Accuracy of the Exeter Hospitalizations-Office Visits-Medical Conditions-Extra Care-Social Concerns Index for...

Area of Science:

• Healthcare Informatics
• Clinical Assessment Tools
• Pediatric Chronic Care

Background:

• Identifying patients with complex chronic conditions (CCCs) is crucial for effective healthcare management.
• Administrative algorithms are commonly used but may not capture the full spectrum of patient complexity.
• A validated point-of-care instrument can improve the accuracy and efficiency of CCC identification.

Purpose of the Study:

• To evaluate the accuracy of the Hospitalizations-Office Visits-Medical Conditions-Extra Care-Social Concerns (HOMES) instrument.
• To compare the HOMES instrument's performance against established algorithms for identifying CCCs.
• To determine the utility of a point-of-care tool in a clinical setting for CCC identification.

Main Methods:

• The HOMES instrument was compared to Feudtner's CCCs classification system.
• Patients were categorized using administrative algorithms into no chronic conditions, non-complex chronic conditions, and CCCs.
• Optimal cut-point analysis was performed on a randomly selected sample to establish scoring thresholds for ≥1 and ≥2 CCCs.

Main Results:

• Optimal cut points for the HOMES instrument were identified as ≥7 for ≥1 CCC and ≥11 for ≥2 CCCs.
• The HOMES instrument showed significant odds ratios for identifying patients with CCCs (OR 19.1 for ≥1 CCC, OR 32.3 for ≥2 CCCs).
• Area under the curve (AUC) values were 0.76 for ≥1 CCC and 0.74 for ≥2 CCCs, with high sensitivity and specificity.

Conclusions:

• The HOMES instrument demonstrates accurate performance in identifying patients with complex chronic conditions.
• This point-of-care tool provides a reliable and efficient method for CCC identification in clinical practice.
• The HOMES instrument can aid healthcare providers in better managing patients with significant and multiple chronic health issues.