Differences in severity at admission for heart failure between rural and urban patients: the value of adding laboratory results to administrative data

Smith et al. BMC Health Services Research (2016) 16:133 DOI 10.1186/s12913-016-1380-z RESEARCH ARTICLE Open Access Differences in severity at admission for heart failure between rural and urban patients: the value of adding laboratory results to administrative data Mark W. Smith1*, Pamela L. Owens2, Roxanne M. Andrews2, Claudia A. Steiner2, Rosanna M. Coffey1, Halcyon G. Skinner3, Jill Miyamura4 and Ioana Popescu5,6 Abstract Background: Rural/urban variations in admissions for heart failure may be influenced by severity at hospital presentation and local practice patterns. Laboratory data reflect clinical severity and guide hospital admission decisions and treatment for heart failure, a costly chronic illness and a leading cause of hospitalization among the elderly. Our main objective was to examine the role of laboratory test results in measuring disease severity at the time of admission for inpatients who reside in rural and urban areas. Methods: We retrospectively analyzed discharge data on 13,998 hospital discharges for heart failure from three states, Hawai’i, Minnesota, and Virginia. Hospital discharge records from 2008 to 2012 were derived from the State Inpatient Databases of the Healthcare Cost and Utilization Project, and were merged with results of laboratory tests performed on the admission day or up to two days before admission. Regression models evaluated the relationship between clinical severity at admission and patient urban/rural residence. Models were estimated with and without use of laboratory data. Results: Patients residing in rural areas were more likely to have missing laboratory data on admission and less likely to have abnormal or severely abnormal tests. Rural patients were also less likely to be admitted with high levels of severity as measured by the All Patient Refined Diagnosis Related Groups (APR-DRG) severity subclass, derivable from discharge data. Adding laboratory data to discharge data improved model fit. Also, in models without laboratory data, the association between urban compared to rural residence and APR-DRG severity subclass was significant for major and extreme levels of severity (OR 1.22, 95 % CI 1.03–1.43 and 1.55, 95 % CI 1.26–1.92, respectively). After adding laboratory data, this association became non-significant for major severity and was attenuated for extreme severity (OR 1.12, 95 % CI 0.94–1.32 and 1.43, 95 % CI 1.15–1.78, respectively). Conclusion: Heart failure patients from rural areas are hospitalized at lower severity levels than their urban counterparts. Laboratory test data provide insight on clinical severity and practice patterns beyond what is available in administrative discharge data. Keywords: Heart failure, Severity of illness, Clinical laboratory results, Discharge data, Rural hospitals, Urban hospitals * Correspondence: 1 Truven Health Analytics, 7700 Old Georgetown Rd, Suite 650, Bethesda, MD 20814, USA Full list of author information is available at the end of the article © 2016 Smith et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Smith et al. BMC Health Services Research (2016) 16:133 Background A substantial number of hospitalizations have been deemed potentially avoidable [1]. They include admissions for ambulatory care sensitive conditions (ACSCs), a set of illnesses for which appropriate, timely ambulatory care may reduce the need for hospitalization [2, 3]. In particular, many studies have noted the higher rate of ACSC hospitalization for prevalent conditions such as heart failure (HF) in rural areas relative to urban areas [3, 4]. While differences in ACSC hospitalization rates by location have been attributed to differences in access to timely ambulatory care, an alternative explanation for differences in rates relates to admission decisions. Physicians may be likely to admit patients from rural areas with lower clinical severity than patients from urban areas. Rural patients could be admitted at lesser severity as a precaution. For example, if the admitting physician believes that the patient is not obtaining sufficient ambulatory care, would not have access to necessary acute care in a timely manner, or would not obtain adequate ambulatory care following a future hospitalization, then a lower severity threshold for admission may be justified. Judging severity of illness at admission is difficult with traditional data. Chart reviews provide very detailed information but are prohibitively expensive. As a result, multi-site studies of hospital care have long relied on administrative discharge data. Discharge data captures diagnosis and procedures during a stay using International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) diagnosis codes and procedure codes. The ICD-9-CM codes frequently do not capture the level of severity or the change in severity over the course of treatment. Laboratory results provide a window into patient health day-by-day during hospitalization and are available from the moment of admission. Recent technological advances in the field of electronic data management, and the adoption of a uniform set of codes for laboratory data (known as the Logical Observation Identifiers Names and Codes, or LOINC) [5], have enabled the successful integration of key laboratory test values with hospital discharge data. Despite variable implementation of these standard codes, integrated discharge and laboratory databases hold the promise of improved severity measurement for a broader range of populations and outcomes than has been possible with medical record data. Research has shown that enhancing administrative data with clinical laboratory data collected at hospital admission substantially improves the performance of models estimating risk-adjusted hospital mortality [6–8]. Using data collected on hospitalized patients we cannot directly evaluate the role of severity in the decision to admit to the hospital because we lack data on patients who were not admitted. Nevertheless, we can observe variations in the level of severity among newly admitted Page 2 of 9 patients, and whether severity on admission as assessed by laboratory values varies across patients from rural versus urban areas. In the current study, we sought to investigate whether patients from rural areas were admitted to hospitals at lower severity levels than patients from urban areas and whether laboratory values at hospital admission would (...truncated)