Case Mix Index: A Common Healthcare Performance Benchmark - Essay Sample

Introduction

Healthcare organizations use a vast number of national benchmarks to better the overall performance. One of the most common benchmarks used within the hospital is Case-Mix Index. Case Mix Index (CMI) refers to the relative average Diagnosis-related group (DRG) hospital’s inpatient discharge (Fronczek et al., 2019). Case Mix Index is obtained by adding the individual discharge weight of Medical Severity-Diagnosis Related Group (MS-DRG) and then dividing by overall discharge count. Case Mix diversity is essential in reflecting aspects such as resource, clinical complexity, and diversity needs of the patients within a hospital. Instances of higher CMI shows resource-intensive and complex caseload (Silver et al. 2019). The weight applied using MS-DRG applies to overall discharges disregarding the payer. The weights are, however, designed for the Medicare population. This paper aims to establish how the healthcare organization currently evaluates its operations to determine whether they have met or exceeded the requirements.

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The current healthcare systems handle the Diagnosis-Related Group (DRG) coding system and evaluate the Case Mix Index (CMI) to be the most dominant inpatient billing and reimbursement standard. It is used as an indicator of all healthcare systems disease severity during instances when patient-level data are unavailable. Patients are assigned to a DRG only after they are discharged. It is also awarded based on the diagnosis and procedure codes (Johnson, 2019). The application of the Case Mix Index relies on the presence of complications, gender, age, and discharge status of a patient. CMS payments are made concerning the weight, which is related to each DRG.

The importance of CMI is to assist in calculating all the clinical complexities and total resource consumption of the patient population in a hospital. It is because it represents the average DRG weight for a hospital. The DRG weight is thus calculated as the sum of the weights of an entire hospital’s DRG divided by the total number of patients admitted during a fixed period. Our facility acknowledges that the target is achieved if the average DRG weight is met during the time frame of interest.

References

Fronczek, J., Polok, K., Devereaux, P. J., Górka, J., Archbold, R. A., Biccard, B., ... & Szczeklik, W. (2019). External validation of the revised cardiac risk index and national surgical quality improvement program myocardial infarction and cardiac arrest calculator in noncardiac vascular surgery. British journal of anesthesia, 123(4), 421-429.

Johnson, C. E., Peralta, J., Lawrence, L., Issai, A., Weaver, F. A., & Ham, S. W. (2019). Focused resident education and engagement in quality improvement enhances documentation, shortens hospital length of stay, and creates a culture of continuous improvement. Journal of surgical education, 76(3), 771-778. https://www.sciencedirect.com/science/article/pii/S1931720418301909

Silver, S. A., Alaryni, A., Alghamdi, A., Digby, G., Wald, R., & Iliescu, E. (2019). Routine laboratory testing every 4 versus every 6 weeks for patients on maintenance hemodialysis: a quality improvement project. American Journal of Kidney Diseases, 73(4), 496-503. https://www.sciencedirect.com/science/article/pii/S0272638618310898