Development of algorithms for identifying patients with Crohn's disease in the Japanese health insurance claims database

Validated administrative data based ICD-10 algorithms for chronic conditions: A systematic review

OBJECTIVE

This systematic review aimed to identify ICD-10 based validated algorithms for chronic conditions using health administrative data.

METHODS

A comprehensive systematic literature search using Ovid MEDLINE, Embase, PsycINFO, Web of Science and CINAHL was performed to identify studies, published between 1983 and May 2023, on validated algorithms for chronic conditions using administrative health data. Two reviewers independently screened titles and abstracts and reviewed full text of selected studies to complete data extraction. A third reviewer resolved conflicts arising at the screening or study selection stages. The primary outcome was validated studies of ICD-10 based algorithms with both sensitivity and PPV of ≥70 %. Studies with either sensitivity or PPV <70 % were included as secondary outcomes.

RESULTS

Overall, the search identified 1686 studies of which 54 met the inclusion criteria. Combining a previously published literature search, a total of 61 studies were included for data extraction. The study identified 40 chronic conditions with high validity and 22 conditions with moderate validity. The validated algorithms were based on administrative data from different countries including Canada, USA, Australia, Japan, France, South Korea, and Taiwan. The algorithms identified included several types of cancers, cardiovascular conditions, kidney diseases, gastrointestinal disorders, and peripheral vascular diseases, amongst others.

CONCLUSION

With ICD-10 prominently used across the world, this up-to-date systematic review can prove to be a helpful resource for research and surveillance initiatives using administrative health data for identifying chronic conditions.

Prevalence Rates of Pneumococcal Vaccination in IBD and 30-Day Clinical Outcomes in Patients With IBD and Pneumococcal Disease Stratified by Receipt of Pneumococcal Vaccination: A Multi-Network Study

This study sought to assess outcomes associated with pneumococcal vaccination in adult inflammatory bowel disease patients. Results found unvaccinated patients had higher adverse outcomes, including greater risk of hospitalization, ICU admission, ventilation, and mortality. These findings underscore the importance of pneumococcal vaccination.

Validation studies of Japanese administrative health care data: A scoping review

PURPOSE

Large-scale administrative health care databases are increasingly being utilized for research. However, there has not been much literature that validated administrative data in Japan; a previous review identified six validation studies published between 2011 and 2017. We conducted a literature review of studies that assessed the validity of Japanese administrative health care data.

METHODS

We searched for studies published by March 2022 that compared individual-level administrative data with a reference standard from another data source, as well as studies that validated administrative data using other data within the same database. The eligible studies were also summarized based on characteristics which included data types, settings, reference standard used, numbers of patients, and conditions validated.

RESULTS

There were 36 eligible studies, including 29 that used external reference standard and seven that validated administrative data using other data within the same database. Chart review was the reference standard in 21 studies (range of the numbers of patients, 72-1674; 11 studies conducted in single institutions and nine studies in 2-5 institutions). Five studies used a disease registry as the reference standard. Diagnoses of cardiovascular diseases, cancer, and diabetes were frequently evaluated.

CONCLUSIONS

Validation studies are being conducted at an increasing rate in Japan, although most of them are small scale. Further large-scale comprehensive validation studies are necessary to effectively utilize the databases for research.

Strategies to Address Current Challenges in Real-World Evidence Generation in Japan

The generation of real-world evidence (RWE), which describes patient characteristics or treatment patterns using real-world data (RWD), is rapidly growing more popular as a tool for decision-making in Japan. The aim of this review was to summarize challenges to RWE generation in Japan related to pharmacoepidemiology, and to propose strategies to address some of these challenges. We first focused on data-related issues, including the lack of transparency of RWD sources, linkage across different care settings, definitions of clinical outcomes, and the overall assessment framework of RWD when used for research purposes. Next the study reviewed methodology-related challenges. As lack of design transparency impairs study reproducibility, transparent reporting of study design is critical for stakeholders. For this review, we considered different sources of biases and time-varying confounding, along with potential study design and methodological solutions. Additionally, the implementation of robust assessment of definition uncertainty, misclassification, and unmeasured confounders would enhance RWE credibility in light of RWD source-related limitations, and is being strongly considered by task forces in Japan. Overall, the development of guidance for best practices on data source selection, design transparency, and analytical methods to address different sources of biases and robustness in the process of RWE generation will enhance credibility for stakeholders and local decision-makers.

A Systematic Review of Crohn's Disease Case Definitions in Administrative or Claims Databases

BACKGROUND

We sought to review Crohn's disease (CD) case definitions that use diagnosis, procedure, and medication claims.

METHODS

We searched PubMed and Embase from inception through January 31, 2022, using terms related to CD, inflammatory bowel disease, administrative claims, or validity. Each article was scrutinized by 2 authors independently screening and abstracting data. Collected data included participant characteristics, case definition characteristics, and case definition validity. When diagnostic accuracy was provided for multiple case definitions, we extracted the case definition selected by the authors. All diagnostic accuracy characteristics were captured.

RESULTS

We identified 30 studies that evaluated a case definition using claims data to identify CD patients. The most common case definition included counts of diagnosis codes (57%) followed by a combination of diagnosis codes and medications (20%). All but 1 study validated the case definition with a medical chart review. In 2 studies, the patient's primary care provider completed a survey to confirm disease status. The positive predictive value of the case definitions ranged from 18% (≥1 code at a single U.S. health plan) to 100% (≥1 code plus a relevant prescription at a U.S. hospital). More complex case definitions (eg, ≥1 code + prescription or ≥2 codes) had lower variability in positive predictive value (≥80%) and specificity (≥85%) than the ≥1 code requirement.

CONCLUSIONS

Health services researchers should validate case definitions in their research cohorts. When such validation cannot be performed, we recommend using a more complex case definition. Studies without a validated CD case definition should use sensitivity analyses to confirm the robustness of their results.

Validity of Diagnostic Algorithms for Inflammatory Bowel Disease in Japanese Hospital Claims Data

Inflammatory bowel disease (IBD) diagnoses are increasing in Japan. Some patients have symptoms that are difficult to control, and further research on IBD is needed. Claims databases, which have a large sample size, can be useful for IBD research. However, it is unclear whether the International Classification of Diseases, Tenth Revision (ICD-10) codes alone can correctly identify IBD. We aimed to develop algorithms to identify IBD in claims databases. We used claims data from the Department of Gastroenterology, Tohoku University Hospital from 1 January 2016 to 31 December 2020. We developed 11 algorithms by combining the ICD-10 code, prescription drug, and workup information. We had access to the database which contains all the information for Crohn’s disease and ulcerative colitis patients who visited our department, and we used it as the gold standard. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value for each algorithm. We enrolled 19,384 patients, and among them, 1012 IBD patients were identified in the gold standard database. Among 11 algorithms, Algorithm 4 (ICD-10 code and ≥1 prescription drugs) showed a strong performance (PPV, 94.8%; sensitivity, 75.6%). The combination of an ICD-10 code and prescription drugs may be useful for identifying IBD among claims data.