With increasing patient out-of-pocket requirements, eMDs expects to see the demand for technologies which can help practices estimate patient responsibility at or before time of service. Eligibility is moving upstream to start getting a more accurate payment estimation based upon plans. That can be a function of both eligibility and/or contracting depending upon the technology “solution” approach. There are quote marks around the solution because the reality is that no matter how much data moves back and forth, there are still industry realities which act as constraints. A classic one is whether prior claims by a patient have been adjudicated by the time of a service with another practice. Clearly that can have a big impact upon whether the out-of-pocket estimates are accurate or not. Another is knowing exactly what services will be rendered for a particular patient condition. In some cases this is much easier to predict, for example, a patient scheduled for a specific surgery. But for others, this is less easy to know because presenting complaints can change.
Additionally, if different payers are providing different information, then this creates problems within practices because it introduces different workflows for practices to learn (e.g. collect up front for payer X and service Y, but not of Payer Z for same service Y). This means more points of inefficiency and potential for failure; and so practices will go back to “business as usual” which is somewhat unfair because it’s the practices providing the service and incurring the cost.
There are already estimation tools on the market and many practices are also creating policies to help facilitate up front collections. The key driver of course is that it becomes significantly more expensive to collect dollars after the fact and practice margins are continuing to tighten as overhead rises out of proportion to reimbursement rate increases (if any). Technology can absolutely help lower costs and we expect demand to really kick up in 2016 although we will have to get through some hype cycle dynamics.