A Scoping Literature Review on Evidence-Based Strategies to Increase Cervical Cancer Screening.

Previous reviews of strategies to increase cervical cancer screening are more than 10 years old, the U.S. continues to fall short of the Healthy People 2030 cervical cancer screening goal, and guidelines were revised in 2018, therefore an updated review of the existing literature is needed. We conducted a scoping review using electronic databases PubMed, Scopus, and Ovid Medline that included publication dates between 2012 and 2021 to answer the question, "Which strategies implemented in U.S. primary care settings have been most successful in increasing rates of cervical cancer screening since the 2012 US Preventative Services Task Force cervical cancer screening guidelines were published?" We mapped findings to pre-specified implementation strategy categories. After initially identifying 399 articles, we excluded 350 due to duplicates or not meeting review criteria, leaving 49 articles for full review. We excluded 37 of these during full-text review and identified 2 additional articles from the manual search of reference lists for a total of 14 studies for abstraction. Eleven articles reported on strategies resulting in increased cervical cancer screening, and 3 did not. Clinic workflow re-design strategies showed the greatest promise in improving cervical cancer screening rates, education strategies for patients had mixed results, and quality management strategies were not effective. These findings suggest clinical workflow re-structures and patient education strategies can increase cervical cancer screening in primary care settings. Results are particularly important in settings that care for underserved populations, as these settings may need additional implementation strategies to decrease cervical cancer screening disparities.

Participatory logic modeling in a multi-site initiative to advance implementation science.

BACKGROUND: Logic models map the short-term and long-term outcomes that are expected to occur with a program, and thus are an essential tool for evaluation. Funding agencies, especially in the United States (US), have encouraged the use of logic models among their grantees. They also use logic models to clarify expectations for their own funding initiatives. It is increasingly recognized that logic models should be developed through a participatory approach which allows input from those who carry out the program being evaluated. While there are many positive examples of participatory logic modeling, funders have generally not engaged grantees in developing the logic model associated with their own initiatives. This article describes an instance where a US funder of a multi-site initiative fully engaged the funded organizations in developing the initiative logic model. The focus of the case study is Implementation Science Centers in Cancer Control (ISC3), a multi-year initiative funded by the National Cancer Institute. METHODS: The reflective case study was collectively constructed by representatives of the seven centers funded under ISC3. Members of the Cross-Center Evaluation (CCE) Work Group jointly articulated the process through which the logic model was developed and refined. Individual Work Group members contributed descriptions of how their respective centers reviewed and used the logic model. Cross-cutting themes and lessons emerged through CCE Work Group meetings and the writing process. RESULTS: The initial logic model for ISC3 changed in significant ways as a result of the input of the funded groups. Authentic participation in the development of the logic model led to strong buy-in among the centers, as evidenced by their utilization. The centers shifted both their evaluation design and their programmatic strategy to better accommodate the expectations reflected in the initiative logic model. CONCLUSIONS: The ISC3 case study demonstrates how participatory logic modeling can be mutually beneficial to funders, grantees and evaluators of multi-site initiatives. Funded groups have important insights about what is feasible and what will be required to achieve the initiative's stated objectives. They can also help identify the contextual factors that either inhibit or facilitate success, which can then be incorporated into both the logic model and the evaluation design. In addition, when grantees co-develop the logic model, they have a better understanding and appreciation of the funder's expectations and thus are better positioned to meet those expectations.

Delivery of Cervical and Colorectal Cancer Screenings During the Pandemic in Community Health Centers: Practice Changes and Recovery Strategies.

BACKGROUND: The coronavirus disease 2019 pandemic led to clinical practice changes, which affected cancer preventive care delivery. OBJECTIVES: To investigate the impact of the coronavirus disease 2019 pandemic on the delivery of colorectal cancer (CRC) and cervical cancer (CVC) screenings. RESEARCH DESIGN: Parallel mixed methods design using electronic health record data (extracted between January 2019 and July 2021). Study results focused on 3 pandemic-related periods: March-May 2020, June-October 2020, and November 2020-September 2021. SUBJECTS: Two hundred seventeen community health centers located in 13 states and 29 semistructured interviews from 13 community health centers. MEASURES: Monthly up-to-date CRC and CVC screening rates and monthly rates of completed colonoscopies, fecal immunochemical test (FIT)/fecal occult blood test (FOBT) procedures, Papanicolaou tests among age and sex-eligible patients. Analysis used generalized estimating equations Poisson modeling. Qualitative analysts developed case summaries and created a cross-case data display for comparison. RESULTS: The results showed a reduction of 75% for colonoscopy [rate ratio (RR) = 0.250, 95% CI: 0.224-0.279], 78% for FIT/FOBT (RR = 0.218, 95% CI: 0.208-0.230), and 87% for Papanicolaou (RR = 0.130, 95% CI: 0.125-0.136) rates after the start of the pandemic. During this early pandemic period, CRC screening was impacted by hospitals halting services. Clinic staff moved toward FIT/FOBT screenings. CVC screening was impacted by guidelines encouraging pausing CVC screening, patient reluctance, and concerns about exposure. During the recovery period, leadership-driven preventive care prioritization and quality improvement capacity influenced CRC and CVC screening maintenance and recovery. CONCLUSIONS: Efforts supporting quality improvement capacity could be key actionable elements for these health centers to endure major disruptions to their care delivery system and to drive rapid recovery.

Participatory Logic Modeling in a Multi-Site Initiative to Advance Implementation Science.

Background: It is increasingly being recognized that logic models should be developed through a participatory approach which allows input from those who carry out the program being evaluated. While there are many positive examples of participatory logic modeling, funders have generally not used this approach in the context of multi-site initiatives. This article describes an instance where the funder and evaluator of a multi-site initiative fully engaged the funded organizations in developing the initiative logic model. The focus of the case study is Implementation Science Centers in Cancer Control (ISC 3 ), a multi-year initiative funded by the National Cancer Institute (NCI). Methods: The case study was collectively constructed by representatives of the seven centers funded under ISC 3 . Members of the Cross-Center Evaluation (CCE) Work Group jointly articulated the process through which the logic model was developed and refined. Individual Work Group members contributed descriptions of how their respective centers reviewed and used the logic model. Cross-cutting themes and lessons emerged through CCE Work Group meetings and the writing process. Results: The initial logic model for ISC 3 changed in significant ways as a result of the input of the funded groups. Authentic participation in the development of the logic model led to strong buy-in among the centers, as evidenced by their utilization. The centers shifted both their evaluation design and their programmatic strategy to better accommodate the expectations reflected in the initiative logic model. Conclusions: The ISC 3 case study provides a positive example of how participatory logic modeling can be mutually beneficial to funders, grantees and evaluators of multi-site initiatives. Funded groups have important insights about what is feasible and what will be required to achieve the initiative's stated objectives. They can also help identify the contextual factors that either inhibit or facilitate success, which can then be incorporated into both the logic model and the evaluation design. In addition, when grantees co-develop the logic model, they have a better understanding and appreciation of the funder's expectations, and thus are better positioned to meet those expectations.

Creating research-ready partnerships: the initial development of seven implementation laboratories to advance cancer control.

BACKGROUND: In 2019-2020, with National Cancer Institute funding, seven implementation laboratory (I-Lab) partnerships between scientists and stakeholders in 'real-world' settings working to implement evidence-based interventions were developed within the Implementation Science Centers in Cancer Control (ISC3) consortium. This paper describes and compares approaches to the initial development of seven I-Labs in order to gain an understanding of the development of research partnerships representing various implementation science designs. METHODS: In April-June 2021, members of the ISC3 Implementation Laboratories workgroup interviewed research teams involved in I-Lab development in each center. This cross-sectional study used semi-structured interviews and case-study-based methods to collect and analyze data about I-Lab designs and activities. Interview notes were analyzed to identify a set of comparable domains across sites. These domains served as the framework for seven case descriptions summarizing design decisions and partnership elements across sites. RESULTS: Domains identified from interviews as comparable across sites included engagement of community and clinical I-Lab members in research activities, data sources, engagement methods, dissemination strategies, and health equity. The I-Labs use a variety of research partnership designs to support engagement including participatory research, community-engaged research, and learning health systems of embedded research. Regarding data, I-Labs in which members use common electronic health records (EHRs) leverage these both as a data source and a digital implementation strategy. I-Labs without a shared EHR among partners also leverage other sources for research or surveillance, most commonly qualitative data, surveys, and public health data systems. All seven I-Labs use advisory boards or partnership meetings to engage with members; six use stakeholder interviews and regular communications. Most (70%) tools or methods used to engage I-Lab members such as advisory groups, coalitions, or regular communications, were pre-existing. Think tanks, which two I-Labs developed, represented novel engagement approaches. To disseminate research results, all centers developed web-based products, and most (n = 6) use publications, learning collaboratives, and community forums. Important variations emerged in approaches to health equity, ranging from partnering with members serving historically marginalized populations to the development of novel methods. CONCLUSIONS: The development of the ISC3 implementation laboratories, which represented a variety of research partnership designs, offers the opportunity to advance understanding of how researchers developed and built partnerships to effectively engage stakeholders throughout the cancer control research lifecycle. In future years, we will be able to share lessons learned for the development and sustainment of implementation laboratories.

Association of parent influenza vaccination and early childhood vaccinations using linked electronic health record data.

INTRODUCTION: Parent and child vaccination behavior is related for human papillomavirus (HPV) and flu vaccine. Thus, it is likely that parental vaccination status is also associated with their children's adherence to guideline-concordant childhood vaccination schedules. We hypothesized that parent influenza (flu) vaccination would be associated with their child's vaccination status at age two. METHODS: We used electronic health record data to identify children and linked parents seen in a community health center (CHC) within the OCHIN network (292 CHCs in 16 states). We randomly selected a child aged <2 years with ≥1 ambulatory visit between 2009-2018. Employing a retrospective, cohort study design, we used general estimating equations logistic regression to estimate the odds of a child being up-to-date on vaccinations based on their linked parents' flu vaccination status. We adjusted for relevant parent and child covariates and stratified by mother only, father only, and two-parent samples. RESULTS: The study included 40,007 family-units: mother only = 35,444, father only = 2,784, and two parents = 1,779. A higher percentage of children were fully vaccinated if their parent or parents received a flu vaccine. Children in the two-parent sample whose parents both received a flu vaccine had more than twice the odds of being fully vaccinated, and two and a half times the odds of being fully vaccinated except flu vaccine compared to children with two parents who did not receive a flu vaccine (covariate-adjusted odds ratio [aOR] = 2.39, 95% CI = 1.67, 3.43 and aOR = 2.54, 95% CI = 1.54, 4.19, respectively). CONCLUSIONS: Parent flu vaccination is associated with routine child vaccination. Future research is needed to understand if this relationship persists over time and in different settings.

Affordable Care Act Medicaid expansion and access to primary-care based smoking cessation assistance among cancer survivors: an observational cohort study.

BACKGROUND: Smoking among cancer survivors can increase the risk of cancer reoccurrence, reduce treatment effectiveness and decrease quality of life. Cancer survivors without health insurance have higher rates of smoking and decreased probability of quitting smoking than cancer survivors with health insurance. This study examines the associations of the Affordable Care Act (ACA) Medicaid insurance expansion with smoking cessation assistance and quitting smoking among cancer survivors seen in community health centers (CHCs). METHODS: Using electronic health record data from 337 primary care community health centers in 12 states that expanded Medicaid eligibility and 273 CHCs in 8 states that did not expand, we identified adult cancer survivors with a smoking status indicating current smoking within 6 months prior to ACA expansion in 2014 and ≥ 1 visit with smoking status assessed within 24-months post-expansion. Using an observational cohort propensity score weighted approach and logistic generalized estimating equation regression, we compared odds of quitting smoking, having a cessation medication ordered, and having ≥6 visits within the post-expansion period among cancer survivors in Medicaid expansion versus non-expansion states. RESULTS: Cancer survivors in expansion states had higher odds of having a smoking cessation medication order (adjusted odds ratio [aOR] = 2.54, 95%CI = 1.61-4.03) and higher odds of having ≥6 office visits than those in non-expansion states (aOR = 1.82, 95%CI = 1.22-2.73). Odds of quitting smoking did not differ significantly between patients in Medicaid expansion versus non-expansion states. CONCLUSIONS: The increased odds of having a smoking cessation medication order among cancer survivors seen in Medicaid expansion states compared with those seen in non-expansion states provides evidence of the importance of health insurance coverage in accessing evidence-based tobacco treatment within CHCs. Continued research is needed to understand why, despite increased odds of having a cessation medication prescribed, odds of quitting smoking were not significantly higher among cancer survivors in Medicaid expansion states compared to non-expansion states.

Community Health Centers' Performance in Cancer Screening and Prevention.

INTRODUCTION: Little is known about what clinic-level factors differentiate community health centers that achieve high performance on cancer-preventive care metrics. This study aims to describe the longitudinal trends in the delivery of 3 cancer-preventive care metrics (cervical and colorectal cancer screenings and tobacco-cessation intervention) and define and compare community health centers with high cancer-preventive care performance with those with low cancer-preventive care performance. METHODS: This observational study used 2012-2019 community health center data (N=933) from the Uniform Data System. High/low performance was based on Healthy People 2020 targets and sample distribution. For each cancer-preventive care metric, the percentage of community health centers that met high (≥70.5% at cervical or colorectal cancer screening or >80% tobacco-cessation intervention) and low thresholds at 1, 2, and all the 3 screenings was estimated. Multivariable generalized estimating equations logistic regression modeling was used to assess the community health center‒level factors associated with screening performance. RESULTS: The community health centers' performance for tobacco-cessation intervention remained at ≥80%, with a small increase over time. Performance for cervical cancer screening remained unchanged with about 50% of patients screened. Colorectal cancer screening performance increased from around 30% in 2012 to 44% in 2019. Very few community health centers reached high performance (3%) in all the 3 indicators, and 13% of community health centers were high in any 2 of the outcomes in 2019. Higher patient volume, a greater proportion of Hispanic patients, fewer uninsured patients, and community health centers located in the Northeast region were associated with high performance in 2019. CONCLUSIONS: Very few community health centers meet all Healthy People 2020 goals in cancer screenings and may struggle to achieve the 2030 goals. Very few indicators differentiated high performers from low performers.

Effectiveness of an insurance enrollment support tool on insurance rates and cancer prevention in community health centers: a quasi-experimental study.

BACKGROUND: Following the ACA, millions of people gained Medicaid insurance. Most electronic health record (EHR) tools to date provide clinical-decision support and tracking of clinical biomarkers, we developed an EHR tool to support community health center (CHC) staff in assisting patients with health insurance enrollment documents and tracking insurance application steps. The objective of this study was to test the effectiveness of the health insurance support tool in (1) assisting uninsured patients gaining insurance coverage, (2) ensuring insurance continuity for patients with Medicaid insurance (preventing coverage gaps between visits); and (3) improving receipt of cancer preventive care. METHODS: In this quasi-experimental study, twenty-three clinics received the intervention (EHR-based insurance support tool) and were matched to 23 comparison clinics. CHCs were recruited from the OCHIN network. EHR data were linked to Medicaid enrollment data. The primary outcomes were rates of uninsured and Medicaid visits. The secondary outcomes were receipt of recommended breast, cervical, and colorectal cancer screenings. A comparative interrupted time-series using Poisson generalized estimated equation (GEE) modeling was performed to evaluate the effectiveness of the EHR-based tool on the primary and secondary outcomes. RESULTS: Immediately following implementation of the enrollment tool, the uninsured visit rate decreased by 21.0% (Adjusted Rate Ratio [RR] = 0.790, 95% CI = 0.621-1.005, p = .055) while Medicaid-insured visits increased by 4.5% (ARR = 1.045, 95% CI = 1.013-1.079) in the intervention group relative to comparison group. Cervical cancer preventive ratio increased 5.0% (ARR = 1.050, 95% CI = 1.009-1.093) immediately following implementation of the enrollment tool in the intervention group relative to comparison group. Among patients with a tool use, 81% were enrolled in Medicaid 12 months after tool use. For the 19% who were never enrolled in Medicaid following tool use, most were uninsured (44%) at the time of tool use. CONCLUSIONS: A health insurance support tool embedded within the EHR can effectively support clinic staff in assisting patients in maintaining their Medicaid coverage. Such tools may also have an indirect impact on evidence-based practice interventions, such as cancer screening. TRIAL REGISTRATION: This study was retrospectively registered on February 4th, 2015 with Clinicaltrials.gov (#NCT02355262). The registry record can be found at https://www.clinicaltrials.gov/ct2/show/NCT02355262 .

Assessing Cancer History Accuracy in Primary Care Electronic Health Records Through Cancer Registry Linkage.

BACKGROUND: Many cancer survivors receive primary care in community health centers (CHCs). Cancer history is an important factor to consider in the provision of primary care, yet little is known about the completeness or accuracy of cancer history data contained in CHC electronic health records (EHRs). METHODS: We probabilistically linked EHR data from more than1.5 million adult CHC patients to state cancer registries in California, Oregon, and Washington and estimated measures of agreement (eg, kappa, sensitivity, specificity). We compared demographic and clinical characteristics of cancer patients as estimated by each data source, evaluating distributional differences with absolute standardized mean differences. RESULTS: A total 74 707 cancer patients were identified between the 2 sources (EHR only, n = 22 730; registry only, n = 23 616; both, n = 28 361). Nearly one-half of cancer patients identified in registries were missing cancer documentation in the EHR. Overall agreement of cancer ascertainment in the EHR vs cancer registries (gold standard) was moderate (kappa = 0.535). Cancer site-specific agreement ranged from substantial (eg, prostate and female breast; kappa > 0.60) to fair (melanoma and cervix; kappa < 0.40). Comparing population characteristics of cancer patients as ascertained from each data source, groups were similar for sex, age, and federal poverty level, but EHR-recorded cases showed greater medical complexity than those ascertained from cancer registries. CONCLUSIONS: Agreement between EHR and cancer registry data was moderate and varied by cancer site. These findings suggest the need for strategies to improve capture of cancer history information in CHC EHRs to ensure adequate delivery of care and optimal health outcomes for cancer survivors.

Uptake of Preventive Services Among Patients With and Without Multimorbidity.

INTRODUCTION: Patients with multiple chronic conditions (multimorbidity) are seen commonly in primary care practices and often have suboptimal uptake of preventive care owing to competing treatment demands. The complexity of multimorbidity patterns and their impact on receiving preventive services is not fully understood. This study identifies multimorbidity combinations associated with low receipt of preventive services. METHODS: This was a retrospective cohort study of U.S. community health center patients aged ≥19 years. Electronic health record data from 209 community health centers for the January 1, 2014-December 31, 2017 study period were analyzed in 2018-2019. Multimorbidity patterns included physical only, mental health only, and physical and mental health multimorbidity patterns, with no multimorbidity as a reference category. Electronic health record-based preventive ratios (number of months services were up-to-date/total months the patient was eligible for services) were calculated for the 14 preventive services. Negative binomial regression models assessed the relationship between multimorbidity physical and/or mental health patterns and the preventive ratio for each service. RESULTS: There was a variation in receipt of preventive care between multimorbidity groups: individuals with mental health only multimorbidity were less likely to be up-to-date with cardiometabolic and cancer screenings than the no multimorbidity group or groups with physical health conditions, and the physical only multimorbidity group had low rates of depression screening. CONCLUSIONS: This study provided critical insights into receipt of preventive service among adults with multimorbidity using a more precise method for measuring up-to-date preventive care delivery. Findings would be useful to identify target populations for future intervention programs to improve preventive care.

The Affordable Care Act improved health insurance coverage and cardiovascular-related screening rates for cancer survivors seen in community health centers.

BACKGROUND: This study assessed the impact of Affordable Care Act (ACA) Medicaid expansion on health insurance rates and receipt of cardiovascular-related preventive screenings (body mass index, glycated hemoglobin [HbA1c], low-density lipoproteins, and blood pressure) for cancer survivors seen in community health centers (CHCs). METHODS: This study identified cancer survivors aged 19 to 64 years with at least 3 CHC visits in 13 states from the Accelerating Data Value Across a National Community Health Center Network (ADVANCE). Via inverse probability of treatment weighting multilevel multinomial modeling, insurance rates before and after the ACA were estimated by whether a patient lived in a state that expanded Medicaid, and changes between a pre-ACA time period and 2 post-ACA time periods were assessed. RESULTS: The weighted estimated sample size included 409 cancer survivors in nonexpansion states and 2650 in expansion states. In expansion states, the proportion of uninsured cancer survivors decreased significantly from 20.3% in 2012-2013 to 4.5%in 2016-2017, and the proportion of those with Medicaid coverage increased significantly from 38.8% to 55.6%. In nonexpansion states, there was a small decrease in uninsurance rates (from 33.6% in 2012-2013 to 22.5% in 2016-2017). Cardiovascular-related preventive screening rates increased over time in both expansion and nonexpansion states: HbA1c rates nearly doubled from the pre-ACA period (2012-2013) to the post-ACA period (2016-2017) in expansion states (from 7.2% to 12.8%) and nonexpansion states (from 9.3% to 16.8%). CONCLUSIONS: This study found a substantial decline in uninsured visits among cancer survivors in Medicaid expansion states. Yet, 1 in 5 cancer survivors living in a state that did not expand Medicaid remained uninsured. Several ACA provisions likely worked together to increase cardiovascular-related preventive screening rates for cancer survivors seen in CHCs.

Tobacco Cessation in Affordable Care Act Medicaid Expansion States Versus Non-expansion States.

INTRODUCTION: Community health centers (CHCs) care for vulnerable patients who use tobacco at higher than national rates. States that expanded Medicaid eligibility under the Affordable Care Act (ACA) provided insurance coverage to tobacco users not previously Medicaid-eligible, thereby potentially increasing their odds of receiving cessation assistance. We examined if tobacco users in Medicaid expansion states had increased quit rates, cessation medications ordered, and greater health care utilization compared to patients in non-expansion states. METHODS: Using electronic health record (EHR) data from 219 CHCs in 10 states that expanded Medicaid as of January 1, 2014, we identified patients aged 19-64 with tobacco use status documented in the EHR within 6 months prior to ACA Medicaid expansion and ≥1 visit with tobacco use status assessed within 24 months post-expansion (January 1, 2014 to December 31, 2015). We propensity score matched these patients to tobacco users from 108 CHCs in six non-expansion states (n = 27 670 matched pairs; 55 340 patients). Using a retrospective observational cohort study design, we compared odds of having a quit status, cessation medication ordered, and ≥6 visits within the post-expansion period among patients in expansion versus non-expansion states. RESULTS: Patients in expansion states had increased adjusted odds of quitting (adjusted odds ratio [aOR] = 1.35, 95% confidence interval [CI]: 1.28-1.43), having a medication ordered (aOR = 1.53, 95% CI: 1.44-1.62), and having ≥6 follow-up visits (aOR = 1.34, 95% CI: 1.28-1.41) compared to patients from non-expansion states. CONCLUSIONS: Increased access to insurance via the ACA Medicaid expansion likely led to increased quit rates within this vulnerable population. IMPLICATIONS: CHCs care for vulnerable patients at higher risk of tobacco use than the general population. Medicaid expansion via the ACA provided insurance coverage to a large number of tobacco users not previously Medicaid-eligible. We found that expanded insurance coverage was associated with increased cessation assistance and higher odds of tobacco cessation. Continued provision of insurance coverage could lead to increased quit rates among high-risk populations, resulting in improvements in population health outcomes and reduced total health care costs.

Cervical and colorectal cancer screening prevalence before and after Affordable Care Act Medicaid expansion.

Community health centers (CHCs), which serve socioeconomically disadvantaged patients, experienced an increase in insured visits after the 2014 Affordable Care Act (ACA) coverage options began. Yet, little is known about how cancer screening rates changed post-ACA. Therefore, this study assessed changes in the prevalence of cervical and colorectal cancer screening from pre- to post-ACA in expansion and non-expansion states among patients seen in CHCs. Electronic health record data on 624,601 non-pregnant patients aged 21-64 eligible for cervical or colorectal cancer screening between 1/1/2012 and 12/31/2015 from 203 CHCs were analyzed. We assessed changes in prevalence and screening likelihood among patients, by insurance type and race/ethnicity and compared Medicaid expansion and non-expansion states using difference-in-difference methodology. Female patients had 19% increased odds of receiving cervical cancer screening post- relative to pre-ACA in expansion states [adjusted odds ratio (aOR) = 1.19, 95% confidence interval (CI) = 1.09-1.31] and 23% increased odds in non-expansion states (aOR = 1.23, 95% CI = 1.05-1.46): the greatest increase was among uninsured patients in expansion states (aOR = 1.36, 95% CI = 1.16-1.59) and privately-insured patients in non-expansion states (aOR = 1.43, 95% CI = 1.11-1.84). Colorectal cancer screening prevalence increased from 11% to 18% pre- to post-ACA in expansion states and from 13% to 21% in non-expansion states. For most outcomes, the observed changes were not significantly different between expansion and non-expansion states. Despite increased prevalences of cervical and colorectal cancer screening in both expansion and non-expansion states across all race/ethnicity groups, rates remained suboptimal for this population of socioeconomically disadvantaged patients.

Prescription opioid use patterns, use disorder diagnoses and addiction treatment receipt after the 2014 Medicaid expansion in Oregon.

BACKGROUND/AIMS: Evidence suggests that Medicaid beneficiaries in the United States are prescribed opioids more frequently than are people who are privately insured, but little is known about opioid prescribing patterns among Medicaid enrollees who gained coverage via the Affordable Care Act Medicaid expansions. This study compared the prevalence of receipt of opioid prescriptions and opioid use disorder (OUD), along with time from OUD diagnosis to medication-assisted treatment (MAT) receipt between Oregon residents who had been continuously insured by Medicaid, were newly insured after Medicaid expansion in 2014 or returned to Medicaid coverage after expansion. DESIGN: Cross-sectional study using inverse-propensity weights to adjust for differences among insurance groups. SETTING: Oregon. PARTICIPANTS: A total of 225 295 Oregon Medicaid adult beneficiaries insured during 2014-15 and either: (1) newly enrolled, (2) returning in 2014 after a > 12-month gap or (3) continuously insured between 2013 and 2015. We excluded patients in hospice care or with cancer diagnoses. MEASUREMENTS: Any opioid-dispensed, chronic (> 90-days) and high-dose (> 90 daily morphine milligram equivalence) opioid use, documented OUD diagnosis and MAT receipt. FINDINGS: Compared with the continuously insured, newly and returning insured enrollees were less likely to be dispensed opioids [newly: 42.3%, 95% confidence interval (CI) = 42.0-42.7%; returning: 49.3%, 95% CI = 48.8-49.7%; continuously: 52.5%, 95% CI = 52.0-53.0%], use opioids chronically (newly: 12.8%, 95% CI = 12.4-13.1%; returning: 11.9%, 95% CI = 11.5-12.3%, continuously: 15.8%, 95% CI = 15.4-16.2%), have OUD diagnoses (newly: 3.6%, 95% CI = 3.4-3.7%; returning: 3.9%, 95% CI = 3.8-4.1%, continuously: 4.7%, 95% CI = 4.5-4.9%) and receive MAT after OUD diagnosis [hazard ratio newly: 0.57, 95% CI = 0.53-0.61; hazard ratio returning: 0.60, 95% CI = 0.56-0.65 (ref: continuously)]. CONCLUSIONS: Residents of Oregon, United States who enrolled or re-enrolled in Medicaid health insurance after expansion of coverage in 2014 as a result of the Affordable Care Act were less likely than those already covered to receive opioids, use them chronically or receive medication-assisted treatment for opioid use disorder.

Smoking-Cessation Assistance: Before and After Stage 1 Meaningful Use Implementation.

INTRODUCTION: Brief smoking-cessation interventions in primary care settings are effective, but delivery of these services remains low. The Centers for Medicare and Medicaid Services' Meaningful Use (MU) of Electronic Health Record (EHR) Incentive Program could increase rates of smoking assessment and cessation assistance among vulnerable populations. This study examined whether smoking status assessment, cessation assistance, and odds of being a current smoker changed after Stage 1 MU implementation. METHODS: EHR data were extracted from 26 community health centers with an EHR in place by June 15, 2009. AORs were computed for each binary outcome (smoking status assessment, counseling given, smoking-cessation medications ordered/discussed, current smoking status), comparing 2010 (pre-MU), 2012 (MU preparation), and 2014 (MU fully implemented) for pregnant and non-pregnant patients. RESULTS: Non-pregnant patients had decreased odds of current smoking over time; odds for all other outcomes increased except for medication orders from 2010 to 2012. Among pregnant patients, odds of assessment and counseling increased across all years. Odds of discussing or ordering of cessation medications increased from 2010 compared with the other 2 study years; however, medication orders alone did not change over time, and current smoking only decreased from 2010 to 2012. Compared with non-pregnant patients, a lower percentage of pregnant patients were provided counseling. CONCLUSIONS: Findings suggest that incentives for MU of EHRs increase the odds of smoking assessment and cessation assistance, which could lead to decreased smoking rates among vulnerable populations. Continued efforts for provision of cessation assistance among pregnant patients is warranted.

Measuring Preventive Care Delivery: Comparing Rates Across Three Data Sources.

INTRODUCTION: Preventive care delivery is an important quality outcome, and electronic data reports are being used increasingly to track these services. It is highly informative when electronic data sources are compared to information manually extracted from medical charts to assess validity and completeness. METHODS: This cross-sectional study used a random sample of Medicaid-insured patients seen at 43 community health centers in 2011 to calculate standard measures of correspondence between manual chart review and two automated sources (electronic health records [EHRs] and Medicaid claims), comparing documentation of orders for and receipt of ten preventive services (n=150 patients/service). Data were analyzed in 2015. RESULTS: Using manual chart review as the gold standard, automated EHR extraction showed near-perfect to perfect agreement (κ=0.96-1.0) for services received within the primary care setting (e.g., BMI, blood pressure). Receipt of breast and colorectal cancer screenings, services commonly referred out, showed moderate (κ=0.42) to substantial (κ=0.62) agreement, respectively. Automated EHR extraction showed near-perfect agreement (κ=0.83-0.97) for documentation of ordered services. Medicaid claims showed near-perfect agreement (κ=0.87) for hyperlipidemia and diabetes screening, and substantial agreement (κ=0.67-0.80) for receipt of breast, cervical, and colorectal cancer screenings, and influenza vaccination. Claims showed moderate agreement (κ=0.59) for chlamydia screening receipt. Medicaid claims did not capture ordered or unbilled services. CONCLUSIONS: Findings suggest that automated EHR and claims data provide valid sources for measuring receipt of most preventive services; however, ordered and unbilled services were primarily captured via EHR data and completed referrals were more often documented in claims data.

Effect of Gaining Insurance Coverage on Smoking Cessation in Community Health Centers: A Cohort Study.

BACKGROUND: Community health center (CHC) patients have high rates of smoking. Insurance coverage for smoking cessation assistance, such as that mandated by the Affordable Care Act, may aid in smoking cessation in this vulnerable population. OBJECTIVE: We aimed to determine if uninsured CHC patients who gain Medicaid coverage experience greater primary care utilization, receive more cessation medication orders, and achieve higher quit rates, compared to continuously uninsured smokers. DESIGN: Longitudinal observational cohort study using electronic health record data from a network of Oregon CHCs linked to Oregon Medicaid enrollment data. PATIENTS: Cohort of patients who smoke and who gained Medicaid coverage in 2008-2011 after ≥ 6 months of being uninsured and with ≥ 1 smoking assessment in the 24-month follow-up period from the baseline smoking status date. This group was propensity score matched to a cohort of continuously uninsured CHC patients who smoke (n = 4140 matched pairs; 8280 patients). INTERVENTION: Gaining Medicaid after being uninsured for ≥ 6 months. MAIN MEASURES: 'Quit' smoking status (baseline smoking status was 'current every day' or 'some day' and status change to 'former smoker' at a subsequent visit), smoking cessation medication order, and ≥ 6 documented visits (yes/no variables) at ≥ 1 smoking status assessment within the 24-month follow-up period. KEY RESULTS: The newly insured had 40 % increased odds of quitting smoking (aOR = 1.40, 95 % CI:1.24, 1.58), nearly triple the odds of having a medication ordered (aOR = 2.94, 95 % CI:2.61, 3.32), and over twice the odds of having ≥ 6 follow-up visits (aOR = 2.12, 95 % CI:1.94, 2.32) compared to their uninsured counterparts. CONCLUSIONS: Newly insured patients had increased odds of quit smoking status over 24 months of follow-up than those who remained uninsured. Providing insurance coverage to vulnerable populations may have a significant impact on smoking cessation.