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Record W3061815054 · doi:10.4103/ijmpo.ijmpo_304_20

“Choosing Wisely” for Cancer Care in India

2020· article· en· W3061815054 on OpenAlexaffabout
C.S. Pramesh, Harit Chaturvedi, Vijay Anand P. Reddy, Tapan Saikia, Sushmita Ghoshal, Mrinalini Pandit, K. Govind Babu, K V Ganpathy, Dhairyasheel Savant, Gunita Mitera, Richard Sullivan, Christopher M. Booth

Bibliographic record

VenueIndian Journal of Medical and Paediatric Oncology · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsQueen's UniversityUniversity of Toronto
Fundersnot available
KeywordsMedicineConversationPsychological interventionQuality managementQuality (philosophy)Healthcare deliveryHealth careFamily medicineIntensive care medicineMedical emergencyNursingOperations managementEconomic growth

Abstract

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Choosing Wisely India (CWI) is an initiative to identify low-value and/or potentially harmful practices in cancer care in India. Modeled after Choosing Wisely in the US and Canada,[ 1 ],[ 2 ],[ 3 ] the CWI project was intended to facilitate a conversation between patients, clinicians, hospitals, and policymakers on delivering high-quality, affordable cancer care. By identifying common low-value and/or harmful practices, this process aims to reduce unnecessary interventions to improve the overall quality of care, reduce patient toxicity, and reduce the financial burden on both the patient and system. The formal CWI report has been recently published in Lancet Oncology;[ 4 ] in this commentary, we provide a summary of the process, describe the Top 10 CWI list, and offer suggestions for future actions to improve the delivery of high-quality cancer in India's cancer system. The National Cancer Grid (NCG) was established in 2012 and now includes 171 cancer centers, research institutes, patient advocacy groups, charitable organizations, and professional societies. The NCG coordinates national efforts related to cancer control, research, and education. A key initiative of the NCG has been the creation of context-specific clinical practice guidelines for common cancers, the goal of which is to standardize and improve the quality of care delivered.[ 5 ] In a parallel project, the NCG undertook CWI to identify and eventually reduce utilization of interventions which do not offer meaningful benefit to patients. The high proportion of out-of-pocket spending among Indian cancer patients makes this highly relevant in a system where a substantial proportion of patients incur catastrophic health expenditures.[ 6 ] The Choosing Wisely initiative has been adopted globally by more than 20 countries as a disease-specific process to identify unnecessary (often expensive) interventions that should be avoided.[ 7 ] Within the US and Canada, there are now over 800 Choosing Wisely recommendations from more than 120 national societies covering a range of diseases.[ 8 ],[ 9 ] Choosing Wisely initiatives focused on cancer have been published in the United States and Canada.[ 1 ],[ 2 ],[ 3 ] CWI represents the first Choosing Wisely initiative within any disease area from a low-middle income country (LMIC) and represents an important step on the path to universal health coverage and the achievement of health Sustainable Development Goals. In 2017, the NCG convened a nine-member CWI Task Force including two members from national patient advocacy organizations and seven physician members from radiation, medical, and surgical oncology. This membership included executive office bearers from the Indian Society of Oncology, Association of Radiation Oncologists of India, Indian Association of Surgical Oncology, and Indian Society of Medical and Pediatric Oncology and the convener of the NCG. Each specialty had at least one representative from each of the public and private health systems. Additional methodologic expertise was provided by three nonvoting advisors from Canada and the UK with experience in Choosing Wisely Canada and global cancer policy. A long list of cancer practices to be considered was collated from clinical members of the NCG, four professional societies, and members of the CWI Task Force, with reference to the existing Choosing Wisely US and Canada lists. The following prioritizing factors were considered in both creating the long list and the subsequent voting process to identify the final Top 10 list: evidence of low value/harm, frequent use in India, cost (including opportunity cost), be practically feasible and measurable, and relevance to the Indian cancer context. Consensus was achieved using a modified Delphi process.[ 10 ] The CWI Task Force consensus voted on the long list and shorter list to identify the final Top 10 list. Membership of the NCG and the four professional societies were given the opportunity to provide input on each of the long list and final list. This final list was reviewed and endorsed by the executive boards of the four professional societies and the NCG. The final list consisted of 10 recommendations (available free for download on https://www.thelancet.com/action/showPdf?pii=S1470-2045%2819%2930092-0 ). Of the 10 practices, four practices were new suggestions and six practices were adapted with modifications from Choosing Wisely US and Canada lists. The CWI initiative will contribute to ongoing policy dialog within and between clinical and patient communities in India's cancer system. Many of the items included in the final list represent recommendations to avoid interventions that offer no benefit to patients and are associated with significant side effects and/or financial costs. The Task Force was careful to ensure that while similar lists from other countries (e.g., Canada and the US) were not ignored, India-specific recommendations were also considered and included in the final list; by no means does this imply that the original Choosing Wisely lists from the US and Canada were not relevant in India – it merely indicates that there were other points which were considered higher priority for India. The Task Force also was conscious of the fact that while some of these recommendations were aspirational and would require systemic changes in health-care delivery (i.e., multidisciplinary input for all patients with curable cancer and delivery of care closer to home), many of them could also be immediate and short-term targets to achieve (e.g., do not order positron emission tomography–computed tomography scans to monitor response to palliative chemotherapy). The dual creation of the NCG clinical practice guidelines with the Choosing Wisely list represents initial steps in a multipronged process to improve the quality, equity, and affordability of cancer care in India.[ 6 ],[ 7 ] At the 2019 NCG annual meeting, there was resounding support to begin multicenter data collection to measure compliance with both clinical practice guidelines and the CWI recommendations. The international Choosing Wisely program emphasizes that costs of care should not be a factor in finalizing the recommendations; however, in countries such as India and other LMICs, these recommendations also serve to demonstrate more optimal ways of deploying scarce resources and maximize public health benefit. The Choosing Wisely recommendations for cancer care in India are also the first ever list (in any health-care domain) developed and published from an LMIC and also the first to include patient representatives in the Task Force. These recommendations could well be an exemplar for other countries or geographical regions to follow. Publication History Received: 22 June 2020 Accepted: 23 June 2020 Article published online: 17 May 2021 © 2020. Indian Society of Medical and Paediatric Oncology. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/.) Thieme Medical and Scientific Publishers Pvt. Ltd. A-12, 2nd Floor, Sector 2, Noida-201301 UP, India

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.032
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0070.008
Scholarly communication0.0100.004
Open science0.0020.008
Research integrity0.0050.017
Insufficient payload (model declined to judge)0.0080.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.222
GPT teacher head0.450
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2020
Admission routes2
Has abstractyes

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