BMC Medical Informatics and Decision Making

https://bmcmedinformdecismak.biomedcentral.com

List of Papers (Total 2,140)

Risk factor analysis of device-related infections: value of re-sampling method on the real-world imbalanced dataset

The incidence of cardiac implantable electronic device infection (CIEDI) is low and usually belongs to the typical imbalanced dataset. We sought to describe our experience on the management of the imbalanced CIEDI dataset. Database from two centers of patients undergoing device implantation from 2001 to 2016 were reviewed retrospectively. Re-sampling technique was used to improve...

Effects of a computerised guideline support tool on child healthcare professionals’ response to suspicions of child abuse and neglect: a community-based intervention trial

Healthcare professionals’ adherence to guidelines on child protection is not self-evident. This study assessed the effects of a computerised support tool on child healthcare professionals’ adherence to the seven recommended guideline activities, and on time spent seeking information presented in this guideline. A community-based intervention trial design was applied, comparing...

Item response theory analysis and properties of decisional conflict scales: findings from two multi-site trials of men with localized prostate cancer

Decisional conflict is associated with decision quality and may affect decision outcomes. In the health sciences literature, the Decisional Conflict Scale is widely used to measure decisional conflict, yet limited research has described the psychometric properties of the Decisional Conflict Scale subscales and of the low literacy version of the scale. The purpose of this...

Regional data exchange to improve care for veterans after non-VA hospitalization: a randomized controlled trial

Coordination of care, especially after a patient experiences an acute care event, is a challenge for many health systems. Event notification is a form of health information exchange (HIE) which has the potential to support care coordination by alerting primary care providers when a patient experiences an acute care event. While promising, there exists little evidence on the...

User evaluation of a novel SMS-based reminder system for supporting post-stroke rehabilitation

According to WHO stroke is a growing societal challenge and the third leading cause of global disease-burden estimated using disability-adjusted life years. Rehabilitation after stroke is an area of mutual interest for health care in many countries. Within the health care sector there is a growing emphasis on ICT services to provide clients with easier access to information, self...

Design and evaluation of a LIS-based autoverification system for coagulation assays in a core clinical laboratory

The autoverification system for coagulation consists of a series of rules that allow normal data to be released without manual verification. With new advances in medical informatics, the laboratory information system (LIS) has growing potential for the autoverification, allowing rapid and accurate verification of clinical laboratory tests. The purpose of the study is to develop...

Combining population-based administrative health records and electronic medical records for disease surveillance

Administrative health records (AHRs) and electronic medical records (EMRs) are two key sources of population-based data for disease surveillance, but misclassification errors in the data can bias disease estimates. Methods that combine information from error-prone data sources can build on the strengths of AHRs and EMRs. We compared bias and error for four data-combining methods...

TASKA: A modular task management system to support health research studies

Many healthcare databases have been routinely collected over the past decades, to support clinical practice and administrative services. However, their secondary use for research is often hindered by restricted governance rules. Furthermore, health research studies typically involve many participants with complementary roles and responsibilities which require proper process...

An online experiment to assess bias in professional medical coding

Multiple studies have documented bias in medical decision making, but no studies have examined whether this bias extends to medical coding practices. Medical coding is foundational to the US health care enterprise. We evaluate whether bias based on patient characteristics influences specific coding practices of professional medical coders. This is an online experimental study of...

The past, present and future of opioid withdrawal assessment: a scoping review of scales and technologies

A common challenge with all opioid use disorder treatment paths is withdrawal management. When withdrawal symptoms are not effectively monitored and managed, they lead to relapse which often leads to deadly overdose. A prerequisite for effective opioid withdrawal management is early identification and assessment of withdrawal symptoms. The objective of this research was to...

The index lift in data mining has a close relationship with the association measure relative risk in epidemiological studies

Data mining tools have been increasingly used in health research, with the promise of accelerating discoveries. Lift is a standard association metric in the data mining community. However, health researchers struggle with the interpretation of lift. As a result, dissemination of data mining results can be met with hesitation. The relative risk and odds ratio are standard...

The effect of computerized decision support systems on cardiovascular risk factors: a systematic review and meta-analysis

Cardiovascular risk management (CVRM) is notoriously difficult because of multi-morbidity and the different phenotypes and severities of cardiovascular disease. Computerized decision support systems (CDSS) enable the clinician to integrate the latest scientific evidence and patient information into tailored strategies. The effect on cardiovascular risk factor management is yet to...

Decision tree–based classifier in providing telehealth service

Although previous research showed that telehealth services can reduce the misuse of resources and urban–rural disparities, most healthcare insurers do not include telehealth services in their health insurance schemes. Therefore, no target variable exists for the classification approaches to learn from or train with. The problem of identifying the potential recipients of...

Development of a novel mobile application to detect urine protein for nephrotic syndrome disease monitoring

Home monitoring of urine protein is a critical component of disease management in childhood nephrotic syndrome. We describe the development of a novel mobile application, UrApp – Nephrotic Syndrome Manager, to aid disease monitoring. UrApp was iteratively developed by a panel of two pediatric nephrologists and three research engineers from May 2017 to October 2018 for Apple...

Mobile applications for pain management: an app analysis for clinical usage

Pain is the most common and distressing symptom for patients in all clinical settings. The dearth of health informatics tools to support acute and chronic pain management may be contributing to the chronic pain and opioid abuse crises. The purpose of this study is to qualitatively evaluate the content and functionality of mobile pain management apps. The Apple App Store and the...

Improving health information systems during an emergency: lessons and recommendations from an Ebola treatment centre in Sierra Leone

The 2014–2016 West Africa Ebola epidemic highlighted the difficulty of collecting patient information during emergencies, especially in highly infectious environments. Health information systems (HISs) appropriate for such settings were lacking prior to this outbreak. Here we describe our development and implementation of paper and electronic HISs at the Sierra Leone Kerry Town...

Patient centred variables with univariate associations with unplanned ICU admission: a systematic review

Multiple predictive scores using Electronic Patient Record data have been developed for hospitalised patients at risk of clinical deterioration. Methods used to select patient centred variables for inclusion in these scores varies. We performed a systematic review to describe univariate associations with unplanned Intensive Care Unit (ICU) admission with the aim of assisting...

A mobile health monitoring-and-treatment system based on integration of the SSN sensor ontology and the HL7 FHIR standard

Mobile health (MH) technologies including clinical decision support systems (CDSS) provide an efficient method for patient monitoring and treatment. A mobile CDSS is based on real-time sensor data and historical electronic health record (EHR) data. Raw sensor data have no semantics of their own; therefore, a computer system cannot interpret these data automatically. In addition...

Machine learning to help researchers evaluate biases in clinical trials: a prospective, randomized user study

Assessing risks of bias in randomized controlled trials (RCTs) is an important but laborious task when conducting systematic reviews. RobotReviewer (RR), an open-source machine learning (ML) system, semi-automates bias assessments. We conducted a user study of RobotReviewer, evaluating time saved and usability of the tool. Systematic reviewers applied the Cochrane Risk of Bias...

Accessing and sharing health information for post-discharge stroke care through a national health information exchange platform - a case study

Patients and citizens need access to their health information to get a retrospective as well as a prospective view on their care and rehabilitation processes. However, patients’ health information is stored in several health information systems and interoperability problems often hamper accessibility. In Sweden a national health information exchange (HIE) platform has been...

Quantile-based fecal hemoglobin concentration for assessing colorectal neoplasms with 1,263,717 Taiwanese screenees

Although fecal hemoglobin concentration (f-Hb) was highly associated with the risk of colorectal neoplasms, current studies on this subject are hampered by skewedness of the data and the ordinal property of f-Hb has not been well studied yet. Our aim was to develop a quantile-based method to estimate adjusted percentiles (median) of fecal hemoglobin concentration and their...

An open access medical knowledge base for community driven diagnostic decision support system development

While early diagnostic decision support systems were built around knowledge bases, more recent systems employ machine learning to consume large amounts of health data. We argue curated knowledge bases will remain an important component of future diagnostic decision support systems by providing ground truth and facilitating explainable human-computer interaction, but that...

“OPTImAL”: an ontology for patient adherence modeling in physical activity domain

Maintaining physical fitness is a crucial component of the therapeutic process for patients with cardiovascular disease (CVD). Despite the known importance of being physically active, patient adherence to exercise, both in daily life and during cardiac rehabilitation (CR), is low. Patient adherence is frequently composed of numerous determinants associated with different patient...

Are Austrian practitioners ready to use medical apps? Results of a validation study

As part of the mobile revolution, smartphone-based applications (apps) have become almost indispensable in today’s information society. Consequently, the use of medical apps among healthcare professionals has increased heavily over the past years. As little is known on medical app use in day-to-day clinical practice in Austria, the present study aims at closing this knowledge gap...

Identifying clinically important COPD sub-types using data-driven approaches in primary care population based electronic health records

COPD is a highly heterogeneous disease composed of different phenotypes with different aetiological and prognostic profiles and current classification systems do not fully capture this heterogeneity. In this study we sought to discover, describe and validate COPD subtypes using cluster analysis on data derived from electronic health records. We applied two unsupervised learning...