QIP Scores and Rates of Mortality among Incident Dialysis Patients

Kidney failure is irreversible and patients with kidney failure require renal replacement therapy or kidney transplantation for survival. Due to the shortage of kidney donors, incompatible blood and tissue type, not being a good candidate for transplantation, or other social barriers, the majority of patients with kidney failure remain on dialysis therapy.

In 1972, the Centers for Medicare & Medicaid Services (CMS) included end-stage renal disease (ESRD) as the first disease-based eligibility; ERSD remains the only disease with such designation. In 1972, the dialysis population was 10,000 patients; in 2014, the number of patients on maintenance dialysis was 399,455. Costs have followed a similar increasing trend in that time period, and CMS has continued to encourage reforms to increase efficiency in care for patients with ESRD.

In the 2011 payment reform, CMS proposed an expanded bundle payment program, recommending a fixed payment per dialysis treatment. As part of the bundle payment reform, CMS implemented a Quality Incentive Program (QIP). In the QIP, care at dialysis facilities is rated on a scale of 0 to 100.

The impact of the QIP program on health outcomes is unknown; the program has been criticized for including laboratory indicators while limiting data on patient health outcomes. Noting that survival rates of patients on dialysis have remained less than optimal, Fozia Ajmal, MD, PhD, and colleagues conducted a study to examine the association between dialysis facility QIP performance scores and patient survival following initiation of dialysis. The researchers sought to test the hypothesis that mortality among incident dialysis patients would be higher among poor-performing facilities compared with those performing well. Results of the study were reported in the American Journal of Kidney Diseases [2020;75(2):177-186].

The retrospective cohort study included 84,493 incident dialysis patients from January to December 2013. Inclusion criteria were survival, no receipt of a kidney transplant, and no loss to follow-up within 90 days of dialysis initiation. Average follow-up was 5 months.

The independent variable was facility QIP scores (ranging from 0 to 100) for calendar year 2013. Facility covariates included chain affiliation, for-profit and low-volume status, dialysis treatments per facility per year, registered nurses per 10,000 treatments, technicians per 10,000 treatments, and services including home hemodialysis, peritoneal dialysis, and late shift.

Five different options were used to identify membership in a chain of dialysis facilities. For the three largest chains, each chain was assigned a number (1-3); facilities affiliated with the smaller or regional chains were consolidated into a single category (chain 4); and the remaining facilities were grouped into an independent category.

County covariates reflected the characteristics of counties where patients resided. The analysis included the proportion of Hispanics, blacks, unemployed, and those living in poverty. Median household income was also a county covariate.

Mean age of the cohort was 63.8 years, 57.3% were men, 51.4% were non-Hispanic white, 29.8% were unemployed, 60.7% were retired, and 40.9% were obese. Comorbidities included hypertension (88.4%); 48.1% had diabetes as the most common cause of kidney failure, followed by hypertension (31.4%). Approximately 7% of the participants were uninsured. Central venous catheter was the most common access modality at dialysis initiation (72.9%).

Most facilities (77.1%) operated 11 to 25 dialysis stations, provided more than 10,000 treatments (45.3%), were affiliated with large chains (chain 1, 33.7%; chain 2, 4.0%; chain 3, 32.4%), and were for profit (92.1%). All centers provided access to hemodialysis; 49.2% provided peritoneal dialysis, 27.6% provided home hemodialysis, and 19.2% offered late-night dialysis.

Of the 2983 counties represented in the analysis, most patients resided in urban areas (81.6%) and the South (44.6%). Average proportions of Hispanics and blacks per county were 15.4% and 17.9%, respectively. The average rate of unemployment was 7.7%.

Following exclusion of patients who died during the first 90 days of the first ESRD service,  11.8% of patients died within 1 year of follow-up. The hazard ratios (HR) of death varied by QIP scores. Compared with mortality rates at facilities with the highest QIP scores (≥90), mortality was higher in patients at facilities with scores <45 (HR, 1.60; 95% confidence interval [CI], 1.37-1.86); 45 to <60 (HR, 1.41; 95% CI, 1.29-1.55); 60 to <70 (HR, 1.09; 95% CI, 1.02-1.16) and 70 to <80 (HR, 1.08; 95% CI, 1.02-1.14). There was no statistically significant difference for patients at facilities scoring 80 to <85 and 85 to <90 compared with patients at facilities scoring ≥90 (reference category).

In fully adjusted models, there was a higher mortality rate among patients at facilities with QIP scores <45 (HR, 1.39; 95% CI, 1.15-1.68) and 45 to <60 (HR, 1.21; 95% CI, 1.10-1.33), compared with facilities with QIP scores ≥90.

In analyses of associations between patient, facility, and county covariates and patient mortality, there were associations between unemployment (HR, 1.76; 95% CI, 1.54-2.00), being retired (HR, 1.84; 95% CI, 1.62-2.09), being underweight (HR, 1.28; 95% CI, 1.17-1.40), being uninsured (HR, 1.63; 95% CI, 1.43-1.87), having ≥2 comorbid conditions (HR, 1.25; 95% CI, 1.16-1.35), and central venous catheter access (HR, 1.45; 95% CI, 1.27-1.65) and increased likelihood of death. There was also an association between each 1-year older age and living ≥10 miles from the dialysis facility and increased mortality risk.

Lower mortality risk was seen in facilities affiliated with chain 3 and those offering home dialysis. Facilities with 11 to 25 dialysis stations and those with >25 dialysis stations also had lower patient mortality risk.

Study limitations cited by the researchers included using the latest available data (2015), potentially limiting the generalizability of the findings to years other than those studied; the inability to adjust for the number of transitions for patients who visited multiple dialysis facilities or for changes in treatment modality; and not adjusting for baseline laboratory markers such as serum albumin level and residual kidney function.

“In conclusion, we show that higher scores using the QIP criteria of 2015 robustly predicted higher patient survival in incident dialysis patients. Our findings support the metrics as used in QIP for monitoring quality and suggest more research to further improve risk prediction of clinical and patient-reported outcomes in dialysis patients using the recent QIP data,” the researchers said.

Takeaway Points

  1. Researchers conducted a retrospective cohort study to test the hypothesis that mortality rates among incident dialysis patients would be higher among dialysis facilities with lower CMS Quality Incentive Program (QIP) scores compared with facilities with higher QIP scores.
  2. In a cohort of 84,493 patients who initiated dialysis from January to December 2013, 11.8% died during an average follow-up of 5 months.
  3. Rates of patient mortality were higher at facilities with QIP scores <45 and 45 to <60, compared with facilities with QIP scores ≥90.