Implementation of an Algorithm of Cohort Classification to Prevent the Spread of COVID-19 in Nursing Homes.
Cristina González de Villaumbrosia, Javier Martínez Peromingo, Juan Ortiz Imedio and 11 others
PMID 33256960WHAT IT FOUND
Nursing homes that used this outbreak algorithm increased antibody testing and improved zone separation, but the paper measured adherence, not infections or deaths.
It is a practical guide for limited PCR testing, not proof that it prevents spread.
Key findings
01The report says 100% of nursing homes increased rapid antibody testing after the intervention.
02The report says 94% of nursing homes made some improvement in sectorization after the intervention.
03The authors state that strong evidence does not yet exist for efficacy or effectiveness, and successful outcomes cannot be assured.
STILL TO COME
How it was doneWhat they foundWhat it means for RNs
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What it does not show
The paper did not measure outcomes such as hospital referrals, mortality, or time to become COVID-19 free. The authors state that strong evidence does not yet exist for efficacy or effectiveness. The algorithm is recommended only for a COVID-19 outbreak when PCR testing is not widely available, because rapid point-of-care tests have reliability limits. The authors say it would not be the recommended approach in a different clinical setting. Practice varied before the intervention, and adherence after implementation was also variable. One nursing home transferred all 28 residents because necessary isolation measures could not be applied.
The easy way to misread this
Do not read this as proof that the algorithm prevented spread or saved lives. The report measured testing and zone separation after implementation, and the authors say strong evidence does not yet exist for efficacy or effectiveness.