Top PDF Prioritizing Patient Assessment Data (PAD) Using the Japanese Psychiatric Nursing Assessment Classification System (PsyNACS)©

Prioritizing Patient Assessment Data (PAD) Using the Japanese Psychiatric Nursing Assessment Classification System (PsyNACS)©

Prioritizing Patient Assessment Data (PAD) Using the Japanese Psychiatric Nursing Assessment Classification System (PsyNACS)©

PsyNACS© is composed of three sections: The general data set composed of nine Patient Assessment Data (PADs), with each PAD having 2 to 5 Cluster Assessment Data (CADs). There were thirty-one CADs which were comprised of selected items. The “level of importance” for each item was evaluated using a Likert scale: (1 point) Unnecessary, (2 points) Quite important; (3 points) with the following valuations Important; and (4 points) Very important. Mean factor points (MFP), derived from the total score factor divided by number of items, was calculated. The average of three points or more of the evaluation of the respondents indicate that the CAD was evaluated as “important” by the professional psychiatric nurses. Considering each of the practice units, the “lev- el of importance” of each CAD that was evaluated by the practicing professional psychiatric nurses were grouped into five practicing units. Subsequently, the data were subjected to Welch’s ANOVA to establish the priority of the CAD according to the unit functions. The Welch’s ANOVA procedure is frequently recommend- ed as the major alternative to the ANOVA F test [6]. Welch’s ANOVA is a form of one-way ANOVA that does not assume equal variances. This study had five groups: ACU, GCU, LCU, CDCU, and DCU. The minimum sample size required were only 75 subjects with each group having at least 15 subjects. There were 435 subjects with valid responses thereby meeting the number of subjects required for performing Welch’s ANOVA as a non-parametric test. The significant difference was observed in items by using the Tamhane’s test as post hoc tests. For all analyses, the statistical significance was established at 0.05 level. All statistical analyses were per- formed using the SPSS for Windows software (version 20.0; SPSS Inc., Chicago, IL).
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pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

pTuneos: prioritizing tumor neoantigens from next-generation sequencing data

cytokine staining (ICS) assay. The first neopeptide TESPEEQHI results from FAM3C (p.K193E) mutation in patient CR9306. In the identified neoantigen list obtained from pTuneos Pre&RecNeo module, this neopeptide ranked in the second place (Additional file 11: Table S10. B). The second neopeptide GLEREGFTF results from CSMD1 (p.G3446E) mutation in patient CR0095. However, we could not find this peptide in the final list from pTuneos Pre&RecNeo module (Additional file 11: Table S10. C). We found that the predicted MHC class I binding affinity %rank between GLEREGFTF and MHC-I alleles (A0201, A3101, B3502, B3906, C0401, C0702) was all greater than 2 predicted by NetMHCpan 4.0, which means that it could not be presented by MHC-I molecules and it was filtered by pTuneos in the epitope identification step. Taking to- gether, pTuneos could identify 2 out of 3 validated neoanti- gen and rank them at the top of final list, demonstrating its effectiveness. Notably, in the original study [5], researchers also found that all the predicted MHC class I affinity of this neopeptide are greater than 500 nM by NetMHC 3.4. These results indicated that the sensitivity of peptide-MHC-I binding affinity prediction methods such as NetMHC and NetMHCpan is needed to be improved, and the low pre- dicted binding affinity of peptide-MHC-I does not neces- sarily indicate that they could not activate T cell response.
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The Changes of Nursing Students’ Assessment Skills at a Simulated Setting: A Quasi Experimental Study

The Changes of Nursing Students’ Assessment Skills at a Simulated Setting: A Quasi Experimental Study

The reflections offered a unique way for students to critically analyze their own performance. Students engaged in introspec- tive learning to self-correct. The reflections focused on students’ primary misconceptions, anything they missed in report or oth- er information they needed from report or the patient to act more effectively, and what they should do differently the next time while emphasizing what was correct, appropriate and safe. It allows the student to clarify their thinking and link the simu- lation to real situation while reinforcing specific knowledge, and to discuss how to intervene professionally in complex clin- ical situations (Gaberson & Oermann, 2010). In this case, stu- dents learned from previous experience and paid close attention to patients’ concerns. They assessed the relevant and important data and explained them to the patient using understandable wording as managing the contingencies and emergencies. They presented better communication skills and patient education across the time of simulation.
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Routine Assessment of Patient Index Data 3(RAPID3) is a Valid Index for Routine Care inPatients with Osteoarthritis

Routine Assessment of Patient Index Data 3 (RAPID3) is a Valid Index for Routine Care in Patients with Osteoarthritis

The multidimensional health assessment questionnaire (MDHAQ) has been developed in patients care with rheumatoid arthritis but has been useful clinically also in patients with other rheumatic diseases. It’s available for free download at www.mdhaq.org [7-9]. RAPID3 is a patient reported outcome (PRO), related to MDHAQ, that uses the three core set criteria evaluated by the patient, namely, physical function, pain, and the overall disease assessment. Physical function is assessed for 10 activities, of which eight are the simplified activities in the MDHAQ and two are complex activities. Each activity is scored from 0 to 3, and the sum of the scores (range, 0–30) is computed and divided by 10 to obtain a score that can range from 0 to 10.
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Systematic review of patient reported outcome measures (PROMs) for assessing disease activity in rheumatoid arthritis

Systematic review of patient reported outcome measures (PROMs) for assessing disease activity in rheumatoid arthritis

Patient assessment of disease activity in rheumatoid arthritis (RA) may be useful in clinical practice, offering a patient-friendly, location independent, and a time-efficient and cost-efficient means of monitoring the disease. The objective of this study was to identify patient-reported outcome measures (PROMs) to assess disease activity in RA and to evaluate the measurement properties of these measures. Systematic literature searches were performed in the PubMed and EMBASE databases to identify articles reporting on clinimetric development or evaluation of PROM-based instruments to monitor disease activity in patients with RA. 2 reviewers independently selected articles for review and assessed their methodological quality based on the Consensus-based Standards for the selection of health Measurement Instruments (COSMIN) recommendations. A total of 424 abstracts were retrieved for review. Of these abstracts, 56 were selected for reviewing the full article and 34 articles, presenting 17 different PROMs, were finally included. Identified were: Rheumatoid Arthritis Disease Activity Index (RADAI), RADAI-5, Patient-based Disease Activity Score (PDAS) I & II, Patient-derived Disease Activity Score with 28-joint counts (Pt-DAS28), Patient-derived Simplified Disease Activity Index (Pt-SDAI), Global Arthritis Score (GAS), Patient Activity Score (PAS) I & II, Routine Assessment of Patient Index Data (RAPID) 2 – 5, Patient Reported Outcome-index (PRO-index) continuous (C) & majority (M), Patient Reported Outcome CLinical ARthritis Activity (PRO-CLARA). The quality of reports varied from poor to good. Typically 5 out of 10 clinimetric domains were covered in the validations of the different instruments. The quality and extent of clinimetric validation varied among PROMs of RA disease activity. The Pt-DAS28, RADAI, RADAI-5 and RAPID 3 had the strongest and most extensive validation. The measurement properties least reported and in need of more evidence were: reliability, measurement error, cross-cultural validity and interpretability of measures.
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<p>Patient interpretation of the Patient-Generated Subjective Global Assessment (PG-SGA) Short Form</p>

<p>Patient interpretation of the Patient-Generated Subjective Global Assessment (PG-SGA) Short Form</p>

interpretation of self-reported questionnaires 28,29 and on empirical experience of patients ’ use of PG-SGA in clinical trials. 23,24 Also, any other behavior of relevance was regis- tered, which were the basis for also generating new categories of behavior during data collection. Whether patients read slowly or fast were based on the two researchers ’ subjective interpretations. After completing the form, the patients were interviewed based on a structured interview guide containing questions about the participants ’ subjective evaluation of the questions and response options, their choice of reading strate- gies, whether questions were found to be easy or dif fi cult, and how they selected response options. The questions were repeated for each of the four sections of the form (Boxes 1 – 4; Figure 1). Additionally, observed patient behavior and/or patients ’ comments during the completion of the form were addressed in the interviews when relevant. The inter- views were conducted by a nurse (CRSJ). Two researchers
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Physician assessment of disease activity in JIA subtypes. Analysis of data extracted from electronic medical records

Physician assessment of disease activity in JIA subtypes. Analysis of data extracted from electronic medical records

Physician global assessment of overall disease activity [4] used a scale from 0 to 10. Patient pain was rated on a Likert scale (with 0 = no pain and 10 = very severe pain) in response to the question “By giving a number between 0 and 10, with 0 being no pain and 10 being the worst possible pain, how much pain on average have you experienced from your arthritis over the past week? ” Patient global assessment was rated on a Likert scale (with 0 = doing very poorly and 10 = doing very well) in response to the question “ By giving a number between 0 and 10, with 0 being doing very poorly and 10 being doing very well, how have you experienced your arthritis in general over the past week? Include not only pain, but also how you feel about your arthritis, how having arthritis affects your getting along with family and friends, and how well you can move around.” Of the 160 patients, 132 (83%) self reported pain and global assessments (13.0 ± 4.0 years). Of the other 28 patients (6.3 ± 2.7 years), mothers of 26 patients reported, and fathers reported for 2 patients.
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Prioritizing patients for renal transplantation?: Analysis of patient preferences for kidney allocation according to ethnicity and gender

Prioritizing patients for renal transplantation?: Analysis of patient preferences for kidney allocation according to ethnicity and gender

The sample consisted of 468 out of 908 patients (51.5%) with successful transplants, 118 out of 908 patients (13%) whose transplant failed, and 279 out of 908 patients (30.7%) who were awaiting transplants, with an average waiting period of 22.6 months. Some patients whose transplant failed are also included in the data for those awaiting transplants. This also applies to all gender and ethnic-minority groups. A total of 237 out of 908 patients (26.3%) were on dialysis without transplantation, and 57 out of 908 patients (6.3%) had kidney disease that did not require dialysis. Renal Registry prevalence data (Farrington et al, 2008b) suggest that 46.6% of patients have successful trans- plants (as this is their current treatment modality), which is reassuringly close to our figure. However, there are no data for patients with failed transplants, or for those awaiting transplants, on dialysis without transplantation, or with kidney disease not requiring transplantation. Among non-white ethnic minorities there were 18 out of 69 patients (26%) with successful transplants, 10 out of 69 patients (14.5%) whose trans- plant failed, 35 out of 69 patients (50.7%) awaiting a
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A coproduced patient and public event: An approach to developing and prioritizing ambulance performance measures

A coproduced patient and public event: An approach to developing and prioritizing ambulance performance measures

There are various reasons why measures from the Delphi study and PPI event may or may not have been taken forward for further de- velopment. A final subset of PhOEBE measures was derived through consideration of both the Delphi and PPI scores by small expert group discussions. Other factors such as feasibility and availability of data, rel- evance to ambulance care, whether measures were already being used, and if they related to the whole or part of the ambulance population had to be considered when creating the final set of measures (See Table 5)

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Routine Assessment of Patient Index Data 3 (RAPID3) alone is insufficient to monitor disease activity in rheumatoid arthritis in clinical practice

Routine Assessment of Patient Index Data 3 (RAPID3) alone is insufficient to monitor disease activity in rheumatoid arthritis in clinical practice

Second, the longitudinal association between RAPID3 (explanatory variable) and DAS28- ESR (main outcome) was tested in GEE models with autoregression (ie, adjusting for the outcome in t-1). The association between RAPID3 and each individual component of DAS28 (SJC, ESR, TJC and PGA) was also tested in sepa- rate GEE models. GEE models with autoregression allow for a truly longitudinal interpretation of the association of interest by ‘isolating’ the within- subject effect while correcting for the inherent correlation by specifying a ‘working correlation matrix’. The exchangeable correla- tion matrix was used since it proved to better fit the data. Interactions between RAPID3 and gender, pain, PGA and age were tested, and if statistically significant (p<0.20) and clinically relevant, the association of interest was tested in stratified models (median value at baseline for continuous variables). In all models, only patients with data on the outcome and explanatory variable available in at least two consecutive visits were included (details on statistical analysis available in online supplementary text S1). All analyses were performed in STATA V.15.1).
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Evaluation of Delivery Analysis to Detect Intrafractional Motion during Tomotherapy

Evaluation of Delivery Analysis to Detect Intrafractional Motion during Tomotherapy

In-treatment assessment is software that quantifies consistency interfraction motion during treatment using post patient detector signals obtained during pa- tient radiation therapy (Figure 1). The purpose is to capture changes in the pa- tient’s anatomy or positional misalignments. The data collection method uses a detector to receive X-rays that have passed through the patient’s body during treatment. As soon as the treatment is finished, the data are taken to a stand-alone workstation separate from the treatment system network. This is done automat- ically. In addition, the consistency of irradiation can be evaluated by managing daily data in a trend graph.
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Value of the Routine Assessment of Patient Index Data 3 in Patients With Psoriatic Arthritis: Results From a Tight‐Control Clinical Trial and an Observational Cohort

Value of the Routine Assessment of Patient Index Data 3 in Patients With Psoriatic Arthritis: Results From a Tight‐Control Clinical Trial and an Observational Cohort

Psoriatic arthritis (PsA) is a complex disease involving both the musculoskeletal and cutaneous systems. Many outcome measures have been developed specifically for PsA to reflect both systems, with composite indices, which may include assessment of arthritis (both peripheral and axial), enthesitis, dactylitis, skin and nail psoriasis, and patient- reported outcomes (1). Such composite indices are used widely in clinical trials, but generally not incorporated into routine practice due to their complexity(1). The only quantitative data available in routine care of many PsA (and other rheumatology) patients are laboratory tests, with significant limitations(2).
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Etanercept versus etanercept plus methotrexate: a registry based study suggesting that the combination is clinically more efficacious

Etanercept versus etanercept plus methotrexate: a registry based study suggesting that the combination is clinically more efficacious

Group comparisons of this nature suffer from several weaknesses that can impact the results. First, the patient groups may be inherently different due to the lack of ran- domisation. We identified differences in the gender distri- bution between the groups, but correcting for this did not meaningfully change the results (data not shown). Disease activity parameters at baseline were well balanced in the two treatment groups, as were some of the known prog- nostic factors for clinical course (rheumatoid factor and shared epitope). One important difference between the two treatment groups, which cannot be eliminated, is the fact itself that the monotherapy group did not receive MTX. In all but a few instances this reflected prior treat- ment with MTX resulting either in treatment-limiting side effects or in a lack of efficacy. This may reflect on the nature of the patients’ disease in a matter that cannot be captured otherwise and may thus have influenced the results. Specifically, studies by Choi and colleagues [8] and by Hurst and colleagues [9] have shown that patients treated with MTX have significant survival benefits com- pared with those treated with other antirheumatic agents. It has been suggested that patients with rheumatoid arthritis who are able to tolerate MTX represent a subset with better prognosis than those patients who cannot take MTX. A baseline imbalance also existed with respect to the patient’s assessment of pain by VAS, which was signifi- cantly lower in the combination group. This imbalance weakens the importance of the difference seen in VAS pain at 3 months, and indeed a statistical comparison of the changes in VAS pain between the groups was not sig- nificant. With respect to the main outcome in this study, the DAS28, it is important to underscore that the VAS pain is not included in the formula for calculating the DAS28. In as much as any baseline imbalance in the outcome of interest would tend to bias towards finding a greater effect in the group with the higher baseline value (through regression to the mean [10]), the slightly higher disease activity indices in the monotherapy group actually strengthen the association between better treatment results and combination therapy.
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Responsiveness of a simple RAPID 3 like index compared to disease specific BASDAI and ASDAS indices in patients with axial spondyloarthritis

Responsiveness of a simple RAPID 3 like index compared to disease specific BASDAI and ASDAS indices in patients with axial spondyloarthritis

A multidimensional health assessment questionnaire (MDHAQ), 13 which includes a simple index, routine assessment of patient index data (RAPID3), has been used effectively in many clinical settings. 7 RAPID3 is a composite index based on the three patient self-report core data set measures, physical function (FN), pain and patient global estimate (PATGL), 14 which may be calcu- lated on an MDHAQ in about 5 seconds. 15 RAPID3 is useful to recognise clinical changes in many other rheumatic diseases, including osteoarthritis, gout, sys- temic lupus erythematosus, vasculitis as well as Ax-SpA. 16–22 Four reports concerning RAPID3 in Ax-SpA indicate high correlations between RAPID3 and BASDAI and ASDAS. 19–21 However, these studies do not analyse responsiveness according to RAPID3 in Ax-SpA, com- pared to AS-speci fi c indices such as BASDAI and ASDAS.
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The Optimized Algorithm For Prioritizing And Scheduling Of Patient Appointment At A Health Center According To The Highest Rating In Waiting Queue

The Optimized Algorithm For Prioritizing And Scheduling Of Patient Appointment At A Health Center According To The Highest Rating In Waiting Queue

and recognizing their types and royalties for each referral, we can determine the status of the patients and provide a timely schedule for patients in the treatment center. In addition, we examine cases or problems that disturb the situation and proper turn-giving to the patient. It is also important to take into account the various turn-giving indexes, including the type of referral to the treatment center, the types of turns, the types of patient status, the receipt of para-clinical services, and the consultation service with the other physician and so on. According to the abovementioned cases, the patient's turn is indicated in different parts of the treatment center and ultimately, the patient's waiting time will also be significantly affected, and the patient's satisfaction from the received services will also have the consent of the physician and the personnel of therapeutic center. This function is also effective in obtaining more services and privileges for the treatment center. This article is organized as follows: Section 2 examines the research and works done in relation to scheduling and prioritizing the turn of patients in health centers. In section three, the question of research is described and the existing shortcomings in previous research, which led to the presentation of the model of this study, are reviewed. The basic model used in modelling the waiting queue of patients is shown in this section, and then the changes and criteria for the study have been added to it. After presenting the model, one of the meta-heuristic algorithms which is called genetic algorithm was used to optimize the patient's visit order and the proposed model's resolution. The genetic algorithm is introduced in this section and its process and implementation stages are described. In Section 4, firstly, by the help of analyzing data, general information about data set and type of data has been obtained. Then the stages of implementation and execution of the model were described in the environment of Visual Studio and SQL Server software. Then, the way of implementing the genetic algorithm for optimizing the queuing of patients is described. In section five, titled Summary and Suggestions, we will have an overall review on the research as well as we will provide suggestions for future work.
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Mining geriatric assessment data for in-patient fall prediction models and high-risk subgroups

Mining geriatric assessment data for in-patient fall prediction models and high-risk subgroups

to identify high-risk subgroups, we deliberately chose the decision tree approach [11] despite our medium- sized data set (> 5,000 instances). Furthermore, we expected - and found - non-linear relationships for some parameters (e.g. age), confirming the justification of our choice. The significant amount of missing data for some sub-items limits the generalizability of our findings, yet this is quite normal in clinical data sets where it is often neither necessary nor practical to apply all available test procedures. We have used model induction algorithms that employ two different strate- gies of dealing with missing data, thus minimizing the effect. Finally, the cost matrix defining the costs of false negatives as being 20-fold higher than those of false positives, is a rough estimate as mentioned above and therefore is to some extent arbitrary, as the authors are not aware of an explicit study providing a ratio compar- ing long-term in-patient fall-related costs with those of non-fallers.
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Assessment of patient safety culture in the gaza strip hospitals

Assessment of patient safety culture in the gaza strip hospitals

Culture is described as a critical element of healthcare safety and quality. This study aims to assess a patient safety culture in GS hospitals.A cross-sectional, descriptive design was utilized. A total number of 376 clinical and non-clinical hospitals’ staff participated in the current study. Data were collected using an Arabic version of the Hospital Survey on Patient Safety Culture (HSOPSC). The study data was evaluated using the SPSS for Windows 20.0. Dimensional- and item-level positive scores were used for results reporting. Additionally descriptive statistics, Chi- square test, independent sample t-test and ANOVA were used for data analyzing. Finding shows,the dimensions which elicited the highest positive ratings were teamwork within units (78%), and organizational learning and continuous improvement (72%); meanwhile those with the lowest ratings included staffing (58%), and non-punitive response to error (48%). Statistically significant differences among hospitals and also in reference to participants working characteristics (P<0.05). Small hospitals recived significantly higher mean safety scores than large hospitals, and physicians were the least positive towards safety than other employees (p<0.05). The study concluded that the status of safety culture in Gaza hospitals is acceptable despite the prevailing difficult conditions, but it can be improved through promoting reporting events, reinforcing management commitment towards safety, and implementing effective communication strategies.
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Vulnerability Assessment of Steel Structures in District 12 of Mashhad City and Prioritizing the Welding Defects Using the Analytic Hierarchy Process

Vulnerability Assessment of Steel Structures in District 12 of Mashhad City and Prioritizing the Welding Defects Using the Analytic Hierarchy Process

To prioritize the defects in different connections of the buildings, importance of connections and the percentage of defects in each of them will be determine. The primary data was collected by two different questionnaires. The first questionnaire was to determine the percentage of each defect in the connections that required tests carried out by the welding inspector. To answer this questionnaire, the weld inspectors used different tools and methods such as visual inspection, penetrant testing, ultrasonic testing and electromagnetic testing to reconnoiter the defects and compare them with the standard range (Figure 4) [14]. It was noted that the study area has about 70 steel buildings where welding test is possible; therefore, according to the Cochran formula, 50 steel buildings were randomly tested [15].
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Impact of tofacitinib on patient outcomes in rheumatoid arthritis &ndash; review of clinical studies

Impact of tofacitinib on patient outcomes in rheumatoid arthritis &ndash; review of clinical studies

Abstract: Rheumatoid arthritis is a chronic, progressive autoimmune disease associated with inflammation and destruction of joints and systemic effects, which result in significant impact on patient’s quality of life and function. Tofacitinib was approved for the treatment of rheuma- toid arthritis in the USA in 2012 and subsequently in other countries, but not by the European Medicines Agency. The goal of this review was to evaluate the impact of tofacitinib on patient- reported and patient-specific outcomes from prior clinical studies, focusing on quality of life, functionality, pain, global disease assessment, major adverse consequences, and withdrawals. A total of 13 reports representing 11 clinical studies on tofacitinib in rheumatoid arthritis were identified through PubMed and reference lists in meta-analyses and other reviews. Data on improvements in patient-driven composite tools to measure disease activity in rheumatoid arthritis, such as the Health Assessment Questionnaire, served as a major outcome evaluated in this review and were extracted from each study. Additional data extracted from those clinical studies included patient assessment of pain (using a 0–100 mm visual analog scale), patient global assessment of disease (using a 0–100 mm visual analog scale), patient withdrawals, withdrawals due to adverse effects or lack of effect, and risk of serious adverse effects, serious infections, and deaths. Tofacitinib 5 mg bid appears to have a favorable impact on patient out- comes related to efficacy and safety when compared with baseline values and with comparator disease-modifying antirheumatic drugs and placebo. Improvements were seen in the composite and individual measures of disease activity. Serious adverse effects, other adverse consequences, overall withdrawals, and withdrawals due to adverse effects and lack of efficacy are similar or more favorable for tofacitinib versus comparator disease-modifying antirheumatic drugs and placebo. At this point, tofacitinib appears to have an important role in the treatment of rheuma- toid arthritis through improvement in these patient outcomes. However, it may require years of additional clinical studies and postmarketing surveillance to fully characterize the benefit-to-risk ratio of tofacitinib in a larger and diverse patient population.
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The Development of the Japanese Psychiatric Nursing Assessment Classification System (PsyNACS©)

The Development of the Japanese Psychiatric Nursing Assessment Classification System (PsyNACS©)

A descriptive correlational survey method was used to determine the clusters of assessment items that comprise the Cluster Assessment Data (CAD) and the Patient Assessment Data (PAD) of the PsyNACS © . The PsyNACS © is composed of three levels or sections: The general data set is composed of 9 PADs, with each PAD having 2 to 5 CADs. There are 31 CADs derived from selected evaluation items. In order to investigate the items necessary for a psychiatric nursing-care assessment data, 211 assessment items were derived from specific assessment items based on selected theoretical models or frameworks of self-care theory by Orem-Underwood [17], the 14 basic needs by Henderson [14], Gordon’s 11 functional health patterns [21] and items from the stress adaptation model by Stuart [22]. The level of importance of each indicator was evaluated as 1) Unnecessary, 2) Not very important, 3) Important and 4) Very important.
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