Agreement between medical record and administrative coding of common comorbidities in orthopaedic trauma patients

Association between type 2 diabetes and long-term outcomes in middle-aged and older trauma patients

“…Clinical coders are employed by the hospital to code conditions within the medical record that are a part of the patient’s current health status, including chronic comorbidities 22 . There is excellent agreement between medical records and International Classification of Diseases 10th revision Australian Modification coding data for T2D in trauma patients 23 …”

“…22 There is excellent agreement between medical records and International Classification of Diseases 10th revision Australian Modification coding data for T2D in trauma patients. 23 Information extracted from the registry included participants' demographics (age, sex, Accessibility/Remoteness Index of Australia (ARIA), Index of Relative Socioeconomic Advantage and Disadvantage (IRSAD), working/studying status prior to injury and level of education), premorbid condition (preinjury disability, Charlson Comorbidity Index [CCI]), details of the injury (type, cause, place, intent, and ISS), trauma service level (major trauma center, metropolitan trauma center, regional trauma center, and other), in-hospital outcomes (ICU admission, death during hospital admission, discharge destination), and 24-month patient-reported outcomes (three-level, EuroQol-five dimensions (EQ-5D-3L) domains, Glasgow Outcome Scale Extended (GOSE) score, return to work/study and self-rated disability). Data for preinjury disability, education, and work status are collected via telephone follow-up up to 24 months postinjury.…”

Detecting non-alcoholic fatty liver disease and risk factors in health databases: accuracy and limitations of the ICD-10-AM

“…These findings support a recent study from Australia that examined the agreement between medical records and ICD-10-AM comorbidity codes in trauma patients. 19 The authors found that, based on clinician documentation, the prevalence of obesity was only 9.3% (compared with the Australian population prevalence of 31% 9 ), with an even lower prevalence based on administrative data. 19 Multiple previous studies have also shown that the completeness of ICD diagnosis coding for overweight/obesity is low compared with its prevalence in medical records based on clinical weight/height or BMI measurements.…”

“…19 The authors found that, based on clinician documentation, the prevalence of obesity was only 9.3% (compared with the Australian population prevalence of 31% 9 ), with an even lower prevalence based on administrative data. 19 Multiple previous studies have also shown that the completeness of ICD diagnosis coding for overweight/obesity is low compared with its prevalence in medical records based on clinical weight/height or BMI measurements. [20][21][22][23] Although it is a potential risk factor for many diseases, obesity is not usually the primary cause of admission and may therefore be overlooked by clinicians when registering diagnoses.…”

“…In our patient cohort, there was almost perfect concordance between administrative codes and documentation Open access of T2DM in medical records. Recent studies examining hospital data from a trauma centre 19 and cancer outcomes registry 24 in Australia have also reported 'excellent' and 'substantial' agreement, respectively, between administrative data and medical records for T2DM. This high concordance is likely a consequence of the mandatory requirement to code T2DM when it is documented, as well as the need to monitor and treat this condition during the hospital admission.…”