Identifying microbial drivers in biological phenotypes with a Bayesian Network Regression model

1. In Bayesian Network Regression models, networks are considered the predictors of continuous responses. These models have been successfully used in brain research to identify regions in the brain that are associated with specific human traits, yet their potential to elucidate microbial drivers in biological phenotypes for microbiome research remains unknown. In particular, microbial networks are challenging due to their high-dimension and high sparsity compared to brain networks. Furthermore, unlike in brain connectome research, in microbiome research, it is usually expected that the presence of microbes have an effect on the response (main effects), not just the interactions. 2. Here, we develop the first thorough investigation of whether Bayesian Network Regression models are suitable for microbial datasets on a variety of synthetic and real data under diverse biological scenarios. We test whether the Bayesian Network Regression model that accounts only for interaction effects (edges in the network) is able to identify key drivers (microbes) in phenotypic variability. 3. We show that this model is indeed able to identify influential nodes and edges in the microbial networks that drive changes in the phenotype for most biological settings, but we also identify scenarios where this method performs poorly which allows us to provide practical advice for domain scientists aiming to apply these tools to their datasets. 4. BNR models provide a framework for microbiome researchers to identify connections between microbes and measured phenotypes. We allow the use of this statistical model by providing an easy-to-use implementation which is publicly available Julia package at https://github.com/solislemuslab/BayesianNetworkRegression.jl.Comment: 62 pages, 49 figure

Frequency of Participation in an Employee Fitness Program and Health Care Expenditures

Regular physical activity is strongly linked to prevention of costly chronic health conditions. However, there has been limited examination of the impact that level of participation in physical activity promotion programs has on health care costs. This study examined a fitness reimbursement program (FRP) offered to small employers. FRP participants received $20 reimbursement every month they visited their fitness center ≥12 days. Visits were recorded electronically. Participants were assigned to 4 mutually exclusive cohorts by mean monthly fitness center visits: low (<4 visits); low-moderate (≥4 and <8 visits), high-moderate (≥8 and <12 visits), and high (≥12 visits, which qualified for reimbursement). Cohorts were matched by inverse propensity score weighting on demographic, health status, health care supply, and socioeconomic characteristics. Between-cohort differences in propensity score-weighted health care costs, starting from FRP program sign-up, were examined with a generalized linear model. Analyses were conducted with and without high-cost outliers during the pre- and post-FRP period. A total of 8723 participants (mean follow-up: 11.1 months) were identified during October 2010-June 2013. With high-cost outliers removed (n?=?226), a pattern of lower per-member-per-month health care costs was observed with increasing participation: compared with the low cohort, monthly savings were:$6.14 (2.6%) for low-moderate (P?=?0.60), $16.40 (6.9$20.01 (8.4%) for high (P?=?0.08). With high-cost outliers included, significant monthly cost savings were observed for the moderate-high ($43.52, P?Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140192/1/pop.2015.0102.pd

Longitudinal patterns of antidepressant prescribing in primary care in the UK: comparison with treatment guidelines

The objective of this study was to determine whether patients beginning therapy on the most common tricyclic antidepressants (TCAs) and selective serotonin reuptake inhibitors (SSRIs) differed in their likelihood of having antidepressant treatment that was consistent with recommended treatment guidelines in the UK. An analytical file constructed from a large general practitioner medical records database (DIN-LINK) from the UK for the years 1992-97 was constructed. A total of 16 204 patients with a new episode of antidepressant therapy who initiated therapy on one of the most often prescribed TCAs (amitriptyline, dothiepin, imipramine and lofepramine) or SSRIs (fluoxetine, paroxetine and sertraline) were analysed. A dichotomous measure was defined to indicate whether subjects were prescribed at least 120 days of antidepressant therapy at an adequate average daily dose within the first 6 months after initiation of therapy. Only 6.0% of patients initiating therapy on aTCA and 32.9% of patients initiating therapy on a SSRI were prescribed antidepressant treatment that was consistent with treatment guidelines. After controlling for observable characteristics, patients who initiated therapy on a SSRI were much more likely (odds ratio=7.473, p<0.001) to have a prescribed average daily dose and duration consistent with recommended treatment guidelines within the first 6 months of initiating therapy than were patients who initiated therapy on a TCA. These findings suggest that initial antidepressant selection is an important determinant of whether the subsequent course of treatment is consistent with current national guidelines for the treatment of depression in the UK.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68732/2/10.1177_026988119901300204.pd

A More Generalizable Method to Evaluate Changes in Health Care Costs with Changes in Health Risks Among Employers of All Sizes

The objective of this study was to estimate the association between changes in health care expenditures relative to changes in health risk status for employers of all sizes. Repeat health risk assessments (HRAs) were obtained from 50,005 employees and spouses with 2 years of health plan enrollment, and from 37,559 employees and spouses with 3 years of enrollment in employer-sponsored medical coverage. Changes in health care expenditures were measured from the year before completion of the first HRA to the years before and after the completion of the second HRA. Propensity score weighting was used to adjust for those who did not repeat the HRA so results could be extrapolated to the larger population. Propensity score weighted multiple regression analyses were used to estimate the relationship between changes in health care expenditures with changes in risk status for 9 risk categories. Significantly higher health care expenditures were associated with those who moved from low risk to medium or high risk, compared to those who remained low risk. Expenditure reductions estimated for those who improved their health status from high risk to medium or low risk were not statistically significant. This study is unique because of its large sample size, its use of data from a wide range of employer sizes, and its efforts to extend generalizability to those who did not complete both HRAs. These results demonstrate that the potential for short-term health care savings may be greater for programs that help maintain low risk than for programs focused on risk reduction. (Population Health Management 2014;17:297?305)Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140183/1/pop.2013.0103.pd

Cost Burden of Illness for Hepatitis C Patients with Employer-Sponsored Health Insurance

The disease burden of hepatitis C virus (HCV) is expected to more than double in the next two decades. Currently, there is very little information about the costs of HCV treatment for employers who pay for treatment and health plans that cover HCV patients. This study reports the medical costs of HCV for workers with health insurance. A retrospective claims data design was used for this study. A sample of HCV patients with health insurance was drawn from the inpatient, outpatient, and enrollment files of the MEDSTAT Group's MarketScan family of databases for 1993-1998. Patients were grouped into cohorts and studied for up to 2 years before and after HCV diagnosis. Sample size varies according to length of follow-up, peaking at 3,077 patients enrolled for at least 6 months. In the first year following HCV diagnosis, average payments for HCV patients ($10,925) were almost six times as high as payments for all patients in the MarketScan database ($1,186). Doctors are encouraged to test high-risk patients to find HCV patients earlier in the course of their disease and to better manage their care in order to avoid unnecessary illness and expenses for this disease.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63140/1/109350702320229195.pd

Disparities in Major Joint Replacement Surgery among Adults with Medicare Supplement Insurance

The objective of this study was to determine if disparities in hip and knee replacement surgery exist among osteoarthritis patients with AARP-branded Medicare supplement plan (ie, Medigap) coverage provided by UnitedHealthcare. Patients were selected into the study if they had 1 or more medical claims with a diagnosis of osteoarthritis from July 1, 2006 to June 30, 2007. Logistic regression analyses tested for age-, sex-, race-, or income-related differences in the likelihood of receiving a hip or knee replacement surgery. The regression models controlled for socioeconomics, health status, type of supplement plan, and residential location. Of the 2.2 million Medigap insureds eligible for this study, 529,652 (24%) had osteoarthritis. Of these, 32,527 (6.1%) received a hip or knee replacement. Males were 6% (P-<-0.001) more likely than females to have a replacement surgery. Patients living in minority or lower income neighborhoods were less likely to receive a hip or knee replacement. Supplement plan type was not a strong predictor of the likelihood of hip or knee replacement. Disparities were much greater by comorbid condition and residential location. Disparities in hip and knee replacement surgery existed by age, sex, race, and income levels. Larger disparities were found by residential location and comorbid condition. Interventions are being considered to address these disparities. (Population Health Management 2011;14:231-238)Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90479/1/pop-2E2010-2E0042.pd

Effectiveness of Writing Groups in Nursing Homes

We examine the effect of participation in an 8-week writing group in six nursing homes. Pretest and posttest assessments of cognitive and affective functional status were administered to 62 participants and 54 control subjects. We asked writing-group participants about previous writing experience and perceived ability to convey feelings, ideas, life experiences, and memories to others. Weekly assessments were conducted on eight group process measures. Findings suggest that participation in writing groups may reduce depression, particularly among residents with higher cognitive ability and greater depression. Significantly more participants than control subjects report an ability to relate feelings and ideas to other residents and staff. Improvement in group process measures is greatest for cognitively impaired participants and those with high physical function scores. There is considerable improve ment in residents for whom writing-group participation frequently is considered inappropriate: those without writing experience, the depressed, and the cognitively impaired.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67030/2/10.1177_073346488900800308.pd

An Emergency Room Decision-Support Program That Increased Physician Office Visits, Decreased Emergency Room Visits, and Saved Money

The objective of this study was to evaluate an Emergency Room having a Decision-Support (ERDS) program designed to appropriately reduce ER use among frequent users, defined as 3 or more visits within a 12-month period. To achieve this, adults with an AARP Medicare Supplement Insurance plan insured by UnitedHealthcare Insurance Company (for New York residents, UnitedHealthcare Insurance Company of New York) were eligible to participate in the program. These included 7070 individuals who elected to enroll in the ERDS program and an equal number of matched nonparticipants who were eligible but either declined or were unreachable. Program-related benefits were estimated by comparing the difference in downstream health care utilization and expenditures between engaged and not engaged individuals after using propensity score matching to adjust for case mix differences between these groups. As a result, compared with the not engaged, engaged individuals experienced better care coordination, evidenced by a greater reduction in ER visits (P=0.033) and hospital admissions (P=0.002) and an increase in office visits (P<0.001). The program was cost-effective, with a return on investment (ROI) of 1.24, which was calculated by dividing the total program savings ($3.41 million) by the total program costs ($2.75 million). The ROI implies that for every dollar invested in this program, $1.24 was saved, most of which was for the federal Medicare program. In conclusion, the decrease in ER visits and hospital admissions and the increase in office visits may indicate the program helped individuals to seek the appropriate levels of care. (Population Health Management 2014;17:257?264)Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140184/1/pop.2013.0117.pd