You will find it challenging to get work done with a desk full of scattered papers, sticky notes on your monitors and missed call messages everywhere. In fact, this type of chaos can be demotivating. The same premise holds true when it comes to your health data management system. If you have no structured system, how can you provide patient-centered care and reduce costs simultaneously? You can’t. The following are some tips to help to improve clinical data management within your system.
Tip #1: Create an effective team
Many analysts are dispersed throughout the organization working on collecting and analyzing data for different processes. If you create a team of analysts that work together to complete these tasks, you can significantly improve clinical data management within your organization. Analysts’ teams will help your organization:
- Achieve higher quality outcomes
- Resolve problems quicker
- Increase productivity
- Create an environment for skills development
By creating a team of analysts, your organization can easily retrieve and assess pertinent data.
Tip #2: Examine Risks within Your Organization
Risks are the unknowns that have the potential to derail your efforts to manage your health data. You can delegate managing risks to specific analysts to ensure that you have a plan for avoiding or reducing the impact of each risk. You should consider some of the following risks to get your team started:
- Challenges with core competencies
- Eliminate data silos
- Examine reporting procedures
- Assess current data governance to ensure strategic alignment
Although the list isn’t exclusive, it is a great starting point for your analysts to safeguard your data management system. Where your team observes gaps, have them develop a strategy to remedy the problems and submit proposals to C-suite executives, including developing a business case.
Tip #3: Every Clinical Data Management System Needs an Enterprise Data Warehouse
Medical facilities collect, store and transmit a lot of data throughout the day. Without a central repository, analysts have a hard time performing their jobs, which reduces productivity. An enterprise data warehouse (EDW) is an internal system that helps your organization report and analyze information. Your EDW is the foundation of your data management system and your health care analytics. With a central repository, your analysts can base their decisions on uniform data, which improves data quality overall.
Tip #4: Establish a System for Data Governance
As the amount of data you are required to report increases year after year, it’s important that you establish a system for managing your data. Your data governance dictates the integrity of your data, what it is used for, when it is available and establishes security protocols for your data. An effective data governance is critical to ensure that your organization is taking every measure to improve the quality of care your patients need. The key to finding an effective data governance strategy is by striking the right balance. Consider the following types of data governance:
Authoritarian: The data governance has a centralized EDW, and it uses a monolithic, early-bind data model. The EDW is nearly locked down using a bureaucratic process that can easily become time-consuming when approvals are needed.
Democratic: Within a democratic data governance system, your EDW is centralized, and the architecture is late-binding. The democratic data governance is a balanced alternative to both the authoritarian and tribal approaches.
Tribal: A tribal data governance is the complete opposite of an authoritarian system. With a tribal system, there is no structure due to the lack of an EDW. Analytics are not in one place, making your analysts jobs harder and less productive.
One strategy your medical practice must consider in your efforts to improve outcomes in clinical data management. Without effectively utilizing your resources, including your team of analysts, you could be undermining your efforts to cut costs and enhance patient care.