Does clinical evidence support ICD-9-CM diagnosis coding of complications?

BACKGROUND Hospital discharge diagnoses, coded by use of the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM), increasingly determine reimbursement and support quality monitoring. Prior studies of coding validity have investigated whether coding guidelines were met, not whether the clinical condition was actually present. OBJECTIVE To determine whether clinical evidence in medical records confirms selected ICD-9-CM discharge diagnoses coded by hospitals. RESEARCH DESIGN AND SUBJECTS Retrospective record review of 485 randomly sampled 1994 hospitalizations of elderly Medicare beneficiaries in Califomia and Connecticut. MAIN OUTCOME MEASURE Proportion of patients with specified ICD-9-CM codes representing potential complications who had clinical evidence confirming the coded condition. RESULTS Clinical evidence supported most postoperative acute myocardial infarction diagnoses, but fewer than 60% of other diagnoses had confirmatory clinical evidence by explicit clinical criteria; 30% of medical and 19% of surgical patients lacked objective confirmatory evidence in the medical record. Across 11 surgical and 2 medical complications, objective clinical criteria or physicians' notes supported the coded diagnosis in >90% of patients for 2 complications, 80% to 90% of patients for 4 complications, 70% to <80% of patients for 5 complications, and <70% for 2 complications. For some complications (postoperative pneumonia, aspiration pneumonia, and hemorrhage or hematoma), a large fraction of patients had only a physician's note reporting the complication. CONCLUSIONS Our findings raise questions about whether the clinical conditions represented by ICD-9-CM codes used by the Complications Screening Program were in fact always present. These findings highlight concerns about the clinical validity of using ICD-9-CM codes for quality monitoring.

[1]  C M Ashton,et al.  International Classification of Diseases, 9th Revision, Clinical Modification codes in discharge abstracts are poor measures of complication occurrence in medical inpatients. , 1997, Medical care.

[2]  L I Iezzoni,et al.  Using administrative data to screen hospitals for high complication rates. , 1994, Inquiry : a journal of medical care organization, provision and financing.

[3]  J P Kassirer,et al.  The use and abuse of practice profiles. , 1994, The New England journal of medicine.

[4]  L. Iezzoni,et al.  Widespread assessment of risk-adjusted outcomes: lessons from local initiatives. , 1994, The Joint Commission journal on quality improvement.

[5]  L. Iezzoni,et al.  The role of severity information in health policy debates: a survey of state and regional concerns. , 1991, Inquiry : a journal of medical care organization, provision and financing.

[6]  D W Simborg,et al.  DRG creep: a new hospital-acquired disease. , 1981, The New England journal of medicine.

[7]  L. Iezzoni Assessing Quality Using Administrative Data , 1997, Annals of Internal Medicine.

[8]  L I Iezzoni,et al.  Identifying Complications of Care Using Administrative Data , 1994, Medical care.

[9]  L. McMahon,et al.  Can Medicare prospective payment survive the ICD-9-CM disease classification system? , 1986, Annals of internal medicine.

[10]  N. Wintfeld,et al.  Report cards on cardiac surgeons. Assessing New York State's approach. , 1995, The New England journal of medicine.

[11]  J. Jollis,et al.  Pennsylvania's Focus on Heart Attack--grading the scorecard. , 1998, The New England journal of medicine.

[12]  E. Hannan,et al.  Using Medicare claims data to assess provider quality for CABG surgery: does it work well enough? , 1997, Health services research.

[13]  L I Iezzoni,et al.  Does the Complications Screening Program flag cases with process of care problems? Using explicit criteria to judge processes. , 1999, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[14]  E L Hannan,et al.  Clinical Versus Administrative Data Bases for CABG Surgery: Does it Matter , 1992, Medical care.

[15]  T. Moloney,et al.  The consumer movement takes hold in medical care. , 1991, Health affairs.

[16]  L. Muhlbaier,et al.  Using Medicare Claims for Outcomes Research , 1994, Medical care.

[17]  B. Vladeċk Medicare hospital payment by diagnosis-related groups. , 1984, Annals of internal medicine.

[18]  Hsia Dc,et al.  Accuracy of Diagnostic Coding for Medicare Patients under the Prospective-Payment System , 1988 .

[19]  E. Fisher,et al.  The accuracy of Medicare's hospital claims data: progress has been made, but problems remain. , 1992, American journal of public health.

[20]  D. Mark,et al.  Bias in the coding of hospital discharge data and its implications for quality assessment. , 1994, Medical care.

[21]  D. K. Williams,et al.  Assessing hospital-associated deaths from discharge data. The role of length of stay and comorbidities. , 1988, JAMA.

[22]  A. Epstein,et al.  Performance reports on quality--prototypes, problems, and prospects. , 1995, The New England journal of medicine.

[23]  W. M. Krushat,et al.  Medicare reimbursement accuracy under the prospective payment system, 1985 to 1988. , 1992, JAMA.

[24]  L I Iezzoni,et al.  Identification of in-hospital complications from claims data. Is it valid? , 2000, Medical care.

[25]  L I Iezzoni,et al.  A method for screening the quality of hospital care using administrative data: preliminary validation results. , 1992, QRB. Quality review bulletin.

[26]  M. Stern,et al.  Miscoding of hospital discharges as acute myocardial infarction: implications for surveillance programs aimed at elucidating trends in coronary artery disease. , 1984, The American journal of cardiology.

[27]  L I Iezzoni,et al.  Coding of acute myocardial infarction. Clinical and policy implications. , 1988, Annals of internal medicine.