How to navigate challenges post go-live
For healthcare data analytics, the transition from planning to implementation marks a critical phase for leaders and organizations. However, many encounter obstacles that hinder their intended outcomes post go-live. Understanding these challenges and adopting a structured, strategic approach can significantly enhance success.
In the post go-live phase, challenges arise as leaders grapple with defining clear objectives, managing evolving data intricacies, establishing effective user support mechanisms, and comprehensively understanding the platform’s functionalities. These hurdles impede the optimal utilization of data analytics tools in healthcare settings.
4 tips for success post go-live for data analytics software implementation
To navigate the complexities post go-live, there are four pivotal pillars instrumental in steering healthcare leaders towards success in leveraging data analytics platforms effectively. These pillars serve as guiding principles to maximize the value derived from these sophisticated tools.
1. Identify and execute on a defined set of initial goals
Success post go-live hinges on meticulously defining and executing a precise set of goals. Balancing overarching vision with achievable incremental objectives is critical.
Organizations must identify primary needs, set incremental goals, and aim for quick wins to foster trust and adoption across the organization. Specificity is key — from identifying low-performing metrics to devising targeted strategies to address them.
Here are our recommendations for how to identify and execute on a defined set of initial goals:
- Avoid tackling too many goals
- Identify a key set of actionable objectives
- Create visibility into platform adoption
- Align internal stakeholders
2. Develop an ongoing data management plan
Beyond integration, data management is an ongoing process that demands continuous attention. Change is a constant, whether it’s alterations in data formats or EHR system migrations. Establishing an expert resource responsible for managing data feeds, understanding their schedules, and aligning internal teams is essential. Tools facilitating comprehensive data monitoring and support, like Arcadia’s upcoming feature for detailed data source analysis, can significantly bolster this endeavor.
See our recommendations below on best practices for developing an ongoing data management plan:
- Identify an internal expert on your data feeds
- Develop a schedule
- Sign up for Arcadia data lag emails
- Keep track of upcoming specification changes
- Create a process for provider hierarchy updates
- Monitor file naming conventions
3. Establish a robust user management and support model
An effective user management and support framework is pivotal.
Designating a central intermediary to manage user issues, liaise with support teams, and gauge user knowledge gaps can streamline issue resolution. This centralized approach not only helps in prioritizing issues but also aids in keeping internal stakeholders aligned with organizational priorities. Proactively addressing user onboarding, access control, and mitigating risks related to sensitive data access are crucial facets of this strategy.
Here are some recommendations to help you establish a robust user management and support model:
- Set up on Arcadia support portal
- Implement a centralized support model
- Intro to Arcadia’s Customer Success team
- Align internal stakeholders on priorities
- Create process for managing user accounts
- Leverage Arc Questions & LMS
- Develop an onboarding plan
4. Immerse yourself in the tool
Mastering a data analytics platform involves a deeper understanding of its functionalities. While initial training provides a foundational understanding, continuous learning through hands-on exploration, following user guides, documenting use cases, and comprehending data intricacies within the tool can be transformational. Leveraging resources like Arcadia’s Learning Management System (LMS) with pre-recorded videos and community-driven query resolution platforms can further augment expertise.
Here are our recommendations for how to properly immerse yourself in the tool:
- Block off time to use Arcadia tools. Trace back through the quick guides.
- Document workflows step by step
- Identify attribution model(s) for each workflow
- Learn how data quality and type interacts with functionality
- Rewatch training videos. Use Arc Questions.
Your roadmap to success and continuous growth
The insights shared emphasize a balanced approach in setting goals post go-live. It’s essential to avoid extremes and instead focus on incremental and achievable objectives that align with the organization’s unique needs. These goals should include quick wins to build trust and foster widespread adoption.
In navigating the complexities post go-live, healthcare leaders must adopt a holistic approach by:
- Defining clear goals
- Instituting robust data management practices
- Establishing effective user support frameworks
- Immersing themselves in the nuances of the tool
By focusing on these four pillars, organizations can unlock the true potential of healthcare data analytics platforms.
Arcadia remains committed to empowering healthcare leaders with comprehensive support and resources for harnessing the full capabilities of our platform. To delve deeper into optimizing your data analytics journey, explore our additional resources and engage with our experts to maximize your success.