Given a passage with a context and an answer, construct a question on the basis of the information present in the passage. Construct the question in such a way that (i) it is unambiguous, (ii) it is answerable from the passage, (iii) its answer is unique (iv) it answer uses text phrases from the passage. Avoid creating questions that (i) can't be answered correctly without actually understanding the passage and (ii) uses the same words or phrases given in the passage.

Example Input: Context: Adipose tissue is responsible for releasing various adipokines that have been related to insulin resistance. Understanding the relationship of these adipokines to insulin resistance may foster the development of new treatments for diabetes.', 'The primary objective of this study was to determine whether an association between retinol-binding protein 4 (RBP4) and insulin resistance exists in nonobese individuals without a family history or diagnosis of diabetes. The secondary objective was to determine by a dual energy x-ray absorptiometry scan which adipose tissue depot most closely relates to RBP4 levels.', 'Cross-sectional analysis of 92 study participants ranging in age from 20 to 83 yr was performed. The range of body mass index (BMI) was from 18 to 30 kg/m(2). Exclusion criteria were a BMI greater than 30 kg/m(2), family history of diabetes, or a diagnosis of diabetes. Insulin sensitivity was determined by a hyperinsulinemic euglycemic clamp. Body fat was measured by dual energy x-ray absorptiometry scan.', 'RBP4 values were lower in females (35.8 +/- 1.7 microg/ml) compared with males (39.9 +/- 1.4 microg/ml; P = 0.06). RBP4 levels were found to correlate negatively with insulin sensitivity (r = -0.32; P = 0.002) and positively with age (r = 0.38; P < 0.001). RBP4 levels did not correlate with BMI (r = -0.13; P = 0.22), trunk fat (r = 0.16; P = 0.22), or percent body fat (r = 0.07; P = 0.65). However, RBP4 levels did correlate with percent trunk fat (r = 0.36; P = 0.001).
Answer: These findings indicate a relationship between RBP4, insulin sensitivity, and percent trunk fat in individuals who may not have features of insulin resistance.
Example Output: Is retinol-binding protein 4 associated with insulin resistance and body fat distribution in nonobese subjects without type 2 diabetes?

Example Input: Context: Autoimmune hepatitis (AIH) is an uncommon autoimmune liver disease of unknown etiology. We used a genome-wide approach to identify genetic variants that predispose individuals to AIH.', 'We performed a genome-wide association study of 649 adults in The Netherlands with AIH type 1 and 13,436 controls. Initial associations were further analyzed in an independent replication panel comprising 451 patients with AIH type 1 in Germany and 4103 controls. We also performed an association analysis in the discovery cohort using imputed genotypes of the major histocompatibility complex region.', 'We associated AIH with a variant in the major histocompatibility complex region at rs2187668 (P = 1.5 × 10(-78)). Analysis of this variant in the discovery cohort identified HLA-DRB1*0301 (P = 5.3 × 10(-49)) as a primary susceptibility genotype and HLA-DRB1*0401 (P = 2.8 × 10(-18)) as a secondary susceptibility genotype. We also associated AIH with variants of SH2B3 (rs3184504, 12q24; P = 7.7 × 10(-8)) and CARD10 (rs6000782, 22q13.1; P = 3.0 × 10(-6)). In addition, strong inflation of association signal was found with single-nucleotide polymorphisms associated with other immune-mediated diseases, including primary sclerosing cholangitis and primary biliary cirrhosis, but not with single-nucleotide polymorphisms associated with other genetic traits.
Answer: In a genome-wide association study, we associated AIH type 1 with variants in the major histocompatibility complex region, and identified variants of SH2B3and CARD10 as likely risk factors. These findings support a complex genetic basis for AIH pathogenesis and indicate that part of the genetic susceptibility overlaps with that for other immune-mediated liver diseases.
Example Output: Does genome-wide association study identify variants associated with autoimmune hepatitis type 1?

Example Input: Context: A safety event drew attention to unsafe and inappropriate payer formulary alerts. These alerts display formulary, coverage, and eligibility data from the pharmacy benefits manager in response to an electronic prescription. They are intended to redirect prescribers to medications that are covered by insurance; however, these alerts were found to be inaccurate and contribute to potentially harmful alerts. Our objective was to reduce inappropriate payer formulary alerts by 30% within 1 year and to change the ePrescribing certification requirements to prevent future instances of harm.', 'Using process mapping we identified the changes that were required both locally and nationally through our electronic health record (EHR) vendor and ePrescribing transaction broker. We partnered with vendors to show the safety risk and to suggest modifications to the payer formulary alert content and ePrescribing certification criteria. On the basis of the new criteria, we modified and deactivated inappropriate alerts. Rates were followed weekly for 13 months and a control chart was used to track progress.', 'From January 2014 to January 2015, we reviewed 59\u2009325 payer formulary alerts from ambulatory care and 11\u2009630 from the emergency department and inpatient wards. Both local and national modifications resulted in significant and sustained decreases in inappropriate alerts.
Answer: Enduring and meaningful change required partnership with multiple stakeholders, including EHR vendors, ePrescribing vendors, and pharmacy benefits managers. Improving drug alerts, reducing alert fatigue, and promoting value-based prescribing in the EHR will likely require similar partnerships.
Example Output:
Does payer Formulary alert as a Cause of Patient Harm and the Journey to Change Them?