The Minimum Data Set (MDS) Frequency data summarizes health status indicators for active residents currently in nursing homes. The MDS is part of the Federally-mandated process for clinical assessment of all residents in Medicare and Medicaid certified nursing homes. This process provides a comprehensive assessment of each resident's functional capabilities and helps nursing home staff identify health problems. Care Area Assessments (CAAs) are part of this process, and provide the foundation upon which a resident's individual care plan is formulated. MDS assessments are completed for all residents in certified nursing homes, regardless of source of payment for the individual resident. MDS assessments are required for residents on admission to the nursing facility, periodically, and on discharge. All assessments are completed within specific guidelines and time frames. In most cases, participants in the assessment process are licensed health care professionals employed by the nursing home. MDS information is transmitted electronically by nursing homes to the national MDS database at CMS. When reviewing the MDS 3.0 Frequency files, some common software programs e.g., ‘Microsoft Excel’ might inaccurately strip leading zeros from designated code values (i.e., "01" becomes "1") or misinterpret code ranges as dates (i.e., O0600 ranges such as 02-04 are misread as 04-Feb). As each piece of software is unique, if you encounter an issue when reading the CSV file of Frequency data, please open the file in a plain text editor such as ‘Notepad’ or ‘TextPad’ to review the underlying data, before reaching out to CMS for assistance.

The purpose of the project is to detect unreported Supplemental Security Income (SSI) recipient admissions to Title XIX institutions. A file containing SSN's of SSI recipients (all eligible individuals and members of eligible couples in current pay) will be matched against the Health Care Financing Administration's (HCFA) Minimum Data Set (MDS) database which contains admission, discharge, re-entry and assessment information about persons in Title XIX facilities for all 50 States and Washington, D.C. This database is updated monthly. The match will produce an output file containing MDS data pertinent to SSI eligibility on matched records. This data will be compared back to the SSR data to generate alerts to the Field Offices for their actions.

This dataset contains quality measures displayed on Nursing Home Compare, based on the resident assessments that make up the nursing home Minimum Data Set (MDS). Each row contains a specific measure for a nursing home and includes the four-quarter score average and scores for individual quarter.

The Patient Assessment File (PAF) database compiles the results of the Patient Assessment Instrument (PAI) questionnaire filled out for intermediate care Veterans Health Administration (VHA) patients. The PAI is filled out within two weeks of admission. It is also completed semi-annually on April 1st and October 1st for each patient by a registered nurse familiar with the patient. The PAI questions cover medical treatments, conditions, selected diagnoses, activities of daily living, behaviors, some rehabilitation therapies, and chronic respiratory support. The database is managed by the Geriatrics & Extended Care Strategic Health Care Group in the Office of Patient Care Services. It is currently running at the Austin Information Technology Center (AITC) and is stored in flat files. PAF's primary customer is the Allocation Resource Center (ARC) in Braintree MA. The ARC receives the data from AITC and combines it with data from the Patient Treatment File (PTF) which contains more detailed demographic and treatment information. The ARC builds ORACLE tables, assigning RUG II (Resource Utilization Group II) scores and weighted work units reflecting the level and type of care needed. The 16 different weighted work units, ranging from 479 to 1800, are a factor in the resource allocation and budget decisions on long-term care, and are used to measure efficiency. The data is also used in other reports to Central Office, the Veterans Integrated Service Networks, and the facilities. Several other units also use PAF information including the Decision Support System (DSS). Currently, PAF is in the process of being replaced by the Resident Assessment Instrument/Minimum Data Set (RAI/MDS). RAI/MDS uses a much more extensive questionnaire as its source of information. The RAI/MDS provides clinical data and care protocols in addition to the newer RUG III scores, and is required by the Centers for Medicare and Medicaid Service funded hospitals.

The Facility-Level Minimum Data Set (MDS) Frequency dataset provides information for active nursing home residents on topics, such as race/ethnicity, age, or marital status; discharge dispositions; hearing, speech, and vision; cognitive patterns; mood; functional abilities and goals; bladder and bowel; active diagnoses; health conditions; swallowing/nutritional status; oral/dental status; skin conditions; medications; special treatments, procedures, and programs; restraints and alarms; and participation in assessment and goal setting. Note: The MDS dataset contains more records than most spreadsheet programs can handle. The use of a database or statistical software is generally required. The dataset can be filtered to a more manageable size for use in a spreadsheet program by clicking on the “View Data” button. Additional filter information can be found in the methodology, if needed.

MDS – multidimensional scaling.For both samples, in more models than expected by chance the marginal effect of the MDS dimensions significantly improved model fit, over and above self-reported ethnicity. Self-reported ethnicity showed mixed statistical evidence of improving model fit conditional on the MDS dimensions.

The study has evaluated the association between measurable residual disease (MRD) determined using digital droplet PCR (ddPCR) and outcome after allogeneic stem cell transplantation for patients with myelodysplastic syndrome (MDS). The patient-specific mutations have been identified using next generation sequencing (NGS).

The dataset contains: 1. NGS data 2. MRD data 3. List of ddPCR-assays 4. Variants for ddPCR only identified at diagnosis 5. Variants of undetermined significance targeted by ddPCR 6. Regression analyses

Descriptive statistics and gender differences for all variables included in cluster and MDS analyses for Sample 2.

The Voice Conversion Challenge (VCC) 2016, one of the special sessions at Interspeech 2016, deals with speaker identity conversion, referred as Voice Conversion (VC). The task of the challenge was speaker conversion, i.e., to transform the voice identity of a source speaker into that of a target speaker while preserving the linguistic content. Using a common dataset consisting of 162 utterances for training and 54 utterances for evaluation from each of 5 source and 5 target speakers, 17 groups working in VC around the world developed their own VC systems for every combination of the source and target speakers, i.e., 25 systems in total, and generated voice samples converted by the developed systems. The objective of the VCC was to compare various VC techniques on identical training and evaluation speech data. The samples were evaluated in terms of target speaker similarity and naturalness by 200 listeners in a controlled environment. This section of the VCC repository contains the listening test results for four of the source-target pairs (two intra-gender and two cross-gender) in more detail. Multidimensional scaling was performed to illustrate where each system was perceived to be in an acoustic space compared to the source and target speakers and to each other. See also item 'The Voice Conversion Challenge 2016' (DOI: 10.7488/ds/1430)

SPSS Dataset with the ranking data of the health domains of the TOPICS-MDS as assessed by the participants of the first round of the Delphi study.

Detection of movements in the extremities of people with Parkinson disease was developed to enhance clinical assessments. This data represents the administration of online motor assessments to detect the movements in the extremities of people with Parkinson's disease by examiners certified in the Movement Disorders Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) (Goetz, et al., 2008).

Ten trained raters who were certified in the administration of the Movement Disorders Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) (Goetz, et al., 2008) conducted 10 online motor assessments for one patient with Parkinson disease. Each rater utilized a separate computer at different location in three continents. At the beginning of each session the patient was asked for his permission to record the session. Second, the investigator asked the patient about the current medications and weight. Third, the investigator announced each motor assessment by saying the number and the name of each task before conducting the task for all of the raters. Fourth, the investigator gave the patient the specific instructions for each task, demonstrated each task, and asked the participant to begin the task. The investigator didn't continue to demonstrate the task after the participant began the task. For the repetitive items the investigator asked the participant to perform the activities as fully and as fast as possible. After performing each task the raters were given one minute to write their scores. This process was repeated for all of the tasks. At the conclusion of the session the participant was excused after setting the next session date, and then all of the raters shared their scores with the investigator by email. Finally the investigator conducted a consensus conference to attain agreement on each score for each task.

One expert certified in the MDS-UPDRS (Goetz, et al., 2008) edited the original videotapes to extract only the administration of each task.The videotape segments correspond to the tasks of the protocol (3.17RTU: 3.17 Rest tremor amplitude upper limbs, 3.17RTUC: 3.17 Rest tremor amplitude upper limbs counting, 3.15PT: 3.15 Postural tremor of the hands, 3.4FT: 3.4 Finger tapping, 3.5HM: 3.5 Hand movements, 3.6PS: 3.6 Pronation-supination movements of the hands, 3.9ACU: 3.9 Arising from chair upper limbs).

1HI recovery ability is assessed by calculating the RMSE values on the Type I data using -fold cross validation, and these values are also called local RMSEs.2A correlation coefficient (CC value) is calculated from the pairwise distances among antigens for every two independent runs. The CC values in this table were calculated from different runs.3A maximum distance (MD value) refers to the difference between the maximum distance among any antigens in the benchmark cartography and that from the method being evaluated (either MC-MDS or metric MDS). The MD values in this table were calculated from different runs.4A pairwise distance RMSE (PD value) is the difference between the pairwise distances among all antigens in the benchmark cartography and those from the method being evaluated. The PD values in this table were calculated from different runs. The PD values for H3N2 data were not assessed since we do not know the ground truth of antigenic cartography for this dataset.5The value in the bracket is the standard deviation of the associated parameter.

The Veterans Equitable Resource Allocation (VERA) database, is operated by the Allocation Resource Center (ARC) in Braintree, MA. The ARC is part of the Resource Allocation & Execution Office of the Office of Finance. The database is developed from the Patient Treatment File, National Patient Care Database, Fee Basis Medical and Pharmacy System, Decision Support System (DSS) National extracts, DSS Derived Monthly Program Cost Report (MPCR), Resident Assessment Instrument (RAI) Minimum Data Set (MDS), Clinical Case Registry (CCR), and Home Dialysis Data Collection System, the Pharmacy Benefits Management database and the Consolidated Enrollment File. Most of the clinical data is Veterans Health Information Systems and Technology Architecture data which is transmitted to the Austin Information Technology Center (AITC) where it is retrieved by the ARC each month. The ARC also retrieves DSS cost data from the AITC as well. Some additional information is received from the Hines Pharmacy Benefits Management and the CCR databases. The data from these sources is combined to develop patient-specific care and cost data for each hospitalization or visit at the location or treatment level. Aggregate tables summarize this data for reporting and analysis purposes. The VERA databases are the basis for resource allocation in the Veterans Health Administration.

We have assessed the molecular profile of a cohort of 70 patients with MDS by next-generation sequencing (NGS) using cfDNA and compared the results to paired bone marrow (BM) DNA.

To identify viral pathogens in patients with secondary glaucoma associated with anterior segment uveitis and compare metagenomic deep sequencing (MDS) with enzyme-linked immunosorbent assay (ELISA) combined with Witmer-Desmonts coefficient (WDC) evaluation and real-time quantitative polymerase chain reaction (qPCR) on investigating pathogens in aqueous humor. Aqueous humor from 31 patients, including 22 Posner-Schlossman Syndrome and 9 other anterior uveitis, was assessed pathogens by ELISA combined with WDC evaluation, virus deoxyribonucleic acid (DNA) detection by real-time qPCR and MDS. Viral pathogens (HCMV or VZV or RV) were detected in 19 out of 31 eyes (61.3%) by real-time qPCR or WDC evaluation. MDS revealed the presence of HCMV DNA sequences in three PSS patients. Virus is an important pathogen in secondary glaucoma associated with anterior segment uveitis. MDS is a potential etiologic diagnosis tool to seek intraocular viral pathogens for secondary glaucoma associated anterior segment uveitis.

Medical conditions with effective therapies are usually managed with objective measurement and therapeutic targets. Parkinson's disease has effective therapies, but continuous objective measurement has only recently become available. This blinded, controlled study examined whether management of Parkinson's disease was improved when clinical assessment and therapeutic decisions were aided by objective measurement. The primary endpoint was improvement in the Movement Disorder Society-United Parkinson's Disease Rating Scale's (MDS-UPDRS) Total Score. In one arm, objective measurement assisted doctors to alter therapy over successive visits until objective measurement scores were in target. Patients in the other arm were conventionally assessed and therapies were changed until judged optimal. There were 75 subjects in the objective measurement arm and 79 in the arm with conventional assessment and treatment. There were statistically significant improvements in the moderate clinically meaningful range in the MDS-UPDRS Total, III, IV scales in the arm using objective measurement, but not in the conventionally treated arm. These findings show that global motor and non-motor disability is improved when the management of Parkinson's disease is assisted by objective measurement.

BackgroundSeveral chimeric antigen receptor T cells (CAR T) targeting CD19 have induced profound and prolonged remission for refractory/relapsed (R/R) B-cell lymphoma. The risk of secondary malignancies, especially myeloid neoplasms, is of particular concern in the CAR T community, which still remains unclear.MethodsFour patients with R/R B-cell lymphoma after CD19 CAR T therapy diagnosed with secondary myeloid neoplasms (SMN) from 2 hospitals in eastern China were presented, including 3 with myelodysplastic syndrome (MDS) and 1 with acute myeloid leukemia (AML). Using single-cell RNA sequencing (scRNA-seq), we compared the cellular components of bone marrow (BM) samples obtained from one of these MDS patients and a health donor. We also provided a review of recently published literature concerning SMN risk of CAR T therapy.ResultsRelevant demographic, clinical, laboratory, therapeutic and outcome data were collected and presented by chart review. In our case series, the male-female ratio was 3.0 and the median age at MDS onset was 61.25 years old (range, 50-78). Median number of previous systemic therapies was 4.5 (range, 4-5), including autologous hematopoietic stem cell transplantation (auto-HSCT) in one patient. BM assessments prior to CAR T therapy confirmed normal hematopoiesis without myeloid neoplasms. Moreover, for 3 patients with SMN in our series, cytogenetic analysis predicted a relatively adverse outcome. In our experience and in the literature, treatment choices for the patients with SMN included allogeneic hematopoietic stem cell transplantation (allo-HSCT), hypomethylating agent (HMA), period filgrastim, transfusions and other supportive care. Finally, treatment responses of lymphoma, together with SMN, directly correlated with the overall survival of this community. Of note, it appeared that pathogenesis of MDS wasn’t associated with the CAR T toxicities, since all 4 patients experienced a pretty mild CRS of grade 1-2. Additionally, scRNA-seq analysis described the transcriptional alteration of CD34+ cells, identified 13 T/NK clusters, and also indicated increased cytotoxic T cells in MDS BM.ConclusionOur study illustrated the onset and progression of SMN after CD19 CAR T therapy in patients with R/R B-cell lymphoma, which provides useful information of this uncommon later event.

IntroductionThere is a need to develop harmonized procedures and a Minimum Data Set (MDS) for cross-border Multi Casualty Incidents (MCI) in medical emergency scenarios to ensure appropriate management of such incidents, regardless of place, language and internal processes of the institutions involved. That information should be capable of real-time communication to the command-and-control chain. It is crucial that the models adopted are interoperable between countries so that the rights of patients to cross-border healthcare are fully respected.ObjectiveTo optimize management of cross-border Multi Casualty Incidents through a Minimum Data Set collected and communicated in real time to the chain of command and control for each incident. To determine the degree of agreement among experts.MethodWe used the modified Delphi method supplemented with the Utstein technique to reach consensus among experts. In the first phase, the minimum requirements of the project, the profile of the experts who were to participate, the basic requirements of each variable chosen and the way of collecting the data were defined by providing bibliography on the subject. In the second phase, the preliminary variables were grouped into 6 clusters, the objectives, the characteristics of the variables and the logistics of the work were approved. Several meetings were held to reach a consensus to choose the MDS variables using a Modified Delphi technique. Each expert had to score each variable from 1 to 10. Non-voting variables were eliminated, and the round of voting ended. In the third phase, the Utstein Style was applied to discuss each group of variables and choose the ones with the highest consensus. After several rounds of discussion, it was agreed to eliminate the variables with a score of less than 5 points. In phase four, the researchers submitted the variables to the external experts for final assessment and validation before their use in the simulations. Data were analysed with SPSS Statistics (IBM, version 2) software.ResultsSix data entities with 31 sub-entities were defined, generating 127 items representing the final MDS regarded as essential for incident management. The level of consensus for the choice of items was very high and was highest for the category ‘Incident’ with an overall kappa of 0.7401 (95% CI 0.1265–0.5812, p 0.000), a good level of consensus in the Landis and Koch model. The items with the greatest degree of consensus at ten were those relating to location, type of incident, date, time and identification of the incident. All items met the criteria set, such as digital collection and real-time transmission to the chain of command and control.ConclusionsThis study documents the development of a MDS through consensus with a high degree of agreement among a group of experts of different nationalities working in different fields. All items in the MDS were digitally collected and forwarded in real time to the chain of command and control. This tool has demonstrated its validity in four large cross-border simulations involving more than eight countries and their emergency services.

For each domain, either a "star" or "no star" is assigned, with a "star" indicating that study design element was considered adequate and less likely to introduce bias. A maximum of two stars can be given for Comparability. A study could receive a maximum of ten stars.

BackgroundUnhealthy diet may increase the risk of impaired physical functioning in older age. Although poor diet and limited physical functioning both seem to be particularly common in Eastern Europe, no previous study has assessed the relationship between these two factors in this region. The current analysis examined the association between overall diet quality and physical functioning in Eastern European populations.MethodsWe used data on 25,504 persons (aged 45–69 years at baseline) who participated in the Health Alcohol and Psychosocial factors in Eastern Europe (HAPIEE) study. Dietary assessment at baseline used food frequency questionnaire, and the overall diet quality was evaluated by the Mediterranean diet score (MDS). Physical functioning (PF) was measured by the physical functioning subscale (PF-10) of the 36-item Short-Form Health Survey at baseline and three subsequent occasions over a 10-year period. The cross-sectional and longitudinal relationships between the MDS and PF were examined simultaneously using growth curve models.ResultsMen and women with higher adherence to the Mediterranean diet had significantly better PF at baseline; after multivariable adjustment, the regression coefficient per 1-unit increase in the MDS was 0.39 (95% CI: 0.25, 0.52) in men and 0.50 (0.36, 0.64) in women. However, we found no statistically significant link between baseline MDS and the subsequent slope of PF decline in neither gender; the coefficients were -0.02 (-0.04, 0.00) in men and -0.01 (-0.03, 0.02) in women.DiscussionOur results do not support the hypothesis that the Mediterranean diet has a substantial impact on the trajectories of physical functioning, although the differences existing at baseline may be related to dietary habits in earlier life.