A desire among practitioners to weather the storm of health care reform (continuing to grow) has recently created a wide berth for alternative health care delivery models and alternate payment mechanisms and models. These include accountable care organizations (ACOs; alternative hospital-centric, integrated delivery models, integrated physician groups, and others. While such models are still evolving, one thing is for certain: Executing them will necessitate the development of practice reporting processes that contain a deeper, more comprehensive analytics component than those currently in use, according to William G. Pickart, CEO of Integrated Medical Partners (IMP; Milwaukee, Wisconsin; www.integratedmp.com).
He says, “Many reports and systems, as they stand, do not offer access to the meaningful and actionable data and detail needed to provide potential participants in an integrated delivery model with an understanding of the implications of various alternative payment mechanisms in play today. Nor do they offer access to or analytics required to enable the practice to demonstrate their ability to achieve the objectives of ACOs and similar delivery models—better patient care, at a lower cost.
“We are moving from a fee-for-service payment model to an episode of care payment model with an overlay of demonstrative evidence of quality outcomes and efficient use of resources (utilization of services) necessary in the emerging healthcare delivery model.”
Pickart offers the example of a report that currently contains data, collected via the revenue cycle management (RCM) process, radiology information system (RIS), hospital information system (HIS), financial reporting systems, and other key data sets, throughout the continuum of care pertaining to services required for an episode of care.
“If, for instance, a patient enters the delivery system, no matter what the episode of care, one will need to be able to capture historical data, with respect to resource utilization for a particular episode of care, and with sufficient granularity across the continuum of care, to identify and assess the costs of delivery of services related to that episode of care,” Pickart says. Outliers and root causes of outlier cost drivers and drivers of utilization variances for a specific episode of care can be identified. Once the historical evidence is understood, then a modeling of revenue and cost, on both a fee-for-service model and bundled episode of care model, can be developed. With such data and information in hand, certain variables included in the data set, such as influences of certain referring physician ordering patterns, performing physician delivery patterns, unique presenting patient demographics (age, sex, and more), one can identify root cause of outliers of cost and utilization drivers that will require management or contractual provisions consideration when supporting the pricing of the episode of care.
Following Up
Analytics contained in the report would also indicate whether imaging studies executed at certain intervals preceding the episode of care, during the episode of care, and following the episode of care, as well as throughout the continuum of care (ER, operating room, inpatient, outpatient, office, and outreach sites of service) result in cost efficient outcomes based upon the care provided. They also point to actionable intervention to reduce or eliminate cost drivers.
“By this, we mean what overall protocols were followed to care for the patient during the episode, and how they compare when benchmarked against similar data collected on other patients,” Pickart states. This helps to makes a case for whether optimal care was provided at optimal cost, and if alternative protocols may be warranted--e.g., three imaging services to support a particular condition and treatment versus seven, based on data demonstrating that the lower number of services was appropriate for a patient with the identical condition and of comparable overall health status.
He adds that second-generation analytics will, in addition, eventually need to incorporate quality of care/care outcomes data that transcends billable diagnostic codes if they are to truly resonate with ACO decision-makers. ICD-10 will bring more specificity to billable diagnostic codes, but in the next three to five years, ACOs and, quite likely, other alternative delivery entities will command “color” to be cross-referenced within report content, Pickart elaborates.
“More and more, ever deeper and broader sets of data are going to include empirical evidence that supports analytics, to create a complete picture for every provider in order to make informed decisions and take appropriate action.” Pickart concludes. “As payment mechanisms change and provider reporting requirements evolve, so, too, will the need for comprehensive analytics of all kinds and effective reporting to ensure appropriate payment for effective and efficient delivery of care and differentiation of provider performance in the emerging healthcare space. Never go to a gun fight with a water pistol.”
Julie Ritzer Ross is editor of RadAnalytics