Patient Classification System Research Articles

Measuring patient acuity and nursing care needs in South Korea: application of a new patient classification system

BackgroundAn accurate and reliable patient classification system (PCS) can help inform decisions regarding adequate assignments for nurse staffing. This study aimed to evaluate the criterion validity of the Asan Patient Classification System (APCS), a new tertiary hospital-specific PCS, by comparing its rating and total scores with those of KPCS-1 and KPCS-GW for measuring patient activity and nursing needs.MethodsWe performed a retrospective analysis of the medical records of 50,314 inpatients admitted to the general wards of a tertiary teaching hospital in Seoul, South Korea in March, June, September, and December 2019. Spearman’s correlation and Kappa statistics according to quartiles were calculated to examine the criterion validity of the APCS compared with the KPCS-1 and KPCS-GW.ResultsThe average patient classification score was 28.3 points for APCS, 25.7 points for KPCS-1, and 21.6 points for KPCS-GW. The kappa value between APCS and KPCS-1 was 0.91 (95% CI:0.9072, 0.9119) and that between APCS and KPCS-GW was 0.88 (95% CI:0.8757, 0.8810). Additionally, Spearman's correlation coefficients among APCS, KPCS-1, and KPCS-GW showed a very strong correlation. However, 10.8% of the participants’ results were inconsistent, and KPCS-1 tended to classify patients into groups with lower nursing needs compared to APCS.ConclusionThis study showed that electronic health record-generated APCS can provide useful information on patients’ severity and nursing activities to measure workload estimation. Additional research is needed to develop and implement a real-world EHR-based PCS system to accommodate for direct and indirect nursing care while considering diverse population and dynamic healthcare system.

How the reliability and validity of the patient classification system can be ensured in daily nursing work? A follow-up study.

This study aimed to determine the reliability and validity of the RAFAELA patient classification system (PCS) for qualified and efficient nurses. The number of patients per nurse or diagnosis-based determination of nursing workload are imprecise measures that do not consider the variation in patients' care needs. Ensuring the reliability and validity of the RAFAELA is important for the efficient allocation of nursing resources. In this study, we investigated how the maintenance (parallel classification measurement and professional assessment of optimal nursing care intensity level measurement) of the RAFAELA was done with 9 years of follow-up data. The results were analysed using quantitative methods supplemented with qualitative audit descriptions. The STROBE checklist was used. The RAFAELA was used continuously in 44 units (40%). The length of use of the RAFAELA influenced the success of parallel classification measurements. Six per cent of units passed parallel classification measurement over 75% after 1-3 years' use, 42% after 4-6 years and 83% after 7-9 years. Among the units that used the RAFAELA PCS continuously, only four (9%) passed the professional assessment of optimal nursing care intensity level measurement. This study shows that ensuring the reliability and validity of the use of the RAFAELA is laborious, requires several years of use and continuous investments in nurses' skills and motivation. Qualified use of PCS is challenging, and organisations should invest to maintenance, training, support and user motivation. Each patient should be classified comprehensively, and nursing resources should be calculated correctly. In addition, utilisation of the nursing intensity level should be maximised. Kuopio University Hospital organisation permit number 73/2014. Information regarding individual patients or nurses was not available to the researchers. All materials are in the form of summary tables.

The clinical characteristics, novel predictive tool, and risk classification system for primary Ewing sarcoma patients that underwent chemotherapy: A large population-based retrospective cohort study.

This study aims to determine the independent prognostic predictors of cancer-specific survival (CSS) in patients with primary Ewing sarcoma (ES) that underwent chemotherapy and create a novel prognostic nomogram and risk stratification system. Demographic and clinicopathologic characteristics related to patients with primary ES that underwent chemotherapy between 2000 and 2018 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. CSS was the primary endpoint of this study. First, independent prognostic predictors of CSS identified from univariate and multivariate Cox regression analyses were used to construct a prognostic nomogram for predicting 1-, 3-, and 5-year CSS of patients with primary ES that underwent chemotherapy. Then, calibration curves and receiver operating characteristic (ROC) curves were used to evaluate the nomogram's prediction accuracy, while decision curve analysis (DCA) was used to evaluate the nomogram's clinical utility. Finally, a mortality risk stratification system was constructed for this subpopulation. A total of 393 patients were included in this study. Age, tumor size, bone metastasis, and surgery were independent prognostic predictors of CSS. The calibration curves, ROC, and DCA showed that the nomogram had excellent discrimination and clinical value, with the 1-, 3-, and 5-year AUCs higher than 0.700. Moreover, the mortality risk stratification system could effectively divide all patients into three risk subgroups and achieve targeted patient management. Based on the SEER database, a novel prognostic nomogram for predicting 1-, 3-, and 5- year CSS in patients with primary ES that underwent chemotherapy has been constructed and validated. The nomogram showed relatively good performance, which could be used in clinical practice to assist clinicians in individualized treatment strategies.

The SHID wound classification system for diabetic foot ulcer patients: a validity study

This study aimed to evaluate the predictive validity of the SHID (Suriadi, Haryanto, Imran dan Defa) wound classification system compared to TU (Texas University) and Wagner wound classification systems in Indonesia. A prospective cohort study included patients with diabetic foot ulcers at Kitamura wound clinic in Indonesia. A total of 111 diabetic foot ulcer patients were assessed with SHID, TU, and Wagner wound classification systems. Two postgraduate nursing students assessed 111 wounds of bedside patients and observed them for 4 weeks. The predictive validity test indicated that the cut-off score of ≤grade 2 for SHID was 74% and 97%, ≤grade IB for TU was 77% and 92%, then ≤grade 2 for Wagner was 84% and 71% for sensitivity and specificity, respectively. The area under the curve (AUC) in SHID, TU, and Wagner tools was 0.90 (95% CI: 0.828-0.950), 0.85 (95% CI: I0.766-0.910), and 0.86 (95% CI: 0.775-0.917), respectively. The Youden index for SHID, TU, and Wagner was 0.72%, 0.70%, and 0.55%, respectively. The wound classification systems are good tools for identifying diabetic foot ulcers. However, the newly developed SHID tool produced the best AUC and Youden Index values compared to the Wagner tool.

Modified Clavien-Dindo-Sink system is reliable for classifying complications following surgical treatment of early-onset scoliosis.

Appropriately measuring and classifying surgical complications is a critical component of research in vulnerable populations, including children with early-onset scoliosis (EOS). The purpose of this study was to assess the inter- and intra-rater reliability of a modified Clavien-Dindo-Sink system (CDS) classification system for EOS patients among a group of pediatric spinal deformity surgeons. Thirty case scenarios were developed and presented to experienced surgeons in an international spine study group. For each case, surgeons were asked to select a level of severity based on the modified CDS system to assess inter-rater reliability. The survey was administered on two occasions to allow for assessment of intra-rater reliability. Weighted Kappa values were calculated, with 0.61 to 0.80 considered substantial agreement and 0.81 to 1.00 considered nearly perfect agreement. 11/12 (91.7%) surgeons completed the first-round survey and 8/12 (66.7%) completed the second. Inter-observer weighted kappa values for the first and second survey were 0.75 [95% CI 0.56-0.94], indicating substantial agreement, and 0.84 [95% CI 0.70-0.98], indicating nearly perfect agreement, respectively. Intra-observer reliability was 0.86 (range 0.74-0.95) between the first and second surveys, indicating nearly perfect agreement . The modified CDS classification system demonstrated substantial to nearly perfect agreement between and within observers for the evaluation of complications following the surgical treatment of EOS patients. Adoption of this reliable classification system as a standard for reporting complications in EOS patients can be a valuable tool for future research endeavors, as we seek to ultimately improve surgical practices and patient outcomes. Level V.

A Novel Prognostic Nomogram and Risk Classification System for Predicting Cancer-Specific Survival of Postoperative Fibrosarcoma Patients: A Large Cohort Retrospective Study.

Background Fibrosarcoma (FS) is a typically invasive sarcoma formed by fibroblasts and collagen fibers. Currently, the standard treatment for FS is the surgical resection, but the high recurrence rate and poor prognosis limit the benefits of postoperative patients. Exploring what factors affect the benefit of postoperative patients is significant for guiding the implementation of surgical resection. Therefore, this study aims to construct a novel nomogram to predict the cancer-specific survival (CSS) of postoperative fibrosarcoma (POFS) patients. Methods The included patients were randomly assigned to the training and validation sets at a ratio of 7 : 3. CSS was indexed as the research endpoint. Firstly, univariate and multivariate Cox regression analyses were used on the training set to determine independent prognostic predictors and build a nomogram for predicting the 1-, 3-, and 5-year CSS of POFS patients. Secondly, the nomogram's discriminative power and prediction accuracy were evaluated by receiver operating characteristic (ROC) and the calibration curve, and a risk classification system for POFS patients was constructed. Finally, the nomogram's clinical utility was evaluated using decision curve analysis (DCA). Results Our study included 346 POFS patients, divided into the training (244) and validation sets (102). Multivariate Cox regression analysis demonstrated that tumor size, SEER stage, and tumor grade were independent prognostic predictors of CSS for POFS patients. They were used to create a nomogram. In the training and validation sets, the ROC curve showed that the 1-, 3-, and 5-year area under the curve (AUC) were higher than 0.700, indicating that the nomogram had good reliability and accuracy. DCA also showed that the nomogram has high application value in clinical practice. Conclusion The larger tumor size, higher tumor grade, and distant metastasis were independently related to the poor prognosis of POFS patients. The nomogram constructed based on the above variables could accurately predict the 1-, 3-, and 5-year CSS of POFS patients. So, the nomogram and risk classification system we built might help make accurate judgments in clinical practice, optimize patient treatment decisions, maximize postoperative benefits, and ultimately improve the prognosis of POFS patients.

The West China Hospital radiographic classification for fibrous dysplasia in femur and adjacent bones: A retrospective analysis of 205 patients.

ObjectiveThis study aims to investigate the reliability and clinical outcome of a newly developed classification system for patients with fibrous dysplasia (FD) of the femur and adjacent bones, optimizing its evaluation and management.MethodsA total of 205 patients (121 female and 84 male) with FD in the femur and adjacent bones were included in this retrospective study. All affected femurs were measured and treated based on this classification at our institution between 2009 and 2019. Based on previous studies and extensive clinical follow‐up, we cautiously proposed the West China Hospital radiographic classification for FD in femur and adjacent bones following corresponding treatment options. There are five types with five radiographic features, including proximal femur bone loss, coxa vara, femoral shaft deformity, genu valgum, and hip arthritis. The intraobserver and interobserver reproducibility of this classification was assessed by four observers using the Cohen kappa statistic. The clinical outcome was evaluated using the criteria of Guille.ResultsAt a median follow‐up of 60 months (range 6–120), 205 patients (median 34.8 years old, range 18–73 years old) were categorized into the following five types: Type I 31.7%, Type II 30.2%, Type III 20.5%, Type IV 10.2%, and Type V 7.3%. The mean interobserver and intraobserver kappa scores were 0.85 (range 0.77–0.89) and 0.85 (range 0.79–0.92), respectively. For clinical outcomes, there was no significant difference in the postoperative Guille score for Type I patients (mean 9.01 ± 1.22). There was a significant increase in the postoperative Guille score in Type II, III, IV, and V, compared to the preoperative values (P < 0.01). For complications, two Type III patients reported pain, and one Type III patient had mild‐to‐moderate Trendelenburg gait. One Type IV patient had a mild Trendelenburg gait. And two Type V patients still had mild limping.ConclusionThis classification is reproducible and serves as a tool for evaluating and treating FD in the femur and adjacent bones. Therefore, we recommend this classification for the diagnosis and treatment of FD‐related deformities in the femur and adjacent bones.

A Hospital's Roadmap for Improving Nursing Excellence Using AACN's Healthy Work Environment Standards.

A Hospital's Roadmap for Improving Nursing Excellence Using AACN's Healthy Work Environment Standards.

Real-world data to enable large-scale assessment of WHO CNS5 glioma classification.

2018 Background: In 2021, the WHO revised its classification of central nervous system tumors (WHO CNS5) around IDH status and inclusion of key somatic alterations in addition to histopathological traits. While providing a more specific classification system for patients, the guidelines introduce new logistical challenges for pathologists, relying on multi-modal data for accurate classification. In this study, we use a combined clinical/molecular real world dataset to reclassify a cohort of adult diffuse gliomas and evaluate prognostic impact using real-world overall survival (rwOS). Methods: We retrospectively analyzed a de-identified dataset of 2,703 adult diffuse glioma samples profiled with the Tempus xT assay (DNA-seq of 595-648 genes at 500x coverage, whole-exome capture RNA-seq). Original diagnoses were identified from sample pathology reports. We assessed mutation status for genes relevant to WHO CNS5 classification ( IDH1/2, ATRX, and TERT) and copy number alterations for genes CDKN2A/B and EGFR, as well as arms 1p, 19q and chromosomes 7 and 10. Samples were excluded if the original diagnosis or molecular findings indicated a diffuse midline or pediatric glioma. Necrosis and microvascular proliferation were inferred from gene expression profiles using machine learning. rwOS was defined as time from original diagnosis until death. To account for left truncation, samples were only considered at risk of death after study entry ( e.g., date of sequencing if sequenced as part of clinical care). Results: Using relevant clinicopathological traits and genomic alterations, we assigned WHO CNS5 labels to all samples—512 astrocytoma, IDH -mutant; 186 oligodendroglioma, IDH -mutant, and 1p/19q co-deleted; and 2,005 glioblastoma, IDH -wildtype (IDH- wt). We further stratified astrocytoma, IDH -mutant samples by grade, resulting in 308 classified as grade 4. Of the samples with an original diagnosis of astrocytoma, oligodendroglioma, or glioblastoma, 13.9% changed under the WHO CNS5 guidelines, including 166 glioblastomas re-classified as grade 4 astrocytoma, IDH -mutant, and 125 astrocytomas re-classified as glioblastoma, IDH -wt. WHO CNS5 reclassification resulted in more accurate prognostic stratification (rwOS) than the original diagnosis (likelihood ratio test; P &lt; 8e-32). For example, the observed hazard ratio (HR) of an original astrocytoma diagnosis (versus glioblastoma) (Cox PH Model; HR = 0.42[CI:0.32,0.56]) was less extreme than the observed HR of an astrocytoma, IDH -mutant diagnosis (versus glioblastoma, IDH -wt) under WHO CNS5 (Cox PH Model; HR =0.08[CI:0.04,0.19] grades 2-3; HR = 0.18[CI:0.12,0.26] grade 4). Conclusions: This work highlights the utility of comprehensive molecular profiling in classifying patients with adult diffuse gliomas according to the newest WHO CNS5 guidelines, and confirms the improved prognostic stratification within a retrospective real-world dataset.

Predicting High-risk and High-cost Patients for Proactive Intervention.

It is well known that 20% of the patients incur 80% of health care costs and many diseases and complications can be prevented or ameliorated with prompt intervention. One of the well-recognized strategies for cost reduction and better outcomes is to predict or identify high-risk and high-cost (HRHC) patients for proactive intervention. The objective of this study was to develop a predictive model that can be used to identify HRHC patients more accurately for proactive intervention. This is an observational study using fiscal year (FY) 2018 administrative data to predict FY 2019 total cost at the patient level. All 5,676,248 patients who received care in both FYs 2018 and 2019 from the Veterans Health Administration were included in the analyses. The Veterans Health Administration Corporate Data Warehouse was our main data source. With split-sample analyses, 3 sets of patient comorbidities and 5 statistical models were assessed for the highest predictive power. The Box-Cox regression using comorbidities designated by the expanded CCSR (Clinical Classifications Software Refined) groups as predictors yielded the highest predictive power. The R2 reached 0.51 and 0.37 for the transformed and raw scale cost, respectively. The predictive model developed in this study exhibits substantially higher predictive power than what has been reported in the literature. The algorithm based on administrative data and a publicly available patient classification system can be readily implemented by other value-based health systems to identify HRHC patients for proactive intervention.

Factors associated with the workload of health professionals in hospital at home: a systematic review

BackgroundUnderstanding the factors related to workload, could help hospital at home (HaH) managers to make decisions on the most appropriate and efficient use of the HaH services. Published studies on this topic are scarce, so we have conducted a systematic review to identify such factors according to published evidence.MethodsDue to the heterogeneity of HaH models, HaH was defined as a care that provides a set of medical and nursing care and attention of hospital rank to patients at home, when they no longer require hospital infrastructure but still need active monitoring and complex care. The electronic data base literature search was conducted in MEDLINE (Ovid), EMBASE (Ovid), and Cinahl (EBSCOhost) from inception to December 2021, including grey literature. Search terms related to `hospital at home´, `workload´ and `care time´ were used. There was no restriction on language, type of study or year of publication. Quality of included studies was assessed using the Critical Appraisal Skills Programme (CASP) checklist and certainty in the body of evidence was assessed using the GRADE Pro Tool. Results were summarised in a tabulated format.ResultsEighteen studies with 56,706 patients were included. Workload was measured as time, number of visits or both. The predictive factors of the workload included variables related to patient characteristics and other valid and reliable patient classification systems, as well as characteristics of the institutions where the studies were conducted. The factors associated with higher workloads were: being older, male, living in a rural environment, presenting a higher number of diagnoses, having worse functional status and being unable to assume self-care.ConclusionsThe identified predictors of workload are mostly associated with home nursing care. The results could be useful and applicable to different organisational models of HaH health systems. More studies that include physicians and proxy measures of workload are needed.

Deep Learning-based Decision Support System for classification of COVID-19 and Pneumonia patients

The fast spread of Coronavirus (COVID-19) poses a huge risk to people all around the world. Recently, COVID-19 testing kits have been unavailable due to rise in effected people and large demand of tests. Keeping the urgency of the situation in mind, an automatic diagnosis method for early detection of COVID-19 is needed. The proposed deep learning decision support system (DSS) for COVID-19 employs MobileNet v2 Deep learning (DL) model for effective and accurate detection. Here we collected Cough auscultations through self-designed digital sensor. The primary experimental results show that the maximum accuracy for training is around 99.91%, and the maximum accuracy for validation is 98.61%, with 97.5% precision, 98.5%recall, and 98% F1-score. The Deep Learning-based model described here strives for similar performance to medical professionals and can help pulmonologist/radiologists increase their working productivity.

Prognostic value of a new clinically-based classification system in patients with CMML undergoing allogeneic HCT: a retrospective analysis of the EBMT-CMWP.

Recently a new three-group clinical classification was reported by an International Consortium to stratify CMML patients with regard to prognosis. The groups were defined as follows: (1) Myelodysplastic (MD)-CMML: WBC ≤ 10 × 109/l, circulating immature myeloid cells (IMC) = 0, no splenomegaly; (2) MD/MP (overlap)-CMML: WBC 10-20 × 109/l or WBC ≤ 10 × 109/l but IMC > 0 and/or splenomegaly; (3) Myeloproliferative (MP)-CMML: WBC > 20 × 109/l. By analysing EBMT Registry patients who underwent allo-HCT for CMML between 1997 and 2016, we aimed to determine the impact of this classification on transplantation outcome and to make a comparison with the conventional WHO classification (CMML-0/CMML-1/CMML-2). Patient grouping was based on the data registered at time of transplantation, with IMC replaced by peripheral blasts. Among 151 patients included in the analysis, 38% were classified as MD-CMML, 42% as MD/MP-CMML and 20% as MP-CMML. With a median survival of 17 months in the whole series, MD-CMML patients were distinguished as a low-risk group with higher CR rate at transplant and a longer post-transplant 2-year progression-free survival in comparison to others (44.5% vs 33.5%, respectively), whereas the WHO classification was superior in identifying high-risk patients (CMML-2) with inferior survival outcomes.

Data Analysis of COVID-19 Hospital Records Using Contextual Patient Classification System.

Humanity today is suffering from one of the most dangerous pandemics in history, the Coronavirus Disease of 2019 (COVID-19). Although today there is immense advancement in the medical field with the latest technology, the COVID-19 pandemic has affected us severely. The virus is spreading rapidly, resulting in an escalation in the number of patients admitted. We propose a contextual patient classification system for better analysis of the data from the discharge summary available from the research hospital. The classification was done using the Knuth–Morris–Pratt algorithm. We have also analyzed the data of COVID-19 and non-COVID-19 patients. During the analysis, studies on the medicines, medical services and tests, pulse count, body temperature, and the overall effect of age and gender was done. The death versus survival ratio for the COVID-19 positive patients has also been studied. The classification accuracy of the contextual patient classification system achieved was 97.4%. The combination of data analysis and contextual patient classification will be helpful to all the sectors to be better prepared for any future waves of the COVID-19 pandemic.

ASO Visual Abstract: Prognostic Performance of Alternative Lymph Node Classification Systems for Patients with Medullary Thyroid Cancer—A Single-Center Cohort Study

ASO Visual Abstract: Prognostic Performance of Alternative Lymph Node Classification Systems for Patients with Medullary Thyroid Cancer—A Single-Center Cohort Study

Beyond patient classification: the "hidden" face of nursing workload.

This is a theoretical-reflective essay, which aimed to reflect on the centralization of Patient Classification Systems in workload and hospital nursing staff sizing. The reflexive interpretations were guided by two axes: Patient Classification Systems : constitution and utilities; and "Hidden" nursing activities in workload measurement. The first evidences the importance and the role of these instruments in workload identification and in hospital nursing staff sizing, exemplifying several possibilities to be used by nurses. On the other hand, with the second axis, it is clear that there are many nursing activities that are not sensitive to the application (even if systematic) of these means of patient assessment. Therefore, nursing workload measurement may be underestimated. It was inferred that the complexity of practice environments requires a macro and micro institutional look at the nursing workload measurement, especially when considered for workforce planning/sizing purposes.

An Analysis of Tasks of Nurses Caring for Patients with COVID-19 in a Nationally-Designated Inpatient Treatment Unit

The purpose of this study was to provide foundational knowledge on nursing tasks performed on patients with COVID-19 in a nationally-designated inpatient treatment unit. This study employs both quantitative and qualitative approaches. The quantitative method investigated the content and frequency of nursing tasks for 460 patients (age ≥ 18 y, 57.4% men) from January 20, 2020, to September 30, 2021, by analyzing hospital information system records. Qualitative data were collected via focus group interviews. The study involved interviews with three focus groups comprising 18 nurses overall to assess their experiences and perspectives on nursing care during the pandemic from February 3, 2022, to February 15, 2022. The data were examined with thematic analysis. Overall, 49 different areas of nursing tasks (n = 130,687) were identified based on the Korean Patient Classification System for nurses during the study period. Among the performed tasks, monitoring of oxygen saturation and measuring of vital signs were considered high-priority. From the focus group interview, three main themes and eleven sub-themes were generated. The three main themes are "Experiencing eventfulness in isolated settings," "All-around player," and "Reflections for solutions." During the COVID-19 pandemic, it is imperative to ensure adequate staffing levels, compensation, and educational support for nurses. The study further propose improving guidelines for emerging infectious diseases and patient classification systems to improve the overall quality of patient care.

Classificação do nível de complexidade assistencial dos pacientes em hospital oncológico

ABSTRACT Objective To classify the level of complexity of care required from Nursing by hospitalized oncology patients. Methods This is an observational, sectional, quantitative study, carried out daily with oncology patients in the Clinical and Surgical Oncology inpatient units of a cancer treatment reference hospital during a three-month period. The collection was carried out through the application of a semi-structured questionnaire and an instrument of patient classification by Fugulin et al. (2007). Results 242 patients were interviewed and 1309 evaluations were performed, with a greater number of males and those with incomplete elementary school education. There was a higher occurrence of cancer in the gastrointestinal system and female reproductive system, respectively, in the admission of Clinical and Surgical Oncology, with higher occupancy rate in the months of June and May, in that order. The behavior observed was quite similar in both admissions, corresponding, respectively, to patients who fell into minimal (33.1%; 35.1%) and intermediate care (30.2%; 37.5%). Conclusion and implications for practice The patient classification and dimensioning system in Nursing in oncology deserves further discussion and lacks validated instruments capable of representing the real situation of care.

Magnetic Resonance Angiography of the Hand Vasculature in Patients With Systemic Sclerosis and Systemic Lupus Erythematosus.

When patients with systemic sclerosis (SSc) and systemic lupus erythematosus (SLE) develop digital ischemia, conventional angiography (CA) is traditionally used to assess hand vasculature. Recently, Chang et al described an angiographic classification system for patients with SSc. Conventional angiography uses intravascular contrast agents that are nephrotoxic and vasoconstrictive. Owing to these limitations, this study assesses the use of contrast-enhanced magnetic resonance angiography (MRA) as an alternative to CA to evaluate hand vasculature in patients with digital ischemia. This retrospective case series reports on 38 contrast-enhanced MRAs of hand vasculature from 30 symptomatic patients with SSc (N = 21) or SLE (N = 9). The radial and ulnar arteries (RA, UA) and the superficial and deep palmar arches were evaluated at standard reference points both quantitatively and qualitatively for their diameter, patency, and Chang classification. In SSc MRAs (n = 26), the UA was significantly smaller than the RA and was occluded in 46%. In SLE MRAs (n = 12), the UA and RA had no difference in diameter and the UA was occluded in 25%. In SSc, the most common Chang classification was type 2 (UA involvement) in 44%. In SLE, the most common Chang classification was type 4 (UA and RA involvement) in 45%, with 18% classified as type 2. Contrast-enhanced MRA used to assess hand vasculature in SSc patients with digital ischemia shows similar patterns of vascular involvement as previously demonstrated by CA. While vascular involvement in SSc predominantly involves the UA, the RA is also frequently involved in SLE.

A Simple Diagnosis-Related Groups-Based Reimbursement System Is Cost Ineffective for Elderly Patients With Displaced Femoral Neck Fracture Undergoing Hemiarthroplasty in Beijing.

Displaced femoral neck fractures (FNF) in the elderly are a major public health concern that necessitates hemiarthroplasty (HA) as the mainstay treatment option. Diagnosis-Related Groups (DRG) are a patient classification system that categorizes patients based on the resources expended on them. The first objective of this study was to evaluate if a simplified DRG-based reimbursement system in Beijing would lower total HA treatment costs for elderly patients with displaced FNF. In addition, we aimed to determine how age, gender, year of admission, length of in-hospital stay, and the Charlson index affected total treatment costs. This retrospective study included 513 patients from the Peking Union Medical College Hospital. The patients were diagnosed with unilateral displaced femoral neck fractures and had HA. Medical information was gathered, including baseline demographic and clinical data, as well as treatment costs. Patients were classified into two groups: those who spent more than the predetermined cut-off cost and those who did not. The cost did not include the use of a bipolar prosthesis. Data from the two groups were compared, and multiple regression analysis models were constructed. The median total cost of treatment was ¥49,626 ($7,316). The majority of the patients (89.7%; 460/513) were categorized as exceeding the cost cut-off. Multiple linear regression analysis revealed that total treatment cost was positively correlated with age (p < 0.01) and the duration of in-hospital stay (p < 0.01) but not with gender (p = 0.160) or the Charlson index (p = 0.548). On implementing the DRG-based reimbursement system, the overall treatment costs increased by ¥21,028 ($3,099) (p < 0.01). The implementation of simplified DRG-prospective payment systems did not result in a significant reduction in total treatment costs for elderly patients with FNF who underwent HA in Beijing. The overall cost of treatment was associated with several factors, including age, length of hospitalization, and year of admission.