Best Way to Identify High-Risk Patients Focus of AJMC Study
PLAINSBORO, N.J. – The concept of the Patient-Centered Medical Home (PCMH) has received plenty of attention, but its foundation is built on understanding who will be the repeat customers. Finding the best yardstick to determine that is the subject of a study published this month by The American Journal of Managed Care
, led by Lindsey R. Haas, MPH. This retrospective cohort analysis involved patients who were treated by the Employee and Community Health Clinic of the Mayo Clinic in the area of Rochester, Minnesota. The study examined six methods of analyzing risk:
Adjusted Clinical Groups.
A method developed by Johns Hopkins involving the presence or absence of specific diagnoses, involves 93 specific categories.
A product of ACG, involves major conditions.
Hierarchical Condition Categories.
Used by the Centers for Medicaid and Medicare Services (CMS) 70 conditions that are assessed for a single risk score. The HCC categories predict the Elder Risk Assessment (ERA) Index, which incorporates age, gender, marital status and prior hospitalization days over the prior 2 years.
Chronic Condition Count.
A comorbidity count grouped in to six categories. Comorbidities are considered higher risk factors for costs.
Charlson Comorbidity Index.
Originally derived to classify comorbidities affecting 1-year mortality in cancer patients, sums weights for 17 specific conditions.
A care coordination patient enrollment process developed in the author’s practice based on combining MN Tiering and the ERA score as a hybrid model.
The authors note that for care coordination to be used effectively, it is important to identify which patients are likely to benefit from it. Prior to the study, there was little evidence exists on which risk-stratification method performed better in predicting hospitalizations, emergency department visits, 30-day readmissions, and high-cost users.
After the analysis, there appeared to be good concordance among the six different instruments in predicting hospitalization. ACG classification was generally better than other models in predicting healthcare utilization. Focusing care coordination efforts within the medical home on patients likely to benefit most requires appropriate identification of the highest-utilizing patients. Click here
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