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

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          Abstract

          Purpose

          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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          Most cited references17

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          Taiwan’s National Health Insurance Research Database: past and future

          Abstract Taiwan’s National Health Insurance Research Database (NHIRD) exemplifies a population-level data source for generating real-world evidence to support clinical decisions and health care policy-making. Like with all claims databases, there have been some validity concerns of studies using the NHIRD, such as the accuracy of diagnosis codes and issues around unmeasured confounders. Endeavors to validate diagnosed codes or to develop methodologic approaches to address unmeasured confounders have largely increased the reliability of NHIRD studies. Recently, Taiwan’s Ministry of Health and Welfare (MOHW) established a Health and Welfare Data Center (HWDC), a data repository site that centralizes the NHIRD and about 70 other health-related databases for data management and analyses. To strengthen the protection of data privacy, investigators are required to conduct on-site analysis at an HWDC through remote connection to MOHW servers. Although the tight regulation of this on-site analysis has led to inconvenience for analysts and has increased time and costs required for research, the HWDC has created opportunities for enriched dimensions of study by linking across the NHIRD and other databases. In the near future, researchers will have greater opportunity to distill knowledge from the NHIRD linked to hospital-based electronic medical records databases containing unstructured patient-level information by using artificial intelligence techniques, including machine learning and natural language processes. We believe that NHIRD with multiple data sources could represent a powerful research engine with enriched dimensions and could serve as a guiding light for real-world evidence-based medicine in Taiwan.
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            Global and regional burden of stroke during 1990–2010: findings from the Global Burden of Disease Study 2010

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              Stroke: a global response is needed

              Worldwide, cerebrovascular accidents (stroke) are the second leading cause of death and the third leading cause of disability. 1 Stroke, the sudden death of some brain cells due to lack of oxygen when the blood flow to the brain is lost by blockage or rupture of an artery to the brain, is also a leading cause of dementia and depression. 2 Globally, 70% of strokes and 87% of both stroke-related deaths and disability-adjusted life years occur in low- and middle-income countries. 3 – 5 Over the last four decades, the stroke incidence in low- and middle-income countries has more than doubled. During these decades stroke incidence has declined by 42% in high-income countries. 3 On average, stroke occurs 15 years earlier in – and causes more deaths of – people living in low- and middle-income countries, when compared to those in high-income countries. 2 Strokes mainly affect individuals at the peak of their productive life. Despite its enormous impact on countries’ socio-economic development, this growing crisis has received very little attention to date. The risk factors for stroke are similar to those for coronary heart disease and other vascular diseases. Effective prevention strategies include targeting the key modifiable factors: hypertension, elevated lipids and diabetes. Risks due to lifestyle factors can also be addressed: smoking, low physical activity levels, unhealthy diet and abdominal obesity. 6 Combinations of such prevention strategies have proved effective in reducing stroke mortality even in some low-income settings. 7 , 8 Furthermore, as most guidelines are based on high-income country data, uncertainty remains regarding best management of stroke of unknown type in low- and middle-income countries. For example, in low- and middle-income countries, 34% of strokes (versus 9% in high-income countries) are of haemorrhagic subtype and up to 84% of stroke patients in low- and middle-income countries (versus 16% in high income countries) die within three years of diagnosis. 2 Current guidelines for the management of acute stroke recommend a course of treatment based on the diagnosis of ischaemic stroke (versus haemorrhagic stroke) made using computed tomography (CT) scanners. In low-resource settings, CT scanners are either unavailable or unaffordable, forcing clinicians to make difficult clinical decisions, such as whether to anticoagulate patients or not, and to what level to control their blood pressure without a means of distinguishing between ischaemic and haemorrhagic stroke. These patient management challenges, combined with inadequate rehabilitation services, lack of preventive measures, as well as poor understanding of the possible unique risk factors associated with stroke in low- and middle-income countries, may account for the disproportionately large stroke burden borne by these countries. The reasons for the younger age of onset, higher rates of haemorrhagic subtype and higher case fatality, are unknown. 2 Better understanding of the possible unique risk factors for this epidemic in low- and middle-income countries is urgently needed. The Stroke Investigative Research and Educational Network study is investigating the underlying risk factors for stroke occurrence, subtype and outcome among people of African ancestry. 9 Understanding the genetic basis for the interactions between risk factors can inform targeted prevention efforts, as part of a broader approach with four parts: surveillance, prevention, acute care and rehabilitation. 2 This type of integrated approach will generate the evidence base to produce the guidelines needed for stroke prevention, treatment and rehabilitation in low- and middle-income countries. In the July 2016 issue of the Bulletin, Aaron Berkowitz 10 examined current acute stroke management practice in low-resource settings and outlined items for consideration when developing treatment guidelines for patients with acute stroke of unknown etiology in settings where there are no CT scanners. Berkowitz emphasized the proven efficacy of supportive care measures, such as maintaining euglycaemia and euthermia, prevention of deep-vein thrombosis and aspiration, early mobilization and prompt seizure treatment for stoke patients. He recommended judicious use of aspirin and provided blood pressure parameters for stroke patients in these circumstances. He also emphasized the need for secondary prevention. Managing acute stroke in low-resource settings requires a novel approach, one that could restart the original WHO global stroke initiative, 11 as a collaboration between the World Health Organization (WHO), the World Stroke Organization and the World Federation of Neurology, to increase awareness of stroke, generate better surveillance data and guide better prevention and management. The WHO Package of essential noncommunicable disease interventions for primary health care in low-resource settings provides protocols for cardiovascular risk reduction and stroke prevention. 12 WHO will develop guidelines for the management of acute stroke in low- and middle-income countries, and aims to expand training programmes in stroke prevention, treatment and rehabilitation through its partners.
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                Author and article information

                Journal
                Clin Epidemiol
                clep
                clinepid
                Clinical Epidemiology
                Dove
                1179-1349
                25 September 2020
                2020
                : 12
                : 1007-1013
                Affiliations
                [1 ]Stroke Center and Department of Neurology, E-Da Hospital , Kaohsiung, Taiwan
                [2 ]School of Medicine for International Students, College of Medicine, I-Shou University , Kaohsiung, Taiwan
                [3 ]Institute of Clinical Medicine, College of Medicine, National Cheng Kung University , Tainan, Taiwan
                [4 ]Department of Neurology, Tainan Sin Lau Hospital , Tainan, Taiwan
                [5 ]School of Pharmacy, Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University , Tainan, Taiwan
                [6 ]Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital , Chiayi City, Taiwan
                [7 ]Department of Information Management and Institute of Healthcare Information Management, National Chung Cheng University , Chiayi County, Taiwan
                [8 ]Department of Nursing, Min-Hwei Junior College of Health Care Management , Tainan, Taiwan
                Author notes
                Correspondence: Sheng-Feng Sung Tel +886 5 276 5041 Ext 7283Fax +886 5 278 4257 Email richard.sfsung@gmail.com
                [*]

                These authors contributed equally to this work

                Author information
                http://orcid.org/0000-0002-8772-4073
                http://orcid.org/0000-0002-6253-8813
                Article
                273853
                10.2147/CLEP.S273853
                7524174
                33061648
                a8132383-a572-49e2-931b-cd2acc3d87cd
                © 2020 Hsieh et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                History
                : 25 July 2020
                : 03 September 2020
                Page count
                Figures: 1, Tables: 9, References: 20, Pages: 7
                Categories
                Original Research

                Public health
                administrative claims data,diagnosis,icd-10-cm,acute ischemic stroke
                Public health
                administrative claims data, diagnosis, icd-10-cm, acute ischemic stroke

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