Identifying potentially preventable complications using a present on admission indicator

Health Care Financing Review, Spring, 2006 by John S. Hughes, Richard F. Averill, Norbert I. Goldfield, James C. Gay, John Muldoon, Elizabeth McCullough, Jean Xiang

INTRODUCTION

The Institute of Medicine's 2000 report on the human and financial costs of medical errors, accelerated efforts to improve patient safety in the U. S. (Kohn, Corrigan, and Donaldson, 2000). Since then, an increasing number of policymakers have advocated not only public reporting of quality measures, but also linking payment to quality measures (Midwest Business Group on Health 2002; Medicare Payment Advisory Commission, 2005; National Committee for Quality Assurance, 2004). Performance-based payment proposals include rewards not only based on processes of care guidelines, but also on outcome measures such as mortality and complication rates. Performance measures are seen as a way to focus quality improvement efforts and to achieve a safer health care system.

In order to determine hospital complication rates, several investigators have created methods using computerized discharge abstract data as an alternative to the time and expense of detailed chart review (Brailer et al., 1996; DesHarnais et al., 1990; Iezzoni et al., 1994; Iezzoni 1992; Romano et al., 2003). The ability to identify complications from discharge abstract diagnoses has been limited, however, because in most of the U.S. it is not possible to distinguish diagnoses that were present at the time of admission from those that arose after admission. As a result, the identification of complications has been limited to secondary diagnoses that are either unlikely to have been present on admission or are complications by definition (e.g., post-operative wound infection). Therefore, complications screening methods have tended to focus on patients that would be unlikely to have had a major complicating problem at the time of admission, such as those undergoing elective surgery. Even with these limits, however, complications screening methods still identify many cases where the condition was preexisting rather than hospital acquired (Lawthers et al., 2000, Naessens and Huschka, 2004).

The lack of a POA indicator also limits the use of risk-adjustment methods for complications screening. Risk of complications varies by the reason for admission, the severity of the underlying illness, and the presence of coexisting diagnoses at the time of admission (Thomas and Brennan, 2000). If present on admission, secondary diagnoses can be used to adjust for a patient's risk of complications; if not present on admission, they could represent complications of care, and should not be used for risk adjustment.

The reason for admission is an important determinant of a patient's risk of complications. Patients treated for medical conditions will be at risk for different complications, and at different rates, than patients admitted for surgery. Among surgical patients, the type of surgery will strongly influence the type and frequency of complications. For example, a patient admitted for coronary bypass grafting will be more likely to develop heart failure than one admitted for a hernia repair. Susceptibility to complications also varies widely among medical patients; a patient admitted with a stroke will be more likely to develop aspiration pneumonia than one admitted with acute urinary retention.

Risk of complications also depends on the severity of the illness that caused the admission, as well as the presence of coexisting illnesses. Patients hospitalized with a more severe form of the underlying illness or with multiple comorbid conditions have a higher risk of complications (Daley, Henderson, and Khuri, 2001; Rosen et al., 1995; Rothschild, Bates, and Leape, 2000). Fair comparisons of complication rates across hospitals require the use of risk-adjustment methods that account for each of these factors.

A POA indicator is currently required on all hospital discharge abstracts by New York and California. It has been proposed as an additional data element on the Uniform Billing form commonly referred to as the UB-044, and has been mandated by the Deficit Reduction Act of 2005 to be used on all bills submitted to Medicare beginning in October 2007. This article describes a new method of reporting risk-adjusted in-hospital complication rates using discharge abstract data and a present on admission indicator for secondary diagnoses. The POA indicator serves two purposes: (1) to create a method for identifying potentially preventable complications from among diagnoses not present on admission, and (2) to allow only those diagnoses designated as present on admission to be used for assessing the risk of incurring complications.

PPC SYSTEM METHODS

Overview

In developing the PPC System it was first necessary to identify the subset of diagnoses that, if not present on admission, would represent potentially preventable complications, and assemble them into groups containing similar diagnoses. The next step was to determine the types of patients for whom each group of complications was potentially preventable. The final step was to adjust for susceptibility to complications based on the reason for admission, SOI, and comorbid conditions. We could then calculate and compare actual and expected risk-adjusted complication rates for individual hospitals using norms derived from statewide average complication rates. This study in particular examines the effect of the reason for admission and admission SOI on patients' susceptibility to potentially preventable complications, and the effect of complications on costs and mortality.