Patient characteristics associated with objective measures of digital health tool use in the United States: A literature review.

The study sought to determine which patient characteristics are associated with the use of patient-facing digital health tools in the United States.We conducted a literature review of studies of patient-facing digital health tools that objectively evaluated use (eg, system/platform data representing frequency of use) by patient characteristics (eg, age, race or ethnicity, income, digital literacy). We included any type of patient-facing digital health tool except patient portals. We reran results using the subset of studies identified as having robust methodology to detect differences in patient characteristics.We included 29 studies; 13 had robust methodology. Most studies examined smartphone apps and text messaging programs for chronic disease management and evaluated only 1-3 patient characteristics, primarily age and gender. Overall, the majority of studies found no association between patient characteristics and use. Among the subset with robust methodology, white race and poor health status appeared to be associated with higher use.Given the substantial investment in digital health tools, it is surprising how little is known about the types of patients who use them. Strategies that engage diverse populations in digital health tool use appear to be needed.Few studies evaluate objective measures of digital health tool use by patient characteristics, and those that do include a narrow range of characteristics. Evidence suggests that resources and need drive use

Developing a Business Case for the Care Coordination and Transition Management Model: Need, Metrics, and Measures

In this descriptive qualitative study, nurse and healthcare leaders\u27 experiences, perceptions of care coordination and transition management (CCTM®), and insights as to how to foster adoption of the CCTM RN role in nursing education, practice across the continuum, and policy were explored. Twenty-five barriers to recognition and adoption of CCTM RN practice across the continuum were identified and categorized. Implications of these findings, recommendations for adoption of CCTM RN practice across the care continuum, and strategies for reimbursement policies are discussed

Social Worker Integrated Care Competencies Scale (SICCS): Assessing Social Worker Clinical Competencies for Health Care Settings

Integrating physical and behavioral health services has the potential to reduce health disparities and service inequities among persons most at risk. However, clinical social workers in integrated health settings must possess relevant knowledge and skills to provide quality care to diverse populations. The Social Worker Integrated Care Competency Scale (SWICCS), developed to complement the Integrated and Culturally Relevant Care (ICRC) field education curriculum, measures students’ self-perceptions of knowledge and skills associated with providing behavioral health care. Three student cohorts (n = 38) completed the SWICCS three times during an integrated care field practicum. Results indicated a statistically significant increase in student knowledge and skills at each time point, with a large effect size (r = −.87). The SWICCS demonstrated utility in measuring and tracking social work student acquisition of knowledge and skills required for practice in integrated care environments

Quality of Life (QoL) in Patients with Traumatic Brain Injury (TBI): a Literature Review

Purpose: To describe the definition of quality of life (QoL) and identify the most appropriate tool for QoL assessment used in patients with TBI.Method: Searching was conducted from PubMed, CINAHL, EBSCO, and ProQuest during 2000-2011. A total of 33 studies were analyzed for this review consisting of 9 review studies, 2 intervention studies, and 22 descriptive studies.Result: Two important definitions of QoL were used in studies related to TBI namely achievement and subjective well-being. Although varieties of generic measurements have been used to measure QoL in TBI patients, there was a lack of TBI-specific Health-related Quality of Life (HRQoL) instrument. Despite the different approach and time measured either short or long outcomes, appropriate domains of QoL tool seem essential particularly among those with moderate and severe TBI.Conclusion: QoL is a wide concept which can be defined in several dimensions. The QOLIBRI as a new disease-specific QoL measurement in TBI seems a feasible and valid approach for the assessment of QoL in TBI. However, the application across cultural remains a challenge and needs a validation

TB STIGMA – MEASUREMENT GUIDANCE

TB is the most deadly infectious disease in the world, and stigma continues to play a significant role in worsening the epidemic. Stigma and discrimination not only stop people from seeking care but also make it more difficult for those on treatment to continue, both of which make the disease more difficult to treat in the long-term and mean those infected are more likely to transmit the disease to those around them. TB Stigma – Measurement Guidance is a manual to help generate enough information about stigma issues to design and monitor and evaluate efforts to reduce TB stigma. It can help in planning TB stigma baseline measurements and monitoring trends to capture the outcomes of TB stigma reduction efforts. This manual is designed for health workers, professional or management staff, people who advocate for those with TB, and all who need to understand and respond to TB stigma

Twitter analysis for depression on social networks based on sentiment and stress

Detecting words that express negativity in a social media message is one step towards detecting depressive moods. To understand if a Twitter user could exhibit depression over a period of time, we applied techniques in stages to discover words that are negative in expression. Existing methods either use a single step or a data subset, whereas we applied a multi-step approach which allowed us to identify potential users and then discover the words that expressed negativity by these users. We address some Twitter specific characteristics in our research. One of which is that Twitter data can be very large, hence our desire to be able to process the data efficiently. The other is that due to its enforced character limitation, the style of writing makes interpreting and obtaining the semantic meaning of the words more challenging. Results show that the sentiment of these words can be obtained and scored efficiently as the computation on these dataset were narrowed to only these selected users. We also obtained the stress scores which correlated well with negative sentiment expressed in the content. This work shows that by first identifying users and then using methods to discover words can be a very effective technique