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Diagnosis Related Groups (DRGs) refer to a scheme for patient classification that seeks to establish a relationship between the type of patients treated within the hospital and the costs incurred by the hospital. DRGs enable hospitals to group patients in terms of similar aspects relating to demographics, diagnosis and therapeutic considerations. Groupings eliminate challenges relating to the determination and allocation of resources within a hospital. However, the incorporation of various measures ensures that DRGs remain mutually exclusive. Criteria such as diagnosis and age provide a basis for evaluation of similarities and differences between groups. There are varieties of groups concerning DRGs. These include the MSDRG, IRDRG, ANDRG and ARDRG. Since the early 1970s, DRGs have undergone numerous changes with countries redesigning DRGs models to address changing needs in healthcare. While Australia began with the HCFA DRG, the adoption of different coding scheme led to the creation of an Australian version of DRGs.

The grouping process in DRG assignment involves several procedures within the surgical, medical and other departments in healthcare. The first step entails the use of relevant tools to edit and analyze hospital records in accordance with stipulated assignment rules. The second step is the Major Diagnostic Category (MDC) assignment. During this procedure, the assignment of key diagnosis should correspond to a body system as expected in the diagnosis and procedure codes. This step helps to eliminate cases of inappropriate assignments due to the large number of MDCs and special case DRGs. The fourth step is the Pre-MDC processing which is vital concerning DRG assignment for high-cost patients. This type of patients introduces aspects that distort characteristics of a DRG established using the Principal Diagnosis approach. These include categories of liver transplant and ECMO. The fifth step is the Adjacent DRG assignment. An adjacent DRG constitutes of DRGs defined using a similar diagnosis or procedure code list. The variability in the levels of resource consumption between DRGs within an Adjacent DRG requires the partitioning of the relevant DRGs. The sixth step involves assignment concerning the Complication and Comorbidity Level (CCL) and the Patient Clinical Complexity Level (PCCL). The final stage is the DRG assignment.

The terms resource homogeneous and clinically meaningful define a competent DRG system. Description of the DRG system as clinically meaningful means that the diagnostic clusters related to the system should be acceptable to clinicians. On the other hand, a resource homogenous DRG system describes the aspect of average resources for every episode within the DRG system. These two concepts require DRG systems to consider vital aspects relating to consumption of resources. In this regard, the definition of DRG systems should incorporate diagnoses, classification procedures and other variables that introduce expenses concerning the treatment of a patient using a different procedure. This factor may introduce difficulties concerning the comparison of performance within diverse DRGs. Another consideration is aspect of the viability of DRG-based hospital payment for individual patients. Changes in practice patterns and costs due to factors such as technological innovation require the frequent updating of DRG systems for them to remain clinically meaningful and economically homogenous.  For a system to meet the two criteria stated above, it is important for the concerned parties to evaluate the type of patients to include in DRG systems. This is because some types of patients introduce challenges in defining either the economic homogeneity of a group or the clinical meaningfulness. The DRG assignment process should ensure the use of high-quality hospital information so that the development and updating of DRG systems ensures fair use of resources. Some crucial aspects of hospital information include the differentiation of costs for individual patients.

Casemix refers to an informal tool that classifies patient care using scientific methods. This classification ensures the grouping of patients with considerations for resource homogeneity and clinical meaningfulness. Casemix is a common aspect in the Australian healthcare sector and globally due to its usefulness in clinical management and regulation on funding. Casemix promotes easier access to patient records and thus enables comparison between facilities. In this regard, it is easy to monitor the output of hospitals and analyze crucial facilities in healthcare such as service delivery and resource utilization. Another important aspect of Casemix is its usefulness in the planning of facilities and workforce. Adequate facilities and workforce are crucial concerning satisfactory services. Casemix’s wide scope has presented it as an effective tool in determination of appropriate funding allocations. One of its components, Activity Based Funding, has received the worldwide acceptance as a tool for analysis of spending in healthcare centers.

The Australian Coding Benchmark Audit (ACBA) system checks the quality of code through re-coding of an indiscriminate sample of medical records. The accuracy associated with this method presents it as an appropriate means of identifying Coder error, which arises due to the variety of factors. Ten reporting categories relate to the errors made by a clinical coder. These include incorrect PDx coding, incorrect PDx selection and incorrect PDx sequencing, which relate to the principle-diagnosis code assignment errors. The other seven reporting categories relate to either the additional diagnosis code assignment or the procedure-code assignment errors. The additional diagnosis category includes incorrect additional diagnosis, incomplete diagnosis code and unsubstantiated or incorrect additional diagnosis code and character. Errors relating to the procedure category include incorrect procedure code, incomplete procedure code and unsubstantiated procedure code. Reports generated from an auditing process should highlight various errors during submission.

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