Development and Validation of a Model to Identify Alzheimer’s Disease and Related Syndromes in Administrative Data

Author(s): Adeline Gallini, David Jegou, Maryse Lapeyre-Mestre, Anaïs Couret, Robert Bourrel, Pierre-Jean Ousset, D Fabre, Sandrine Andrieu, Virginie Gardette*

Journal Name: Current Alzheimer Research

Volume 18 , Issue 2 , 2021


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Abstract:

Background: Administrative data are used in the field of Alzheimer’s Disease and Related Syndromes (ADRS), however their performance to identify ADRS is unknown.

Objective: i) To develop and validate a model to identify ADRS prevalent cases in French administrative data (SNDS), ii) to identify factors associated with false negatives.

Methods: Retrospective cohort of subjects ≥ 65 years, living in South-Western France, who attended a memory clinic between April and December 2013. Gold standard for ADRS diagnosis was the memory clinic specialized diagnosis. Memory clinics’ data were matched to administrative data (drug reimbursements, diagnoses during hospitalizations, registration with costly chronic conditions). Prediction models were developed for 1-year and 3-year periods of administrative data using multivariable logistic regression models. Overall model performance, discrimination, and calibration were estimated and corrected for optimism by resampling. Youden index was used to define ADRS positivity and to estimate sensitivity, specificity, positive predictive and negative probabilities. Factors associated with false negatives were identified using multivariable logistic regressions.

Results: 3360 subjects were studied, 52% diagnosed with ADRS by memory clinics. Prediction model based on age, all-cause hospitalization, registration with ADRS as a chronic condition, number of anti-dementia drugs, mention of ADRS during hospitalizations had good discriminative performance (c-statistic: 0.814, sensitivity: 76.0%, specificity: 74.2% for 2013 data). 419 false negatives (24.0%) were younger, had more often ADRS types other than Alzheimer’s disease, moderate forms of ADRS, recent diagnosis, and suffered from other comorbidities than true positives.

Conclusion: Administrative data presented acceptable performance for detecting ADRS. External validation studies should be encouraged.

Keywords: Dementia, Alzheimer's disease, administrative data, claims, validation study, ADRS.

[1]
Hallas J, Hellfritzsch M, Rix M, Olesen M, Reilev M, Pottegård A. Odense pharmacoepidemiological database: A review of use and content. Basic Clin Pharmacol Toxicol 2017; 120(5): 419-25.
[http://dx.doi.org/10.1111/bcpt.12764] [PMID: 28164442]
[2]
Moulis G, Lapeyre-Mestre M, Palmaro A, Pugnet G, Montastruc J-L, Sailler L. French health insurance databases: What interest for medical research? Rev Med Interne 2015; 36(6): 411-7.
[http://dx.doi.org/10.1016/j.revmed.2014.11.009] [PMID: 25547954]
[3]
Nishtala P, Ndukwe H, Chyou T-Y, Salahudeen M, Narayan S. An overview of pharmacoepidemiology in New Zealand: Medical databases, registries and research achievements. N Z Med J 2017; 130(1449): 52-61.
[PMID: 28178730]
[4]
Palmaro A, Moulis G, Despas F, Dupouy J, Lapeyre-Mestre M. Overview of drug data within French health insurance databases and implications for pharmacoepidemiological studies. Fundam Clin Pharmacol 2016; 30(6): 616-24.
[http://dx.doi.org/10.1111/fcp.12214] [PMID: 27351637]
[5]
Pearson S-A, Pesa N, Langton JM, Drew A, Faedo M, Robertson J. Studies using Australia’s Pharmaceutical Benefits Scheme data for pharmacoepidemiological research: a systematic review of the published literature (1987-2013). Pharmacoepidemiol Drug Saf 2015; 24(5): 447-55.
[http://dx.doi.org/10.1002/pds.3756] [PMID: 25833702]
[6]
Wettermark B, Zoëga H, Furu K, et al. The Nordic prescription databases as a resource for pharmacoepidemiological research--a literature review. Pharmacoepidemiol Drug Saf 2013; 22(7): 691-9.
[http://dx.doi.org/10.1002/pds.3457] [PMID: 23703712]
[7]
Chen H, Kwong JC, Copes R, et al. Living near major roads and the incidence of dementia, Parkinson’s disease, and multiple sclerosis: a population-based cohort study. Lancet 2017; 389(10070): 718-26.
[http://dx.doi.org/10.1016/S0140-6736(16)32399-6] [PMID: 28063597]
[8]
Zissimopoulos JM, Barthold D, Brinton RD, Joyce G. Sex and race differences in the association between statin use and the incidence of Alzheimer disease. JAMA Neurol 2017; 74(2): 225-32.
[http://dx.doi.org/10.1001/jamaneurol.2016.3783]
[9]
Goodman RA, Lochner KA, Thambisetty M, Wingo TS, Posner SF, Ling SM. Prevalence of dementia subtypes in United States Medicare fee-for-service beneficiaries, 2011-2013. Alzheimers Dement 2017; 13(1): 28-37.
[http://dx.doi.org/10.1016/j.jalz.2016.04.002] [PMID: 27172148]
[10]
Wexler NS, Collett L, Wexler AR, et al. Incidence of adult Huntington’s disease in the UK: A UK-based primary care study and a systematic review. BMJ Open 2016; 6(2): e009070.
[http://dx.doi.org/10.1136/bmjopen-2015-009070] [PMID: 26908513]
[11]
Hunter CA, Kirson NY, Desai U, Cummings AKG, Faries DE, Birnbaum HG. Medical costs of Alzheimer’s disease misdiagnosis among US Medicare beneficiaries. Alzheimers Dement 2015; 11(8): 887-95.
[http://dx.doi.org/10.1016/j.jalz.2015.06.1889] [PMID: 26206626]
[12]
Brüggenjürgen B, Andersohn F, Ezzat N, Lacey L, Willich S. Medical management, costs, and consequences of Alzheimer’s disease in Germany: An analysis of health claims data. J Med Econ 2015; 18(6): 466-73.
[http://dx.doi.org/10.3111/13696998.2015.1014090] [PMID: 25692902]
[13]
Gilden DM, Kubisiak JM, Sarsour K, Hunter CA. Diagnostic pathways to Alzheimer Disease: Costs incurred in a medicare population. Alzheimer Dis Assoc Disord 2015; 29(4): 330-7.
[http://dx.doi.org/10.1097/WAD.0000000000000070] [PMID: 25635340]
[14]
Doblhammer G, Fink A, Fritze T. Short-term trends in dementia prevalence in Germany between the years 2007 and 2009. Alzheimers Dement 2015; 11(3): 291-9.
[http://dx.doi.org/10.1016/j.jalz.2014.02.006] [PMID: 25301681]
[15]
Princic N, Gregory C, Willson T, et al. Development and validation of an algorithm to identify patients with multiple myeloma using administrative claims data. Front Oncol 2016; 6: 224.
[http://dx.doi.org/10.3389/fonc.2016.00224] [PMID: 27833899]
[16]
Moulis G, Germain J, Adoue D, et al. Validation of immune thrombocytopenia diagnosis code in the French hospital electronic database. Eur J Intern Med 2016; 32: e21-2.
[http://dx.doi.org/10.1016/j.ejim.2016.02.021] [PMID: 27012473]
[17]
Bowker SL, Savu A, Lam NK, Johnson JA, Kaul P. Validation of administrative data case definitions for gestational diabetes mellitus. Diabet Med 2017; 34(1): 51-5.
[http://dx.doi.org/10.1111/dme.13030] [PMID: 26555571]
[18]
Funch D, Holick C, Velentgas P, et al. Algorithms for identification of Guillain-Barré Syndrome among adolescents in claims databases. Vaccine 2013; 31(16): 2075-9.
[http://dx.doi.org/10.1016/j.vaccine.2013.02.009] [PMID: 23474311]
[19]
Quantin C, Benzenine E, Hägi M, et al. Estimation of national colorectal-cancer incidence using claims databases. J Cancer Epidemiol 2012; 2012: 298369.
[http://dx.doi.org/10.1155/2012/298369] [PMID: 22792103]
[20]
Carnahan RM. Mini-Sentinel’s systematic reviews of validated methods for identifying health outcomes using administrative data: summary of findings and suggestions for future research. Pharmacoepidemiol Drug Saf 2012; 21(1): 90-9.
[http://dx.doi.org/10.1002/pds.2318] [PMID: 22262597]
[21]
Moisan F, Gourlet V, Mazurie J-L, et al. Prediction model of Parkinson’s disease based on antiparkinsonian drug claims. Am J Epidemiol 2011; 174(3): 354-63.
[http://dx.doi.org/10.1093/aje/kwr081] [PMID: 21606234]
[22]
Gershon AS, Wang C, Guan J, Vasilevska-Ristovska J, Cicutto L, To T. Identifying patients with physician-diagnosed asthma in health administrative databases. Can Respir J 2009; 16(6): 183-8.
[http://dx.doi.org/10.1155/2009/963098] [PMID: 20011725]
[23]
Hux JE, Ivis F, Flintoft V, Bica A. Diabetes in Ontario: Determination of prevalence and incidence using a validated administrative data algorithm. Diabetes Care 2002; 25(3): 512-6.
[http://dx.doi.org/10.2337/diacare.25.3.512] [PMID: 11874939]
[24]
Bezin J, Girodet P-O, Rambelomanana S, et al. Choice of ICD-10 codes for the identification of acute coronary syndrome in the French hospitalization database. Fundam Clin Pharmacol 2015; 29(6): 586-91.
[http://dx.doi.org/10.1111/fcp.12143] [PMID: 26301735]
[25]
Palmaro A, Gauthier M, Conte C, Grosclaude P, Despas F, Lapeyre-Mestre M. Identifying multiple myeloma patients using data from the French health insurance databases: Validation using a cancer registry. Medicine (Baltimore) 2017; 96(12): e6189.
[http://dx.doi.org/10.1097/MD.0000000000006189] [PMID: 28328805]
[26]
Sahli L, Lapeyre-Mestre M, Derumeaux H, Moulis G. Positive predictive values of selected hospital discharge diagnoses to identify infections responsible for hospitalization in the French national hospital database. Pharmacoepidemiol Drug Saf 2016; 25(7): 785-9.
[http://dx.doi.org/10.1002/pds.4006] [PMID: 27125251]
[27]
Zhu CW, Ornstein KA, Cosentino S, Gu Y, Andrews H, Stern Y. Misidentification of dementia in medicare claims and related costs. J Am Geriatr Soc 2019; 67(2): 269-76.
[http://dx.doi.org/10.1111/jgs.15638] [PMID: 30315744]
[28]
Tuppin P, de Roquefeuil L, Weill A, Ricordeau P, Merlière Y. French national health insurance information system and the permanent beneficiaries sample. Rev Epidemiol Sante Publique 2010; 58(4): 286-90.
[http://dx.doi.org/10.1016/j.respe.2010.04.005] [PMID: 20598822]
[29]
Croisile B, Tedesco A, Gavant S, Minssieux-Catrix G, Mollion H. The specialist-referred patients represent 42% of the activity of an academic memory clinic. Presse Medicale Paris Fr 1983; 41(7-8): e391-396.
[30]
Anthony S, Pradier C, Chevrier R, Festraëts J, Tifratene K, Robert P. The French National Alzheimer database: A fast growing database for researchers and clinicians. Dement Geriatr Cogn Disord 2014; 38(5-6): 271-80.
[http://dx.doi.org/10.1159/000360281] [PMID: 24994018]
[31]
Pradier C, Sakarovitch C, Le Duff F, et al. The mini mental state examination at the time of Alzheimer’s disease and related disorders diagnosis, according to age, education, gender and place of residence: A cross-sectional study among the French National Alzheimer database. PLoS One 2014; 9(8): e103630.
[http://dx.doi.org/10.1371/journal.pone.0103630] [PMID: 25093735]
[32]
Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975; 12(3): 189-98.
[http://dx.doi.org/10.1016/0022-3956(75)90026-6] [PMID: 1202204]
[33]
Grober E, Buschke H, Crystal H, Bang S, Dresner R. Screening for dementia by memory testing. Neurology 1988; 38(6): 900-3.
[http://dx.doi.org/10.1212/WNL.38.6.900] [PMID: 3368071]
[34]
Kasai M, Meguro K, Hashimoto R, Ishizaki J, Yamadori A, Mori E. Non-verbal learning is impaired in very mild Alzheimer’s disease (CDR 0.5): Normative data from the learning version of the Rey-Osterrieth Complex Figure Test. Psychiatry Clin Neurosci 2006; 60(2): 139-46.
[http://dx.doi.org/10.1111/j.1440-1819.2006.01478.x] [PMID: 16594936]
[35]
Deloche G, Hannequin D. Test de dénomination orale d’images (DO80) Paris: ECPA . 1997.
[36]
Cardebat D, Doyon B, Puel M, Goulet P, Joanette Y. Formal and semantic lexical evocation in normal subjects. Performance and dynamics of production as a function of sex, age and educational level. Acta Neurol Belg 1990; 90(4): 207-17.
[PMID: 2124031]
[37]
Cahn DA, Salmon DP, Monsch AU, et al. Screening for dementia of the alzheimer type in the community: The utility of the Clock Drawing Test. Arch Clin Neuropsychol 1996; 11(6): 529-39.
[http://dx.doi.org/10.1093/arclin/11.6.529] [PMID: 14588458]
[38]
Reitan R. Validity of the trail making test as an indicator of organic brain damage. Percept Mot Skills 1958; (8): 271-6.
[http://dx.doi.org/10.2466/pms.1958.8.3.271]
[39]
Lawton MP, Brody EM. Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontologist 1969; 9(3): 179-86.
[http://dx.doi.org/10.1093/geront/9.3_Part_1.179] [PMID: 5349366]
[40]
Le Duff F, Develay AE, Quetel J, et al. The 2008-2012 French Alzheimer plan: Description of the national Alzheimer information system. J Alzheimers Dis 2012; 29(4): 891-902.
[http://dx.doi.org/10.3233/JAD-2012-111943] [PMID: 22366771]
[41]
Rey G, Jougla E, Fouillet A, Hémon D. Ecological association between a deprivation index and mortality in France over the period 1997 - 2001: Variations with spatial scale, degree of urbanicity, age, gender and cause of death. BMC Public Health 2009; 9: 33.
[http://dx.doi.org/10.1186/1471-2458-9-33] [PMID: 19161613]
[42]
Harrell FE Jr, Lee KL, Mark DB. Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996; 15(4): 361-87.
[http://dx.doi.org/10.1002/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4] [PMID: 8668867]
[43]
Newcomer R, Clay T, Luxenberg JS, Miller RH. Misclassification and selection bias when identifying Alzheimer’s disease solely from Medicare claims records. J Am Geriatr Soc 1999; 47(2): 215-9.
[http://dx.doi.org/10.1111/j.1532-5415.1999.tb04580.x] [PMID: 9988293]
[44]
Taylor DH Jr, Fillenbaum GG, Ezell ME. The accuracy of medicare claims data in identifying Alzheimer’s disease. J Clin Epidemiol 2002; 55(9): 929-37.
[http://dx.doi.org/10.1016/S0895-4356(02)00452-3] [PMID: 12393082]
[45]
Williams SE, Carnahan R, McPheeters ML. A systematic review of validated methods for identifying uveitis using administrative or claims data. Vaccine 2013; 31(10): K88-97.
[http://dx.doi.org/10.1016/j.vaccine.2013.03.077] [PMID: 24331079]
[46]
Chung CP, Rohan P, Krishnaswami S, McPheeters ML. A systematic review of validated methods for identifying patients with rheumatoid arthritis using administrative or claims data. Vaccine 2013; 31(Suppl. 10): K41-61.
[http://dx.doi.org/10.1016/j.vaccine.2013.03.075] [PMID: 24331074]
[47]
Sharifi M, Krishanswami S, McPheeters ML. A systematic review of validated methods to capture acute bronchospasm using administrative or claims data. Vaccine 2013; 31(10): K12-20.
[http://dx.doi.org/10.1016/j.vaccine.2013.06.091] [PMID: 24331069]
[48]
Hudson M, Avina-Zubieta A, Lacaille D, Bernatsky S, Lix L, Jean S. The validity of administrative data to identify hip fractures is high--a systematic review. J Clin Epidemiol 2013; 66(3): 278-85.
[http://dx.doi.org/10.1016/j.jclinepi.2012.10.004] [PMID: 23347851]
[49]
Townsend L, Walkup JT, Crystal S, Olfson M. A systematic review of validated methods for identifying depression using administrative data. Pharmacoepidemiol Drug Saf 2012; 21(1): 163-73.
[http://dx.doi.org/10.1002/pds.2310] [PMID: 22262603]
[50]
Andrade SE, Harrold LR, Tjia J, et al. A systematic review of validated methods for identifying cerebrovascular accident or transient ischemic attack using administrative data. Pharmacoepidemiol Drug Saf 2012; 21(1): 100-28.
[http://dx.doi.org/10.1002/pds.2312] [PMID: 22262598]
[51]
Lin P-J, Kaufer DI, Maciejewski ML, Ganguly R, Paul JE, Biddle AK. An examination of Alzheimer’s disease case definitions using Medicare claims and survey data. Alzheimers Dement 2010; 6(4): 334-41.
[http://dx.doi.org/10.1016/j.jalz.2009.09.001] [PMID: 20434960]
[52]
Pressley JC, Trott C, Tang M, Durkin M, Stern Y. Dementia in community-dwelling elderly patients: A comparison of survey data, medicare claims, cognitive screening, reported symptoms, and activity limitations. J Clin Epidemiol 2003; 56(9): 896-905.
[http://dx.doi.org/10.1016/S0895-4356(03)00133-1] [PMID: 14505776]
[53]
Phung TKT, Andersen BB, Høgh P, Kessing LV, Mortensen PB, Waldemar G. Validity of dementia diagnoses in the Danish hospital registers. Dement Geriatr Cogn Disord 2007; 24(3): 220-8.
[http://dx.doi.org/10.1159/000107084] [PMID: 17690555]
[54]
Solomon A, Ngandu T, Soininen H, Hallikainen MM, Kivipelto M, Laatikainen T. Validity of dementia and Alzheimer’s disease diagnoses in Finnish national registers. Alzheimers Dement 2014; 10(3): 303-9.
[http://dx.doi.org/10.1016/j.jalz.2013.03.004] [PMID: 23849592]
[55]
Rizzuto D, Feldman AL, Karlsson IK, Dahl Aslan AK, Gatz M, Pedersen NL. Detection of dementia cases in two swedish health registers: A validation study. J Alzheimers Dis 2018; 61(4): 1301-10.
[http://dx.doi.org/10.3233/JAD-170572] [PMID: 29376854]
[56]
Taylor DH Jr, Østbye T, Langa KM, Weir D, Plassman BL. The accuracy of Medicare claims as an epidemiological tool: The case of dementia revisited. J Alzheimers Dis 2009; 17(4): 807-15.
[http://dx.doi.org/10.3233/JAD-2009-1099] [PMID: 19542620]
[57]
Bharmal MF, Weiner M, Sands LP, Xu H, Craig BA, Thomas J III. Impact of patient selection criteria on prevalence estimates and prevalence of diagnosed dementia in a Medicaid population. Alzheimer Dis Assoc Disord 2007; 21(2): 92-100.
[http://dx.doi.org/10.1097/WAD.0b013e31805c0835] [PMID: 17545733]
[58]
Pippenger M, Holloway RG, Vickrey BG. Neurologists’ use of ICD-9CM codes for dementia. Neurology 2001; 56(9): 1206-9.
[http://dx.doi.org/10.1212/WNL.56.9.1206] [PMID: 11342688]
[59]
van de Vorst IE, Vaartjes I, Sinnecker LF, Beks LJM, Bots ML, Koek HL. The validity of national hospital discharge register data on dementia: A comparative analysis using clinical data from a university medical centre. Neth J Med 2015; 73(2): 69-75.
[PMID: 25753071]
[60]
Quan H, Li B, Saunders LD, et al. Assessing validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions in a unique dually coded database. Health Serv Res 2008; 43(4): 1424-41.
[http://dx.doi.org/10.1111/j.1475-6773.2007.00822.x] [PMID: 18756617]
[61]
Brown A, Kirichek O, Balkwill A, et al. Comparison of dementia recorded in routinely collected hospital admission data in England with dementia recorded in primary care. Emerg Themes Epidemiol 2016; 13: 11.
[http://dx.doi.org/10.1186/s12982-016-0053-z] [PMID: 27800007]
[62]
Jaakkimainen RL, Bronskill SE, Tierney MC, Herrmann N, Green D, Young J, et al. Identification of physician-diagnosed Alzheimer’s disease and related dementias in population-based administrative data: A validation study using family physicians’ electronic medical records. J Alzheimers Dis JAD 2016; 54(1): 337-49.
[63]
Wilkinson T, Schnier C, Bush K, et al. Identifying dementia outcomes in UK Biobank: a validation study of primary care, hospital admissions and mortality data. Eur J Epidemiol 2019; 34(6): 557-65.
[http://dx.doi.org/10.1007/s10654-019-00499-1] [PMID: 30806901]
[64]
Chen Y, Tysinger B, Crimmins E, Zissimopoulos JM. Analysis of dementia in the US population using Medicare claims: Insights from linked survey and administrative claims data. Alzheimers Dement (N Y) 2019; 5: 197-207.
[http://dx.doi.org/10.1016/j.trci.2019.04.003] [PMID: 31198838]
[65]
Sommerlad A, Perera G, Singh-Manoux A, Lewis G, Stewart R, Livingston G. Accuracy of general hospital dementia diagnoses in England: Sensitivity, specificity, and predictors of diagnostic accuracy 2008-2016. Alzheimers Dement 2018; 14(7): 933-43.
[http://dx.doi.org/10.1016/j.jalz.2018.02.012] [PMID: 29703698]
[66]
St Germaine-Smith C, Metcalfe A, Pringsheim T, et al. Recommendations for optimal ICD codes to study neurologic conditions: A systematic review. Neurology 2012; 79(10): 1049-55.
[http://dx.doi.org/10.1212/WNL.0b013e3182684707] [PMID: 22914826]
[67]
Wilkinson T, Ly A, Schnier C, et al. Identifying dementia cases with routinely collected health data: A systematic review. Alzheimers Dement 2018; 14(8): 1038-51.
[http://dx.doi.org/10.1016/j.jalz.2018.02.016] [PMID: 29621480]
[68]
Ponjoan A, Garre-Olmo J, Blanch J, et al. How well can electronic health records from primary care identify Alzheimer’s disease cases? Clin Epidemiol 2019; 11: 509-18.
[http://dx.doi.org/10.2147/CLEP.S206770] [PMID: 31456649]
[69]
Fowler NR, Chen Y-F, Thurton CA, Men A, Rodriguez EG, Donohue JM. The impact of Medicare prescription drug coverage on the use of antidementia drugs. BMC Geriatr 2013; 13: 37.
[http://dx.doi.org/10.1186/1471-2318-13-37] [PMID: 23621892]


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VOLUME: 18
ISSUE: 2
Year: 2021
Published on: 15 April, 2021
Page: [142 - 156]
Pages: 15
DOI: 10.2174/1567205018666210416094639
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