Objective

A growing body of evidence suggests that testing for influenza virus alone is more appropriate than multiplex respiratory viral panel (RVP) testing for general populations of patients with respiratory tract infections. We aimed to decrease the proportion of RVPs out of total respiratory viral testing ordered during influenza season.

Methods

We implemented two consecutive interventions: reflex testing for RVPs only after a negative influenza test, and noninterruptive clinical decision support (CDS) including modifications of the computerized physician order entry search behavior and cost display. We conducted an interrupted time series of RVPs and influenza polymerase chain reaction tests pre- and postintervention, and performed a mixed-effects logistic regression analysis with a primary outcome of proportion of RVPs out of total respiratory viral tests. The primary predictor was the intervention period, and covariates included the provider, clinical setting, associated diagnoses, and influenza incidence.

Results

From March 2013 to April 2019, there were 24,294 RVPs and 26,012 influenza tests (n = 50,306). Odds of ordering an RVP decreased during the reflex testing period (odds ratio: 0.432, 95% confidence interval: 0.397-0.469), and decreased more dramatically during the noninterruptive CDS period (odds ratio: 0.291, 95% confidence interval: 0.259-0.327).

Discussion

The odds of ordering an RVP were 71% less with the noninterruptive CDS intervention, which projected 4,773 fewer RVPs compared with baseline. Assuming a cost equal to Medicare reimbursement rates for RVPs and influenza tests, this would generate an estimated averted cost of $1,259,474 per year.

Conclusion

Noninterruptive CDS interventions are effective in reducing unnecessary and expensive testing, and avoid typical pitfalls such as alert fatigue.

Introduction

Pooled testing is a potentially efficient alternative strategy for COVID-19 testing in congregate settings. We evaluated the utility and cost-savings of pooled testing based on imperfect test performance and potential dilution effect due to pooling and created a practical calculator for online use.

Methods

We developed a 2-stage pooled testing model accounting for dilution. The model was applied to hypothetical scenarios of 100 specimens collected during a one-week time-horizon cycle for varying levels of COVID-19 prevalence and test sensitivity and specificity, and to 338 skilled nursing facilities (SNFs) in Los Angeles County (Los Angeles) (data collected and analyzed in 2020).

Results

Optimal pool sizes ranged from 1 to 12 in instances where there is a least one case in the batch of specimens. 40% of Los Angeles SNFs had more than one case triggering a response-testing strategy. The median number (minimum; maximum) of tests performed per facility were 56 (14; 356) for a pool size of 4, 64 (13; 429) for a pool size of 10, and 52 (11; 352) for an optimal pool size strategy among response-testing facilities. The median costs of tests in response-testing facilities were $8250 ($1100; $46,100), $6000 ($1340; $37,700), $6820 ($1260; $43,540), and $5960 ($1100; $37,380) when adopting individual testing, a pooled testing strategy using pool sizes of 4, 10, and optimal pool size, respectively.

Conclusions

Pooled testing is an efficient strategy for congregate settings with a low prevalence of COVID-19. Dilution as a result of pooling can lead to erroneous false-negative results.