healthcare technology

South Korea introduced a new health care IT system named the Narcotics Information Management System (NIMS) with the objective of managing all aspects of opioid use, including manufacturing, distribution, sales, disposal, etc.

The authors conducted an analysis using national claims data from 45,582 patients diagnosed with musculoskeletal and connective tissue disorders between 2016 and 2020.  The approach included using an interrupted time-series analysis and constructing segmented regression models. Within these models, the authors considered the primary intervention to be the implementation of NIMS, while we treated the COVID-19 outbreak as the secondary event.

To comprehensively assess inappropriate opioid use, we examined 4 key indicators, as established in previous studies:

(1) the proportion of patients on high-dose opioid treatment,

(2) the proportion of patients receiving opioid prescriptions from multiple providers,

(3) the overlap rate of opioid prescriptions per patient, and

(4) the naloxone use rate among opioid users.

This study suggests that, in its current form, the NIMS may not have brought significant improvements to the identified indicators of opioid overuse and misuse. Additionally, the COVID-19 outbreak exhibited no significant influence on opioid use patterns.

The absence of real-time monitoring feature within the NIMS could be a key contributing factor. Further exploration and enhancements are needed to maximize the NIMS’ impact on curbing inappropriate opioid use.

read the original at https://publichealth.jmir.org/2024/1/e47130/

Roughly 1 percent of searches on Google are symptom related. Starting  this week, when consumers access Google’s mobile search for information about certain symptoms, they will quick, accurate facts on relevant related medical conditions up front on their smartphone or other mobile device.

Announced in a blog post by  a product manager on Google’s search team, the goal of the new symptom search feature allows consumers to quickly explore and navigate health conditions related to symptoms.

Consumers can easily get basic answers on common a conditions, risk factors associated with the condition, self-treatment options and guidance on when to seek medical care.

As Web-based social media are growing in popularity, the number of people who share their experiences or ask for support in health-related social media has also increased. A study found that 41% of e-patients have read someone else’s commentary or experience about health on a Web-based news group, website, or blog.

Another study reported that more than 60 million Americans read or contribute to Health 2.0 apps, in which they consider these apps as their first source when gathering data and opinions. About 40% of Americans doubt a professional opinion when it conflicted with what they form from Web-based health social media.

One of the key benefits of health-related Web-based social media reported by researchers is the increased access to information to various demographic groups, regardless of age, education, income, or location. However, previous work has mainly relied on user surveys to study the effect of the use of social media to health-related factors such as psychological distress. In addition, previous work does not reveal granular information on what disorders or other health topics are mostly discussed in the Internet by each demographic group, which would allow health care providers to create targeted and effective educational campaigns.

In this work, we conducted the first, to our best knowledge, large-scale data-driven comparative analysis of the content of health-related social media across various demographic dimensions—gender, age, ethnicity, location, and writing level. For each demographic group, we study the content of the posts across the following dimensions: sentiment, popular terms (keywords), and medical concepts (particularly disorders and drugs). Concepts refer to entries in the Unified Medical Language System (UMLS) vocabulary, whereas terms are just words from the posts’ text that may or may not belong to any UMLS concept.

We report results for 3 types of social media:

(1) general Web-Based Social Networks, namely Google+ and Twitter,

(2) drug review websites, and

(3) health Web forums.

The selection of social media types was based on their popularity and on our study of the literature on health-related social content.

The objective of this study was to identify which health topics are discussed in which social media by which demographic groups, to better guide educational outreach and research activities.

read the whole study at http://www.jmir.org/2016/6/e148/