Skip To Main Content
 
 Figure 5.1Percent of Medicare patients aged 66+ (a) with at least one AKI hospitalization, and (b) percent among those with an AKI hospitalization who required dialysis, and by whether an intensive care unit (ICU) stay was required, 2005-2015
 Figure 5.2Percent of Optum Clinformatics™ patients aged 22+ (a) with at least one AKI hospitalization, and (b) percent among those with an AKI hospitalization who required dialysis, 2005-2015
 Table 5.1Characteristics of Medicare and Optum Clinformatics™ patients with at least one hospitalization, by age, sex, race, CKD, DM, and presence of AKI, 2015
 Table AKDIGO definition and staging of acute kidney injury
 Table 5.2Characteristics of Veterans Affairs patients aged 22+ with at least one hospitalization, by age, sex, race, CKD, DM, presence and stage of AKI, defined by serum creatinine, FY 2015
 Figure 5.3Unadjusted rates of hospitalization with AKI, per 1,000 patient-years at risk, by age, 2005-2015
 Figure 5.4Unadjusted rates of hospitalization with AKI, per 1,000 patient-years at risk, by race, 2005-2015
 Figure 5.5Unadjusted rates of hospitalization with AKI, per 1,000 patient-years at risk, by CKD, and DM, 2005-2015
 Figure 5.6Cumulative probability of a recurrent AKI hospitalization within two years of live discharge from first AKI hospitalization in 2013 for Medicare patients aged 66+, (a) overall, (b) by age, (c) by race, and (d) by CKD and DM
 Figure 5.7Cumulative probability of a recurrent AKI hospitalization within two years of live discharge from first AKI hospitalization in 2013 for Optum Clinformatics™ patients aged 22+, (a) overall, (b) by age, (c) by race, and (d) by CKD and DM
 Figure 5.8Cumulative probability of death-censored ESRD, death, and the composite of death or ESRD within one year of live discharge from first AKI hospitalization occurring in 2013-2014
 Figure 5.9Cumulative probability of a claim for an outpatient nephrology visit within six months of live discharge from first AKI hospitalization, overall and by CKD, DM, 2005-2014
 Table BICD-9-CM codes for Chronic Kidney Disease (CKD) stages
 Figure 5.10Renal status one year following discharge from AKI hospitalization in 2013-2014, among surviving patients without kidney disease prior to AKI hospitalization, by CKD stage and ESRD status
 Figure 5.11Hospital discharge status of first hospitalization for Medicare patients aged 66+ (a) with diagnosis of AKI during stay, and (b) without diagnosis of AKI during stay, 2015
Download
Search This Page
Search All
Translate

Chapter 5: Acute Kidney Injury

  • In 2015, 4.3% of Medicare fee-for-service beneficiaries experienced a hospitalization complicated by Acute Kidney Injury (AKI); this appears to have plateaued since 2011 (Figure 5.1). The 2015 Optum Clinformatics™ population showed a similar trend—0.3% had an AKI hospitalization (Figure 5.2).
  • Among patient’s hospitalization of Department of Veterans Affairs’ (VA) which did not have diagnosis of AKI, 15% of them had an actual AKI defined using serum creatinine-based criteria per the KDIGO guideline (Table A). This proportion is 13.4%, 0.5% and 1.2% for Stage 1, Stage 2, and Stage 3 AKI (Table 5.2).
  • In 2013, Medicare patients aged 66 years and older who were hospitalized for AKI had a 35% cumulative probability of a recurrent AKI hospitalization within one year (Figure 5.6.a). For Optum Clinformatics™ patients aged 22 years and older, the probability of recurrent AKI hospitalization was 23% (Figure 5.7.a).
  • Among these older Medicare patients, 28% were given an initial diagnosis of CKD in the year following an AKI hospitalization (Figure 5.10.a). In the Optum Clinformatics™ population, 19% of patients with an AKI hospitalization were newly classified as having CKD in the subsequent year (Figure 5.10.b).
  • Among Medicare patients aged 66 years and older with a first AKI hospitalization in 2015, the in-hospital mortality rate was 8.7%, or 13.7% when including discharge to hospice. Comparable mortality rates for non-AKI hospitalizations were 2.1% and 4.2%. Less than half of all patients returned to their home on discharge, as compared to two-thirds of non-AKI patients, while 30.6% were discharged to an institution such as a rehabilitation or skilled nursing facility. About one-quarter of non-AKI patients are discharged to rehabilitation or skilled nursing facilities (Figure 5.11).

Introduction

Acute kidney injury (AKI) is now recognized as a major risk factor for the development of chronic kidney disease (CKD). This is obvious in cases of severe, dialysis-requiring AKI where patients fail to recover kidney function. Indeed, acute tubular necrosis without recovery is the primary diagnosis for 2% to 3% of incident end-stage renal disease (ESRD) cases annually. Yet, this represents a small fraction of the kidney disease burden resulting from AKI. Studies have demonstrated significantly increased long-term risk of CKD and ESRD following AKI, even after initial recovery of function (Heung, 2012). Furthermore, this relationship is bidirectional—CKD patients are at substantially higher risk of suffering an episode of AKI. As a result, AKI is frequently superimposed on CKD, and plays a key role in CKD progression.

This year we again present data from three sources: the Medicare 5% sample, the Optum Clinformatics™ Data Mart dataset (from OptumInsight, representing claims from a large U.S. national health insurance company), and national data from the U.S. Department of Veterans Affairs (VA) health system. Medicare and Optum Clinformatics™ administrative data do not contain clinical or biochemical data with which to identify an AKI episode using the consensus criteria based on changes in serum creatinine or urinary output. In these data sources, episodes of AKI were identified using ICD-9-CM and ICD-10-CM (International Classification of Diseases, Ninth/Tenth Revision, Clinical Modification) diagnosis codes from claims. While this approach carries a high degree of specificity, an important limitation of this indirect method is poor sensitivity, generally <30%, and even lower for less severe cases of AKI. In particular, trends in AKI incidence must be interpreted with caution due to the possibility of “code creep”, whereby non-clinical factors such as changing billing thresholds or increased awareness and recognition of AKI increase the likelihood of administrative coding for AKI. Thus, a rising incidence of AKI may represent a true increase in cases, an increased likelihood to code for AKI, or a combination of both factors. In addition, a lower threshold for coding would lead to identification of less severe episodes and an apparent decrease in the rate of associated adverse outcomes.

In contrast to Medicare and Optum Clinformatics™, VA data contain clinical information to identify episodes of AKI through serum creatinine-based criteria. We present some data from the VA population to illustrate the potential gap between AKI episodes identified by administrative coding versus clinical data.

We begin this chapter by exploring trends in hospitalizations that became complicated by AKI, and describing the characteristics of those patients. We refer to “AKI hospitalizations” as any hospitalization during which there was a diagnosis of AKI; the AKI diagnosis was not necessarily the primary or admitting diagnosis. We focus on hospitalizations because the occurrence of AKI exclusively in the community is uncommon and often unrecognized. Next, we explore the risk of re-hospitalization with recurrent AKI, and describe follow-up care after an episode. We end by examining the impact of AKI on outcomes, including subsequent CKD status and patient disposition after an AKI hospitalization.

Methods

Starting with the 2013 claim year, the USRDS Coordinating Center has received the Medicare 5% sample from the Medicare Chronic Conditions Warehouse, a different data source than in previous years. This has coincided with a subsequent decrease in AKI hospitalizations, and we cannot rule out that this is an artifact of the differing source of the Medicare 5% data files. Conclusions regarding trends should be made in this context.

For the Medicare data, we often present results for those aged 66 and older. This allows a full year of Medicare eligibility (ages 65-66) for us to assess the patient’s CKD and diabetes mellitus (DM) status prior to the hospitalization within which AKI occurred.

In contrast to the Medicare data, we also present figures and tables from the commercial insurance plans of a large national U.S. health insurance company, as included in the Optum Clinformatics™ Data Mart from OptumInsight. These data represent mainly working-age people and their minor dependents.

We present results only for patients aged 22 and older. In Volume 1, Chapter 2: Identification and Care of Patients with CKD see Table 2.1 for demographic characteristics of the Optum Clinformatics™ population (all ages) and Table 2.2 (ages 22-64) and Table 2.3 (all ages) for the prevalence of CKD and related conditions. Additionally, Table 5.2 of this chapter uses data from all patients hospitalized at a VA hospital during fiscal year 2015, to show AKI as defined by serum creatinine measurements and staged as outlined in the KDIGO clinical practice guideline for AKI (KDIGO, 2012). Note that urine output data was not available, so identification of AKI episodes did not include the KDIGO criteria related to urine output.

Age a major risk factor for AKI. Each of the included datasets have interactions between sex and age that are important to keep in mind when comparing differences in AKI by sex. Within both Optum Clinformatics™ and the VA, women were younger on average than men. In Optum Clinformatics™, 56% of women were between the ages of 22 and 39, compared to only 19.4 percent of men. Among VA patients with at least one outpatient visit, 82% of men were aged 60 and older compared to only 46.6% of women. Conversely, women in the Medicare 5% sample were older, on average. Women had a mean age of 77.2 years while for men it was 75.5 years, and a higher proportion of women (20.4%) than men (13.2%) were aged 85 and older.

Note that the analyses for all figures except Figure 5.11 were based on all beneficiaries meeting the specified inclusion criteria. In Figure 5.11, we excluded those beneficiaries who were admitted from a long-term care facility to the inpatient setting where the AKI hospitalization occurred. Therefore, the category of institution in this figure includes only those newly admitted following a hospitalization.

Details of this data are described in the Data Sources section of the CKD Analytical Methods chapter. Also see the CKD Analytical Methods section of the CKD Analytical Methods chapter for an explanation of the analytical methods used to generate the study cohorts, figures, and tables in this chapter. Microsoft Excel and PowerPoint files containing the data and graphics for these figures and tables are available to download from the USRDS website.

Characteristics of Patients with Acute Kidney Injury

The percentage of Medicare fee-for-service patients with an AKI hospitalization has risen over the past decade, but appears to have plateaued near 4.0% since 2011 (Figure 5.1). Of note, the increase was mostly seen in patients who did not require an intensive care unit (ICU) stay during their hospitalization. Over the same period, the proportion of AKI patients requiring inpatient dialysis initially declined, but also appears to have become stable since 2011. Not surprisingly, a higher proportion of patients with an ICU stay had AKI requiring dialysis, compared to patients without an ICU stay. Figure 5.2 reveals very similar trends in the Optum Clinformatics™ population, although the overall percentage of patients with an AKI hospitalization was far lower for these younger patients, at 0.3% in 2015. Taken together, these findings seem to support “code creep”: while the threshold for defining (and thus coding for) AKI has decreased over the last 10 years, the threshold for dialysis initiation has likely remained stable.

Figure 5.1 Percent of Medicare patients aged 66+ (a) with at least one AKI hospitalization, and (b) percent among those with an AKI hospitalization who required dialysis, and by whether an intensive care unit (ICU) stay was required, 2005-2015

Figure 5.2 Percent of Optum Clinformatics™ patients aged 22+ (a) with at least one AKI hospitalization, and (b) percent among those with an AKI hospitalization who required dialysis, 2005-2015

Table 5.1 presents demographic and comorbidity characteristics of Medicare and Optum Clinformatics™ patients with AKI in 2015. AKI occurs commonly in older adults, and the incidence rises with age. In the fee-for-service Medicare population, over half of all patients with an AKI hospitalization were aged 80 or older. In both the Medicare and ClinformaticsTM populations, a higher proportion of Black/African American patients had AKI compared to Whites or Asians. Diabetes and pre-existing CKD are recognized as two major risk factors for AKI; at least one of these risk factors was present in nearly 58% of Medicare patients with an AKI hospitalization and 21% of patients had both. Even in the younger Optum Clinformatics™ population, about 34% of patients with an AKI hospitalization had either DM, CKD, or both.

Table 5.1 Characteristics of Medicare and Optum Clinformatics™ patients with at least one hospitalization, by age, sex, race, CKD, DM, and presence of AKI, 2015

Table 5.2 presents characteristics of VA patients who had an AKI hospitalization. Here, AKI was defined using serum creatinine-based criteria per the KDIGO guideline (Table A). For VA patients with diabetes, about 28.2% of them had AKI hospitalization as defined by KDIGO criteria. This percentage increased to 43.7% among CKD patients, and 54.4% among patients with both DM and CKD.

Table A KDIGO definition and staging of acute kidney injury

Table 5.2 Characteristics of Veterans Affairs patients aged 22+ with at least one hospitalization, by age, sex, race, CKD, DM, presence and stage of AKI, defined by serum creatinine, FY 2015

As shown in Figure 5.3, rates of AKI were strongly influenced by age. Among fee-for-service Medicare patients in 2015, the rate of AKI for those aged 66-69 was 26.8 per 1,000 patient years, increasing to 37.4, 55.4, 77.1, and 110.5 for those aged 70-74, 75-79, 80-84, and 85 years and older. Between 2005 and 2012, unadjusted rates of AKI increased for all age groups. Data from 2011 to 2015 showed a plateau or slight decrease in AKI rates for patients less than 80 years, however, rates continued to rise in older patients. Among Optum Clinformatics™ patients, the overall group AKI rate increased over time, peaking at 4.2 per 1,000 patient years in 2015. For the subgroup aged 66 and older, the 2011 rate was 27.1 per 1,000 patient-years and remained somewhat stable at 26.6 per 1,000 in 2015.

Figure 5.3 Unadjusted rates of hospitalization with AKI, per 1,000 patient-years at risk, by age, 2005-2015

Figure 5.4 highlights differences in AKI rates by race. In 2015, among fee-for-service Medicare patients aged 66 and older, the incidence rate for those of Black race was 90.2 per 1,000 patient years at risk compared to 53.4 and 43, in Whites, and individuals of other races. A similar relationship was observed in the Optum Clinformatics™ population, albeit at much lower rates: 6.1, 4.5, and 2.8 per 1,000 patient years at risk in Blacks, Whites, and individuals of other races.

Figure 5.4 Unadjusted rates of hospitalization with AKI, per 1,000 patient-years at risk, by race, 2005-2015

As shown in Figure 5.5, incidence rates for AKI also varied substantially by underlying comorbidity. In 2015, Medicare patients with DM but no known CKD had an AKI incidence rate of 65.3 per 1,000 patient years compared to 29.7 per 1,000 patient years in non-diabetic, non-CKD patients. Non-diabetic patients with CKD experienced an AKI incidence rate of 179.3 per 1,000 patient years, while the rate in patients with both DM and CKD was 281.4 per 1,000. That is, about 28% of Medicare patients with both CKD and DM experienced a hospitalization with AKI in each year.

The Optum Clinformatics™ population showed similar relationships. Patients with both CKD and DM experienced the highest rates of AKI hospitalization at 142.1 per 1,000 patient years. However, their overall rates were much lower, presumably reflecting the younger age range in this population.

Figure 5.5 Unadjusted rates of hospitalization with AKI, per 1,000 patient-years at risk, by CKD, and DM, 2005-2015

Re-hospitalization Associated with Acute Kidney Injury

Figures 5.6 and 5.7 show the probability of a patient’s recurrent AKI hospitalization after their live discharge from an initial AKI hospitalization. Among 2013 Medicare patients aged 66 and older the overall probability of a recurrent AKI event was 0.35 in the next 12 months and 0.48 by 24 months, as shown in Figure 5.6.a. Among Optum Clinformatics™ patients, these probabilities were 0.23 and 0.31. In contrast to first episodes, the rate of recurrent AKI was relatively similar across age groups in the fee-for-service Medicare population (Figure 5.6.b). Interpretation of this finding is limited, however, because of the effect of death censoring, which was higher in older age groups.

In both the Medicare and Optum Clinformatics™ populations, Blacks had a higher probability of recurrent AKI compared to Whites or individuals of other races (Figures 5.6.c and 5.7.c). Similarly, having either DM or CKD was associated with an increased probability for recurrent AKI compared to having neither (see Figures 5.6.d and 5.7.d). The highest probability for recurrent AKI was for patients with both DM and CKD, reaching 0.59 by 24 months among Medicare patients and 0.45 among Optum Clinformatics™ patients. In contrast, Medicare patients with neither comorbidity had a cumulative probability for recurrent AKI hospitalization of 0.30 by 24 months, while their Optum Clinformatics™ counterparts had a probability of 0.21 by 24 months.

Siew et al. (2016) examined recurrent AKI for VA patients in 2003 and 2010 who survived their first AKI hospitalization (n=11,683). Of these, 8.5% had a second AKI episode within 30 days, 14.6% within 90 days, 19.5% within 180 days, and 25.3% with 12 months. AKI was defined according to KDIGO criteria using serum creatinine.

Figure 5.6 Cumulative probability of a recurrent AKI hospitalization within two years of live discharge from first AKI hospitalization in 2013 for Medicare patients aged 66+, (a) overall, (b) by age, (c) by race, and (d) by CKD and DM

Figure 5.7 Cumulative probability of a recurrent AKI hospitalization within two years of live discharge from first AKI hospitalization in 2013 for Optum Clinformatics™ patients aged 22+, (a) overall, (b) by age, (c) by race, and (d) by CKD and DM

Patient Care and Outcomes

Poor short-term outcomes for AKI, including hospital mortality, are well recognized. Figure 5.8 illustrates that survivors of an AKI hospitalization who are discharged alive continued to face significant risk for adverse outcomes. Among survivors of an AKI hospitalization in 2013-2014, the overall probability of developing ESRD in the following year was about 2% in the Medicare fee-for-service population aged 66 and older, and 5% in the Optum Clinformatics™ population. In this same period, the probability of death was 41.3% and 7.3% in the Medicare and Optum Clinformatics™ populations.

Figure 5.8 Cumulative probability of death-censored ESRD, death, and the composite of death or ESRD within one year of live discharge from first AKI hospitalization occurring in 2013-2014

In 2014, 16% of Medicare patients discharged alive from an AKI hospitalization had outpatient nephrology follow-up within the next six months, while 17% of Optum Clinformatics™ patients had follow-up over the same period. As shown in Figure 5.9, follow-up rates varied by comorbidity. Among patients with AKI superimposed on pre-existing CKD, but without DM, 19% of Medicare and 24% of Optum Clinformatics™ patients were seen by a nephrologist within six months following discharge. For patients with both CKD and DM, these proportions rose to 25% and 32. In contrast, just 3% of Medicare and 6% of Optum Clinformatics™ AKI patients without DM or CKD were seen by a nephrologist by six months following an AKI hospitalization.

Trends over the past decade showed a slight decrease in post-AKI hospitalization nephrology follow-up for both the Medicare and Optum Clinformatics™ populations. This may once again reflect code creep: with milder cases of AKI are captured by diagnosis, but may be the least likely to require nephrology referral.

Figure 5.9 Cumulative probability of a claim for an outpatient nephrology visit within six months of live discharge from first AKI hospitalization, overall and by CKD, DM, 2005-2014

Changes in CKD Status after Acute Kidney Injury

CKD status changes significantly in the year following an AKI hospitalization, as shown in Figure 5.10. Among Medicare patients without baseline CKD, nearly 28% were reclassified as having some degree of CKD, including 0.2% being declared ESRD. In the Optum Clinformatics™ population, about 19% of patients with an AKI hospitalization were newly classified as having CKD in the subsequent year, and 2.2% were given a diagnosis of ESRD. Although the percent of patients with ESRD is markedly higher in the younger Optum Clinformatics™ population as compared to Medicare patients, it is important to note that these are proportions of surviving patients only. Table B shows the ICD-9-CM diagnosis codes used to define stages of chronic kidney disease for Figure 5.10.

Table B ICD-9-CM codes for Chronic Kidney Disease (CKD) stages

Figure 5.10 Renal status one year following discharge from AKI hospitalization in 2013-2014, among surviving patients without kidney disease prior to AKI hospitalization, by CKD stage and ESRD status

In Figure 5.11, we examined the status and disposition of 2015 Medicare AKI patients once they were discharged from the hospital. After excluding patients admitted from a skilled nursing facility (SNF; n=1,890, leaving 53,710 AKI discharges), among AKI patients aged 66 and older about 48% were discharged directly to their home. Mortality (including those discharged to hospice) was 13.7%, while 30.6% of patients were discharged to institutions such as short-term SNFs, rehabilitation hospitals, or long-term care facilities. By comparison, among hospitalized Medicare patients without a diagnosis of AKI (excluding those admitted from a SNF, n= 2,979, leaving 170,626 discharges), 68% returned home and around 23% were discharged to institutions.

Figure 5.11 Hospital discharge status of first hospitalization for Medicare patients aged 66+ (a) with diagnosis of AKI during stay, and (b) without diagnosis of AKI during stay, 2015

References

Chawla LS, Eggers PW, Star RA, Kimmel PL. Acute kidney injury and chronic kidney disease as interconnected syndromes. N Engl J Med 2014;371:58-66.

Grams ME, Waikar SS, MacMahon B, Whelton S, Ballew SH, Coresh J. Performance and limitations of administrative data in the identification of AKI. Clin J Am Soc Nephrol 2014;9:682-689.

Heung M, Chawla LS. Predicting progression to chronic kidney disease after recovery from acute kidney injury. Curr Opin Nephrol Hypertens 2012;21:628–634.

Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney Injury Workgroup. KDIGO clinical practice guideline for acute kidney injury. Kidney Int 2012;2:1-138.

Siew ED, Parr SK, Abdel-Kader K, Eden SK, Peterson JF, Bansal N, Hung AM, Fly J, Speroff T, Ikizler RA, Matheny EW. Predictors of Recurrent AKI. JASN 2016;27: 1190-1200.

Waikar SS, Wald R, Chertow GM, Curhan GC, Winkelmayer WC, Liangos O, Sosa MA, Jaber BL. Validity of international classification of diseases, ninth revision, clinical modification codes for acute renal failure. J Am Soc Nephrol 2006;17:1688–1694.