Utilization and outcomes of transcranial magnetic stimulation and usual care for MDD in a large group psychiatric practice.

BACKGROUND: General psychiatrists' practice standards vary regarding when to implement transcranial magnetic stimulation (TMS) for care of patients with major depressive disorder (MDD). Furthermore, few studies have examined real-world utilization and clinical outcomes of TMS. This study analyzed data from a large, multi-site psychiatric practice to evaluate utilization and outcomes of TMS as well as usual care (UC) for patients with MDD. METHODS: Depression outcomes for TMS and UC among adult patients at a multi-site psychiatric group practice were examined in this retrospective cohort analysis. Patients with a primary diagnosis of MDD, PHQ-9 ≥ 10, and a visit in November 2020 with 6-month follow-up were included and categorized into the TMS or UC cohorts. RESULTS: Of 1,011 patients with qualifying PHQ-9 at the baseline visit, 9% (89) received a full course of TMS, and 583 patients receiving UC met study inclusion criteria (339 patients were excluded due to lacking a 6-month follow-up visit or receiving esketamine during the study period). The TMS cohort had higher baseline PHQ-9 than UC (17.9 vs. 15.5, p < .001) and had failed more medication trials (≥ 4 vs. 3.1, p < .001). Mean PHQ-9 decreased by 5.7 points (SD = 6.7, p < .001) in the TMS cohort and by 4.2 points (SD = 6.4, p < .001) in the UC cohort over the study period. Among patients who had failed four or more antidepressant medications, PHQ-9 decreased by 5.8 points in the TMS cohort (SD = 6.7, p < .001) and by 3.2 points in the UC cohort (SD = 6.3, p < .001). CONCLUSIONS: TMS utilization was low, despite TMS showing significant real-world clinical benefits. Future research should examine and address barriers to wider adoption of TMS into routine patient care for patients with treatment-resistant MDD. Wider adoption including routine use of TMS in less treatment-resistant patients will allow statistical comparisons of outcomes between TMS and UC populations that are difficult to do when TMS is underutilized.

Comparison of study samples recruited with virtual versus traditional recruitment methods.

BACKGROUND: Traditionally, clinical studies rely on brick-and-mortar sites to recruit participants. Newer technology-based studies have utilized non-traditional virtual methods that can potentially recruit more diverse populations and shorten recruitment timelines. This manuscript aims to quantify how sample metrics across three virtual studies compare to traditionally recruited samples, as a first step in building an empirical evidence base for the experience of participant recruitment in virtual studies. METHODS: We conducted a systematic search of the literature using PubMed to identify relevant studies conducted in the United States in cognitive health, diabetes, and hypertension (which we called comparator studies) to compare to three virtual studies. For each included study, we extracted participant demographic characteristics and information on recruitment methods and timing. Two investigators independently extracted this data, compared results for consistency, and contacted comparator study authors for clarifications. Characteristics for measurement included age, sex, race/ethnicity, states represented, recruitment time, and recruitment rate. RESULTS: We identified 19 comparator studies. Virtually recruited samples were slightly younger, had more female participants, and were split on enrollment of racial minorities as compared to comparator studies. Virtually recruited samples were more diverse geographically and recruited faster. CONCLUSIONS: Virtual recruitment may enhance efficiency and enable more individuals to participate in clinical research. To our knowledge, this is the first rigorous and replicable study comparing participant demographic characteristics and recruitment metrics between virtual and traditional recruitment methodologies. Future research should compare a wider range of studies on other metrics such as overall cost of recruitment and quality of participants.

Design, Recruitment, and Baseline Characteristics of a Virtual 1-Year Mental Health Study on Behavioral Data and Health Outcomes: Observational Study.

BACKGROUND: Depression and anxiety greatly impact daily behaviors, such as sleep and activity levels. With the increasing use of activity tracking wearables among the general population, there has been a growing interest in how data collected from these devices can be used to further understand the severity and progression of mental health conditions. OBJECTIVE: This virtual 1-year observational study was designed with the objective of creating a longitudinal data set combining self-reported health outcomes, health care utilization, and quality of life data with activity tracker and app-based behavioral data for individuals with depression and anxiety. We provide an overview of the study design, report on baseline health and behavioral characteristics of the study population, and provide initial insights into how behavioral characteristics differ between groups of individuals with varying levels of disease severity. METHODS: Individuals who were existing members of an online health community (Achievement, Evidation Health Inc) and were 18 years or older who had self-reported a diagnosis of depression or anxiety were eligible to enroll in this virtual 1-year study. Participants agreed to connect wearable activity trackers that captured data related to physical activity and sleep behavior. Mental health outcomes such as the Patient Health Questionnaire (PHQ-9), the Generalized Anxiety Disorder Questionnaire (GAD-7), mental health hospitalizations, and medication use were captured with surveys completed at baseline and months 3, 6, 9, and 12. In this analysis, we report on baseline characteristics of the sample, including mental health disease severity and health care utilization. Additionally, we explore the relationship between passively collected behavioral data and baseline mental health status and health care utilization. RESULTS: Of the 1304 participants enrolled in the study, 1277 individuals completed the baseline survey and 1068 individuals had sufficient activity tracker data. Mean age was 33 (SD 9) years, and the majority of the study population was female (77.2%, 994/1288) and identified as Caucasian (88.3%, 1137/1288). At baseline, 94.8% (1211/1277) of study participants reported experiencing depression or anxiety symptoms in the last year. This baseline analysis found that some passively tracked behavioral traits are associated with more severe forms of anxiety or depression. Individuals with depressive symptoms were less active than those with minimal depressive symptoms. Severe forms of depression were also significantly associated with inconsistent sleep patterns and more disordered sleep. CONCLUSIONS: These initial findings suggest that longitudinal behavioral and health outcomes data may be useful for developing digital measures of health for mental health symptom severity and progression.

Correction: The Association Between Medication Adherence for Chronic Conditions and Digital Health Activity Tracking: Retrospective Analysis.

[This corrects the article DOI: 10.2196/11486.].

The Association Between Medication Adherence for Chronic Conditions and Digital Health Activity Tracking: Retrospective Analysis.

BACKGROUND: Chronic diseases have a widespread impact on health outcomes and costs in the United States. Heart disease and diabetes are among the biggest cost burdens on the health care system. Adherence to medication is associated with better health outcomes and lower total health care costs for individuals with these conditions, but the relationship between medication adherence and health activity behavior has not been explored extensively. OBJECTIVE: The aim of this study was to examine the relationship between medication adherence and health behaviors among a large population of insured individuals with hypertension, diabetes, and dyslipidemia. METHODS: We conducted a retrospective analysis of health status, behaviors, and medication adherence from medical and pharmacy claims and health behavior data. Adherence was measured in terms of proportion of days covered (PDC), calculated from pharmacy claims using both a fixed and variable denominator methodology. Individuals were considered adherent if their PDC was at least 0.80. We used step counts, sleep, weight, and food log data that were transmitted through devices that individuals linked. We computed metrics on the frequency of tracking and the extent to which individuals engaged in each tracking activity. Finally, we used logistic regression to model the relationship between adherent status and the activity-tracking metrics, including age and sex as fixed effects. RESULTS: We identified 117,765 cases with diabetes, 317,340 with dyslipidemia, and 673,428 with hypertension between January 1, 2015 and June 1, 2016 in available data sources. Average fixed and variable PDC for all individuals ranged from 0.673 to 0.917 for diabetes, 0.756 to 0.921 for dyslipidemia, and 0.756 to 0.929 for hypertension. A subgroup of 8553 cases also had health behavior data (eg, activity-tracker data). On the basis of these data, individuals who tracked steps, sleep, weight, or diet were significantly more likely to be adherent to medication than those who did not track any activities in both the fixed methodology (odds ratio, OR 1.33, 95% CI 1.29-1.36) and variable methodology (OR 1.37, 95% CI 1.32-1.43), with age and sex as fixed effects. Furthermore, there was a positive association between frequency of activity tracking and medication adherence. In the logistic regression model, increasing the adjusted tracking ratio by 0.5 increased the fixed adherent status OR by a factor of 1.11 (95% CI 1.06-1.16). Finally, we found a positive association between number of steps and adherent status when controlling for age and sex. CONCLUSIONS: Adopters of digital health activity trackers tend to be more adherent to hypertension, diabetes, and dyslipidemia medications, and adherence increases with tracking frequency. This suggests that there may be value in examining new ways to further promote medication adherence through programs that incentivize health tracking and leveraging insights derived from connected devices to improve health outcomes.

Accelerating Research With Technology: Rapid Recruitment for a Large-Scale Web-Based Sleep Study.

BACKGROUND: Participant recruitment can be a significant bottleneck in carrying out research studies. Connected health and mobile health platforms allow for the development of Web-based studies that can offer improvement in this domain. Sleep is of vital importance to the mental and physical health of all individuals, yet is understudied on a large scale or beyond the focus of sleep disorders. For this reason and owing to the availability of digital sleep tracking tools, sleep is well suited to being studied in a Web-based environment. OBJECTIVE: The aim of this study was to investigate a method for speeding up the recruitment process and maximizing participant engagement using a novel approach, the Achievement Studies platform (Evidation Health, Inc, San Mateo, CA, USA), while carrying out a study that examined the relationship between participant sleep and daytime function. METHODS: Participants could access the Web-based study platform at any time from any computer or Web-enabled device to complete study procedures and track study progress. Achievement community members were invited to the study and assessed for eligibility. Eligible participants completed an electronic informed consent process to enroll in the study and were subsequently invited to complete an electronic baseline questionnaire. Then, they were asked to connect a wearable device account through their study dashboard, which shared their device data with the research team. The data were used to provide objective sleep and activity metrics for the study. Participants who completed the baseline questionnaires were subsequently sent a daily single-item Sleepiness Checker activity for 7 consecutive days at baseline and every 3 months thereafter for 1 year. RESULTS: Overall, 1156 participants enrolled in the study within a 5-day recruitment window. In the 1st hour, the enrollment rate was 6.6 participants per minute (394 per hour). In the first 24 hours, the enrollment rate was 0.8 participants per minute (47 participants per hour). Overall, 1132 participants completed the baseline questionnaires (1132/1156, 97.9%) and 1047 participants completed the initial Sleepiness Checker activity (1047/1156, 90.6%). Furthermore, 1000 participants provided activity-specific wearable data (1000/1156, 86.5%) and 982 provided sleep-specific wearable data (982/1156, 84.9%). CONCLUSIONS: The Achievement Studies platform allowed for rapid recruitment and high study engagement (survey completion and device data sharing). This approach to carrying out research appears promising. However, conducting research in this way requires that participants have internet access and own and use a wearable device. As such, our sample may not be representative of the general population.

A Remote Intervention to Prevent or Delay Cognitive Impairment in Older Adults: Design, Recruitment, and Baseline Characteristics of the Virtual Cognitive Health (VC Health) Study.

BACKGROUND: A growing body of evidence supports the use of lifestyle interventions for preventing or delaying the onset of Alzheimer disease and other forms of dementia in at-risk individuals. The development of internet-delivered programs would increase the scalability and reach of these interventions, but requires validation to ensure similar effectiveness to brick-and-mortar options. OBJECTIVE: We describe the study design, recruitment process, and baseline participant characteristics of the sample in the Virtual Cognitive Health (VC Health) study. Future analyses will assess the impact of the remotely delivered lifestyle intervention on (1) cognitive function, (2) depression and anxiety, and (3) various lifestyle behaviors, including diet, exercise, and sleep, in a cohort of older adults with subjective memory decline. Additional analyses will explore feasibility outcomes, as well as the participants' engagement patterns with the program. METHODS: Older adults (aged 60-75 years) with subjective memory decline as measured by the Subjective Cognitive Decline 9-item (SCD-9) questionnaire, and who reported feeling worried about their memory decline, were eligible to participate in this single-arm pre-post study. All participants enrolled in the yearlong digital intervention, which consists of health coach-guided lifestyle change for improving diet, exercise, sleep, stress, and cognition. All components of this study were conducted remotely, including the collection of data and the administration of the intervention. We assessed participants at baseline, 12 weeks, 24 weeks, and 52 weeks with online surveys and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) test. We will conduct intention-to-treat analysis on all outcomes. RESULTS: A total of 85 participants enrolled in the intervention and 82 are included in the study sample (3 participants withdrew). The study cohort of 82 participants comprises 61 (74%) female, 72 (88%) white, and 64 (78%) overweight or obese participants, and 55 (67%) have at least a college degree. The average baseline RBANS score was 95.9 (SD 11.1), which is within age-adjusted norms. The average SCD-9 score was 6.0 (SD 2.0), indicating minor subjective cognitive impairment at the beginning of the study. The average baseline Generalized Anxiety Disorder 7-item scale score was 6.2 (SD 4.5), and the average Patient Health Questionnaire 9-item score was 8.5 (SD 4.9), indicating mild levels of anxiety and depression at baseline. CONCLUSIONS: Internet-delivered lifestyle interventions are a scalable solution for the prevention or delay of Alzheimer disease. The results of this study will provide the first evidence for the effectiveness of a fully remote intervention and lay the groundwork for future investigations. TRIAL REGISTRATION: ClinicalTrials.gov NCT02969460; http://clinicaltrials.gov/ct2/show/NCT02969460 (Archived by WebCite at http://www.webcitation.org/71LkYAkSh). REGISTERED REPORT IDENTIFIER: RR1-10.2196/11368.

Association of a Smartphone Application With Medication Adherence and Blood Pressure Control: The MedISAFE-BP Randomized Clinical Trial.

Importance: Medication nonadherence accounts for up to half of uncontrolled hypertension. Smartphone applications (apps) that aim to improve adherence are widely available but have not been rigorously evaluated. Objective: To determine if the Medisafe smartphone app improves self-reported medication adherence and blood pressure control. Design, Setting, and Participants: This was a 2-arm, randomized clinical trial (Medication Adherence Improvement Support App For Engagement-Blood Pressure [MedISAFE-BP]). Participants were recruited through an online platform and were mailed a home blood pressure cuff to confirm eligibility and to provide follow-up measurements. Of 5577 participants who were screened, 412 completed consent, met inclusion criteria (confirmed uncontrolled hypertension, taking 1 to 3 antihypertensive medications), and were randomized in a ratio of 1:1 to intervention or control. Interventions: Intervention arm participants were instructed to download and use the Medisafe app, which includes reminder alerts, adherence reports, and optional peer support. Main Outcomes and Measures: Co-primary outcomes were change from baseline to 12 weeks in self-reported medication adherence, measured by the Morisky medication adherence scale (MMAS) (range, 0-8, with lower scores indicating lower adherence), and change in systolic blood pressure. Results: Participants (n = 411; 209 in the intervention group and 202 controls) had a mean age of 52.0 years and mean body mass index, calculated as weight in kilograms divided by height in meters squared, of 35.5; 247 (60%) were female, and 103 (25%) were black. After 12 weeks, the mean (SD) score on the MMAS improved by 0.4 (1.5) among intervention participants and remained unchanged among controls (between-group difference: 0.4; 95% CI, 0.1-0.7; P = .01). The mean (SD) systolic blood pressure at baseline was 151.4 (9.0) mm Hg and 151.3 (9.4) mm Hg, among intervention and control participants, respectively. After 12 weeks, the mean (SD) systolic blood pressure decreased by 10.6 (16.0) mm Hg among intervention participants and 10.1 (15.4) mm Hg among controls (between-group difference: -0.5; 95% CI, -3.7 to 2.7; P = .78). Conclusions and Relevance: Among individuals with poorly controlled hypertension, patients randomized to use a smartphone app had a small improvement in self-reported medication adherence but no change in systolic blood pressure compared with controls. Trial Registration: clinicaltrials.gov Identifier: NCT02727543.

A Diabetes Mobile App With In-App Coaching From a Certified Diabetes Educator Reduces A1C for Individuals With Type 2 Diabetes.

Purpose There are currently many diabetes apps available, but there is limited evidence demonstrating clinical impact. The purpose of this study is to evaluate the impact of a diabetes mobile app with in-app coaching by a certified diabetes educator on glycemic control for individuals with type 2 diabetes. Methods A 12 week-long single-arm intent-to-treat trial evaluated the impact of a diabetes mobile app and coaching program (One Drop | Mobile With One Drop | Experts), which facilitated tracking of self-care and included an in-app diabetes education program, on A1C for individuals with type 2 diabetes and an A1C ≥7.5% (58 mmol/mol). An online study platform (Achievement Studies, Evidation Health Inc, San Mateo, CA) was used to screen, consent, and enroll participants; collect study data; and track participants' progress throughout the study. Baseline and study end A1C measurements as well as questionnaire data from participants were collected. Results Participants (n = 146) were 52 ± 9 years old, 71% female, 25% black or Hispanic, diagnosed with diabetes for 11 ± 7 years, and with a mean baseline A1C of 9.87% ± 2.0 (84 mmol/mol). In adjusted repeated measures models, mean A1C improved by -0.86% among study completers (n = 127), -0.96% among active users of the app and coaching program (n = 93), and -1.32% among active users with a baseline A1C ≥9.0% (75 mmol/mol) (n = 53). Conclusions This program was associated with a clinically meaningful and significant reduction in A1C and can potentially increase access to effective diabetes self-management education and support for individuals with diabetes.

Mobile and traditional cognitive behavioral therapy programs for generalized anxiety disorder: A cost-effectiveness analysis.

BACKGROUND: Generalized anxiety disorder (GAD) is a debilitating mental health illness that affects approximately 3.1% of U.S. adults and can be treated with cognitive behavioral therapy (CBT). With the emergence of digital health technologies, mobile CBT may be a cost-effective way to deliver care. We developed an analysis framework to quantify the cost-effectiveness of internet-based CBT for individuals with GAD. As a case study, we examined the potential value of a new mobile-delivered CBT program for GAD. METHODS: We developed a Markov model of GAD health states combined with a detailed economic analysis for a cohort of adults with GAD in the U.S. In our case study, we used pilot program efficacy data to evaluate a mobile CBT program as either prevention or treatment only and compared the strategies to traditional CBT and no CBT. Traditional CBT efficacy was estimated from clinical trial results. We calculated discounted incremental costs and quality-adjusted life-years (QALYs) over the cohort lifetime. CASE STUDY RESULTS: In the base case, for a cohort of 100,000 persons with GAD, we found that mobile CBT is cost-saving. It leads to a gain of 34,108 QALYs and 81,492 QALYs and a cost reduction of $2.23 billion and $4.54 billion when compared to traditional CBT and no CBT respectively. Results were insensitive to most model inputs and mobile CBT remained cost-saving in almost all scenarios. LIMITATIONS: The case study was conducted for illustrative purposes and used mobile CBT efficacy data from a small pilot program; the analysis should be re-conducted once robust efficacy data is available. The model was limited in its ability to measure the effectiveness of CBT in combination with pharmacotherapy. CONCLUSIONS: Mobile CBT may lead to improved health outcomes at lower costs than traditional CBT or no intervention and may be effective as either prevention or treatment.

The Impact of the Virtual Cognitive Health Program on the Cognition and Mental Health of Older Adults: Pre-Post 12-Month Pilot Study.

BACKGROUND: Face-to-face multidomain lifestyle interventions have shown to be effective for improving or maintaining cognitive function in older adults at risk for dementia. Remotely delivered interventions could increase access to such solutions but first require evidence to support that these programs can successfully impact health outcomes. OBJECTIVE: The objective of this study was to evaluate the impact of a remotely delivered multidomain lifestyle intervention, the virtual cognitive health (VC Health) program, on the cognitive function and mental health of older adults with subjective cognitive decline (SCD). METHODS: A 52-week, prospective, single-arm, pre-post, remote nationwide clinical trial was conducted to measure the change in cognitive function, depression, and anxiety levels for older adults at risk of developing dementia who participated in the VC Health program. A Web-based study platform was used to screen, consent, and enroll participants across the United States. Participants completed the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) test and Web-based assessments (which included the Patient Health Questionnaire [PHQ-9] and Generalized Anxiety Disorder [GAD-7] surveys) at baseline and weeks 12, 24, and 52; all data were collected remotely. Changes in RBANS, PHQ-9, and GAD-7 were assessed using 2-tailed paired t tests and nonparametric signed-rank tests. RESULTS: Participants (N=82) were, on average, aged 64 years (range 60.0-74.9 years), 74% (61/82) female, 88% (72/82) white, and 67% (55/82) had a college degree or higher. At baseline, participants had a mean and median RBANS Total Index score of 95.9 (SD 11.1) and 95.5 (interquartile range, IQR=13). Participants experienced a mean and median increase of 5.8 (SD 7.4) and 6 (IQR=11) in RBANS Total Index score from baseline to week 52 (P<.001). Participants had a mean and median PHQ-9 score of 8.5 (SD 4.9) and 8 (IQR=6) at baseline and experienced a mean and median decrease of 3.8 (SD 4.1) and 4 (IQR=6) units in PHQ-9 score from baseline to week 52 (P<.001). At baseline, participants had a mean and median GAD-7 score of 6.2 (SD 4.5) and 5.5 (IQR=6) and experienced a mean and median decrease of 2.9 (SD 4.1) and 2 (IQR=5) units in GAD-7 score from baseline to week 52 (P<.001). Participants were engaged and very satisfied with various program components. CONCLUSIONS: In this study, older adults with SCD who were at risk for dementia experienced statistically significant improvements in their cognitive function, depression, and anxiety levels. These findings serve as initial evidence for the overall feasibility and effectiveness of the VC Health program to improve or maintain cognitive function in older adults who are experiencing SCD. Further research should be conducted to understand the degree to which the improvements are attributable to specific components of the intervention. TRIAL REGISTRATION: ClinicalTrials.gov NCT02969460; https://clinicaltrials.gov/ct2/show/NCT02969460 (Archived by WebCite at http://www.webcitation.org/73XOph9Qm).

The Impact of an Online Crowdsourcing Diagnostic Tool on Health Care Utilization: A Case Study Using a Novel Approach to Retrospective Claims Analysis.

BACKGROUND: Patients with difficult medical cases often remain undiagnosed despite visiting multiple physicians. A new online platform, CrowdMed, uses crowdsourcing to quickly and efficiently reach an accurate diagnosis for these patients. OBJECTIVE: This study sought to evaluate whether CrowdMed decreased health care utilization for patients who have used the service. METHODS: Novel, electronic methods of patient recruitment and data collection were utilized. Patients who completed cases on CrowdMed's platform between July 2014 and April 2015 were recruited for the study via email and screened via an online survey. After providing eConsent, participants provided identifying information used to access their medical claims data, which was retrieved through a third-party web application program interface (API). Utilization metrics including frequency of provider visits and medical charges were compared pre- and post-case resolution to assess the impact of resolving a case on CrowdMed. RESULTS: Of 45 CrowdMed users who completed the study survey, comprehensive claims data was available via API for 13 participants, who made up the final enrolled sample. There were a total of 221 health care provider visits collected for the study participants, with service dates ranging from September 2013 to July 2015. Frequency of provider visits was significantly lower after resolution of a case on CrowdMed (mean of 1.07 visits per month pre-resolution vs. 0.65 visits per month post-resolution, P=.01). Medical charges were also significantly lower after case resolution (mean of US $719.70 per month pre-resolution vs. US $516.79 per month post-resolution, P=.03). There was no significant relationship between study results and disease onset date, and there was no evidence of regression to the mean influencing results. CONCLUSIONS: This study employed technology-enabled methods to demonstrate that patients who used CrowdMed had lower health care utilization after case resolution. However, since the final sample size was limited, results should be interpreted as a case study. Despite this limitation, the statistically significant results suggest that online crowdsourcing shows promise as an efficient method of solving difficult medical cases.

HIV Treatment and Prevention: A Simple Model to Determine Optimal Investment.

OBJECTIVE: To create a simple model to help public health decision makers determine how to best invest limited resources in HIV treatment scale-up and prevention. METHOD: A linear model was developed for determining the optimal mix of investment in HIV treatment and prevention, given a fixed budget. The model incorporates estimates of secondary health benefits accruing from HIV treatment and prevention and allows for diseconomies of scale in program costs and subadditive benefits from concurrent program implementation. Data sources were published literature. The target population was individuals infected with HIV or at risk of acquiring it. Illustrative examples of interventions include preexposure prophylaxis (PrEP), community-based education (CBE), and antiretroviral therapy (ART) for men who have sex with men (MSM) in the US. Outcome measures were incremental cost, quality-adjusted life-years gained, and HIV infections averted. RESULTS: Base case analysis indicated that it is optimal to invest in ART before PrEP and to invest in CBE before scaling up ART. Diseconomies of scale reduced the optimal investment level. Subadditivity of benefits did not affect the optimal allocation for relatively low implementation levels. The sensitivity analysis indicated that investment in ART before PrEP was optimal in all scenarios tested. Investment in ART before CBE became optimal when CBE reduced risky behavior by 4% or less. Limitations of the study are that dynamic effects are approximated with a static model. CONCLUSIONS: Our model provides a simple yet accurate means of determining optimal investment in HIV prevention and treatment. For MSM in the US, HIV control funds should be prioritized on inexpensive, effective programs like CBE, then on ART scale-up, with only minimal investment in PrEP.

Economic utility of a blood-based genomic test for the assessment of patients with symptoms suggestive of obstructive coronary artery disease.

Approximately 3 million patients with symptoms suggestive of obstructive coronary artery disease (CAD) present to primary care offices in the United States annually, resulting in approximately $6.7 billion in cardiac workup costs. Despite wide application of existing diagnostic technologies, yield of obstructive CAD at invasive coronary angiography (ICA) is low. This study used a decision analysis model to assess the economic utility of a novel gene expression score (GES) for the diagnosis of obstructive CAD. Within a representative commercial health plan's adult membership, current practice for obstructive CAD diagnosis (usual care) was compared to a strategy that incorporates the GES test (GES-directed care). The model projected the number of diagnostic tests and procedures performed, the number of patients receiving medical therapy, type I and type II errors for each strategy of obstructive CAD diagnosis, and the associated costs over a 1-year time horizon. Results demonstrate that GES-directed care to exclude the diagnosis of obstructive CAD prior to myocardial perfusion imaging may yield savings to health plans relative to usual care by reducing utilization of noninvasive and invasive cardiac imaging procedures and increasing diagnostic yield at ICA. At a 50% capture rate of eligible patients in GES-directed care, it is projected that a commercial health plan will realize savings of $0.77 per member per month; savings increase proportionally to the GES capture rate. These findings illustrate the potential value of this new blood-based, molecular diagnostic test for health plans and patients in an age of greater emphasis on personalized medicine.

The cost-effectiveness of preexposure prophylaxis for HIV prevention in the United States in men who have sex with men.

BACKGROUND: A recent randomized, controlled trial showed that daily oral preexposure chemoprophylaxis (PrEP) was effective for HIV prevention in men who have sex with men (MSM). The Centers for Disease Control and Prevention recently provided interim guidance for PrEP in MSM at high risk for HIV. Previous studies did not reach a consistent estimate of its cost-effectiveness. OBJECTIVE: To estimate the effectiveness and cost-effectiveness of PrEP in MSM in the United States. DESIGN: Dynamic model of HIV transmission and progression combined with a detailed economic analysis. DATA SOURCES: Published literature. TARGET POPULATION: MSM aged 13 to 64 years in the United States. TIME HORIZON: Lifetime. PERSPECTIVE: Societal. INTERVENTION: PrEP was evaluated in both the general MSM population and in high-risk MSM and was assumed to reduce infection risk by 44% on the basis of clinical trial results. OUTCOME MEASURES: New HIV infections, discounted quality-adjusted life-years (QALYs) and costs, and incremental cost-effectiveness ratios. RESULTS OF BASE-CASE ANALYSIS: Initiating PrEP in 20% of MSM in the United States would reduce new HIV infections by an estimated 13% and result in a gain of 550,166 QALYs over 20 years at a cost of $172,091 per QALY gained. Initiating PrEP in a larger proportion of MSM would prevent more infections but at an increasing cost per QALY gained (up to $216,480 if all MSM receive PrEP). Preexposure chemoprophylaxis in only high-risk MSM can improve cost-effectiveness. For MSM with an average of 5 partners per year, PrEP costs approximately $50,000 per QALY gained. Providing PrEP to all high-risk MSM for 20 years would cost $75 billion more in health care-related costs than the status quo and $600,000 per HIV infection prevented, compared with incremental costs of $95 billion and $2 million per infection prevented for 20% coverage of all MSM. RESULTS OF SENSITIVITY ANALYSIS: PrEP in the general MSM population would cost less than $100,000 per QALY gained if the daily cost of antiretroviral drugs for PrEP was less than $15 or if PrEP efficacy was greater than 75%. LIMITATION: When examining PrEP in high-risk MSM, the investigators did not model a mix of low- and high-risk MSM because of lack of data on mixing patterns. CONCLUSION: PrEP in the general MSM population could prevent a substantial number of HIV infections, but it is expensive. Use in high-risk MSM compares favorably with other interventions that are considered cost-effective but could result in annual PrEP expenditures of more than $4 billion. PRIMARY FUNDING SOURCE: National Institute on Drug Abuse, Department of Veterans Affairs, and National Institute of Allergy and Infectious Diseases.

The cost-effectiveness of symptom-based testing and routine screening for acute HIV infection in men who have sex with men in the USA.

OBJECTIVE: Acute HIV infection often causes influenza-like illness (ILI) and is associated with high infectivity. We estimated the effectiveness and cost-effectiveness of strategies to identify and treat acute HIV infection in men who have sex with men (MSM) in the USA. DESIGN: Dynamic model of HIV transmission and progression. INTERVENTIONS: We evaluated three testing approaches: viral load testing for individuals with ILI, expanded screening with antibody testing, and expanded screening with antibody and viral load testing. We included treatment with antiretroviral therapy for individuals identified as acutely infected. MAIN OUTCOME MEASURES: New HIV infections, discounted quality-adjusted life years (QALYs) and costs, and incremental cost-effectiveness ratios. RESULTS: At the present rate of HIV-antibody testing, we estimated that 538,000 new infections will occur among MSM over the next 20 years. Expanding antibody screening coverage to 90% of MSM annually reduces new infections by 2.8% and costs US$ 12,582 per QALY gained. Symptom-based viral load testing with ILI is more expensive than expanded antibody screening, but is more effective and costs US$ 22,786 per QALY gained. Combining expanded antibody screening with symptom-based viral load testing prevents twice as many infections compared to expanded antibody screening alone, and costs US$ 29,923 per QALY gained. Adding viral load testing to all annual HIV tests costs more than US$ 100,000 per QALY gained. CONCLUSION: Use of HIV viral load testing in MSM with ILI prevents more infections than does expanded annual antibody screening alone and is inexpensive relative to other screening interventions. Clinicians should consider symptom-based viral load testing in MSM, in addition to encouraging annual antibody screening.

Population strategies to decrease sodium intake and the burden of cardiovascular disease: a cost-effectiveness analysis.

BACKGROUND: Sodium consumption raises blood pressure, increasing the risk for heart attack and stroke. Several countries, including the United States, are considering strategies to decrease population sodium intake. OBJECTIVE: To assess the cost-effectiveness of 2 population strategies to reduce sodium intake: government collaboration with food manufacturers to voluntarily cut sodium in processed foods, modeled on the United Kingdom experience, and a sodium tax. DESIGN: A Markov model was constructed with 4 health states: well, acute myocardial infarction (MI), acute stroke, and history of MI or stroke. DATA SOURCES: Medical Panel Expenditure Survey (2006), Framingham Heart Study (1980 to 2003), Dietary Approaches to Stop Hypertension trial, and other published data. TARGET POPULATION: U.S. adults aged 40 to 85 years. TIME HORIZON: Lifetime. PERSPECTIVE: Societal. OUTCOME MEASURES: Incremental costs (2008 U.S. dollars), quality-adjusted life-years (QALYs), and MIs and strokes averted. RESULTS OF BASE-CASE ANALYSIS: Collaboration with industry that decreases mean population sodium intake by 9.5% averts 513 885 strokes and 480 358 MIs over the lifetime of adults aged 40 to 85 years who are alive today compared with the status quo, increasing QALYs by 2.1 million and saving $32.1 billion in medical costs. A tax on sodium that decreases population sodium intake by 6% increases QALYs by 1.3 million and saves $22.4 billion over the same period. RESULTS OF SENSITIVITY ANALYSIS: Results are sensitive to the assumption that consumers have no disutility with modest reductions in sodium intake. LIMITATION: Efforts to reduce population sodium intake could result in other dietary changes that are difficult to predict. CONCLUSION: Strategies to reduce sodium intake on a population level in the United States are likely to substantially reduce stroke and MI incidence, which would save billions of dollars in medical expenses. PRIMARY FUNDING SOURCE: Department of Veterans Affairs, Stanford University, and National Science Foundation.