Impact of "Sambhav" Program (Financial Assistance and Counselor Services) on Hepatitis C Pegylated Interferon Alpha Treatment Initiation in India
Bibliographic record
Abstract
BACKGROUND: Financial constraints, social taboos and beliefs in alternative medicine are common reasons for delaying or not considering treatment for hepatitis C in India. The present study was planned to analyze the impact of non-banking interest free loan facility in patients affected with hepatitis C virus (HCV) in North India. METHODS: This one year observational, retrospective study was conducted in Department of Gastroenterology (January 2012-December 2013), Dayanand Medical College and Hospital Ludhiana, to evaluate the impact of program titled "Sambhav" (which provided non-banking financial assistance and counselor services) on treatment initiation and therapeutic compliance in HCV patients. Data of fully evaluated patients with chronic hepatitis, and/or cirrhosis due to HCV infection who were treated with Peginterferon alfa and ribavirin (RBV) combination during this duration (2012-2013) was collected from patient medical records and analyzed. In the year 2012, eligible patients who were offered antiviral treatment paid for treatment themselves, while in 2013, 'Sambhav' program was launched and this provided interest free financing by non-banking financial company (NBFC) for the treatment of HCV in addition to free counselor services for disease management. The treatment initiation and compliance rates were compared between the patients (n = 585) enrolled in 2013 who were offered 'Sambhav' assistance and those enrolled in 2012 (n = 628) when 'Sambhav' was not available. RESULTS: Introduction of Sambhav program improved the rates of treatment initiation (59% in 2013 vs. 51% in 2012, P=.004). Of the 585 eligible patients offered 'Sambhav' assistance in 2013, 233 patients (39.8%) applied but 106/233 (45.4%) received assistance. Antiviral therapy was started in 93/106 (87.7%) of these patients, while only 52 (42.5%) of 127 patients whose applications were rejected underwent treatment. Compliance to antiviral therapy also improved with the introduction of 'Sambhav' program (87.7% vs. 74.1%, P=.001). CONCLUSION: 'Sambhav' program had significant impact on the initiation of antiviral therapy by overcoming the financial hurdles. The free counselor services helped to mitigate social taboos and imparted adequate awareness about the disease to the patients. Initiatives like 'Sambhav' can be utilized for improving healthcare services in developing countries, especially for chronic diseases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".