Positive Predictive Values of International Classification of Diseases, 10th Revision Coding Algorithms to Identify Patients With Autosomal Dominant Polycystic Kidney Disease

Kalatharan, Vinusha; Pei, York; Clemens, Kristin K.; McTavish, Rebecca K; Dixon, Stephanie N.; Rochon, Matthew; Nash, Danielle M.; Jain, Arsh K.; Sarma, Sisira; Zaleski, Andrew; Lum, Andrea; Garg, Amit X.

doi:10.1177/2054358116679130

Cited by 9 publications

(16 citation statements)

References 15 publications

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“…However, the validity of our method is supported by a recent study that found ICD-10 coding in administrative data could identify adult patients who meet strict clinical criteria for ADPKD as assessed through medical chart review [31]. A sensitivity analyses was performed to compare algorithms for detecting ADPKD in large populations.…”

Section: Methodsmentioning

confidence: 95%

Analysis of Nationwide Data to Determine the Incidence and Diagnosed Prevalence of Autosomal Dominant Polycystic Kidney Disease in the USA: 2013–2015

et al. 2019

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Background: This study addresses an important gap, as it is the first US nationwide, epidemiologic study of ADPKD incidence and prevalence. Summary: This 3-year, observational study utilized data from Truven Health MarketScan® administrative claims, as well as cross-sectional data from the National Ambulatory Medical Care Survey (NAMCS). We estimated the annual incidence and diagnosed prevalence using population-based data on over 170 million de-identified patients to provide the most current epidemiologic estimates available. The ADPKD-diagnosed prevalence was 4.3 per 10,000 in the NAMCS, which closely corresponded with age-adjusted rates from patients with either commercial insurance or employer-sponsored Medicare supplemental insurance. The annual incidence was 0.62 per 10,000. Both nationwide data sets indicate that approximately 140,000 patients are currently diagnosed in the USA. We also found significant differences by gender and age. Females are nearly twice as likely as males to be diagnosed in early adulthood, while the incidence in males was highest in those aged 65 years or older. ADPKD appears more likely to be diagnosed in men after disease progression or the development of chronic kidney disease. Key Messages: Our results revealed striking age and gender differences in the incidence of ADPKD. Young women are diagnosed with ADPKD at nearly twice the rate of young men, perhaps due to the use of ultrasound in women during child-bearing years. This points to a need for increased recognition of ADPKD, with an emphasis on younger men in particular. ADPKD has been inaccurately perceived as a common condition based on misinterpretation of early epidemiologic data (1957) confirmed by our data and recent European data. ADPKD affects approximately 140,000 patients in the USA and meets the criterion for a rare disease. Our results indicate a need for further study of gender and ADPKD diagnosis, progression, management, and outcomes.

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Section: Methodsmentioning

confidence: 95%

Analysis of Nationwide Data to Determine the Incidence and Diagnosed Prevalence of Autosomal Dominant Polycystic Kidney Disease in the USA: 2013–2015

et al. 2019

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“…Literature on the validity of administrative coding algorithms related to ADPKD is scarce. To date, only one study assessed the positive predictive value of ICD-9 code 75312 (polycystic kidney disease, unspecified) and another study described the positive predictive value of ICD-10 coding algorithms related to ADPKD [ 3 , 4 ]. Both studies showed that hospital encounter codes related to ADPKD have a high positive predictive value when applied in the general population, meaning that a high percentage of patients with ADPKD codes truly have ADPKD [ 3 , 4 ].…”

Section: Discussionmentioning

confidence: 99%

“…To date, only one study assessed the positive predictive value of ICD-9 code 75312 (polycystic kidney disease, unspecified) and another study described the positive predictive value of ICD-10 coding algorithms related to ADPKD [ 3 , 4 ]. Both studies showed that hospital encounter codes related to ADPKD have a high positive predictive value when applied in the general population, meaning that a high percentage of patients with ADPKD codes truly have ADPKD [ 3 , 4 ]. To the best of our knowledge, our study is the first to estimate the sensitivity and specificity of administrative coding algorithms related to ADPKD in a specialized cystic kidney disease clinic population and provides insight into whether these algorithms differentiate patients with ADPKD from patients with other cystic conditions.…”

Section: Discussionmentioning

confidence: 99%

“…We must first ensure that ADPKD administrative coding algorithms can reliably identify patients with ADPKD and distinguish them from patients with similar conditions before using them. To date, two studies have assessed the performance of ICD-9 and ICD-10 codes related to ADPKD [ 3 , 4 ]. Both studies showed that a high percentage of patients identified with a code for ADPKD truly had ADPKD (i.e.…”

Section: Introductionmentioning

confidence: 99%

“…Both studies showed that a high percentage of patients identified with a code for ADPKD truly had ADPKD (i.e. a high-positive predictive value) [ 3 , 4 ]. However, these studies did not assess the sensitivity and specificity of these codes or the performance of the OHIP diagnosis codes.…”

Section: Introductionmentioning

confidence: 99%

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Diagnostic accuracy of administrative codes for autosomal dominant polycystic kidney disease in clinic patients with cystic kidney disease

Kalatharan

McArthur²,

Nash³

et al. 2020

Clinical Kidney Journal

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Background The ability to identify patients with autosomal dominant polycystic kidney disease (ADPKD) and distinguish them from patients with similar conditions in healthcare administrative databases is uncertain. We aimed to measure the sensitivity and specificity of different ADPKD administrative coding algorithms in a clinic population with non-ADPKD and ADPKD kidney cystic disease. Methods We used a dataset of all patients who attended a hereditary kidney disease clinic in Toronto, Ontario, Canada between 1 January 2010 and 23 December 2014. This dataset included patients who met our reference standard definition of ADPKD or other cystic kidney disease. We linked this dataset to healthcare databases in Ontario. We developed eight algorithms to identify ADPKD using the International Classification of Diseases, 10th Revision (ICD-10) codes and provincial diagnostic billing codes. A patient was considered algorithm positive if any one of the codes in the algorithm appeared at least once between 1 April 2002 and 31 March 2015. Results The ICD-10 coding algorithm had a sensitivity of 33.7% [95% confidence interval (CI) 30.0–37.7] and a specificity of 86.2% (95% CI 75.7–92.5) for the identification of ADPKD. The provincial diagnostic billing code had a sensitivity of 91.1% (95% CI 88.5–93.1) and a specificity of 10.8% (95% CI 5.3–20.6). Conclusions ICD-10 coding may be useful to identify patients with a high chance of having ADPKD but fail to identify many patients with ADPKD. Provincial diagnosis billing codes identified most patients with ADPKD and also with other types of cystic kidney disease.

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Validity of administrative data in identifying complex surgical site infections from a population-based cohort after primary hip and knee arthroplasty in Alberta, Canada

Rennert-May

Manns

Smith

et al. 2018

American Journal of Infection Control

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Positive Predictive Values of International Classification of Diseases, 10th Revision Coding Algorithms to Identify Patients With Autosomal Dominant Polycystic Kidney Disease

Cited by 9 publications

References 15 publications

Analysis of Nationwide Data to Determine the Incidence and Diagnosed Prevalence of Autosomal Dominant Polycystic Kidney Disease in the USA: 2013–2015

Analysis of Nationwide Data to Determine the Incidence and Diagnosed Prevalence of Autosomal Dominant Polycystic Kidney Disease in the USA: 2013–2015

Diagnostic accuracy of administrative codes for autosomal dominant polycystic kidney disease in clinic patients with cystic kidney disease

Validity of administrative data in identifying complex surgical site infections from a population-based cohort after primary hip and knee arthroplasty in Alberta, Canada

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