Self-Service Analytics

The Self-Service Analytics Suite enables users to conduct their own analytics and reporting tasks without the help of advanced analysts or data scientists. Business and clinical leader users can use the tools in the suite to create accurate, timely analytics and reporting. The suite relies on data from the Health Catalyst data and analytics platform, and it includes IDEA, Health Catalyst Pop Analyzer™, Health Catalyst Pop Insights™, and Healthcare.AI™.

With Self-Service Analytics, build on your data foundation (DOS and source marts) to quickly integrate new data, build populations, create and disseminate reports, and forecast future states to guide improvement efforts.

The problem

Analytics teams are often overwhelmed with countless analytics requests, many of which are simple and repetitive. Constrained by a need for SQL expertise to gain data insights, organizations struggle to avoid an analytics bottleneck.

Because of this, business and clinical leaders are not getting the data insights they need to drive more informed decision-making in a timely manner. These team members—from executives to frontline workers—need to “explore” their data without involving the organization’s analyst teams.

Chief Information or Chief Analytics Officers share in the frustrations of analysts and leaders. However, they don’t have the tools to reduce workload for analysts and provide timely data insights for business and clinical leaders.

Our approach

Self-Service Analytics for Healthcare Organizations enables standardization and reuse of analytics assets while unleashing the data beyond SQL experts to provide business and clinical users with a self-service option, easing the burden on analyst teams and enabling analysts to operate at the top of their license. This increased dissemination of data results in positive business outcomes, such as increased efficiency, better customer satisfaction, and higher revenue and profits.

Benefits and features

• Provide easy, fast, self-service analytics and reporting for non-technical users. The suite drives dramatically faster answers in seconds or minutes instead of weeks or with right-sized capabilities for end-users (not too complicated, not too simple).
• Reduce the burden on overworked data analysts. By putting analytics in the hands of stakeholders, you reduce high-volume analytic queues. This frees up analyst time to do more advanced analytics—and leads to top-of-license job satisfaction.
• Reduce licensing costs. The suite provides economical, broad-based reporting capabilities without analytics and business intelligence licensing fees.
• Support broad, self-service tool distribution across your organization. Stakeholders throughout the organization have access to data, analytics insights, and collaborative best practices. The right audience sees appropriate data with flexible security options and guidelines, tailored to the needs of diverse groups.
• Quickly integrate augmented intelligence (AI) into existing analytics and business intelligence tools and applications with one click. Once installed, it can be up and running and creating insights in minutes. Healthcare.AI provides dynamic, user-driven dashboard reporting instead of static reports.
• Unlock healthcare-optimized data from DOS with a fully integrated reporting tool. Users can unlock, use, and reuse all DOS data currently in your analytics and BI tools and applications. Data includes common, sharable measures and populations.

Use cases

• A COVID Taskforce at a healthcare system needed to quickly understand vaccine administration and inventory. Using Self-Service Analytics, the team rapidly analyzed vaccine administration data and inventory status reconciliation data in a matter of minutes. From this data, they could accurately model vaccination schedules, forecast vaccine supply needs, identify and resolve quality/safety concerns, and generate required regulatory reports. The result: 30 percent increase in scheduled vaccinations per week, while ensuring adequate inventory for second doses.
• A team of analysts were buried under requests for analytics—and couldn’t meet service-level agreement timelines. Using the tools in Self-Service Analytics, the team reduced the time to complete many projects from 20+ hours to less than 2 hours. Analysts now spend most of their time analyzing—rather than preparing—data. They also reduced service requests by 27 percent.
• Clinical leadership at a clinically integrated network needed grant funds to implement and integrate custom algorithms into an analytics application. To support this project, it was critical to identify pre-diabetes, diabetes, and hypertension patients hidden in the EHR. Using DOS data and Pop Analyzer, the team accurately and quickly identified patients, met DOH requirements, and secured $40K in grant funds for further improvement work for targeted populations.