influenza-like illness by national health insurance databases

Comorbidity Attributes that Link to Unfavorable Outcomes of Influenza-

like Illness-related Inpatients -- A Nationwide Cohort Analysis

以台灣全民健保資料庫分析探索類流感關聯病人不良預後之共病特質

及預測模式陳勁辰 金傳春 …

Introduction

• Susceptible –(1)-> Influenza –(2)-> Outcome• Comorbidity (Como) affects (2)• Real world: symptoms/syndrome groups• Influenza-like illness (ILI)• Aim: Como effect of ILI on outcomes

Methods

• National Health Insurance Database (NHID)• Materials: One-million samples of NHID of

2007, 2008, 2009, 2010• Roughly: Seasonal in 2007+2008; Pandemic in

2009+2010• ILI defined by EID• ILI-related inpatients: hospitalized with ILI or

ambulatory visits for ILI =< 1 day

Marsden-Haug N, Foster VB, Gould PL, Elbert E, Wang H, Pavlin JA. Code-based syndromic surveillance for influenzalike illness by International Classification of Diseases, Ninth Revision. Emerging Infect. Dis. 2007;13(2):207–216.

Methods

• ILIR cohort: EID definition• Como: Selected by relevance and advisors• Outcomes: – Cost: from NHID– Length of stay (LOS): from NHID– Daily cost: Cost/LOS– Death: by endpoint code– ICU: by treatment code– Adverse event (AE): Death or ICU

Strata by Age

• By social-economic status• [0, 6): pre-school• [6, 15): school children• [15, 25): the youth• [25, 45): young adults• [45, 65): middle-aged• [65, oo): the elderly

Methods

• Data management by SAS 9.3, SAS-SQL programs

• “Big Data” computation on NTU virtual machine remotely

• Statistics by StataMP 13.1 Mac• Programs and files shared in “Clouds”

Models

• Outcome Y• Como X• Adjusted by Sex• Y = B0 + B1 X + B2 Sex (Each Age stratum)• Cost, LOS, Dcost -> log-transformed -> Linear

regression• Death, ICU, AE -> Logistic regression

Algorithms

• ILI hetero each year? Checked by sex, age, como’s, outcomes, ILI top-ten codes;

• Combine homo years, then proceed;• In each age stratum, como is selected if:– Sig in all regression models (all endpts)– Age-specific prevalence>5%

Algorithm

• ILI Score = Sum of <Como> * <In Age>• Internal validation by modeling ILI score on

outcomes– Cost/LOS/Dcost by Spearman correlation– Death/ICU/AE by ROC

Basic Statistics

Results: Yearly Comparison

• ILI ICD9: freq rank; fisher's exact test p=0.9090• Sex: fisher's exact test p=0.2380• Age: Mann-Whitney U test as scale; Fisher's exact

test as strata nominal; p<0.001 (age up with year)• Como: each p<0.001 except preg, cong, imdef,

autoimm• Endpt: each p<0.001 (cost, los, daycost, die, icu,

ae)

Results: Data Merge by Pandemic State

• Yearly data cannot be merged into one;• Yearly formulae are not practical;• Formulae by pandemic attribute (pan=0 or 1)• Seasonal (pan=0): 2007+2008• Pandemic (pan=1): 2009+2010

Results: Seasonal (pan=0)

• Como: cancer, cong, cv, cva, htn, esrd, imdef, dm;• 0-6: cancer, cong;

6-15: cv, cva;15-25: cv, cva;25-45: cv, cva, htn, esrd, imdef;45-65: dm, esrd;65+: esrd.

• => (cancer*[0-6), cong*[0-6), cv*[6-45), cva*[6-45), htn*[25-45), esrd*[25+), dm*[45-65), imdef*[25-45))

Results: Pandemic (pan=1)

• Como: cv, cancer, cong, cva, esrd, imdef;• 0-6: cv, cong;

6-15: cva, cancer; 15-25: cv, cva, cancer;25-45: cv, cva, cancer, esrd, imdef;45-65: esrd;65+: esrd.

• => (cancer*[6-45), cong*[0-6), cv*[0-6, 15-45), cva*[6-45), esrd*[25+), imdef*[25-45))

Results: Formula

Results: Formula

• 1. Cong*[0-6)+cva*[6-45)+esrd*[25+)+imdef*[25-45);

• +2. Seasonal: dm*[45-65) +htn*[25-45) +cancer*[0-6) +cv*[6-45).

• +2'. Pandemic: cancer*[6-45) +cv*[0-6, 15-45).

Internal Validation

Future Directions

• Covariates weights in formulae• Combined effect• External validation: 2011~ data?• Advanced models: agent-base models (Dr.

Nathaniel Osgood)

Thank you!

Results: Cost

Results: LOS

Como-wise Statistics

Como-wise Statistics

Age-wise Statistics

Age-wise Como PrevalenceComorbidity prevalence in each age stratum2007+2008

0-6 6-15 15-25 25-45 45-65 65+2009+2010

0-6 6-15 15-25 25-45 45-65 65+

Allergy 27.64 24.25 9.17 7.54 6.80 7.74 Allergy 28.38 25.30 10.37 7.68 6.72 7.36

DM 0.56 1.67 2.93 7.17 29.10 37.20 DM 0.34 1.69 2.74 8.26 29.28 37.89

Hlipid 0.14 0.45 1.63 6.26 21.17 18.25 Hlipid 0.10 0.67 1.26 6.92 22.85 20.70

CV 0.67 2.03 3.61 7.03 26.64 50.39 CV 0.68 1.24 3.27 7.17 25.86 49.70

HTN 0.05 0.36 2.04 9.09 41.66 65.47 HTN 0.07 0.60 1.83 10.25 42.61 67.52

CVA 0.13 1.28 2.70 3.42 13.76 31.68 CVA 0.95 0.73 2.29 3.44 13.07 30.99

Dementia 0.06 0.24 1.45 3.89 3.86 16.98 Dementia 0.17 0.34 1.65 3.40 3.90 18.11

Cancer 1.56 7.30 3.18 10.06 27.28 22.90 Cancer 3.61 4.29 4.83 10.05 28.54 24.09

Pregnancy 0.00 0.03 18.95 24.70 0.17 0.00 Pregnancy 0.00 0.10 14.10 24.21 0.14 0.00

congenital 4.85 7.90 3.06 1.91 2.13 2.11 congenital 4.75 6.85 3.24 2.16 2.06 2.26

Uremia NA 0.09 0.78 1.52 6.58 10.74 Uremia NA 0.10 0.90 1.68 6.93 11.73

Lungs 23.40 14.75 4.55 5.07 13.14 34.35 Lungs 26.66 15.23 3.88 5.17 11.69 32.08

Imdef 0.02 0.32 0.21 0.62 1.09 0.99 Imdef 0.02 0.33 0.67 0.81 1.25 0.80

Autoimm 0.03 0.86 2.06 2.25 3.01 2.96 Autoimm 0.07 1.13 1.80 2.32 2.90 3.20

Selected Como 2007-2008

Selected Como 2007-2008

Selected Como 2009-2010

Selected Como 2009-2010