Healthcare Q&A: Maria Clemens, CIO of Management and Network Services

Maria Clemens, CIO of Management and Network Services

We recently sat down with CIO Maria Clemens to learn more about how her organization – Management and Network Services (MNS) – approaches ecosystem interoperability. The nation’s leading independent expert in managed care within the skilled nursing environment, MNS offers a single point of contact for skilled nursing facilities’ network needs, value-added services, and efficient solutions.

Maria and her team just came off an interoperability initiative to minimize the use of faxes and phones to transmit patient authorization and preapprovals between providers and payers. The effort has paid off in the form of time savings and improved patient care. We’re excited that Maria is sharing her experiences with us.

HULFT: Interoperability means different things to different healthcare organizations. How does MNS define it?

Maria: Healthcare is a complex phenomenon where all patients present differently. AT MNS, we view interoperability as the communication between two or more systems for the purpose of data gathering, interpretation, analysis, and then further using that data to improve (within a skilled nursing facility) a patient’s length of stay, readmission rates, and quality of care.

This definition is pretty broad, and I want to remind people that interoperability doesn’t have to be all or nothing. You can think big picture but start with smaller, realistic goals.

HULFT: You’ve recently embarked on a project to minimize the use of fax machines. Why were fax machines a problem?

Maria: The original process was pretty time consuming – data were being sent via fax and phones to insurance payers for approval, which meant the risk of data loss was much higher. If the right people weren’t receiving the data they needed, patients ended up being in the hospital longer than necessary before they could be transferred to a skilled nursing facility for rehab.

Generally speaking, this process authorization and preapproval are still being conducted via telephone and electronic fax. Even in our digital age, many continue to operate in a space where telephonic and faxed updates are still the ‘norm.’ At MNS, we sought to achieve even better results from our digital opportunities to increase the speed at which the authorizations and pre-approvals are managed.

HULFT: What’s the framework around the plan to minimize and eventually eliminate the use of fax machines? 

Maria: First, we created a “portal” that will bring data in from hospitals and the nursing homes for patients that are receiving skilled care in a nursing home. The idea is to electronically deliver that data to the insurance payer for approval online.

The portal is designed to allow for systematic processing of authorizations and preapprovals for skilled nursing placements. We have implemented hosted services with document storage, patient demographic entry, benefit details, and relevant documents. All documents related to a patient case are available in one central location for access by the hospital, receiving provider, and insurance payer. Once the approval or denial is entered, the relevant parties are systematically notified of the change in the record, and each change/addition/amendment is documented in the case. In the end, the opportunity to evaluate turnaround times is available to executives for analysis.

HULFT: In your case, how does digital automation impact patient care?

Maria: So much of the problem is centered on access and quality/timeliness of data. We created APIs that could pull patient information from a nursing home’s EMR in a way that keeps the data up-to-date.

These APIs pull the therapy, nursing, wounds, and medication lists, making it less cumbersome for the provider to get that information into our portal. That data needs to be updated on a weekly basis, and the payer has to authorize the stay.

We have made it easier for both the providers and payers to come together, bringing in the data more quickly so that we can get the patients moved to the next level of care. Ultimately, digital automation means very little if it doesn’t translate into better patient care. Moving a patient from one level of attention to another in a quicker fashion is viewed as desirable for the patient’s overall quality of care, and it eventually saves money for the healthcare system overall.

HULFT: What, if any, obstacles did you face in this project?

Maria: We had to spend about 12-13 months getting through all the red tape with the compliance and legal teams of the various payers within our network. This was challenging because they have an upstream contract with the government.

In addition to regulations, we had to identify and nourish the change agents in the project. Most organizations have available change agents that are the typical cheerleaders. MNS had to identify each of these change agents and work closely with them to get the rest of the teams to buy into the prospect of using the new and improved processes.

HULFT: What has been the outcome so far?

Maria: The most significant improvement is time savings – we’ve been able to cut out an entire day and a half of the pre-certification process by utilizing a system that pulls all the data together from the hospital H&P and the nursing home therapy, wounds, and medications.

We’re basically seeing a lower length of stay, fewer readmissions because the patients are leaving the hospital and getting the rehab they need faster in the nursing homes. They’re getting appropriately discharged at the right time, getting the proper care in a timelier fashion and, as a result, they’re not bouncing back to the hospitals as much.

HULFT: Any advice for our readers in healthcare who are wrestling with getting the right data to the right people at the right time?

Maria: First, get over the idea that you need every single piece of data out there. You don’t. We’re all on data overload, and that makes it challenging for us to know how to incorporate or analyze the outcomes and put them into business practices.

Second, start with a reliable data foundation. For us, this meant establishing a small “data governance” team to help us determine what’s critical and what isn’t. Without that solid data foundation, you won’t be successful in implementing predictive analytics and intelligence.

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