RESUMO
Introduction: Genetic testing is increasingly accessible to patients with kidney diseases. Racial disparities in renal genetics evaluations have not been investigated. Methods: A cohort of patients evaluated by the Cleveland Clinic Renal Genetics Clinic (RGC) from January 2019 to March 2022 was analyzed. Results: Forty-eight Black patients, including 27 (56.3%) males, median age 34 (22-49) years and 232 White patients, including 76 (32.8%) males, median age 35 (21-53) years, were evaluated. Black patients were more likely to have end-stage kidney disease (ESKD) at the time of referral compared with White patients (23% vs. 7.3%, P = 0.004), more likely to be covered by Medicaid (46% vs. 15%, P < 0.001), and less likely to be covered by private insurance (35% vs. 66%, P < 0.001). Black patients were more likely to "no show" to scheduled appointment(s) or not submit specimens for genetic testing compared with White patients (24.1% vs. 6.7%, P = 0.0005). Genetic testing was completed in 35 Black patients. Of these, 37% had a positive result with 9 unique monogenic disorders and 1 chromosomal disorder diagnosed. Sixty-nine percent of Black patients with positive results received a new diagnosis or a change in diagnosis. Of these, 44% received a significant change in disease management. No differences in diagnostic yield and implications of management were noted between Black and White patients. Conclusion: Black patients equally benefit from renal genetics evaluation, but barriers to access exist. Steps must be taken to ensure equitable and early access for all patients. Further studies investigating specific interventions to improve access are needed.
RESUMO
BACKGROUND: We previously reported a new management variable, work rate, defined as work load due per hour, based on cumulative standard treatment times. We found that work rates were unachievable (ie, exceeded 1 hour of scheduled work per hour of available labor) for 75% of scheduled due times, despite presumed achievable average work load. OBJECTIVE: To determine the optimal strategy for creating work assignments based on work rate. METHODS: A focus group used root-cause analysis to identify ways to balance assignments based on work rate. We surveyed employees to assess their willingness to start earlier. We determined the ratio of scheduled to unscheduled work during a 12-month period. The scheduled work comprised administering small-volume nebulizer, metered-dose inhaler, noninvasive ventilation, and mechanical ventilation. The unscheduled work consisted of all other modalities. We also developed a spreadsheet model to assess the effect of shifting the start time on work-rate distribution in a representative 24-hour period. RESULTS: The focus group determined that starting treatments 1 hour earlier would help. Fifteen of the 24 clinicians surveyed responded, and 13 of the respondents were willing to start earlier. The scheduled work load averaged approximately 55% of the total work load, but there was high variability per assignment area (range 0-99%). The spreadsheet model showed that shifting treatment start times improved the distribution of work rate throughout the day, but did not guarantee that labor demand never outstrips supply. CONCLUSIONS: Our studies to date suggest that: basing assignments on average work load leads to periods of unachievable work rate, resulting in missed treatments and staff dissatisfaction. We have only limited ability to reduce peaks in work rate, but staggering treatment times is effective. Fair assignment of work should differentiate scheduled from unscheduled work.
