Risk Stratification in Primary Care: Value-Based Contributions of Provider Adjudication.
J Gen Intern Med
; 37(3): 601-607, 2022 02.
Article
in En
| MEDLINE
| ID: mdl-34100237
ABSTRACT
BACKGROUND:
In primary care risk stratification, automated algorithms do not consider the same factors as providers. The process of adjudication, in which providers review and adjust algorithm-derived risk scores, may improve the prediction of adverse outcomes.OBJECTIVE:
We assessed the patient factors that influenced provider adjudication behavior and evaluated the performance of an adjudicated risk model against a commercial algorithm.DESIGN:
(1) Structured interviews with primary care providers (PCP) and multivariable regression analysis and (2) receiver operating characteristic curves (ROC) with sensitivity analyses.PARTICIPANTS:
Primary care patients aged 18 years and older with an adjudicated risk score. APPROACH AND MAINMEASURES:
(1) Themes from structured interviews and discrete variables associated with provider adjudication behavior; (2) comparison of concordance statistics and sensitivities between risk models. KEYRESULTS:
47,940 patients were adjudicated by PCPs in 2018. Interviews revealed that, in adjudication, providers consider disease severity, presence of self-management skills, behavioral health, and whether a risk score is actionable. Provider up-scoring from the algorithmic risk score was significantly associated with patient male sex (OR 1.24, CI 1.15-1.34), age > 65 (OR 2.55, CI 2.24-2.91), Black race (1.26, CI 1.02-1.55), polypharmacy >10 medications (OR 4.87, CI 4.27-5.56), a positive depression screen (OR 1.57, CI 1.43-1.72), and hemoglobin A1c >9 (OR 1.89, CI 1.52-2.33). Overall, the adjudicated risk model performed better than the commercial algorithm for alloutcomes:
ED visits (c-statistic 0.689 vs. 0.684, p < 0.01), hospital admissions (c-statistic 0.663 vs. 0.649, p < 0.01), and death (c-statistic 0.753 vs. 0.721, p < 0.01). When limited to males or seniors, the adjudicated models displayed either improved or non-inferior performance compared to the commercial model.CONCLUSIONS:
Provider adjudication of risk stratification improves model performance because providers have a personal understanding of their patients and are able to apply their training to clinical decision-making.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Primary Health Care
/
Hospitalization
Type of study:
Etiology_studies
/
Prognostic_studies
/
Qualitative_research
/
Risk_factors_studies
Limits:
Adolescent
/
Humans
/
Male
Language:
En
Journal:
J Gen Intern Med
Journal subject:
MEDICINA INTERNA
Year:
2022
Type:
Article
Affiliation country:
United States