tetano
Editor, Senior Moderator
Open Forum Infect Dis. 2019 Jun 10;6(6)
fz231. doi: 10.1093/ofid/ofz231. eCollection 2019 Jun.
[h=1]Determination of Eligibility for Influenza Research: A Clinical Informatics Approach.[/h] Silveira FP[SUP]1[/SUP], Saul M[SUP]1[/SUP], Nowalk MP[SUP]2[/SUP], Saul S[SUP]2[/SUP], Sax TM[SUP]3[/SUP], Eng H[SUP]3[/SUP], Zimmerman RK[SUP]2[/SUP], Balasubramani GK[SUP]3[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] [h=4]Background:[/h] A clinical informatics algorithm (CIA) was developed to systematically identify potential enrollees for a test-negative, case-control study to determine influenza vaccine effectiveness, to improve enrollment over manual records review. Further testing may enhance the CIA for increased efficiency.
[h=4]Methods:[/h] The CIA generated a daily screening list by querying all medical record databases for patients admitted in the last 3 days, using specified terms and diagnosis codes located in admission notes, emergency department notes, chief complaint upon registration, or presence of a respiratory viral panel charge or laboratory result (RVP). Classification and regression tree analysis (CART) and multivariable logistic regression were used to refine the algorithm.
[h=4]Results:[/h] Using manual records review, 204 patients (<4/day) were approached and 144 were eligible in the 2014-2015 season compared with 3531 (12/day) patients who were approached and 1136 who were eligible in the 2016-2017 season using a CIA. CART analysis identified RVP as the most important indicator from the CIA list for determining eligibility, identifying 65%-69% of the samples and predicting 1587 eligible patients. RVP was confirmed as the most significant predictor in regression analysis, with an odds ratio (OR) of 4.9 (95% confidence interval [CI], 4.0-6.0). Other significant factors were indicators in admission notes (OR, 2.3 [95% CI, 1.9-2.8]) and emergency department notes (OR, 1.8 [95% CI, 1.4-2.3]).
[h=4]Conclusions:[/h] This study supports the benefits of a CIA to facilitate recruitment of eligible participants in clinical research over manual records review. Logistic regression and CART identified potential eligibility screening criteria reductions to improve the CIA's efficiency.
[h=4]KEYWORDS:[/h] acute respiratory infection; influenza vaccination; respiratory viral panel
PMID: 31205975 PMCID: PMC6557306 DOI: 10.1093/ofid/ofz231
fz231. doi: 10.1093/ofid/ofz231. eCollection 2019 Jun.[h=1]Determination of Eligibility for Influenza Research: A Clinical Informatics Approach.[/h] Silveira FP[SUP]1[/SUP], Saul M[SUP]1[/SUP], Nowalk MP[SUP]2[/SUP], Saul S[SUP]2[/SUP], Sax TM[SUP]3[/SUP], Eng H[SUP]3[/SUP], Zimmerman RK[SUP]2[/SUP], Balasubramani GK[SUP]3[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] [h=4]Background:[/h] A clinical informatics algorithm (CIA) was developed to systematically identify potential enrollees for a test-negative, case-control study to determine influenza vaccine effectiveness, to improve enrollment over manual records review. Further testing may enhance the CIA for increased efficiency.
[h=4]Methods:[/h] The CIA generated a daily screening list by querying all medical record databases for patients admitted in the last 3 days, using specified terms and diagnosis codes located in admission notes, emergency department notes, chief complaint upon registration, or presence of a respiratory viral panel charge or laboratory result (RVP). Classification and regression tree analysis (CART) and multivariable logistic regression were used to refine the algorithm.
[h=4]Results:[/h] Using manual records review, 204 patients (<4/day) were approached and 144 were eligible in the 2014-2015 season compared with 3531 (12/day) patients who were approached and 1136 who were eligible in the 2016-2017 season using a CIA. CART analysis identified RVP as the most important indicator from the CIA list for determining eligibility, identifying 65%-69% of the samples and predicting 1587 eligible patients. RVP was confirmed as the most significant predictor in regression analysis, with an odds ratio (OR) of 4.9 (95% confidence interval [CI], 4.0-6.0). Other significant factors were indicators in admission notes (OR, 2.3 [95% CI, 1.9-2.8]) and emergency department notes (OR, 1.8 [95% CI, 1.4-2.3]).
[h=4]Conclusions:[/h] This study supports the benefits of a CIA to facilitate recruitment of eligible participants in clinical research over manual records review. Logistic regression and CART identified potential eligibility screening criteria reductions to improve the CIA's efficiency.
[h=4]KEYWORDS:[/h] acute respiratory infection; influenza vaccination; respiratory viral panel
PMID: 31205975 PMCID: PMC6557306 DOI: 10.1093/ofid/ofz231