Jason M Sutherland1, Olafr Steinum. 1. The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, Hanover, NH 03766, USA. Jason.Sutherland@dartmouth.edu
Abstract
OBJECTIVES: As chronic conditions affect the evaluation, treatment, and possible clinical outcomes of patients, accurate reporting of chronic diseases into the patient record is expected. In some countries, the reported magnitude of comorbidity inaccuracy and incompleteness is compelling. Beyond incentives provided in payment systems, the role and significance of other factors that contribute to inaccurate and incomplete reporting of chronic conditions is not well understood. A complementary approach that identifies factors associated with inaccurate and incomplete data is proposed. METHODS: In a two-step process, the method links hospitalizations of patients who are repeatedly hospitalized over a determined period and identifies characteristics associated with accurate and complete reporting of chronic conditions. These methods leverage the high prevalence of chronic conditions amongst patients with multiple hospitalizations. The study is based on retrospective analysis of longitudinal hospital discharge data from a cohort of Ontario (Canada) patients. RESULTS: There are a multitude of factors associated with incomplete clinical data reporting. Patients discharged from community or small hospitals, discharged alive, or transferred to another acute inpatient hospital tend to have less complete comorbidity reporting. For some chronic diseases, very old age affects chronic disease reporting. CONCLUSIONS: Longitudinally analyzing chronically ill patients is a novel approach to identifying incompletely reported clinical data. Using these results, coding quality initiatives can be focused in a directed manner.
OBJECTIVES: As chronic conditions affect the evaluation, treatment, and possible clinical outcomes of patients, accurate reporting of chronic diseases into the patient record is expected. In some countries, the reported magnitude of comorbidity inaccuracy and incompleteness is compelling. Beyond incentives provided in payment systems, the role and significance of other factors that contribute to inaccurate and incomplete reporting of chronic conditions is not well understood. A complementary approach that identifies factors associated with inaccurate and incomplete data is proposed. METHODS: In a two-step process, the method links hospitalizations of patients who are repeatedly hospitalized over a determined period and identifies characteristics associated with accurate and complete reporting of chronic conditions. These methods leverage the high prevalence of chronic conditions amongst patients with multiple hospitalizations. The study is based on retrospective analysis of longitudinal hospital discharge data from a cohort of Ontario (Canada) patients. RESULTS: There are a multitude of factors associated with incomplete clinical data reporting. Patients discharged from community or small hospitals, discharged alive, or transferred to another acute inpatient hospital tend to have less complete comorbidity reporting. For some chronic diseases, very old age affects chronic disease reporting. CONCLUSIONS: Longitudinally analyzing chronically ill patients is a novel approach to identifying incompletely reported clinical data. Using these results, coding quality initiatives can be focused in a directed manner.