This paper summarizes existing research on the relationship between energy efficiency and demand response. Using information gathered through interviews with program administrators, customers, and service providers, this paper discusses the coordination of energy efficiency and demand response programs, with a particular focus on current practices and opportunities. It also discusses barriers to coordinating these two types of programs. This paper was developed as a resource for a variety of audiences that may be interested in the nexus between energy efficiency and demand response. Intended audiences include policy-makers, program administrator staff, regulatory staff, service provider organizations, and stakeholders who provide input on the design and implementation of energy efficiency and demand response programs and tariffs.

IntroductionPatients with mental and physical health conditions are complex to treat and often use multiple medications. It is unclear how adherence to one medication predicts adherence to others. A predictive relationship could permit less expensive adherence monitoring if overall adherence could be predicted through tracking a single medication.MethodsTo test this hypothesis, we examined whether patients with multiple mental and physical illnesses have similar adherence trajectories across medications. Specifically, we conducted a retrospective cohort analysis using health insurance claims data for enrollees who were diagnosed with a serious mental illness, initiated an atypical antipsychotic, as well as an SSRI (to treat serious mental illness), biguanides (to treat type 2 diabetes), or an ACE inhibitor (to treat hypertension). Using group-based trajectory modeling, we estimated adherence patterns based on monthly estimates of the proportion of days covered with each medication. We measured the predictive value of the atypical antipsychotic trajectories to adherence predictions based on patient characteristics and assessed their relative strength with the R-squared goodness of fit metric.ResultsWithin our sample of 431,591 patients, four trajectory groups were observed: non-adherent, gradual discontinuation, stop–start, and adherent. The accuracy of atypical antipsychotic adherence for predicting adherence to ACE inhibitors, biguanides, and SSRIs was 44.5, 44.5, and 49.6%, respectively (all p < 0.001 vs. random). We also found that information on patient adherence patterns to atypical antipsychotics was a better predictor of patient adherence to these three medications than would be the case using patient demographic and clinical characteristics alone.ConclusionAmong patients with multiple chronic mental and physical illnesses, patterns of atypical antipsychotic adherence were useful predictors of adherence patterns to a patient’s adherence to ACE inhibitors, biguanides, and SSRIs.FundingOtsuka Pharmaceutical Development & Commercialization, Inc.Electronic supplementary materialThe online version of this article (10.1007/s12325-018-0700-6) contains supplementary material, which is available to authorized users.

Background With some Medicaid state programs still restricting patient access to hepatitis C (HCV) treatment, it is important to demonstrate how states could expand treatment access to a broader Medicaid population and balance short-term budget concerns. Methods We used the HCV Transmission and Progression (TaP) Markov model to quantify the impact of removing restrictions to HCV treatment access on the infected populations, expenditures, and net social value for the North Carolina (NC), Oregon (OR), and Wisconsin (WI) Medicaid programs. Four HCV treatment access scenarios were modeled: 1) Baseline : Patients were treated according to Medicaid disease severity and sobriety requirements in 2015; 2) Remove Sobriety Restrictions : Disease severity restrictions were maintained, but people who inject drugs (PWID) were given access to treatment; 3) Treat Early : All patients, except for PWIDs, regardless of disease severity, were eligible for treatment and the diagnosis rate increased from 50 to 66%; and 4) Remove Access Restrictions : all patients, regardless of disease severity and sobriety, were eligible for treatment. Our key model outputs were: number of infected Medicaid beneficiaries, HCV-related medical and treatment expenditures, total social value, and state Medicaid spending over 10 years. Results Across all three states, removing access restrictions resulted in the greatest benefits over 10 years (net social value relative to baseline = $408 M in NC; $408 M in OR; $271 M in WI) and the smallest infected population (5200 in NC; 2000 in OR; 614 in WI). Reduced disease transmission resulted in lower health care expenditures (-$66 M in NC; -$50 M in OR; -$54 M in WI). All of the expanded treatment access policies achieved break-even costs—where total treatment and health care expenditures fell below those of Baseline—in 4 to 8 years. Removing access restrictions yielded the greatest improvement in social value (net of medical expenditures and treatment costs, QALYs valued at $150 K per QALY). Conclusions While increasing treatment access in Medicaid will raise short-term costs, it will also provide clear benefits relatively quickly by saving money and improving health within a 10-year window. Patients and taxpayers would benefit by considering these gains and taking a more expansive and long-term view of HCV treatment policies. Electronic supplementary material The online version of this article (10.1186/s12913-019-3956-x) contains supplementary material, which is available to authorized users.

IMPORTANCE The United States is currently facing an epidemic of deaths related to substance use disorder (SUD), with totals exceeding those due to motor vehicle crashes and gun violence. The epidemic has led to decreased life expectancy in some populations. In recent years, Medicaid eligibility has expanded in some states, and the association of this expansion with SUD-related deaths is yet to be examined. OBJECTIVE To examine the association between eligibility thresholds for state Medicaid coverage and SUD-related deaths. DESIGN, SETTING, AND PARTICIPANTS Economic evaluation study using a retrospective analysis of state-level data between 2002 and 2015 to determine the association between the Medicaid eligibility threshold and SUD-related deaths, controlling for other relevant policies, state socioeconomic characteristics, fixed effects, and a time trend. Policy variables were lagged by 1 year to allow time for associations to materialize. Data were collected and analyzed from 2016 to 2017. EXPOSURES The policy of interest was the state Medicaid eligibility threshold, ie, the highest allowed income that qualifies a person for Medicaid, expressed as a percentage of the federal poverty level. State policies related to mental health, overdose treatment, and law enforcement of drug crimes were included as controls. MAIN OUTCOMES AND MEASURES The primary outcome was number of SUD-related deaths, obtained from data provided by the Centers for Disease Control and Prevention. RESULTS Across 700 state-year observations, the mean (SD) number of SUD-related deaths was 21.15 (6.05) per 100 000 population. Between 2002 and 2015, the national SUD-related death rate increased from 16.0 to 27.5 per 100 000, while the average Medicaid eligibility threshold increased from 87.2% to 97.1% of the federal poverty level. Over this period, every 100-percentage point increase in the Medicaid eligibility threshold (eg, from 50% to 150% of the federal poverty level) was associated with 1.373 (95% CI, −2.732 to −0.014) fewer SUD-related deaths per 100 000 residents, a reduction of 6.50%. In the 22 states with net contractions in eligibility thresholds between 2005 and 2015, an estimated increase of 570 SUD-related deaths (95% CI, −143 to 1283) occurred. In the 28 states that increased eligibility thresholds, an estimated 1045 SUD-related deaths (95% CI, −209 to 2299) may have been prevented. CONCLUSIONS AND RELEVANCE These findings suggest that the overall increase in SUD-related deaths between 2002 and 2015 may have been greater had the average eligibility threshold for Medicaid not increased over this period. Broader eligibility for Medicaid coverage may be one tool to (continued) Key Points Question What is the association between changes in state Medicaid eligibility thresholds and deaths due to substance use disorder? Findings This economic evaluation of publicly available data on state policies, demographic characteristics, and mortality demonstrated an association between expanded Medicaid eligibility thresholds and reduced deaths ...

Despite improvements in outcomes for kidney transplant recipients in the past decade, graft failure continues to impose substantial burden on patients. However, the population‐wide economic burden of graft failure has not been quantified. This study aims to fill that gap by comparing outcomes from a simulation model of kidney transplant patients in which patients are at risk for graft failure with an alternative simulation in which the risk of graft failure is assumed to be zero. Transitions through the model were estimated using Scientific Registry of Transplant Recipients data from 1987 to 2017. We estimated lifetime costs, overall survival, and quality‐adjusted life‐years (QALYs) for both scenarios and calculated the difference between them to obtain the burden of graft failure. We find that for the average patient, graft failure will impose additional medical costs of $78 079 (95% confidence interval [CI] $41 074, $112 409) and a loss of 1.66 QALYs (95% CI 1.15, 2.18). Given 17 644 kidney transplants in 2017, the total incremental lifetime medical costs associated with graft failure is $1.38B (95% CI $725M, $1.98B) and the total QALY loss is 29 289 (95% CI 20 291, 38 464). Efforts to reduce the incidence of graft failure or to mitigate its impact are urgently needed.