Understanding Antihypertensive Medication Use after Living Kidney Donation through Linked National Registry and Pharmacy Claims Data

Abstract

Background: Use of antihypertensive medications (AHM) after living kidney donation is not well described. Methods: We examined a database wherein national transplant registry data for 4,650 living kidney donors in 1987-2007 were linked to pharmacy claims from a US private health insurer (2000-2007 claims) to identify post-donation AHM fills. Cox regression with left- and right-censoring was used to estimate the frequencies and relative likelihood (adjusted hazards ratios, aHR) of post-donation AHM fills according to donor demographic traits. Medication possession ratio (MPRs), defined as (days of AHM dispensed)/(days observed), were also compared among donors and non-donor general beneficiaries. Results: Overall, 17.8% of the sample filled at least one AHM by 5 years post-donation. As compared with White living donors, African-Americans had 37% higher relative likelihood of any AHM use after donation (aHR 1.37, p < 0.0007), including significantly higher likelihoods of filling diuretics (aHR 2.25, p < 0.0001), ACEi/ARBs (aHR 1.46, p < 0.01), calcium channel blockers (aHR 1.56, p = 0.03), and vasodilators/other agents (aHR 2.17, p = 0.03). MPRs for any AHM and subcategories were lower among donors compared with age- and sex-matched non-donors. However, AHM MPRs rose in donors with multiple hypertension diagnoses, and prescription fill exposure for all AHM classes except diuretics was similar among donors and general non-donors with ≥3 hypertension diagnoses. Conclusions: While AHM requirements are lower after kidney donation than among unscreened general persons, racial variation in AHM use occurs in privately insured donors. Demonstration of pharmaceutical care needs of insured donors supports the need for long-term follow-up and healthcare access for all donors.

Gout after Living Kidney Donation: Correlations with Demographic Traits and Renal Complications

“…When describing health outcomes to potential living kidney donors, important perspectives include overall event frequencies after donation, within-donor comparisons across donor sub-groups such as race, comparisons of outcomes among donors vs. the general population, and when possible, comparisons of outcomes among donors vs. selected non-donor controls with similar baseline health (Table 3) (20, 38). Due to the rigorous evaluation that donors undergo as part of the selection process, living kidney donors are inherently healthier than the general population, contributing to improved outcomes usually seen in most studies comparing these two populations (e.g.…”

“…[20] b Data from the current study estimating the risk of gout diagnosis based on health care administrative database codes or pharmacy fill for a medication used to treat gout. c Data from Lam et al . estimating the risk of gout diagnosis based on health care administrative database codes.…”

Gender differences in use of prescription narcotic medications among living kidney donors

“…Lastly, our non-donor comparisons used general (rather than “healthy”) controls, as we lacked sufficient capture durations to allow for screening and selection of non-donors free of baseline co-morbidity. While general population comparisons do not address risk attributable to donation, as long as the type of comparison is explicit, general population experience can provide one relevant benchmark for framing post-donation outcomes (40,54). …”

“…Our study, therefore, provides insight into within-donor comparisons of narcotic use according to factors such as sex, as well as comparisons to the average general population as one commonly used benchmark (14,36,40,55). While we were unable to address the risk of narcotic medication use attributable to donor nephrectomy itself, we examined patterns of primary healthcare diagnoses in the 7 days preceding narcotic prescription fills, and found that the majority of healthcare visits were related to diagnoses such as spinal, joint, and soft tissue complaints.…”

The Impact of the mKidney mHealth System on Live Donor Follow-Up Compliance: Protocol for a Randomized Controlled Trial (Preprint)

“…The proposed research will identify barriers to technological innovations for LKD follow-up and engagement and design the mHealth system thus informing clinical care management and risk mitigation. This is particularly important for AfricanAmerican LKDs who have the highest ESRD risk attributable to donation as well as higher rates of postdonation HTN diagnoses [24].…”