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Am J Manag Care. 2015 Oct 1;21(10):e576-82.

Clinician considerations when selecting high-risk patients for care management.

Author information

1
Mongan Institute for Health Policy, Massachusetts General Hospital, 50 Staniford St, 9th Fl, Boston, MA 02114. E-mail: cvogeli@mgh.harvard.edu.

Abstract

OBJECTIVES:

Hybrid approaches to case finding show promise as a method to increase the success of care management programs (CMPs). A large healthcare system implemented a hybrid approach in which clinicians review algorithm-generated lists of potential high-risk patients within their practice and select the patients most appropriate for the CMP. We sought to understand the criteria clinicians used when selecting patients.

STUDY DESIGN:

We conducted 20 semi-structured interviews with a convenience sample of primary care clinicians and their care managers from a diverse set of practices.

METHODS:

Two independent reviewers thematically coded interview responses through an iterative process.

RESULTS:

In addition to clinical need (eg, disease severity or multiple comorbidities), interviewees considered a number of nonclinical patient characteristics that they felt placed patients at risk for suboptimal healthcare utilization and poor adherence. These include patients' predisposing (eg, health literacy or navigation challenges, physical vulnerabilities, insight regarding their health) and enabling characteristics (eg, social and home environment, coping skills, financial resources). Interviewees also considered patients' existing linkages with the health system and whether other clinicians were already meeting a patient's care needs.

CONCLUSIONS:

In selecting patients for a CMP, clinicians considered patient characteristics that are not easily captured in standard clinical and administrative data. A hybrid approach to case finding concentrates clinician review on patients who meet standard clinical and healthcare utilization criteria, and allows clinicians to incorporate knowledge of patients' predisposing and enabling characteristics that are not readily maintained in clinical data.

PMID:
26619059
[Indexed for MEDLINE]
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