From the 2018 HVPAA National Conference
Ken Lee (Johns Hopkins University), Pam Johnson (Johns Hopkins University), Lisa Ishii (Johns Hopkins School of Medicine), Steven Frank (Johns Hopkins University), Michael Borowitz (Johns Hopkins University)
Background
Data is one of the key ingredients in driving higher value patient care. However, data alone cannot solve any problems. Being able to efficiently generate insight and rapidly cycle through the feedback loop between the information producer and information consumer is critical.
Objectives
To assess and optimize the intermediaries between the data source such as an Electronic Medical Record system and the data consumers such as providers working on high value care initiatives. The goal is to minimize delay and maximize efficiency in delivering data driven solutions to the consumers.
Methods
Time to complete requested analytics tasks were compared between two time periods. During the first time period of 2013-2015, the data infrastructure to support high value initiatives was non-existent. During the second time period of 2016-2018, the infrastructure and processes were in place to support the initiatives. In each period, each intermediary between the original system of record (e.g. Epic) and the final consumer of information was identified and the time spent on each step was identified. Within each time period, five unique analytic tasks were studied.
Results
Disintermediation is effective in driving higher value patient care in multiple ways. It connects the consumers of information directly to the data source while cutting down steps and resources required to complete tasks. Comparing the two time periods, a typical analytic task took 50-100 times more time in the pre-infrastructure period compared to the post-infrastructure period.
Conclusion
Providing quick and accurate information to the information consumer such as providers working on high value care initiatives is a key factor in achieving success. This requirement calls for optimizing intermediaries and their functions between the data source and the final consumer. Our newly designed infrastructure showed that it only requires 1-2% of the previous time required to complete the selected tasks. The more efficient process enabled rapid and multiple iterations that led to higher value patient care.
Implications for the Patient
Cutting down time to deliver information to the providers will enable more relevant and timely patient care.
