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Evaluation of code-based algorithms to identify pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension patients in large administrative databases.

ABSTRACT: Large administrative healthcare (including insurance claims) databases are used for various retrospective real-world evidence studies. However, in pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension, identifying patients retrospectively based on administrative codes remains challenging, as it relies on code combinations (algorithms) and the accuracy for patient identification of most of them is unknown. This study aimed to assess the performance of various algorithms in correctly identifying patients with pulmonary arterial hypertension or chronic thromboembolic pulmonary hypertension in administrative databases. A systematic literature review was performed to find publications detailing code-based algorithms used to identify pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension patients. PheValuator, a diagnostic predictive modelling tool, was applied to three US claims databases, yielding models that estimated the probability of a patient having the disease. These models were used to evaluate the performance characteristics of selected pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension algorithms. With increasing algorithm complexity, average positive predictive value increased (pulmonary arterial hypertension: 13.4-66.0%; chronic thromboembolic pulmonary hypertension: 10.3-75.1%) and average sensitivity decreased (pulmonary arterial hypertension: 61.5-2.7%; chronic thromboembolic pulmonary hypertension: 20.7-0.2%). Specificities and negative predictive values were high (?97.5%) for all algorithms. Several of the algorithms performed well overall when considering all of these four performance parameters, and all algorithms performed with similar accuracy across the three claims databases studied, even though most were designed for patient identification in a specific database. Therefore, it is the objective of a study that will determine which algorithm may be most suitable; one- or two-component algorithms are most inclusive and three- or four-component algorithms identify most precise pulmonary arterial hypertension or chronic thromboembolic pulmonary hypertension populations, respectively.

SUBMITTER: Sprecher VP

PROVIDER: S-EPMC7675881 | biostudies-literature | 2020 Oct-Dec

REPOSITORIES: biostudies-literature

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Evaluation of code-based algorithms to identify pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension patients in large administrative databases.

Sprecher Viviane P VP Didden Eva-Maria EM Swerdel Joel N JN Muller Audrey A

Pulmonary circulation 20201001 4

Large administrative healthcare (including insurance claims) databases are used for various retrospective real-world evidence studies. However, in pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension, identifying patients retrospectively based on administrative codes remains challenging, as it relies on code combinations (algorithms) and the accuracy for patient identification of most of them is unknown. This study aimed to assess the performance of various algorithm ...[more]

PMID: 33240487

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Project description:IntroductionPulmonary arterial hypertension (PAH) and chronic thromboembolic pulmonary hypertension (CTEPH) are rare, life-threatening diseases in which chronically elevated pressure in the pulmonary arteries results in vascular remodeling and right heart failure. Treatment goals are to improve patient functioning, exercise capacity, and symptoms; delay disease progression; normalize the right ventricular function; and, ultimately, improve survival. Therapeutic management centers on the affected physiologic pathways and includes endothelin receptor antagonists, phosphodiesterase-5 inhibitors, and prostacyclins. Recently, riociguat, a novel therapeutic agent that stimulates soluble guanylate cyclase via the nitric oxide pathway, was approved for the treatment of both PAH and CTEPH. Clinical trial data show that riociguat significantly improves exercise capacity as well as hemodynamic parameters in PAH/CTEPH.MethodsWe report on the early use of riociguat at our center-a large, metropolitan pulmonary hypertension treatment facility that cares for >250 patients with PAH/CTEPH. Through our initial clinical experience, we offer evidence on the benefits of riociguat in three patients with PAH associated with different etiologies, symptoms, and treatment goals.ResultsOverall, patients at our center who have received riociguat have experienced clinical benefits, including improvement in symptomatic and hemodynamic parameters, increase in 6-min walk distance, and improvement or stabilization of World Health Organization functional class. In several cases, initial response to riociguat has been encouraging and has helped patients reach their treatment goals. Riociguat appears to be well tolerated, with only one patient experiencing mild, self-limiting side effects.ConclusionNovel agents are continuously being introduced into the PAH/CTEPH armamentarium, and clinicians must decide how best to integrate them into their existing treatment algorithms. This case series offers initial evidence from our practice on the benefits of riociguat in optimizing hemodynamic and functional parameters. These benefits have been observed in PAH associated with different etiologies and functional status, and in both first-line and combination use.FundingBayer HealthCare Pharmaceuticals.

Dataset Information

Evaluation of code-based algorithms to identify pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension patients in large administrative databases.

Publications

Evaluation of code-based algorithms to identify pulmonary arterial hypertension and chronic thromboembolic pulmonary hypertension patients in large administrative databases.

Similar Datasets

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