Although attending physician assessments were given precedence over assessments by residents or other healthcare staff, reassignment of the ICD-9-CM codes from these sources only occurred if the attending physician documented that assessments by these sources was incorrect. Each hospital admission was assigned one primary diagnosis and up to 14 secondary diagnoses on the basis of the medical record including the radiology reports. the CT scans themselves were not re-read.Īs part of routine clinical care, ICD-9-CM codes were assigned by one of nine inpatient coders, who were not aware of the study at the time of code assignment. Only radiology reports were reviewed i.e. The data were then compared to ICD-9-CM codes to determine coding accuracy. Discrepancies were resolved by consensus. Transverse process and spinous process fractures were also noted. ![]() Reports were blinded for review, and reviewed by two independent observers to document the presence, chronicity, and level of cervical fracture(s). Patients without cervical spine CT or CTA reports were excluded. Patients were identified using ICD-9-CM codes in the ranges of 805.00–805.18, 806.00–806.18, and 839.00–839.18 from the hospital’s discharge database for the year 2006. We used ICD-9-CM discharge diagnosis codes to identify traumatic cervical spine fractures and trauma admissions to a Level I trauma center in a one-year period. Since researchers commonly use ICD-9-CM codes to select study subjects or to define injury severity, we had the following study questions: The accuracy of ICD-9-CM coding for cervical spine fractures has not previously been studied. Although overall accuracy of coding has trended toward improvement over the past three decades, it is clear that there is wide variability reported in the literature. al, reported a 46% sensitivity for correctly identifying patients with ICD-9-CM discharge diagnosis codes. For mild traumatic brain injury, Bazarian, et. Kokotailo and Hill found ICD-9-CM codes to have a 64 to 98% positive predictive value (PPV) for stroke type (ischemic, intracranial hemorrhage, subarachnoid hemorrhage, or transient ischemic attack). Faciszewski, et.al, studied hospital records and found that coding sensitivity for detecting spinal conditions in a subset of patients was 28 to 100%. In 1977, the Institute of Medicine reported a 60 to 64% agreement between Medicare billing codes and an independent chart review. ![]() Percentage of agreement, accuracy, positive predictive value, and sensitivity have all been used to report coding error. One difficulty with quantifying the validity of ICD-9-CM coding is the variety of reporting methods that have been used in previous studies. ![]() These types of error may decrease the reliability of data gathered via administrative databases using ICD-9-CM codes. al, errors can occur in coding because of lack of quality information in the medical record, lack of detailed documentation by healthcare providers, provider inexperience with particular diagnoses, variance within the medical record, level of coder training and experience, miscoding, unbundling (the assignment of codes for all separate parts of a diagnosis, instead of one code for the overall diagnosis), and upcoding (the erroneous assignment of codes for higher reimbursement over codes for lesser reimbursement). ĭespite these applications, the use of ICD-9-CM codes has limitations. In addition, a method of converting ICD-9-CM codes to an Abbreviated Injury Scale (AIS) score has been validated and used to define injury severity in administrative databases. These codes have previously been shown to correlate with patient outcome in trauma-registry databases. ![]() ICD-9-CM codes are increasingly being used for research in part because of their ready availability in administrative databases that contain data for large numbers of patients.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |