Brault’s Practice Solutions portal is a browser-accessible dashboard driven by SAP’s industry-leading Business Intelligence software. Using our integrated reporting models, clients can establish custom performance indicators for more than 120 clinical, operational, billing, and patient-satisfaction measures – with drill-down capability into individual physicians and/or patient metrics on most reports.
Custom Data Integrations
Brault’s technical team works with your hospital IT department to pull from the data sources necessary for integration into Brault’s Practice Solutions portal (with little impact on other hospital IT projects). This process is typically achievable within 60-90 days. And, depending on your hospital’s IT capabilities, data can either be extracted in batch intervals or in real-time.
Common integrations include: hospital EDIS, Press Ganey (and other satisfaction surveys), physician scheduling systems, and data from the Emergency Department Benchmarking Alliance (for comparison to national performance indicators from more than 1,200 participating emergency departments).
Practice Management Analytics
Brault’s Practice Solutions dashboard is unmatched in data depth, breadth and usefulness by any other commercially-available software. Our analytics provide your Practice with the information necessary to affect real process and provider performance improvement.
The benefit of custom analytics are many but one practical example is compensation modeling, which allows practice leaders to easily analyze cost trends, total group compensation, individual salaries and related information. Combining this level of operations and billing data into a single repository can even help you determine how practice styles across individual providers may impact your Practice’s overall billing performance.
These custom analytics can also help nurture the relationship between your Practice and your hospital C-suite by better illuminating the patient experience in the ER, observation and daily-care settings. This analytics-based modeling can help identify patterns in patient arrival, treatment and discharge times, which could reveal under-staffing issues that affect patient satisfaction, and by extension, Net Promoter Score (NPS), or NP ratios.
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