Beyond the rollout: Digitization technology is only the first step for file analysis

Healthcare files are not a rotisserie chicken.

Now, this may not surprise you, but it seems some organizations want to treat them like one, taking Ronco’s famous “set it and forget it” approach. Too often, healthcare organizations embrace digitization and then don’t know where to go from there, either from quick initial training in the technology or of a strong plan once the technology is implemented.

The electronic medical record (EMR) provides healthcare organizations with the ability to search and retrieve critical patient records where and when they are needed. But many times the issue of “set it and forget it” lies with what has been done with the many other files and administrative records needed to run a health system, such as HR/physician credentialing files, AP/AR documents, legal files, and so on. In healthcare, nurses, doctors and administrative staff are often in a rush, so they need files to be quickly, easily and reliably accessible. If a digitized system is not all of these things, then users will often resort to their preferred ways that “just work” in the short term, even if they’re costly and inefficient. To have a truly effective file management approach, an organization needs not just the technology, but a file management system, which includes people, processes and technology. This can be segmented into three phases: Define, Design, Disinfect.

Define
The define phase is a three-step process. Organizations must first define “the haystack” – their current state, the pool of files through which users will look for their “needle” – which takes into account factors such as volumes, silos, duplication, file types, locations, interoperability and even how people access these files. To adapt to that final factor, a physical walkthrough noting how users handle files is an integral part of any baseline assessment. From there, technologies can be used to automatically discover volumes based on these other categories.

Once the current state is identified, organizations need to define their preferred end state. Beyond the factors uncovered in the baseline assessment that shape what is possible, organizational goals shape this definition. Are there budgetary constraints that would make minimizing costs a priority? Do you handle particularly high volumes of sensitive data, so controlling risk and aiding compliance are crucial? Other common examples include increasing efficiency, increasing visibility and defensibly and efficiently destroying unneeded data.

The final step of the “define” phase is to define policies and technologies that further end state goals. Once an organization has its Point A and Point B, it’s time to sketch the map between them. Common choices for file analysis include technologies, training and workflows.

Design
The “design” stage is where the route between Point A’s current state and Point B’s end state become detailed and the journey starts to move. A strategic roadmap includes well thought-out decisions as well as considerations for adjustments. Frequently, a strategic roadmap for file analysis improvement includes technical training to help ensure end-users follow best practices, workflows to aid efficiency and break down silos, and technologies to facilitate the end state.

Another common aspect of the roadmap is change management, or strategic transformation. It can be easy for decision makers to think “this is what’s best for us and the people we serve, and I’m implementing it, so it will get done.” As anyone who has hastily written crucial information because technology “doesn’t work” for them can attest, this doesn’t always work. Change management gives employees the technical know-how to benefit from new processes and technologies and secures their buy-in. By learning how and why the new way is better, end-users may think twice before reverting to “the old way.”

Disinfect
Once an organization has begun bringing its people, processes and technology approach in line with its best practices, it’s time to clean up inefficiencies from previous approaches. “Disinfecting” the backfile brings old files into the fold with the new system.

However, pairing a quality file analysis tool with a skilled user can bring order to chaos. By applying optical character recognition (OCR) to improve searchability, these tools can apply categorical metadata, deduplicate data, freeing up storage space, speeding up searches and bringing structure to the unstructured.

Even once all of the backfile has been digitized, ROT (redundant, obsolete or trivial) files linger. While hoarding everything is tempting in regulated industries like healthcare, keeping files that don’t need to be preserved reduces efficiency and increases opportunity for information security violations.

Technological tools can be used to create rules that apply metadata to files as they are digitized, known as autocategorization. Rules can identify high-risk material based on structure or even document types. Even subject matter can be automatically inferred based on scanning document text. These tools can also aid compliance efforts, creating defensible audit trails; monitor employee behavior, catching resource waste; and repair inaccurate metadata.

More advanced tools can accomplish these benefits and can “go live” in a matter of hours. They leverage the combined processing power of endpoints – such as the laptops where organizational data reside – to accomplish tasks, with no noticeable impact to those endpoints’ performance. Because they only use a sliver of an endpoint’s processing power, the system would be largely unaffected if one endpoint exited the network.

The most important aspect for backfile conversion is that it is defined, documented, defensible and repeatable. Or, to put it another way, there must be a strategic data-handling plan that is carefully tracked and documented.

By following these three phases, healthcare organizations can implement effective, efficient file analysis procedures – and actually get their employees to use them. That makes information more accessible and secure for those who need it, aiding care coordination and helping to ensure patients get the best care with the least wait.

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