Concept: Chronic Kidney Disease (CKD)

Introduction

This concept defines chronic kidney disease (CKD) as it was used in the Care of Manitobans Living with Chronic Kidney Disease deliverable by Chartier et al. (2015). CKD was identified through two different methods; one using administrative health data and the second using laboratory data. Each of these methods is described, including the age groups applied, the data sources for each definition, the code values and conditions identifying chronic kidney disease (CKD), and any additional conditions / restrictions that are applied.

"Chronic kidney disease (CKD) is a general term for heterogeneous disorders affecting kidney structure and function. CKD was previously perceived as a life-threatening condition affecting a small number of people, but it is now thought of as a common disorder requiring a public health strategy (Levey & Coresh, 2012). CKD encompasses disorders that damage the glomeruli (kidney filters) and lead to gradual long-term loss of kidney function. End stage kidney disease (ESKD) or kidney failure is the last and most debilitating stage of CKD." (Chartier et al. (2015).

Technical Definition of Chronic Kidney Disease Using Administrative Health Data

The technical definition of chronic kidney disease (CKD) using administrative health data described in Chartier et al. (2015) is as follows:


• Age Groups:
  
  • Children: 0-17 years old
    
  • Adults: 18 years and older
  
  
• Data Sources:
  
  • Hospital Abstracts data;
    
  • Medical Services (Physician Claims) data; and the
    
  • Drug Program Information Network (DPIN) data;
  
  
• Code Values and Conditions: - defined as Manitoba residents who had one of the following diagnoses / drug prescriptions within a three-year period, between April 1, 2009 – March 31, 2012:
  
  
  • two or more physician claims with diagnoses for hypertensive chronic kidney disease, hypertensive heart and chronic kidney disease, acute glomerulonephritis, nephrotic syndrome, chronic glomerulonephritis, nephritis and nephropathy not specified as acute or chronic, chronic kidney disease, renal failure (unspecified), renal sclerosis (unspecified), disorders resulting from impaired renal function, hydronephrosis, other disorders of kidney and ureter, congenital anomalies of urinary system (ICD-9-CM: 403, 404, 580, 581, 582, 583, 585, 586, 587, 588, 591, 593, 753) from the Medical Services data; or
    
    
  • one or more hospitalizations with diagnoses for diabetes with renal manifestations, hypertensive chronic kidney disease, hypertensive heart and chronic kidney disease, acute glomerulonephritis, nephrotic syndrome, chronic glomerulonephritis, nephritis and nephropathy not specified as acute or chronic, chronic kidney disease, renal failure (unspecified), renal sclerosis (unspecified), disorders resulting from impaired renal function, hydronephrosis, unspecified disorder of kidney and ureter, congenital anomalies of urinary system (ICD-9-CM: 250.4, 403, 404, 580, 581, 582, 583, 585, 586, 587, 588, 591, 593.9, 753; ICD-10-CA: E10.2, E11.2, I12, I13, N18, N19, N00-16, N25, N26, N28.82, N39.1, Q60-64) from the Hospital Abstracts data; or
    
    
  • one or more filled prescriptions for drugs used in CKD management, from the Drug Program Information Network (DPIN) data using either:
    
    
    • generic names: Vitamin B Complex/Vitamin C, Calcitriol, Epoetin Alfa, Sodium Polystyrene Sulfonate, Sevelamer HCL, Darbepoetin Alfa, Alfacalcidol, Cinacalcet HCL, Calcium Polystyrene sulphonate, Polystyrene Sod Sulfonate 454, doxercalciferol, paricalcitol, lanthanum, calcium acetate, calcium carbonate, peginesatide, replavite, lanthanum; or
      
    • Anatomical Therapeutic Chemical (ATC) drug classification system codes: A11CC04, A11CC03, H05BX03, H05BX02, V03AE02, V03AE03, V03AE04, B03XA01, B03XA02, B03XA04, V03AE03, V03AE01, A02AC01,A12AA04, H05BX01; or
      
    • Drug Identification Number (DINs): 00800970, 02017741, 80007498, 02240409, 02244872, 00646873, 00761281, 00667501, 01981708, 00722308, 00731250, 00644684, 00626341, 00643971, 00622710, 00802077, 00708704, 00530328, 00033197, 01902776

Technical Definition of Chronic Kidney Disease Using Laboratory Data

The technical definition of chronic kidney disease (CKD) using laboratory data described in Chartier et al. (2015) is as follows:


• Age Groups:
  
  • Children: 0-17 years old
    
  • Adults: 18 years and older
  
  
• Data Sources:
  
  • Diagnostic Services Manitoba (DSM) - now named Shared Health Diagnostic Services (SHDS) - Chemistry Data (2006/07 - 2011/12).
  
  
• Code Values and Conditions: - defined as Manitoba residents with:
  
  
  • two abnormal tests for proteinuria ( albumin-creatinine ratio (ACR) or protein-creatinine ratio (PCR) ) at least 90 days apart; or
    
  • one abnormal proteinuria test with a diagnosis of CKD based on administrative health data (see technical definition above); or
    
  • two abnormal Estimated Glomerular Filtration Rate (eGFR) tests at least 90 days apart; or
    
  • one abnormal eGFR test with a diagnosis of CKD based on administrative health data (see technical definition above).
  
  
• Conditions / Restrictions: - abnormal test values were defined as:
  
  
  • ACR >=3 mg/mmol or PCR >=15 mg/mmol;
    
  • eGFR values <90 for children and <60 for adults

Chronic Kidney Disease Prevalence

In Chartier et al. (2015), they used three methods to calculate the child and adult prevalence of CKD: (1) administrative and laboratory data, (2) laboratory data only, and (3) a capture-recapture method. Measuring CKD is challenging because no symptoms are apparent in the early stages. In addition, a CKD diagnosis may not be recorded when a patient has diagnoses for several other conditions. This may be particularly important for outpatients because outpatient claims are limited to a single diagnosis code.


1. They counted all CKD cases captured by the administrative data and by the laboratory data, added them together, and then divided by the total Manitoba population. This estimate will likely underestimate the true prevalence, because it will not include people in the early stages of CKD who have not been diagnosed by a physician.
   
2. They counted all CKD cases captured through the laboratory data and divided by all residents with laboratory data required to make a CKD diagnosis.
   
3. They used both the administrative and laboratory data to estimate CKD prevalence through a capture-recapture
   method. This approach is often used in estimating the size of animal populations in the wilderness (Brittain & Böhning, 2009). An example is estimating the number of turtles in a lake. We catch a sample of turtles, count them, mark them and release them back in the lake. We then catch another sample of turtles, count them and, among those caught, count how many are marked. The estimated number of turtles is calculated using the Chapman formula (eq. 5) (Chapman, 1951). We applied this capture-recapture method to our CKD data using the Chapman formula:

   CKD prevalence = [((N _{CKD cases in administrative data} + 1) * (N _{CKD cases in laboratory data} + 1)) ÷ (N _{CKD cases in both data} + 1)] - 1

For information on the results of this prevalence calculation, please see Chapter 3 Key Findings in the deliverable.