Informatica - Accountable Care Analytics: 360 Degree View of the Patient

In the traditional fee-for-service reimbursement system, health information is rarely shared across the continuum of care or between disparate healthcare settings. Data that is shared can be lost, late, incomplete, or inaccurate, resulting in an imperfect picture of a patient’s condition, medical history, and prior treatment. As a result, providers may deliver inappropriate care, order redundant tests, prescribe contraindicative medications, or give the patient contrasting follow-up care recommendations. These types of medical errors can drain a health provider’s resources, have an adverse impact on patient experience, or cause serious harm to the patient.

In an attempt to overcome the adverse effects of siloed care under the fee-for-service reimbursement model, ACA introduced new value-based delivery models such as accountable care organizations (ACOs) to improve quality and contain costs. Broadly defined as a group of providers that are integrated across disparate settings into a unified network, ACOs require vast amounts of data to manage a patient population, coordinate care across the continuum, and take on risk for the beneficiaries that are assigned to them. In the two years since the Centers for Medicare & Medicaid Services (CMS) rolled out pilot ACO programs, various models of accountable care have proliferated through federal payment mechanisms focused primarily on Medicare populations and within the private sector. However, all accountable care organization models require extensive data to monitor performance and patient outcomes in accordance with the quality standards and evidence-based guidelines associated with reimbursement, accountability, and risk.

ACO, analytics, accountable care organizations