Agreement between medical record and ICD-10-AM coding of mental health, alcohol and drug conditions in trauma patients

Transcription

1 MONASH PUBLIC HEALTH & PREVENTIVE MEDICINE Agreement between medical record and ICD-10-AM coding of mental health, alcohol and drug conditions in trauma patients Tu Quan Nguyen AIPN Conference November 13, 2017

2 Background Injury is a major public health problem 1,2 and risk factors for injury include mental health, drug and alcohol conditions 3,4 Valid and reliable measurement of mental health, drug and alcohol conditions is important Epidemiological studies commonly rely on routinely collected ICD-10 data In some jurisdictions such as Australia, these data are primarily collected for activity-based funding 1 DALYs GBD, HALE Collaborators, 2015, 2 Haagsma et al, 2016, 3 Brattstrom et al, 2015, 4 O Donnell et al 2

3 Australian Coding Standards (ACS) and recent changes from 1 July, 2015 Due to the ACS, conditions are coded as associated conditions only if they impact on the hospital stay A review of the ACS aimed to address under-coding of chronic conditions Supplementary U conditions included mental and behavioural disorders To be assigned when it is documented that a condition is present during an episode of admitted care, but has not met the criteria for coding 3

4 Aims of the study To assess the level of agreement for mental health, drug and alcohol conditions coded from the medical record with ICD-10-AM diagnoses before and after the introduction of mandatory coding between intentional and unintentional injury patients in a severely injured patient population 4

5 Study design The Victorian State Trauma Registry collects information about major trauma patients in Victoria Random sample of 500 patients extracted from the registry Medical record review to assess the level of agreement between medical record documentation and ICD-10-AM coding before and after changes to the ACS 5

6 Major trauma An patients admitted to either The Alfred or Royal Melbourne Hospital (n=500) * Australian Coding Standards Random sample of patients from each hospital n=250 Before ACS* changes Admitted 1 July 2013 to 1 June, 2015 n=200 After ACS* changes Admitted 1 July December, 2015 n=50 Unintentional n=120 Intentional n=80 Unintentional n=30 Intentional n=20 6

7 Statistical methods Assess level of agreement between medical record coded comorbidities and ICD-10-AM coded conditions Cohen s kappa statistics Prevalence-adjusted bias-adjusted kappa (PABAK) and bootstrapping techniques for 95% CI 7

8 Study population n (%) Total n=500 Age (years) Median (IQR) 44 (27) Gender Charlson Comorbidity Index Injury Severity Score Male Female < > (74.8) 126 (25.2) 351 (70.2) 115 (23.0) 34 (6.8) 25 (5.0) 163 (32.6) 202 (40.4) 110 (22.0) Compensable status Compensable Non-compensable 180 (36.1) 318 (63.9) 8

9 Prevalence of mental health, drug and alcohol conditions in the medical record and ICD-10-AM data Condition Medical record n=500 Total n (%) ICD-10-AM data n=500 Total n (%) Any mental, drug or alcohol use conditions 225 (45.0) 119 (23.8) Any mental health condition 157 (32.0) 68 (13.6) Any drug use condition 97 (19.4) 21 (4.2) Alcohol use condition 104 (20.8) 23 (4.6) 9

10 Prevalence of mental health, drug and alcohol conditions in ICD-10-AM before and after coding changes Condition Pre-ACS n=400 Post-ACS n=100 n (%) n (%) Any mental health, drug or alcohol use condition 91 (22.8) 28 (28.0) Any mental health condition 49 (12.3) 19 (19.0) Any drug use condition 15 (3.8) 6 (6.0) Alcohol use condition 21 (5.3) 2 (2.0) 10

11 Level of agreement for all mental health, drug and alcohol use conditions Agreement (%) К coefficient (95% CI) PABAK (95% CI) All patients (0.37, 0.51) 0.46 (0.37, 0.54) Unintentional (0.19, 0.39) 0.52 (0.42, 0.62) Intentional (0.26, 0.49) 0.36 (0.23, 0.49) Pre-ACS (0.26, 0.45) 0.40 (0.30, 0.50) Post-ACS (0.48, 0.78) 0.46 (0.37, 0.54) Alfred Hospital (0.39, 0.58) 0.49 (0.37, 0.60) RMH (0.26, 0.48) 0.42 (0.31, 0.54) 11

12 Strengths and limitations of the study Strengths Good generalisability of sample to severely injured patients Consistent, standardised data collection from the medical records Limitations Not a formal validation study to assess whether the condition was truly present in a patient or not based on a gold standard diagnostic criteria 12

13 Concluding remarks Prevalence of all mental health, drug and alcohol condition higher in medical record data vs ICD-10-AM A large proportion of conditions are not coded in hospital administrative data, resulting in incomplete comorbidity capture There was little difference in the level of agreement after introduction of compulsory coding, and between hospitals Researchers and policymakers shoulder consider the limitations of these data 13