Future pandemic influenza control (FPIC) related strategic management plan based on the 2009 H1N1 pandemic influenza review of health policy decisions, their practice and implications

This cross-sectional study is based on the qualitative and quantitative research design to review health policy decisions, their practice and implications during 2009 H1N1 influenza pandemic in the United States and globally. The “Future Pandemic Influenza Control (FPIC) related Strategic Management Plan” was developed based on the incorporation of the “National Strategy for Pandemic Influenza (2005)” for the United States from the U.S. Homeland Security Council and “The Canadian Pandemic Influenza Plan for the Health Sector (2006)” from the Canadian Pandemic Influenza Committee for use by the public health agencies in the United States as well as globally. The “global influenza experts’ survey” was primarily designed and administered via email through the “Survey Monkey” system to the 2009 H1N1 influenza pandemic experts as the study respondents. The effectiveness of this plan was confirmed and the approach of the study questionnaire was validated to be convenient and the excellent quality of the questions provided an efficient opportunity to the study respondents to evaluate the effectiveness of predefined strategies/interventions for future pandemic influenza control.^ The quantitative analysis of the responses to the Likert-scale based questions in the survey about predefined strategies/interventions, addressing five strategic issues to control future pandemic influenza. The effectiveness of strategies defined as pertinent interventions in this plan was evaluated by targeting five strategic issues regarding pandemic influenza control. For the first strategic issue pertaining influenza prevention and pre pandemic planning; the confirmed effectiveness (agreement) for strategy (1a) 87.5%, strategy (1b) 91.7% and strategy (1c) 83.3%. The assessment of the priority level for strategies to address the strategic issue no. (1); (1b (High Priority) > 1a (Medium Priority) > 1c (Low Priority) based on the available resources of the developing and developed countries. For the second Strategic Issue encompassing the preparedness and communication regarding pandemic influenza control; the confirmed effectiveness (agreement) for the strategy (2a) 95.6%, strategy (2b) 82.6%, strategy (2c) 91.3% and Strategy (2d) 87.0%. The assessment of the priority level for these strategies to address the strategic issue no. (2); (2a (highest priority) > 2c (high priority) >2d (medium priority) > 2b (low priority). For the third strategic issue encompassing the surveillance and detection of pandemic influenza; the confirmed effectiveness (agreement) for the strategy (3a) 90.9% and strategy (3b) 77.3%. The assessment of the priority level for theses strategies to address the strategic Issue No. (3) (3a (high priority) > 3b (medium/low priority). For the fourth strategic issue pertaining the response and containment of pandemic influenza; the confirmed effectiveness (agreement) for the strategy (4a) 63.6%, strategy (4b) 81.8%, strategy (4c) 86.3%, and strategy (4d) 86.4%. The assessment of the priority level for these strategies to address the strategic issue no. (4); (4d (highest priority) > 4c (high priority) > 4b (medium priority) > 4a (low priority). The fifth strategic issue about recovery from influenza and post pandemic planning; the confirmed effectiveness (agreement) for the strategy (5a) 68.2%, strategy (5b) 36.3% and strategy (5c) 40.9%. The assessment of the priority level for strategies to address the strategic issue no. (5); (5a (high priority) > 5c (medium priority) > 5b (low priority).^ The qualitative analysis of responses to the open-ended questions in the study questionnaire was performed by means of thematic content analysis. The following recurrent or common “themes” were determined for the future implementation of various predefined strategies to address five strategic issues from the “FPIC related Strategic Management Plan” to control future influenza pandemics. (1) Pre Pandemic Influenza Prevention, (2) Seasonal Influenza Control, (3) Cost Effectiveness of Non Pharmaceutical Interventions (NPI), (4) Raising Global Public Awareness, (5) Global Influenza Vaccination Campaigns, (6)Priority for High Risk Population, (7) Prompt Accessibility and Distribution of Influenza Vaccines and Antiviral Drugs, (8) The Vital Role of Private Sector, (9) School Based Influenza Containment, (10) Efficient Global Risk Communication, (11) Global Research Collaboration, (12) The Critical Role of Global Public Health Organizations, (13) Global Syndromic Surveillance and Surge Capacity and (14) Post Pandemic Recovery and Lessons Learned. The future implementation of these strategies with confirmed effectiveness to primarily “reduce the overall response time’ in the process of ‘early detection’, ‘strategies (interventions) formulation’ and their ‘implementation’ to eventually ensure the following health outcomes: (a) reduced influenza transmission, (b) prompt and effective influenza treatment and control, (c) reduced influenza related morbidity and mortality.^

COMPREHENSIVE CALCULATION-BASED IMRT QA USING R&V DATA, TREATMENT RECORDS, AND A SECOND TREATMENT PLANNING SYSTEM

Purpose: Traditional patient-specific IMRT QA measurements are labor intensive and consume machine time. Calculation-based IMRT QA methods typically are not comprehensive. We have developed a comprehensive calculation-based IMRT QA method to detect uncertainties introduced by the initial dose calculation, the data transfer through the Record-and-Verify (R&V) system, and various aspects of the physical delivery. Methods: We recomputed the treatment plans in the patient geometry for 48 cases using data from the R&V, and from the delivery unit to calculate the “as-transferred” and “as-delivered” doses respectively. These data were sent to the original TPS to verify transfer and delivery or to a second TPS to verify the original calculation. For each dataset we examined the dose computed from the R&V record (RV) and from the delivery records (Tx), and the dose computed with a second verification TPS (vTPS). Each verification dose was compared to the clinical dose distribution using 3D gamma analysis and by comparison of mean dose and ROI-specific dose levels to target volumes. Plans were also compared to IMRT QA absolute and relative dose measurements. Results: The average 3D gamma passing percentages using 3%-3mm, 2%-2mm, and 1%-1mm criteria for the RV plan were 100.0 (σ=0.0), 100.0 (σ=0.0), and 100.0 (σ=0.1); for the Tx plan they were 100.0 (σ=0.0), 100.0 (σ=0.0), and 99.0 (σ=1.4); and for the vTPS plan they were 99.3 (σ=0.6), 97.2 (σ=1.5), and 79.0 (σ=8.6). When comparing target volume doses in the RV, Tx, and vTPS plans to the clinical plans, the average ratios of ROI mean doses were 0.999 (σ=0.001), 1.001 (σ=0.002), and 0.990 (σ=0.009) and ROI-specific dose levels were 0.999 (σ=0.001), 1.001 (σ=0.002), and 0.980 (σ=0.043), respectively. Comparing the clinical, RV, TR, and vTPS calculated doses to the IMRT QA measurements for all 48 patients, the average ratios for absolute doses were 0.999 (σ=0.013), 0.998 (σ=0.013), 0.999 σ=0.015), and 0.990 (σ=0.012), respectively, and the average 2D gamma(5%-3mm) passing percentages for relative doses for 9 patients was were 99.36 (σ=0.68), 99.50 (σ=0.49), 99.13 (σ=0.84), and 98.76 (σ=1.66), respectively. Conclusions: Together with mechanical and dosimetric QA, our calculation-based IMRT QA method promises to minimize the need for patient-specific QA measurements by identifying outliers in need of further review.