Publications by Year: 2017

BACKGROUND: The field of dissemination and implementation (D&I) research in health has grown considerably in the past decade. Despite the potential for advancing the science, limited research has focused on mapping the field.

METHODS: We administered an online survey to individuals in the D&I field to assess participants' demographics and expertise, as well as engagement with journals and conferences, publications, and grants. A combined roster-nomination method was used to collect data on participants' advice networks and collaboration networks; participants' motivations for choosing collaborators was also assessed. Frequency and descriptive statistics were used to characterize the overall sample; network metrics were used to characterize both networks. Among a sub-sample of respondents who were researchers, regression analyses identified predictors of two metrics of academic performance (i.e., publications and funded grants).

RESULTS: A total of 421 individuals completed the survey, representing a 30.75% response rate of eligible individuals. Most participants were White (n = 343), female (n = 284, 67.4%), and identified as a researcher (n = 340, 81%). Both the advice and the collaboration networks displayed characteristics of a small world network. The most important motivations for selecting collaborators were aligned with advancing the science (i.e., prior collaborators, strong reputation, and good collaborators) rather than relying on human proclivities for homophily, proximity, and friendship. Among a sub-sample of 295 researchers, expertise (individual predictor), status (advice network), and connectedness (collaboration network) were significant predictors of both metrics of academic performance.

CONCLUSIONS: Network-based interventions can enhance collaboration and productivity; future research is needed to leverage these data to advance the field.

Venous thromboembolism occurs in up to one-third of patients with primary brain tumors. Spontaneous intracranial hemorrhage (ICH) is also a frequent occurrence in these patients, but there is limited data on the safety of therapeutic anticoagulation. To determine the rate of ICH in patients treated with enoxaparin, we performed a matched, retrospective cohort study with blinded radiology review for 133 patients with high-grade glioma. After diagnosis of glioma, the cohort that received enoxaparin was 3 times more likely to develop a major ICH than those not treated with anticoagulation (14.7% vs 2.5%; P = .036; hazard ratio [HR], 3.37; 95% confidence interval [CI], 1.02-11.14). When enoxaparin was analyzed as a time-varying covariate, anticoagulation was associated with a >13-fold increased risk of hemorrhage (HR, 13.26; 95% CI, 3.33-52.85; P < .0001). Overall survival was significantly shorter for patients who suffered a major ICH on enoxaparin compared with patients not receiving anticoagulation (3.3 vs 10.2 months; log-rank P = .012). We applied a validated ICH prediction risk score PANWARDS (platelets, albumin, no congestive heart failure, warfarin, age, race, diastolic blood pressure, stroke), and observed that all major ICHs on enoxaparin occurred in the setting of a PANWARDS score ≥25, corresponding with a sensitivity of 100% (95% CI, 63% to 100%) and a specificity of 40% (95% CI, 25% to 56%). We conclude that caution is warranted when considering therapeutic anticoagulation in patients with high-grade gliomas given the increased risk of ICH and poor prognosis after a major hemorrhage on anticoagulation. The PANWARDS score may assist clinicians in identifying the patients at greatest risk of suffering a major intracranial hemorrhage with anticoagulation.

OBJECTIVE: To determine whether there were gender differences in likelihood of receiving a first National Institutes of Health (NIH) R01 award among 5445 instructors and assistant professors at Harvard Medical School (HMS).

MATERIALS AND METHODS: Data on R01 award principal investigators were obtained from NIH ExPORTER and linked with faculty data. Using Cox proportional hazard regression, we examined the association of gender with receipt of first R01 award between 2008 and 2015 accounting for demographics, research productivity metrics, and professional characteristics.

RESULTS: Compared to males, females had fewer publications, lower h-index, smaller coauthor networks and were less likely to be assistant professors (p < 0.0001). Four hundred and thirteen of 5445 faculty (7.6%) received their first R01 award during the study period. There was no gender difference in receipt of R01 awards in age-adjusted (hazard ratio [HR]: 0.87, 95% confidence interval [CI]: 0.70-1.08) or multivariable-adjusted models (HR: 1.07, 95% CI: 0.86-1.34). Compared to white males, there was a nonsignificant 10%, 18%, and 30% lower rate of R01 receipt among white, Asian or Pacific Islander, and underrepresented minority females, respectively. These differences were eliminated in the multivariable-adjusted model. Network reach, age, HMS start year, h-index, academic rank, previous K award, terminal degree, and HMS training were all significant predictors of receiving an R01 award.

CONCLUSIONS: A relatively small proportion of HMS junior faculty obtained their first NIH R01 award during the study period. There was no significant gender difference in likelihood of award. However, we are unable to distinguish faculty that never applied from those who applied and were not successful.

OBJECTIVE: We sought to depict the topical, geospatial, and temporal diffusion of the 2015 North American Menopause Society position statement on the nonhormonal management of menopause-associated vasomotor symptoms released on September 21, 2015, and its associated press release from September 23, 2015.

METHODS: Three data sources were used: online news articles, National Public Radio, and Twitter. For topical diffusion, we compared keywords and their frequencies among the position statement, press release, and online news articles. We also created a network figure depicting relationships across key content categories or nodes. For geospatial diffusion within the United States, we compared locations of the 109 National Public Radio (NPR) stations covering the statement to 775 NPR stations not covering the statement. For temporal diffusion, we normalized and segmented Twitter data into periods before and after the press release (September 12, 2015 to September 22, 2015 vs September 23, 2015 to October 3, 2015) and conducted a burst analysis to identify changes in tweets from before to after.

RESULTS: Topical information diffused across sources was similar with the exception of the more scientific terms "vasomotor symptoms" or "vms" versus the more colloquial term "hot flashes." Online news articles indicated media coverage of the statement was mainly concentrated in the United States. NPR station data showed similar proportions of stations airing the story across the four census regions (Northeast, Midwest, south, west; P = 0.649). Release of the statement coincided with bursts in the menopause conversation on Twitter.

CONCLUSIONS: The findings of this study may be useful for directing the development and dissemination of future North American Menopause Society position statements and/or press releases.

OBJECTIVE: One promise of nationwide adoption of electronic health records (EHRs) is the availability of data for large-scale clinical research studies. However, because the same patient could be treated at multiple health care institutions, data from only a single site might not contain the complete medical history for that patient, meaning that critical events could be missing. In this study, we evaluate how simple heuristic checks for data "completeness" affect the number of patients in the resulting cohort and introduce potential biases.

MATERIALS AND METHODS: We began with a set of 16 filters that check for the presence of demographics, laboratory tests, and other types of data, and then systematically applied all 216 possible combinations of these filters to the EHR data for 12 million patients at 7 health care systems and a separate payor claims database of 7 million members.

RESULTS: EHR data showed considerable variability in data completeness across sites and high correlation between data types. For example, the fraction of patients with diagnoses increased from 35.0% in all patients to 90.9% in those with at least 1 medication. An unrelated claims dataset independently showed that most filters select members who are older and more likely female and can eliminate large portions of the population whose data are actually complete.

DISCUSSION AND CONCLUSION: As investigators design studies, they need to balance their confidence in the completeness of the data with the effects of placing requirements on the data on the resulting patient cohort.