Development and Validation of Claims-Based Algorithms for Conjunctivitis and Keratitis.

IF 2.4 4区医学 Q3 PHARMACOLOGY & PHARMACY Pharmacoepidemiology and Drug Safety Pub Date : 2024-11-01 DOI:10.1002/pds.70052

Andrea K Chomistek, Jessica M Franklin, Rachel E Sobel, Andrea F Marcus, Sarah-Jo Sinnott, Stephen M Ezzy, Robert V Gately, Jeannette Green, Ashley Howell, Ihtisham Sultan, Esen K Akpek, Florence T Wang

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Abstract

Background: Ocular surface disorders have been reported among patients with various medical conditions, including atopic dermatitis (AD). Nonetheless, validated algorithms to identify conjunctivitis and keratitis in claims data are lacking.

Objective: Develop validated, claims-based algorithms for conjunctivitis and keratitis among patients with AD using medical records.

Methods: Patients with AD were identified in a claims database between March 2017 and November 2019. Among these patients, candidate algorithms were developed that included diagnosis codes for conjunctivitis or keratitis, alone and in combination with ophthalmic treatments. Among patients who met ≥ 1 candidate algorithms, a subset was randomly selected for medical record review. Additionally, records from a random sample of patients with AD were reviewed to assess sensitivity. Overall, 341 records were sought and 262 adjudicated by an expert ophthalmologist. The positive predictive value (PPV) of each algorithm was calculated and compared to a pre-specified threshold of ≥ 70%.

Results: For conjunctivitis, the final algorithm was ≥ 1 conjunctivitis diagnosis (PPV = 81%, 95% confidence interval [CI]: 73%-87%). For keratitis, the final algorithm combined the following 2 candidate algorithms: ≥ 1 keratitis diagnosis and ≥ 1 dispensing of a topical antibiotic or antibiotic-steroid combination (PPV = 91%); and ≥ 1 keratitis diagnosis and ≥ 1 dispensing of an ophthalmic corticosteroid, topical immune-modulator, or topical NSAID (PPV = 68%) for an overall PPV of 80% (95% CI: 55%-93%).

Conclusion: The first claims-based algorithms to identify conjunctivitis and keratitis among AD patients were developed and validated. They are available for use in future studies, particularly to better understand conjunctivitis and keratitis occurrence among patients with AD.

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结膜炎和角膜炎索赔算法的开发与验证。

背景：据报道，患有特应性皮炎（AD）等各种疾病的患者都有眼表疾病。然而，在索赔数据中缺乏识别结膜炎和角膜炎的有效算法：利用医疗记录，针对 AD 患者中的结膜炎和角膜炎开发经过验证的、基于理赔的算法：在 2017 年 3 月至 2019 年 11 月期间的理赔数据库中识别出 AD 患者。在这些患者中，制定了包括结膜炎或角膜炎诊断代码的候选算法，包括单独或结合眼科治疗。在符合≥1种候选算法的患者中，随机抽取一个子集进行病历审查。此外，为了评估灵敏度，还对随机抽样的 AD 患者的病历进行了审查。总体而言，共查找了 341 份病历，并由眼科专家对其中的 262 份病历进行了裁定。计算了每种算法的阳性预测值（PPV），并与预先设定的≥70%的阈值进行了比较：结膜炎的最终算法是≥1 次结膜炎诊断（PPV = 81%，95% 置信区间 [CI]：73%-87%）。对于角膜炎，最终算法结合了以下 2 种候选算法：≥ 1 次角膜炎诊断和≥ 1 次局部抗生素或抗生素-类固醇复方制剂配药（PPV = 91%）；以及≥ 1 次角膜炎诊断和≥ 1 次眼用皮质类固醇、局部免疫调节剂或局部非甾体抗炎药配药（PPV = 68%），总 PPV 为 80%（95% 置信区间 [CI]：55%-93%）：我们开发并验证了首个基于索赔的算法，用于识别 AD 患者中的结膜炎和角膜炎。这些算法可用于未来的研究，尤其是更好地了解 AD 患者结膜炎和角膜炎的发生情况。

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来源期刊

Pharmacoepidemiology and Drug Safety 医学-药学

CiteScore

4.80

自引率

7.70%

发文量

173

审稿时长

3 months

期刊介绍： The aim of Pharmacoepidemiology and Drug Safety is to provide an international forum for the communication and evaluation of data, methods and opinion in the discipline of pharmacoepidemiology. The Journal publishes peer-reviewed reports of original research, invited reviews and a variety of guest editorials and commentaries embracing scientific, medical, statistical, legal and economic aspects of pharmacoepidemiology and post-marketing surveillance of drug safety. Appropriate material in these categories may also be considered for publication as a Brief Report. Particular areas of interest include: design, analysis, results, and interpretation of studies looking at the benefit or safety of specific pharmaceuticals, biologics, or medical devices, including studies in pharmacovigilance, postmarketing surveillance, pharmacoeconomics, patient safety, molecular pharmacoepidemiology, or any other study within the broad field of pharmacoepidemiology; comparative effectiveness research relating to pharmaceuticals, biologics, and medical devices. Comparative effectiveness research is the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition, as these methods are truly used in the real world; methodologic contributions of relevance to pharmacoepidemiology, whether original contributions, reviews of existing methods, or tutorials for how to apply the methods of pharmacoepidemiology; assessments of harm versus benefit in drug therapy; patterns of drug utilization; relationships between pharmacoepidemiology and the formulation and interpretation of regulatory guidelines; evaluations of risk management plans and programmes relating to pharmaceuticals, biologics and medical devices.