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DNP 835 Topic 7 Discussion Question Two
DNP 835 Topic 7 Discussion Question Two
One key issue related to poor adherence to prescribed treatment is patient lack of understanding. What tools are available to determine a level of health literacy and how can they be utilized to improve patient outcomes?
2.1. Setting and sample
The Baylor University Institutional Review Board approved the survey and informed consent procedures used in this research study, which was nested within a larger study designed to assess self-reported health behaviors and the prevalence of perceived health symptoms. The target population were patients of the Family Health Center (FHC), a large federally qualified health center in central Texas. At the health center in 2016, 165,784 primary medical care encounters were provided to 49,581 patients by 68 physicians (21 family physicians, 38 resident/fellow family physicians, 2 pediatricians, 3 internists, 4 obstetrician/gynecologists), 14 nurse practitioners, and 5 physician assistants. Approximately 1 out of every 5 county residents is a health center patient, and over 90% of FHC patients live at or below 200% of federal poverty guidelines.
Between February 15 and June 15, 2016, patients were approached in FHC waiting rooms to determine eligibility. Eligible patients were English-speaking adult patients ≥40 years of age. Patients who met inclusion criteria and provided consent were administered
orally a 10-minute survey by study staff. After the survey was complete, study staff accessed electronic medical records to obtain laboratory, medication, and healthcare utilization data. When the patient completed the survey, his/her name was included in a drawing for a 1 in 10 chance of winning a $20 gift card to a local grocery store.
Health literacy was assessed with 2 tools: the NVS and a single-item screening question. The NVS is a quick and valid functional health literacy assessment. Administration time ranges from 2 to 6 minutes and it has a high sensitivity to detect limited healthy literacy. Patients are given an ice cream nutrition label and asked subsequent 6 questions. Questions focus on caloric and nutritional intake (testing reading and numeracy) and ingredients (testing functional health literacy); responses are scored as correct or incorrect and correct responses are summed (see Appendix 1). According to previous work, patients who respond with 4 or more correct responses are likely to have adequate health literacy, patients who respond with 2 or 3 correct responses have a possibility of limited health literacy, and patients who respond with 0 or 1 correct responses have a high likelihood of limited health literacy. In addition to the NVS, a single-item screening question was also used to identify perceived difficulty with medical information. Patients were asked “How confident are you filling out medical forms by yourself?” Response choices included Extremely, Quite a bit, Somewhat, A little bit, and Not at all. Patients completed this single question during a telephone call after they completed the oral survey to obtain all other data in 2016.
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Patients were also asked to provide self-rated health status, determined from the question “In general, would you say your health is excellent, very good, good, fair, or poor?” Demographic data were obtained from the electronic medical record and included age, sex, and race/ethnicity (categorized as Hispanic/Latino, non-Hispanic white, non-Hispanic black, or non-Hispanic other (which included Asian)). Health data from the electronic medical record included body mass index (BMI; kg/m2), diabetes status (yes/no), and number of current medications. Healthcare utilization in the previous 24 months included number of office visits and number of missed appointments, defined as the number of “no shows” plus the number of canceled appointments.
2.3. Statistical analysis
Descriptive statistics, including mean (standard deviation) for continuous variables and percent for categorical variables, were calculated for all variables in the total study population. We also described the study population by NVS assessment results, using 4 categories: missing (i.e., patient declined NVS assessment), high likelihood of limited health literacy, possibility of limited health literacy, and adequate health literacy. We compared the 4 categories, which included the “missing” health literacy category, using analysis of variance (ANOVA) for continuous variables and Chi-square tests for categorical variables. We generated odds ratios (OR) and corresponding 95% confidence intervals (CI) from logistic regression to determine the association between each predictor variable separately and the possibility or high likelihood of limited health literacy (NVS < 4). We also used multivariate logistic regression to simultaneously adjust for all other predictor variables. Data management, descriptive statistics, and logistic regression models were conducted using SAS v9.4 (SAS Institute Inc., Cary, NC).
Receiver operating curves (ROC) were constructed using MedCalc software (v17.7.2) to determine the perceived level of confidence completing medical forms that has the best balance of sensitivity and specificity in comparison to the NVS instrument used as the reference standard. The larger the area under the receiver operating curve (AUROC)—that is, the closer the curve follows the left and top borders of the plot—the more accurate the test.[24,27] We also calculated the sensitivity, specificity, and positive and negative likelihood ratios as predictors of possibly or high likelihood of limited health literacy (NVS < 4). Statistical significance was defined a priori at the 2-sided α = 0.05 level.
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