Computational analysis of non-adherence and non-attendance using the text of narrative physician notes in the electronic medical record

Patient and economic benefits of psychological support for noncompliant patients

The current paper provides an overview of treatment noncompliance at various points in the treatment pathway, especially with respect to treatment for Pelvic-floor Dysfunction (PFD). The effects of noncompliance on healthcare are considered, and examples of supporting patients psychologically to increase compliance are discussed. An outline of a method to identify costs of non-compliance, and where such costs most intensely impact the healthcare system, is provided. It is suggested that psychological support is effective in terms of increased compliance and improved healthcare economics. The model is presented for PFD, but the principles developed can be generalised to many aspects of healthcare.

The use of count data models in biomedical informatics evaluation research

OBJECTIVES

Studies on the impact and value of health information technology (HIT) have often focused on outcome measures that are counts of such things as hospital admissions or the number of laboratory tests per patient. These measures with their highly skewed distributions (high frequency of 0s and 1s) are more appropriately analyzed with count data models than the much more frequently used variations of ordinary least squares (OLS). Use of a statistical procedure that does not properly fit the distribution of the data can result in significant findings being overlooked. The objective of this paper is to encourage greater use of count data models by demonstrating their utility with an example based on the authors' current work.

TARGET AUDIENCE

Researchers conducting impact and outcome studies related to HIT.

SCOPE

We review and discuss count data models and illustrate their value in comparison to OLS using an example from a study of the impact of an electronic health record (EHR) on laboratory test orders. The best count data model reveals significant relationships that OLS does not detect. We conclude that comprehensive model checking is highly recommended to identify the most appropriate analytic model when the dependent variable being examined contains count data. This strategy can lead to more valid and precise findings in HIT evaluation studies.

Innovations in the Utilization of Health Information Technology in Psychiatric Services

There is ever-increasing activity in applying information technology to various areas of healthcare, including mental health. Examples of innovations include applications in screening, treatment, clinical decision support, communication and coordination, telemedicine, Internet-based education and services, public health research, training and education, and bioinformatics. Issues and challenges include protection of privacy, managing narrative free text, assessing the reliability of information found online, and mitigating impact on clinical workflow. While many of the innovations described will not be fully realized until national information systems reach a larger scale, many are having a positive impact on mental healthcare today.

Good Medical Practice: what are we trying to say? Textual analysis using tag clouds

OBJECTIVES

Good Medical Practice, produced by the General Medical Council (GMC), represents the professional code of practice for doctors in the UK. It is regularly updated to reflect the changing relationships of the profession with both patients and society in general. The discourse within this guidance appears to have shifted over time to a stance that aligns itself more closely with the protection of patients, rather than with the traditional professional provision of guidance and support to doctors.

METHODS

Tag clouds are a feature of the latest applications of the World Wide Web, commonly known as Web 2.0. They can be used to rapidly analyse textual data, revealing textual messages in a pictorial form. Tag cloud-generating software was used to produce tag clouds of four texts illustrating GMC guidance produced between 1963 and 2006 to aid textual analysis and to determine whether this methodology could pick up this change in tenor.

RESULTS

This analysis supports the view that there has been a shift from a doctor-centred regulatory discourse to a patient-centred health improvement agenda over the period of time examined.

DISCUSSION

Whether this documentation voices a deprofessionalisation agenda or simply mirrors a period of societal change in general is discussed. The changing discourse around professionalism highlights the need to avoid adopting 'nostalgic' notions of professionalism in educating doctors and reinforces where the GMC sees we should focus our education efforts: in patient-centred care and team-working. The demands on, and responsibilities of students and juniors entering the profession have been fundamentally altered and our teaching, particularly in the domain of professionalism, needs to reflect this. Tag clouds provide an interesting and innovative way of analysing text and revealing obscured discourses, and their potential in education and research is worthy of further exploration.