title: Coding for quality measurement: the relationship between hospital structural characteristics and coding accuracy from the perspective of quality measurement.
abstract: This study examines the relationship between hospital structural characteristics and coding accuracy from the perspective of quality measurement. To measure coding accuracy for quality measurement, the study utilizes the "present on admission" indicator, a data element in the New York state hospital administrative database. This data element is used by hospitals across New York state to indicate if a particular secondary diagnosis is "present on admission," "not present on admission," or "uncertain." Since the accurate distinction between comorbidities (present at admission) and complications (not present at admission,) is critical for risk adjustment in comparative hospital quality reports, this study uses the occurrence of the value "uncertain" in the "present on admission" indicator as the primary measure of coding accuracy. A lower occurrence of the value "uncertain" is considered to be reflective of better coding accuracy. Moreover, since coding accuracy of the "present on admission" indicator links back to the accuracy of physician documentation, a focus on the occurrence of the value "uncertain," also helps gain insight into physician documentation efficacy within the facility. By utilizing this approach, therefore, the study serves the twin purpose of 1) addressing the gap in the literature with respect to large-scale studies of "coding for quality," and 2) providing insight into the structural characteristics of institutions that are likely facing organizational challenges of physician documentation from the perspective of quality measurement.
authors: Quality and Patient Safety at Fairview Hospital in Great Barrington, MA, USA.
authors: Pavani
authors: P
authors: Rangachari
mesh_terms: D016208:Databases, Factual; D006742:Hospital Bed Capacity / Q000706:statistics & numerical data; D006761:Hospitals / Q000145:classification / Q000706:statistics & numerical data*; D006801:Humans; D019451:Information Management / Q000145:classification / Q000458:organization & administration*; D016347:Medical Records Systems, Computerized / Q000458:organization & administration*; D009518:New York; D011785:Quality Assurance, Health Care; D012044:Regression Analysis