The Outcomes Measurement Information System ( Promis ) Was Funded By The Nih Roadmap For Medical Research Initiative

• Scoring: The inventory uses a 5-point scale of distress (0–4), ranging from “not at all” (0) to “extremely” (4). The DIE yields raw scores and T scores for the Total Score and Primary Dimension scores. Results are hand scored. T scores above 65 on the Total Score and the Primary Dimensions are considered in the “clinical range.”

Patients are asked to rate their symptom for each question for a period of two weeks. The patient is the one who rates himself, therefore, this instrument’s results are subjective. The sum total is the calculated, and interpreted to

Illness perceptions are often linked to outcomes of illness, for instance quality of life. A large study of 1785 adults in primary care found that patients’ illness perceptions could predict self-reported health status up to two years after the initial medical consultation (Frostholm et al. 2007). Patients were assessed based on the Illness Perception Questionnaire. Furthermore,

Coding systems are used in the inpatient and outpatient settings for the classification of patient morbidity and mortality information for statistical use. The World Health Organization (WHO) developed the Ninth Revision, International Classification of Diseases (ICD-9) in the 1970s to track mortality statistics across the world. The International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), is the adaptation the U.S. health system uses as a standard list of six-character alphanumeric codes to describe diagnoses. Globally utilizing a standardized system improves consistency in recording symptoms and diagnoses for payer claims reimbursement, as well as clinical research, and tracking purposes.

According to Stevens (2013), the call to develop and implement evidence-based practice (EBP) within all healthcare disciplines is fueled by legislative demands for improvement in standard medical metrics such as mortality and morbidity. However, increasing demands by the public for evidence related to the metrics and outcomes of such concepts as quality of life illustrate what may be more important to the client (Stevens, 2013). This client-directed focus has resulted in patient-centered outcomes research (PCOR) (Stevens, 2013). "The Patient-Centered Outcomes Research Institute (PCORI) helps people make informed health care decisions, and improves health care delivery and outcomes, by producing and promoting high integrity, evidence-based information

These objectives reflect a shift away from the traditional provider centered medical model, in which patients are often treated as passive recipients of care, and toward a more patient centered service model in which health decision making is expected to involve the active participation of the patient or consumer. In keeping with the Healthy People 2020 objectives and incorporating the Institute of Medicine’s goals for evidence-based care which emphasize patient centered care and respecting patients’ individual preferences (Institute of Medicine, 2001), the Health Outcomes Research Program at St. Luke’s Mid-American Heart Institute has developed a database with which patient-specific data can be used to estimate and model individual patient outcomes during clinical care. Decision aids created from these predictive risk estimates can

As I grow as a nurse, it is important to reflect on how I have grown throughout my clinical experiences. The Creighton Clinical Evaluation Instrument (C-CEI) is a tool used to measure growth in competency throughout my clinical experiences. The C-CEI measures competence in four areas: Assessment, communication, clinical decision making, and safety. The assessment portion of the C-CEI is broken down into three categories.

CSI is a severity scoring system that uses disease-specific measurements to categorize different levels of a patient’s severity. [51-53] These measurements include patient historical factors, physiologic parameters, and laboratory results. CSI covers a wide spectrum of diseases; more than 3,500 disease-specific severity matrices have been developed. It has been applied to predict patients’ prognosis[46], length of stay, re-hospitalization[54] and service cost[55, 56] and so on. Additionally, it has been used as a control factor in both retrospective [56, 57] and prospective clinical studies [58], which is hallmark of the Practice-Based Evidence (PBE) Research [59, 60]. Compared with traditional randomized control trial (RCT) studies[59], PBE studies simplify inclusion of a larger sample size, promote conducting long term follow-up, and are closer to real practice as opposed to the restrictions placed recruitment in RCTs. Compared with traditional observational studies[59], PBE standardizes confounding factors and makes the study design easier, more reliable, and more reproducible.

The instrument measured physical and mental health dimensions through eleven questions and thirty-six items covering eight components that were represented by functional capacity, physical pain, general health, vitality, social functioning, emotional aspects, mental health, and a related question about the current general health a year before the interview (Girardi et al., 2015).

We surveyed random individuals using Qualtrics to gather primary data for our research. Forty-nine individuals responded to our survey, out of which twenty-seven were valid surveys we used for testing. Our survey consisted of the below questions:

This is a patient questionnaire that uses a score of 0-4 to assess subjective neuropathic symptoms (Functional Assessment of Chronic Illness Therapy, 2007).

While patient assessment can never be 100% correct in all aspects the combined use of objective and subjective data gives the best initial assessment of a patient’s current condition and how to care for them in the near

Outcome is the desired result of the delivery of care on the overall health status of the patient. There are two types of outcomes: 1) technical outcomes, this denotes to the physical and functional aspects of care, such as absence of complications and reduction in disease, morbidity and mortality; and 2) interpersonal outcomes which include patients’ satisfaction with the received care and impact of care on patient’s quality of life in patient’s perspective. Outcome data are information which reflects, directly or indirectly, the performance of a health intervention, facility, service or system in maintaining or improving the wellbeing of its target population. Additionally, outcome data are high level clinical and financial outcomes that

The World Health Organization defines quality of life as a person’s perceptions of their position in life in the setting of the culture and value systems in which they live in relation to their goals, expectations, standards and concerns (Krageloh et al., 2011). The WHOQOL-100 was developed by the World Health Organization composed of many different doctors and other healthcare providers in order to develop an assessment that could be used internationally and cross-culturally to measure a person’s overall quality of life and well-being, instead of a specific disease. This assessment led to the development of the WHOQOL-BREF, which is an abbreviated version of the WHOQOL-100 because the WHOQOL-100 is too lengthy for practical use; WHOQOL-BREF includes instructions for administering and scoring the assessment. The purpose of this assessment is to provide quality assessments in healthcare, focus attention on all aspects of health, and produce interventions that increase focus on a patient’s well-being (Harper, 1996). There were three main stages to the development of the WHOQOL assessment. The first stage of development consisted of the establishment of a definition of quality of life and how the assessment would be used internationally. The second stage of development explored the quality of life cross-culturally among different fields to establish relevance to the quality of life assessment. The third stage of

Most of the respondents (n= 128; 53.9%) rated their overall quality of life as very good and good. 40.1% (n=93) reported ‘Neither poor nor good’ overall HRQOL. Whereas, a small percentage had ‘Poor’ (n=8, 3.4%) and ‘Very poor’ (n=6, 2.6%) HRQOL. Major respondents 75.4% (n=175) were satisfied with their health. This finding is consistent