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Health informatics (also referred to as medical informatics or biomedical informatics) is an interdisciplinary field that deals with health-related data in healthcare and with the technologies that are used to support healthcare services. While the goal of some health informatics systems is to automate processes, the more common goal is to help clinicians, patients, policymakers, and others to manage health information, and to communicate that information efficiently and effectively to end users. Thus, there is considerable overlap between the fields of health informatics and health communication, and this intriguing intersection between the two fields opens many opportunities for innovation. Health communication is often visible in health informatics in the area of patient communication. Examples of this include patient self-management tools that support behavior change. Correspondingly, health informatics is often visible in health communication in the use of computational methods and “big data” to build on communication theory. Future research in health communication will likely involve more and more intensive use of information technology. This can bring exciting new possibilities for both interventions and analytical techniques, yet researchers should ensure that information technology interventions respect participants' privacy and guarantee their safety. Investigating the effect of information technology on communications between healthcare professionals and with patients also offers interesting opportunities for collaborative research.

UNLABELLED: We determined adherence to nine fall-related ACOVE quality indicators to investigate the quality of management of falls in the elderly population by general practitioners in the Netherlands. Our findings demonstrate overall low adherence to these indicators, possibly indicating insufficiency in the quality of fall management. Most indicators showed a positive association between increased risk for functional decline and adherence, four of which with statistical significance. INTRODUCTION: This study aims to investigate the quality of detection and management of falls in the elderly population by general practitioners in the Netherlands, using the Assessing Care of Vulnerable Elders (ACOVE) quality indicators. METHODS: Community-dwelling persons aged 70 years or above, registered in participating general practices, were asked to fill in a questionnaire designed to determine general practitioner (GP) adherence to fall-related indicators. We used logistic regression to estimate the association between increased risk for functional decline-quantified by the Identification of Seniors At Risk for Primary Care score-and adherence. We then cross-validated the self-reported falls with medical records. RESULTS: Of the 950 elders responding to our questionnaire, only 10.6 % reported that their GP proactively asked them about falls. Of the 160 patients who reported two or more falls, or one fall for which they visited the GP, only 23.1 % had fall documentation in their records. Adherence ranged between 13.6 and 48.6 %. There was a significant positive association between the ISAR-PC scores and adherence in four QIs. Documentation of falls was highest (36.7 %) in patients whom the GP had proactively asked about falls. CONCLUSION: Based on patient self-reports, adherence to the ACOVE fall-related indicators was poor, suggesting that the quality of evaluation and management of falls in community-dwelling older persons in the Netherlands is poor. The documentation of falls and fall-related risk factors was also poor. However, for most QIs, adherence to them increased with the increase in the risk of functional decline.

To investigate which medications are associated with recurrent falls in elderly patients who attend the accident and emergency department following a fall. Cross-sectional study. Patients aged ≥ 65 years who attended the accident and emergency department between 2004 and 2010 following a fall, were invited to fill in a validated fall-questionnaire designed to assess the risk of falling accidents. We divided self-reported medications into anatomic therapeutic chemical (ATC) classes. Univariate logistic regression analysis was performed to explore the association between ATC medication classes and recurrent falls. Multivariate logistic regression analysis was used to assess the associations after adjustment for potential confounders. In total, 2258 patients participated in our study, of whom 39% (873) had sustained ≥ 2 falls within the previous year. After adjustment for potential confounders, the following medications appeared to be significantly more frequently associated with recurrent falls than with single fall incidents: antacids (adjusted odds ratio (aOR): 1.29; 95% CI: 1.03-1.60); analgesics (aOR: 1.22; CI: 1.06-1.41); anti-Parkinson medication (aOR: 1.59; CI: 1.02-2.46); nasal preparations (aOR: 1.49; CI: 1.07-2.08); ophthalmological medications (aOR: 1.51; CI: 1.10-2.09); antipsychotics (aOR: 2.21; CI: 1.08-4.52); and antidepressants (aOR: 1.64; CI: 1.13-2.37). Medications known to increase the risk of falls, such as psychotropic drugs, anti-Parkinson medications and analgesics, increase the risk of recurrent falls. Additionally, we found 4 other drug classes that showed significant association with recurrent falls. It could be that the use of medications from these classes is an indication of frailty and comorbidity in the elderly in general, or they may reflect a difference in the risk-profile between recurrent and single fallers. Further investigation is required to achieve improved insight into the causes and mechanisms associated with medication-related recurrent falls in the elderly