Brandi Robinson

Effect of self-referral on bone mineral density testing and osteoporosis treatment

Background:Despite national guidelines recommending bone mineral density screening with dual-energy x-ray absorptiometry (DXA) in women aged 65 years and older, many women do not receive initial screening. Objective:To determine the effectiveness of health system and patient-level interventions designed to increase appropriate DXA testing and osteoporosis treatment through (1) an invitation to self-refer for DXA (self-referral); (2) self-referral plus patient educational materials; and (3) usual care (UC, physician referral). Research Design:Parallel, group-randomized, controlled trials performed at Kaiser Permanente Northwest (KPNW) and Kaiser Permanente Georgia (KPG). Subjects:Women aged 65 years and older without a DXA in past 5 years. Measures:DXA completion rates 90 days after intervention mailing and osteoporosis medication receipt 180 days after initial intervention mailing. Results:From >12,000 eligible women, those randomized to self-referral were significantly more likely to receive a DXA than UC (13.0%–24.1% self-referral vs. 4.9%–5.9% UC, P<0.05). DXA rates did not significantly increase with patient educational materials. Osteoporosis was detected in a greater proportion of self-referral women compared with UC (P<0.001). The number needed to receive an invitation to result in a DXA in KPNW and KPG regions was approximately 5 and 12, respectively. New osteoporosis prescription rates were low (0.8%–3.4%) but significantly greater among self-referral versus UC in KPNW. Conclusions:DXA rates significantly improved with a mailed invitation to schedule a scan without physician referral. Providing women the opportunity to self-refer may be an effective, low-cost strategy to increase access for recommended osteoporosis screening.

Cohort profile: Study of Transition, Outcomes and Gender (STRONG) to assess health status of transgender people

Purpose The Study of Transition, Outcomes and Gender (STRONG) was initiated to assess the health status of transgender people in general and following gender-affirming treatments at Kaiser Permanente health plans in Georgia, Northern California and Southern California. The objectives of this communication are to describe methods of cohort ascertainment and data collection and to characterise the study population. Participants A stepwise methodology involving computerised searches of electronic medical records and free-text validation of eligibility and gender identity was used to identify a cohort of 6456 members with first evidence of transgender status (index date) between 2006 and 2014. The cohort included 3475 (54%) transfeminine (TF), 2892 (45%) transmasculine (TM) and 89 (1%) members whose natal sex and gender identity remained undetermined from the records. The cohort was matched to 127 608 enrollees with no transgender evidence (63 825 women and 63 783 men) on year of birth, race/ethnicity, study site and membership year of the index date. Cohort follow-up extends through the end of 2016. Findings to date About 58% of TF and 52% of TM cohort members received hormonal therapy at Kaiser Permanente. Chest surgery was more common among TM participants (12% vs 0.3%). The proportions of transgender participants who underwent genital reconstruction surgeries were similar (4%–5%) in the two transgender groups. Results indicate that there are sufficient numbers of events in the TF and TM cohorts to further examine mental health status, cardiovascular events, diabetes, HIV and most common cancers. Future plans STRONG is well positioned to fill existing knowledge gaps through comparisons of transgender and reference populations and through analyses of health status before and after gender affirmation treatment. Analyses will include incidence of cardiovascular disease, mental health, HIV and diabetes, as well as changes in laboratory-based endpoints (eg, polycythemia and bone density), overall and in relation to gender affirmation therapy.

Mental Health of Transgender and Gender Nonconforming Youth Compared With Their Peers

The prevalence of mental health conditions among transfeminine and transmasculine youth 3 to 17 years old at initial presentation is estimated and compared with matched cisgender counterparts. BACKGROUND: Understanding the magnitude of mental health problems, particularly life-threatening ones, experienced by transgender and/or gender nonconforming (TGNC) youth can lead to improved management of these conditions. METHODS: Electronic medical records were used to identify a cohort of 588 transfeminine and 745 transmasculine children (3–9 years old) and adolescents (10–17 years old) enrolled in integrated health care systems in California and Georgia. Ten male and 10 female referent cisgender enrollees were matched to each TGNC individual on year of birth, race and/or ethnicity, study site, and membership year of the index date (first evidence of gender nonconforming status). Prevalence ratios were calculated by dividing the proportion of TGNC individuals with a specific mental health diagnosis or diagnostic category by the corresponding proportion in each reference group by transfeminine and/or transmasculine status, age group, and time period before the index date. RESULTS: Common diagnoses for children and adolescents were attention deficit disorders (transfeminine 15%; transmasculine 16%) and depressive disorders (transfeminine 49%; transmasculine 62%), respectively. For all diagnostic categories, prevalence was severalfold higher among TGNC youth than in matched reference groups. Prevalence ratios (95% confidence intervals [CIs]) for history of self-inflicted injury in adolescents 6 months before the index date ranged from 18 (95% CI 4.4–82) to 144 (95% CI 36–1248). The corresponding range for suicidal ideation was 25 (95% CI 14–45) to 54 (95% CI 18–218). CONCLUSIONS: TGNC youth may present with mental health conditions requiring immediate evaluation and implementation of clinical, social, and educational gender identity support measures.

The Impact of Using Mid-level Providers in Face-to-Face Primary Care on Health Care Utilization.

Background: There has been concern that greater use of nurse practitioners (NP) and physician assistants (PA) in face-to-face primary care may increase utilization and spending. Objective: To evaluate a natural experiment within Kaiser Permanente in Georgia in the use of NP/PA in primary care. Study Design: From 2006 through early 2008 (the preperiod), each NP or PA was paired with a physician to manage a patient panel. In early 2008, NPs and PAs were removed from all face-to-face primary care. Using the 2006–2010 data, we applied a difference-in-differences analytic approach at the clinic level due to patient triage between a NP/PA and a physician. Clinics were classified into 3 different groups based on the percentage of visits by NP/PA during the preperiod: high (over 20% in-person primary care visits attended by NP/PAs), medium (5%–20%), and low (<5%) NP/PA model clinics. Measures: Referrals to specialist physicians; emergency department visits and inpatient admissions; and advanced diagnostic imaging services. Results: Compared with the low NP/PA model, the high NP/PA model and the medium NP/PA model were associated with 4.9% and 5.1% fewer specialist referrals, respectively (P<0.05 for both estimates); the high NP/PA model and the medium NP/PA model also showed fewer hospitalizations and emergency department visits and fewer advanced diagnostic imaging services, but none of these was statistically significant. Conclusions: We find no evidence to support concerns that under a physicians supervision, NPs and PAs increase utilization and spending.

Cross-sex Hormones and Acute Cardiovascular Events in Transgender Persons: A Cohort Study

Transgender persons are a diverse group whose gender identity differs from a male or female sex designation, which usually is assigned at birth (1). Although some transgender persons may not self-identify on the basis of binary definitions (2), a person whose gender identity differs from a male sex designation at birth often is referred to as male-to-female, transfeminine, or trans woman, and a person whose gender identity differs from a female sex designation at birth often is referred to as female-to-male, transmasculine, or trans man (3, 4). Some transgender persons undergo medical treatment to align their physical appearance with their gender identity (5, 6). A specific area of concern in transgender health is the risk for acute cardiovascular events (ACVEs), including venous thromboembolism (VTE), ischemic stroke, and myocardial infarction, which might plausibly be related to cross-sex hormone therapy (7). As reviewed elsewhere (811), the direct evidence addressing this issue is sparse and inconsistent because of the predominance of small studies with very few reported events. A direct evaluation of the evidence regarding the incidence of ACVEs requires a longitudinal study that includes large numbers of transfeminine and transmasculine participants, with sufficient follow-up, appropriate control groups, and documented cross-sex hormone use among participants (12). Integrated health care systems with electronic medical records (EMRs) allow efficient identification and follow-up of hard-to-reach population subgroups, such as transgender persons. Our objective was to compare ACVE incidence rates in a cohort of transgender persons enrolled in 3 such health care systems with rates observed in age-, race-, site-, and membership-matched cisgender men and women (reference cohorts). Methods Cohort Ascertainment This study took place at Kaiser Permanente sites in Georgia, northern California, and southern California and was coordinated by Emory University. All activities were reviewed and approved by the institutional review boards of the 4 institutions. The methods of cohort ascertainment were described in detail previously (13, 14). As summarized in the Supplement and Supplement Figure 1, cohort selection involved a 3-step algorithm: an initial EMR search to identify cohort candidates (step 1), validation of transgender status (step 2), and determination of transmasculine or transfeminine status (step 3). Supplement. Technical Appendix Ten male and 10 female cisgender Kaiser Permanente enrollees were matched to each member of the final validated transgender cohort by race/ethnicity (non-Hispanic white, non-Hispanic black, Asian/Pacific Islander, Hispanic, and other), year of birth (within a 5-year interval), study site, and calendar year of membership based on the index date. Index date was defined as the first recorded evidence of transgender status. We used both male and female cisgender reference groups because hormone serum concentrations among transgender persons may range from normal physiologic male to normal physiologic female levels, depending on receipt and dosage of hormone therapy as well as individual characteristics (15). A 10:1 ratio was used to allow stratified analyses (for example, by hormone therapy type) while ensuring a sufficient number of cisgender referents for each cohort member. Each transgender cohort member was linked to matched referents via a unique cluster identification number (ID) to allow subanalyses. Data Collection and Analysis Only persons aged 18 years or older at their index date who were determined to be transmasculine or transfeminine, along with their matched referents, were included. All study participants were characterized with respect to their Kaiser Permanente enrollment history and their cigarette smoking status, body mass index (BMI; kilograms per square meter), blood pressure, and total blood cholesterol level at baseline. Variable categorization is presented in the footnotes to the tables and in the Supplement. Transgender hormone treatment was determined through EMR linkages to prescription data by using national drug codes. Linkages with the International Classification of Diseases, Ninth Revision and 10th Revision (ICD-9 and ICD-10), and Current Procedural Terminology codes were used to ascertain surgeries and other interventions. Feminizing drugs (such as estradiol and spironolactone) in a participant recorded as male at birth and masculinizing drugs (such as testosterone) in a participant documented as female at birth were considered evidence of hormone therapy. In both the transgender and the reference cohorts, ACVEs were ascertained on the basis of ICD-9 or ICD-10 codes. The lists of codes and numbers of cases ascertained by each code are specified in Supplement Table 3. Only ACVEs with a diagnosis date during follow-up were used in the analyses. History of ACVEs was defined as having an event with a diagnosis date before the start of follow-up. Statistical Analysis All transgender cohort members were characterized as transfeminine or transmasculine and grouped further according to their history of cross-sex hormone use. Follow-up in the overall analysis extended from the index date until the first occurrence of the event of interest, disenrollment from the plan for more than 90 days, death, or the end of the study period (30 November 2016). For participants who began hormone therapy at Kaiser Permanente after the index date (hormone initiation cohort), additional analyses were conducted. In these analyses, follow-up started on the date of the first filled prescription for estrogen or testosterone for transfeminine or transmasculine participants, respectively. Matched referents were assigned the same start date for follow-up. Missing covariate values for BMI, blood pressure, and total cholesterol level were assigned by using multiple imputation methods (n= 5 imputations). Incidence rates were calculated as the number of cases per 1000 person-years, and the corresponding 95% CIs were calculated by using the Poisson distribution. Both unadjusted KaplanMeier curves and weighted cumulative incidence curves adjusted for covariates at the population means were constructed to compare the incidence of each ACVE type in the transmasculine and transfeminine participants with those in the corresponding matched reference cohorts. Risk differences at 2, 4, 6, and 8 years were calculated directly from the adjusted cumulative incidence curves. The 95% CI for each risk difference estimate was calculated via a bootstrapping procedure using 1000 random samples with replacement. In the primary analysis, we used multivariable Cox proportional hazards models to compare ACVE rates in the overall transfeminine and transmasculine cohorts and among members of the hormone initiation cohorts with those in the matched cisgender reference groups, after controlling for history of any ACVE, smoking status, BMI, blood pressure, and blood cholesterol level ascertained near the index date. Each model was stratified by cluster ID to account for matching. Proportional hazards assumptions were tested by examining log-minus-log plots for each variable in the model and by performing a goodness-of-fit test using Schoenfeld residuals (16). The results of the Cox models were expressed as adjusted hazard ratios with corresponding 95% CIs. Because the weighted cumulative incidence curves could not account for matching, hazard ratios from models that were not stratified by cluster ID were also calculated and are included in Supplement Tables 4 and 5. When evidence (such as log-minus-log survival plots) suggested that the proportional hazards assumption was violated, stratified Cox models were used to control for covariates, and extended Cox models with time-dependent hazard ratio estimates were used for the main independent variables of interest (16). Although the cohort size precluded detailed analyses by specific hormone therapy regimens, some examination of treatment subcategories was possible. These secondary exploratory analyses focused on transfeminine cohort subgroups defined on the basis of administration route (oral or other) and estrogen type (estradiol or other). In addition, the highest daily hormone dosages were summarized for participants who had an event of interest and in those who received hormone therapy but remained ACVE-free. We examined the effect of different case and exposure definitions, risk factors, and analytic approaches by conducting a series of sensitivity analyses (Supplement). To investigate the effects of unaccounted confounding, we calculated a range of E-values for the main results and the lower limits of their 95% CIs observed in Cox regression models (17). The data analyses were performed with SAS, version 9.4 (SAS Institute). E-values were obtained by using an online calculator for hazard ratios with an outcome prevalence of less than 15%. Role of the Funding Source This study was funded by the Patient-Centered Outcomes Research Institute (PCORI) and the Eunice Kennedy Shriver National Institute of Child Health and Human Development. The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. Results A total of 6456 transgender cohort members were identified in the EMR. After persons younger than 18 years at their index date (n= 1347), those with unknown sex designation at birth (n= 75), and those with no follow-up data (n= 74) were excluded, the study group included 4960 transgender participants and matched reference cohorts of 48686 cisgender men and 48775 cisgender women. The transgender cohort comprised 2842 (57%) transfeminine and 2118 (43%) transmasculine persons (Table 1). More than 50% of participants in both groups were non-Hispanic whites; Hispanics represented 18% of transfeminine and 14% of transmasculine participants,

Agreement between medical records and self-reports: Implications for transgender health research

A key priority of transgender health research is the evaluation of long-term effects of gender affirmation treatment. Thus, accurate assessment of treatment receipt is critical. The data for this analysis came from an electronic medical records (EMR) based cohort of transgender individuals. A subset of cohort members were also asked to complete a self-administered survey. Information from the EMR was compared with survey responses to assess the extent of agreement regarding transmasculine (TM)/transfeminine (TF) status, hormone therapy receipt, and type of surgery performed. Logistic regression models were used to assess whether participant characteristics were associated with disagreement between data sources. Agreement between EMR and survey-derived information was high regarding TM/TF status (99%) and hormone therapy receipt (97%). Lower agreement was observed for chest reconstruction surgery (72%) and genital reconstruction surgery (84%). Using survey responses as the “gold standard”, both chest and genital reconstruction surgeries had high specificity (95 and 93%, respectively), but the corresponding sensitivities were low (49 and 68%, respectively). A lower proportion of TM had concordant results for chest reconstruction surgery (64% versus 79% for TF) while genital reconstruction surgery concordance was lower among TF (79% versus 89% for TM). For both surgery types, agreement was highest among the youngest participants. Our findings offer assurance that EMR-based data appropriately classify cohort participants with respect to their TM/TF status or hormone therapy receipt. However, current EMR data may not capture the complete history of gender affirmation surgeries. This information is useful in future studies of outcomes related to gender affirming therapy.

Evaluation of a worksite wellness program designed to reduce cardiovascular risks.

We evaluated a multifactorial worksite wellness program designed to improve lifestyle and reduce cardiovascular risks at a small professional services company. Program participation (N = 60 employees) consisted of an enrollment session, a 6-month period of wellness program activities, and a disenrollment session. Lifestyle and biometric measures were obtained at enrollment and disenrollment. Over 6-months, percentage of dietary fat intake decreased (P < .01); daily fruit and vegetable servings and fiber intake increased (P = .02); systolic and diastolic blood pressure decreased (P = .04 and 0.01, respectively), and high-density lipoprotein increased (P < .01). This worksite wellness program achieved meaningful improvements in dietary intake and reduction in cardiovascular risks.

CA2-03: “What Would You Say to this Patient?” Cancer Care Providers’ Attitudes and Experiences

Background/Aims Effective patient-provider communication is critical in cancer care but often does not occur. Understanding providers’ perspectives on challenges in cancer care communication could support interventions. Methods We surveyed providers in primary care, oncology, and oncology nursing at three CRN sites (Group Health Cooperative, WA; Kaiser Permanente, GA; Fallon Clinic, MA). Questionnaires assessed providers’ attitudes and experiences about communicating with cancer patients, situations providers find challenging, and how providers would communicate in two scenarios (error involving multiple providers leading to delayed diagnosis; miscommunication regarding patient symptoms). Results Questionnaires were received from 406 of the 682 eligible providers (59%). Nearly all (98% (393 of 399)) reported their organizations value good patient-provider communication, and 95% (374 of 393) agreed that they communicate effectively with cancer patients. However, only 62% (239 of 385) agreed that they knew when their cancer patients had unanswered concerns or questions, and 67% (262 of 391) agreed that they were aware of most of the serious communication breakdowns that occurred in their patients’ care. Almost all, 99% (394 of 400) 99% agreed that their organization should encourage patients to alert the system when there has been a serious care breakdown, and 88% (340 of 386) agreed these reports would provide actionable information. Providers found some communication situations especially difficult. A majority (61% (242 of 397)) found it extremely/very difficult to respond to patients’ unrealistic beliefs about prognosis, 55% (217 of 395) found it extremely/very difficult to respond to patients’ concerns about delayed diagnosis, but only 5% (21 of 397) found it extremely/very difficult to respond to patients who are unhappy about care from another clinician. In response to a hypothetical patient who experienced a delayed breast cancer diagnosis, 55% (221 of 399) would provide very limited information to the patient, not explicitly mentioning the error causing the delay. Discussion Cancer care providers value patient-provider communication but find discussions of prognosis, as well as disclosure regarding care breakdowns and delayed diagnosis, especially challenging. Providers support mechanisms to solicit cancer patients’ concerns about their care. Health systems should explore how to create care delivery environments that improve patient-provider communication.

C-A1-02: Evaluating Kaiser Permanente Georgia’s Worksite Wellness Programs in the Atlanta Area

Background/Aims: There are few prospective evaluations of the effectiveness of worksite wellness programs in achieving improved lifestyle and health. Our study has two objectives: to assess the cross-sectional associations of biometric status, lifestyle, and health obtained at a wellness program’s enrollment session, and to assess changes in biometric status, lifestyle, and health between the enrollment and 6-month disenrollment sessions. Methods: For this prospective cohort study, participants were recruited from Kaiser Permanente Georgia (KPG) subscribers who were employed at a mid-sized private employer group. Participants completed a biometric assessment and written survey. The biometric measures included height, weight, blood pressure, hip/waist ratio, and total cholesterol. The written survey included measures of: health (SF-12), patient activation (PAM-13), leisure physical activity (BRFSS), food screeners (Block), and work presenteeism (SPS-6) and absenteeism. Over the next 6 months, participants will attend seminars on exercise, weight loss, and healthy cooking and eating. The biometric assessment and survey be repeated in February 2010. Results: Of the 63 eligible KPG subscribers, 60 (41 females and 19 males) consented to participate. Participant ages ranged from 28–77 years. Overall, physical and emotional health, activation, leisure physical activity, dietary intake, and BMI were comparable to results obtained among relatively healthy, low risk working age adults in a 2005 survey of KPG subscribers in large group employers. Total cholesterol was significantly (p<0.05), positively associated with percent fat in diet; and, percent fat in diet was significantly, inversely associated with activation. Participants with 1 or more days absent from work in the most recent 4-week period reported significantly higher total cholesterol and percent fat in diet and significantly lower activation. Participants with high levels of presenteeism were significantly less likely to report leisure physical activity at the recommended level. Conclusions: The initial results indicate that improving levels of activation (improved self-efficacy, motivation to pursue a healthy lifestyle and adhere to recommended care) might improve dietary intake (thereby reducing fat intake and cholesterol levels) and decrease BMI. The final wellness program evaluation will indicate how much change in these measures might occur in a relatively healthy group of working age adults.

PS2-17: Diabetes Social Support Feasibility Pilot Study: Utilizing Mobile Technology and Self-Identified Supporters to Enhance Self-Monitoring of Blood Glucose

Background and Aims: Self-monitoring of blood glucose (SMBG) is associated with improved glycemic control among patients with type 2 diabetes, however, the practice of daily self-monitoring is not optimal. Telecommunications technology may improve adherence to recommended self-management practices by remotely transmitting automated reminders to motivate patients, and utilizing social networking for peer support. The purpose of this pilot study is to demonstrate the feasibility and usability of mobile technology and the potential added value of social support to improve SMBG frequency and glycemic control among adults with type 2 diabetes. Methods: Adults 25–74 years of age with type 2 DM and an average HbA1c > 8.0% were recruited from Kaiser Permanente Georgia (KPGA) and Oakhurst Medical Center (OMC, a community health clinic) to participate in a 3-month study using wireless technology. Enrollment sessions with presentations on SMBG techniques, use of the wireless technology, and motivational coaching to enhance social support were conducted in November 2009. During the subsequent 3-months, both diabetes patients and their self-selected supporters will receive text messages to their cell phones summarizing a patient’s SMBG frequency and levels. Participants and their supporters will attend a disenrollment session in February 2010 when feasibility and usability will be assessed in focus groups. Results: 6 of 161 eligible diabetes patients at KPGA and 9 of 28 eligible diabetes patients at OMC, and their self-selected supporters, consented to participate. The average age of diabetes patients was 49.3 years. 86.7% (N=13) were African-American; and 33.3% (N=5) were male. Five days after enrollment, 60% (N=9) of patients had connected their wireless transmitters and had current blood glucose data. Follow-up phone calls will be made to ensure that all participants are connected to the wireless technology within 10 days of the enrollment session. Conclusion: Integrating mobile telecommunications technology with chronic disease management may empower patients in their own self-care and ease the burden on health care providers. Our study will evaluate the potential for studying the use of wireless mobile technology in a larger randomized controlled trial and will obtain participant comments on what changes might improve participant compliance.