Associations between Missed Colonoscopy Appointments and Multiple Prior Adherence Behaviors in an Integrated Healthcare System: An Observational Study.

BACKGROUND: Missed colonoscopy appointments delay screening and treatment for gastrointestinal disorders. Prior nonadherence with other care components may be associated with missed colonoscopy appointments. OBJECTIVE: To assess variability in prior adherence behaviors and their association with missed colonoscopy appointments. DESIGN: Retrospective cohort study. PARTICIPANTS: Patients scheduled for colonoscopy in an integrated healthcare system between January 2016 and December 2018. MAIN MEASURES: Prior adherence behaviors included: any missed outpatient appointment in the previous year; any missed gastroenterology clinic or colonoscopy appointment in the previous 2 years; and not obtaining a bowel preparation kit pre-colonoscopy. Other sociodemographic, clinical, and system characteristics were included in a multivariable model to identify independent associations between prior adherence behaviors and missed colonoscopy appointments. KEY RESULTS: The median age of the 57,590 participants was 61 years; 52.8% were female and 73.4% were white. Of 77,684 colonoscopy appointments, 3,237 (4.2%) were missed. Individuals who missed colonoscopy appointments were more likely to have missed a previous primary care appointment (62.5% vs. 38.4%), a prior gastroenterology appointment (18.4% vs. 4.7%) or not to have picked up a bowel preparation kit (42.4% vs. 17.2%), all p < 0.001. Correlations between the three adherence measures were weak (phi < 0.26). The rate of missed colonoscopy appointments increased from 1.8/100 among individuals who were adherent with all three prior care components to 24.6/100 among those who were nonadherent with all three care components. All adherence variables remained independently associated with nonadherence with colonoscopy in a multivariable model that included other covariates; adjusted odds ratios (with 95% confidence intervals) were 1.6 (1.5-1.8) for outpatient appointments, 1.9 (1.7-2.1) for gastroenterology appointments, and 3.1 (2.9-3.4) for adherence with bowel preparation kits, respectively. CONCLUSIONS: Three prior adherence behaviors were independently associated with missed colonoscopy appointments. Studies to predict adherence should use multiple, complementary measures of prior adherence when available.

Ethical Aspects of Physician Decision-Making for Deprescribing Among Older Adults With Dementia.

Importance: Physicians endorse deprescribing of risky or unnecessary medications for older adults (aged ≥65 years) with dementia, but there is a lack of information on what influences decisions to deprescribe in this population. Objective: To understand how physicians make decisions to deprescribe for older adults with moderate dementia and ethical and pragmatic concerns influencing those decisions. Design, Setting, and Participants: A cross-sectional national mailed survey study of a random sample of 3000 primary care physicians from the American Medical Association Physician Masterfile who care for older adults was conducted from January 15 to December 31, 2021. Main Outcomes and Measures: The study randomized participants to consider 2 clinical scenarios in which a physician may decide to deprescribe a medication for older adults with moderate dementia: 1 in which the medication could cause an adverse drug event if continued and the other in which there is no evidence of benefit. Participants ranked 9 factors related to possible ethical and pragmatic concerns through best-worst scaling methods (from greatest barrier to smallest barrier to deprescribing). Conditional logit regression quantified the relative importance for each factor as a barrier to deprescribing. Results: A total of 890 physicians (35.0%) returned surveys; 511 (57.4%) were male, and the mean (SD) years since graduation was 26.0 (11.7). Most physicians had a primary specialty in family practice (50.4% [449 of 890]) and internal medicine (43.5% [387 of 890]). A total of 689 surveys were sufficiently complete to analyze. In both clinical scenarios, the 2 greatest barriers to deprescribing were (1) the patient or family reporting symptomatic benefit from the medication (beneficence and autonomy) and (2) the medication having been prescribed by another physician (autonomy and nonmaleficence). The least influential factor was ease of paying for the medication (justice). Conclusions and Relevance: Findings from this national survey study of primary care physicians suggests that understanding ethical aspects of physician decision-making can inform clinician education about medication management and deprescribing decisions for older adults with moderate dementia.

Telemedicine-based inspiratory muscle training and walking promotion with lung cancer survivors following curative intent therapy: a parallel-group pilot randomized trial.

PURPOSE: Following curative-intent therapy of lung cancer, many survivors experience dyspnea and physical inactivity. We investigated the feasibility, acceptability, safety, and potential efficacy of inspiratory muscle training (IMT) and walking promotion to disrupt a postulated "dyspnea-inactivity" spiral. METHODS: Between January and December 2022, we recruited lung cancer survivors from Kaiser Permanente Colorado who completed curative-intent therapy within 1-6 months into a phase-IIb, parallel-group, pilot randomized trial (1:1 allocation). The 12-week intervention, delivered via telemedicine, consisted of exercise training (IMT + walking), education, and behavior change support. Control participants received educational materials on general exercise. We determined feasibility a priori: enrollment of ≥ 20% eligible patients, ≥ 75% retention, study measure completion, and adherence. We assessed acceptability using the Telemedicine-Satisfaction-and-Usefulness-Questionnaire and safety events that included emergency department visits or hospitalizations. Patient-centered outcome measures (PCOMs) included dyspnea (University-of-California-San-Diego-Shortness-of-Breath-Questionnaire), physical activity (activPAL™ steps/day), functional exercise capacity (mobile-based-six-minute-walk-test), and health-related quality of life (HRQL, St.-George's-Respiratory-Questionnaire). We used linear mixed-effects models to assess potential efficacy. RESULTS: We screened 751 patients, identified 124 eligible, and consented 31 (25%) participants. Among 28 participants randomized (14/group), 22 (11/group) completed the study (79% retention). Intervention participants returned > 90% of self-reported activity logs, completed > 90% of PCOMs, and attended > 90% of tele-visits; 75% of participants performed IMT at the recommended dose. Participants had high satisfaction with tele-visits and found the intervention useful. There was no statistically significant difference in safety events between groups. Compared to control participants from baseline to follow-up, intervention participants had statistically significant and clinically meaningful improved HRQL (SGRQ total, symptom, and impact scores) (standardized effect size: -1.03 to -1.30). CONCLUSIONS: Among lung cancer survivors following curative-intent therapy, telemedicine-based IMT + walking was feasible, acceptable, safe, and had potential to disrupt the "dyspnea-inactivity" spiral. Future efficacy/effectiveness trials are warranted and should incorporate IMT and walking promotion to improve HRQL. TRIAL REGISTRATION: ClinicalTrials.gov NCT05059132.

Update of a Multivariable Opioid Overdose Risk Prediction Model to Enhance Clinical Care for Long-term Opioid Therapy Patients.

BACKGROUND: Clinical opioid overdose risk prediction models can be useful tools to reduce the risk of overdose in patients prescribed long-term opioid therapy (LTOT). However, evolving overdose risk environments and clinical practices in addition to potential harmful model misapplications require careful assessment prior to widespread implementation into clinical care. Models may need to be tailored to meet local clinical operational needs and intended applications in practice. OBJECTIVE: To update and validate an existing opioid overdose risk model, the Kaiser Permanente Colorado Opioid Overdose (KPCOOR) Model, in patients prescribed LTOT for implementation in clinical care. DESIGN, SETTING, AND PARTICIPANTS: The retrospective cohort study consisted of 33, 625 patients prescribed LTOT between January 2015 and June 2019 at Kaiser Permanente Colorado, with follow-up through June 2021. MAIN MEASURES: The outcome consisted of fatal opioid overdoses identified from vital records and non-fatal opioid overdoses from emergency department and inpatient settings. Predictors included demographics, medication dispensings, substance use disorder history, mental health history, and medical diagnoses. Cox proportional hazards regressions were used to model 2-year overdose risk. KEY RESULTS: During follow-up, 65 incident opioid overdoses were observed (111.4 overdoses per 100,000 person-years) in the study cohort, of which 11 were fatal. The optimal risk model needed to risk-stratify patients and to be easily interpreted by clinicians. The original 5-variable model re-validated on the new study cohort had a bootstrap-corrected C-statistic of 0.73 (95% CI, 0.64-0.85) compared to a C-statistic of 0.80 (95% CI, 0.70-0.88) in the updated model and 0.77 (95% CI, 0.66-0.87) in the final adapted 7-variable model, which was also well-calibrated. CONCLUSIONS: Updating and adapting predictors for opioid overdose in the KPCOOR Model with input from clinical partners resulted in a parsimonious and clinically relevant model that was poised for integration in clinical care.

Association between changes in loneliness identified through screening and changes in depression or anxiety in older adults.

BACKGROUND: Changes in loneliness are associated with corresponding changes in depression, anxiety, and general health in population surveys, but few studies have assessed these associations through repeated screening in clinical settings. METHODS: Retrospective cohort study among individuals ≥age 65 in an integrated health care system who completed loneliness screening before two annual wellness visits, separated by a mean of 12.9 (SD 2.0) months, between 2013 and 2018. Their responses identified four subgroups: individuals who were persistently lonely; not lonely; experienced an increase (recently lonely); or decrease (previously lonely) in loneliness. Loneliness was assessed with a single item. Depression was assessed with the Patient Health Questionnaire-2. Anxiety was assessed with the Generalized Anxiety Disorder-2. Fair/poor general health was assessed by a single item. Linear mixed effects models assessed changes in outcomes after covariate adjustment. RESULTS: The cohort comprised 24,666 individuals (19.2% of older adults in the system). Mean age was 73.7 years (SD 6.4); 54.6% were female, and 11.6% were members of racial and ethnic minority groups. Of these individuals, 1936 (7.8%) were persistently lonely, 1687 (6.8%) were recently lonely, 1551 (6.3%) were previously lonely, and 19,492 (79.0%) were not lonely at either time point. After adjustment for sociodemographic, clinical and social variables, recent loneliness was associated with increases in depression (adjusted odds ratio [aOR] 1.76, 95% confidence interval [CI] 1.41-2.19) and anxiety (aOR 1.67, 95% CI 1.32-2.10). Previous loneliness was associated with decreases in depression (aOR, 0.46, 95% CI 0.36-0.58) and anxiety (aOR 0.69, 95% CI 0.54-0.90). Changes in loneliness were not associated with changes in general health. CONCLUSIONS: Changes in loneliness identified through screening were associated with corresponding changes in depression and anxiety. These findings support the potential value of identifying social risk factors in clinical settings among older adults.

Pre-Operative Predictors for Discharge to Post-Acute Care Facilities After Total Knee Arthroplasty.

BACKGROUND: Joint replacement surgery is in increasing demand and is the most common inpatient surgery for Medicare beneficiaries. The venue for post-operative rehabilitation, including early outpatient therapy after surgery, influences recovery and quality of life. As part of a comprehensive total joint program at Kaiser Permanente Colorado, we developed and validated a predictive model to anticipate and plan the disposition for rehabilitation of our patients after total knee arthroplasty (TKA). METHODS: We analyzed data for TKA patients who completed a pre-operative Total Knee Risk Assessment in 2017 (the model development cohort) or during the first 6 months of 2018 (the model validation cohort). The Total Knee Risk Assessment, which is used to guide disposition for rehabilitation, included questions in mobility, social, and environment domains. Multivariable logistic regression was used to predict discharge to post-acute care facilities (PACFs) (ie, skilled nursing facilities or acute rehabilitation centers). RESULTS: Data for a total of 1481 and 631 patients who underwent TKA were analyzed in the development and validation cohorts, respectively. Ninety-three patients (6.3%) in the development cohort and 22 patients (3.5%) in the validation cohort were discharged to PACFs. Eight risk factors for discharge to PACFs were included in the final multivariable model. Patients with a diagnosis of neurological disorder and with a mobility/balance issue had the greatest chance of discharge to PACFs. CONCLUSION: This validated predictive model for discharge disposition following TKA may be used as a tool in shared decision-making and discharge planning for patients undergoing TKA.

VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images.

Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit clinical decision support systems for diagnosis, surgery planning, and population-based analysis of spine and bone health. However, designing automated algorithms for spine processing is challenging predominantly due to considerable variations in anatomy and acquisition protocols and due to a severe shortage of publicly available data. Addressing these limitations, the Large Scale Vertebrae Segmentation Challenge (VerSe) was organised in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) in 2019 and 2020, with a call for algorithms tackling the labelling and segmentation of vertebrae. Two datasets containing a total of 374 multi-detector CT scans from 355 patients were prepared and 4505 vertebrae have individually been annotated at voxel level by a human-machine hybrid algorithm (https://osf.io/nqjyw/, https://osf.io/t98fz/). A total of 25 algorithms were benchmarked on these datasets. In this work, we present the results of this evaluation and further investigate the performance variation at the vertebra level, scan level, and different fields of view. We also evaluate the generalisability of the approaches to an implicit domain shift in data by evaluating the top-performing algorithms of one challenge iteration on data from the other iteration. The principal takeaway from VerSe: the performance of an algorithm in labelling and segmenting a spine scan hinges on its ability to correctly identify vertebrae in cases of rare anatomical variations. The VerSe content and code can be accessed at: https://github.com/anjany/verse.

Factors Associated With Opting Out of Automated Text and Telephone Messages Among Adult Members of an Integrated Health Care System.

Importance: Health care systems deliver automated text or telephone messages to remind patients of appointments and to provide health information. Patients who receive multiple messages may demonstrate message fatigue by opting out of future messages. Objective: To assess whether the volume of automated text or interactive voice response (IVR) telephone messages is associated with the likelihood of patients requesting to opt out of future messages. Design, Setting, and Participants: This retrospective cohort study was conducted at Kaiser Permanente Colorado (KPCO), an integrated health care system. All adult members who received 1 or more automated text or IVR message between October 1, 2018, and September 30, 2019, were included. Exposures: Receipt of automated text or IVR messages. Main Outcomes and Measures: Message volume and opt-out rates obtained from messaging systems over 1 year. Results: Of the 428 242 adults included in this study, 59.7% were women, and 66.5% were White; the mean (SD) age was 52.3 (17.7) years. During the study period, 84.1% received 1 or more text messages (median, 4 messages; interquartile range, 2-8 messages) and 67.8% received 1 or more IVR messages (median, 3 messages; interquartile range, 1-6 messages). A total of 8929 individuals (2.5%) opted out of text messages, and 4392 (1.5%) opted out of IVR messages. In multivariable analyses, individuals who received 10 to 19.9 or 20 or more text messages per year had higher opt-out rates for text messages compared with those who received fewer than 2 messages per year (adjusted odds ratio [aOR]: 10-19.9 vs <2 messages, 1.27 [95% CI, 1.17-1.38]; ≥20 vs <2 messages, 3.58 [95% CI, 3.28-3.91]), whereas opt-out rates increased progressively in association with IVR message volume, with the highest rates among individuals who received 10.0 to 19.9 messages (aOR, 11.11; 95% CI, 9.43-13.08) or 20.0 messages or more (aOR, 49.84; 95% CI, 42.33-58.70). Individuals opting out of text messages were more likely to opt out of IVR messages (aOR, 4.07; 95% CI, 3.65-4.55), and those opting out of IVR messages were more likely to opt out of text messages (aOR, 5.92; 95% CI, 5.29-6.61). Conclusions and Relevance: In this cohort study among adult members of an integrated health care system, requests to discontinue messages were associated with greater message volume. These findings suggest that, to preserve the benefits of automated outreach, health care systems should use these messages judiciously to reduce message fatigue.

Application of Fourier transform near-infrared spectroscopy combined with GC in rapid and simultaneous determination of essential components in Amomum villosum.

A method is described using rapid and sensitive Fourier transform near-infrared spectroscopy combined with Gas Chromatograpy internal standard method detection for the simultaneous identification and determination of three bioactive compounds in Amomum villosum samples. Partial least squares regression is selected as the analysis type and multiplicative scatter correction, second derivative, and SNV were adopted for the spectral pretreatment. The correlation coefficients (R) of the calibration models were above 0.95 and the root mean square error of predictions were under 0.8. The developed models were applied to unknown samples with satisfantory results. The established method was validated and can be applied to the intrinsic quality control of Amomum villosum.

Association of Exercise Behavior with Overall Survival in Stage I-IIIA Lung Cancer.

Rationale: Exercise assessments may help predict outcomes for patients with diagnosed lung cancer. Objectives: We examined the relationship between prediagnosis exercise behavior and clinical outcomes among patients with stage I-IIIA lung cancer. Methods: In a retrospective cohort study of patients with stage I-IIIA lung cancer at Kaiser Permanente Colorado who had at least one Exercise Vital Sign assessment-a questionnaire tool to help promote exercise in chronic disease management-within the year before diagnosis, we defined exercise behavior as active (any min/wk of moderate-to-vigorous-intensity physical activity) or inactive (no moderate-to-vigorous physical activity). The outcomes were 1) overall survival (OS) and 2) acute healthcare use (AHCU). We used the Kaplan-Meier method, Cox proportional hazard model, and negative binomial regression model to analyze the effects of exercise on outcomes, adjusting for demographic, socioeconomic, clinical, and lung-cancer characteristics. Results: Among 552 patients with lung cancer, 230 (42%) were identified as physically active before their diagnosis of cancer. There was no significant difference in the stage distribution between active and inactive patients. The median survival times were 2.4 years for the active group and 1.8 years for inactive patients (P < 0.001). The mean rates (standard deviations) of AHCU were 1.09 (1.55) and 2.31 (5.61) per person-year for active and inactive groups, respectively (P < 0.01). Active exercise, compared with inactivity, was associated with better OS (hazard ratio, 0.52 [0.39-0.69]) and lower AHCU (rate ratio, 0.63 [0.49-0.80]) in unadjusted analyses; in adjusted analyses, active exercise was associated with better OS (hazard ratio, 0.62 [0.45-0.86]), but AHCU was not lower by a statistically significant amount (rate ratio, 0.82 [0.65-1.04]). Conclusions: Prediagnosis active exercise was associated with better OS after diagnosis of stage I-IIIA lung cancer. Exercise assessments may help predict outcomes, risk-stratify patients for curative-intent therapy, and identify those who would benefit from increased physical activity and exercise.

Enhancing effect of macroporous adsorption resin on gamma-aminobutyric acid production by Enterococcus faecium in whole-cell biotransformation system.

Gamma-aminobutyric acid (GABA) biosynthesis depended to a great extent on the biotransformation characterization of glutamate decarboxylase (GAD) and process conditions. In this paper, the enhancing effect of D101 macroporous adsorption resin (MAR) on the GABA production was investigated based on the whole-cell biotransformation characterization of Enterococcus faecium and adsorption characteristics of D101 MAR. The results indicated that the optimal pH for reaction activity of whole-cell GAD and pure GAD was 4.4 and 5.0, respectively, and the pH range retained at least 50% of GAD activity was from 4.8 to 5.6 and 4.0-4.8, respectively. No substrate inhibition effect was observed on both pure GAD and whole-cell GAD, and the maximum activity could be obtained when the initial L-glutamic acid (L-Glu) concentration exceeded 57.6 mmol/L and 96.0 mmol/L, respectively. Besides, GABA could significantly inhibit the activity of whole-cell GAD rather than pure GAD. When the initial GABA concentration of the reaction solution remained 100 mmol/L, 33.51 ± 9.11% of the whole-cell GAD activity was inhibited. D101 MAR exhibited excellent properties in stabilizing the pH of the conversion reaction system, supplementing free L-Glu and removing excess GABA. Comparison of the biotransformation only in acetate buffer, the GABA production, with 50 g/100 mL of D101 MAR, was significantly increased by 138.71 ± 5.73%. D101 MAR with pre-adsorbed L-Glu could significantly enhance the production of GABA by gradual replenishment of free L-Glu, removing GABA and maintaining the pH of the reaction system, which would eventually make the GABA production more economical and eco-friendly.

Development and Validation of a Model for Predicting Rehabilitation Care Location Among Patients Discharged Home After Total Knee Arthroplasty.

BACKGROUND: Demand for joint replacement is increasing, with many patients receiving postsurgical physical therapy (PT) in non-inpatient settings. Clinicians need a reliable tool to guide decisions about the appropriate PT setting for patients discharged home after surgery. We developed and validated a model to predict PT location for patients in our health system discharged home after total knee arthroplasty. METHODS: We analyzed data for patients who completed a preoperative total knee risk assessment in 2017 (model development cohort) or during the first 6 months of 2018 (model validation cohort). The initial total knee risk assessment, to guide rehabilitation disposition, included 28 variables in mobility, social, and environment domains, and on patient demographics and comorbidities. Multivariable logistic regression was used to identify factors that best predict discharge to home health service (HHS) vs home with outpatient PT. Model performance was assessed by standard criteria. RESULTS: The development cohort included 259 patients (19%) discharged to HHS and 1129 patients (81%) discharged to home with outpatient PT. The validation cohort included 609 patients, with 91 (15%) discharged to HHS. The final model included age, gender, motivation for outpatient PT, and reliable transportation. Patients without motivation for outpatient PT had the highest probability of discharge to HHS, followed by those without reliable transportation. Model performance was excellent in the development and validation cohort, with c-statistics of 0.91 and 0.86, respectively. CONCLUSION: We developed and validated a predictive model for total knee arthroplasty PT discharge location. This model includes 4 variables with accurate prediction to guide patient-clinician preoperative decision making.

Using Self-Reported Data to Segment Older Adult Populations with Complex Care Needs.

BACKGROUND: Tailored care management requires effectively segmenting heterogeneous populations into actionable subgroups. Using patient reported data may help identify groups with care needs not revealed in traditional clinical data. METHODS: We conducted retrospective segmentation analyses of 9,617 Kaiser Permanente Colorado members age 65 or older at risk for high utilization due to advanced illness and geriatric issues who had completed a Medicare Health Risk Assessment (HRA) between 2014 and 2017. We separately applied clustering methods and latent class analyses (LCA) to HRA variables to identify groups of individuals with actionable profiles that may inform care management. HRA variables reflected self-reported quality of life, mood, activities of daily living (ADL), urinary incontinence, falls, living situation, isolation, financial constraints, and advance directives. We described groups by demographic, utilization, and clinical characteristics. RESULTS: Cluster analyses produced a 14-cluster solution and LCA produced an 8-class solution reflecting groups with identifiable care needs. Example groups included: frail individuals with memory impairment less likely to live independently, those with poor physical and mental well-being and ADL limitations, those with ADL limitations but good mental and physical well-being, and those with few health or other limitations differentiated by age, presence or absence of a documented advance directive, and tobacco use. CONCLUSIONS: Segmenting populations with complex care needs into meaningful subgroups can inform tailored care management. We found groups produced through cluster methods to be more intuitive, but both methods produced actionable information. Applying these methods to patient-reported data may make care more efficient and patient-centered.

The longitudinal relationship between food insecurity in older adults with diabetes and emergency department visits, hospitalizations, hemoglobin A1c, and medication adherence.

AIMS: To examine the relationship between food insecurity and emergency department (ED) visits, hospitalizations, A1c, and diabetes medication adherence over one year of follow-up among individuals >65 years with diabetes mellitus. METHODS: We conducted a longitudinal cohort study of adults >65 years with diabetes who did (n = 742) or did not (n = 2226) report food insecurity at baseline. We used conditional logistic regression for the ED visits or hospitalization outcomes, and mixed effects models for A1c and non-insulin diabetes medication adherence. RESULTS: In bivariate analyses, individuals with food insecurity were more likely to have an ED visit (OR = 1.40, 95% CI 1.15-1.72) or hospitalization (OR = 1.41, 95% CI 1.11-1.78) in the year after the food security assessment. In addition, A1c was higher (7.5% vs. 7.2%, p < 0.001). There was no difference in medication adherence. These differences persisted with adjustment for basic demographic and clinical characteristics, but were attenuated with further adjustment for socioeconomic status. CONCLUSIONS: Differences in diabetes outcomes by food insecurity status were attenuated by adjustment for socioeconomic status. Adverse outcomes in individuals with diabetes and food insecurity may be driven by effects of food insecurity per se or be mediated by a constellation of basic resource needs or lower socioeconomic status.

Food Insecurity in Older Adults in an Integrated Health Care System.

OBJECTIVES: To estimate food insecurity prevalence and develop a statistical prediction model for food insecurity. DESIGN: Retrospective cohort study. SETTING: Kaiser Permanente Colorado. PARTICIPANTS: Adult members who completed a pre-Medicare Annual Wellness Visit survey. MEASUREMENTS: Food insecurity was assessed using a single screening question. Sociodemographic and clinical characteristics from electronic health records and self-reported characteristics from the survey were used to develop the prediction model. RESULTS: Of 130,208 older adult members between January 2012 and December 2015, 50,097 (38.5%) completed food insecurity screening, 2,859 of whom (5.7% of respondents) reported food insecurity. The prevalence of food insecurity was 10.0% or greater among individuals who were black or Hispanic, had less than high school education, had Medicaid insurance, were extremely obese, had poor health status or quality of life, had depression or anxiety, had impairments in specific activities of daily living, had other nutritional risk factors, or were socially isolated (all p<.001). A multivariable model based on these and other characteristics showed moderate discrimination (c-statistic = 0.74) between individuals with food insecurity and those without and 14.3% of individuals in the highest quintile of risk reported food insecurity. CONCLUSION: Food insecurity is prevalent even in older adults with private-sector healthcare coverage. Specific individual characteristics, and a model based on those characteristics, can identify older adults at higher risk of food insecurity. System-level interventions will be necessary to connect older adults with community-based food resources.

Comparison of Inappropriate Shocks and Other Health Outcomes Between Single- and Dual-Chamber Implantable Cardioverter-Defibrillators for Primary Prevention of Sudden Cardiac Death: Results From the Cardiovascular Research Network Longitudinal Study of Implantable Cardioverter-Defibrillators.

BACKGROUND: In US clinical practice, many patients who undergo placement of an implantable cardioverter-defibrillator (ICD) for primary prevention of sudden cardiac death receive dual-chamber devices. The superiority of dual-chamber over single-chamber devices in reducing the risk of inappropriate ICD shocks in clinical practice has not been established. The objective of this study was to compare risk of adverse outcomes, including inappropriate shocks, between single- and dual-chamber ICDs for primary prevention. METHODS AND RESULTS: We identified patients receiving a single- or dual-chamber ICD for primary prevention who did not have an indication for pacing from 15 hospitals within 7 integrated health delivery systems in the Longitudinal Study of Implantable Cardioverter-Defibrillators from 2006 to 2009. The primary outcome was time to first inappropriate shock. ICD shocks were adjudicated for appropriateness. Other outcomes included all-cause hospitalization, heart failure hospitalization, and death. Patient, clinician, and hospital-level factors were accounted for using propensity score weighting methods. Among 1042 patients without pacing indications, 54.0% (n=563) received a single-chamber device and 46.0% (n=479) received a dual-chamber device. In a propensity-weighted analysis, device type was not significantly associated with inappropriate shock (hazard ratio, 0.91; 95% confidence interval, 0.59-1.38 [P=0.65]), all-cause hospitalization (hazard ratio, 1.03; 95% confidence interval, 0.87-1.21 [P=0.76]), heart failure hospitalization (hazard ratio, 0.93; 95% confidence interval, 0.72-1.21 [P=0.59]), or death (hazard ratio, 1.19; 95% confidence interval, 0.93-1.53 [P=0.17]). CONCLUSIONS: Among patients who received an ICD for primary prevention without indications for pacing, dual-chamber devices were not associated with lower risk of inappropriate shock or differences in hospitalization or death compared with single-chamber devices. This study does not justify the use of dual-chamber devices to minimize inappropriate shocks.

Association between Continuity of Care and Health-Related Quality of Life.

BACKGROUND: Patient-reported outcomes (PROs) are considered potential quality metrics for patients with multiple chronic medical conditions (MCC). Although continuity of care (COC) is an essential MCC care process, the association between common PROs and COC is unknown. METHODS: We assessed baseline and two-year follow-up self-reported health status, physical, and emotional well-being, and COC in seniors with MCC. Using mixed effects models with repeated measures adjusting for age, gender, and morbidity, we assessed each outcome as a function of COC. RESULTS: Of 2,078 seniors, 961 completed the initial survey and 806 completed follow-up. On a 0-100 scale, mean (sd) baseline self-reported health status, physical well-being, and emotional well-being were 48.7 (22.0), 36.4 (11.4), and 54.8 (9.0). On a 0 to 1 scale, mean baseline and 2-year COC were 0.24 (sd 0.22) and 0.22 (0.18). Follow-up self-reported health status, physical well-being, and emotional well-being were 48.8 (23.1), 36.5 (11.5), and 55.3 (8.8). In adjusted primary and secondary analyses using all available data, there were no associations between any outcomes and COC. CONCLUSION: Given the measurement burden of quality assessment, negative associations between potential quality metrics and care processes are informative. Systematic assessment of PROs can inform patient-centered MCC care. However, PRO scores should be used with caution as quality measures.

Risk of Breast Cancer With Long-Term Use of Calcium Channel Blockers or Angiotensin-Converting Enzyme Inhibitors Among Older Women.

Controversy exists about breast cancer risk associated with long-term use of calcium channel blockers (CCBs) or angiotensin-converting enzyme inhibitors (ACEis), respectively. Our objective in this study was to separately evaluate associations between duration of CCB or ACEi use and breast cancer in hypertensive women aged ≥55 years at 3 sites in the Kaiser Permanente health-care system (1997­2012). Exposures included CCB or ACEi use of 1­12 years' duration, determined from pharmacy dispensings. Outcomes included invasive lobular or ductal carcinoma. Statistical methods included discrete-time survival analyses. The cohort included 19,674 (17.9%) CCB users and 90,078 (82.1%) ACEi users. Two percent (n = 397) of CCB users and 1.9% (n = 1,733) of ACEi users developed breast cancer. Compared with 1­<2 years of use, in adjusted analysis, there was no association between CCB use for 2­<12 years and breast cancer: All 95% confidence intervals included 1. Increasing duration of ACEi use was associated with reduced breast cancer risk: Compared with 1­<2 years of use, the adjusted hazard ratio was 0.76 (95% confidence interval: 0.63, 0.92) for 5­<6 years of use and 0.63 (95% confidence interval: 0.43, 0.93) for 9­<10 years of use. We conclude that among older women with hypertension, long-term CCB use does not increase breast cancer risk and long-term treatment with ACEis may confer protection against breast cancer.