Search

BackgroundAlthough lung cancer incidence rates according to smoking status, sex, and detailed race/ethnicity have not been available, it is estimated that more than half of Asian American, Native Hawaiian, and Pacific Islander (AANHPI) females with lung cancer have never smoked.MethodsWe calculated age-adjusted incidence rates for lung cancer according to smoking status and detailed race/ethnicity among females, focusing on AANHPI ethnic groups, and assessed relative incidence across racial/ethnic groups. We used a large-scale dataset that integrates data from electronic health records from 2 large health-care systems-Sutter Health in Northern California and Kaiser Permanente Hawai'i-linked to state cancer registries for incident lung cancer diagnoses between 2000 and 2013. The study population included 1 222 694 females (n = 244 147 AANHPI), 3297 of which were diagnosed with lung cancer (n = 535 AANHPI).ResultsIncidence of lung cancer among never-smoking AANHPI as an aggregate group was 17.1 per 100 000 (95% confidence interval [CI] = 14.9 to 19.4) but varied widely across ethnic groups. Never-smoking Chinese American females had the highest rate (22.8 per 100 000, 95% CI = 17.3 to 29.1). Except for Japanese American females, incidence among every never-smoking AANHPI female ethnic group was higher than that of never-smoking non-Hispanic White females, from 66% greater among Native Hawaiian females (incidence rate ratio = 1.66, 95% CI = 1.03 to 2.56) to more than 100% greater among Chinese American females (incidence rate ratio = 2.26, 95% CI = 1.67 to 3.02).ConclusionsOur study revealed high rates of lung cancer among most never-smoking AANHPI female ethnic groups. Our approach illustrates the use of innovative data integration to dispel the myth that AANHPI females are at overall reduced risk of lung cancer and demonstrates the need to disaggregate this highly diverse population.

BackgroundA relatively high proportion of Asian American, Native Hawaiian, and Pacific Islander (AANHPI) females with lung cancer have never smoked. We used an integrative data approach to assemble a large-scale cohort to study lung cancer risk among AANHPIs by smoking status with attention to representation of specific AANHPI ethnic groups.MethodsWe leveraged electronic health records (EHRs) from two healthcare systems-Sutter Health in northern California and Kaiser Permanente Hawai'i-that have high representation of AANHPI populations. We linked EHR data on lung cancer risk factors (i.e., smoking, lung diseases, infections, reproductive factors, and body size) to data on incident lung cancer diagnoses from statewide population-based cancer registries of California and Hawai'i for the period between 2000 and 2013. Geocoded address data were linked to data on neighborhood contextual factors and regional air pollutants.ResultsThe dataset comprises over 2.2 million adult females and males of any race/ethnicity. Over 250,000 are AANHPI females (19.6% of the female study population). Smoking status is available for over 95% of individuals. The dataset includes 7,274 lung cancer cases, including 613 cases among AANHPI females. Prevalence of never-smoking status varied greatly among AANHPI females with incident lung cancer, from 85.7% among Asian Indian to 14.4% among Native Hawaiian females.ConclusionWe have developed a large, multilevel dataset particularly well-suited to conduct prospective studies of lung cancer risk among AANHPI females who never smoked.ImpactThe integrative data approach is an effective way to conduct cancer research assessing multilevel factors on cancer outcomes among small populations.

BackgroundThere is tremendous potential to leverage the value gained from integrating electronic health records (EHR) and population-based cancer registry data for research. Registries provide diagnosis details, tumor characteristics, and treatment summaries, while EHRs contain rich clinical detail. A carefully conducted cancer registry linkage may also be used to improve the internal and external validity of inferences made from EHR-based studies.MethodsWe linked the EHRs of a large, multispecialty, mixed-payer health care system with the statewide cancer registry and assessed the validity of our linked population. For internal validity, we identify patients that might be "missed" in a linkage, threatening the internal validity of an EHR study population. For generalizability, we compared linked cases with all other cancer patients in the 22-county EHR catchment region.ResultsFrom an EHR population of 4.5 million, we identified 306,554 patients with cancer, 26% of the catchment region patients with cancer; 22.7% of linked patients were diagnosed with cancer after they migrated away from our health care system highlighting an advantage of system-wide linkage. We observed demographic differences between EHR patients and non-EHR patients in the surrounding region and demonstrated use of selection probabilities with model-based standardization to improve generalizability.ConclusionsOur experiences set the foundation to encourage and inform researchers interested in working with EHRs for cancer research as well as provide context for leveraging linkages to assess and improve validity and generalizability.ImpactResearchers conducting linkages may benefit from considering one or more of these approaches to establish and evaluate the validity of their EHR-based populations.See all articles in this CEBP Focus section, "Modernizing Population Science."

Introduction: Recent guideline changes for lung cancer screening with low-dose computed tomography recommend smoking cessation interventions be done in parallel with screening. The purpose of this study is to determine the post-guideline rates of smoking cessation interventions among patients eligible and ineligible for lung cancer screening.Methods: Using electronic health records collected from a large ambulatory care system in northern California between 2010 and 2017, authors identified new patients who were current smokers aged 55–80 years visiting a primary care provider, and grouped patients into lung cancer screening–eligible heavy smokers, screening-ineligible moderate smokers, and screening-ineligible light smokers. Screening-eligible smokers versus screening-ineligible smokers were compared in receipt of smoking cessation interventions before (2010–2013) and after (2014–2017) the guideline change, overall and by intervention type (formal counseling, informal counseling, pharmacotherapy) using hierarchical generalized linear models. Analyses were conducted in 2018–2019.Results: After the guideline change, the likelihood of receiving any smoking cessation intervention (OR=1.44, 95% CI=1.28, 1.61, p

With the growth of precision medicine research on health data and biospecimens, research institutions will need to build and maintain long-term, trusting relationships with patient-participants. While trust is important for all research relationships, the longitudinal nature of precision medicine research raises particular challenges for facilitating trust when the specifics of future studies are unknown. Based on focus groups with racially and ethnically diverse patients, we describe several factors that influence patient trust and potential institutional approaches to building trustworthiness. Drawing on these findings, we suggest several considerations for research institutions seeking to cultivate long-term, trusting relationships with patients: (1) Address the role of history and experience on trust, (2) engage concerns about potential group harm, (3) address cultural values and communication barriers, and (4) integrate patient values and expectations into oversight and governance structures.

PurposeTo examine the characteristics of voluntary online commitment contracts that may be associated with greater weight loss.DesignRetrospective analysis of weight loss commitment contracts derived from a company that provides web-based support for personal commitment contracts. Using regression, we analyzed whether percentage weight loss differed between participants who incentivized their contract using monetary deposits and those who did not.SettingOnline.ParticipantsUsers (N = 3857) who voluntarily signed up online in 2013 for a weight loss contract.InterventionParticipants specified their own weight loss goal, time period, and self-reported weekly weight. Deposits were available in the following 3 categories: charity, anticharity (a nonprofit one does not like), or donations made to a friend.MeasuresPercentage weight loss per week.AnalysisMultivariable linear regressions.ResultsControlling for several participant and contract characteristics, contracts with anticharity, charity, and friend deposits had greater reported weight loss than nonincentivized contracts. Weight change per week relative to those without deposits was -0.33%, -0.28%, and -0.25% for anti-charity, charity, and friend, respectively ( P < 0.001). Contracts without a weight verification method claimed more weight loss than those with verification.ConclusionVoluntary use of commitment contracts may be an effective tool to assist weight loss. Those who choose to use monetary incentives report more weight loss. It is not clear whether this is due to the incentives or higher motivation.

Time spent by physicians is a key resource in health care delivery. This study used data captured by the access time stamp functionality of an electronic health record (EHR) to examine physician work effort. This is a potentially powerful, yet unobtrusive, way to study physicians' use of time. We used data on physicians' time allocation patterns captured by over thirty-one million EHR transactions in the period 2011-14 recorded by 471 primary care physicians, who collectively worked on 765,129 patients' EHRs. Our results suggest that the physicians logged an average of 3.08 hours on office visits and 3.17 hours on desktop medicine each day. Desktop medicine consists of activities such as communicating with patients through a secure patient portal, responding to patients' online requests for prescription refills or medical advice, ordering tests, sending staff messages, and reviewing test results. Over time, log records from physicians showed a decline in the time allocated to face-to-face visits, accompanied by an increase in time allocated to desktop medicine. Staffing and scheduling in the physician's office, as well as provider payment models for primary care practice, should account for these desktop medicine efforts.

ObjectiveTo develop a technology-based method for evaluating the nutritional quality of chain-restaurant menus to increase the efficiency and lower the cost of large-scale data analysis of food items.DesignUsing a Modified Nutrient Profiling Index (MNPI), we assessed chain-restaurant items from the MenuStat database with a process involving three steps: (i) testing 'extreme' scores; (ii) crowdsourcing to analyse fruit, nut and vegetable (FNV) amounts; and (iii) analysis of the ambiguous items by a registered dietitian.ResultsIn applying the approach to assess 22 422 foods, only 3566 could not be scored automatically based on MenuStat data and required further evaluation to determine healthiness. Items for which there was low agreement between trusted crowd workers, or where the FNV amount was estimated to be >40 %, were sent to a registered dietitian. Crowdsourcing was able to evaluate 3199, leaving only 367 to be reviewed by the registered dietitian. Overall, 7 % of items were categorized as healthy. The healthiest category was soups (26 % healthy), while desserts were the least healthy (2 % healthy).ConclusionsAn algorithm incorporating crowdsourcing and a dietitian can quickly and efficiently analyse restaurant menus, allowing public health researchers to analyse the healthiness of menu items.

The 23rd annual conference of the Health Care Systems Research Network (HCSRN, formerly the HMO Research Network) was held in San Diego, California, March 21-23, 2017, attracting 387 attendees. As a consortium of 20 research organizations embedded in or affiliated with large health care delivery organizations, the HCSRN has held annual research conferences since 1994. The overall aim of the conferences is to bring researchers, project staff, research funders and other stakeholders together to share latest scientific findings and foster new research ideas and collaborations. The 2017 conference was hosted by the Palo Alto Medical Foundation Research Institute. Each host site takes responsibility for the content and structure of the conference, and the 2017 team introduced several new features. In particular, past conferences used concurrent sessions to present research results in different topical areas, such as chronic disease, cancer, health informatics, mental health or precision medicine. This year, concurrent sessions shifted to panel discussions about how research results were achieved, including the use of methods, partnerships and analytic approaches. The 35 panels were organized into tracks such as engagement, data and informatics, partnerships and research implementation. Scientific results from HCSRN projects were presented via 120 posters in two poster sessions. Plenary sessions included a town hall-style panel with different funding agency representatives, an opening presentation on the range of opportunities and benefits to studying health systems, and a concluding presentation on how researchers can apply design thinking in their work.

PurposeThe 21-gene recurrence score (RS) identifies patients with breast cancer who derive little benefit from chemotherapy; it may reduce unwarranted variability in the use of chemotherapy. We tested whether the use of RS seems to guide chemotherapy receipt across different cancer care settings.MethodsWe developed a retrospective cohort of patients with breast cancer by using electronic medical record data from Stanford University (hereafter University) and Palo Alto Medical Foundation (hereafter Community) linked with demographic and staging data from the California Cancer Registry and RS results from the testing laboratory (Genomic Health Inc., Redwood City, CA). Multivariable analysis was performed to identify predictors of RS and chemotherapy use.ResultsIn all, 10,125 patients with breast cancer were diagnosed in the University or Community systems from 2005 to 2011; 2,418 (23.9%) met RS guidelines criteria, of whom 15.6% received RS. RS was less often used for patients with involved lymph nodes, higher tumor grade, and age < 40 or ≥ 65 years. Among RS recipients, chemotherapy receipt was associated with a higher score (intermediate v low: odds ratio, 3.66; 95% CI, 1.94 to 6.91). A total of 293 patients (10.6%) received care in both health care systems (hereafter dual use); although receipt of RS was associated with dual use (v University: odds ratio, 1.73; 95% CI, 1.18 to 2.55), there was no difference in use of chemotherapy after RS by health care setting.ConclusionAlthough there was greater use of RS for patients who sought care in more than one health care setting, use of chemotherapy followed RS guidance in University and Community health care systems. These results suggest that precision medicine may help optimize cancer treatment across health care settings.

Economics influences how medical care is delivered, organized, and progresses. Fee-for-service payment encourages delivery of services. Fee-for-individual-service, however, offers no incentives for clinicians to efficiently organize the care their patients need. Global capitation provides such incentives; it works well in highly integrated practices but not for independent practitioners. The failures of utilization management in the 1990s demonstrated the need for a third alternative to better align incentives, such as bundling payment for an episode of care. Building on Medicare's approach to hospital payment, one can define expanded diagnosis-related groups that include all hospital, physician, and other costs during the stay and appropriate preadmission and postdischarge periods. Physicians and hospitals voluntarily forming a new entity (a care delivery team) would receive such bundled payments along with complete flexibility in allocating the funds. Modifications to gainsharing and antikickback rules, as well as reforms to malpractice liability laws, will facilitate the functioning of the care delivery teams. The implicit financial incentives encourage efficient care for the patient; the episode focus will facilitate measuring patient outcomes. Payment can be based on the resources used by those care delivery teams achieving superior outcomes, thereby fostering innovation improving outcomes and reducing waste.

We compare rates and days of maternity and nonmaternity hospital admission for the years 1981 through 1984 for three groups of employees and dependents from a large private employer: those continuously enrolled in a fee-for-service (FFS) plan (N = 147,700), those continuously enrolled in a health maintenance organization (HMO) (N = 30,957), and those switching from the FFS plan to the HMO (N = 2,144). The rate of maternity admissions for plan switchers increased by 106% (P < 0.001) in the post-switch year compared with the pre-switch year, while maternity rates for continuing FFS-plan enrollees declined by 12% (P < 0.001) and rates for continuing HMO enrollees remained unchanged. Nonmaternity admission rates for switchers decreased by 19% (P = 0.079), consistent with the expectation that HMOs reduce these rates substantially, while rates for FFS-plan stayers increased 4% (P < 0.001) and those for HMO stayers remained unchanged. We conclude that employees often switch health plans when anticipating increased needs for maternity care and therefore that pre-switch rates of utilization are unreliable measures of the true magnitude of risk selection between HMOs and FFS plans.