Miscoding of hospital discharges as acute myocardial infarction: Implications for surveillance programs aimed at elucidating trends in coronary artery disease

Kennedy, Gemma T.; Stern, Michael P.; Crawford, Michael H.

doi:10.1016/0002-9149(84)90625-8

Cited by 46 publications

(22 citation statements)

References 9 publications

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“…Several studies have investigated the validity of hospital discharge and/or mortality data on acute myocardial infarction by comparing these data with specific study registers [8][9][10][11][12][13][14][15] or physician reviews [5,[26][27][28]. In these studies, a wide range of estimated values for the sensitivity and positive predictive value was found due to differences in case identification.…”

Section: Discussionmentioning

confidence: 99%

“…Two possible explanations for this decreasing mortality rate are a decline in the population risk of CHD leading to a lower incidence, or a better survival of cases with CHD resulting in a lower case-fatality rate. Information about the trend in the incidence rate could be used to distinguish between these two explanations [5].…”

Section: Introductionmentioning

confidence: 99%

“…Because cardiovascular disease registries are lacking in most countries, record linkage with national hospital discharge and mortality data is often used to estimate the incidence of CHD [5,6]. Recently, Koek et al [7] estimated the incidence rate of a first acute myocardial infarction in 2000 by record linkage to the Dutch hospital discharge register (HDR) and causes of death registry from Statistics Netherlands.…”

Section: Introductionmentioning

confidence: 99%

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Validity of coronary heart diseases and heart failure based on hospital discharge and mortality data in the Netherlands using the cardiovascular registry Maastricht cohort study

et al. 2009

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Incidence rates of cardiovascular diseases are often estimated by linkage to hospital discharge and mortality registries. The validity depends on the quality of the registries and the linkage. Therefore, we validated incidence rates of coronary heart disease (CHD), acute myocardial infarction, unstable angina pectoris, and heart failure, estimated by this method, against the disease registry of the cardiovascular registry Maastricht cohort study. The cohort consists of 21,148 persons, born between 1927 and 1977, who were randomly sampled from Maastricht and surrounding communities in 1987-1997. Incident cases were identified by linkage to the Netherlands causes of death registry and either the hospital discharge registry (HDR) or the cardiology information system (CIS) of the University Hospital Maastricht. Sensitivities and positive predictive values were calculated using the CIS-based registry as gold standard. Relatively high sensitivities and positive predictive values were found for CHD (72 and 91%, respectively) and acute myocardial infarction (84 and 97%, respectively). These values were considerably lower for unstable angina pectoris (53 and 78%, respectively) and heart failure (43 and 80%, respectively). A substantial number of cases (14-47%) were found only in the CISbased registry, because they were missed or miscoded in the HDR-based registry. As a consequence, the incidence rates in the HDR-based registry were considerably lower than in the CIS-based registry, especially for unstable angina pectoris and heart failure. Incidence rates based on hospital discharge and mortality data may underestimate the true incidence rates, especially for unstable angina pectoris and heart failure.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Validity of coronary heart diseases and heart failure based on hospital discharge and mortality data in the Netherlands using the cardiovascular registry Maastricht cohort study

et al. 2009

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“…Health care organizations are currently using this data to assess the quality of care, evaluate hospital utilization and practice patterns, study the appropriateness of health care costs, conduct epidemiological studies, and supplement their decision support systems (Kennedy, Stern, & Crawford, 1984;Hannah, 1995). With the rise in ambulatory care over the past decade, the attention of health care professionals is now shifting to better understand the content of the ambulatory encounter.…”

Section: Statement Of the Problemmentioning

confidence: 99%

“…Sensitivity (true positive rate), also referred in some studies as "completeness" or "accuracy rate," is the conditional probability that a diagnosis within the specified group was coded on the original record given that a diagnosis within the specified group was actually present on the re-abstracted record (Fisher et al, 1992;Hogan & Wagner, 1997;Yarnall et al, 1995). Reported sensitivity rates of DRG diagnoses vary from 79% (Hsai et al, 1988), 94% for myocardial infarctions (Kennedy et al, 1984), 58% to 97% (Fisher et al, 1992), and 68% to 97% (Meyer & Krakauer, 1997). The most recent studies concerning outpatient diagnosis coding report slightly lower sensitivity rates that include 69% (Horner et al, 1991), 69%, and 82% (Yarnall et al, 1995).…”

Section: Statement Of the Problemmentioning

confidence: 99%

Coding Accuracy of the Ambulatory Data System: A Study of Coding Accuracy Within the General Internal Medicine Clinic, Walter Reed Army Medical Center

Gall¹

1998

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Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302, and The Military Health System (MHS) has implemented a relatively new automated information system to help capture diagnoses, procedures, and insurance data for all ambulatory encounters. This system, recently implemented at Walter Reed Army Medical Center (WRAMC), is called the Ambulatory Data System (ADS). While the current MHS metric for ADS focuses on compliance, the quality of the data has yet to be extensively measured. Hence, the purpose of this project was to statistically analyze the data quality by studying the coding accuracy of International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes, Evaluation and Management (E&M) codes, and insurance indicator codes within the General Internal Medicine Clinic (GIMC) at WRAMC. Interventions to improve the data quality were identified, developed, and implemented during the course of this project. The sensitivities, positive predictive values (PPVs), and the kappa statistics determined from random samples collected before and after the interventions were compared using Chi square analysis (alpha = 05). The results showed an increase in overall non-adjusted ICD-9-CM coding rates from 60% to 67% sensitivity, 66% to 73% PPV, and kappa = .18 to .36, however, the differences were not significant. E&M coding improved from a poor sensitivity rate of 21% to significantly better rate of 55%. The study also identified a poor level of accuracy concerning the capture of insurance information (kappas = .18 and . 16) that conservatively indicated approximately $1.35 million dollars of missed third party collections within the past year. This study provides a model to improve the quality ADS data that may enhance the organization's ability to efficiently and effectively identify clinical process improvements, make sound resource allocation decisions, increase third party collections, and conduct outcomes research.14. SUBJECT TERMS AMBULATORY DATA SYSTEM; CODING ACCURACY positive predictive values (PPVs), and the kappa statistics determined from random samples collected before and after the interventions were compared using Chi square analysis (alpha = 05). The results showed an increase in overall non-adjusted ICD-9-CM coding rates from 60% to 67% sensitivity, 66% to 73% PPV, and kappa = .18 to .36, however, the differences were not significant. E&M coding improved from a poor sensitivity rate of 21% to significantly better rate of 55%. The study also identifi...

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Accuracy of Medicare Reimbursement for Cardiac Arrest

Hsia¹

1990

JAMA

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Miscoding of hospital discharges as acute myocardial infarction: Implications for surveillance programs aimed at elucidating trends in coronary artery disease

Cited by 46 publications

References 9 publications

Validity of coronary heart diseases and heart failure based on hospital discharge and mortality data in the Netherlands using the cardiovascular registry Maastricht cohort study

Validity of coronary heart diseases and heart failure based on hospital discharge and mortality data in the Netherlands using the cardiovascular registry Maastricht cohort study

Coding Accuracy of the Ambulatory Data System: A Study of Coding Accuracy Within the General Internal Medicine Clinic, Walter Reed Army Medical Center

Accuracy of Medicare Reimbursement for Cardiac Arrest

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