DiabetesSistersVoices: Virtual Patient Community to Identify Research Priorities for Women Living With Diabetes.

BACKGROUND: Women with or at high risk of diabetes have unique health concerns across their life course. Effective methods are needed to engage women living with diabetes to develop and carry out a patient-centered research agenda. OBJECTIVE: This study aimed to (1) describe the creation of DiabetesSistersVoices, a virtual patient community for women living with and at risk for diabetes and (2) assess the feasibility and acceptability of DiabetesSistersVoices for engaging women in talking about their experiences, health care, and research priorities. METHODS: We partnered with a national advocacy organization to create DiabetesSistersVoices and to develop recruitment strategies, which included use of social media, Web-based newsletters, and weblinks through partnering organizations. Study inclusion criteria were as follows: Being a woman aged ≥18 years, residing in the United States, and self-reporting a diagnosis of diabetes or risk of diabetes. Eligible participants were given access to DiabetesSistersVoices and completed online surveys at enrollment and 6 months. We assessed trends in participants' activities, including posting questions, sharing experiences about living with diabetes, and searching for posted resources. RESULTS: We enrolled 332 women (white: 86.5%; type 1 diabetes: 76.2%; median age: 51 years [interquartile range: 31 to 59 years]) over 8 months. Most (41.6%, 138/332) were classified as being active users (ie, posting) of the virtual community, 36.1% (120/332) as observers (ie, logged in but no posts), and 22.3% (74/332) as never users (ie, completed baseline surveys but then never logged in). Online activities were constant during the study, although participants had the highest website usage during the first 10 weeks after their enrollment. CONCLUSIONS: We demonstrated the feasibility and acceptability of an online patient community for women living with diabetes by showing durability of recruitment and online usage over 6 months of testing. Next steps are to address barriers to joining a virtual patient community for women of color and women with type 2 diabetes to enhance inclusiveness and gain diverse perspectives to inform diabetes research.

Optimizing research in symptomatic uterine fibroids with development of a computable phenotype for use with electronic health records.

BACKGROUND: Women with symptomatic uterine fibroids can report a myriad of symptoms, including pain, bleeding, infertility, and psychosocial sequelae. Optimizing fibroid research requires the ability to enroll populations of women with image-confirmed symptomatic uterine fibroids. OBJECTIVE: Our objective was to develop an electronic health record-based algorithm to identify women with symptomatic uterine fibroids for a comparative effectiveness study of medical or surgical treatments on quality-of-life measures. Using an iterative process and text-mining techniques, an effective computable phenotype algorithm, composed of demographics, and clinical and laboratory characteristics, was developed with reasonable performance. Such algorithms provide a feasible, efficient way to identify populations of women with symptomatic uterine fibroids for the conduct of large traditional or pragmatic trials and observational comparative effectiveness studies. Symptomatic uterine fibroids, due to menorrhagia, pelvic pain, bulk symptoms, or infertility, are a source of substantial morbidity for reproductive-age women. Comparing Treatment Options for Uterine Fibroids is a multisite registry study to compare the effectiveness of hormonal or surgical fibroid treatments on women's perceptions of their quality of life. Electronic health record-based algorithms are able to identify large numbers of women with fibroids, but additional work is needed to develop electronic health record algorithms that can identify women with symptomatic fibroids to optimize fibroid research. We sought to develop an efficient electronic health record-based algorithm that can identify women with symptomatic uterine fibroids in a large health care system for recruitment into large-scale observational and interventional research in fibroid management. STUDY DESIGN: We developed and assessed the accuracy of 3 algorithms to identify patients with symptomatic fibroids using an iterative approach. The data source was the Carolina Data Warehouse for Health, a repository for the health system's electronic health record data. In addition to International Classification of Diseases, Ninth Revision diagnosis and procedure codes and clinical characteristics, text data-mining software was used to derive information from imaging reports to confirm the presence of uterine fibroids. Results of each algorithm were compared with expert manual review to calculate the positive predictive values for each algorithm. RESULTS: Algorithm 1 was composed of the following criteria: (1) age 18-54 years; (2) either ≥1 International Classification of Diseases, Ninth Revision diagnosis codes for uterine fibroids or mention of fibroids using text-mined key words in imaging records or documents; and (3) no International Classification of Diseases, Ninth Revision or Current Procedural Terminology codes for hysterectomy and no reported history of hysterectomy. The positive predictive value was 47% (95% confidence interval 39-56%). Algorithm 2 required ≥2 International Classification of Diseases, Ninth Revision diagnosis codes for fibroids and positive text-mined key words and had a positive predictive value of 65% (95% confidence interval 50-79%). In algorithm 3, further refinements included ≥2 International Classification of Diseases, Ninth Revision diagnosis codes for fibroids on separate outpatient visit dates, the exclusion of women who had a positive pregnancy test within 3 months of their fibroid-related visit, and exclusion of incidentally detected fibroids during prenatal or emergency department visits. Algorithm 3 achieved a positive predictive value of 76% (95% confidence interval 71-81%). CONCLUSION: An electronic health record-based algorithm is capable of identifying cases of symptomatic uterine fibroids with moderate positive predictive value and may be an efficient approach for large-scale study recruitment.

Perceived barriers and preferred components for physical activity interventions in African-American survivors of breast or endometrial cancer with type 2 diabetes: the S.U.C.C.E.S.S. framework.

PURPOSE: African-American (AA) female cancer survivors share a disproportionate burden of diabetes compared to their white counterparts. Our objectives were to explore the perspectives of AA survivors with type 2 diabetes on perceived barriers to physical activity (PA) and preferences for a PA intervention and develop a framework for a PA program after cancer treatment. METHODS: Trained interviewers conducted semi-structured interviews with AA survivors of breast or endometrial cancer with diabetes (total n = 20; 16 breast, 4 endometrial). Thirteen open-ended questions were posed to stimulate discussions, which were audio recorded and transcribed verbatim. Two investigators independently reviewed transcriptions and extracted coded quotations to identify major themes. RESULTS: Median age of participants was 63 years. Nine themes were identified that focused on post-treatment physical symptoms (e.g., lymphedema, bone/joint pain, depression symptoms and self-motivation as barriers to PA, exercise routines tailored to physical limitations and peer partners and program leaders who understand their emotional health needs). The S.U.C.C.E.S.S. framework summarizes the survivors' preferences for an effective lifestyle intervention: Support efforts to maintain PA, Understand physical and depression symptoms, Collaborate with multi-disciplinary provider, Coordinate in-person intervention activities, Encourage partnerships among survivors for comorbidity risk reduction, develop Sustainable coping strategies for side effects of treatment, and Share local community resources. CONCLUSIONS: Survivors verbalized the need for a multi-disciplinary team to assist with their psychosocial needs and physical limitations to achieve their PA goals, as integrated into the S.U.C.C.E.S.S. IMPLICATIONS FOR CANCER SURVIVORS: The S.U.C.C.E.S.S. framework reflects the perspectives of survivors with type 2 diabetes and may help to inform post-treatment programs.