IS01
Multiple Sclerosis (MS) Database Integrated with the Electronic Health Record (EHR) Promotes Dissemination of Clinical Picture across Teams and Saves Time

Thursday, May 31, 2018
Exhibit Hall A (Nashville Music City Center)
Kimberly L Cooley, RN, CCRC , Research, OSF Saint Francis Medical Center, Peoria, IL
PDF


Background:

MS data is often buried within EHRs resulting in lengthy reviews to retrieve patient histories. The OSF Healthcare Illinois Neurological Institute MS Clinic created an EHR-integrated MS database to overcome this challenge.

Objectives:

The primary objective was faster Disease Modifying Therapy (DMT) access by expediting the prior authorization process. Secondary objectives were decrease relapse rates and MS hospitalizations, staff satisfaction, increase investigator initiated studies and provider/staff time saving.

Methods:

A retrospective review was performed 1 year prior- and post-database implementation. Times to data extraction and medication approval were examined by multivariable generalized linear regression models controlling for age, gender, race and Charlson comorbidity index. A McNemar’s test compared the relapse rate and the hospitalization rate pre- and post-implementation. A paired t-test compared staff time for retrieving information from the EHR to that from the database. A sub-analysis in a new provider compared provider time versus times to data extraction and medication approval pre- and post-implementation.

Results:

1224 total patients were included. The reduction of time from prescription to data extraction was not significant for the initial and sub-analysis (p>0.05 for all). Time from data extraction to medication approval was similar between pre- and post-implementation (10.9 days vs 9.5 days, p=0.369) in the initial analysis, but had a significant reduction in the sub-analysis (7.8 days vs post 0.8 days, p=0.032) after 5 patients were excluded with newly FDA-approved drugs or no documentation. The relapse rate was 12.3% and 11.0% in 1 year pre- and post-implementation, respectively (p=0.302). Provider and staff time in the EHR was significantly longer than that from the database pre and post database implementation (36.3 vs 15.7 min, and 3.3 vs 1.1 min, respectively; p<0.001 for all). Furthermore, the hospitalization rate was significantly reduced after database implementation (1.4% vs. 0.4%, p=0.012).

Conclusions:

Many factors beyond the clinic’s control influence DMT approval process (ex. insurance protocols, patient compliance, prior wash-out, pre-testing, and new FDA approved DMTs) making it difficult to study the database influence on this outcome. However, results did confirm significant provider/staff time-saving and hospitalization rate reduction with the new platform. Future studies could study qualitative focus group data to support the database’s value.