Identifying rising risk patients can reduce costs for healthcare organizations

Identifying future high-risk, or rising risk, patients can help healthcare organizations reduce population health costs through early intervention. In this paper, Milliman consultants Ksenia Whittal and Abigail Caldwell examine predictive models to determine whether an enhanced model can better identify individuals with rising risk relative to traditional prospective risk adjustment models. The authors also assess the capability of these models to select members whose costs will increase in the future year.

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  1. Please be aware that the Social Determinants of Health are currently not in ‘Big Data’ much. A big reason is that previously only MD/NP/PA’s notes could be used for medical coding purposes. That rule changed earlier this year. (see below). Please encourage those involved with EMR design to incorporate this into modules for Case managers, Social Workers, SBIRT workers, Community Service Workers and others so that we can more accurately capture this information to help in better defining risk.

    Per the Coding Clinic Editorial Advisory Board. First Quarter 2018 issue of Coding Clinic:

    Question:

    Is it appropriate to utilize nonphysician documentation to assign codes that provide information on social determinants of health? For example, codes from categories Z55-Z65, Persons with potential health hazards related to socioeconomic and psychosocial circumstances, provide important information that is typically only found in nurses or social worker documentation.

    Answer:

    Categories Z55-Z65, Persons with potential health hazards related to socioeconomic and psychosocial circumstances, represent social information, rather than medical diagnoses. As such, it is acceptable to report these codes based on information documented by other clinicians involved in the care of the patient.

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