Perceived Barriers and Trends in HPV Vaccination via Patient Survey Responses at Kalamazoo, Michigan's Federally-Qualified Health Center.

Human Papillomavirus (HPV) is the most common sexually transmitted infection (STI) in the United States. Despite numerous studies proving the safety and efficacy of the HPV vaccine, immunization rates remain low, especially among underserved populations. To identify factors contributing to low HPV vaccination rates, patients at a federally qualified health center in Kalamazoo MI were surveyed. Surveys were administered during routine patient visits to determine self-reported vaccination status and vaccination barriers. A total of 98 vaccine-eligible (males/females, ages 9-26 years old) patients/guardians completed the survey. In all, 46% of respondents completed the multi-dose vaccination course, and 56% of those identified as female. White patients reported higher vaccination rates (50%) than patients of color (45%). Of those vaccinated, the most common reason was "physician recommendation" (39%). Those not fully vaccinated most commonly reported being "too young" (39%). Importantly, individuals who had begun, but not completed, the vaccination course reported that their provider had not spoken to them about future vaccines in the series (74%). This study revealed disparities in vaccination rates between the sexes and racial groups, and emphasized the influential role of physician's recommendation on vaccination. Interestingly, other frequently cited barriers to vaccination-an association with sex, personal/religious beliefs, efficacy-proved to be insignificant barriers for this population. Instead, age-related misunderstandings and lack of consistent physician communication about vaccination provided significant barriers. Based on our results, education and reminders about the HPV vaccine by providers is a significant tool to maximize vaccination coverage.

Cancer Screening Reminders: Addressing the Spectrum of Patient Preferences.

CONTEXT: Health care systems continue to seek evidence about how to optimize the efficiency and effectiveness of cancer screening reminders. Annual reminders to receive preventive services can be an efficient strategy. OBJECTIVE: To understand patient motivators and barriers to cancer screening and preferences about reminder strategies. DESIGN: We conducted 11 focus groups among adults recommended for cancer screening within Kaiser Permanente Washington. We held separate focus groups with women aged 21 to 49 years, women 50 to 75 years, and men 50 to 75 years. We used an inductive, validated coding scheme for analysis. MAIN OUTCOME MEASURES: Motivators and barriers to obtaining recommended cancer screening and general cancer screening reminder content and modality preferences. RESULTS: Half of our participants were women aged 50 to 75 years, and 25% were men aged 50 to 75 years. Differences by age, sex, insurance status, financial status, and health beliefs all drove the participants' preferences for whether they seek these recommended services and how and when they wish to be reminded about recommended cancer screening. Most participants preferred personalized reminders, and many favored receiving reminders less than 3 months before the recommended procedure date rather than a consolidated annual reminder. Younger participants more commonly requested electronic reminders, such as texts and e-mails. CONCLUSION: Optimizing cancer screening reminders within a health care system involves a multifaceted approach that enables members to request which form of reminder they prefer (eg, electronic, paper, telephone) and the timing with which they want to be reminded, while staying affordable and manageable to the health care system.

Validation of natural language processing to extract breast cancer pathology procedures and results.

BACKGROUND: Pathology reports typically require manual review to abstract research data. We developed a natural language processing (NLP) system to automatically interpret free-text breast pathology reports with limited assistance from manual abstraction. METHODS: We used an iterative approach of machine learning algorithms and constructed groups of related findings to identify breast-related procedures and results from free-text pathology reports. We evaluated the NLP system using an all-or-nothing approach to determine which reports could be processed entirely using NLP and which reports needed manual review beyond NLP. We divided 3234 reports for development (2910, 90%), and evaluation (324, 10%) purposes using manually reviewed pathology data as our gold standard. RESULTS: NLP correctly coded 12.7% of the evaluation set, flagged 49.1% of reports for manual review, incorrectly coded 30.8%, and correctly omitted 7.4% from the evaluation set due to irrelevancy (i.e. not breast-related). Common procedures and results were identified correctly (e.g. invasive ductal with 95.5% precision and 94.0% sensitivity), but entire reports were flagged for manual review because of rare findings and substantial variation in pathology report text. CONCLUSIONS: The NLP system we developed did not perform sufficiently for abstracting entire breast pathology reports. The all-or-nothing approach resulted in too broad of a scope of work and limited our flexibility to identify breast pathology procedures and results. Our NLP system was also limited by the lack of the gold standard data on rare findings and wide variation in pathology text. Focusing on individual, common elements and improving pathology text report standardization may improve performance.