ICD-10 coding algorithms for defining comorbidities of acute myocardial infarction

[1]  Pat Armstrong,et al.  Health Care in Canada , 1994 .

[2]  H. Quan,et al.  Assessing record linkage between health care and Vital Statistics databases using deterministic methods , 2006, BMC Health Services Research.

[3]  P. Austin,et al.  Utilisation of coronary angiography after acute myocardial infarction in Ontario over time: have referral patterns changed? , 2002, Heart.

[4]  S. Sheps,et al.  Specific comorbidity risk adjustment was a better predictor of 5-year acute myocardial infarction mortality than general methods. , 2006, Journal of clinical epidemiology.

[5]  Frank E. Harrell,et al.  Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis , 2001 .

[6]  R. Walld,et al.  Physician visits, hospitalizations, and socioeconomic status: ambulatory care sensitive conditions in a canadian setting. , 2005, Health services research.

[7]  J. Goo,et al.  Receiver Operating Characteristic (ROC) Curve: Practical Review for Radiologists , 2004, Korean journal of radiology.

[8]  W. Browner Willy Sutton and the number needed to treat. , 2004, The American journal of medicine.

[9]  K. Lee,et al.  Prediction of 1-year survival after thrombolysis for acute myocardial infarction in the global utilization of streptokinase and TPA for occluded coronary arteries trial. , 2000, Circulation.

[10]  R. Deyo,et al.  ADAPTING A CLINICAL COMORBIDITY USE WITH ICD-g-CM ADMINISTRATIVE INDEX FOR DATABASES , 1992 .

[11]  E. Antman,et al.  Application of the TIMI risk score for ST-elevation MI in the National Registry of Myocardial Infarction 3. , 2001, JAMA.

[12]  H. Tunstall-Pedoe,et al.  Definitions for Acute Coronary Heart Disease in Epidemiology and Clinical Research Studies , 2003 .

[13]  H. Krumholz,et al.  Predicting one-year mortality among elderly survivors of hospitalization for an acute myocardial infarction: results from the Cooperative Cardiovascular Project. , 2001, Journal of the American College of Cardiology.

[14]  A. Laupacis,et al.  Age, risk-benefit trade-offs, and the projected effects of evidence-based therapies. , 2004, The American journal of medicine.

[15]  E W Steyerberg,et al.  Predictors of outcome in patients with acute coronary syndromes without persistent ST-segment elevation. Results from an international trial of 9461 patients. The PURSUIT Investigators. , 2000, Circulation.

[16]  Ewout W Steyerberg,et al.  Applicability of clinical prediction models in acute myocardial infarction: a comparison of traditional and empirical Bayes adjustment methods. , 2005, American heart journal.

[17]  R. Deyo,et al.  Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. , 1992, Journal of clinical epidemiology.

[18]  J. Knight,et al.  coding in , 2022 .

[19]  John F. Hurdle,et al.  Measuring diagnoses: ICD code accuracy. , 2005, Health services research.

[20]  W. Leslie,et al.  Prognostic utility of sestamibi lung uptake does not require adjustment for stress-related variables: A retrospective cohort study , 2006, BMC nuclear medicine.

[21]  J V Tu,et al.  Development and validation of the Ontario acute myocardial infarction mortality prediction rules. , 2001, Journal of the American College of Cardiology.

[22]  A. Zwisler,et al.  Hospital Variation in Mortality After First Acute Myocardial Infarction in Denmark From 1995 to 2002: Lower Short-Term and 1-Year Mortality in High-Volume and Specialized Hospitals , 2005, Medical care.

[23]  H. Quan,et al.  Coding Algorithms for Defining Comorbidities in ICD-9-CM and ICD-10 Administrative Data , 2005, Medical care.

[24]  E. Antman,et al.  Application of the TIMI risk score for ST-elevation MI in the National Registry of Myocardial Infarction 3. , 2001, JAMA.

[25]  Hude Quan,et al.  Comparison of the Elixhauser and Charlson/Deyo Methods of Comorbidity Measurement in Administrative Data , 2004, Medical care.

[26]  Laurel Jebamani,et al.  Data Quality in an Information-Rich Environment: Canada as an Example , 2005, Canadian Journal on Aging / La Revue canadienne du vieillissement.

[27]  P. Austin,et al.  Utilisation of coronary angiography after acute myocardial infarction in Ontario over time: have referral patterns changed? , 2002, Heart.

[28]  J. Jollis Measuring the effectiveness of medical care delivery. , 2001, Journal of the American College of Cardiology.

[29]  D. Alter,et al.  The impact of implantable cardiac defibrillators for primary prophylaxis in the community: baseline risk and clinically meaningful benefits. , 2006, Journal of evaluation in clinical practice.

[30]  H. Quan,et al.  Mortality in Acute Myocardial Infarction Patients Cared for by General Practice Physicians: Effect of Specialist Consultation , 2005 .

[31]  Mandeep Singh,et al.  Scores for Post–Myocardial Infarction Risk Stratification in the Community , 2002, Circulation.

[32]  H. Quan,et al.  Acute myocardial infarction in Alberta: temporal changes in outcomes, 1994 to 1999. , 2004, The Canadian journal of cardiology.

[33]  C. Torp‐Pedersen,et al.  Mortality after acute myocardial infarction according to income and education , 2006, Journal of Epidemiology and Community Health.

[34]  P. Duncan,et al.  Inaccuracy of the International Classification of Diseases (ICD-9-CM) in identifying the diagnosis of ischemic cerebrovascular disease , 1997, Neurology.

[35]  H. Quan,et al.  Validity of Procedure Codes in International Classification of Diseases, 9th revision, Clinical Modification Administrative Data , 2004, Medical care.

[36]  Michael D. Hill,et al.  Coding of Stroke and Stroke Risk Factors Using International Classification of Diseases, Revisions 9 and 10 , 2005, Stroke.

[37]  W. Leslie,et al.  Prognostic value of lung sestamibi uptake in myocardial perfusion imaging of patients with known or suspected coronary artery disease. , 2005, Journal of the American College of Cardiology.