Penetrance of Hemochromatosis in HFE Genotypes Resulting in p.Cys282Tyr and p.[Cys282Tyr];[His63Asp] in the eMERGE Network.

Hereditary hemochromatosis (HH) is a common autosomal-recessive disorder associated with pathogenic HFE variants, most commonly those resulting in p.Cys282Tyr and p.His63Asp. Recommendations on returning incidental findings of HFE variants in individuals undergoing genome-scale sequencing should be informed by penetrance estimates of HH in unselected samples. We used the eMERGE Network, a multicenter cohort with genotype data linked to electronic medical records, to estimate the diagnostic rate and clinical penetrance of HH in 98 individuals homozygous for the variant coding for HFE p.Cys282Tyr and 397 compound heterozygotes with variants resulting in p.[His63Asp];[Cys282Tyr]. The diagnostic rate of HH in males was 24.4% for p.Cys282Tyr homozygotes and 3.5% for compound heterozygotes (p < 0.001); in females, it was 14.0% for p.Cys282Tyr homozygotes and 2.3% for compound heterozygotes (p < 0.001). Only males showed differences across genotypes in transferrin saturation levels (100% of homozygotes versus 37.5% of compound heterozygotes with transferrin saturation > 50%; p = 0.003), serum ferritin levels (77.8% versus 33.3% with serum ferritin > 300 ng/ml; p = 0.006), and diabetes (44.7% versus 28.0%; p = 0.03). No differences were found in the prevalence of heart disease, arthritis, or liver disease, except for the rate of liver biopsy (10.9% versus 1.8% [p = 0.013] in males; 9.1% versus 2% [p = 0.035] in females). Given the higher rate of HH diagnosis than in prior studies, the high penetrance of iron overload, and the frequency of at-risk genotypes, in addition to other suggested actionable adult-onset genetic conditions, opportunistic screening should be considered for p.[Cys282Tyr];[Cys282Tyr] individuals with existing genomic data.

Nudging physician prescription decisions by partitioning the order set: results of a vignette-based study.

BACKGROUND: Healthcare professionals are rapidly adopting electronic health records (EHRs). Within EHRs, seemingly innocuous menu design configurations can influence provider decisions for better or worse. OBJECTIVE: The purpose of this study was to examine whether the grouping of menu items systematically affects prescribing practices among primary care providers. PARTICIPANTS: We surveyed 166 primary care providers in a research network of practices in the greater Chicago area, of whom 84 responded (51% response rate). Respondents and non-respondents were similar on all observable dimensions except that respondents were more likely to work in an academic setting. DESIGN: The questionnaire consisted of seven clinical vignettes. Each vignette described typical signs and symptoms for acute respiratory infections, and providers chose treatments from a menu of options. For each vignette, providers were randomly assigned to one of two menu partitions. For antibiotic-inappropriate vignettes, the treatment menu either listed over-the-counter (OTC) medications individually while grouping prescriptions together, or displayed the reverse partition. For antibiotic-appropriate vignettes, the treatment menu either listed narrow-spectrum antibiotics individually while grouping broad-spectrum antibiotics, or displayed the reverse partition. MAIN MEASURES: The main outcome was provider treatment choice. For antibiotic-inappropriate vignettes, we categorized responses as prescription drugs or OTC-only options. For antibiotic-appropriate vignettes, we categorized responses as broad- or narrow-spectrum antibiotics. KEY RESULTS: Across vignettes, there was an 11.5 percentage point reduction in choosing aggressive treatment options (e.g., broad-spectrum antibiotics) when aggressive options were grouped compared to when those same options were listed individually (95% CI: 2.9 to 20.1%; p = .008). CONCLUSIONS: Provider treatment choice appears to be influenced by the grouping of menu options, suggesting that the layout of EHR order sets is not an arbitrary exercise. The careful crafting of EHR order sets can serve as an important opportunity to improve patient care without constraining physicians' ability to prescribe what they believe is best for their patients.

Electronic health record-based patient identification and individualized mailed outreach for primary cardiovascular disease prevention: a cluster randomized trial.

BACKGROUND: Many individuals at higher risk for cardiovascular disease (CVD) do not receive recommended treatments. Prior interventions using personalized risk information to promote prevention did not test clinic-wide effectiveness. OBJECTIVE AND DESIGN: To perform a 9-month cluster-randomized trial, comparing a strategy of electronic health record-based identification of patients with increased CVD risk and individualized mailed outreach to usual care. PARTICIPANTS: Patients of participating physicians with a Framingham Risk Score of at least 5 %, low-density lipoprotein (LDL)-cholesterol level above guideline threshold for drug treatment, and not prescribed a lipid-lowering medication were included in the intention-to-treat analysis. INTERVENTION: Patients of physicians randomized to the intervention group were mailed individualized CVD risk messages that described benefits of using a statin (and controlling hypertension or quitting smoking when relevant). MAIN MEASURES: The primary outcome was occurrence of a LDL-cholesterol level, repeated in routine practice, that was at least 30 mg/dl lower than prior. A secondary outcome was lipid-lowering drug prescribing. Clinicaltrials.gov identifier: NCT01286311. KEY RESULTS: Fourteen physicians with 218 patients were randomized to intervention, and 15 physicians with 217 patients to control. The mean patient age was 60.7 years and 77% were male. There was no difference in the primary outcome (11.0 % vs. 11.1 %, OR 0.99, 95 % CI 0.56-1.74, P = 0.96), but intervention group patients were twice as likely to receive a prescription for lipid-lowering medication (11.9 %, vs. 6.0 %, OR 2.13, 95 % CI 1.05-4.32, p = 0.038). In post hoc analysis with extended follow-up to 18 months, the primary outcome occurred more often in the intervention group (22.5 % vs. 16.1 %, OR 1.59, 95 % CI 1.05-2.41, P = 0.029). CONCLUSIONS: In this effectiveness trial, individualized mailed CVD risk messages increased the frequency of new lipid-lowering drug prescriptions, but we observed no difference in proportions lowering LDL-cholesterol after 9 months. With longer follow-up, the intervention's effect on LDL-cholesterol levels was apparent.

Changes in performance after implementation of a multifaceted electronic-health-record-based quality improvement system.

BACKGROUND: Electronic health record (EHR) systems have the potential to revolutionize quality improvement (QI) methods by enhancing quality measurement and integrating multiple proven QI strategies. OBJECTIVES: To implement and evaluate a multifaceted QI intervention using EHR tools to improve quality measurement (including capture of contraindications and patient refusals), make point-of-care reminders more accurate, and provide more valid and responsive clinician feedback (including lists of patients not receiving essential medications) for 16 chronic disease and preventive service measures. DESIGN: Time series analysis at a large internal medicine practice using a commercial EHR. SUBJECTS: All adult patients eligible for each measure (range approximately 100-7500). MEASURES: The proportion of eligible patients who satisfied each measure after removing those with exceptions from the denominator. RESULTS: During the year before the intervention, performance improved significantly for 8 measures. During the year after the intervention, performance improved significantly for 14 measures. For 9 measures, the primary outcome improved more rapidly during the intervention year than during the previous year (P < 0.001 for 8 measures, P = 0.02 for 1). Four other measures improved at rates that were not significantly different from the previous year. Improvements resulted from increases in patients receiving the service, documentation of exceptions, or a combination of both. For 5 drug-prescribing measures, more than half of physicians achieved 100% performance. CONCLUSIONS: Implementation of a multifaceted QI intervention using EHR tools to improve quality measurement and the accuracy and timeliness of clinician feedback improved performance and/or accelerated the rate of improvement for multiple measures simultaneously.

Frequency of inappropriate medical exceptions to quality measures.

BACKGROUND: Quality improvement programs that allow physicians to document medical reasons for deviating from guidelines preserve clinicians' judgment while enabling them to strive for high performance. However, physician misconceptions or gaming potentially limit programs. OBJECTIVE: To implement computerized decision support with mechanisms to document medical exceptions to quality measures and to perform peer review of exceptions and provide feedback when appropriate. DESIGN: Observational study. SETTING: Large internal medicine practice. PARTICIPANTS: Patients eligible for 1 or more quality measures. MEASUREMENTS: A peer-review panel judged medical exceptions to 16 chronic disease and prevention quality measures as appropriate, inappropriate, or of uncertain appropriateness. Medical records were reviewed after feedback was given to determine whether care changed. RESULTS: Physicians recorded 650 standardized medical exceptions during 7 months. The reporting tool was used without any medical reason 36 times (5.5%). Of the remaining 614 exceptions, 93.6% were medically appropriate, 3.1% were inappropriate, and 3.3% were of uncertain appropriateness. Frequencies of inappropriate exceptions were 7 (6.9%) for coronary heart disease, 0 (0%) for heart failure, 10 (10.8%) for diabetes, and 2 (0.6%) for preventive services. After physicians received direct feedback about inappropriate exceptions, 8 of 19 (42%) changed management. The peer-review process took less than 5 minutes per case, but for each change in clinical care, 65 reviews were required. LIMITATION: The findings could differ at other sites or if financial incentives were in place. CONCLUSION: Physician-recorded medical exceptions were correct most of the time. Peer review of medical exceptions can identify myths and misconceptions, but the process needs to be more efficient to be sustainable. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality.

Associations Between Health Literacy and Medication Self-Management Among Community Health Center Patients with Uncontrolled Hypertension.

PURPOSE: Examine associations between health literacy and several medication self-management constructs among a population of adults with uncontrolled hypertension. PATIENTS AND METHODS: Cross-sectional study of health center patients from the Chicago area with uncontrolled hypertension enrolled between April 2012 and February 2015. Medication self-management constructs-applied to hypertension medications, chronic condition medications and all medications-included: 1) medication reconciliation, 2) knowledge of drug indications, 3) understanding instructions and dosing, and 4) self-reported adherence over 4 days (no missed doses). We determined associations between health literacy and self-management outcomes using multivariable generalized linear regression. RESULTS: There were 1460 patients who completed screening interviews; 62.9% enrolled and had complete baseline data collected, and were included in the analysis. Of 919 participants, 47.4% had likely limited (low), 33.2% possibly limited, and 19.4% likely adequate health literacy. Compared to participants with likely adequate health literacy, participants with low health literacy were less likely to have chronic medications reconciled (18.0% versus 29.6%, p=0.007), know indications for chronic medications (64.1% versus 83.1%, p<0.001), and demonstrate understanding of instructions and dosing (68.1% versus 82.9%, p=0.001). Self-reported adherence to hypertension medications was higher among the low health literacy group (65.6% versus 56.0%, p=0.010). In multivariable models, health literacy was strongly associated with knowledge of drug indications, and understanding of instructions and dosing. CONCLUSION: Low health literacy was associated with worse medication self-management in several domains. However, non-adherence was greatest in the most health literate in unadjusted analysis. Among a population of patients with uncontrolled hypertension, the drivers of poor control may vary by health literacy.

Effect of Electronic Health Record-Based Medication Support and Nurse-Led Medication Therapy Management on Hypertension and Medication Self-management: A Randomized Clinical Trial.

Importance: Complex medication regimens pose self-management challenges, particularly among populations with low levels of health literacy. Objective: To test medication management tools delivered through a commercial electronic health record (EHR) with and without a nurse-led education intervention. Design, Setting, and Participants: This 3-group cluster randomized clinical trial was performed in community health centers in Chicago, Illinois. Participants included 794 patients with hypertension who self-reported using 3 or more medications concurrently (for any purpose). Data were collected from April 30, 2012, through February 29, 2016, and analyzed by intention to treat. Interventions: Clinics were randomly assigned to to groups: electronic health record-based medication management tools (medication review sheets at visit check-in, lay medication information sheets printed after visits; EHR-alone group), EHR-based tools plus nurse-led medication management support (EHR plus education group), or usual care. Main Outcomes and Measures: Outcomes at 12 months included systolic blood pressure (primary outcome), medication reconciliation, knowledge of drug indications, understanding of medication instructions and dosing, and self-reported medication adherence. Medication outcomes were assessed for all hypertension prescriptions, all prescriptions to treat chronic disease, and all medications. Results: Among the 794 participants (68.6% women; mean [SD] age, 52.7 [9.6] years), systolic blood pressure at 12 months was greater in the EHR-alone group compared with the usual care group by 3.6 mm Hg (95% CI, 0.3 to 6.9 mm Hg). Systolic blood pressure in the EHR plus education group was not significantly lower compared with the usual care group (difference, -2.0 mm Hg; 95% CI, -5.2 to 1.3 mm Hg) but was lower compared with the EHR-alone group (-5.6 mm Hg; 95% CI, -8.8 to -2.4 mm Hg). At 12 months, hypertension medication reconciliation was improved in the EHR-alone group (adjusted odds ratio [OR], 1.8; 95% CI, 1.1 to 2.9) and the EHR plus education group (adjusted odds ratio [OR], 2.0; 95% CI, 1.3 to 3.3) compared with usual care. Understanding of medication instructions and dosing was greater in the EHR plus education group than the usual care group for hypertension medications (OR, 2.3; 95% CI, 1.1 to 4.8) and all medications combined (OR, 1.7; 95% CI, 1.0 to 2.8). Compared with usual care, the EHR tools alone and EHR plus education interventions did not improve hypertension medication adherence (OR, 0.9; 95% CI, 0.6-1.4 for both) or knowledge of chronic drug indications (OR for EHR tools alone, 1.0 [95% CI, 0.6 to 1.5] and OR for EHR plus education, 1.1 [95% CI, 0.7-1.7]). Conclusions and Relevance: The study found that EHR tools in isolation improved medication reconciliation but worsened blood pressure. Combining these tools with nurse-led support suggested improved understanding of medication instructions and dosing but did not lower blood pressure compared with usual care. Trial Registration: ClinicalTrials.gov identifier: NCT01578577.

Patient knowledge and recall of health information following exposure to "facts and myths" message format variations.

OBJECTIVE: To assess if exposure to varying "facts and myths" message formats affected participant knowledge and recall accuracy of information related to influenza vaccination. METHODS: Consenting patients (N=125) were randomized to receive one of four influenza related messages (Facts Only; Facts and Myths; Facts, Myths, and Refutations; or CDC Control), mailed one week prior to a scheduled physician visit. Knowledge was measured using 15 true/false items at pretest and posttest; recall accuracy was assessed using eight items at posttest. RESULTS: All participants' knowledge scores increased significantly (p<0.05); those exposed to the CDC Control message had a higher posttest knowledge score (adjusted mean=11.18) than those in the Facts Only condition (adjusted mean 9.61, p=<0.02). Participants accurately recalled a mean of 4.49 statements (SD=1.98). ANOVA demonstrated significant differences in recall accuracy by condition [F(3, 83)=7.74, p<.001, η(2)=0.22]. CONCLUSION: Messages that include facts, myths, and evidence to counteract myths appear to be effective in increasing participants' knowledge. We found no evidence that presenting both facts and myths is counterproductive to recall accuracy. PRACTICE IMPLICATIONS: Use of messages containing facts and myths may engage the reader and lead to knowledge gain. Recall accuracy is not assured by merely presenting factual information.

Implementation of EHR-based strategies to improve outpatient CAD care.

OBJECTIVES: To evaluate the effects of a multifaceted quality improvement intervention during 2 time periods on 4 coronary artery disease [CAD] measures in 4 primary care practices. During the first phase, electronic reminders prompted physicians to order indicated medications or record contraindications and refusals (exceptions). In the second phase, physicians also received reports about their performance (including lists of patients not satisfying these measures), and financial incentives were announced. STUDY DESIGN: Time series analysis. METHODS: Adult CAD patients seen within the preceding 18 months were included. The primary outcome was the performance on each measure (proportion of eligible patients satisfying each measure after removing those with exceptions). Secondary outcomes were the proportion with the medication on their medication list, and the proportion with exceptions. RESULTS: Median performance at baseline was 78.8% for antiplatelet treatment, 85.1% for statin treatment, 77.0% for beta-blocker after myocardial infarction (MI), and 67.1% for angiotensinconverting enzyme inhibitor or angiotensin receptor blocker after MI. Performance improved slightly for 3 measures during the first phase and improved more substantially for all 4 measures during the second phase. For 3 of 4 measures, however, documentation of exceptions increased but not medication prescribing. Most exceptions were judged to be appropriate by peer review. CONCLUSIONS: Physicians responded more to the combination of feedback and financial incentives than they had to electronic reminders alone. High performance was only achieved for 1 of 4 measures and recording of exceptions rather than increases in medication prescribing accounted for most of the observed improvements.

Effects of standardized outreach for patients refusing preventive services: a quasiexperimental quality improvement study.

OBJECTIVE: To determine the effect of standardized outreach on the receipt of preventive services for patients whose physicians record that the patient refused the service. STUDY DESIGN: Prospective observational study of a quality improvement intervention using a nonrandomly assigned comparator group. METHODS: Patients from a large internal medicine practice with recorded refusals to preventive services were included. A nonclinician care manager mailed plain-language educational brochures, attempted telephone contact, and provided logistical assistance. The primary patient outcome was the time from refusal to first receipt of a refused service (colorectal cancer screening, breast cancer screening [mammography], cervical cancer screening, osteoporosis screening [bone density testing], or pneumococcal vaccination). We compared the time to completion of refused sevices during the period when outreach was performed (February 8, 2008, to November 25, 2008 [outreach cohort]), and during a subsequent period when refusals were recorded but no outreach was performed (November 26, 2008, to December 1, 2009 [nonintervention cohort]), using Cox proportional hazards regression models adjusted for patient characteristics. We recorded the time spent performing outreach. RESULTS: In total, 407 patients refused 520 preventive services in the outreach cohort, and 378 patients refused 510 services in the nonintervention cohort. After 6 months of follow-up, 6.1% of the outreach cohort and 4.8% of the nonintervention cohort had received a refused service (adjusted hazard ratio, 1.3; 95% confidence interval, 0.7-2.5). The care manager spent 214 hours performing the outreach. CONCLUSIONS: Standardized educational outreach was not a promising strategy for improving preventive services use among patients who have refused services recommended by their physician. The amount of time required to perform the outreach was substantial.