As the era of value-based payment approaches, practices around the country must figure out how to quickly and efficiently collect and analyze their clinical and financial data to achieve quality measurement goals and control costs.
At Davis Family Physicians, a seven-doctor group in Layton, Utah, we have implemented clinical analytics software that helps aggregate real-time data from physicians, which we then use to produce quality metric reports. By refining clinical quality data analysis and providing physicians access to real-time practice-wide data, we have increased our reimbursement due to an improved ability to identify and close gaps in care; at the same time, we have prepared the practice for emerging payment models.
The increase in reimbursement has not come from the fee schedules of existing managed care contracts. Rather, from two main areas of emphasis:
- The capture of greater incentive payments from payer-sponsored quality initiatives. We had the opportunity to participate in the focus of senior wellness exams. With a small database of senior patients who participate with one Medicare advantage plan we collected over $18,000 of additional incentive that we would not have otherwise collected.
- Improved exception reporting. Using data sets generated by the analytics software we were able to connect with many of our patients who were overdue to receive past due medical care that generated additional office visits for the Family Practice-Preventive PQRS measures — smoking cessation, osteoporosis, mammography, BMI, influenza and senior vaccination. This significantly improved the quality of care we were able to render.
Real-time data analysis essential
Improving clinical quality performance has always been a priority at Davis Family Physicians. For years, we submitted our EHR data to a university-affiliated research network that compared our physicians' performance against a national database of three million patients on 58 quality measures.
All demographic data from our 80,000 patient-chart database was removed before analysis and then returned to us, requiring our leadership team to spend six to eight hours each quarter matching their report — which was by then at least three months old — to each patient’s record. This was in addition to the four to five hours our staff spent initially extracting the data from electronic charts.
Davis had not yet pursued any clinical quality-based payment incentives from our payers other than meaningful use. Nonetheless, our practice leaders recognized that the industry was shifting toward compensation models based on achieving quality targets and controlling costs, as evidenced by the growth of accountable care organizations from Medicare and commercial payers. The key to succeeding in these programs was being able to monitor performance and encourage physicians to change behaviors.
Analytic tools at the point-of-care
Spurred by the changing payment landscape, we began to explore clinical data analytic software tools that would deliver real-time reports at the point-of-care.
Our practice’s EHR system reseller, which had also been investigating clinical analytics tools to offer their clients, recommended Clinigence, a cloud-based software platform that integrated with the EHR system. In minutes rather than months, the software delivered the types of quality guideline reports we were receiving from the research organization, with the patient demographics intact. Since the patients’ data came from our own charts, the clinical information was up-to-date and accurate.
Our reseller had recommended one other analytics partner, but we determined that the data-transfer and conversion process would have been laborious and difficult. In comparison, with Clinigence, we could immediately export patient data to health quality measures.
Physician leaders investigated the software and were immediately impressed by its ability to help them visualize their compliance with selected guidelines and established care protocols, and identify patients requiring intervention. To fully leverage the analytics software, however, our practice would have to reconfigure workflows and our EHR system templates to capture the adequate data needed to create robust quality reports.
Our leaders met with physicians and clinical support staff, as well as coding and billing employees, to educate them on the importance of detailed documentation. In some cases, this increased data capture required medical assistants to ask additional questions prior to the physician arriving in the exam room. EHR templates were altered so assistants would be reminded via alerts to ask patients questions about managing their relevant chronic conditions, along with queries about the chief complaint.
Our physicians were motivated to improve their documentation detail to increase their reimbursement level — but also to deliver better patient care by addressing more co-morbidities during a single visit. Their productivity, however, was not dramatically impacted due to the redesigned EHR templates that required medical assistants or support staff to gather more data earlier in the visit.
In only the first few months, Davis Family Physicians has already experienced an overall increase in billings and collections, primarily due to the increased reimbursement that our clinical quality data analytics software allowed us to achieve. The estimated improvement is at least 15 percent among the providers who, empowered by the analytics, have implemented new practices.
The practice plans to leverage this quality improvement momentum by applying for Patient-Centered Medical Home recognition from the National Committee for Quality Assurance and is adding a patient relations/compliance assistant team member to help earn the recognition.
In the meantime, we will continue to monitor and help improve our physicians’ performance with this clinical analytics tool while seeking new opportunities to grow reimbursement through our already superior level of evidence-based care.
Jon Goates is chief executive officer of Davis Family Physicians in Layton, Utah.