Validity of Myocardial Infarction Diagnoses in Administrative Databases: A Systematic Review

Background Though administrative databases are increasingly being used for research related to myocardial infarction (MI), the validity of MI diagnoses in these databases has never been synthesized on a large scale. Objective To conduct the first systematic review of studies reporting on the validity of diagnostic codes for identifying MI in administrative data. Methods MEDLINE and EMBASE were searched (inception to November 2010) for studies: (a) Using administrative data to identify MI; or (b) Evaluating the validity of MI codes in administrative data; and (c) Reporting validation statistics (sensitivity, specificity, positive predictive value (PPV), negative predictive value, or Kappa scores) for MI, or data sufficient for their calculation. Additonal articles were located by handsearch (up to February 2011) of original papers. Data were extracted by two independent reviewers; article quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. Results Thirty studies published from 1984–2010 were included; most assessed codes from the International Classification of Diseases (ICD)-9th revision. Sensitivity and specificity of hospitalization data for identifying MI in most [≥50%] studies was ≥86%, and PPV in most studies was ≥93%. The PPV was higher in the more-recent studies, and lower when criteria that do not incorporate cardiac troponin levels (such as the MONICA) were employed as the gold standard. MI as a cause-of-death on death certificates also demonstrated lower accuracy, with maximum PPV of 60% (for definite MI). Conclusions Hospitalization data has higher validity and hence can be used to identify MI, but the accuracy of MI as a cause-of-death on death certificates is suboptimal, and more studies are needed on the validity of ICD-10 codes. When using administrative data for research purposes, authors should recognize these factors and avoid using vital statistics data if hospitalization data is not available to confirm deaths from MI.

[1]  Hugo A. Katus,et al.  Myocardial infarction redefined--a consensus document of The Joint European Society of Cardiology/American College of Cardiology Committee for the redefinition of myocardial infarction. , 2000, European heart journal.

[2]  A. Folsom,et al.  Trends in the sensitivity, positive predictive value, false-positive rate, and comparability ratio of hospital discharge diagnosis codes for acute myocardial infarction in four US communities, 1987-2000. , 2004, American journal of epidemiology.

[3]  L. Lix,et al.  Surveillance of systemic autoimmune rheumatic diseases using administrative data , 2011, Rheumatology International.

[4]  Peter A Kavsak,et al.  The impact of the ESC/ACC redefinition of myocardial infarction and new sensitive troponin assays on the frequency of acute myocardial infarction. , 2006, American heart journal.

[5]  R. Schlienger,et al.  Effect of rheumatoid arthritis or systemic lupus erythematosus on the risk of first-time acute myocardial infarction. , 2004, The American journal of cardiology.

[6]  Trends in incidence and mortality from acute myocardial infarction in Nova Scotia and Saskatchewan 1974 to 1985. The Nova Scotia-Saskatchewan Cardiovascular Disease Epidemiology Group. , 1992, The Canadian journal of cardiology.

[7]  J. Ranstam,et al.  Validity of register data on acute myocardial infarction and acute stroke , 1993, Scandinavian journal of social medicine.

[8]  T. Meade Cardiovascular Disease: Epidemiology , 2001 .

[9]  A. Maguire,et al.  Use of oral corticosteroids and the risk of acute myocardial infarction. , 2007, Atherosclerosis.

[10]  D. Lacaille,et al.  Systematic Review of Validation Studies of the Use of Administrative Data to Identify Serious Infections , 2013, Arthritis care & research.

[11]  L. Lix,et al.  The validity of administrative data to identify hip fractures is high--a systematic review. , 2013, Journal of clinical epidemiology.

[12]  Lisa Lix,et al.  Consensus Statements for the Use of Administrative Health Data in Rheumatic Disease Research and Surveillance , 2013, The Journal of Rheumatology.

[13]  S. Soedamah-Muthu,et al.  High risk of cardiovascular disease in patients with type 1 diabetes in the U.K.: a cohort study using the general practice research database. , 2006, Diabetes care.

[14]  S. Gabriel,et al.  Do cardiovascular risk factors confer the same risk for cardiovascular outcomes in rheumatoid arthritis patients as in non-rheumatoid arthritis patients? , 2007, Annals of the rheumatic diseases.

[15]  E. Ingelsson,et al.  The validity of a diagnosis of heart failure in a hospital discharge register , 2005, European journal of heart failure.

[16]  D. Labarthe,et al.  An assessment of the validity of ICD Code 410 to identify hospital admissions for myocardial infarction: The Corpus Christi Heart Project. , 1996, International journal of epidemiology.

[17]  J. Virtamo,et al.  Validity of diagnoses of major coronary events in national registers of hospital diagnoses and deaths in Finland , 1997, European Journal of Epidemiology.

[18]  J. Boer,et al.  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 , 2009, European Journal of Epidemiology.

[19]  The World Health Organization MONICA Project (monitoring trends and determinants in cardiovascular disease): a major international collaboration. WHO MONICA Project Principal Investigators. , 1988, Journal of clinical epidemiology.

[20]  L. See,et al.  Risk of myocardial infarction among patients with gout: a nationwide population-based study. , 2013, Rheumatology.

[21]  Estimation of the incidence of acute myocardial infarction using record linkage: a feasibility study in Nova Scotia and Saskatchewan. Nova Scotia-Saskatchewan Cardiovascular Disease Epidemiology Group. , 1989, Canadian journal of public health = Revue canadienne de sante publique.

[22]  C. Kooperberg,et al.  Comparison of self-report, hospital discharge codes, and adjudication of cardiovascular events in the Women's Health Initiative. , 2004, American journal of epidemiology.

[23]  B. Yawn,et al.  Trends in Incidence, Severity, and Outcome of Hospitalized Myocardial Infarction , 2010, Circulation.

[24]  H. Guess,et al.  All-cause mortality and vascular events among patients with rheumatoid arthritis, osteoarthritis, or no arthritis in the UK General Practice Research Database. , 2003, The Journal of rheumatology.

[25]  M. Kornitzer,et al.  The World Health Organization MONICA Project (Monitoring trends and determinants in cardiovascular disease): A major international Collaboration , 1988 .

[26]  A. Dobson,et al.  The accuracy of hospital records and death certificates for acute myocardial infarction. , 1995, Australian and New Zealand journal of medicine.

[27]  V. Salomaa,et al.  The validity of the routine mortality statistics on coronary heart disease in Finland: comparison with the FINMONICA MI register data for the years 1983-1992. Finnish multinational MONItoring of trends and determinants in CArdiovascular disease. , 1999, Journal of clinical epidemiology.

[28]  R. Carney,et al.  Anxiety disorders increase risk for incident myocardial infarction in depressed and nondepressed Veterans Administration patients. , 2010, American heart journal.

[29]  C. Pineau,et al.  A population-based assessment of systemic lupus erythematosus incidence and prevalence--results and implications of using administrative data for epidemiological studies. , 2007, Rheumatology.

[30]  P. Bossuyt,et al.  BMC Medical Research Methodology , 2002 .

[31]  H. Tunstall-Pedoe,et al.  The World Health Organization MONICA Project (monitoring trends and determinants in cardiovascular disease): a major international collaboration , 1988 .

[32]  R. Beaglehole,et al.  Validation of coronary heart disease hospital discharge data. , 1987, Australian and New Zealand journal of medicine.

[33]  Peter C Austin,et al.  A multicenter study of the coding accuracy of hospital discharge administrative data for patients admitted to cardiac care units in Ontario. , 2002, American heart journal.

[34]  M. Kornitzer,et al.  Misclassification of coronary heart disease in mortality statistics. Evidence from the WHO-MONICA Ghent-Charleroi Study in Belgium. , 1998, Journal of Epidemiology and Community Health.

[35]  D. Balzi,et al.  Hospital discharge data for assessing myocardial infarction events and trends, and effects of diagnosis validation according to MONICA and AHA criteria , 2010, Journal of Epidemiology & Community Health.

[36]  Hude Quan,et al.  Measuring agreement of administrative data with chart data using prevalence unadjusted and adjusted kappa , 2009, BMC medical research methodology.

[37]  Principal Investigators,et al.  The World Health Organization MONICA project (monitoring trends and determinants in cardiovascular disease): a major international collabaration , 1988 .

[38]  J. Murabito,et al.  Long-Term Trends in Myocardial Infarction Incidence and Case Fatality in the National Heart, Lung, and Blood Institute's Framingham Heart Study , 2009, Circulation.

[39]  Alastair Gray,et al.  Economic burden of cardiovascular diseases in the enlarged European Union. , 2006, European heart journal.

[40]  T. Marandi,et al.  Diagnosis and treatment of acute myocardial infarction in tertiary and secondary care hospitals in Estonia , 2006, Scandinavian journal of public health.

[41]  Sebastian Schneeweiss,et al.  Accuracy of Medicare claims-based diagnosis of acute myocardial infarction: estimating positive predictive value on the basis of review of hospital records. , 2004, American heart journal.

[42]  C D Naylor,et al.  False-positive coding for acute myocardial infarction on hospital discharge records: chart audit results from a tertiary centre. , 1990, The Canadian journal of cardiology.

[43]  J. Spinelli,et al.  Co-morbidity data in outcomes research: are clinical data derived from administrative databases a reliable alternative to chart review? , 2000, Journal of clinical epidemiology.

[44]  Jacek A Kopec,et al.  Trends in physician-diagnosed osteoarthritis incidence in an administrative database in British Columbia, Canada, 1996-1997 through 2003-2004. , 2008, Arthritis and rheumatism.

[45]  V. Salomaa,et al.  The validity of the Finnish Hospital Discharge Register and Causes of Death Register data on coronary heart disease , 2005, European journal of cardiovascular prevention and rehabilitation : official journal of the European Society of Cardiology, Working Groups on Epidemiology & Prevention and Cardiac Rehabilitation and Exercise Physiology.

[46]  B. Hemmelgarn,et al.  Prevalence of autoimmune inflammatory myopathy in the first nations population of Alberta, Canada , 2012, Arthritis care & research.

[47]  B. Hemmelgarn,et al.  Prevalence of systemic lupus erythematosus and systemic sclerosis in the First Nations population of Alberta, Canada , 2012, Arthritis care & research.

[48]  K. Thygesen,et al.  Erratum: Myocardial infarction redefined - A consensus document of the Joint European Society of Cardiology/American College of Cardiology Committee for the Redefinition of Myocardial Infarction (Journal of the American College of Cardiology (2000) 36 (959-969)) , 2001 .

[49]  V. Salomaa,et al.  The validity of hospital discharge register data on coronary heart disease in Finland , 1997, European Journal of Epidemiology.

[50]  N S Rawson,et al.  Validity of the recording of ischaemic heart disease and chronic obstructive pulmonary disease in the Saskatchewan health care datafiles. , 1995, Statistics in medicine.

[51]  R. Beaglehole,et al.  Validation of coronary heart disease death certificate diagnoses. , 1988, The New Zealand medical journal.

[52]  U. Keil,et al.  Case finding, data quality aspects and comparability of myocardial infarction registers: results of a south German register study. , 1991, Journal of clinical epidemiology.

[53]  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.

[54]  J. Kopec,et al.  Independent impact of gout on the risk of acute myocardial infarction among elderly women: a population-based study , 2010, Annals of the rheumatic diseases.

[55]  Maarten L. Simoons,et al.  The third universal definition of myocardial infarction , 2013 .

[56]  Jordi Castellsague,et al.  Positive predictive value of ICD‐9 codes 410 and 411 in the identification of cases of acute coronary syndromes in the Saskatchewan Hospital automated database , 2008, Pharmacoepidemiology and drug safety.

[57]  S. Normand,et al.  Positive predictive value of the diagnosis of acute myocardial infarction in an administrative database , 1999, Journal of General Internal Medicine.

[58]  J. Ornato,et al.  Impact of the troponin standard on the prevalence of acute myocardial infarction. , 2003, American heart journal.

[59]  Karen Tu,et al.  Systematic Review and Critical Appraisal of Validation Studies to Identify Rheumatic Diseases in Health Administrative Databases , 2013, Arthritis care & research.

[60]  L. Melton,et al.  Determining perioperative complications associated with vaginal hysterectomy: code classification versus chart review. , 2009, Journal of the American College of Surgeons.

[61]  M Rosén,et al.  A national record linkage to study acute myocardial infarction incidence and case fatality in Sweden. , 2001, International journal of epidemiology.

[62]  Sebastian Schneeweiss,et al.  Validation of claims‐based diagnostic and procedure codes for cardiovascular and gastrointestinal serious adverse events in a commercially‐insured population , 2010, Pharmacoepidemiology and drug safety.

[63]  George A Mensah,et al.  An overview of cardiovascular disease burden in the United States. , 2007, Health affairs.

[64]  V. Salomaa,et al.  A new definition for myocardial infarction: what difference does it make? , 2005, European heart journal.

[65]  J. Kopec,et al.  Risk of Cardiovascular Disease in Patients With Osteoarthritis: A Prospective Longitudinal Study , 2013, Arthritis care & research.

[66]  J. Tuomilehto,et al.  Diagnosis of acute myocardial infarction by MONICA and FINMONICA diagnostic criteria in comparison with hospital discharge diagnosis. , 1994, Journal of clinical epidemiology.

[67]  A R Levy,et al.  Coding accuracy of hospital discharge data for elderly survivors of myocardial infarction. , 1999, The Canadian journal of cardiology.

[68]  L I Iezzoni,et al.  Does clinical evidence support ICD-9-CM diagnosis coding of complications? , 2000, Medical care.

[69]  V. Sundararajan,et al.  Quality of Diagnosis and Procedure Coding in ICD-10 Administrative Data , 2006, Medical care.

[70]  J. Avorn,et al.  Immunosuppressive medications and hospitalization for cardiovascular events in patients with rheumatoid arthritis. , 2006, Arthritis and rheumatism.

[71]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[72]  M. Kramer Life-Table (Survival) Analysis , 1988 .