Evaluation of claims-based computable phenotypes to identify heart failure patients with preserved ejection fraction

被引:21
作者
Cohen, Sarah S. [1 ]
Roger, Veronique L. [2 ]
Weston, Susan A. [2 ]
Jiang, Ruoxiang [2 ]
Movva, Naimisha [1 ]
Yusuf, Akeem A. [3 ]
Chamberlain, Alanna M. [2 ]
机构
[1] EpidStrategies, 1249 Kildaire Farm Rd,134, Cary, NC 27511 USA
[2] Mayo Clin, Dept Hlth Sci Res, Rochester, MN USA
[3] Amgen Inc, Ctr Observat Res, Thousand Oaks, CA 91320 USA
关键词
Administrative Data; Algorithm; Electronic Health Records; Heart failure; ADMINISTRATIVE DATA;
D O I
10.1002/prp2.676
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
The purpose of this analysis was to develop and validate computable phenotypes for heart failure (HF) with preserved ejection fraction (HFpEF) using claims-type measures using the Rochester Epidemiology Project. This retrospective study utilized an existing cohort of Olmsted County, Minnesota residents aged >= 20 years diagnosed with HF between 2007 and 2015. The gold standard definition of HFpEF included meeting the validated Framingham criteria for HF and having an LVEF >= 50%. Computable phenotypes of claims-type data elements (including ICD-9/ICD-10 diagnostic codes and lab test codes) both individually and in combinations were assessed via sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) with respect to the gold standard. In the Framingham-validated cohort, 2,035 patients had HF; 1,172 (58%) had HFpEF. One in-patient or two out-patient diagnosis codes of ICD-9 428.3X or ICD-10 I50.3X had 46% sensitivity, 88% specificity, 84% PPV, and 54% NPV. The addition of a BNP/NT-proBNP test code reduced sensitivity to 35% while increasing specificity to 91% (PPV = 84%, NPV = 51%). Broadening the diagnostic codes to ICD-9 428.0, 428.3X, and 428.9/ICD-10 I50.3X and I50.9 increased sensitivity at the expense of decreasing specificity (diagnostic code-only model: 87% sensitivity, 8% specificity, 56% PPV, 30% NPV; diagnostic code and BNP lab code model: 61% sensitivity, 43% specificity, 60% PPV, 45% NPV). In an analysis conducted to mimic real-world use of the computable phenotypes, any one in-patient or out-patient code of ICD-9 428/ICD-10 150 among the broader population (N = 3,755) resulted in lower PPV values compared with the Framingham cohort. However, one in-patient or two out-patient instances of ICD-9 428.0, 428.9, or 428.3X/ICD-10 150.3X or 150.9 brought the PPV values from the two cohorts closer together. While some misclassification remains, the computable phenotypes defined here may be used in claims databases to identify HFpEF patients and to gain a greater understanding of the characteristics of patients with HFpEF.
引用
收藏
页数:8
相关论文
共 15 条
[1]   Comparing methods for identifying patients with heart failure using electronic data sources [J].
Alqaisi, Fadi ;
Williams, L. Keoki ;
Peterson, Edward L. ;
Lanfear, David E. .
BMC HEALTH SERVICES RESEARCH, 2009, 9
[2]  
Benjamin EJ, 2017, CIRCULATION, V135, pE146, DOI [10.1161/CIR.0000000000000485, 10.1161/CIR.0000000000000558, 10.1161/CIR.0000000000000530]
[3]   Heart failure with preserved ejection fraction: pathophysiology, diagnosis, and treatment [J].
Borlaug, Barry A. ;
Paulus, Walter J. .
EUROPEAN HEART JOURNAL, 2011, 32 (06) :670-+
[4]   Administrative Data and the Philosopher's Stone: Turning Heart Failure Claims Data into Quantitative Assessment of Left Ventricular Ejection Fraction [J].
Bovitz, Tanya ;
Gilbertson, David T. ;
Herzog, Charles A. .
AMERICAN JOURNAL OF MEDICINE, 2016, 129 (02) :223-225
[5]   A NEW METHOD OF CLASSIFYING PROGNOSTIC CO-MORBIDITY IN LONGITUDINAL-STUDIES - DEVELOPMENT AND VALIDATION [J].
CHARLSON, ME ;
POMPEI, P ;
ALES, KL ;
MACKENZIE, CR .
JOURNAL OF CHRONIC DISEASES, 1987, 40 (05) :373-383
[6]   Development and Preliminary Validation of a Medicare Claims-Based Model to Predict Left Ventricular Ejection Fraction Class in Patients With Heart Failure [J].
Desai, Rishi J. ;
Lin, Kueiyu Joshua ;
Patorno, Elisabetta ;
Barberio, Julie ;
Lee, Moa ;
Levin, Raisa ;
Evers, Thomas ;
Wang, Shirley V. ;
Schneeweiss, Sebastian .
CIRCULATION-CARDIOVASCULAR QUALITY AND OUTCOMES, 2018, 11 (12) :e004700
[7]   A Practical, Global Perspective on Using Administrative Data to Conduct Intensive Care Unit Research [J].
Garland, Allan ;
Gershengorn, Hayley B. ;
Marrie, Ruth Ann ;
Reider, Nadia ;
Wilcox, M. Elizabeth .
ANNALS OF THE AMERICAN THORACIC SOCIETY, 2015, 12 (09) :1373-1386
[8]   A Contemporary Appraisal of the Heart Failure Epidemic in Olmsted County, Minnesota, 2000 to 2010 [J].
Gerber, Yariv ;
Weston, Susan A. ;
Redfield, Margaret M. ;
Chamberlain, Alanna M. ;
Manemann, Sheila M. ;
Jiang, Ruoxiang ;
Killian, Jill M. ;
Roger, Veronique L. .
JAMA INTERNAL MEDICINE, 2015, 175 (06) :996-1004
[9]   SURVIVAL AFTER THE ONSET OF CONGESTIVE-HEART-FAILURE IN FRAMINGHAM HEART-STUDY SUBJECTS [J].
HO, KKL ;
ANDERSON, KM ;
KANNEL, WB ;
GROSSMAN, W ;
LEVY, D .
CIRCULATION, 1993, 88 (01) :107-115
[10]   Validity of Heart Failure Diagnoses in Administrative Databases: A Systematic Review and Meta-Analysis [J].
McCormick, Natalie ;
Lacaille, Diane ;
Bhole, Vidula ;
Avina-Zubieta, J. Antonio .
PLOS ONE, 2014, 9 (08)