Computational phenotyping within electronic healthcare data to identify transgender people in the United States: A narrative review.

PURPOSE: With the expansion of research utilizing electronic healthcare data to identify transgender (TG) population health trends, the validity of computational phenotype (CP) algorithms to identify TG patients is not well understood. We aim to identify the current state of the literature that has utilized CPs to identify TG people within electronic healthcare data and their validity, potential gaps, and a synthesis of future recommendations based on past studies. METHODS: Authors searched the National Library of Medicine's PubMed, Scopus, and the American Psychological Association PsycInfo's databases to identify studies published in the United States that applied CPs to identify TG people within electronic healthcare data. RESULTS: Twelve studies were able to validate or enhance the positive predictive value (PPV) of their CP through manual chart reviews (n = 5), hierarchy of code mechanisms (n = 4), key text-strings (n = 2), or self-surveys (n = 1). CPs with the highest PPV to identify TG patients within their study population contained diagnosis codes and other components such as key text-strings. However, if key text-strings were not available, researchers have been able to find most TG patients within their electronic healthcare databases through diagnosis codes alone. CONCLUSION: CPs with the highest accuracy to identify TG patients contained diagnosis codes along with components such as procedural codes or key text-strings. CPs with high validity are essential to identifying TG patients when self-reported gender identity is not available. Still, self-reported gender identity information should be collected within electronic healthcare data as it is the gold standard method to better understand TG population health patterns.

The Carolina hysterectomy cohort (CHC): a novel case series of reproductive-aged hysterectomy patients across 10 hospitals in the US south.

BACKGROUND: Hysterectomy is a common surgery among reproductive-aged U.S. patients, with rates highest among Black patients in the South. There is limited insight on causes of these racial differences. In the U.S., electronic medical records (EMR) data can offer richer detail on factors driving surgical decision-making among reproductive-aged populations than insurance claims-based data. Our objective in this cohort profile paper is to describe the Carolina Hysterectomy Cohort (CHC), a large EMR-based case-series of premenopausal hysterectomy patients in the U.S. South, supplemented with census and surgeon licensing data. To demonstrate one strength of the data, we evaluate whether patient and surgeon characteristics differ by insurance payor type. METHODS: We used structured and abstracted EMR data to identify and characterize patients aged 18-44 years who received hysterectomies for non-cancerous conditions between 10/02/2014-12/31/2017 in a large health care system comprised of 10 hospitals in North Carolina. We used Chi-squared and Kruskal Wallis tests to compare whether patients' socio-demographic and relevant clinical characteristics, and surgeon characteristics differed by patient insurance payor (public, private, uninsured). RESULTS: Of 1857 patients (including 55% non-Hispanic White, 30% non-Hispanic Black, 9% Hispanic), 75% were privately-insured, 17% were publicly-insured, and 7% were uninsured. Menorrhagia was more prevalent among the publicly-insured (74% vs 68% overall). Fibroids were more prevalent among the privately-insured (62%) and the uninsured (68%). Most privately insured patients were treated at non-academic hospitals (65%) whereas most publicly insured and uninsured patients were treated at academic centers (66 and 86%, respectively). Publicly insured and uninsured patients had higher median bleeding (public: 7.0, uninsured: 9.0, private: 5.0) and pain (public: 6.0, uninsured: 6.0, private: 3.0) symptom scores than the privately insured. There were no statistical differences in surgeon characteristics by payor groups. CONCLUSION: This novel study design, a large EMR-based case series of hysterectomies linked to physician licensing data and manually abstracted data from unstructured clinical notes, enabled identification and characterization of a diverse reproductive-aged patient population more comprehensively than claims data would allow. In subsequent phases of this research, the CHC will leverage these rich clinical data to investigate multilevel drivers of hysterectomy in an ethnoracially, economically, and clinically diverse series of hysterectomy patients.

Patient and Surgery Characteristics of Inpatient Hysterectomies Among Transgender Individuals.

Purpose: The purpose of this study is to estimate population-based rates of inpatient hysterectomy and accompanying bilateral salpingo-oophorectomy by indication and evaluate surgical patient characteristics by indication, year, patient age, and hospital location. Methods: We used 2016 and 2017 cross-sectional data from the Nationwide Inpatient Sample to estimate the hysterectomy rate for individuals aged 18-54 years with a primary indication for gender-affirming care (GAC) compared to other indications. Outcome measures were population-based rates for inpatient hysterectomy and bilateral salpingo-oophorectomy by indication. Results: The population-based rate of inpatient hysterectomy for GAC per 100,000 was 0.05 (95% confidence interval [CI] = 0.02-0.09) in 2016 and 0.09 (95% CI = 0.03-0.15) in 2017. For comparison, the rates per 100,000 for fibroids were 85.76 in 2016 and 73.25 in 2017. Rates of bilateral salpingo-oophorectomy in the setting of hysterectomy were higher in the GAC group (86.4%) than in comparison groups (22.7%-44.1% for all other benign indications, 77.4% for cancer) across all age ranges. A higher rate of hysterectomies performed for GAC was done laparoscopically or robotically (63.6%) than other indications, and none was done vaginally, as opposed to comparison groups (0.7%-9.8%). Conclusion: The population-based rate for GAC was higher in 2017 compared to 2016 and low compared to other hysterectomy indications. Rates of concomitant bilateral salpingo-oophorectomy were more prevalent for GAC than for other indications at similar ages. The patients in the GAC group tended to be younger, insured, and most procedures occurred in the Northeast (45.5%) and West (36.4%).

Does the Use of Motivational Interviewing Skills Promote Change Talk Among Young People Living With HIV in a Digital HIV Care Navigation Text Messaging Intervention?

Motivational interviewing (MI) is a counseling approach to facilitate behavior change. MI has been widely applied to in-person-delivered, health behavior change interventions; however, mobile health (mHealth) interventions are beginning to adopt and expand the reach of MI in health promotion practice with the use of mobile phones and digital platforms. This study examines whether the use of MI skills (e.g., OARS [open-ended questions, affirmations, reflective listening, and summaries]) promotes change talk in an SMS text messaging intervention for young people living with HIV in San Francisco. We undertake a novel method of analyzing text message intervention data in order to characterize the microprocesses of change talk. Data were collected via computer-assisted self-interviewing surveys of self-reported sociodemographic information, and two-way text messages facilitated by a digital HIV care navigator during the 6-month intervention. We qualitatively assessed all text messages exchanged for the utilization of four basic MI skills on the part of the interventionist (OARS) and participant change talk. This study found that high levels of all four MI skills-and moderate levels of open-ended questions only-were associated with more change talk compared to low levels. Additionally, using three or more MI skills was associated with change talk. Future research is needed to inform how to analyze large amounts of data passively collected as a native part of implementing mHealth and text messaging applications of MI interventions.

Intersectional Discrimination Is Associated with Housing Instability among Trans Women Living in the San Francisco Bay Area.

Trans women face numerous structural barriers to health due to discrimination. Housing instability is an important structural determinant of poor health outcomes among trans women. The purpose of this study was to determine if experiences of intersectional anti-trans and racial discrimination are associated with poor housing outcomes among trans women in the San Francisco Bay Area. A secondary analysis of baseline data from the Trans *National study (n = 629) at the San Francisco Department of Public Health (2016-2018) was conducted. Multivariable logistic regression was used to analyze the association between discrimination as an ordered categorical variable (zero, one to two, or three or more experiences) and housing status adjusting for age, years lived in the Bay Area, and gender identity. We found that the odds of housing instability increased by 1.25 for every categorical unit increase (1-2, or 3+) in reported experiences of intersectional (both anti-trans and racial) discrimination for trans women (95% CI = 1.01-1.54, p-value < 0.05). Intersectional anti-trans and racial discrimination is associated with increased housing instability among trans women, giving some insight that policies and programs are needed to identify and address racism and anti-trans stigma towards trans women. Efforts to address intersectional discrimination may positively impact housing stability, with potential for ancillary effects on increasing the health and wellness of trans women who face multiple disparities.