Aligning quality improvement efforts and policy goals in a national integrated health system

OBJECTIVE

To describe the design and impact of a systematic, enterprise-wide process for engaging US Department of Veterans Affairs (VA) leadership in prioritizing scarce implementation and evaluation resources.

DATA SOURCES

From 2017 to 2021, the VA Quality Enhancement Research Initiative (QUERI) identified priorities from local, regional, and national leaders through qualitative discussions and a national survey and tracked impacts via reports generated from competitively funded initiatives addressing these priorities.

STUDY DESIGN

Guided by the Learning Health System framework and QUERI Implementation Roadmap, QUERI engaged stakeholders to nominate and rank-order priorities, peer-reviewed and funded initiatives to scale up and spread evidence-based practices (EBPs) using theory-based implementation strategies, and evaluated the impact of these initiatives using the QUERI Impact Framework.

DATA COLLECTION/EXTRACTION METHODS

QUERI collected priority nominations through qualitative discussions and a web-based survey, and live voting was used to rank-order priorities. QUERI-funded teams regularly submitted progress reports describing the key activities, findings, and impacts of the quality improvement (QI) initiatives using a standardized form created in the VA Research Electronic Data Capture (REDCap).

PRINCIPAL FINDINGS

QUERI launched five QI initiatives to address priorities selected by VA leadership. In partnership with 28 health system leaders, these initiatives are implementing 10 EBPs across 53 sites, supporting 1055 VA employees in delivering evidence-based care. The success of these initiatives led to an expansion of QUERI's process to address 2021 VA leadership priorities: virtual care, health disparities, delayed or suppressed care due to COVID-19, employee burnout, long-term and home care options, and quality and cost of community care.

CONCLUSIONS

QUERI, a unique program embedded in a national integrated health system, deployed a novel approach to inform policy making and enhance the real-world impact of research through prioritization of limited resources, rigorous peer-review, and assessment of impacts on the health system, employees, and Veterans.

The Quality Enhancement Research Initiative (QUERI) Impact Framework: Measuring the Real-world Impact of Implementation Science

BACKGROUND

Measuring the health, economic, and cultural gains generated by scientific investments is crucial to reducing waste and improving quality of care. To date, there is no comprehensive framework for assessing the multi-faceted contributions of implementation and quality improvement sciences towards quality, cost, and patient and provider experiences in health systems.

OBJECTIVE

We describe the Quality Enhancement Research Initiative (QUERI) Impact Framework and its application to QUERI investments.

METHODS

The QUERI Impact Framework adapts and expands on metrics from the National Academy of Medicine, incorporating lessons learned from QUERI initiatives. The cross-cutting impact metrics reflect QUERI's strategic methodology across five domains of impact (Alignment, Commitment, Tailoring, Informing the field, Observing healthcare changes and generating New questions/projects or ACTION). Key impact metrics, including the number of implementation facilities, number of staff trained, and number of patients served, were derived directly from health system performance plan goals. QUERI applied the Framework by conducting iterative rapid assessments of impacts for QUERI Program centers, which are implementation laboratories that support 3-7 initiatives aligned with a cross-disciplinary goal addressing a national priority.

KEY RESULTS

From October 2015 to September 2019, QUERI Programs supported implementation of 49 evidence-based practices and promising innovations across 465 facilities, including 15 facilities that are experiencing quality gaps. As part of these implementation efforts, the programs worked with 71 operations partners to develop 71 tools/toolkits/manuals and support training of 5147 VA staff, serving 250,159 Veterans.

CONCLUSIONS

The QUERI Impact Framework aligns multiple stakeholders at different levels of a health system around common metrics, which cross implementation science and quality improvement boundaries. The Framework supports a comprehensive assessment of the short-term and distal impacts of implementation efforts in a health system, allowing both research and operations leadership to understand the value of implementation and quality improvement investments to inform program and policy decisions.

Research Lifecycle to Increase the Substantial Real-world Impact of Research: Accelerating Innovations to Application

BACKGROUND

US health care systems face a growing demand to incorporate innovations that improve patient outcomes at a lower cost. Funding agencies increasingly must demonstrate the impact of research investments on public health. The Learning Health System promotes continuous institutional innovation, yet specific processes to develop innovations for further research and implementation into real-world health care settings to maximize health impacts have not been specified.

OBJECTIVE

We describe the Research Lifecycle and how it leverages institutional priorities to support the translation of research discoveries to clinical application, serving as a broader operational approach to enhance the Learning Health System.

METHODS

Developed by the US Department of Veterans Affairs Office of Research and Development Research-to-Real-World Workgroup, the Research Lifecycle incorporates frameworks from product development, translational science, and implementation science methods. The Lifecycle is based on Workgroup recommendations to overcome barriers to more direct translation of innovations to clinical application and support practice implementation and sustainability.

RESULTS

The Research Lifecycle posits 5 phases which support a seamless pathway from discovery to implementation: prioritization (leadership priority alignment), discovery (innovation development), validation (clinical, operational feasibility), scale-up and spread (implementation strategies, performance monitoring), and sustainability (business case, workforce training). An example of how the Research Lifecycle has been applied within a health system is provided.

CONCLUSIONS

The Research Lifecycle aligns research and health system investments to maximize real-world practice impact via a feasible pathway, where priority-driven innovations are adapted for effective clinical use and supported through implementation strategies, leading to continuous improvement in real-world health care.

Relationship between paediatric CT scans and subsequent risk of leukaemia and brain tumours: assessment of the impact of underlying conditions

BACKGROUND

We previously reported evidence of a dose-response relationship between ionising-radiation exposure from paediatric computed tomography (CT) scans and the risk of leukaemia and brain tumours in a large UK cohort. Underlying unreported conditions could have introduced bias into these findings.

METHODS

We collected and reviewed additional clinical information from radiology information systems (RIS) databases, underlying cause of death and pathology reports. We conducted sensitivity analyses excluding participants with cancer-predisposing conditions or previous unreported cancers and compared the dose-response analyses with our original results.

RESULTS

We obtained information from the RIS and death certificates for about 40% of the cohort (n∼180 000) and found cancer-predisposing conditions in 4 out of 74 leukaemia/myelodysplastic syndrome (MDS) cases and 13 out of 135 brain tumour cases. As these conditions were unrelated to CT exposure, exclusion of these participants did not alter the dose-response relationships. We found evidence of previous unreported cancers in 2 leukaemia/MDS cases, 7 brain tumour cases and 232 in non-cases. These previous cancers were related to increased number of CTs. Exclusion of these cancers reduced the excess relative risk per mGy by 15% from 0.036 to 0.033 for leukaemia/MDS (P-trend=0.02) and by 30% from 0.023 to 0.016 (P-trend<0.0001) for brain tumours. When we included pathology reports we had additional clinical information for 90% of the cases. Additional exclusions from these reports further reduced the risk estimates, but this sensitivity analysis may have underestimated risks as reports were only available for cases.

CONCLUSIONS

Although there was evidence of some bias in our original risk estimates, re-analysis of the cohort with additional clinical data still showed an increased cancer risk after low-dose radiation exposure from CT scans in young patients.

Adolescent and mid-life diet and subsequent risk of thyroid cancer in the NIH-AARP diet and health study

Although thyroid cancer is suspected to have a nutritional etiology, prospective studies examining the relationship between diet and thyroid cancer are lacking. During 1996-1997, NIH-AARP Diet and Health Study participants, ages 51-72 years, completed a 37-item food frequency questionnaire about diet at ages 12-13 years (adolescence) and 10 years before baseline (mid-life). Over a median 10 years of follow-up, 325 individuals (143 men and 182 women) were diagnosed with thyroid cancer. Multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated for intakes of foods and food groups comparing the highest to the lowest quartiles. Adolescent intakes of chicken/turkey (HR = 1.59, 95% CI: 0.97-2.60; ptrend  < 0.01) and sweet baked goods (HR = 1.59, 95% CI: 1.09-2.34; ptrend  = 0.04) were positively associated with thyroid cancer risk, while intake of butter/margarine was inversely associated with risk (HR = 0.64, 95% CI: 0.44-0.91; ptrend  < 0.02). Similar to adolescent diet, mid-life intake of sweet baked goods was nonsignificantly associated with an increased risk of thyroid cancer (HR = 1.39, 95% CI: 0.96-2.00; ptrend  = 0.11), but intake of butter/margarine was inversely associated with risk (HR = 0.66, 95% CI: 0.46-0.95; ptrend  = 0.03). Among men, higher adolescent consumption of canned tuna was positively associated with risk of thyroid cancer (HR = 1.69, 95% CI: 1.01-2.83; ptrend  = 0.03), and greater mid-life intake of broccoli was associated with a twofold increased risk (HR = 2.13, 95% CI: 1.13-3.99; ptrend  < 0.01). This large prospective study suggests that several components of the adolescent and mid-life diet, including iodine-rich foods and goitrogens, may influence thyroid cancer risk.

Benign breast and gynecologic conditions, reproductive and hormonal factors, and risk of thyroid cancer

The higher incidence of thyroid cancer in women compared with men suggests an influence of sex steroid hormones in the etiology of this malignancy. We investigated a comprehensive set of potential indicators of lifetime sex steroid hormone exposure in relation to thyroid cancer risk. Using data from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, which enrolled 70,047 women, 50 to 78 years old, we prospectively examined associations of self-reported history of benign breast and gynecologic conditions, reproductive factors, and exogenous sex hormone use with thyroid cancer risk. Multivariable-adjusted HRs and 95% confidence intervals (CI) were calculated in models using age as the time metric. During follow-up (median, 11 years), 127 women were diagnosed with first primary thyroid cancer. Older age at natural menopause (≥55 vs. <50 years; HR, 2.24; 95% CI, 1.20-4.18), greater estimated lifetime number of ovulatory cycles (≥490 vs. <415 cycles; HR, 2.40; 95% CI, 1.33-4.30), greater number of live births (≥5 vs. 1-2; HR, 1.72; 95% CI, 1.05-2.82), and history of uterine fibroids (HR, 1.72; 95% CI, 1.18-2.50) were associated with an increased risk of thyroid cancer. Earlier age at menarche, greater number of reproductive years, history of a tubal ligation, and history of ovarian cysts were nonsignificantly associated with increased thyroid cancer risk. No associations were observed for oral contraceptive use, menopausal hormone therapy, or history of benign breast disease or endometriosis. In general, we found that factors reflecting a greater length of exposure to endogenous hormones, particularly during the reproductive years, were associated with risk of postmenopausal thyroid cancer.

Personal history of diabetes, genetic susceptibility to diabetes, and risk of brain glioma: a pooled analysis of observational studies

BACKGROUND

Brain glioma is a relatively rare and fatal malignancy in adulthood with few known risk factors. Some observational studies have reported inverse associations between diabetes and subsequent glioma risk, but possible mechanisms are unclear.

METHODS

We conducted a pooled analysis of original data from five nested case-control studies and two case-control studies from the United States and China that included 962 glioma cases and 2,195 controls. We examined self-reported diabetes history in relation to glioma risk, as well as effect modification by seven glioma risk-associated single-nucleotide polymorphisms (SNP). We also examined the associations between 13 diabetes risk-associated SNPs, identified from genome-wide association studies, and glioma risk. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using multivariable-adjusted logistic regression models.

RESULTS

We observed a 42% reduced risk of glioma for individuals with a history of diabetes (OR = 0.58; 95% CI, 0.40-0.84). The association did not differ by sex, study design, or after restricting to glioblastoma, the most common histological subtype. We did not observe any significant per-allele trends among the 13 diabetes-related SNPs examined in relation to glioma risk.

CONCLUSION

These results support an inverse association between diabetes history and glioma risk. The role of genetic susceptibility to diabetes cannot be excluded, and should be pursued in future studies together with other factors that might be responsible for the diabetes-glioma association.

IMPACT

These data suggest the need for studies that can evaluate, separately, the association between type 1 and type 2 diabetes and subsequent risk of adult glioma.

Abstract 2516: Are alcohol drinking and cigarette smoking related to risk of glioma? A large prospective U.S. cohort study

Background: Glioma is a relatively uncommon and highly fatal malignancy with few known risk factors. Alcohol consumption and cigarette smoking are associated with an increased risk of several types of cancer, but whether these exposures are related to the risk of glioma remains unclear.

Methods: We prospectively examined the relationship between cigarette smoking, alcohol intake, and risk of glioma in the National Institutes of Health-AARP Diet and Health Study, a large prospective cohort of 477,095 U.S. men and women between the ages of 50-71 years. Hazard ratios (HRs) and 95% confidence intervals (CIs) for glioma risk according to alcohol intake (total alcohol, beer, wine, and liquor) and smoking status, intensity, and, among former smokers, time since quitting were calculated using models adjusted for sex, education, marital status, and race/ethnicity.

Results: During a median 10.5 person-years of follow-up, 492 men and 212 women were diagnosed with glioma. Among men, current, heavier (&gt;20 cigarettes per day) smoking was associated with a reduced risk of glioma compared to never smoking (HR=0.40, 95% CI: 0.21-0.79). Men who quit smoking &lt;5 years before baseline had a non-significant reduced risk of glioma (HR=0.73, 95% CI: 0.46-1.14) relative to male never smokers. Smoking behaviors were not associated with glioma risk in women. Greater alcohol consumption was associated with a decreasing risk of glioma in men (&gt;2 drinks per day versus &lt;1 drink per week: HR=0.65, 95% CI: 0.47-0.90; P-trend=0.02) but not women. An inverse association with greater beer intake was apparent both in men (&gt;2 drinks per day versus &lt;1 drink per week: HR=0.56, 95% CI: 0.33-0.93; P-trend=0.03) and women (≥1 drink per week versus &lt;1 drink per week: HR=0.66, 95% CI: 0.33-1.34; P-trend=0.27). Results were similar by education level, after mutual adjustment for smoking and alcohol, and after restricting to glioblastoma, the most common and lethal histological subtype of glioma.

Conclusions: Among men, current, heavy cigarette smoking and greater alcohol, particularly beer, consumption were inversely associated with the risk of glioma. Pooled analyses of prospective studies are needed to investigate more precisely the potential influence of these exposures on glioma risk.

Citation Format: Melissa Z. Braganza, Preetha Rajaraman, Yikyung Park, Peter D. Inskip, Neal D. Freedman, Amy Berrington de González, Cari M. Kitahara. Are alcohol drinking and cigarette smoking related to risk of glioma? A large prospective U.S. cohort study. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2516. doi:10.1158/1538-7445.AM2013-2516

Ionizing radiation and the risk of brain and central nervous system tumors: a systematic review

Although exposure to moderate-to-high doses of ionizing radiation is the only established environmental risk factor for brain and CNS tumors, it is not clear whether this relationship differs across tumor subtypes, by sex or age at exposure, or at the low-to-moderate range of exposure. This systematic review summarizes the epidemiologic evidence on the association between ionizing radiation exposure and risk of brain/CNS tumors. Articles included in this review estimated radiation exposure doses to the brain and reported excess relative risk (ERR) estimates for brain/CNS tumors. Eight cohorts were eligible for inclusion in the analysis. Average age at exposure ranged from 8 months to 26 years. Mean dose to the brain ranged from 0.07 to 10 Gy. Elevated risks for brain/CNS tumors were consistently observed in relation to ionizing radiation exposure, but the strength of this association varied across cohorts. Generally, ionizing radiation was more strongly associated with risk for meningioma compared with glioma. The positive association between ionizing radiation exposure and risk for glioma was stronger for younger vs older ages at exposure. We did not observe an effect modification on the risk for meningioma by sex, age at exposure, time since exposure, or attained age. The etiologic role of ionizing radiation in the development of brain/CNS tumors needs to be clarified further through additional studies that quantify the association between ionizing radiation and risk for brain/CNS tumors at low-to-moderate doses, examine risks across tumor subtypes, and account for potential effect modifiers.