Regional variability in anaemia management and haemoglobin in the US

Donal N. Reddan1,, Diane L. Frankenfield2, Preston S. Klassen1, Joseph A. Coladonato1, Lynda Szczech1, Curtis A. Johnson3, Anatole Besarab4, Michael Rocco5, William McClellan6, Jay Wish7 and William F. Owen Jr1 for CMS's ESRD CPM Workgroup

1 Duke Institute of Renal Outcomes Research and Health Policy, Duke University Medical Center, Durham, NC, 2 Center for Beneficiary Choices, Centers for Medicare & Medicaid Services, Baltimore, MD, 3 University of Wisconsin School of Pharmacy, Madison, WI, 4 West Virginia University, Morgantown, WV, 5 Wake Forest University School of Medicine, Winston-Salem, NC, 6 Emory University, Atlanta, GA and 7 University Hospitals of Cleveland, Cleveland, OH, USA



   Abstract
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Background. Regional differences in haemoglobin values and process care measures were examined using data from the Centers for Medicare & Medicaid Services' End-Stage Renal Disease (ESRD) Clinical Performance Measures Project. It was posited that regional differences in haemoglobin values are consequent upon differences in components of clinical practice.

Methods. A national random sample of 8336 adult, in-centre haemodialysis patients, stratified by the 18 regional ESRD Networks, was drawn. Information was collected for October–December 1998. Multivariable stepwise linear and logistic regression analyses were performed to identify variables associated with haemoglobin. Linear regression analysis was used to identify variables associated with Epo/Hb index (mean weight-adjusted treatment level erythropoietin (Epo) dose divided by mean haemoglobin).

Results. The percentage of patients with haemoglobin concentration <11 g/dl ranged from 34 to 52% across ESRD Networks. In addition to haemoglobin there was significant, non-random variation among ESRD Networks with regard to prescribed Epo dose and administration route, intravenous (IV) iron prescription and dialyser flux (high flux=KUf >=20 ml/mmHg/h) (all P-values <0.001). Higher haemoglobin was associated with older age, male gender, higher serum albumin, higher transferrin saturation, higher Kt/V, lower serum ferritin and lower prescribed Epo dose (all P-values <0.01). Diabetes mellitus as cause of ESRD, high-flux dialyser use, IV iron prescription or subcutaneous Epo prescription were not associated with haemoglobin. Male gender, diabetes as cause of ESRD, older age, higher transferrin saturation and higher albumin concentrations were associated with lower Epo/Hb index. Prescription of IV iron and IV Epo were associated with higher Epo/Hb index.

Conclusions. Regional mean haemoglobin levels vary considerably across the US and the variation in haemoglobin is explained by both non-modifiable factors and modifiable clinical practice-derived variables.

Keywords: anaemia; Centers for Medicare & Medicaid Services; end-stage renal disease; erythropoietin; haemodialysis; iron



   Introduction
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Anaemia affects the majority of end-stage renal disease (ESRD) patients and almost all affected patients receive recombinant (biosynthetic) human erythropoietin (Epo) as primary treatment for their anaemia. Because the extent of anaemia correction in ESRD patients has been associated with clinical outcomes, clinical practice guidelines arising from a structured review of available clinical literature advocate a haematocrit range from 33 to 36% [1]. Because absolute or relative iron deficiency [2] is a common cause of relative unresponsiveness to Epo, concomitant clinical practice guideline statements have also been developed for iron administration [1]. The recommendations are for the performance of regular monitoring of the percentage transferrin saturation (TSAT) and the serum ferritin concentration and maintenance of these values >=20% and 100 ng/ml, respectively.

To encourage and assist in the achievement of the target haematocrit, quality improvement projects focused at dialysis facilities have been established and executed through individual dialysis unit providers and nephrologists. Based on results from several national registries and datasets, the haematocrit values for haemodialysis patients in the US have increased over the past 8 years [3,4]. The Centers for Medicare & Medicaid Services' (CMS) National ESRD Core Indicators/Clinical Performance Measures (CPM) Project is one such quality improvement project and reporting system. From 1994 to 1998, the mean haematocrit for a nationally representative sample of adult (>=18 years old) haemodialysis patients increased from 31 to 34%. Despite the national improvement in mean haematocrit values, substantial regional differences continue to be observed, especially when reported as the percentage values greater than or equal to the Kidney Disease Outcomes Quality Initiative (KDOQI) benchmark value of 33% [1,4].

Haematocrit values are generally highest in the north-west portion of the US and lowest in the south-eastern US. The basis for this regional variation is debated, i.e. the role of patient-specific variables vs processes of patient care. Several patient-specific variables as well as provider actions influence the achieved haematocrit, the prescribed doses of Epo and the relationship of Epo dose to haematocrit. For example, increasing age, white race, male gender and greater serum albumin and creatinine concentrations have been independently associated with higher haematocrit values [4,5]. In turn, provider behaviours such as the dose and route of administration of Epo [6] and iron [7], the achievement of higher mean TSAT and higher doses of haemodialysis [5], and the use of high-flux haemodialysers [8] have been shown to influence haematocrit. The relative contributions of these individual and aggregate associates of achieved haematocrit and Epo dose have not been examined. It is hypothesized that geographic variation in provider behaviour relating to anaemia management principally accounts for the geographic differences in haemoglobin. We tested this hypothesis using nationally representative data collected on adult (>=18 years old) in-centre haemodialysis patients.



   Subjects and methods
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
The sampling strategy and design of the ESRD CPM project have been described in detail previously [9,10]. Briefly, all Medicare-eligible, adult ESRD patients receiving in-centre haemodialysis on 31 December 1998 were eligible for inclusion in the sample. A random sample of patients, stratified by the 18 ESRD Networks, was identified. The sample size provided a 95% confidence interval (CI) of ±5% for ESRD Network-specific estimates. Patient demographic and clinical information was collected for the months October–December 1998.

Data gathered included the patient's prescribed Epo dose and route of administration, the prescribed route of iron administration, the first monthly-recorded haemoglobin (Hb) value, transferrin saturation (TSAT) value, serum ferritin concentration and serum albumin concentration as well as the laboratory technique used to assess the albumin concentration (bromocresol green (BCG) or bromocresol purple (BCP)). The single pool Kt/V (calculated using the Daugirdas second generation formula) [11] was generated from first monthly pre-dialysis and post-dialysis blood urea nitrogen (BUN) concentrations, pre-dialysis and post-dialysis body weight, and the delivered haemodialysis time at the session the BUN measurements were drawn. The KUf of the haemodialyser membrane was used to classify them as high or low flux. A KUf value >=20 ml/mmHg/h was considered high flux and a value <20 ml/mmHg/h low flux. Patients were categorized as dialysing with high-flux dialysers if high-flux dialysers were used for two or more of the 3 months, or if a patient had no data recorded for dialyser type for 2 months but high-flux dialysers were used for one of the 3 months. If the dialyser type was not recorded for 1 month and mixed in the other 2 months, the patient was excluded from multivariable analyses involving dialyser type.

Only monthly Hb values with parallel reported prescribed Epo doses were used for analysis. The prescribed Epo route was assigned based on data over 3 months. Patients prescribed intravenous (IV) Epo for >=1 month and not prescribed any subcutaneous (SC) Epo were categorized as having been prescribed IV Epo. Patients prescribed both IV and SC Epo were excluded from multivariable analyses that used route of Epo administration as a variable. Patients were categorized as having been prescribed IV iron if they were prescribed IV iron at any time during the 3 months of data collection. For repeated measures, such as the dose of Epo, Hb and serum ferritin, the averages of the values for each patient recorded during the 3 month abstraction period were used for subsequent analysis. An Epo/Hb index for each patient was calculated by dividing the average per dialysis treatment weight-adjusted Epo dose by the average Hb over 3 months.

Statistical analysis
Bivariate analyses, including chi-square test, Student's t-test and hierarchical analysis of variance (ANOVA), were conducted to determine associations between variables. Mean values are presented as means±SD. Associations by race were limited to black and white race only, due to small numbers of patients of other races. Analyses that included the serum albumin concentration were restricted to the subset of patients with serum albumin values reported by the BCG assay only (84% of the 8336 patients). A two-tailed P-value <0.01 was considered significant. Linear correlations were performed to test for associations between Hb values and the variables of interest. Multivariable linear and logistic regression analyses were performed separately to adjust simultaneously for potential confounding variables and to identify independent variables associated with the Hb concentration. The linear regression analysis was then repeated with Epo/Hb index as the dependent variable.

The initial linear regression model was developed with the mean Hb concentration as the dependent variable. The model was developed using a forward stepwise process with entry criteria of 0.1. The variables in the stepwise selection process included all demographic variables, diabetes mellitus as the cause of ESRD vs all other aetiologies combined, duration of haemodialysis, mean prescribed Epo dose and route of administration, prescription of IV iron, mean TSAT, mean serum ferritin concentration, dose of haemodialysis, vascular access type, dialyser KUf category, mean serum albumin concentration (BCG method only) and ESRD Network. Appropriate interactions were tested. A final model was subsequently generated using the variables noted to be significant in the stepwise analysis and other variables thought to be clinically relevant. Subsequently, a linear regression model was generated with the Epo/Hb index as the dependent variable. This model was generated using the same pool of independent predictor variables as the earlier model predicting Hb concentration.

Potential predictor variables and other clinically relevant variables significantly associated with mean Hb concentration >=11 g/dl (P<0.01) in bivariate analyses were introduced into logistic regression models. Mean Hb concentration >=11 g/dl was the dependent variable of interest. Predictor variables assessed included patient demographics, diabetes as the cause of ESRD vs all other aetiologies combined, duration of haemodialysis, dose of dialysis (mean Kt/V and mean urea reduction ration (URR) separately), mean prescribed Epo dose and route of administration, prescription of IV iron, mean TSAT, mean serum ferritin and albumin concentrations (BCG method only), type of vascular access, dialyser KUf category and ESRD Network. Interaction terms were tested. Linear regression analyses were performed using SAS software v. 6.12 (SAS Institute Inc., Cary, NC) and logistic regression analyses were performed using SPSS v. 8.0 [12].



   Results
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
There were 8336 patients (94% response rate) in the sample for analysis. Tied or parallel monthly Hb and prescribed Epo doses were available for 7592 (91%) of the patients. There were no significant differences in patient demographic characteristics between patients with tied monthly Hb and Epo values available and those without. The final sample closely resembled the entire Medicare ESRD population with its slight preponderance of men, a disproportionate number of whites and diabetes being the principal reported cause of ESRD [13] (Table 1Go). The median age was 62 years and the median duration of dialysis was 2.1 years. Most patients dialysed through a prosthetic graft or autologous fistula. The median delivered (single pool) Kt/V was 1.4.


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Table 1.  Patient characteristics

 
Eighty-nine percent of patients were prescribed IV Epo; 10% of patients were prescribed SC Epo and 1% were prescribed both routes. Median Epo dose for IV and SC routes was 54.0 and 45.8 units/kg, respectively. The distribution of prescribed Epo doses by route of administration is shown in Figure 1Go. The prescribed route of Epo administration varied significantly among ESRD Networks with 71–98% of the patients prescribed IV Epo (chi-square 374.5, P<0.0001) (Figure 2Go). Mean prescribed Epo dose also varied significantly by ESRD Network, ranging from 56.1 to 90.7 units/kg (F-statistic 9.64, P<0.0001).



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Fig. 1.  Distribution of Epo dose by route of administration. Closed bars, SC; open bars, IV. Median Epo dose was 45.8 and 54.0 units/kg for SC and IV Epo, respectively.

 


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Fig. 2.  Percentage of patients receiving IV Epo by ESRD Network. Grey bar, overall percentage across all ESRD Networks. P<0.0001.

 
The mean Hb for all patients was 11.1±1.2 g/dl. There was no significant difference in mean Hb concentration by prescribed route of Epo administration; 11.1±1.2 g/dl for IV Epo and 11.1±1.2 g/dl for SC Epo (P=0.637). The frequency distribution of Hb values by prescribed route of Epo administration for the US is illustrated in Figure 3Go and this figure demonstrates that Hb values were normally distributed. Hierarchical analysis of variance of Hb concentrations across all ESRD Networks revealed significant non-random variation (i.e. variation not due to chance), with mean Hb values ranging from 10.8 to 11.4 g/dl (F-statistic 4.74, P<0.001). The proportion of patients across Networks with Hb values >=11.0 g/dl ranged from 48 to 66% (chi-square 77.8, P<0.001).



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Fig. 3.  Haemoglobin distribution. Closed squares, SC; open squares, IV. Mean Hb 11.07±1.21 g/dl for SC and 11.09±1.21 g/dl for IV.

 
Figure 4Go describes the details of the relationship between Epo dose, iron utilization and mean Hb. Mean Hb achieved was lower across increasing quartiles of Epo dose and this relationship was similar among patients prescribed and not prescribed IV iron. There was significant variability among ESRD Networks in the percentage of patients prescribed IV iron, ranging from 47 to 70% across Networks (chi-square 173.0, P<0.0001). There was also significant variability across ESRD Networks with regard to mean TSAT, ranging from 19.2 to 32.5% (F-statistic 21.45, P<0.0001) and there was considerable variability among ESRD Networks in terms of use of high-flux haemodialysers (chi-square 575.1, P<0.001). At one extreme is ESRD Network 3, in which only 31% of patients were dialysed with high-flux dialysers in contrast to ESRD Network 18 in which 76% were dialysed with high-flux dialysers. The other ESRD Networks had percentages intermediate to these two.



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Fig. 4.  Mean Hb by quartile of Epo dose with and without parenteral iron administration.

 
For the final linear model, 72% of the patients were included (5475 of 7592). The variables found to be significant in the stepwise selection process having a positive relationship with Hb concentration included increasing age, male gender, lower mean Epo doses, higher mean TSAT, lower mean serum ferritin concentration, higher mean serum albumin concentrations, greater mean haemodialysis doses and receiving care in ESRD Networks 4 or 12. The parameter estimates and significance levels can be seen in Table 2Go. There were no significant interaction terms found during the linear modelling procedure.


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Table 2.  Significant variables in the final linear model with Hb as the dependent variable

 
Seventy-two percent of the patients (5454 of 7592) were included in the final logistic regression model predicting a mean Hb >=11 g/dl. The significant predictors in the final logistic regression model are depicted in Table 3Go. Increasing age, male gender, duration of haemodialysis <1 year, lower mean doses of Epo, higher mean TSAT, higher mean Kt/V, higher mean serum albumin and receiving care in ESRD Network 4 (all P-values <0.01) were significantly associated with experiencing a mean Hb >=11 g/dl. There were no significant interaction terms found during the logistic regression procedure.


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Table 3.  Final logistic regression model predicting a mean Hb >=11 g/dla

 
The mean Epo/Hb index for the population studied was 6.44±5.62 units/kg/dose/g/dl. When a multivariable linear regression model was generated with Epo/Hb index as the dependent variable, male gender, diabetes as cause of ESRD, older age, higher transferrin saturation, higher albumin concentrations and receiving care in ESRD Networks 11 or 15 were associated with lower Epo/Hb index (Table 4Go). Prescription of IV iron and IV Epo and receiving care in Network 4 were associated with higher Epo/Hb index.


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Table 4.  Predictors of Epo/Hb index

 



   Discussion
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 
Based on a nationally representative sample of ESRD patients receiving in-centre haemodialysis, significant regional differences were observed in both mean Hb concentration and the percentage of patients with mean Hb exceeding the recommended minimum value of 11.0 g/dl [1]. Previous work has suggested that both patient-specific variables and provider practices can affect the final Hb concentration [5]. In addition to confirming observations about non-modifiable factors [5], the additional information provided by this analysis is a clarification of the influence of modifiable factors on achieved Hb targets.

The finding that between 46 and 58% of patients in individual Networks had Hb concentrations equal to or higher than 11 g/dl suggests that a slightly higher proportion of patients reached target Hb levels than the 43.6% reported at the end of the European Survey on Anaemia Management (ESAM) study in France. The ESAM study also reported that unsatisfactory prescription and monitoring of the effects of iron supplementation accounted for a large part of the under-achievement of Hb targets [14].

We describe significant variability in Hb accounted for by patient-specific and clinical practice variables. Patient-specific variables included age, gender and albumin. Variables that were considered modifiable clinical practice variables included mean weekly Epo dose and mean dialysis dose. Variables describing iron stores, TSAT and serum ferritin could also be considered modifiable clinical practice variables and were explanatory. However, the complex interactions between measures of iron stores and serum ferritin, in particular with inflammation, make it difficult to define them as completely modifiable.

The absence of specific iron dosing information is a limitation of these analyses and despite the observation of non-random regional differences in prescription of IV iron, the prescription of IV iron was not found to be a significant predictor of Hb. The positive association of TSAT with Hb, however, suggests the possibility of an association of increased Hb with successful iron repletion.

That route of Epo administration was predictive of Epo/Hb index but not predictive of Hb probably reflects appropriate adjustment by nephrologists for the reduced efficacy of IV relative to SC Epo. That higher Epo doses predicted lower mean Hb could possibly be explained by indication bias, in that relatively higher doses of Epo may be given to poorly responsive Epo-resistant patients.

This analysis bears the typical limitations associated with observational analyses. Bias by indication is likely for some elements, such as the prescription of parenteral iron and SC Epo. Facility-specific data describing practice patterns or other characteristics were not available. Despite these limitations, these findings are strengthened by the large number of subjects and observations, the use of an established and validated nationally representative sample, confirmation of conventional associations using this dataset and the use of complimentary multivariable analyses with comparable results.

We also used this dataset to examine the relationships between Epo doses and achieved Hb concentration, by determining predictors of the Epo/Hb index. Previous analyses have reported reduced Epo doses or enhanced responsiveness for patients receiving SC rather than IV Epo [15,16] and IV rather than oral iron [17,18]. These data confirm that the use of SC Epo is associated with more efficient Epo dosing. The finding that higher TSAT also leads to reduced Epo/Hb index is also consistent with these earlier findings. The finding that prescription of IV iron predicted a higher Epo/Hb index could be explained by indication bias and may have been less evident had iron dosing data been available.

Erythropoietin dosing on a population basis has been increasing in recent years and a relationship has been established between increased doses and increased Hb targets [19]. This observation obviously has substantial cost implications. These findings provide evidence to support the development of focused quality improvement projects that rely upon the continued development and application of clinical practice guidelines and performance measures. By encouraging administration of SC Epo, more iron use and greater attention to evaluating Epo hyporesponsiveness, Epo effectiveness may be enhanced. Moreover, Hynes et al. [20] suggest that use of SC Epo could lead to substantial cost savings. More importantly, further exploration of the relative ineffectiveness of existing quality-improvement projects already implemented in many health systems across the world is warranted. Possible explanations for such ineffectiveness include provider disbelief of recommendations, inadequate CPM dissemination, incomplete prospective monitoring and feedback of results or insufficient systems to support and/or implement changes [21]. The absence of a clear correlation between reimbursement and quality of care could also be playing an important role [22]. Linking reimbursement with quality is one example of a possible ecological health system intervention that could lead to improvement in quality of care. Further refinements in the CPM process that could lead to improved interpretation and implementation of CPMs might be achieved by the expansion of the process to collect data at a dialysis-unit level, in addition to the current patient-specific data collection.

In conclusion, we have shown that regional mean Hb levels vary considerably across the US. The variation in Hb is explained by both non-modifiable factors and modifiable clinical practice-derived variables. Considerable opportunity for improvement exists with respect to the management of anaemia by enhanced implementation of appropriate clinical performance measures.



   Acknowledgments
 
These data were presented previously in abstract form at the American Society of Nephrology meeting 2001 in San Francisco.



   Notes
 
Correspondence and offprint requests to: Dr Donal Reddan, Duke Institute of Renal Outcomes Research and Health Policy, Box 3646, Duke University Medical Center, Durham, NC 27710, USA. Email: redda001{at}mc.duke.edu

The authors wish it to be known that, in their opinion, the first two authors contributed equally to this work. The views expressed in this manuscript are those of the authors and do not necessarily reflect official policy of the Centers for Medicare & Medicaid Services. Back



   References
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 References
 

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Received for publication: 8. 3.02
Accepted in revised form: 29. 8.02