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Aim: This study aimed to determine the psychosocial markers associated with pre‐hospital delay among patients with diabetic foot (DF). Design: This study has a cross‐sectional design. Methods: The participants completed a questionnaire including pre‐hospital time, demographic characteristics, Social Support Rate Scale, Brief Illness Perception Questionnaire and Type D Personality Scale‐14. Bivariate and multivariate analyses were conducted to explore independent associations with pre‐hospital delay. Results: Only 1.8% (3/164) of participants arrived at the hospital for medical care in 24 h of symptom onset. Patients with low utilization of social support (p = 0.029), low negative illness perceptions (p = 0.014) and high levels of negative affectivity (p = 0.009) are likely to arrive late at the clinic. Medical staff should pay attention to identifying diabetic patients' Type D personalities and take actions to improve their social support as well as illness perception, so as to reduce the occurrence of hospital delay. Implications for the Profession and/or Patient Care: Psychosocial factors play a vital role in the delay in seeking medical treatment for patients with DF. Medical staff need to improve patients' illness perception as well as self‐management ability through health education. Importantly, key family members provide an emotional and psychological support system for diabetic patients. Therefore, nurses need to work with family members together to give information and psychological support during family visits. Additionally, building and maintaining trust with patients is crucial to encouraging individuals to express their concerns and worries. In this case, nurses may identify patients' negative emotions and conduct timely intervention, so as to achieve favourable outcomes. Patient or Public Contribution: This study used a convenience sample of 164 participants with DF recruited from the wound clinic of Northern Jiangsu People's Hospital and Yangzhou Hospital of TCM in China. [ABSTRACT FROM AUTHOR]

Background: Psychiatric illness may pose an additional risk of death for older adults during the COVID‐19 pandemic. Older adults in the community versus institutions might be influenced by the pandemic differently. This study examines excess deaths during the COVID‐19 pandemic among Medicare beneficiaries with and without psychiatric diagnoses (depression, anxiety, bipolar disorder, and schizophrenia) in the community versus nursing homes. Methods: This is a retrospective cohort study of a 20% random sample of 15,229,713 fee‐for‐service Medicare beneficiaries, from January 2019 through December 2021. Unadjusted monthly mortality risks, COVID‐19 infection rates, and case‐fatality rates after COVID‐19 diagnosis were calculated. Excess deaths in 2020, compared to 2019 were estimated from multivariable logistic regressions. Results: Of all included Medicare beneficiaries in 2020 (N = 5,140,619), 28.9% had a psychiatric diagnosis; 1.7% lived in nursing homes. In 2020, there were 246,422 observed deaths, compared to 215,264 expected, representing a 14.5% increase over expected. Patients with psychiatric diagnoses had more excess deaths than those without psychiatric diagnoses (1,107 vs. 403 excess deaths per 100,000 beneficiaries, p < 0.01). The largest increases in mortality risks were observed among patients with schizophrenia (32.4% increase) and bipolar disorder (25.4% increase). The pandemic‐associated increase in deaths with psychiatric diagnoses was only found in the community, not in nursing homes. The increased mortality for patients with psychiatric diagnoses was limited to those with medical comorbidities. The increase in mortality for psychiatric diagnoses was associated with higher COVID‐19 infection rates (1‐year infection rate = 7.9% vs. 4.2% in 2020), rather than excess case fatality. Conclusions: Excess deaths during the COVID‐19 pandemic were disproportionally greater in beneficiaries with psychiatric diagnoses, at least in part due to higher infection rates. Policy interventions should focus on preventing COVID‐19 infections and deaths among community‐dwelling patients with major psychiatric disorders in addition to those living the nursing homes. [ABSTRACT FROM AUTHOR]

Nursing homes (NHs) in micropolitan areas are reported to have different facility and market factors than urban NHs, but how these factors contribute to differences in emergency department (ED) visits remains unknown. This study examined and quantified sources of micropolitan-urban differences in NH risk-adjusted rates of any ED visit, ED without hospitalization or observation stay (outpatient ED), and potentially avoidable ED (PAED) visits of long-stay residents. The 2011-2013 national Medicare claims and NH Minimum Data Set (MDS) 3.0 were analyzed. We implemented generalized estimating equation models to examine micropolitan-urban differences in ED rates and Blinder-Oaxaca decompositions to quantify the contributions of NH and market factors. The study cohort included 12,883 unique privately owned, freestanding NHs from urban and micropolitan areas. Quarterly risk-adjusted rates of any ED visits, outpatient ED visits, and PAED visits were calculated from Medicare claims and MDS. NH and market characteristics were extracted from the Certification And Survey Provider Enhanced Reporting and Area Health Resources File. Over the study period, risk-adjusted rates averaged 10.2%, 3.4%, and 3.3% for any ED, outpatient ED, and PAED visits, respectively. Compared with urban NHs, micropolitan NHs reported similar rates of any ED, but significantly higher rates of outpatient ED and PAED (β = 0.20% and 0.27%; both P <.05). Observable differences in NH characteristics (eg, number of beds, percentage Medicare or Medicaid residents, and employment of nurse practitioners and physician assistants) explained more than 20% of the micropolitan-urban differences in rates of outpatient ED and PAED visits; market factors (mainly Medicare Advantage penetration) explained about 46% of the differences in rates of outpatient ED visits. Compared with urban NHs, micropolitan NHs tend to utilize more avoidable emergency care that can be partially explained by facility size, payer mix, use of nurse practitioners and physician assistants, and market structure. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to develop and validate a multimorbidity index using self-reported chronic conditions for predicting 5-year mortality risk. Methods: We analyzed data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and included 11,853 community-dwelling older adults aged 65–84 years. Restrictive association rule mining (ARM) was used to identify disease combinations associated with mortality based on 13 chronic conditions. Data were randomly split into the training (N = 8,298) and validation (N = 3,555) sets. Two multimorbidity indices with individual diseases only (MI) and disease combinations (MIDC) were developed using hazard ratios (HR s) for 5-year morality in the training set. We compared the predictive performance in the validation set between the models using condition count, MI, and MIDC by the concordance (C) statistic, the Integrated Discrimination Improvement (IDI), and the Net Reclassification Index (NRI). Results: A total of 13 disease combinations were identified. Compared with condition count (C-statistic: 0.710), MIDC (C-statistic: 0.713) showed significantly better discriminative ability (C-statistic: p = 0.016; IDI: 0.005, p < 0.001; NRI: 0.038, p = 0.478). Compared with MI (C-statistic: 0.711), the C-statistic of the model using MIDC was significantly higher (p = 0.031), while the IDI was more than 0 but not statistically significant (IDI: 0.003, p = 0.090). Conclusion: Although current multimorbidity status is commonly defined by individual chronic conditions, this study found that the multimorbidity index incorporating disease combinations showed supreme performance in predicting mortality among community-dwelling older adults. These findings suggest a need to consider significant disease combinations when measuring multimorbidity in medical research and clinical practice. [ABSTRACT FROM AUTHOR]

Aim: This study aims to develop a reliable and validate Chinese version of Oldenburg Burnout Inventory (OLBI). Design: A cross‐sectional validation design was adopted in this study. Methods: After obtaining the copyright by contacting with the author, the original English OLBI was developed to Chinese by forward translation, back‐translation, cultural adaptation and a pre‐test (20 nurses). The Chinese OLBI and Maslach Burnout Inventory (MBI) were administered to 641 clinical nurses during July and August, 2020. Internal consistency (Cronbach's α coefficient), split reliability (split half coefficient), construct validity (confirmatory factor analysis) and criterion validity (comparison with MBI, using Pearson correlation analysis) were assessed. Results: The Chinese OLBI included 16 items. Exploratory factor analysis extracted two factors with a cumulative contribution of 62.245%. Two‐dimensional structure (exhaustion and disengagement) was confirmed. It has good internal consistency (Cronbach's α coefficient values of 0.905, 0.933 and 0.876 for the total questionnaire, exhaustion dimension and disengagement dimension, respectively), split half reliability (split half coefficient = 0.883, p <.01) and criterion validity (r = 0.873, p <.01). Pearson coefficients between 16 items and the scale varied from 0.479–0.765. An acceptable model fit (χ2/df = 2.49, RMSEA = 0.068, TLI = 0.906, CFI = 0.922, SRMR = 0.061) was achieved. [ABSTRACT FROM AUTHOR]

Background: Caregiver perceived autonomy support by the oncologist is important for caregiver well‐being and may be affected by the patient's survival. We determined the association of caregiver‐oncologist discordance in patient's life expectancy estimates with perceived autonomy support over time and whether the association differed by patient survival status. Materials and Methods: We used data from a geriatric assessment cluster‐randomized trial (URCC 13070) that recruited patients aged at least 70 years with incurable cancer considering or receiving treatment, their caregivers, and their oncologists. At baseline, caregivers and oncologists were asked to estimate patient's life expectancy (0–6 months, 7–12 months, 1–2 years, 2–5 years, and >5 years; any difference in response was considered discordant). At 4–6 weeks, 3 months, and 6 months, caregivers completed the Health Care Climate Questionnaire (HCCQ), which measured perceived autonomy support by the oncologist. Generalized estimating equation modeling was conducted to assess the association of baseline caregiver‐oncologist discordance with longitudinal HCCQ scores, stratified by patient 6‐month survival status. Results: Discordant life expectancy estimates were present in 72.0% of dyads. In multivariate analyses, caregiver‐oncologist discordance in patient's life expectancy estimates was associated with higher caregiver HCCQ scores. In stratified analysis, caregiver‐oncologist discordance was associated with lower caregiver HCCQ scores (β = −3.46; 95% CI, −4.64 to −2.29) among patients who died within 6 months but with higher caregiver HCCQ scores (β = 1.33; 95% CI, 0.63–2.04) among patients who survived beyond 6 months. Conclusion: Interventions aimed at mitigating discordance need to consider its association with caregiver perceived autonomy support and patient's survival in order to better inform caregiver expectations. Implications for Practice: Among patients who died within the first 6 months, caregivers who estimated a different length of life for the patient compared with oncologists were more likely to report lower support from the oncologist, whereas the opposite relationship was seen within patients who survived beyond the first 6 months. When designing interventions to improve caregiver understanding of the patient's prognosis, its relationship with caregiver‐perceived support and patient's survival needs to be considered. Prognostic discordance refers to a discrepancy in estimates of prognosis by two individuals. This article evaluates the association between caregiver‐oncologist prognostic discordance regarding a patient's life expectancy estimates and caregiver perceived autonomy support. [ABSTRACT FROM AUTHOR]

Hospitalizations are common among long-stay nursing home (NH) residents, but the role of rurality in hospitalization is understudied. This study examines the relationships between rurality, NH, and market characteristics and NH quarterly risk-adjusted hospitalization rates of long-stay residents over 10 quarters (2011 Q2-2013 Q3). The longitudinal associations of NH and market factors and hospitalization rates were modeled separately on urban, micropolitan, and rural NHs using generalized estimating equation models and a fully interacted model of all NH and market characteristics with micropolitan and rural indicators to test significance of differences compared with urban NHs. In total, 14,600 unique NHs. Risk-adjusted hospitalization rates were calculated from 2011 to 2013 national Medicare claims and NH Minimum Data Set 3.0. Rurality was defined based on the 2010 Rural Urban Commuting Area codes. NH and market characteristics were extracted from Certification and Survey Provider Enhanced Reporting and Area Health Resources File. Over the study period, risk-adjusted hospitalization rates averaged 9.8% (standard deviation = 8.2%). No difference was found in the overall hospitalization rates of long-stay NH residents among urban, micropolitan, and rural NHs. Generalized estimating equation models show that urban NHs with higher percentages of Medicare and Medicaid residents and any nurse practitioner/physician assistant were associated with lower rates, but these associations were insignificant in rural settings. Higher registered nurse to total nurses ratio was only associated with lower hospitalization rates in urban settings. Higher median household income was associated with lower hospitalization rates in micropolitan and rural NHs. Rurality is not associated with hospitalization rates of long-stay residents, but NH and market factors (eg, payer distribution, staffing, and population income) may affect hospitalization differently in micropolitan/rural NHs than urban NHs. Future intervention on hospitalization should target factors unique to micropolitan/rural NHs which adopt strategies appropriate to their setting. [ABSTRACT FROM AUTHOR]

During the Coronavirus Disease 2019 (COVID-19) pandemic, US nursing homes (NHs) have been under pressure to maintain staff levels with limited access to personal protection equipment (PPE). This study examines the prevalence and factors associated with shortages of NH staff during the COVID-19 pandemic. We obtained self-reported information on staff shortages, resident and staff exposure to COVID-19, and PPE availability from a survey conducted by the Centers for Medicare and Medicaid Services in May 2020. Multivariate logistic regressions of staff shortages with state fixed-effects were conducted to examine the effect of COVID-19 factors in NHs. 11,920 free-standing NHs. The dependent variables were self-reported shortages of licensed nurse staff, nurse aides, clinical staff, and other ancillary staff. We controlled for NH characteristics from the most recent Nursing Home Compare and Certification and Survey Provider Enhanced Reporting, market characteristics from Area Health Resources File, and state Medicaid reimbursement calculated from Truven data. Of the 11,920 NHs, 15.9%, 18.4%, 2.5%, and 9.8% reported shortages of licensed nurse staff, nurse aides, clinical staff, and other staff, respectively. Georgia and Minnesota reported the highest rates of shortages in licensed nurse and nurse aides (both >25%). Multivariate regressions suggest that shortages in licensed nurses and nurse aides were more likely in NHs having any resident with COVID-19 (adjusted odds ratio [AOR] = 1.44, 1.60, respectively) and any staff with COVID-19 (AOR = 1.37, 1.34, respectively). Having 1-week supply of PPE was associated with lower probability of staff shortages. NHs with a higher proportion of Medicare residents were less likely to experience shortages. Abundant staff shortages were reported by NHs and were mainly driven by COVID-19 factors. In the absence of appropriate staff, NHs may be unable to fulfill the requirement of infection control even under the risk of increased monetary penalties. [ABSTRACT FROM AUTHOR]

Medicaid nursing home (NH) reimbursement rates and bed-hold policies have been shown to be associated with hospitalization of urban NH residents, but their relationships with emergency department (ED) visits, especially in rural NHs, remain unknown. This study explores the relationships of Medicaid NH policies with three NH quarterly risk-adjusted rates of ED use for long-stay residents and evaluates whether the associations differed by NHs' geographical locations. Longitudinal study of Medicaid policies and NH risk-adjusted rates over 3 quarters (2011 Q3, 2012 Q3, and 2013 Q3), using Generalized Estimating Equation (GEE) models. 14,514 unique NHs. Quarterly risk-adjusted rates of any ED visit, ED visits without hospitalization or observation stay (outpatient ED), and potentially avoidable ED visits (PAED) were calculated from national Medicare claims and NH Minimum Data Set 3.0. Medicaid policies were consolidated from several publicly available sources. NH and market characteristics were extracted from the Certification And Survey Provider Enhanced Reporting and the Area Health Resources File. In 2012, states reimbursed NHs, on average, $162.60 per resident-day, and 36 states employed bed-hold policies. Although a $10 increase in reimbursement rates was associated with statistically significantly lower rates of any ED, outpatient ED, and PAED in both urban and micropolitan NHs (−0.79%, −1.09%, and −1.02% for urban NHs; −1.29%, −1.90%, and −3.22% for micropolitan NHs, respectively), it was not associated with any ED measure in rural NHs. Medicaid bed-hold polices were associated with about 9% to 12% lower rates of all types of ED visits in urban NHs, but were not related to any of the ED measures in micropolitan and rural NHs. Associations of Medicaid NH policies with ED utilization are weaker in rural NHs than urban NHs. Yet, the financial viability of increasing Medicaid reimbursement to reduce the ED use may not be cost-effective. [ABSTRACT FROM AUTHOR]

Background: Suicide is an urgent public health challenge for China. This study aims to examine the prevalence, influence factors, and gender differences of suicidal ideation among general population in Northwestern Urban China.Methods: Data used in this study were derived from the third wave of a cohort study of a randomized community sample with 4291 participants (≥ 20 years) in 2008 in Lanzhou City and Baiyin City, Gansu Province. Data were collected via face-to-face interview by the trained interviewers. Descriptive analyses, chi-square tests and multivariate logistic regressions were performed by using Stata 12.0, as needed.Results: The prevalence of 12-month suicidal ideation was 4.29%, there was no significant difference between males and females [5.04% vs 3.62%, Adjusted Odds Ratio (AOR) = 0.83, p = 0.351]. Several risk factors for suicidal ideation were confirmed, including being unmarried (AOR = 1.55, p = 0.030), having depression symptoms (AOR = 2.33, p < 0.001), having other insurance (AOR = 1.83, p = 0.01) or no insurance (AOR = 1.73, p = 0.024). In addition, several influence factors were significantly different in males and females, such as being currently married (unmarried vs married, AOR = 1.84, p = 0.027, for females; no difference for males), feeling hopeless (hopless vs hopeful, AOR = 1.92, p = 0.06, for females; no difference for males), having other insurances (having other insurances vs having basic employee medical insurance, AOR = 1.92, p = 0.044, for males; no difference for females), having debts (having debts vs no debts, AOR = 2.69, p = 0.001, for males; no difference for females), currently smoking (smoking vs nonsmoking, AOR = 3.01, p = 0.019 for females, no difference for males), and currently drinking (drinking vs nondrinking, AOR =2.01, p = 0.022, for males; no difference for females).Discussion and Conclusion: These findings suggested that comprehensive suicide prevention strategies should be developed or strengthened in order to prevent suicide ideation in China, and the gender-specific differences need to be explored through further researches. [ABSTRACT FROM AUTHOR]

The article discusses a study regarding the characteristics of the help-seeking behaviors and pathways of people with physical and mental illness from rural regions of China. Topics discussed include documentation of 203 patients with mental disorders using the World Health Organization (WHO)'s pathway encounter form, the use of Mann-Whitney U test, and lack of awareness about treatment services with mental disorders.

Successful discharge of nursing home (NH) residents to community has been reported in Nursing Home Compare (NHCompare) as a quality indicator, yet it is likely influenced by the availability of home- and community-based services (HCBS). Medicaid NH reimbursement rates and bed-hold policies have been shown to be related to quality of care, which may also affect successful discharge. This study explores the relationship of state Medicaid long-term care policies and successful discharge. Longitudinal study of Medicaid policies and NHCompare successful discharge rates over 3 time periods, 2014-2015, 2015-2016, and 2016-2017, using generalized estimating equation models. 11,694 unique NHs. Risk-adjusted rates of successful discharge were downloaded from NHCompare. Truven's "Medicaid Expenditures for Long-term Services and Supports" reports provided states' expenditures on HCBS and NHs. Details of bed-hold policies in 2014 were obtained from the Medicaid and CHIP Payment and Access Commission. Data on NH and market characteristics were extracted from LTCFocUs.org and Area Health Resources File. The national average-adjusted successful discharge rates were 49.7%, 56.8%, and 56.2% in 2014-2015, 2015-2016, and 2016-2017, respectively. In 2015, states spent between 30.6% (Mississippi) and 82.2% (Oregon) on HCBS, with an overall average of 53.1%. States reimbursed NHs, on average, $185.7 per resident day. Five percent increase in Medicaid spending for HCBS was statistically significantly associated with 0.47% higher successful discharge rates. Compared to NHs in states with reimbursement rates in the first quartile (≤$152), NHs in the second ($153-$178), third ($179-$212), and fourth (≥$213) quartiles were associated with 2.33%, 1.86%, and 1.15% higher successful discharge rates (all P <.01). Results were stronger in states without bed-hold policies. This study provides promising evidence to state governments that shifting expenditures from institutions to communities as well as more generous reimbursements to NHs may improve quality of care in NHs. [ABSTRACT FROM AUTHOR]

To examine whether facility-reported staff shortages and total staff levels were independently associated with changes in nursing home (NH) outcomes in 2020. Longitudinal cohort study. A total of 8466 NHs with staffing and outcome data. This study used NH COVID-19 Public File (2020), Nursing Home Compare (2019-2020), and Payroll-Based Journal data (2019-2020). Outcome measures included the percentage of long-stay residents in a facility with declines in activities in daily living (ADLs), decreases in mobility, weight loss, and pressure ulcers in 2020 Q2, 2020 Q3, and 2020 Q4. Independent variables were whether NHs reported any shortage of aides or licensed nurses and total staff hours per resident day (HPRD). Separate 2-level (NH, state) Hierarchical Generalized Linear Mixed models examined the association of facility-reported shortages and staff hours with key NH resident outcomes, controlling for NH characteristics and COVID-19 infections. The weekly percentage of NHs reporting any staff shortage averaged 20%. Total staff HPRD increased slightly from 3.7 in 2019 to 3.8 in 2020. Health outcomes were stable during 2019 and 2020 Q1 but worsened substantially starting in 2020 Q2. For example, the percentage of residents with mobility loss increased from 16.2% in 2020 Q1 to 27.9% in 2020 Q4. Facility-reported staff shortages were associated with an increase in the proportion of residents with an ADL decline (0.54 percentage points), mobility loss (0.80 percentage points), weight loss (0.22 percentage points), and pressure ulcers (0.22 percentage points) (all P <.01). Total staff HPRD was not associated with changes in any outcomes (all P >.05). NHs reported worsened health outcomes among long-stay residents in 2020, with worse outcomes found among facilities that reported staff shortages but not among those with lower total staff levels. Facility-reported shortages provide important quality information during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]