Patient Dashboard: the use of a colour-coded computerised clinical reminder in Whanganui regional general practices

Abstract

INTRODUCTION: Clinical reminders have been shown to help general practice achieve an increase in some preventive care items, especially if they identify a patient’s eligibility for the target item, prompt clinicians at the right time, provide a fast link to management tools and facilitate clinical recording. WRPHO has introduced the Patient Dashboard clinical reminder and monitored its impact on health targets. Aim: This paper reports the impact of a computerised colour-coded clinical reminder on achieving agreed health targets in Whanganui regional practices. METHODS: Patient Dashboard was developed from previous versions in Auckland and Northland and provided to Whanganui regional practices with Primary Health Organisation (PHO) support. The Dashboard was linked with existing and new clinical management tools which automatically updated clinical records. Data from practices was pooled by Whanganui Regional Primary Health Organisation and target achievement rates reported over 15 months. RESULTS: Over the initial 15 months of Patient Dashboard use, recording of smoking status increased from 74% to 82% and of alcohol use from 15% to 47%. Screening for diabetes increased from 62% to 74%, cardiovascular risk assessment from 20% to 43%, cervical screening from 71% to 79%, and breast screening from 60% to 80%. DISCUSSION: Patient Dashboard was associated with increased performance indicators both for those targets which were part of a PHO programme and for targets without additional support. KEYWORDS: Reminder systems; quality indicators, health care; preventive health services; mass screening

Are interventions to increase the uptake of screening for cardiovascular disease risk factors effective? A systematic review and meta-analysis

“…One study published three papers from data obtained at different periods [32–34], and the most recent paper was included [33]. A total of 9 studies fulfilled the inclusion criteria and were included [27, 33, 35, 36, 47, 54, 55, 58, 59]. Forward and backward searches of the reference lists and bibliography citations of the 9 studies yielded an additional 16 studies [37, 39, 48–53, 56, 57, 60–65] and resulted in a total of 25 studies for qualitative synthesis.…”

“…Two authors provided the requested information [27, 37] while authors of the other four studies were either not contactable or stated that they no longer had access to the data. These four studies [35, 36, 39, 65] were excluded, and the final number of studies included in the meta-analysis was 21. Figure 1 illustrates the process of study search and selection.

Fig.

…”

Investigating Analytics Dashboards’ Support for the Value-based Healthcare Delivery Model

“…Source Primary care practitioner [40]- [42], [45], [47]- [49], [52] General Practitioner [34] Clinician [9], [17]- [21], [31], [46], [50], [55], [56], [58], [59] Physician [5], [35], [39], [42], [44], [53] Nurse [4], [33], [36], [38], [42], [50] Medical Staff [4], [6], [7], [19], [21], [33], [37], [39], [43], [50], [51], [57] Pharmacist [40], [60] Administrator and Managers [36], [53], [57] Patient [4], [17]- [21], [52],…”

“…Furthermore, for a useful design, not only colours needs to be selected based on the medical experts' suggestions regarding colour semantics of the domain, but also needs be chosen based on other users' characteristics (such as colour-blind users) [4]. In our analysis in some cases the traffic light colour coding principle was adopted in dashboards' design [7], [18], [38], [39], [41], [42], [44], [47], [50]- [52]. As an example, Starmer et al (2008), [7] used a simple color scheme of (red, yellow and green) to indicate several conditions compliance with processes.…”

Scoping the Design Space for Data Supported Decision-Making Tools in Respiratory Care

“…Existing research has identified different types of DSDM tools, from patient health self-tracking apps that share data with clinicians for personalized care planning [16]; to system dashboards used by clinicians to interlink data from different sources and support decision-making around patient treatment [18]. This paper focuses on data dashboards due to their extensive use in healthcare delivery, including hospital admissions reduction [16], best practice adherence [17], high risk patients' identification [27] and medication monitoring [18]. Related work highlights the challenge of integrating systems into clinical use, due to poor cultural fit or lack of integration and linkage to other key clinical systems [5,6].…”