Validation of Acute Ischemic Stroke Codes Using the International Classification of Diseases Tenth Revision

Alhajji, Mohamed; Kawsara, Akram; Alkhouli, Mohamad

doi:10.1016/j.amjcard.2020.01.004

Cited by 31 publications

(14 citation statements)

References 6 publications

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“…14 A more recent study also found that in a cohort of US patients, using I63* as the primary discharge diagnosis to identify patients admitted with AIS yielded a high PPV of 97.6%, which is equal to or even higher than the PPV values when ICD-9-CM codes were used for AIS. 15 However, the US cohort was limited to patients coded for AIS in the primary discharge diagnosis, making it impossible to assess other performance metrics such as sensitivity. Other possible explanations could include the influence of the nationwide quality improvement initiative on the quality of stroke care 16 and a newly implemented pay-for-performance program for AIS in Taiwan.…”

Section: Discussionmentioning

confidence: 99%

<p>Performance of ICD-10-CM Diagnosis Codes for Identifying Acute Ischemic Stroke in a National Health Insurance Claims Database</p>

Hsieh¹,

Hsieh²,

Tsai³

et al. 2020

CLEP

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The validity of the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coding for the identification of acute ischemic stroke (AIS) in Taiwan's National Health Insurance claims database has not been investigated. This study aimed to construct and validate the case definition algorithms for AIS based on ICD-10-CM diagnostic codes. Patients and Methods: This study identified all hospitalizations with ICD-10-CM code of I63* in any position of the discharge diagnoses from the inpatient claims database and all patients with a final diagnosis of AIS from the stroke registry between Jan 2018 and Dec 2019. Hospitalizations in the claims data that could be successfully linked to those in the registry data were regarded as true episodes of AIS. Otherwise, their electronic medical records and images were manually reviewed to ascertain whether they were true episodes of AIS. Using the true episodes of AIS as the reference standard, the positive predictive value (PPV) and sensitivity of various case definition algorithms for AIS were calculated. Results: A total of 1227 hospitalizations were successfully linked. Among the 155 hospitalizations that could not be linked, 54 were determined to be true episodes of AIS. Using ICD-10-CM code of I63* in any position of the discharge diagnoses to identify AIS yielded a PPV and sensitivity of 92.7% and 99.4%, respectively. The PPV increased to 99.8% with >12% decrease in the sensitivity when AIS was restricted to those with I63* as the primary diagnosis. When AIS was defined to be I63* as the primary, first secondary, or second secondary diagnosis, both PPV and sensitivity were greater than 97%. Conclusion: This study demonstrated the validity of various case definition algorithms for AIS based on ICD-10-CM coding and can provide a reference for future claims-based stroke research.

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Section: Discussionmentioning

confidence: 99%

<p>Performance of ICD-10-CM Diagnosis Codes for Identifying Acute Ischemic Stroke in a National Health Insurance Claims Database</p>

Hsieh¹,

Hsieh²,

Tsai³

et al. 2020

CLEP

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“…I63.419, I63.422, I63.431, I63.432, I63.441, I63.442, I63.449, I63.50, I63.511, I63.512, I63.519, I63.521, I63.522, I63.529, I63.531, I63.532, I63.539, I63.541, I63.542, I63.549, I63.59, I63.6, I63.8, I63.9). Those codes have been found to have a positive predictive value of 97.6% in identifying AIS encounters 11 . EST was identified by ICD‐10‐CM codes 03CG3Z7, 03CG3ZZ, 03CG4ZZ.…”

Section: Methodsmentioning

confidence: 99%

Mortality and functional outcomes of endovascular stroke therapy in the United States

Alqahtani

Osman

Harris³

et al. 2020

Cathet Cardio Intervent

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Background We sought to evaluate the nationwide trends in the characteristics and outcomes of for endovascular stroke therapy in contemporary practice. Methods We selected patients with acute ischemic stroke who underwent endovascular stroke therapy between 01 October 2015 and 30 September 2019 in a large academic consortium database. The end points of this study were (a) in‐hospital mortality and functional outcomes and, (b) predictors of poor functional outcome, defined as death or discharge to hospice, or to a long‐term nursing facility. Results Among the 22,193 included patients; 50.3% were females, and 66.5% were white. Mean age was 68±15 years. Poor functional outcomes occurred in 8,274 patients (37.4%), of whom 2,741 (12.4%) died in the hospital, 1,345 (6.1%) were discharged to hospice, and 4,188 (18.9%) were discharged to other long‐term facilities. Most common in‐hospital complications were mechanical ventilation (32.3%), intracranial hemorrhage (18.9%), and acute kidney injury (15.6%). Median total and intensive‐care length‐of‐stay were 7 days (IQR = 4–9), and 2 days (IQR = 1–4), respectively. Median cost was $36,609 (IQR = $26,034–$54,313). In a multi‐logistic regression analysis; age, hypertension, diabetes, anemia, heart failure, vascular disease, chronic pulmonary disease, renal insufficiency, Medicare/medicaid insurance, transfer from nonendovascular capable hospital, and low procedural volume independently predicted poor functional outcomes. Tissue plasminogen activator use was associated with better functional outcomes. Conclusion There is a substantial growth in the performance of endovascular stroke interventions in the United States in recent years, and those were associated with favorable short‐term outcomes.

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“…The result was similar to a previous study that reported, "ICD-10-CM code I63.9 was the most common code in patients who were coded for AIS but did not actually have an AIS." 29 In addition, the ICD-10 code I63 was commonly used for cerebral infarction as an outcome in an administrative database, and the PPV ranged from 52% to 100%. 30 Therefore, the ICD-10 code I63.x was considered to be the most appropriate diagnostic code for the identification of AIS with high validity in MID-NET ® .…”

Section: Discussionmentioning

confidence: 99%

Validity of identification algorithms combining diagnostic codes with other measures for acute ischemic stroke in MID‐NET®

Tanigawa

Kohama

Nonaka

et al. 2022

Pharmacoepidemiology and Drug

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Purpose: We aimed to develop a reliable identification algorithm combining diagnostic codes with several treatment factors for inpatients with acute ischemic stroke (AIS) to conduct pharmacoepidemiological studies using the administrative database MID-NET ® in Japan. Methods:We validated 11 identification algorithms based on 56 different diagnostic codes (International Classification of Diseases, Tenth Revision; ICD-10) using Diagnosis Procedure Combination (DPC) data combined with information on AIS therapeutic procedures added as "AND" condition or "OR" condition. The target population for this study was 366 randomly selected hospitalized patients with possible cases of AIS, defined as relevant ICD-10 codes and diagnostic imaging and prescription or surgical procedure, in three institutions between April 1, 2015 and March 31, 2017. We determined the positive predictive values (PPVs) of these identification algorithms based on comparisons with a gold standard consisting of chart reviews by experienced specialist physicians. Additionally, the sensitivities of them among 166 patients with the possible cases of AIS at a single institution were evaluated.Results: The PPVs were 0.618 (95% confidence interval [CI]: 0.566-0.667) to 0.909 (95% CI: 0.708-0.989) and progressively increased with adding or limiting information on AIS therapeutic procedures as "AND" condition in the identification algorithms. The PPVs for identification algorithms based on diagnostic codes I63.x were >0.8. However, the sensitivities progressively decreased to a maximum of $0.2 after adding information on AIS therapeutic procedures as "AND" condition. Conclusions:The identification algorithms based on the combination of appropriate ICD-10 diagnostic codes in DPC data and other AIS treatment factors may be useful to studies for AIS at a national level using MID-NET ® .

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Validation of Acute Ischemic Stroke Codes Using the International Classification of Diseases Tenth Revision

Cited by 31 publications

References 6 publications

<p>Performance of ICD-10-CM Diagnosis Codes for Identifying Acute Ischemic Stroke in a National Health Insurance Claims Database</p>

<p>Performance of ICD-10-CM Diagnosis Codes for Identifying Acute Ischemic Stroke in a National Health Insurance Claims Database</p>

Mortality and functional outcomes of endovascular stroke therapy in the United States

Validity of identification algorithms combining diagnostic codes with other measures for acute ischemic stroke in MID‐NET®

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