Third Party Inspection Services | Inspection Company in China | AQI Service

1. How Effective Is Your Support Services Data? How effective is your Support Services Performance Data? As health care administrators, the old adage, "you can't manage what you don't measure" applies to every part of our management portfolios. Given the breadth of health care issues, there is constant influx of data on quality, finance, efficiency, regulatory compliance and a host of other indicators. So much so that many leaders suffer from data overload and are often unable to use the data to help them make more informed decisions. Worse, decisions are being made from data that is misleading or inaccurate, or different data sources are leading members of the same management team to come to different conclusions. In recent years, management "dashboards" and "scorecards" have come into favor. A dashboard can provide a quick snapshot of an organization's performance, allowing management to understand multiple performance indicators in a simple, graphically visual format. Yet, the effectiveness of these tools for decision support has had very mixed results. Too often, glossy reports with graphics and visualizations lull the healthcare management team into the "Dashboredom Effect". [1] Review of data becomes routine and misses the key point of leading management to prioritize their actions.

2. There is a need for organizations to take a methodical approach to understand what they need from their data and how to produce data reports that optimally aid the management team in achieving their goals. In their article "Corporate performance Management: Beyond Dashboards and Scorecards" [2] Stijn Viaene and Jürgen Willems argue that a primary objective of a performance management tool is to align the priorities of all levels of management. The organization's goals should be translated into meaningful key performance indicators. Through careful planning and prioritization, dashboards can help ensure that the management team is moving together toward the same goal. Let's use an example of a database for a sourcing support service division at a large academic medical center that spans several campuses and several different departments. In this example, the objective is to provide strategic information for the department's senior management, as well as tactical data for over 100 managers and supervisors. The overarching goal to provide an exceptional patient experience, issupported by monthly data from multiple sources including patient satisfaction, turnaround time data and quality survey data. Using an Access database, we developed a process to receive the source data into our data warehouse and turn out reports for multiple users. The result was that by the 15th of each month, senior management, as well as supervisors on each patient unit had performance data from the previous month, as well as data trended over time. Through the use of a data structure that allows multiple views of the data, it is possible to ensure data integrity while producing different reports that are valuable for all levels of management. The data warehouse acts as a central repository of raw data. It receives data from multiple sources that are both internal and external to the organization. In the above example, the data warehouse received data from Press Ganey (Patient Satisfaction), Sentact (a work order system measuring response time), Teletracking (a patient escort system measuring turnaround time) as well as internal quality data. To ensure data integrity, each data source has a set of rules to guarantee the quality of the data. An example would be that patient satisfaction data must come directly from the vendor database after the monthly close date. The data warehouse is programmed not to accept any patient satisfaction data that does not meet these criteria. This ensures that all patient satisfaction scores will be the same on any report generated throughout the organization.