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Patient classification systems

Two basic types of patient classification systems exist: prototype and factor. A prototype evaluation system is considered both subjective and descriptive. It classifies patients into broad categories and uses these categories to predict patient care needs. The relative intensity measures (RIMs) system is a prototype system. This system classifies patient care needs based on their diagnosis-related group (DRG). The data are then fed to an electronic decision support system that integrates clinical and financial information. A factor evaluation system is considered more objective than a prototype evaluation system. It gives each task, thought process, and patient care activity a time or rating. These associations are then summed to determine the hours of direct care required, or they are weighted for each patient. Each intervention is given a name and a definition and is further specified to incorporate a list of all associated interventional activities. The list of interventions is comprehensive and applicable to inpatient, outpatient, home care, and long-term care patients. Typically, if these systems are used for staffing decisions, organizations use a combination. Some patient types with a single healthcare focus, such as maternal deliveries or outpatient surgical patients, would be appropriately classified with a prototype system. Patients with more complex care needs and a less predictable disease course, such as those with pneumonia or stroke, are more appropriately evaluated with a factor system.

 Numerous potential problems exist with patient classification systems. The issue most often raised by administrators relates to the questionable reliability and validity of the data collected through a self-reporting mechanism. Another concern with patient classification data relates to the inability of the organization to meet the prescribed staffing levels outlined by the patient classification system.

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Harper, K., & McCully, C. (2007). Acuity systems dialogue and patient classification system essentials. Nursing administration quarterly, 31(4), 284-299.

 

Hopfe, M., Stucki, G., Marshall, R., Twomey, C. D., Üstün, T. B., & Prodinger, B. (2015). Capturing patients’ needs in casemix: a systematic literature review on the value of adding functioning information in reimbursement systems. BMC health services research, 16(1), 40.

 

355 Words  1 Pages
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