Optimizing Prescribing for Individuals With Type 2 Diabetes and Chronic Kidney Disease Through the Development and Validation of Algorithms for Community Pharmacists.

Background: Diabetes is the leading cause of kidney disease and contributes to 38% of kidney failure requiring dialysis. A gap in detection and management of type 2 diabetes (T2D) in chronic kidney disease (CKD) exists in primary care. Community pharmacists are positioned to support those not able to access kidney care through traditional pathways. Algorithms were developed and validated to assist community pharmacists in identifying individuals with T2D in CKD and prescribing kidney-protective medications.

Objective: The objective was to develop and validate pharmacist algorithms to confirm T2D and CKD and to prescribe guideline-directed therapies for individuals with an estimated glomerular filtration rate (eGFR) of 30 to 60 mL/min/1.73 m² in community pharmacy primary care clinics in Nova Scotia.

Design: Lynn's method was utilized for algorithm development and content validation. Interview data were analyzed using qualitative descriptive analysis.

Setting: Pharmacists working in primary care clinic settings completed content and face algorithm validation, and virtual interviews were conducted following each round of validation.

Patients: The algorithms aim to support individuals with T2D and CKD in primary care by optimizing the resources and capacity of community pharmacists while ensuring safety and quality of care through a team-based approach. Patient partners were not part of algorithm development and validation.

Measurements: Content validity was computed using an item-level content validity index (I-CVI) and scale-level content validity index (S-CVI/Ave) per round. To measure face validity, percentages of those that "agreed" or "strongly agreed" to five statements were calculated.

Methods: Evidence- and expert-informed algorithms were developed and revised using Lynn's 3-step method (domain identification, item generation per domain, and instrument formation). Best evidence was collated with literature searches, and experts in nephrology, endocrinology, family medicine, nursing, and pharmacy revised the algorithms until there was consensus agreement on 4 final algorithms (detection of T2D and CKD, initiation/titration of angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, and initiation/management of sodium-glucose cotransporter-2 inhibitors and finerenone). Six community pharmacists per round for 3 rounds were needed to validate the algorithms. A 2-part questionnaire was utilized where pharmacists rated content and face validity using Likert scales. I-CVI and S-CVI/Ave per round and across 3 rounds were determined. Percentages were calculated for the rating level of agreement to 5 statements. Interviews were conducted and analyzed. Revisions were made to the algorithms between rounds.

Results: Eighteen community pharmacists (6 per round) participated with a mean ± standard deviation of 18 ±11 years of experience. The I-CVI of each item of the algorithms per round ranged from 0.83 to 1, which met the content validity threshold of 0.83 (P < .05) for at least 6 participants. The overall S-CVI/Ave across 3 rounds was 0.97. The overall percentage of participants across 3 rounds who agreed or strongly agreed to 5 face validity statements ranged from 83% to 100%, which was above the prespecified threshold for face validity consensus.

Limitations: The algorithms are intended for individuals with an eGFR of 30 to 60 mL/min/1.73m². While guideline medications are indicated below this threshold, this cut point was selected as these individuals should typically be referred to a nephrologist. There is a potential for delays in initiation of kidney-protective medications below this threshold while waiting to be seen by nephrology.

Conclusions: This is the first study to develop and validate algorithms for a new model of care that utilizes community pharmacists to identify and manage T2D and CKD in primary care. The algorithms achieved high content and face validity. Future implementation and evaluation will determine the effectiveness and safety of the algorithms.

Trial registration: Not registered.