A Conceptual Framework for Appropriateness in Surgical Care

Cooper, Zara; Sayal, Puneet; Abbett, Sarah K.; Neuman, Mark D.; Rickerson, Elizabeth; Bader, Angela M.

doi:10.1097/aln.0000000000000899

Cited by 35 publications

(14 citation statements)

References 22 publications

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“…This model also assumed that all reported historical surgical volumes were appropriately indicated for surgery, which may not always hold true and vary over time depending on variations in practice patterns. 45…”

Section: Discussionmentioning

confidence: 99%

The Ophthalmic Surgical Backlog caused by the COVID-19 Pandemic: A population-based and microsimulation modelling study

Felfeli

Ximenes

Naimark

et al. 2021

Preprint

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Background: Jurisdictions worldwide ramped down ophthalmic surgeries to mitigate the effects of coronavirus disease 2019 (COVID-19), creating a global surgical backlog. We sought to predict the long-term impact of COVID-19 on ophthalmology surgical care delivery. Methods: This is a population-based study and a microsimulation model for predicting future outcomes. Provincial administrative data from January 2019 to November 2020 was used to estimate the decline in surgical volumes during the COVID-19 pandemic. For the post-pandemic recovery phase, we estimated the resources required to clear the backlog of patients accumulated on the waitlist since the pandemic. Results: A total of 56,923 patients were on the waitlist in the province of Ontario awaiting non-emergency ophthalmic surgery as of March 15, 2020. The number of non-emergency surgeries performed in the province decreased by 45-98% between March to May 2020 compared to the same months in 2019. By 2 years and 3 years, the overall estimated number of patients awaiting surgery grew by 125% and 148%, respectively. The mean wait time for patients for all subspecialty surgeries increased to 198.49 days (SD 81.38) in March 2021 compared to 94.41 days (SD 97.42) in 2019. The provincial monthly additional resources required to clear the backlog by March 2023 was estimated to be 126% (3,538 additional surgeries). Discussion: The magnitude of the ophthalmic surgical backlog from COVID-19 has important implications for the recovery phase. The estimates from the surgical database and microsimulation modelling can be adapted to other jurisdictions to assist with recovery planning.

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Section: Discussionmentioning

confidence: 99%

The Ophthalmic Surgical Backlog caused by the COVID-19 Pandemic: A population-based and microsimulation modelling study

Felfeli

Ximenes

Naimark

et al. 2021

Preprint

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“…Determining the type of procedure performed and the primary indication for that procedure can be useful in a variety of contexts. In particular, it is important for studies that evaluate whether or not a decision to have surgery was the result of a SDM process, since SDM interventions are often only applicable for certain procedures and indications where there are multiple treatment options available [ 22 , 23 ]. The algorithm developed in this study was able to classify surgical cases with the correct procedure and primary indication combination with high specificity across the four combinations analyzed.…”

Section: Discussionmentioning

confidence: 99%

Validation of an electronic coding algorithm to identify the primary indication of orthopedic surgeries from administrative data

Giardina¹,

Cha

Atlas

et al. 2020

BMC Med Inform Decis Mak

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Background Determining the primary indication of a surgical procedure can be useful in identifying patients undergoing elective surgery where shared decision-making is recommended. The purpose of this study was to develop and validate an algorithm to identify patients receiving the following combinations of surgical procedure and primary indication as part of a study to promote shared decision-making: (1) knee arthroplasty to treat knee osteoarthritis (KOA); (2) hip arthroplasty to treat hip osteoarthritis (HOA); (3) spinal surgery to treat lumbar spinal stenosis (SpS); and (4) spinal surgery to treat lumbar herniated disc (HD). Methods Consecutive surgical procedures performed by participating spine, hip, and knee surgeons at four sites within an integrated care network were included. Study staff reviewed electronic medical records to ascertain a “gold standard” determination of the procedure and primary indication status. Electronic algorithms consisting of ICD-10 and CPT codes for each combination of procedure and indication were then applied to records for each case. The primary measures of validity for the algorithms were the sensitivity and specificity relative to the gold standard review. Results Participating surgeons performed 790 procedures included in this study. The sensitivity of the algorithms in determining whether a surgical case represented one of the combinations of procedure and primary indication ranged from 0.70 (HD) to 0.92 (KOA). The specificity ranged from 0.94 (SpS) to 0.99 (HOA, KOA). Conclusion The electronic algorithm was able to identify all four procedure/primary indication combinations of interest with high specificity. Additionally, the sensitivity for the KOA cases was reasonably high. For HOA and the spine conditions, additional work is needed to improve the sensitivity of the algorithm to identify the primary indication for each case.

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“…Nous aurions besoin de plus de données pour prédire la demande en chirurgie durant la reprise et la possible phase de réduction des interventions advenant d’autres vagues de COVID-19. De plus, nous avons présumé que toutes les interventions du volume attendu étaient cliniquement indiquées, alors que ce n’est probablement pas toujours le cas 29 . En ce qui concerne les tendances dans l’utilisation des ressources, il faut préciser qu’en raison d’une progression de la maladie, par exemple du cancer ou d’une affection cardiaque, les patients qui attendent plus longtemps avant d’être traités pourraient nécessiter plus de ressources que ceux traités avant la pandémie, voire ne plus être admissibles à l’opération.…”

Section: Interprétationunclassified

Reprise du retard en chirurgie causé par la COVID-19 en Ontario : étude de modélisation de séries chronologiques

Wang

Vahid

Eberg

et al. 2021

CMAJ

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L e 11 mars 2020, l'Organisation mondiale de la Santé (OMS) a déclaré que la propagation de la maladie à coronavirus 2019 (COVID-19), maladie qui a de lourdes conséquences sur la santé, l'échiquier politique et l'économie à l'échelle mondiale, avait atteint le stade de pandémie 1. Maintenant que certains pays ont passé le pire de la première vague, on en voit bien les séquelles sur le système de santé-surtout en chirurgie 2. D'après les estimations du CovidSurg Collaborative, 28 404 603 opérations chirurgicales dans 190 pays auraient été annulées ou reportées durant les 12 premières semaines de la COVID-19, dont 37,7 % des interventions pour un cancer et 81,7 % des autres interventions (affections bénignes) 3. S'ils augmentaient de 20 % leur volume chirurgical par rapport à la normale, les pays touchés auraient besoin d'un temps médian de 45 semaines pour reprendre le retard accumulé. Selon un modèle de reprise postpandémie des interventions orthopédiques planifiées, il faudrait 7-16 mois aux États-Unis pour retrouver un rythme stable, et le nombre d'opérations à reprendre dépasserait le million 4. Le 15 mars 2020, le ministère de la Santé de l'Ontario a demandé aux hôpitaux d'opérer une « réduction mesurée du nombre d'opérations chirurgicales et autres activités non urgentes » en RECHERCHE SERVICES DE SANTÉ Reprise du retard en chirurgie causé par la COVID-19 en Ontario : étude de modélisation de séries chronologiques

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A Conceptual Framework for Appropriateness in Surgical Care

Abstract: Innovations that foster high quality shared surgical decision making, in combination with successful elements of previous appropriateness methodologies, can reduce futile and unwanted procedures and increase the appropriateness of the care that our patients receive.

Cited by 35 publications

References 22 publications

The Ophthalmic Surgical Backlog caused by the COVID-19 Pandemic: A population-based and microsimulation modelling study

The Ophthalmic Surgical Backlog caused by the COVID-19 Pandemic: A population-based and microsimulation modelling study

Validation of an electronic coding algorithm to identify the primary indication of orthopedic surgeries from administrative data

Reprise du retard en chirurgie causé par la COVID-19 en Ontario : étude de modélisation de séries chronologiques

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