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1.
J Hum Nutr Diet ; 35(6): 1178-1191, 2022 12.
Article in English | MEDLINE | ID: mdl-34921448

ABSTRACT

BACKGROUND: Dietary management plays an important role in patients with kidney failure. Current dietary habits of Australians and New Zealanders (ANZ) and Malaysians with chronic kidney disease (CKD Stage 4-5) have not been adequately investigated. We report the dietary habits of people with advanced CKD and their adherence to country-specific dietary guidelines. METHODS: Participants with CKD Stage 4-5, enrolled in the Omega-3 Fatty Acids (Fish oils) and Aspirin in Vascular access Outcomes in Renal Disease (FAVOURED) trial, completed a lifestyle questionnaire at baseline on their dietary intake. RESULTS: Of 567 participants, 538 (ANZ, n = 386; Malaysian, n = 152; mean ± SD age 54.8 ± 14.3 years, 64% male) completed the questionnaire. Dietary fruit and vegetable intakes were higher in ANZ participants; 49% (n = 189) consumed ≥2 serves day-1 of fruit and 61% (n = 235) ate ≥2 serves day-1 of vegetables compared to 24% (n = 36) and 34% (n = 52) of Malaysians, respectively (p < 0.0001). Only 4% (n = 15) of ANZ participants met Australian Dietary recommendations of two fruit and five vegetable serves day-1 . Fish consumption was higher in Malaysians with 83% (n = 126) consuming ≥2 serves week-1 compared to 21% (n = 81) of ANZ participants (p < 0.001). Red meat intake was higher in ANZ participants; however, chicken consumption was similar; 48% (n = 185) consumed >2 chicken serves week-1 and 65% (n = 251) ate >2 serves week-1 of red meat compared to 43% (n = 65) and 15% (n = 23) of Malaysians, respectively. CONCLUSIONS: Significant regional variation in dietary intake for fruit, vegetables and animal protein is described that likely reflects cultural and economic differences. Barriers to meeting recommended dietary intakes require further investigation.


Subject(s)
Renal Insufficiency, Chronic , Vegetables , Animals , Humans , Male , Female , Cross-Sectional Studies , New Zealand , Australia , Feeding Behavior , Diet , Fruit
2.
J Clin Oncol ; 41(15): 2756-2766, 2023 05 20.
Article in English | MEDLINE | ID: mdl-36473135

ABSTRACT

PURPOSE: Quitting smoking improves patients' clinical outcomes, yet smoking is not commonly addressed as part of cancer care. The Cancer Center Cessation Initiative (C3I) supports National Cancer Institute-designated cancer centers to integrate tobacco treatment programs (TTPs) into routine cancer care. C3I centers vary in size, implementation strategies used, and treatment approaches. We examined associations of these contextual factors with treatment reach and smoking cessation effectiveness. METHODS: This cross-sectional study used survey data from 28 C3I centers that reported tobacco treatment data during the first 6 months of 2021. Primary outcomes of interest were treatment reach (reach)-the proportion of patients identified as currently smoking who received at least one evidence-based tobacco treatment component (eg, counseling and pharmacotherapy)-and smoking cessation effectiveness (effectiveness)-the proportion of patients reporting 7-day point prevalence abstinence at 6-month follow-up. Center-level differences in reach and effectiveness were examined by center characteristics, implementation strategies, and tobacco treatment components. RESULTS: Of the total 692,662 unique patients seen, 44,437 reported current smoking. Across centers, a median of 96% of patients were screened for tobacco use, median smoking prevalence was 7.4%, median reach was 15.4%, and median effectiveness was 18.4%. Center-level characteristics associated with higher reach included higher smoking prevalence, use of center-wide TTP, and lower patient-to-tobacco treatment specialist ratio. Higher effectiveness was observed at centers that served a larger overall population and population of patients who smoke, reported a higher smoking prevalence, and/or offered electronic health record referrals via a closed-loop system. CONCLUSION: Whole-center TTP implementation among inpatients and outpatients, and increasing staff-to-patient ratios may improve TTP reach. Designating personnel with tobacco treatment expertise and resources to increase tobacco treatment dose or intensity may improve smoking cessation effectiveness.


Subject(s)
Neoplasms , Smoking Cessation , United States/epidemiology , Humans , Nicotiana , National Cancer Institute (U.S.) , Cross-Sectional Studies , Smoking Cessation/psychology , Tobacco Use , Neoplasms/epidemiology , Neoplasms/therapy
3.
Implement Sci Commun ; 4(1): 50, 2023 May 11.
Article in English | MEDLINE | ID: mdl-37170381

ABSTRACT

BACKGROUND: The Cancer Center Cessation Initiative (C3I) is a National Cancer Institute (NCI) Cancer Moonshot Program that supports NCI-designated cancer centers developing tobacco treatment programs for oncology patients who smoke. C3I-funded centers implement evidence-based programs that offer various smoking cessation treatment components (e.g., counseling, Quitline referrals, access to medications). While evaluation of implementation outcomes in C3I is guided by evaluation of reach and effectiveness (via RE-AIM), little is known about technical efficiency-i.e., how inputs (e.g., program costs, staff time) influence implementation outcomes (e.g., reach, effectiveness). This study demonstrates the application of data envelopment analysis (DEA) as an implementation science tool to evaluate technical efficiency of C3I programs and advance prioritization of implementation resources. METHODS: DEA is a linear programming technique widely used in economics and engineering for assessing relative performance of production units. Using data from 16 C3I-funded centers reported in 2020, we applied input-oriented DEA to model technical efficiency (i.e., proportion of observed outcomes to benchmarked outcomes for given input levels). The primary models used the constant returns-to-scale specification and featured cost-per-participant, total full-time equivalent (FTE) effort, and tobacco treatment specialist effort as model inputs and reach and effectiveness (quit rates) as outcomes. RESULTS: In the DEA model featuring cost-per-participant (input) and reach/effectiveness (outcomes), average constant returns-to-scale technical efficiency was 25.66 (SD = 24.56). When stratified by program characteristics, technical efficiency was higher among programs in cohort 1 (M = 29.15, SD = 28.65, n = 11) vs. cohort 2 (M = 17.99, SD = 10.16, n = 5), with point-of-care (M = 33.90, SD = 28.63, n = 9) vs. no point-of-care services (M = 15.59, SD = 14.31, n = 7), larger (M = 33.63, SD = 30.38, n = 8) vs. smaller center size (M = 17.70, SD = 15.00, n = 8), and higher (M = 29.65, SD = 30.99, n = 8) vs. lower smoking prevalence (M = 21.67, SD = 17.21, n = 8). CONCLUSION: 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.

4.
Implement Sci Commun ; 2(1): 41, 2021 Apr 09.
Article in English | MEDLINE | ID: mdl-33836840

ABSTRACT

BACKGROUND: The Cancer Center Cessation Initiative (C3I) was launched in 2017 as a part of the NCI Cancer Moonshot program to assist NCI-designated cancer centers in developing tobacco treatment programs for oncology patients. Participating centers have implemented varied evidence-based programs that fit their institutional resources and needs, offering a wide range of services including in-person and telephone-based counseling, point of care, interactive voice response systems, referral to the quitline, text- and web-based services, and medications. METHODS: We used a mixed methods comparative case study design to evaluate system-level implementation costs across 15 C3I-funded cancer centers that reported for at least one 6-month period between July 2018 and June 2020. We analyzed operating costs by resource category (e.g., personnel, medications) concurrently with transcripts from semi-structured key-informant interviews conducted during site visits. Personnel salary costs were estimated using Bureau of Labor Statistics wage data adjusted for area and occupation, and non-wage benefits. Qualitative findings provided additional information on intangible resources and contextual factors related to implementation costs. RESULTS: Median total monthly operating costs across funded centers were $11,045 (range: $5129-$20,751). The largest median operating cost category was personnel ($10,307; range: $4122-$19,794), with the highest personnel costs attributable to the provision of in-person program services. Monthly (non-zero) cost ranges for other categories were medications ($17-$573), materials ($6-$435), training ($96-$516), technology ($171-$2759), and equipment ($10-$620). Median cost-per-participant was $466 (range: $70-$2093) and cost-per-quit was $2688 (range: $330-$9628), with sites offering different combinations of program components, ranging from individually-delivered in-person counseling only to one program that offered all components. Site interviews provided context for understanding variations in program components and their cost implications. CONCLUSIONS: Among most centers that have progressed in tobacco treatment program implementation, cost-per-quit was modest relative to other prevention interventions. Although select centers have achieved similar average costs by offering program components of various levels of intensity, they have varied widely in program reach and effectiveness. Evaluating implementation costs of such programs alongside reach and effectiveness is necessary to provide decision makers in oncology settings with the important additional information needed to optimize resource allocation when establishing tobacco treatment programs.

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