Multiple comorbid conditions and healthcare resource utilization among adult patients with hyperkalemia: A retrospective observational cohort study using association rule mining.

Objectives: To estimate the prevalence of specific comorbid conditions (CCs) and multiple comorbid conditions (MCCs) among adult patients with hyperkalemia and examine the associations between MCCs and healthcare resource utilization (HRU) and costs. Methods: This retrospective observational cohort study was conducted using a large administrative claims database. We identified patients with hyperkalemia (ICD-10-CM: E87.5; or serum potassium >5.0 mEq/L; or NDC codes for either patiromer or sodium polystyrene sulfonate) during the study period (1/1/2016-6/30/2019). The earliest service/claim date with evidence of hyperkalemia was identified as index date. Qualified patients had ≥12 months of enrolment before and after index date, ≥18 years of age. Comorbid conditions were assessed using all data within 12 months prior to the index date. Healthcare resource utilization and costs were estimated using all data within 12 months after the index date. Association rule mining was applied to identify MCCs. Generalized linear models were used to examine the associations between MCCs and HRU and costs. Results: Of 22,154 patients with hyperkalemia, 94% had ≥3 CCs. The most common individual CCs were chronic kidney disease (CKD, 85%), hypertension (HTN, 83%), hyperlipidemia (HLD, 81%), and diabetes mellitus (DM, 47%). The most common dyad combination of CCs was CKD+HTN (71%). The most common triad combination was CKD+HTN+HLD (62%). The most common quartet combination was CKD+HTN+HLD+DM (36%). The increased number of CCs were significantly associated with increased ED visits, length of hospital stays, and total healthcare costs (all p-value < 0.0001). Conclusions: MCCs are very prevalent among patients with hyperkalemia and are strongly associated with HRU and costs.

Healthcare utilization and expenditures associated with hyperkalemia management: a retrospective study of Medicare Advantage patients.

AIMS: This study aimed to estimate the association of patiromer exposure vs. no potassium (K+) binder (NoKb) exposure with healthcare utilization and expenditures among a cohort of Medicare Advantage patients with hyperkalemia (HK). METHODS: Using Optum's Clinformatics Data Mart (study period 2016-2019), the authors assessed propensity score-matched patients (1:1) with a serum K+ concentration ≥5.0 mmol/L and an HK diagnosis that were exposed to patiromer or NoKb on baseline characteristics. The following outcomes were compared: (1) inpatient/emergency department (ED) encounters, (2) inpatient costs greater than or equal to mean Medicare Advantage inpatient cost (i.e. $14,900), and (3) the relative healthcare spending rate. Logistic regression and zero-inflated negative binomial regression were used to analyze the outcomes. RESULTS: The study cohort included 1,539 patiromer and NoKb matched pairs. Baseline characteristics were (patiromer/NoKb): age 74/75 years; female 42/40%; serum K+ 5.6/5.6 mmol/L; eGFR rate 36/36 mL/min/1.73 m2; low-income subsidy 42/41%, chronic kidney disease 96/96%; end-stage renal disease 12/12%; and congestive heart failure 37/36%. A total of 253 matched pairs (506 patients) remained uncensored and were analyzed at 6 months. Inpatient/ED encounters were observed for 25% (patiromer) and 37% (NoKb) (odds ratio [OR] 0.58, 95% confidence interval [CI]: 0.38-0.89). The relative odds of having inpatient costs ≥$14,900 were ∼50% less for patients exposed to patiromer vs. NoKb (OR [95% CI]: 0.47 [0.25-0.89]). The relative total healthcare spending rate (including inpatient, outpatient, ED, and pharmacy costs) was 19% less for patients exposed to patiromer vs. NoKb (spending rate ratio [95% CI]: 0.81 [0.67-0.98]). CONCLUSION AND LIMITATIONS: Among Medicare Advantage patients with HK, patiromer exposure (vs. NoKb) was associated with statistically significant reductions in the proportion with inpatient/ED encounters, inpatient costs ≥$14,900, and lower total healthcare spending. Further research, with larger sample size, is warranted to fully validate these findings.

Hyperkalemia Management in Older Adults With Diabetic Kidney Disease Receiving Renin-Angiotensin-Aldosterone System Inhibitors: A Post Hoc Analysis of the AMETHYST-DN Clinical Trial.

RATIONALE & OBJECTIVE: Older people are more likely to have reduced kidney function and multiple comorbid conditions predisposing them to hyperkalemia. This post hoc subgroup analysis aimed to evaluate the effectiveness of patiromer, a sodium-free nonabsorbed polymer, in lowering serum potassium levels in older patients receiving a renin-angiotensin-aldosterone system inhibitor with chronic kidney disease (CKD), type 2 diabetes mellitus (T2DM), and hypertension. STUDY DESIGN: Post hoc subgroup analysis of the randomized open-label AMETHYST-DN clinical trial. SETTING & PARTICIPANTS: Multicenter clinical trial. Individuals 75 years and older with CKD, T2DM, hypertension, and hyperkalemia at baseline (N = 60; mean age, 77 years; 30 men [50%]; mean estimated glomerular filtration rate, 41.6 ± 14.3 mL/min/1.73 m2). INTERVENTION: Patients with hyperkalemia were randomly assigned to receive patiromer at doses ranging from 4.2 to 16.8 g twice daily. OUTCOMES: We evaluated changesin serum potassium levels from baseline to week 4 and time points through 52 weeks. Long-term safety and tolerability were assessed through the end of 52 weeks and included frequency of adverse events, clinical laboratory measurements, and vital signs. RESULTS: Of 306 AMETHYST-DN participants, 60 were 75 years or older. All 60 patients had CKD and T2DM; 37% had heart failure. At screening, patients had an estimated glomerular filtration rate of 42 mL/min/1.73 m2, median urinary albumin-creatinine ratio of 127 mg/g, and baseline mean serum potassium level of 5.19 mEq/L. Mean serum potassium level was reduced at each time point from the first postbaseline visit (day 3) through week 52. LIMITATIONS: This small subgroup analysis was not prespecified and therefore randomization was lost; thus, it should be considered hypothesis generating. CONCLUSIONS: Among older patients with hyperkalemia and diabetic kidney disease, treatment with patiromer resulted in significant reductions in serum potassium levels after 4 weeks and lasted through 52 weeks. Patiromer was effective in lowering serum potassium levels and was well tolerated in older patients. FUNDING: Vifor Pharma, Inc. TRIAL REGISTRATION: NCT01371747.

A Predictive Model for Progression of Chronic Kidney Disease to Kidney Failure Using a Large Administrative Claims Database.

BACKGROUND: To create an appropriate chronic kidney disease (CKD) management program, we developed a predictive model to identify patients in a large administrative claims database with CKD stages 3 or 4 who were at high risk for progression to kidney failure. METHODS: The predictive model was developed and validated utilizing a subset of patients with CKD stages 3 or 4 derived from a large Aetna claims database. The study spanned 36 months, comprised of a 12-month (2015) baseline period and a 24-month (2016-2017) prediction period. All patients were ≥18 years of age and continuously enrolled for 36 months. Multivariate logistic regression was used to develop models. Prediction model performance measures included area under the receiver operating characteristic curve (AUROC), calibration, and gain and lift charts. RESULTS: Of the 74,114 patients identified as having CKD stages 3 or 4 during the baseline period, 2476 (3.3%) had incident kidney failure during the prediction period. The predictive model included the effect of numerous variables, including age, gender, CKD stage, hypertension (HTN), diabetes mellitus (DM), congestive heart failure, peripheral vascular disease, anemia, hyperkalemia (HK), prospective episode risk group score, and poor adherence to renin-angiotensin-aldosterone system inhibitors. The strongest predictors of progression to kidney failure were CKD stage (4 vs 3), HTN, DM, and HK. The ROC and calibration analyses in the validation sample demonstrated good predictive accuracy (AUROC=0.844) and calibration. The top two prediction deciles identified 70.8% of patients who progressed to kidney failure during the prediction period. CONCLUSION: This novel predictive model had good accuracy for identifying, from a large national database, patients with CKD who were at high risk of progressing to kidney failure within 2 years. Early identification using this model could potentially lead to improved health outcomes and reduced healthcare expenditures in this at-risk population.

A Model to Predict Risk of Hyperkalemia in Patients with Chronic Kidney Disease Using a Large Administrative Claims Database.

BACKGROUND: Chronic kidney disease (CKD) is responsible for substantial clinical and economic burden. Drugs that inhibit the renin-angiotensin-aldosterone system inhibitors (RAASi) slow CKD progression in many common clinical scenarios. Guideline-directed medical therapy requires maximal recommended doses of RAASi, which clinicians are often reluctant to prescribe because of the associated risk of hyperkalemia (HK). OBJECTIVE: This study aims to develop and validate a model to identify individuals with CKD at elevated risk for developing HK over a 12-month period on the basis of lab, medical, and pharmacy claims. METHODS: Using claims from a large US healthcare payer, we developed a model to predict the probability of individuals identified with CKD but not HK in 2016 (baseline year [BY]) who developed HK in 2017 (prediction year [PY]). The study population was comprised of members continuously enrolled with medical and pharmacy benefits and CKD (BY). Members were excluded from the analysis if they had HK (by lab results or diagnosis code) or dialysis (BY). Prediction model performance measures included area under the receiver operating characteristic curve (AUROC), calibration, and gain and lift charts. RESULTS: Of 435,512 members identified with CKD but not HK (BY), 6235 (1.43%) showed incident HK (PY). Compared with individuals without incident HK (PY), these members had a higher comorbidity burden, use of RAASi, and healthcare utilization. The AUROC and calibration analyses showed good predictive accuracy (area under the curve [AUC]=0.843 and calibration). The top 2 HK-prediction deciles identified 75.94% of members who went on to develop HK (PY). CONCLUSION: Guideline-recommended doses of RAASi therapy can be limited by the risk of HK. Novel potassium binders may permit more patients at risk to benefit from these maximal RAASi doses. This predictive model successfully identified the risk of developing HK up to 1 year in advance.

Hyperkalemia treatment modalities: A descriptive observational study focused on medication and healthcare resource utilization.

Renin-angiotensin-aldosterone system inhibitor (RAASi) therapy has been shown to improve outcomes among patients with congestive heart failure, diabetes, or renal dysfunction. These patients are also at risk for the development of hyperkalemia (HK), often leading to down-titration and/or discontinuation of RAASi therapy. Patiromer is the first sodium-free, non-absorbed potassium (K+) binder approved for the treatment of hyperkalemia (HK) in over 50 years. We described the association between use of K+ binders (Patiromer and sodium polystyrene sulfonate [SPS]) and renin-angiotensin-aldosterone system inhibitor (RAASi), on healthcare resource utilization (HRU). The study population consisted of Medicare Advantage patients with HK (K+ ≥ 5.0 mmol/L) in Optum's Clinformatics® Data Mart between 1/1/2016-12/31/2017. Patiromer and (SPS) initiators, and HK patients not exposed to a K+ binder (NoKb) were included. The index date was the date of the first K+ binder dispensing or HK diagnosis. Outcomes assessed at 6 months post-index were: (1) K+ binder utilization, (2) RAASi continuation, and (3) HRU (pre- vs post-index). HRU change was analyzed using McNemar's statistical test. Study cohorts included 610 (patiromer), 5556 (SPS), and 21,282 (NoKb) patients. Overall baseline patient characteristics were: mean age 75 years; female 49%, low-income subsidy 29%, chronic kidney disease 48% (63% for patiromer cohort), and congestive heart failure 29%. At 6 months post-index, 28% (patiromer) and 2% (SPS) remained continuously exposed to the index K+ binder. RAASi continued for 78% (patiromer), 57% (SPS), and 57% (NoKb). The difference (pre- vs post-index) in hospitalized patients was: -9.4% (patiromer; P<0.05), -7.2% (SPS), and +16.8% (NoKb; P<0.001). Disparate K+ binder utilization patterns were observed. The majority of patiromer patients continued RAASi therapy while the percentage of SPS patients that continued RAASi therapy was lower, overlapping CIs were observed. Following continuous patiromer exposure, statistically significant reductions in hospital admissions and emergency department visits were observed, continuous SPS exposure observed no statistically significant reductions in either hospitalizations or ED visits, while NoKb patients with continuous exposure had statistically significant increases in both. Further research, with a larger sample size using comparative analytic methods, is warranted.

The Economic Implications of Hyperkalemia in a Medicaid Managed Care Population.

BACKGROUND: Hyperkalemia, defined as a serum potassium level >5 mEq/L that results from multiple mechanisms, is a serious medical condition that can lead to life-threatening arrhythmias and sudden cardiac death. The coexistence of cardiac and renal diseases (ie, cardiorenal syndrome) significantly increases the complexity of care, but its economic impact is not well-characterized in this understudied Medicaid managed care population with hyperkalemia. OBJECTIVE: To calculate the economic impact of hyperkalemia on patients with cardiorenal syndrome in a Medicaid managed care population in the United States using real-world data. METHODS: In this retrospective cohort study, we used a proprietary Medicaid managed care database from 1 southern state. The total study population included 3563 patients, including 973 patients with hyperkalemia and 2590 controls (without hyperkalemia), who were matched based on age, comorbidities, and Medicaid eligibility status and duration, during a 30-month period between 2013 and 2016. The inclusion criteria for the hyperkalemia cohort were age ≥18 years, Medicaid-only insurance status, coded cardiorenal diagnosis, and a claim for hyperkalemia during the study period. The cost was determined using paid claims data. RESULTS: The mean healthcare costs (medical and pharmacy per member per year [PMPY] for patients with hyperkalemia was higher than that for the control cohort without hyperkalemia ($56,002 vs $23,653, respectively). These cost differences were driven by medical costs accrued in the hyperkalemia and in the control cohorts ($49,648 and $18,399 PMPY, respectively). Two of the largest drivers of the medical cost variance were inpatient costs ($33,116 vs $10,629 PMPY for the hyperkalemia and control cohorts, respectively) and dialysis costs ($2716 vs $810 PMPY, respectively). The medical loss ratios were 552% for the hyperkalemia cohort and 260% for the control cohort. Both cohorts had revenue deficits to the health plan, but the hyperkalemia cohort had double the medical loss ratio compared with the control cohort. CONCLUSIONS: The findings from this Medicaid managed care population suggest that hyperkalemia increases healthcare utilization and costs, which were primarily driven by the costs associated with inpatient care and dialysis. Our findings demonstrate that the Medicaid beneficiaries who have cardiorenal comorbidities accrue high costs to the Medicaid health plan, and these costs are even higher if a hyperkalemia diagnosis is present. The very high medical loss ratio for the hyperkalemia cohort in our analysis indicates that enhanced monitoring and management of patients with hyperkalemia should be considered.

All-cause costs increase exponentially with increased chronic kidney disease stage.

OBJECTIVE: To evaluate the economic impact of chronic kidney disease (CKD) on US health plans. STUDY DESIGN: A retrospective analysis identified patients with a renin-angiotensin-aldosterone system inhibitor (RAASi) prescription from an electronic medical record (EMR) database (Humedica); those with =90 days in =1 CKD stage were selected based on estimated glomerular filtration rate or diagnosis code, and a cohort on RAASi medications without CKD was selected. Costs for specific services obtained from OptumInsight were applied to services in EMR data of patients aged <65 years (commercial) and =65 years (Medicare). Dialysis costs were excluded. RESULTS: The study included 106,050 patients with CKD and 56,761 no-CKD controls (90,302 commercial and 72,509 Medicare overall). Mean annualized all-cause costs increased exponentially with advancing stage, from $7537 (no CKD) to $76,969 (CKD stages 4-5) in the commercial group, and $8091 (no CKD) to $46,178 (CKD stages 4-5) in the Medicare group (P <.001; all comparisons with preceding disease stage). Mean costs for end-stage renal disease (ESRD) patients were $121,948 and $87,339 in the commercial and Medicare groups, respectively. Inpatient costs were the largest contributor to total costs, and their relative contribution increased with advancing CKD. CONCLUSIONS: Cost to US health plans increases exponentially with each CKD stage progression. ESRD costs are even higher. Because readmissions lead to higher costs, efforts to reduce readmissions would result in cost reductions. Furthermore, healthcare reengineering paradigms that manage increasing comorbidities with advancing CKD, including heart failure, diabetes, and hyperkalemia, should offer additional potential for cost reductions.