How to Optimize EHR for the Plan-Centric Model

The lack of information prioritization in the current healthcare climate has put strict limits on the care that clinicians can provide. To resolve this, innovators of Electronic Health Record (EHR) systems must introduce ways to plan for a patient’s health management. This blog discusses how EHR’s capabilities can be optimized and extended to make this move.

The healthcare sector is moving from a Fee For Service (FFS) model to a Value-Based Care model to improve treatment outcomes. But the limited capability of Electronic Health Records (EHR) to support the discovery of flaws in a patient’s ongoing treatment does little to improve the situation.

Most EHR optimization solutions focus on shortening the learning curve of user interfaces or equipping tools to enhance interoperability. The value-based care model which prioritizes the outcomes of treatment by introducing incentives for the same must be supported by EHR capabilities.

Shaping EHR to Fit the Value-Based Care Model

Modern EHR needs to support the move from the reactive treatment of sickness to proactive management of a patient’s health. The emphasis needs to shift from the patient’s current health record to the patient’s overall health plan.

Several innovations over the last few years have sharpened the ability of EHRs to store historical patient data. But can this technology help healthcare providers prepare a roadmap or plan for a patient’s potential health management?

What Capabilities Must a Plan-Centric EHR Have?

COVID-19 has demonstrated the dire need for the prevention of illness and early detection of disease. A plan-centric approach to healthcare could standardize the outcomes and also minimize errors with fewer complications. 

A University of Melbourne research paper revealed that advance care planning can reduce hospitalizations by about 26%. With the following few enhancements, EHR can support the healthcare industry’s shift to the plan-centric model:

i) Instituting Care Plan Libraries

A patient whose diabetes is well within prediabetic levels would require a treatment plan that is vastly different from one whose diabetes is out of control. Creating a plan for a patient surrounded by family or other care surrogates would be different from planning for a patient living alone. Incorporating a wide variety of care plans in EHR that could be tweaked along multiple parameters is essential.

ii) Algorithmic Planning

Feasible and optimal planning requires the involvement of algorithms that automatically generate treatment summaries. Combining the data around the various chronic and lifestyle-related ailments of a patient, a master plan can be formulated. Once a plan is in place, the algorithm can help further in reducing conflicts and redundancies in the patient’s medical information.

iii) Patient Event Support

A Decision Support System (DSS) must be in place to remind staff members about upcoming and overdue patient-related events. In case the patient’s ongoing treatment plan needs changes on the fly, relevant messages must be routed to the appropriate team member. The EHR’s workflow logic can accordingly be changed as per the new test results.

iv) Individual and Population Analytics

In addition to taking care of the individual patient’s data analytics, the EHR can be extended to handle the business intelligence of the healthcare provider’s entire patient base. In this way, the EHR must be able to use the lessons learned with one patient and apply them to a patient with similar needs.

EHR Process Improvements to Drive the Plan-Centric Model

International healthcare systems are looking at altering long-established EHR processes for their intended purpose – patient satisfaction. Ongoing innovation in this technology is being expedited to serve the immediate demand for value-based treatment. 

Three examples of technologies that could aid this transition are:

• Natural Language Processing for Workflow Enhancement

Natural Language Processing (NLP) software programs help decipher medical vocabulary that consists of a vast lexicon of terms and concepts. Via a microphone in a medical practitioner’s office setting, this software automatically captures audio and interprets the technicalities of what’s being said. 

For completely unstructured medical text, clinical NLP or cNLP comes into play. The cNLP model helps codify and scale information relevant to ongoing care management of chronic conditions like diabetes or pulmonary ailments.

This technology can help highlight the encounter date, diagnosis, and procedures of the associated treatment plans based on audio transcriptions. While NLP or cNLP are pivotal in catching complicating conditions at the right time, they can provide valuable insights in planning out a treatment roadmap as well.

• Predictive Analytics-Powered Decision Support

Prediction of clinical outcomes is essential in planning out procedures and decision support for a patient and healthcare organization’s EHR. AI-based modeling, statistics, and data mining can help organizations utilize learnings from one patient’s health records and implement them in another patient with similar underlying symptoms.

To effectively go about implementing the plan-centric approach, care delivery and patient experience must be at the forefront of EHR innovation. Additionally, real-time device data analytics combined with NLP can yield actionable insights for preparing robust care plans.

• Increasing the Patients’ Interaction with their Own Data

Engaging the patient with access to their own EHR is an important goal to make the healthcare system more patient-centric. In addition to regular access to their data, electronic copies of their EHR should be available on demand. User-friendly patient portals, where patients interact with their data, must have all these functionalities.

In an ideal scenario the primary collection, storage, and sharing of information would all be integrated into the patient portal. This way the patient could feel more connected to the healthcare system they are a part of. Increased ownership for the patient is the first step in building a plan-centric EHR paradigm.

ALSO READ: 5 ways Electronic Health Record (EHR) improves Patient experience

Improve Your Bottom Line with Plan-Centric EHR

A plan-centric approach is certainly a more holistic take on EHR management. However, the end goal in the large-scale shift of healthcare systems to the new model is not just limited to disease prevention and reduced treatment redundancies. 

At the end of the day, more patient engagement and repeat business translate to increased revenues for healthcare providers. While cutting down on overheads, providers can fully utilize their resources for continuous innovation. You can learn about our array of EHR optimization strategies.