Assessment of Unmet Health-Related Social Needs Among Patients With Mental Illness Enrolled in Medicare Advantage.

Importance: A large body of literature has found associations between unmet health-related social needs (HRSNs) and adverse mental health outcomes. A comparative analysis of the risks associated with HRSNs among patients with varying severity of mental illness and an assessment of how these risks compare with those of individuals without mental illness are needed. Objective: To examine the prevalence and risks of HRSNs among patients with serious and persistent mental illness (SPMI), patients with mental health diagnoses but no serious and persistent mental illness (non-SPMI), and patients with both SPMI and non-SPMI compared with individuals without mental illness. Design, Setting, and Participants: This retrospective cohort study used data from the Accountable Health Communities HRSN Screening Tool surveys, which target a nationally representative sample of Medicare Advantage members of a large payer (Humana Inc). The surveys were conducted between October 16, 2019, and February 29, 2020. Of the initial 329 008 eligible Medicare Advantage enrollees, 70 273 responded to the survey (21.4% response rate). Of those, 56 081 respondents (79.8%) had complete survey responses and were included in the final analytic sample. Main Outcomes and Measures: Outcomes of interest included 7 HRSNs (financial strain, food insecurity, housing instability, housing quality, severe loneliness, transportation problems, and utility affordability) based on responses to the survey. The major independent variable was the presence of mental illness up to 12 months preceding the date of survey completion. Codes indicating mental illness listed as the primary, principal, or secondary diagnoses of a patient's inpatient or outpatient medical claims data were identified, and participants were grouped into 4 cohorts: SPMI, non-SPMI, SPMI plus non-SPMI, and no mental illness. Results: Among 56 081 older adults, the mean (SD) age was 71.31 (8.59) years; 32 717 participants (58.3%) were female, and 43 498 (77.6%) were White. A total of 21 644 participants (38.6%) had at least 1 mental illness diagnosis in the past year, 30 262 (54.0%) had an HRSN, and 14 163 (25.3%) had both mental illness and an HRSN. Across all specific HRSNs, the odds of experiencing the respective HRSN was most substantial for those with SPMI plus non-SPMI vs those with only non-SPMI or SPMI. The HRSN with the largest risk differences among the study cohorts was severe loneliness; compared with the cohort without mental illness, the non-SPMI cohort had 2.07 times higher odds (95% CI, 1.84-2.32; P < .001), the SPMI cohort had 3.35 times higher odds (95% CI, 3.03-3.71; P < .001), and the SPMI plus non-SPMI cohort had 5.13 times higher odds (95% CI, 4.68-5.61; P < .001) of severe loneliness. Conclusions and Relevance: In this study, the increased risk of having HRSNs associated with SPMI, alone or in combination with non-SPMI, emphasizes the need for more targeted interventions to address social needs in this vulnerable population.

Association Between Self-reported Health-Related Social Needs and Acute Care Utilization Among Older Adults Enrolled in Medicare Advantage.

Importance: There is increased focus on identifying and addressing health-related social needs (HRSNs). Understanding how different HRSNs relate to different health outcomes can inform targeted, evidence-based policies, investments, and innovations to address HRSNs. Objective: To examine the association between self-reported HRSNs and acute care utilization among older adults enrolled in Medicare Advantage. Design Setting and Participants: This cross-sectional study used data from a large, national survey of Medicare Advantage beneficiaries to identify the presence of HRSNs. Survey data were linked to medical claims, and regression models were used to estimate the association between HRSNs and rates of acute care utilization from January 1, 2019, through December 31, 2019. Exposures: Self-reported HRSNs, including food insecurity, financial strain, loneliness, unreliable transportation, utility insecurity, housing insecurity, and poor housing quality. Main Outcomes and Measures: All-cause hospital stays (inpatient admissions and observation stays), avoidable hospital stays, all-cause emergency department (ED) visits, avoidable ED visits, and 30-day readmissions. Results: Among a final study population of 56 155 Medicare Advantage beneficiaries (mean [SD] age, 74.0 [5.8] years; 32 779 [58.4%] women; 44 278 [78.8%] White; and 7634 [13.6%] dual eligible for Medicaid), 27 676 (49.3%) reported 1 or more HRSNs. Health-related social needs were associated with statistically significantly higher rates of all utilization measures, with the largest association observed for avoidable hospital stays (incident rate ratio for any HRSN, 1.53; 95% CI, 1.35-1.74; P < .001). Compared with beneficiaries without HRSNs, beneficiaries with an HRSN had a 53.3% higher rate of avoidable hospitalization (incident rate ratio, 1.53; 95% CI, 1.35-1.74; P < .001). Financial strain and unreliable transportation were each independently associated with increased rates of hospital stays (marginal effects of 26.5 [95% CI, 14.2-38.9] and 51.2 [95% CI, 30.7-71.8] hospital stays per 1000 beneficiaries, respectively). All HRSNs, except for utility insecurity, were independently associated with increased rates of ED visits. Unreliable transportation had the largest association with increased hospital stays and ED visits, with marginal effects of 51.2 (95% CI, 30.7-71.8) and 95.5 (95% CI, 65.3-125.8) ED visits per 1000 beneficiaries, respectively. Only unreliable transportation and financial strain were associated with increased rates of 30-day readmissions, with marginal effects of 3.3% (95% CI, 2.0%-4.0%) and 0.4% (95% CI, 0.2%-0.6%), respectively. Conclusions and Relevance: In this cross-sectional study of older adults enrolled in Medicare Advantage, self-reported HRSNs were common and associated with statistically significantly increased rates of acute care utilization, with variation in which HRSNs were associated with different utilization measures. These findings provide evidence of the unique association between certain HRSNs and different types of acute care utilization, which could help refine the development and targeting of efforts to address HRSNs.

Effect of interventions for non-emergent medical transportation: a systematic review and meta-analysis.

INTRODUCTION: Transportation is an important social determinant of health. We conducted a systematic review of the associations on health and health care utilization of interventions aimed at reducing barriers to non-emergency transportation and non-medical transportation. METHODS: We searched three databases and the gray literature through mid-January 2022. Included studies needed to assess an intervention targeted at non-emergency or non-medical transportation barriers, report missed (or kept) visits, health care utilization, costs, or health outcomes. Data extraction was performed in duplicate and included information about study design, results, and risk of bias. Primary outcomes were frequency of missed appointments, health care utilization, costs, and health outcomes. Synthesis was both narrative and meta-analytic using a random effects model. RESULTS: Twelve studies met inclusion criteria, three randomized trials, one controlled trial, and eight observational studies. All included studies had some element of risk of bias. Populations studied usually had chronic or serious health conditions or were poor. Interventions included van rides, bus or taxi vouchers, ride-sharing services, and others. Meta-analysis of seven studies (three trials, four observational studies) yielded a pooled estimate of missed appointments = 0.63 (95% confidence interval [CI] 0.48, 0.83) favoring interventions. Evidence on cost, utilization, and health outcomes were too sparse to support conclusions. Evidence on the effect of non-medical transportation is limited to a single study. CONCLUSIONS AND RELEVANCE: Interventions aimed at non-emergency transportation barriers to access health care are associated with fewer missed appointments; the association with costs, utilization or health outcomes is insufficiently studied to reach conclusions. This review was registered in PROSPERO as ID CRD42020201875.

Change in self-reported health: A signal for early intervention in a medicare population.

BACKGROUND: Health plans and risk-bearing provider organizations seek information sources to inform proactive interventions for patients at risk of adverse health events. Interventions should take into account the strong relationship between social context and health. This retrospective cohort study of a Medicare Advantage population examined whether a change in self-reported health-related quality of life (HRQOL) signals a subsequent change in healthcare needs. METHODS: A retrospective longitudinal analysis of administrative claims data was conducted for participants in a Medicare Advantage plan with prescription drug coverage (MAPD) who responded to 2 administrations of the Centers for Disease Control and Prevention 4-item Healthy Days survey within 6-18 months during 2015-2018. Changes in HRQOL, as measured by the Healthy Days instrument, were compared with changes in utilization and costs, which were considered to be a reflection of change in healthcare needs. RESULTS: A total of 48,841 individuals met inclusion criteria. Declining HRQOL was followed by increases in utilization and costs. An adjusted analysis showed that every additional unhealthy day reported one year after baseline was accompanied by an $8 increase in monthly healthcare costs in the subsequent six months for the average patient. CONCLUSIONS: Declining HRQOL signaled subsequent increases in healthcare needs and utilization. IMPLICATIONS: Findings suggest that HRQOL assessments in general, and the Healthy Days instrument in particular, could serve as a leading indicator of the need for interventions designed to mitigate poor health outcomes and rising healthcare costs. LEVEL OF EVIDENCE: III.

Identifying impacts of air pollution on subacute asthma symptoms using digital medication sensors.

BACKGROUND: Objective tracking of asthma medication use and exposure in real-time and space has not been feasible previously. Exposure assessments have typically been tied to residential locations, which ignore exposure within patterns of daily activities. METHODS: We investigated the associations of exposure to multiple air pollutants, derived from nearest air quality monitors, with space-time asthma rescue inhaler use captured by digital sensors, in Jefferson County, Kentucky. A generalized linear mixed model, capable of accounting for repeated measures, over-dispersion and excessive zeros, was used in our analysis. A secondary analysis was done through the random forest machine learning technique. RESULTS: The 1039 participants enrolled were 63.4% female, 77.3% adult (>18) and 46.8% White. Digital sensors monitored the time and location of over 286 980 asthma rescue medication uses and associated air pollution exposures over 193 697 patient-days, creating a rich spatiotemporal dataset of over 10 905 240 data elements. In the generalized linear mixed model, an interquartile range (IQR) increase in pollutant exposure was associated with a mean rescue medication use increase per person per day of 0.201 [95% confidence interval (CI): 0.189-0.214], 0.153 (95% CI: 0.136-0.171), 0.131 (95% CI: 0.115-0.147) and 0.113 (95% CI: 0.097-0.129), for sulphur dioxide (SO2), nitrogen dioxide (NO2), fine particulate matter (PM2.5) and ozone (O3), respectively. Similar effect sizes were identified with the random forest model. Time-lagged exposure effects of 0-3 days were observed. CONCLUSIONS: Daily exposure to multiple pollutants was associated with increases in daily asthma rescue medication use for same day and lagged exposures up to 3 days. Associations were consistent when evaluated with the random forest modelling approach.

Structural basis of RNA polymerase recycling by the Swi2/Snf2 family of ATPase RapA in Escherichia coli.

After transcription termination, cellular RNA polymerases (RNAPs) are occasionally trapped on DNA, impounded in an undefined post-termination complex (PTC), limiting the free RNAP pool and subsequently leading to inefficient transcription. In Escherichia coli, a Swi2/Snf2 family of ATPase called RapA is known to be involved in countering such inefficiency through RNAP recycling; however, the precise mechanism of this recycling is unclear. To better understand its mechanism, here we determined the structures of two sets of E. coli RapA-RNAP complexes, along with the RNAP core enzyme and the elongation complex, using cryo-EM. These structures revealed the large conformational changes of RNAP and RapA upon their association that has been implicated in the hindrance of PTC formation. Our results along with DNA-binding assays reveal that although RapA binds RNAP away from the DNA-binding main channel, its binding can allosterically close the RNAP clamp, thereby preventing its nonspecific DNA binding and PTC formation. Taken together, we propose that RapA acts as a guardian of RNAP by which RapA prevents nonspecific DNA binding of RNAP without affecting the binding of promoter DNA recognition σ factor, thereby enhancing RNAP recycling.

CsrA-Mediated Translational Activation of ymdA Expression in Escherichia coli.

The sequence-specific RNA-binding protein CsrA is the central component of the conserved global regulatory Csr system. In Escherichia coli, CsrA regulates many cellular processes, including biofilm formation, motility, carbon metabolism, iron homeostasis, and stress responses. Such regulation often involves translational repression by CsrA binding to an mRNA target, thereby inhibiting ribosome binding. While CsrA also extensively activates gene expression, no detailed mechanism for CsrA-mediated translational activation has been demonstrated. An integrated transcriptomic study identified ymdA as having the strongest CsrA-mediated activation across the E. coli transcriptome. Here, we determined that CsrA activates ymdA expression posttranscriptionally. Gel mobility shift, footprint, toeprint, and in vitro coupled transcription-translation assays identified two CsrA binding sites in the leader region of the ymdA transcript that are critical for translational activation. Reporter fusion assays confirmed that CsrA activates ymdA expression at the posttranscriptional level in vivo Furthermore, loss of binding at either of the two CsrA binding sites abolished CsrA-dependent activation. mRNA half-life studies revealed that CsrA also contributes to stabilization of ymdA mRNA. RNA structure prediction revealed an RNA hairpin upstream of the ymdA start codon that sequesters the Shine-Dalgarno (SD) sequence, which would inhibit ribosome binding. This hairpin also contains one of the two critical CsrA binding sites, with the other site located just upstream. Our results demonstrate that bound CsrA destabilizes the SD-sequestering hairpin such that the ribosome can bind and initiate translation. Since YmdA represses biofilm formation, CsrA-mediated activation of ymdA expression may repress biofilm formation under certain conditions.IMPORTANCE The Csr system of E. coli controls gene expression and physiology on a global scale. CsrA protein, the central component of this system, represses translation initiation of numerous genes by binding to target transcripts, thereby competing with ribosome binding. Variations of this mechanism are so common that CsrA is sometimes called a translational repressor. Although CsrA-mediated activation mechanisms have been elucidated in which bound CsrA inhibits RNA degradation, no translation activation mechanism has been defined. Here, we demonstrate that CsrA binding to two sites in the 5' untranslated leader of ymdA mRNA activates translation by destabilizing a structure that otherwise prevents ribosome binding. The extensive role of CsrA in activating gene expression suggests the common occurrence of similar activation mechanisms.

Claims identification of patients with severe cancer-related symptoms.

OBJECTIVES: The goal of this study was to establish a claims-based mechanism for identifying patients with metastatic non-small cell lung cancer (mNSCLC) and high levels of patient-reported cancer-related symptoms who could benefit from engagement with health care programs. STUDY DESIGN: A cross-sectional survey of patients with mNSCLC was conducted from July 2017 to May 2018. Surveys were mailed to patients who were within 3 months of cancer treatment and enrolled in a Medicare Advantage health plan. METHODS: Pain, fatigue, and sleep disturbance were measured using the Patient-Reported Outcomes Measurement Information System. Depression was assessed using the Patient Health Questionnaire-2. Medical claims were linked to survey results to identify comorbidities and assess preindex health care resource utilization. Cluster analysis was used to differentiate patients based on patient-reported pain interference, pain intensity, depression, and sleep disturbance. Logistic regression was used to identify claims-based measures associated with more severe symptoms. RESULTS: For 698 respondents, 2 distinct symptom clusters were identified: a less severe (38.4%) cluster and a more severe (61.6%) cluster. Patients in the more severe cluster were younger, were more frequently dually eligible for Medicare and Medicaid, and more frequently had prescription fills for opioids. Claims-based factors associated with the more severe cluster included 2 or more 30-day fills for opioids in the prior 6 months, age younger than 75 years, depression diagnosis or antidepressants, bone metastases, and pain-related outpatient visits. CONCLUSIONS: The claims-based factors associated with the severe symptom cluster can enable identification of patients with mNSCLC who could benefit from clinical outreach programs to enhance the care and support provided to these patients.

Initiation of triple therapy maintenance treatment among patients with COPD.

OBJECTIVES: Triple therapy is indicated for patients with very severe chronic obstructive pulmonary disease (COPD). Use of this treatment in the appropriate patient population is important to ensure optimal outcomes. This study quantified the use of triple therapy and assessed concordance with 2013-2016 Global Initiative for Chronic Obstructive Lung Disease (GOLD) recommendations within a national health plan. STUDY DESIGN: Retrospective cohort study using data from a large national health plan. METHODS: To estimate the prevalence of triple therapy using claims data, patients in the first of 2 cohorts were indexed on their first diagnosis of COPD between January 1, 2012, and December 31, 2014, and required to have 24 months postindex continuous enrollment. To assess concordance with GOLD recommendations, a second cohort was created and indexed on the date of triple therapy initiation between January 1, 2013, and November 30, 2016, and required to have 12 months preindex and 1 month postindex continuous enrollment. For both cohorts, patients were aged 40 years or older, with no International Classification of Diseases code for asthma, cystic fibrosis, or lung cancer during the study period. RESULTS: In the first cohort of 92,248 patients with COPD receiving any COPD maintenance medication, 17% were prescribed triple therapy. In the second cohort (n = 19,645), the majority (60%) of patients on triple therapy were classified as GOLD group A or B (ie, no evidence of any exacerbation or only 1 exacerbation not resulting in hospitalization at baseline). CONCLUSIONS: Results showed that triple therapy was often prescribed among patients classified as GOLD group A or B. Additional research is required, however, to further assess whether these patients may have had an exacerbation that was not evident in claims data. Treatment of COPD should be individualized to optimize outcomes and reduce adverse events.

Primary Care Provider Encounter Cadence and HbA1c Control in Older Patients With Diabetes.

INTRODUCTION: Primary care provider encounters are associated with health and well-being; however, limited evidence guides optimal primary care provider rate of visit, referred to as encounter cadence. This study measures associations between primary care provider encounter cadence and diabetes outcomes among individuals newly diagnosed with type 2 diabetes mellitus. METHODS: In this retrospective cohort study, 7,106 people enrolled in Medicare Advantage and newly diagnosed with type 2 diabetes mellitus between July 1, 2012 and June 30, 2013 were identified and followed for 36 months. Two methods measured primary care provider encounter cadence: total primary care provider encounters (frequency) and quarters with primary care provider encounter (regularity). Logistic regression measured relationships between primary care provider encounter cadence and non-insulin diabetes medication adherence, HbA1c control, emergency department visits, and inpatient admissions. Non-insulin diabetes medication adherence was defined according to the National Committee for Quality Assurance, Healthcare Effectiveness Data and Information Set specifications and measured using healthcare claims data. Post-hoc models examined adherence and diabetes control among those nonadherent (n=5,212) and with noncontrolled HbA1c (n=326) during the encounter/cadence period. Data were extracted and analyzed in 2017. RESULTS: Adjusted models indicated that both frequency (AOR=1.08, 95% CI=1.06, 1.10) and regularity (AOR=1.18, 95% CI=1.13, 1.22) of primary care provider encounters were associated with increased odds of adherence. Post-hoc analyses indicated that more frequent (AOR=1.12, 95% CI=1.10, 1.15) and regular (AOR=1.27, 95% CI=1.22, 1.33) primary care provider encounters were associated significantly with adherence and were associated directionally with HbA1c control. CONCLUSIONS: More frequent and regular primary care provider encounters are associated with an increased likelihood of non-insulin diabetes medication adherence. These findings contribute to data needed to establish evidence-based guidelines for primary care provider encounter cadence for those newly diagnosed with type 2 diabetes mellitus.

Charlson Comorbidity Index: ICD-9 Update and ICD-10 Translation.

BACKGROUND: The original Charlson Comorbidity Index (CCI) encompassed 19 categories of medical conditions that were identifiable in medical records. Subsequent publications provided scoring algorithms based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes. The recent adoption of International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes in the United States created a need for a new scoring scheme. In addition, a review of existing claims-based scoring systems suggested 3 areas for improvement: the lack of explicit identification of secondary diabetes, the lack of differentiation between HIV infection and AIDS, and insufficient guidance on scoring hierarchy. In addition, addressing the third need raised the issue of disease severity in renal disease. OBJECTIVES: This initiative aimed to create an expanded and refined ICD-9 scoring system for CCI, addressing the classification of issues noted above, create a corresponding ICD-10 system, assess the comparability of ICD-9- and ICD-10-based scores, and validate the new scoring scheme. METHODS: We created ICD-9 and ICD-10 code tables for 19 CCI medical conditions. The new scoring scheme was labeled CDMF CCI and was tested using claims-based data for individuals aged ≥65 years who participated in a Humana Medicare Advantage plan during at least 1 of 3 consecutive 12-month periods. Two 12-month periods were during the ICD-9 era and the third 12-month period was during the ICD-10 era. Because many individuals were counted in more than one 12-month period, we described the study population as comprising 3 panels. We used regression models to analyze the association between the CCI score and same-year inpatient admissions and near-term (90-day) mortality. Additional testing was done by comparing the mean CCI score or disease prevalence in the 3 subpopulations of people with HIV/AIDS, renal disease, or diabetes. Finally, we calculated area under the receiver operating characteristics (AUC-ROC) curve values by applying the Deyo system and our ICD-9 and ICD-10 scoring systems. RESULTS: The CDMF ICD-9 and ICD-10 scoring scheme yielded comparable scores across the 3 panels, and inpatient admissions and mortality rates consistently increased in each panel as the CCI score increased. Comparisons of the performance of the Deyo system and our proposed CDMF ICD-9 system in the 3 key subpopulations showed that the CDMF ICD-9 system produced a lower CCI score in the presence of HIV infection without AIDS, achieved similar detection ability of diabetes, and allowed good differentiation between mild-to-moderate and severe renal disease. AUC-ROC values were similar between the CDMF ICD-9 coding system and the Deyo system. CONCLUSION: Our results support the implementation of the CDMF CCI scoring instrument to triage individual patients for disease- and care-management programs. In addition, the CDMF scheme allows for a more precise understanding of chronic disease at a population level, thus allowing health systems and plans to design services and benefits to meet multifactorial clinical needs. Preliminary validation sets the stage for further testing using long-term follow-up data and for the adaptation of this coding scheme to a chart review instrument.

Using the Healthy Days Measure to Assess Factors Associated with Poor Health-Related Quality of Life for Patients with Metastatic Breast, Lung, or Colorectal Cancer Enrolled in a Medicare Advantage Health Plan.

This study investigated factors associated with patient-reported health-related quality of life (HRQoL) using the Centers for Disease Control and Prevention's Healthy Days tool for patients with Medicare Advantage undergoing treatment for metastatic breast, lung, and colorectal cancer. In 2015, a total of 6390 patients were mailed surveys regarding factors that may influence their HRQoL, including cancer-related symptoms. HRQoL was measured as the number of physically and mentally unhealthy days experienced in the past 30 days and summed for the total number of unhealthy days. Frequent unhealthy days was defined as ≥14 total unhealthy days in the prior month. Of 1567 respondents, the mean number of total unhealthy days (standard deviation) was 14.0 (11.9) with 46.2% experiencing frequent unhealthy days. On average, patients reported 10.5 (10.5) physically and 6.7 (9.4) mentally unhealthy days. Cancer-related symptoms, particularly pain and fatigue, were significantly associated with increased unhealthy days. In adjusted models, patients with pain had 83% more unhealthy days than patients without pain; patients with fatigue had 104% more unhealthy days than patients without fatigue. Diarrhea/constipation and shortness of breath also were associated with more unhealthy days. Cancer-related symptoms, most notably pain and fatigue, were associated with worse HRQoL for patients with metastatic cancer. Interventions aimed at ameliorating symptoms may improve quality of life for patients undergoing cancer treatment.

Posttranscription Initiation Control of Gene Expression Mediated by Bacterial RNA-Binding Proteins.

RNA-binding proteins play vital roles in regulating gene expression and cellular physiology in all organisms. Bacterial RNA-binding proteins can regulate transcription termination via attenuation or antitermination mechanisms, while others can repress or activate translation initiation by affecting ribosome binding. The RNA targets for these proteins include short repeated sequences, longer single-stranded sequences, RNA secondary or tertiary structure, and a combination of these features. The activity of these proteins can be influenced by binding of metabolites, small RNAs, or other proteins, as well as by phosphorylation events. Some of these proteins regulate specific genes, while others function as global regulators. As the regulatory mechanisms, components, targets, and signaling circuitry surrounding RNA-binding proteins have become better understood, in part through rapid advances provided by systems approaches, a sense of the true nature of biological complexity is becoming apparent, which we attempt to capture for the reader of this review.

Spirometry evaluation to assess performance of a claims-based predictive model identifying patients with undiagnosed COPD.

BACKGROUND: A claims-based model to predict patients likely to have undiagnosed COPD was developed by Moretz et al in 2015. This study aims to assess the performance of the aforementioned model using prospectively collected spirometry data. METHODS: A study population aged 40-89 years enrolled in a Medicare Advantage plan with prescription drug coverage or commercial health plan and without a claim for COPD diagnosis was identified from April 1, 2012 to March 31, 2016 in the Humana claims database. This population was stratified into subjects likely or unlikely to have undiagnosed COPD using the claims-based predictive model. Subjects were randomly selected for spirometry evaluation of FEV1 and FVC. The predictive model was validated using airflow limitation ratio (FEV1/FVC <0.70). RESULTS: A total of 218 subjects classified by the predictive model as likely and 331 not likely to have undiagnosed COPD completed spirometry evaluation. Those predicted to have undiagnosed COPD had a higher mean age (70.2 vs 67.9 years, P=0.0012) and a lower mean FEV1/FVC ratio (0.724 vs 0.753, P=0.0002) compared to those predicted not to have undiagnosed COPD. Performance metrics for the predictive model were: area under the curve =0.61, sensitivity =52.5%, specificity =64.6%, positive predictive value =33.5%, and negative predictive value =80.1%. CONCLUSION: The claims-based predictive model identifies those not at risk of having COPD eight out of ten times, and those who are likely to have COPD one out of three times.

In vivo RNA structural probing of uracil and guanine base-pairing by 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC).

Many biological functions performed by RNAs arise from their in vivo structures. The structure of the same RNA can differ in vitro and in vivo owing in part to the influence of molecules ranging from protons to secondary metabolites to proteins. Chemical reagents that modify the Watson-Crick (WC) face of unprotected RNA bases report on the absence of base-pairing and so are of value to determining structures adopted by RNAs. Reagents have thus been sought that can report on the native RNA structures that prevail in living cells. Dimethyl sulfate (DMS) and glyoxal penetrate cell membranes and inform on RNA secondary structure in vivo through modification of adenine (A), cytosine (C), and guanine (G) bases. Uracil (U) bases, however, have thus far eluded characterization in vivo. Herein, we show that the water-soluble carbodiimide 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC) is capable of modifying the WC face of U and G in vivo, favoring the former nucleobase by a factor of ∼1.5, and doing so in the eukaryote rice, as well as in the Gram-negative bacterium Escherichia coli While both EDC and glyoxal target Gs, EDC reacts with Gs in their typical neutral state, while glyoxal requires Gs to populate the rare anionic state. EDC may thus be more generally useful; however, comparison of the reactivity of EDC and glyoxal may allow the identification of Gs with perturbed pKas in vivo and genome-wide. Overall, use of EDC with DMS allows in vivo probing of the base-pairing status of all four RNA bases.

Examining Changes in Healthy Days After Health Coaching.

PURPOSE: To describe changes in health-related quality of life (HRQOL) related to variation in demographic characteristics, program goals, and program participation, among health coaching program participants. DESIGN: A retrospective observational study of a health coaching program. SETTING AND PARTICIPANTS: A total of 2169 adults enrolled in an individually purchased or employer-sponsored health plan from a large health and well-being company, who participated in a health coaching program between January 2016 and April 2017. INTERVENTION: The health coaching program used evidence-based behavior change strategies to encourage skill development, self-monitoring, and goal setting/achievement. Health coaching program modalities included online and telephonic coaching sessions. MEASURES: Demographic characteristics (gender, age, race, income), goal categories (weight management, fitness, nutrition, stress management, other), program modality (online, telephonic, both), engagement level (low, medium, high), and Healthy Days, a validated HRQOL measure developed by the Centers for Disease Control and Prevention. ANALYSIS: t Tests, mixed analysis of variance (ANOVA). RESULTS: There were significant ( P < .05) reductions in average total unhealthy days (UHDs) across all goal categories. Mixed ANOVAs identified a significant main effect for time, for all demographic characteristics ( P values < .05), and a significant effect for program modality ( P < .0001), time ( P < .0001), and interaction effects, between program modality and time, on average UHD ( P = .01). CONCLUSION: Our findings indicate significant reductions in UHD, following 6 months of health coaching, and support the use of HRQOL measures, which are known to be highly correlated with traditional measures of health, to evaluate health coaching programs.

Retracted: Using the Healthy Days Measure to Assess Factors Associated with Poor Health-Related Quality of Life for Patients with Metastatic Breast, Lung, or Colorectal Cancer Enrolled in a Medicare Advantage Health Plan.

The article entitled, "Using the Healthy Days Measure to Assess Factors Associated with Poor Health-Related Quality of Life for Patients with Metastatic Breast, Lung, or Colorectal Cancer Enrolled in a Medicare Advantage Health Plan," by Casebeer AW et al, which published online ahead of print in Population Health Management [doi: 10.1089/pop.2018.0024], is being retracted by the authors so that they can remove references to the 8-item Morisky Medication Adherence Scale (MMAS-8) and republish the article without such references. Dr. Casebeer's team obtained a license to use the MMAS-8 scale from Dr. Morisky prior to conducting the study. Nevertheless, after publication of a separate article in the Journal of Patient-Reported Outcomes that also cited the MMAS-8, as the lead author, Dr. Casebeer was contacted by Dr. Morisky who requested that a number of changes be made to the article. Dr. Casebeer and her team have no desire to engage in a dispute with Dr. Morisky and therefore proactively contacted the Editor of Population Health Management and requested that the scale be removed from her published paper. After assessing all of the provided information, the Editor agreed to the authors' request. It is important to note that the retraction of Dr. Casebeer's article is not the result of any misconduct on her part or that of her team. The retraction serves to remove the published version of the article that contains the MMAS-8 scale and a revised version that does not contain the tool or any references to it will be published. The elimination of the scale does not alter the results or conclusions of the study. Population Health Management is committed to upholding the highest standards of peer review and the community it serves.

The relationship between comorbidity medication adherence and health related quality of life among patients with cancer.

BACKGROUND: Studies have demonstrated that comorbidities compound the adverse influence of cancer on health-related quality of life (HRQoL). Comorbidities adversely impact adherence to cancer treatment. Additionally, adherence to medications for comorbidities is positively associated with HRQoL for various diseases. This study used the Center for Disease Control and Prevention's Healthy Days measure of HRQoL to explore the association between HRQoL and adherence to comorbidity medication for elderly patients with cancer and at least one comorbid condition. METHODS: We conducted a cross-sectional survey combined with retrospective claims data. Patients with metastatic breast, lung or colorectal cancer were surveyed regarding their HRQoL, comorbidity medication adherence and cancer-related symptoms. Patients reported the number of physical, mental and total unhealthy days in the prior month. The Morisky Medication Adherence 8-point scale was differentiated into moderate/high (> 6) and low (≤ 6) comorbidity medication adherence. RESULTS: Of the 1847 respondents, the mean age was 69.2 years, most were female (66.8%) and the majority of the sample had Medicare coverage (88.2%). Low comorbidity medication adherence was associated with significantly more total, mental and physical unhealthy days. Low comorbidity medication adherence was associated with the presence of patient-reported cancer-related symptoms. Patients reporting low, as compared to moderate/high, comorbidity medication adherence had 23.4% more unhealthy days in adjusted analysis, P = 0.007. CONCLUSION: The positive association between low comorbidity medication adherence and the number of unhealthy days suggests that addressing barriers to comorbidity medication adherence during cancer treatment may be an avenue for improving or maintaining HRQoL for older patients with cancer and comorbid conditions.