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Data envelopment analysis to evaluate the efficiency of tobacco treatment programs in the NCI Moonshot Cancer Center Cessation Initiative.

Kathryn PlutaSarah D HohlHeather D'AngeloJamie S OstroffDonna ShelleyYasmin AsvatLi-Shiun ChenK Michael CummingsNeely DahlAndrew T DayLinda FleisherAdam O GoldsteinRashelle HayesBrian HitsmanDeborah Hudson BucklesAndrea C KingCho Y LamKatie LenhoffArnold H LevinsonMara MinionCary PresantJudith J ProchaskaKimberly ShoenbillVani SimmonsKathryn TaylorHilary TindleElisa TongJustin S WhiteKara P WisemanGraham W WarrenTimothy B BakerBetsy RollandMichael C FioreRamzi George Salloum
Published in: Implementation science communications (2023)
Most C3I programs assessed were technically inefficient relative to the most efficient center benchmark and may be improved by optimizing the use of inputs (e.g., cost-per-participant) relative to program outcomes (e.g., reach, effectiveness). This study demonstrates the appropriateness and feasibility of using DEA to evaluate the relative performance of evidence-based programs.
Keyphrases
  • public health
  • quality improvement
  • randomized controlled trial
  • papillary thyroid
  • systematic review
  • squamous cell carcinoma
  • big data
  • machine learning
  • replacement therapy
  • deep learning