Objective To report the design and implementation of the Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment Protocol that was developed to test the concept that prescribers can deliver genome guided therapy at the point-of-care by using preemptive pharmacogenomics (PGx) data and clinical decision support (CDS) integrated in the electronic medical record (EMR). Patients and Methods We used a multivariable prediction model to identify patients with a high risk of initiating statin therapy within 3 years. The model was used to target a study cohort most likely to benefit from preemptive PGx testing among Mayo Clinic Biobank participants with a recruitment goal of 1000 patients. Cox proportional hazards model was utilized using the variables selected through the Lasso shrinkage method. An operational CDS model was adapted to implement PGx rules within the EMR. Results The prediction model included age, sex, race, and 6 chronic diseases categorized by the Clinical Classifications Software for ICD-9 codes (dyslipidemia, diabetes, peripheral atherosclerosis, disease of the blood-forming organs, coronary atherosclerosis and other heart diseases, and hypertension). Of the 2000 Biobank participants invited, 50% provided blood samples, 13% refused, 28% did not respond, and 9% consented but did not provide a blood sample within the recruitment window (October 4, 2012 – March 20, 2013). Preemptive PGx testing included CYP2D6 genotyping and targeted sequencing of 84 PGx genes. Synchronous real-time CDS is integrated in the EMR and flags potential patient-specific drug-gene interactions and provides therapeutic guidance. Conclusion These interventions will improve understanding and implementation of genomic data in clinical practice.

BackgroundThe prevention of recurrent hospitalizations in the frail elderly requires the implementation of high-intensity interventions such as case management. In order to be practically and financially sustainable, these programs require a method of identifying those patients most at risk for hospitalization, and therefore most likely to benefit from an intervention. The goal of this study is to demonstrate the use of an electronic medical record to create an administrative index which is able to risk-stratify this heterogeneous population.MethodsWe conducted a retrospective cohort study at a single tertiary care facility in Rochester, Minnesota. Patients included all 12,650 community-dwelling adults age 60 and older assigned to a primary care internal medicine provider on January 1, 2005. Patient risk factors over the previous two years, including demographic characteristics, comorbid diseases, and hospitalizations, were evaluated for significance in a logistic regression model. The primary outcome was the total number of emergency room visits and hospitalizations in the subsequent two years. Risk factors were assigned a score based on their regression coefficient estimate and a total risk score created. This score was evaluated for sensitivity and specificity.ResultsThe final model had an AUC of 0.678 for the primary outcome. Patients in the highest 10% of the risk group had a relative risk of 9.5 for either hospitalization or emergency room visits, and a relative risk of 13.3 for hospitalization in the subsequent two year period.ConclusionsIt is possible to create a screening tool which identifies an elderly population at high risk for hospital and emergency room admission using clinical and administrative data readily available within an electronic medical record.

Background Efficiently caring for frail, older adults will become an increasingly important part of healthcare reform; telemonitoring within homes may be an answer to improve outcomes. This study sought to determine the difference in hospitalizations and emergency room (ER) visits in older adults using telemonitoring versus usual care. Methods This was a randomized trial of adults older than 60 years with high-risk for rehospitalization. Subjects were randomized to telemonitoring with daily input versus patient-driven usual care. Telemonitoring was accomplished by daily biometrics, symptom reporting and videoconference. The primary outcome included a composite end-point of hospitalization and ER visits in the 12 months following enrollment. Secondary end-points included hospital days, hospital admissions, and ER visits. Intention to treat analysis was performed. Results Two hundred and five subjects were enrolled with a mean age of 80.3 years. There was no difference in hospitalizations and ER visits between the telemonitoring group (63.7%) and the group receiving usual care (57.3%) (P value 0.345). There was no difference in individual outcomes including hospital days, hospital admissions and ER visits. There also was no significant change between hospitalizations and ER visits in the pre-enrollment and post-enrollment period. Mortality was higher in the telemonitoring group (14.7%), compared to usual care (3.9%) (P value 0.008). Conclusions Among elderly patients, telemonitoring did not result in lower hospitalizations or ER visits. There were no differences determined within the secondary outcomes. The cause of the mortality difference is unknown.

OBJECTIVE To report the design and first three years of enrollment of the Mayo Clinic Biobank. PATIENTS AND METHODS Preparations for this Biobank began with a 4-day Deliberative Community Engagement with local residents to obtain community input into the design and governance of the biobank. Recruitment, which began in April 2009, is ongoing with a target goal of 50,000. Any Mayo Clinic patient who is 18+ years, able to consent, and a US resident is eligible to participate. Each participant completes a health history questionnaire, provides a blood sample and allows access to existing tissue specimens and all data from their Mayo Clinic medical record (EMR). A Community Advisory Board provides ongoing advice and guidance on complex decisions. RESULTS After three years of recruitment, 21,736 subjects have enrolled. Participants were 58% female, 95% of European ancestry, and median age of 62 years. Seventy-four percent lived in Minnesota, 42% from Olmsted County where the Mayo Clinic Rochester is located. The five most commonly self-reported conditions were hyperlipidemia (41%), hypertension (38%), osteoarthritis (30%), any cancer (29%), and gastroesophageal reflux disease (26%). Among self-reported cancer patients, the five most common types were non-melanoma skin cancer (14%), prostate cancer (12% in men), breast cancer (4%), melanoma (3%), and cervical cancer (2% in women). Fifty-six percent of participants had at least 15 years of EMR history. To date, over sixty projects and over 69,000 samples have been approved for use. CONCLUSION The Mayo Clinic Biobank has quickly been established as a valuable resource for researchers.

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Testosterone (Te) production declines in the aging male, albeit for unknown reasons. Plausible mechanisms include reduced secretion of GnRH, less feedforward by LH, and/or altered feedback by systemic Te. The present study tests all three postulates in a cohort of 10 young (20-35 yr old) and eight older (50-72 yr old) men. The experimental paradigm comprised graded blockade of the GnRH receptor to create four distinct strata of LH and Te pulsatility in each subject. A novel analytical formalism was developed to reconstruct implicit dose-response functions linking 1) virtual GnRH outflow positively to LH secretion, 2) LH pulses positively to Te secretion, and 3) Te concentrations negatively to the size and number of LH secretory bursts. Validation was by direct pituitary sampling in the horse and sheep. Statistical comparisons disclosed that age decreased the efficacy of each of 1) virtual GnRH outflow (P < 0.01), 2) LH drive of Te secretion (P < 0.01), and 3) total, bioavailable and free Te feedback on GnRH-driven LH secretion (P = 0.015). In contrast, age increased the potency of virtual GnRH feedforward (P = 0.013) and did not affect Te's inhibition of LH pulse frequency. Unexplained variance was less than 10%. Robustness was shown by resampling techniques. Accordingly, competitive silencing of one locus of control and ensemble-based analyses identified triple regulatory deficits in the aging male gonadal axis. The generality of the present integrative model suggests utility in parsing interlinked adaptations in other physiological networks.

BackgroundTwo primary objectives when caring for older adults are to slow the decline to a worsened frailty state and to prevent disability. Telemedicine may be one method of improving care in this population. We conducted a secondary analysis of the Tele-ERA study to evaluate the effect of home telemonitoring in reducing the rate of deterioration into a frailty state and death in older adults with comorbid health problems.MethodsThis trial involved 205 adults over the age of 60 years with a high risk of hospitalization and emergency department visits. For 12 months, the intervention group received usual medical care and telemonitoring case management, and the control group received usual care alone. The primary outcome was frailty, which was based on five criteria, ie, weight loss, weakness, exhaustion, low activity, and slow gait speed. Participants were classified as frail if they met three or more criteria; prefrail if they met 1–2 criteria; and not frail if they met no criteria. Both groups were assessed for frailty at baseline, and at 6 and 12 months. Frailty transition analyses were performed using a multiple logistic regression method. Kaplan–Meier and Cox proportional hazards methods were used to evaluate each frailty criteria for mortality and to compute unadjusted hazard ratios associated with being telemonitored, respectively. A retrospective power analysis was computed.ResultsDuring the first 6 months, 19 (25%) telemonitoring participants declined in frailty status or died, compared with 17 (19%) in usual care (odds ratio 1.41, 95% confidence interval [CI] 0.65–3.06, P = 0.38). In the subsequent 6 months, there was no transition to a frailty state, but seven (7%) participants from the telemonitoring and one (1%) from usual care group died (odds ratio 5.94, 95% CI 0.52–68.48, P = 0.15). Gait speed (hazards ratio 3.49, 95% CI 1.42–8.58) and low activity (hazards ratio 3.10, 95% CI 1.25–7.71) were shown to predict mortality.ConclusionThis study did not provide sufficient evidence to show that the telemonitoring group did better than usual care in reducing the decline of frailty states and death. Transitions occurred primarily in the first 6 months.

ContextStudies on 24-h cortisol secretion are rare. The impact of sex, age and adiposity on cortisol levels, often restricted to one or a few samples, are well recognized, but conflicting.ObjectiveTo investigate cortisol dynamics in 143 healthy men and women, spanning 7 decades and with a 2-fold body mass index (BMI) range with different analytic tools.SettingClinical Research Unit.DesignCortisol concentrations in 10-min samples collected for 24 h. Outcomes were mean levels, deconvolution parameters, approximate entropy (ApEn, regularity statistic) and 24-h rhythms.ResultsTotal 24-h cortisol secretion rates estimated by deconvolution analysis were sex, age and BMI independent. Mean 24-h cortisol concentrations were lower in premenopausal women than those in men of comparable age (176 ± 8.2 vs 217 ± 9.4 nmol/L, P = 0.02), but not in subjects older than 50 years. This was due to lower daytime levels in women, albeit similar in the quiescent overnight period. Aging increased mean cortisol by 10 nmol/L per decade during the quiescent secretory phase and advanced the acrophase of the diurnal rhythm by 24 min/decade. However, total 24-h cortisol secretion rates estimated by deconvolution analysis were sex, age and BMI independent. ApEn of 24-h profiles was higher (more random) in premenopausal women than those in men (1.048 ± 0.025 vs 0.933 ± 0.023, P = 0.001), but not in subjects older than 50 years. ApEn peaked during the daytime.ConclusionSex and age jointly determine the 24-h cortisol secretory profile. Sex effects are largely restricted to age <50 years, whereas age effects elevate concentrations in the late evening and early night and advance the timing of the peak diurnal rhythm.