Predictive Validity of the Sitting Balance Scale and Function in Sitting Test in People with Stroke

Impairment of trunk control is a common problem after stroke, and trunk impairment may affect many functions such as breathing, speech, limb movements and transfers. The present study was aimed to investigate the effect of trunk control on sitting balance and upper extremity functions in individuals with subacute stroke. A total of 30 patients with subacute stroke (14 female, 16 male) were included in this study. The mean age of the included patients was 59.80 ± 13.22 years, and the mean disease duration was 2.90 ± 1.38 months. Trunk Impairment Scale (TIS), Trunk Control Test (TCT), Function in Sitting Test (FIST), Fugl-Meyer Assessment Upper Extremity (FMA-UE), Brunnstrom Recovery Stages of Arm (BRS-A) and Brunnstrom Recovery Stages of Hand (BRS-H) were performed to the patients. The results of our study showed that there was a strong positive correlation was found between TIS and FIST (r = 0.765, p < 0.001). There was also a positive moderate correlation between TCT and FIST, FMA-UE, BRS-A and BRS-H (r = 0.67, r = 0.49, r = 0.49, r = 0.44; p < 0.05; respectively). There was a positive moderate correlation between TIS and FMA-UE, BRS-A and BRS-H (r = 0.67, r = 0.65 and r = 0.58; p < 0.005; respectively). In conclusion, trunk control has been shown to be a factor associated with sitting balance and upper extremity function in patients with subacute stroke.

The purpose of the study was to investigate the reliability and validity of the Turkish version of the Sitting Balance Scale (SBS-T). SBS-T was tested with 60 individuals with stroke. Test-retest reliability was calculated with the Intraclass Correlation Coefficient (ICC). The Trunk Impairment Scale (TIS), Function in Sitting Test (FIST), The Berg Balance Scale (BBS), and Barthel Index (BI) were used to test the validity of SBS-T. The internal consistency of the SBS-T items was calculated with the Cronbach Alpha Analysis. Factor analysis and hypothesis testing were used for construct validity. Ceiling and floor effects were calculated for reliability. The intra-observer ICC was found to be 0.970 and the inter-observer ICC value was 0.999. The Cronbach's Alpha Coefficient was detected to be 0.955. A high correlation was detected between SBS-T and TIS, BBS, FIST, and BI (r = 0.861, p = 0.001; r = 0.849, p = 0.001; r = 0.906, p = 0.001; r = 0.848, p = 0.001, respectively). As a result of the factor analysis, it was found that the scale was determined by one single factor. No ceiling and floor effects were detected. The Turkish version of the SBS is a valid and reliable scale for predicting mobility and functionality in stroke for use in clinical and scientific studies. NCT04801927.

Background: Approximately 60% of adverse events in skilled nursing facilities are likely preventable. This provides an opportunity to improve care and decrease costs for ill, and especially aged, patients. The primary line of defense against adverse events in these facilities are the nurses caring for these patients each day. Nurses are responsible for recognizing early warning signs of illness and preventing falls and other complications. The care of patients with multiple comorbidities requires nurses to attend to an often overwhelming set of interacting details. Objective: Our goal is to operationalize standards of care that can be implemented by nursing staff at skilled nursing and long-term care facilities in a manner complementing their natural workflow and facilitating patient interaction and shift documentation. To improve point of care patient management, nurses require a mobile solution that can guide their patient care unobtrusively. Methods: Nurses at a Boston-area 100-bed skilled nursing/long-term care facility used our solution consisting of an app on a mobile device together with a Web-based administration and reporting system. Our custom software running on an iPod Touch device implements an adaptive methodology for succinctly guiding nurses through a systematic review of systems, a physical exam, a fall risk protocol, and other assessments suitable to their roles in the nursing facility. Dynamically created checklists that prescribe appropriate and immediate nursing interventions are automatically presented to the nurses following each assessment based on the data collected. The software utilizes behavioral “nudges” to nurse-users to minimize errors and improve speed of data entry. Additionally, a custom content creation system allows for high-level abstraction of protocol logic, enabling real-time improvement and customization of complex protocol algorithms without the need for error-prone software programming. These methods facilitate automated reporting that aids the structured thought processes of providers and caregivers. Results: Pilot results were acquired using qualitative surveys and free-form interviews. Nurses reported a high facility after only an initial 15-minute training session. All nurses confirmed that having access to an efficient and mobile care facilitation device improved the likelihood of identifying patient complications. They also felt that a mobile documentation system lowered error rates by encouraging real-time documentation. Furthermore, systematic data gathering provided an improved level of documentation both in terms of comprehensiveness and clarity. Nurses claimed the system increased efficiency and lowered the overall time required for combined patient assessment and documentation. Most importantly, staff satisfaction was highly positive, encouraging continued usage of the intervention. Conclusions: Technological interventions at skilled nursing facilities, when implemented to address the point-of-care needs of nursing personnel, can positively impact quality improvement goals, empower nursing staff, and improve patient care. The suite of tools developed here enables the operationalization of standards of care with sufficient comprehensiveness to address a sufficient portion of the complexity faced in daily nursing duties. We conclude that access to real-time protocols has a highly beneficial effect on nursing care. [iproc 2016;2(1):e31]

In California, >29,000 residents in skilled nursing facility (SNFs) were diagnosed with novel coronavirus disease 2019 (COVID-19) between March 2020 and November 2020. Prior research suggests that SNFs serving racially and ethnically minoritized residents often have fewer resources and lower quality of care. We performed a cross-sectional analysis of COVID-19 incidence among residents in California SNFs, assessing the association of SNF-level racial and ethnic compositions and facility- and neighborhood-level (census tract- and county-level) indicators of socioeconomic status (SES). SNFs were grouped based on racial and ethnic composition using data from the Centers for Medicare and Medicaid Services; categories included SNFs with ≥88% White residents, SNFs with ≥32% Black or Latinx residents, SNFs with ≥32% Asian residents, or SNFs not serving a high proportion of any racial and ethnic composition (mixed). SNF resident-level COVID-19 infection data were obtained from the National Healthcare Safety Network from May 25, 2020 to August 16, 2020. Multilevel mixed-effects negative binomial regressions were used to estimate incidence rate ratios (IRR) for confirmed COVID-19 infections among residents. Among 971 SNFs included in our sample, 119 (12.3%) had ≥88% White residents; 215 (22.1%) had ≥32% Black or Latinx residents; 78 (8.0%) had ≥32% Asian residents; and 559 (57.6%) were racially and ethnically mixed. After adjusting for confounders, SNFs with ≥32% Black or Latinx residents (IRR=2.40 [95% CI=1.56, 3.68]) and SNFs with mixed racial and ethnic composition (IRR=2.12 [95% CI=1.49, 3.03]) both had higher COVID-19 incidence rates than SNFs with ≥88% White residents. COVID-19 incidence rates were also found to be higher in SNFs with low SES neighborhoods compared to those in high SES neighborhoods. Public health personnel should consider SNF- and neighborhood-level factors when identifying facilities to prioritize for COVID-19 outbreak prevention and control.

Telemedicine in skilled nursing facilities (SNFs) has the potential to improve access and timeliness of care. During the COVID-19 pandemic in 2020 to 2022, telemedicine coverage expanded, but little is known about patterns of use in SNFs. To describe patterns of telemedicine use in SNFs. This cohort study used 2018 to 2022 Medicare fee-for-service claims and Minimum Data Set 3.0 records to identify short- and long-term care SNF residents. Clinician visits were grouped into routine SNF visits (ie, regular primary care within SNF) and other outpatient visits (ie, with non-SNF affiliated primary and specialty care clinicians). Using a difference-in-differences approach, assessments included whether off-hours visits (measured as weekend visits), new specialist visits, psychiatrist visits, or visits for residents with limited mobility changed differentially between 2018 to 2019 and 2020 to 2021 for SNFs with high compared with low telemedicine use in 2020. Telemedicine adoption at SNF after 2020. Number and proportion of telemedicine SNF and outpatient visits. Across 15 434 SNFs and 4 463 591 residents from the period January 2019 through June 2022 (mean [SD] age, 79.7 [11.6] years; 61% female in 2020), telemedicine visits increased from 0.15% in January 2019 to February 2020 to 15% SNF visits and 25% outpatient visits in May 2020. By 2022, telemedicine dropped to 2% of SNF visits and 8% of outpatient visits. The proportion of SNFs with any telemedicine visits annually dropped from 91% in 2020 to 61% in 2022. The facilities with high telemedicine use were more likely to be rural (adjusted odds ratio vs urban, 2.06; 95% CI, 1.77 to 2.40). Psychiatry visits differentially increased in high vs low telemedicine-use SNFs (20.2% relative increase; 95% CI, 1.2% to 39.2%). In contrast, there was little change in outpatient visits for residents with limited mobility (7.2%; 95% CI, -0.1% to 14.6%) or new specialist visits (-0.7%; 95% CI, -2.5% to 1.2%). In this cohort study of SNF residents, telemedicine was rapidly adopted in early 2020 but subsequently stabilized at a low use rate that was nonetheless higher than before 2020. Higher telemedicine use in SNFs was associated with improved access to psychiatry visits in SNFs. A policy to encourage continued telemedicine use may facilitate further access to important services as the technology matures.

Functional Recovery Rate: A Feasible Method for Evaluating and Comparing Rehabilitation Outcomes Between Skilled Nursing Facilities

The Centers for Medicare & Medicaid Services (CMS) Nursing Home Quality Initiative aims to improve quality through performance measurement. We describe quality improvement (QI) changes that skilled nursing facilities (SNFs) reported making in response to CMS performance measurements and whether reported QI changes were associated with better performance on CMS performance measures. Nationally representative survey. A total of 15,475 SNFs that reported quality performance on Nursing Home Compare in 2016. A total of 1,182 SNFs (58% of random sample of 2,045 SNFs). Adoption of 22 possible QI changes, grouped into seven categories (organizational culture, health information technology, care process redesign, provider incentives, changes to staffing responsibilities, performance monitoring, and measure-specific QI initiatives and technical assistance); performance on the CMS Nursing Home Compare Five-Star Quality Rating System's quality measure rating. SNFs reported making an average of 13 QI changes (interquartile range = 11-16 changes). SNFs mostly commonly reported becoming a learning organization (87%) and providing training to staff on QI strategies (87%). After controlling for patient and facility characteristics, larger SNFs were more likely to obtain assistance on measure reporting from QI organizations and use provider champions than smaller SNFs by 14 and 11 percentage points, respectively. Rural SNFs and SNFs with higher proportions of disabled, black, or Hispanic residents adopted QI changes at similar rates as other SNFs. Of the 22 QI changes, 20 were considered at least somewhat helpful by more than 80% of adopting SNFs. Implementation of all 22 QI changes (vs no changes) was associated with a .48-star higher quality measure rating (95% confidence interval = .003-.98 stars; P = .05). In response to CMS measurement programs, SNFs reported making substantial QI investments that were associated with better performance on CMS quality measures. To guide future SNF investments in QI, work is needed to identify the QI changes that yield the greatest performance improvements.

Delivering on quality measures: Six new CMS SNF quality measures

Addressing Skilled Nursing Facilities' COVID-19 Psychosocial Needs Via Staff Training and a Process Group Intervention

Risk of Readmission After Discharge From Skilled Nursing Facilities Following Heart Failure Hospitalization: A Retrospective Cohort Study

Early COVID-19 Successes in Skilled Nursing Facilities in San Francisco.

Background: The CDC Core Elements of Antibiotic Stewardship (AS) include 7 evidence-based best practices adapted for a variety of healthcare settings, including nursing homes. We aimed to identify barriers and facilitators related to AS implementation in skilled nursing facilities (SNFs) within 18 months of the CMS mandate for AS implementation in SNFs, and to examine their relevance to the CDC’s Core Elements for Nursing Homes. Methods: We conducted 56 semistructured interviews with administrators, clinicians, and nonclinical staff at 10 SNFs in urban, suburban, rural, and border regions of Arizona. All interviews were recorded, transcribed, and imported into NVivo v12.0 software for constant comparative analysis by 3 researchers using a priori and emergent codes. After iterative coding, we confirmed high interrater reliability (κ = 0.8), finalized the code book, and used matrix coding queries to examine relationships and generate themes. Results: We identified 7 themes as “influencers” that were less (barrier) or more (facilitator) supportive of AS in SNFs. Intra- and interfacility communication were the most frequently described: respondents described stronger communication within the SNF and between the SNF and hospitals, labs, and pharmacies as critical to robust AS implementation. Other influencers included AS education, antibiotic tracking systems, SNF prescribing norms, human resources, and diagnostic resources. The Core Elements were reflected in all influencer themes except interfacility communication between SNFs and hospitals. Additionally, themes pertaining to systems emerged as critical to successful AS implementation, including the need to address: the interactions of multiple roles across the traditional SNF hierarchy, stewardship barriers from the lens of patient-level concerns (as opposed to population-level concerns), the distinction between antibiotic prescribing gatekeepers and stewardship gatekeepers, and care transition policies and practices. The Core Elements target many aspects of these systems themes—for example, they recognize the importance of creating a culture of stewardship. However, they do not address care transition policies or procedures beyond recommending that transfer-initiated antibiotics be tracked and verified. Conclusions: Because the interactions of various agents within and beyond the SNF can facilitate or inhibit stewardship in complex ways, our findings suggest the use of a systems approach to AS implementation that prioritizes communication within the SNF hierarchy, and between SNFs and hospitals, diagnostic facilities, and pharmacies. When followed, the CDC’s Core Elements can provide crucial guidance. However, SNFs need support to overcome the challenges of incorporating these elements into policy and practice. Additionally, more work is needed to understand and enhance stewardship-related care transition, which remains under-addressed by the CDC.Disclosures: NoneFunding: None

Background: Inpatient rehabilitation facilities (IRFs) are central to post-stroke recovery, yet large-scale analyses of the association of post-cute IRF care with major adverse cardiovascular events (MACE) among acute ischemic stroke (AIS) survivors are lacking. We evaluated the association between discharge to IRF, compared to home (with or without home health services) or skilled nursing facilities (SNFs), and the 1-year risk of MACE and other vascular outcomes. Methods: We identified adult AIS survivors (≥18 years) from statewide inpatient and emergency department databases of Florida, New York, Maryland, Washington, and Georgia (2016–2019). We fit multivariable Cox regression models to evaluate the association of IRF care with the 1-year risk of experiencing MACE (a composite of AIS, intracerebral hemorrhage [ICH], vascular death [VD], and acute myocardial infarction [AMI]), VD, and all-cause mortality. Fine-Gray models, with death as a competing risk, were used for 1-year recurrent AIS (r-AIS), ICH, and AMI. Adjusted hazard ratios (aHR), sub-distribution hazard ratios (aSHR), and 95% CIs are reported. Results: Among 316,499 AIS survivors (median age [IQR]: 71 [61–81] years; 49.1% female), 63.6% were discharged home, 16.0% to IRF, and 20.4% to SNF. Patients discharged home (53.5%) or to IRF (51.4%) were predominantly male (vs. SNF: 42.3%). Median age was lower for home (68 years) and IRF (70 years) than SNF (80 years). Medicare was most common among SNF discharges (86%), while private insurance was more frequent in home (22.9%) and IRF discharges (17.6%) than SNF (6.3%). At 1 year, 6.7% of AIS patients experienced MACE, and 6.6%, 0.3%, 0.9%, 0.5%, and 2.0% experienced r-AIS, ICH, AMI, VD, and mortality, respectively. IRF discharge was associated with a lower risk of MACE (aHR, 95% CI: 0.79, 0.75–0.82 vs. home; 0.76, 0.73–0.80 vs. SNF), r-AIS (aSHR, 95% CI: 0.78, 0.74–0.81 vs. home; 0.76, 95% CI 0.72–0.80 vs. SNF), AMI (aSHR, 95% CI: 0.84, 0.75–0.94 vs. home; 0.89, 0.78–1.01 vs. SNF), ICH (aSHR, 95% CI: 0.81, 0.66–0.99 vs. SNF), VD (aHR 95% CI: 0.83, 0.71–0.98 vs. SNF) and all-cause mortality (aHR 95% CI: 0.65, 0.60–0.70 vs. SNF). Conclusions: Post-acute IRF care represents a modifiable target to reduce adverse vascular events after AIS. However, only 16% of survivors receive IRF care, with marked age, sex, and insurance disparities. Expanding access to IRFs potentially offers an opportunity to improve population-level outcomes among AIS survivors.

BackgroundMedicare Advantage (MA) and Medicare fee-for-service (FFS) plans have different financial incentives. Medicare pays predetermined rates per beneficiary to MA plans for providing care throughout the year, while providers serving FFS patients are reimbursed per utilization event. It is unknown how these incentives affect post-acute care in skilled nursing facilities (SNFs). The objective of this study was to examine differences in rehabilitation service use, length of stay, and outcomes for patients following hip fracture between FFS and MA enrollees.Methods and findingsThis was a retrospective cohort study to examine differences in health service utilization and outcomes between FFS and MA patients in SNFs following hip fracture hospitalization during the period January 1, 2011, to June 30, 2015, and followed up until December 31, 2015. We linked the Master Beneficiary Summary File, Medicare Provider and Analysis Review data, Healthcare Effectiveness Data and Information Set data, the Minimum Data Set, and the American Community Survey. The 6 primary outcomes of interest in this study included 2 process measures and 4 patient-centered outcomes. Process measures included length of stay in the SNF and average rehabilitation therapy minutes (physical and occupational therapy) received per day. Patient-centered outcomes included 30-day hospital readmission, changes in functional status as measured by the 28-point late loss MDS-ADL scale, likelihood of becoming a long-term resident, and successful discharge to the community. Successful discharge from a SNF was defined as being discharged to the community within 100 days of SNF admission and remaining alive in the community without being institutionalized in any acute or post-acute setting for at least 30 days. We analyzed 211,296 FFS and 75,554 MA patients with hip fracture admitted directly to a SNF following an index hospitalization who had not been in a nursing facility or hospital in the preceding year. We used inverse probability of treatment weighting (IPTW) and nursing facility fixed effects regression models to compare treatments and outcomes between MA and FFS patients. MA patients were younger and less cognitively impaired upon SNF admission than FFS patients. After applying IPTW, demographic and clinical characteristics of MA patients were comparable with those of FFS patients. After adjusting for risk factors using IPTW-weighted fixed effects regression models, MA patients spent 5.1 (95% CI -5.4 to -4.8) fewer days in the SNF and received 463 (95% CI to -483.2 to -442.4) fewer minutes of total rehabilitation therapy during the first 40 days following SNF admission, i.e., 12.1 (95% CI -12.7 to -11.4) fewer minutes of rehabilitation therapy per day compared to FFS patients. In addition, MA patients had a 1.2 percentage point (95% CI -1.5 to -1.1) lower 30-day readmission rate, 0.6 percentage point (95% CI -0.8 to -0.3) lower rate of becoming a long-stay resident, and a 3.2 percentage point (95% CI 2.7 to 3.7) higher rate of successful discharge to the community compared to FFS patients. The major limitation of this study was that we only adjusted for observed differences to address selection bias between FFS and MA patients with hip fracture. Therefore, results may not be generalizable to other conditions requiring extensive rehabilitation.ConclusionsCompared to FFS patients, MA patients had a shorter course of rehabilitation but were more likely to be discharged to the community successfully and were less likely to experience a 30-day hospital readmission. Longer lengths of stay may not translate into better outcomes in the case of hip fracture patients in SNFs.

Unplanned 30-day hospital readmissions are an important measure of hospital quality and a focus of national regulations. Skilled nursing facilities (SNFs) play an important role in the readmission process, but few studies have examined the factors that contribute to readmissions from SNFs, leaving hospitalists and other hospital-based clinicians with limited evidence on how to reduce SNF readmissions. To understand the perspectives of clinicians working at SNFs regarding factors contributing to readmissions. We prospectively identified consecutive readmissions from SNFs to a single tertiary-care hospital. Index admissions and readmissions were to the hospital's inpatient general medicine service. SNF clinicians who cared for the readmitted patients were identified and interviewed about root causes of the readmissions using a structured interview tool. Transcripts of the interviews were inductively analyzed using grounded theory methodology. RESULTS: We interviewed 28 clinicians at 15 SNFs. The interviews covered 24 patient readmissions. SNF clinicians described a range of procedural, technological, and cultural contributors to unplanned readmissions. Commonly cited causes of readmission included a lack of coordination between emergency departments and SNFs, poorly defined goals of care at the time of hospital discharge, acute illness at the time of hospital discharge, limited information sharing between a SNF and hospital, and SNF process and cultural factors. SNF clinicians identified a broad range of factors that contribute to readmissions. Addressing these factors may mitigate patients' risk of readmission from SNFs to acute care hospitals.