients/mo) and the maximal patient arrival rate that could be achieved by adding 1 extra nurse (348 patients/mo).

Conclusions: Our modeling approach was instrumental in helping us characterize key process parameters and estimate the impact of adding staff on the time between identifying patients with heart failure and connecting them with appropriate discharge services.

Our work on heart failure management has been featured on the Mass General Hospital’s Heart Center website:

http://www.massgeneral.org/heartcenter/index.aspx?page=news_media&subpage=news_heartfailure_tracking

Here’s a poster illustrating our work with heart failure presented at the AMIA Spring Congress 08

J Am Med Inform Assoc. 2008;15:524-533. DOI 10.1197/jamia.M2598.

Shortcomings surrounding the care of patients with diabetes have been attributed largely to a fragmented, disorganized, and duplicative health care system that focuses more on acute conditions and complications than on managing chronic disease. To address these shortcomings, we developed a diabetes registry population management application to change the way our staff manages patients with diabetes. Use of this new application has helped us coordinate the responsibilities for intervening and monitoring patients in the registry among different users. Our experiences using this combined workflow-informatics intervention system suggest that integrating a chronic disease registry into clinical workflow for the treatment of chronic conditions creates a useful and efficient tool for managing disease.

This paper was published on Oct 2007 in Review of Endocrinology. Click here to retrieve article (PDF format).