Data Disconnects
Is This The Same Problem?
Looking for data shouldn't require guesswork. Central repositories are beneficial when duplicate information can be found in multiple systems. Technology should improve process. If less efficiency is result of change, start with Kaizen to help identify wasted effort before taking additional steps.
Example - Analysts must check Systems A, B, & C when searching for "Tulips". Each unique data store contains similar detail but most recent entry should be considered official. Human error can lead to invalid result if manual intervention is required for robust system interpretations.
Who has access?
Generic system user accounts with access to all aren't providing optimal security tracking details. Although convenient on forever changing teams, these Goliath profiles are creating unwelcome opportunity. Do you know which accounts are used for installs and updates to your most valuable systems?
Example - The same account was used for supporting requested customizations. Although risk was known, team members decided one with access to all was more secure than 4 unique profiles. This generic account was used to log into our system over the weekend and all team members confirmed it wasn't them. What other risks might be connected to this account?
Better Decisions
Isolated change can lead to downstream issues when communication is restricted.
Example - Support team decided to reduce chance of breach by changing system user account password. Biometrics seemed more secure. After successfully testing, production system update was carefully applied. Reports of lost access to data immediately followed.
Our Discoveries
Days of believing one talks too much have long passed on teams supporting effort with major impacts. Keep communication and remove barriers that prevent progression. Use alternate methods to ensure all members are contributing valuable information based on their unique skillsets.
New Standards
Use Explainers. The best way to ensure your goals are understood is to have individuals personalize their roles in supporting them. Make others interpretation of shared effort standard. Responsibility overlaps might encourage unforeseen team building along the way. Identify work dependencies early and allow teams to bring concerns forward.
System Failure
How It Starts
Gotchas are expensive and add unnecessary burden of proof challenges to everyone operating under process first, technology second, people last organizational plans. Identifying which third is priority can likely be determined by impact order of good result. People, process, people outcome might present opportunity to dig deeper; what people, how were they affected, which process, and why isn’t technology part of solution that requires automated leadership approval? Sporadic system use might occasionally work but chance of mistake from human error ensures technology will eventually fail.
Disconnects often take years to find with teams of dedicated supporters and multiple sources of information. When finally uncovered, facts might be used to address isolated concerns without ever initiating plans that target loopholes. We realize data owners lack permanent staffing to identify overlaps and support massive standardization efforts. HL7 format is example of how healthcare transformed information sharing. PlanAids hopes to bring concerns forward with skilled teams positioned to move toward long-term solution for other unregulated entities. We’d love to hear from you! Be a part of our discussion with the Validity of Data survey .
