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Background: It is unknown whether the stress of the COVID-19 pandemic, which had a particular impact on inpatient and long-term care (LTC) nurses, had an effect on nurses' choice of employment settings.

Objective: Determine whether the COVID-19 pandemic contributed to changes in nurses' choice of employment setting.

Methods: This study used data from the 2018 and 2022 National Sample Survey of Registered Nurses to conduct a difference-in-difference analysis. We constructed a state-level measure of COVID-19 caseload, defined as COVID-19 cases per hospital bed; High versus Low COVID-19 states were defined as those above versus below the median, respectively. Logistic regression models were used to estimate the effect of exposure to High COVID-19 caseload (vs. Low) and time (2022 vs. 2018) on nurse employment choices across inpatient, LTC, outpatient, and nonclinical settings.

Results: From 2018 to 2022, the size of the US nursing workforce grew from 3.27 to 3.57 million nurses; however, RN FTEs increased in outpatient settings and decreased in all other settings. In adjusted analyses, nurses were less likely to work in LTC settings in 2022 than in 2018; yet, those exposed to High COVID-19 caseloads were 0.9% (95% CI: 0.3-1.5) more likely to work in LTC than those exposed to Low COVID-19 caseloads. Differences between High versus Low COVID-19 caseload exposure were not statistically significant for the likelihood of working in inpatient, outpatient, and nonclinical settings.

Conclusions: Our findings suggest that exposure to High COVID-19 caseload was not associated with changes in nurses' employment settings.

Objective: To advance patient-centered care for high-need homeless-experienced patients, we identified the rates of various personal health goals, the broader domains that underlie these goals, and associations between these domains and the health-related needs of this population.

Method: The sample consisted of 176 veterans from 3 VA Medical Centers who were enrolled in primary care, on VA's Homeless Registry, and high utilizers of acute care. An interview was conducted with each participant to collect information on their personal health goals and health-related needs. Exploratory factor analysis was used to identify broad domains underlying endorsement of personal health goals. Associations between these broad goal domains and health-related needs (substance use, mental and physical health, treatment engagement, and psychosocial) were examined using an exploratory structural equation modeling-within-confirmatory factor analysis approach.

Results: Three broad domains were found to underlie the personal health goals of the sample: social functioning, health promotion, and substance use. Social functioning and health promotion were highly correlated, whereas substance use was weakly correlated with both social functioning and health promotion. All substance use-related needs were positively associated with substance use goals. Mental and physical health needs were primarily associated with health promotion goals. Treatment engagement and psychosocial needs demonstrated associations across all 3 goal domains.

Conclusions: Findings highlight the high value that many high-need homeless-experienced patients place on their social well-being and the potential benefits to measuring both deficiency and growth needs in this population. Clinical implications and future directions for research are discussed.

Objectives: To compare predictive accuracy of 3-step theory of suicide (3ST) factor scores derived from natural language processing of Veterans Health Administration (VHA) clinical progress notes versus a model that underlies VHA's Recovery Engagement and Coordination for Health-Veterans Enhanced Treatment (REACH VET) program retrained to predict the combined outcome of suicide attempt or suicide death, and to compare characteristics of patients accurately predicted by both approaches.

Background: As health systems incorporate risk prediction models to guide suicide prevention efforts, it is important to evaluate their predictive accuracy and to consider the benefits of different modeling approaches.

Methods: A comparative cohort design in which both risk prediction approaches were evaluated for the same random sample (n=162,132) of VHA patients alive on May 1, 2018, who had clinical encounters during the 4 weeks before that date.

Results: At the highest risks (top 1%-5%), the model based on REACH VET variables outperformed the 3ST approach in terms of positive predictive value and false-negative rate. Among patients who attempted or died by suicide, uniquely identified by the 3ST approach and not by the retrained REACH VET model, none had attempted suicide during the prior 6 months, emergency department visits during the prior month, discharges from mental health hospitalizations during the prior 12 months, or a diagnosis of bipolar disorder during the prior 24 months.

Conclusions: Additional research is recommended to further prepare 3ST factor scores based on NLP of clinical progress notes for use in clinical decision-making.

Background and objective: Low volume has been recognized as a problem when benchmarking hospitals due to outcome rate instability. We asked if low-volume hospital outcomes, using matching to control for many clinical and sociodemographic characteristics, would expose quality problems not observed with CMS methods.

Research design: Matched cohort study. Grades derive from mortality differences between all patients at the low-volume hospital and their matched controls.

Subjects: Medicare patients admitted with Acute Myocardial Infarction, Heart Failure and Pneumonia in 78 low-volume Pennsylvania acute care hospitals (combined condition volume=75≤N≤750 for the 3 y, 2017-2019), using Medicare's Virtual Research Data Center.

Measures: Thirty-day mortality.

Results: Using matching, 10 of 78 reportable low-volume hospitals had significantly higher mortality versus matched typical controls and 16 low-volume hospitals displayed significantly higher mortality versus well-resourced controls. In contrast, Medicare reported that only 3 of these same 78 hospitals had significantly higher mortality than "the national rate" on AMI, HF, or pneumonia.

Conclusions: We find that some low-volume hospitals performed well. Other low-volume hospitals had significantly worse outcomes than both well-resourced and typical hospitals; and some displayed significantly worse mortality compared with well-resourced controls but did not reach significant differences from typical controls. In short, performing "no different from the national rate," as is almost always reported for low-volume hospitals when using CMS methods, does not imply a low-volume hospital has acceptable outcomes. Reports based on matching can expose low-volume hospital quality problems not apparent using standard methods. Low-volume hospitals have more quality problems than generally reported.

Background: The Accelerating Data Value Across a National Community Health Center Network (ADVANCE) collaborative is 1 of 8 clinical research networks participating in PCORnet®, the National Patient-Centered Clinical Research Network. Providing data, engagement, and regulatory infrastructure, ADVANCE facilitates the inclusion of people who receive primary care in community-based health centers (CHC) across over 90 patient-centered research studies. Centrally coordinated by OCHIN, in partnership with Fenway Health, Health Choice Network, Oregon Health & Science University, and the University of Washington, ADVANCE comprises the nation's most comprehensive network for health care and outcomes research in community-based primary care and hospital-based settings.

Objective: This manuscript discusses ADVANCE's unique past, present, and future approaches to strengthen infrastructure and capacity to enhance research in community-based primary care settings.

Main arguments: As community-based primary care organizations, CHCs have relationships, trust, and expertise with the communities they serve. ADVANCE provides critical data and engagement resources for including CHCs and their patients in research to improve patient-centered care and outcomes. Despite past investment, there is a recognized need for additional engagement, investment, capacity building, and research infrastructure to realize the full potential of CHC partnerships in clinical research and PCORnet® studies. By partnering with CHCs and tertiary hospitals, ADVANCE and the PCORnet infrastructure can provide enhanced access to clinical research opportunities that further support patient-centered, high-quality care delivery, and positive health outcomes while meeting CHCs' priorities and goals, progressing their own research capacity and infrastructure, and contributing to scalable research readiness models.

Background: PCORnet is a large, federated "network of networks" that facilitates innovative patient-centered comparative clinical effectiveness research (CER) and other health research at a national scale. As a flagship infrastructure program funded by the Patient-Centered Outcomes Research Institute® (PCORI®), an independent, nonprofit research organization, PCORnet is unique among national clincial research networks given the scale of the network. With linkages to more than 47 million unique patients, strong governance, research expertise, and commitment to keeping the patient at the center of all activities, PCORnet can be used to conduct a range of study types, from pragmatic trials to observational studies. Since 2015, PCORnet has been used to conduct more than 250 studies, ranging from observational research to pragmatic trials.

Objective: The main objective of this commentary is to provide PCORI's perspective on the importance of clinical research infrastructure, the unique contributions of the PCORnet infrastructure to patient-centered research, and PCORI's approach to continuous evaluation and evolution of PCORnet.

Relevance to the special issue: This commentary aims to be useful to readers in understanding PCORI's vision for PCORnet and approach to monitoring progress and measuring success.

Background/objective: Evidence about the patient benefits of alternative primary care delivery models for high-cost/high needs patients is mixed. We conducted a follow-up study of a program designed to improve outcomes of seriously ill adult patients in an integrated delivery system.

Methods: Using a quasi-experimental design, we examined the 180-day mortality of patients empaneled to a complex care program (CCP, n=1445) compared with that of eligible but unempaneled patients who continued to receive usual primary care (UPC, n=6409) for January 2019 through June 2021. Patients in the CCP and UPC were propensity score-matched on demographics, comorbidities, and frailty. In the propensity score matched samples (n=1440 in each group), the hazard of mortality was estimated using Cox proportional hazards regression.

Results: The CCP continued to empanel eligible adults with more comorbidities and greater frailty compared with the eligible patient population in UPC. In the matched samples, CCP patients had a significantly lower hazard of 180-day mortality compared with UPC in this replication cohort (0.71, 95% CI: 0.61-0.82). This was higher than the hazard ratio in the prior inception cohort (0.58, 95% CI: 0.47-0.70).

Conclusions: A reduced hazard of death was reproduced within a second incident cohort of among seriously ill adult patients who were empaneled to a CCP in an integrated health care system compared with matched, but unempaneled patients whose care remained within UPC.

PCORnet® is a large, complex network that may appear intimidating for new investigators and funders, posing a perceived barrier to expanding the use of this powerful resource for research. In this commentary, I highlight the importance of mentorship, immersion, and didactic training to build the future cadre of investigators leveraging the PCORnet infrastructure and expand the impact of PCORnet® Studies, while sharing personal experience navigating the opportunities and challenges offered by this network.

Background: The Congenital Heart Initiative-Redefining Outcomes and Navigation to Adult-Centered Care (CHI-RON) study is a unique collaboration between the PCORnet and Congenital Heart Initiative (CHI), the first patient powered registry for adult congenital heart disease (ACHD) patients. The CHI-RON study examines the effects of gaps in recommended care in ACHD.

Objective: Recruitment of racially diverse, younger, out-of-care, and male participants has been challenging in ACHD studies. Our goal was to design patient engagement and recruitment strategies to improve representation.

Research design: Launched in December 2020, patients from any location can self-enroll in the CHI registry, while the CHI-RON study (5/2022 - 10/2023) recruited ACHD patients at 12 sites participating in PCORnet. CHI-RON Recruitment methodology included a patient partner engagement toolkit and a recruitment algorithm using the PCORnet® Common Data Model designed specifically to improve diversity and reduce self-enrollment biases in comparison to the CHI registry.

Subjects: ACHD patients, age 18 years or older, with the ability to complete PROs independently.

Measures: Demographic/Recruitment Statistics for study participants and Patient Engagement in Research Scale (PEIRS-22) for the study team partners.

Results: As of October 2023, a total of 2652 participants were recruited through CHI-RON recruitment methodology while 1326 were self-enrolled in the CHI. CHI-RON recruitment methodologies have increased representation when compared with self-enrolled CHI participants in terms of ethnicity (10.9% vs. 7.4% Hispanic, P<0.001), race (5.4% vs. 2.6%, Black/African American, P<0.001), sex (41% vs. 28% male, P<0.001), younger age (35.5 +/-12.8 y vs. 43.5±14.5 y, P<0.001), and education (33.4% vs. 24% high school equivalent or less, P<0.001).Most study team patient partners (n=12, 86%) reported a very to extremely high degree of engagement (PEIRS-22 average score 101.6), especially in the subdomains of contributions, support, feeling valued, and benefits.

Conclusions: Patient engagement and novel recruitment strategies are critical to improving the inclusion of under-represented populations in clinical research and ensuring alignment with the needs of ACHD patients.

Background: Descriptive studies have documented high hospital nurse burnout and turnover but there are few, if any, large-scale evaluations of organizational interventions to improve clinician retention. The Magnet model is an organizational hospital intervention associated with better clinician and patient outcomes but there is insufficient evidence as to whether the Magnet model based on structural empowerment of clinicians results in better outcomes or rewards hospitals with good work environments, and whether the Magnet model can be implemented at scale outside the United States.

Objective: To evaluate whether Magnet4Europe-a multiyear organizational intervention of European hospitals-could be implemented and would result in improvements in nurse well-being, care quality, and patient safety.

Design: Quasi-experimental longitudinal evaluation of 56 European intervention hospitals in 6 countries. Hospital-level implementation of the intervention measured by changes (from baseline to follow-up) in 77 Magnet model intervention targets. Outcome measures (eg, nurse burnout, intent to leave, quality of care, patient safety) were derived from surveys of nurses (4546 nurses at baseline; 3171 at follow-up).

Findings: Hospitals that implemented intervention targets during the study period observed reductions in nurse burnout, nurses' intentions to leave their jobs, and unfavorable care quality. Each 10-percentage-point increase in intervention target implementation was associated with 2.7%-point reduction in nurses who intend to leave (β -2.66; 95% CI: -4.74, -0.58, P <0.05). Hospitals which implemented more than 25% of intervention targets observed 6.3%-point reduction in nurse burnout, 7.6%-point reduction in intent to leave, 6.4%-point reduction in unfavorable care quality, and 3.7%-point reduction in unfavorable patient safety. Improvements in hospital percentages of nurses reporting staffing adequacy were associated with reductions in burnout, intentions to leave, unfavorable care quality, and patient safety.

Conclusion: Successful implementation of Magnet4Europe demonstrates promise for international adoption at scale of Magnet as an organizational intervention for improving clinician well-being, care quality, and patient safety.