Association of neurocognitive disorders with morbidity and mortality in older adults undergoing major surgery in the USA: a retrospective, population-based, cohort study.

BACKGROUND: Neurocognitive disorders become increasingly common as patients age, and increasing numbers of surgical interventions are done on older patients. The aim of this study was to understand the clinical characteristics and outcomes of surgical patients with neurocognitive disorders in the USA in order to guide future targeted interventions for better care. METHODS: This retrospective cohort study used claims data for US Medicare beneficiaries aged 65 years and older with a record of inpatient admission for a major diagnostic or therapeutic surgical procedure between Jan 1, 2017, and Dec 31, 2018. Data were retrieved through a data use agreement between Dartmouth Hitchcock Medical Center and US Centers for Medicare and Medicaid Services via the Research Data Assistance Center. The exposure of interest was the presence of a pre-existing neurocognitive disorder as defined by diagnostic code within 3 years of index hospital admission. The primary outcome was mortality at 30 days, 90 days, and 365 days from date of surgery among all patients with available data. FINDINGS: Among 5 263 264 Medicare patients who underwent a major surgical procedure, 767 830 (14·59%) had a pre-existing neurocognitive disorder and 4 495 434 (85·41%) had no pre-existing neurocognitive disorder. Adjusting for demographic factors and comorbidities, patients with a neurocognitive disorder had higher 30-day (hazard ratio 1·24 [95% CI 1·23-1·25]; p<0·0001), 90-day (1·25 [1·24-1·26]; p<0·0001), and 365-day mortality (1·25 [1·25-1·26]; p<0·0001) compared with patients without a neurocognitive disorder. INTERPRETATION: Our findings suggest that the presence of a neurocognitive disorder is independently associated with an increased risk of mortality. Identification of a neurocognitive disorder before surgery can help clinicians to better disclose risks and plan for patient care after hospital discharge. FUNDING: Department of Anesthesiology and Perioperative Medicine at Dartmouth Hitchcock Medical Center.

Telehealth Use Following COVID-19 Within Patient-Sharing Physician Networks at a Rural Comprehensive Cancer Center: Cross-sectional Analysis.

BACKGROUND: In response to the COVID-19 pandemic, cancer centers rapidly adopted telehealth to deliver care remotely. Telehealth will likely remain a model of care for years to come and may not only affect the way oncologists deliver care to their own patients but also the physicians with whom they share patients. OBJECTIVE: This study aimed to examine oncologist characteristics associated with telehealth use and compare patient-sharing networks before and after the COVID-19 pandemic in a rural catchment area with a particular focus on the ties between physicians at the comprehensive cancer center and regional facilities. METHODS: In this retrospective observational study, we obtained deidentified electronic health record data for individuals diagnosed with breast, colorectal, or lung cancer at Dartmouth Health in New Hampshire from 2018-2020. Hierarchical logistic regression was used to identify physician factors associated with telehealth encounters post COVID-19. Patient-sharing networks for each cancer type before and post COVID-19 were characterized with global network measures. Exponential-family random graph models were performed to estimate homophily terms for the likelihood of ties existing between physicians colocated at the hub comprehensive cancer center. RESULTS: Of the 12,559 encounters between patients and oncologists post COVID-19, 1228 (9.8%) were via telehealth. Patient encounters with breast oncologists who practiced at the hub hospital were over twice as likely to occur via telehealth compared to encounters with oncologists who practiced in regional facilities (odds ratio 2.2, 95% CI 1.17-4.15; P=.01). Patient encounters with oncologists who practiced in multiple locations were less likely to occur via telehealth, and this association was statistically significant for lung cancer care (odds ratio 0.26, 95% CI 0.09-0.76; P=.01). We observed an increase in ties between oncologists at the hub hospital and oncologists at regional facilities in the lung cancer network post COVID-19 compared to before COVID-19 (93/318, 29.3%, vs 79/370, 21.6%, respectively), which was also reflected in the lower homophily coefficients post COVID-19 compared to before COVID-19 for physicians being colocated at the hub hospital (estimate: 1.92, 95% CI 1.46-2.51, vs 2.45, 95% CI 1.98-3.02). There were no significant differences observed in breast cancer or colorectal cancer networks. CONCLUSIONS: Telehealth use and associated changes to patient-sharing patterns associated with telehealth varied by cancer type, suggesting disparate approaches for integrating telehealth across clinical groups within this health system. The limited changes to the patient-sharing patterns between oncologists at the hub hospital and regional facilities suggest that telehealth was less likely to create new referral patterns between these types of facilities and rather replace care that would otherwise have been delivered in person. However, this study was limited to the 2 years immediately following the initial outbreak of COVID-19, and longer-term follow-up may uncover delayed effects that were not observed in this study period.

Sacubitril/valsartan vs ACEi/ARB at hospital discharge and 5-year survival in older patients with heart failure with reduced ejection fraction: A decision analysis approach.

BACKGROUND: In clinical trials, sacubitril/valsartan has demonstrated significant survival benefits compared to angiotensin converting enzyme inhibitors or angiotensin receptor blockers (ACEi/ARB). Whether older patients with heart failure with reduced ejection fraction (HFrEF) benefit as much, due to higher rates of comorbidities, frailty and drug discontinuation, is unknown. METHODS AND RESULTS: Using a cohort of Medicare beneficiaries hospitalized with HFrEF between 2016 and 2018, we determined all-cause mortality and HF-readmission rates among patients not given ACEi/ARB or sacubitril/valsartan at hospital discharge, by age. We then used risk reductions from the SOLVD, PARADIGM-HF and PIONEER-HF trials to estimate the benefits of ACEi/ARB and sacubitril/valsartan. We then incorporated age-specific estimates of drug discontinuation from Medicare. A Markov decision process model was used to simulate 5-year survival and estimate number needed to treat, comparing discharge on ACEi/ARB vs sacubitril/valsartan by age. After accounting for drug discontinuation rates, which were surprisingly slightly higher among those discharged on ACEi/ARB (2.3%/month vs 1.9%/month), there was a small but significant survival advantage to discharge on sacubitril/valsartan over 5 years (+0.81 months [95% CI 0.80, 0.81]). The benefit of sacubitril/valsartan over ACEi/ARB did not decrease with increasing age - the number needed to treat among 66 to 74-year-old patients was 84 and among 85+ year-old patients was 67. CONCLUSIONS: Even after accounting for "real world" rates of drug discontinuation, discharge on sacubitril/valsartan after conferred a small, but significant, survival advantage which does not appear to wane with increasing age.

Weak correlations in health services research: Weak relationships or common error?

OBJECTIVE: To examine whether the correlation between a provider's effect on one population of patients and the same provider's effect on another population is underestimated if the effects for each population are estimated separately as opposed to being jointly modeled as random effects, and to characterize how the impact of the estimation procedure varies with sample size. DATA SOURCES: Medicare claims and enrollment data on emergency department (ED) visits, including patient characteristics, the patient's hospitalization status, and identification of the doctor responsible for the decision to hospitalize the patient. STUDY DESIGN: We used a three-pronged investigation consisting of analytical derivation, simulation experiments, and analysis of administrative data to demonstrate the fallibility of stratified estimation. Under each investigation method, results are compared between the joint modeling approach to those based on stratified analyses. DATA COLLECTION/EXTRACTION METHODS: We used data on ED visits from administrative claims from traditional (fee-for-service) Medicare from January 2012 through September 2015. PRINCIPAL FINDINGS: The simulation analysis demonstrates that the joint modeling approach is generally close to unbiased, whereas the stratified approach can be severely biased in small samples, a consequence of joint modeling benefitting from bivariate shrinkage and the stratified approach being compromised by measurement error. In the administrative data analyses, the estimated correlation of doctor admission tendencies between female and male patients was estimated to be 0.98 under the joint model but only 0.38 using stratified estimation. The analogous correlations for White and non-White patients are 0.99 and 0.28 and for Medicaid dual-eligible and non-dual-eligible patients are 0.99 and 0.31, respectively. These results are consistent with the analytical derivations. CONCLUSIONS: Joint modeling targets the parameter of primary interest. In the case of population correlations, it yields estimates that are substantially less biased and higher in magnitude than naive estimators that post-process the estimates obtained from stratified models.

Long-term Reintervention After Endovascular Abdominal Aortic Aneurysm Repair.

OBJECTIVE: To describe the long-term reintervention rate after endovascular abdominal aortic aneurysm repair (EVR), and identify factors predicting reintervention. SUMMARY OF BACKGROUND DATA: EVR is the most common method of aneurysm repair in America, and reintervention after EVR is common. Clinical factors predicting reintervention have not been described in large datasets with long-term follow-up. METHODS: We studied patients who underwent EVR using the Vascular Quality Initiative registry linked to Medicare claims. Our primary outcome was reintervention, defined as any procedure related to the EVR after discharge from the index hospitalization. We used classification and regression tree modeling to inform a multivariable Cox-regression model predicting reintervention after EVR. RESULTS: We studied 12,911 patients treated from 2003 to 2015. Mean age was 75.5 ±â€Š7.3 years, 79.9% were male, and 89.1% of operations were elective. The 3-year reintervention rate was 15%, and the 10-year rate was 33%. Five factors predicted reintervention: operative time ≥3.0 hours, aneurysm diameter ≥6.0 cm, an iliac artery aneurysm ≥2.0 cm, emergency surgery, and a history of prior aortic surgery. Patients with no risk factors had a 3-year reintervention rate of 12%, and 10-year rate of 26% (n = 7310). Patients with multiple risk factors, such as prior aortic surgery and emergent surgery, had a 3-year reintervention rate 72%, (n = 32). Modifiable factors including EVR graft manufacturer or supra-renal fixation were not associated with reintervention (P = 0.76 and 0.79 respectively). CONCLUSIONS: All patients retain a high likelihood of reintervention after EVR, but clinical factors at the time of repair can predict those at highest risk.

Influence of Peer Physicians on Intensity of End-of-Life Care for Cancer Decedents.

BACKGROUND: The intensity of end-of-life care varies substantially both within and between areas. Differing practice patterns of individual physicians are likely influenced by their peers. OBJECTIVE: To assess whether intensity of end-of-life care previously provided by a physician's peers influences patterns of care at the end-of-life for that physician's patients. RESEARCH DESIGN: Observational study. SUBJECTS: A total of 185,947 fee-for-service Medicare enrollees with cancer who died during 2006-2010 who were treated by 26,383 physicians. MEASURES: Spending in the last month of life, >1 emergency room visit, >1 hospitalization, intensive care unit admission in the last month of life, chemotherapy within 2 weeks of death, no/late hospice, terminal hospitalization. RESULTS: Mean (SD) spending in the last month of life was $16,237 ($17,124). For each additional $1000 of spending for a peer physician's patients in the prior year, spending for the ego physician's patients was $83 higher (P<0.001). Among physicians with peers both in and out of their practice, more of the peer effect was explained by physicians outside of the practice ($72 increase for each $1000 increase by peer physicians' patients, P<0.001) than peer physicians in the practice ($27 for each $1000 increase by within-practice peer physicians' patients, P=0.01). Results were similar across the other measures of end-of-life care intensity. CONCLUSIONS: Physician's peers exert influence on the intensity of care delivered to that physician's patients at the end-of-life. Physician education efforts led by influential providers and provider organizations may have potential to improve the delivery of high-value end-of-life care.

Assessing Variation in Implantable Cardioverter Defibrillator Therapy Guideline Adherence With Physician and Hospital Patient-sharing Networks.

BACKGROUND: Implantable cardioverter defibrillator (ICD) therapy is used for primary prevention of death among people with heart failure, and new evidence in 2005 on its effectiveness changed practice guidelines in the United States. OBJECTIVES: The objective of this study is to examine how the connectedness of physicians and hospitals, measured using network analysis, relates to guideline-consistent ICD implantation. RESEARCH DESIGN: We constructed physician and hospital networks for cardiovascular disease. Physicians were linked if they shared cardiovascular disease patients; these links were aggregated by hospital affiliation to construct a hospital network. SUBJECTS: Medicare beneficiaries who underwent ICD therapy for primary prevention from 2007 to 2011. MEASURES: The clinical outcome of interest was guideline-consistent ICD implantation, calculated using the National Cardiovascular Data Registry. The exposure variables of interest were the network measures of the ICD surgeon, the referring hospital, and the hospital where the ICD surgery occurred. RESULTS: We focused on patients who were referred between hospitals for ICD implantation because they were more likely influenced by the hospital network (n=28,179). Patients were less likely to meet guidelines if their referring hospital had more connections to other hospitals (OR, 0.49; 95% confidence interval, 0.25-0.96) and more likely to meet guidelines if their ICD surgery hospital had more connections (OR, 1.61; 95% confidence interval, 0.98-2.64). The ICD surgeon's network measures were not associated with guideline-consistent implantation. CONCLUSIONS: Associations between the hospital network measures and guideline adherence suggests new approaches to better disseminate clinical guidelines across health systems.

The psychometric properties of Observer OPTION(5), an observer measure of shared decision making.

OBJECTIVES: Observer OPTION(5) was designed as a more efficient version of OPTION(12), the most commonly used measure of shared decision making (SDM). The current paper assesses the psychometric properties of OPTION(5). METHODS: Two raters used OPTION(5) to rate recordings of clinical encounters from two previous patient decision aid (PDA) trials (n=201; n=110). A subsample was re-rated two weeks later. We assessed discriminative validity, inter-rater reliability, intra-rater reliability, and concurrent validity. RESULTS: OPTION(5) demonstrated discriminative validity, with increases in SDM between usual care and PDA arms. OPTION(5) also demonstrated concurrent validity with OPTION(12), r=0.61 (95%CI 0.54, 0.68) and intra-rater reliability, r=0.93 (0.83, 0.97). The mean difference in rater score was 8.89 (95% Credibility Interval, 7.5, 10.3), with intraclass correlation (ICC) of 0.67 (95% Credibility Interval, 0.51, 0.91) for the accuracy of rater scores and 0.70 (95% Credibility Interval, 0.56, 0.94) for the consistency of rater scores across encounters, indicating good inter-rater reliability. Raters reported lower cognitive burden when using OPTION(5) compared to OPTION(12). CONCLUSIONS: OPTION(5) is a brief, theoretically grounded observer measure of SDM with promising psychometric properties in this sample and low burden on raters. PRACTICE IMPLICATIONS: OPTION(5) has potential to provide reliable, valid assessment of SDM in clinical encounters.

Nursing home capabilities and decisions to hospitalize: a survey of medical directors and directors of nursing.

OBJECTIVES: To obtain information from decision makers about attitudes toward hospitalization and the factors that influence their decisions to hospitalize nursing home residents. DESIGN: Cross-sectional survey. SETTING: Four hundred forty-eight nursing homes, 76% of which were nonprofit, from 25 states. PARTICIPANTS: Medical directors and directors of nursing (DONs). MEASUREMENTS: Participants were surveyed about resource availability, determinants of hospitalization, causes of overhospitalization, and nursing home practice. RESULTS: The survey response rate was 81%, with at least one survey from 93% of the facilities. Medical directors and DONs agreed that resident preference was the most important determinant in the decision to hospitalize, followed by quality of life. Although both groups ranked on-site doctor/nurse practitioner evaluation within 4 hours as the least accessible resource, they did not rank doctors not being quickly available as an important cause of overhospitalization. Rather, medical directors perceived the lack of information and support to residents and families around end-of-life care and the lack of familiarity with residents by covering doctors as the most important causes of overhospitalization. DONs agreed but reversed the order. Medical directors and DONs expressed confidence in provider and staff ability, although DONs were significantly more positive. CONCLUSION: Medical directors and DONs agree about most factors that influence decisions to hospitalize nursing home residents. Patient-centered factors play the largest roles, and the most important causes of overhospitalization are potentially modifiable.