Development of an Ambulatory Clinical Pharmacy Prioritization Prediction Model for Patients With Diabetes

Area of Science:

• Pharmacology
• Clinical Pharmacy
• Diabetes Management

Background:

• Healthcare reform and primary care physician shortages necessitate efficient multidisciplinary collaboration.
• No prior studies have assessed factors predicting treatment success for patients referred to clinical pharmacists.

Purpose of the Study:

• To develop a prediction model for identifying diabetes patients most likely to benefit from pharmacy interventions.
• The model aims to improve patient selection for collaborative pharmacy care.

Main Methods:

• A retrospective, nested case-control study included adult patients with diabetes (hemoglobin A1C ≥9%) receiving collaborative pharmacy care.
• A multivariable logistic regression model was developed and validated to predict clinical success.
• Success was defined as a 2% A1C decrease or A1C <8% within one year.

Main Results:

• Of 544 patients, 44.7% achieved clinical success.
• Factors predicting success included cerebrovascular accident history and higher baseline A1C.
• Failure was associated with short-acting insulin use and more diabetes medication classes.

Conclusions:

• Patient baseline characteristics predict clinical success in collaborative pharmacy care.
• The developed prediction model demonstrated good performance and calibration.
• This model can enhance pharmacist efficiency in resource-constrained settings.