The Future of Electronic Health Records - Part 1 of 4: EHR as a Business Model Enabler

When I speak with innovators who are creating new business models for care delivery, I ask them about how they are going to do the documentation. In most cases, they say that they will have to build their own EHR system. In this series, “The Future of Electronic Health Records”, I would like to touch upon some ideas on how EHRs can morph themselves to serve the healthcare provider and patient communities better.

We all know the importance of the role that Electronic Health Records (EHR) play in the delivery of healthcare. When care is delivered in a fee-for-service care setting, we are using this documentation in an EHR for reimbursement purposes. Imagine what would happen if you are not getting paid based on documentation. Then, how would the need for documentation change? EHRs have to be modified for documenting a clinical process, mainly to support the new business model. Outside of healthcare, information technology has grown by leaps and bounds and is enabling new business models to flourish. Here I describe some business models where EHR can play an extended role in order to support these newer models of care.

1. Direct Primary Care:  The American Academy of Family Physicians defines Direct Primary Care as “a practice and payment model where patients/consumers pay their physician or practice directly in the form of periodic payments for a defined set of primary care services.” This eliminates the middlemen in the payment process. This is a fixed payment for predetermined services. The payment does not depend on the documentation. The documentation here is mainly for continuity of care purposes. There is no incentive to document more nor have an elaborate coding and billing process. The audio or video recordings may need to be stored for future use. Here patient satisfaction plays a major role. Open and available communication channels are critical. Patient’s preferences need to be catered to. An Omni channel strategy for communication and marketing are important. The front end needs to be robust. Whether it is a web portal, self-service appointment system or social media presence, it makes a big difference in attracting and keeping the clientele.

2. Telehealth Model: The COVID-19 pandemic has brought this scarcely utilized service to the forefront. It also showed that many services could be delivered through this touchless system of care. It created a telecare-only business model where companies can provide care to patients remotely and will refer them to on-site care only if needed. Do you save the video or audio recording? Here home testing and diagnostic assessments play a prominent role. Remote patient monitoring and chronic care management also fall into this category, where patients are taken care of at home and thus decreasing the need for hospitalization or coming to the clinic for a face to face visit. In this business model there are challenges to the data that needs to be transmitted to the EHR. The person entering data could be the patient, care giver or a visiting nurse. The data could also be coming from a device or a connected testing device. How does one condense or summarize continuous data that is coming from a device? How do you separate the noise from the signal? Although the device maker has a role in this process, the EHR needs to tackle this problem at some level on how to collect, condense and collate it for the physician consumption.

3. Full-Risk Capitation Model: In this model the physician group is taking on full risk for the care of a patient for a fixed cost. This is a way to control total costs for the payers while providing quality care. This is in a way, the opposite of a fee-for-service business model. In this model the provider makes money when the patient is healthy and loses money when they get sick. It is in the providers’ best interest to prevent bad outcomes and expensive care. In such a business model a lot of attention has to be given to data that helps make better decisions for patients. This may include guideline implementation, risk stratification and knowledge translation. This is probably the best use case for information technology tools such as machine learning and artificial intelligence in healthcare in predicting and preventing bad outcomes for patients. Close attention needs to be paid to the variables that need to be collected in order to do the analytics that the data science team needs to do. The EHR plays a major role in not only data collection for analytics, but in providing decision support at the point of care.

In the future, the role of EHR as the hub for data acquisition becomes more important. As care models of the future evolve, the EHRs need to evolve to provide support to these new and evolving business models.