Using marketing theory to inform strategies for recruitment: a recruitment optimisation model and the txt2stop experience.

BACKGROUND: Recruitment is a major challenge for many trials; just over half reach their targets and almost a third resort to grant extensions. The economic and societal implications of this shortcoming are significant. Yet, we have a limited understanding of the processes that increase the probability that recruitment targets will be achieved. Accordingly, there is an urgent need to bring analytical rigour to the task of improving recruitment, thereby increasing the likelihood that trials reach their recruitment targets. This paper presents a conceptual framework that can be used to improve recruitment to clinical trials. METHODS: Using a case-study approach, we reviewed the range of initiatives that had been undertaken to improve recruitment in the txt2stop trial using qualitative (semi-structured interviews with the principal investigator) and quantitative (recruitment) data analysis. Later, the txt2stop recruitment practices were compared to a previous model of marketing a trial and to key constructs in social marketing theory. RESULTS: Post hoc, we developed a recruitment optimisation model to serve as a conceptual framework to improve recruitment to clinical trials. A core premise of the model is that improving recruitment needs to be an iterative, learning process. The model describes three essential activities: i) recruitment phase monitoring, ii) marketing research, and iii) the evaluation of current performance. We describe the initiatives undertaken by the txt2stop trial and the results achieved, as an example of the use of the model. CONCLUSIONS: Further research should explore the impact of adopting the recruitment optimisation model when applied to other trials.

The effectiveness of mobile-health technologies to improve health care service delivery processes: a systematic review and meta-analysis.

BACKGROUND: Mobile health interventions could have beneficial effects on health care delivery processes. We aimed to conduct a systematic review of controlled trials of mobile technology interventions to improve health care delivery processes. METHODS AND FINDINGS: We searched for all controlled trials of mobile technology based health interventions using MEDLINE, EMBASE, PsycINFO, Global Health, Web of Science, Cochrane Library, UK NHS HTA (Jan 1990-Sept 2010). Two authors independently extracted data on allocation concealment, allocation sequence, blinding, completeness of follow-up, and measures of effect. We calculated effect estimates and we used random effects meta-analysis to give pooled estimates. We identified 42 trials. None of the trials had low risk of bias. Seven trials of health care provider support reported 25 outcomes regarding appropriate disease management, of which 11 showed statistically significant benefits. One trial reported a statistically significant improvement in nurse/surgeon communication using mobile phones. Two trials reported statistically significant reductions in correct diagnoses using mobile technology photos compared to gold standard. The pooled effect on appointment attendance using text message (short message service or SMS) reminders versus no reminder was increased, with a relative risk (RR) of 1.06 (95% CI 1.05-1.07, I(2) = 6%). The pooled effects on the number of cancelled appointments was not significantly increased RR 1.08 (95% CI 0.89-1.30). There was no difference in attendance using SMS reminders versus other reminders (RR 0.98, 95% CI 0.94-1.02, respectively). To address the limitation of the older search, we also reviewed more recent literature. CONCLUSIONS: The results for health care provider support interventions on diagnosis and management outcomes are generally consistent with modest benefits. Trials using mobile technology-based photos reported reductions in correct diagnoses when compared to the gold standard. SMS appointment reminders have modest benefits and may be appropriate for implementation. High quality trials measuring clinical outcomes are needed. Please see later in the article for the Editors' Summary.

The effectiveness of mobile-health technology-based health behaviour change or disease management interventions for health care consumers: a systematic review.

BACKGROUND: Mobile technologies could be a powerful media for providing individual level support to health care consumers. We conducted a systematic review to assess the effectiveness of mobile technology interventions delivered to health care consumers. METHODS AND FINDINGS: We searched for all controlled trials of mobile technology-based health interventions delivered to health care consumers using MEDLINE, EMBASE, PsycINFO, Global Health, Web of Science, Cochrane Library, UK NHS HTA (Jan 1990-Sept 2010). Two authors extracted data on allocation concealment, allocation sequence, blinding, completeness of follow-up, and measures of effect. We calculated effect estimates and used random effects meta-analysis. We identified 75 trials. Fifty-nine trials investigated the use of mobile technologies to improve disease management and 26 trials investigated their use to change health behaviours. Nearly all trials were conducted in high-income countries. Four trials had a low risk of bias. Two trials of disease management had low risk of bias; in one, antiretroviral (ART) adherence, use of text messages reduced high viral load (>400 copies), with a relative risk (RR) of 0.85 (95% CI 0.72-0.99), but no statistically significant benefit on mortality (RR 0.79 [95% CI 0.47-1.32]). In a second, a PDA based intervention increased scores for perceived self care agency in lung transplant patients. Two trials of health behaviour management had low risk of bias. The pooled effect of text messaging smoking cessation support on biochemically verified smoking cessation was (RR 2.16 [95% CI 1.77-2.62]). Interventions for other conditions showed suggestive benefits in some cases, but the results were not consistent. No evidence of publication bias was demonstrated on visual or statistical examination of the funnel plots for either disease management or health behaviours. To address the limitation of the older search, we also reviewed more recent literature. CONCLUSIONS: Text messaging interventions increased adherence to ART and smoking cessation and should be considered for inclusion in services. Although there is suggestive evidence of benefit in some other areas, high quality adequately powered trials of optimised interventions are required to evaluate effects on objective outcomes.

The effectiveness of M-health technologies for improving health and health services: a systematic review protocol.

BACKGROUND: The application of mobile computing and communication technology is rapidly expanding in the fields of health care and public health. This systematic review will summarise the evidence for the effectiveness of mobile technology interventions for improving health and health service outcomes (M-health) around the world. FINDINGS: To be included in the review interventions must aim to improve or promote health or health service use and quality, employing any mobile computing and communication technology. This includes: (1) interventions designed to improve diagnosis, investigation, treatment, monitoring and management of disease; (2) interventions to deliver treatment or disease management programmes to patients, health promotion interventions, and interventions designed to improve treatment compliance; and (3) interventions to improve health care processes e.g. appointment attendance, result notification, vaccination reminders.A comprehensive, electronic search strategy will be used to identify controlled studies, published since 1990, and indexed in MEDLINE, EMBASE, PsycINFO, Global Health, Web of Science, the Cochrane Library, or the UK NHS Health Technology Assessment database. The search strategy will include terms (and synonyms) for the following mobile electronic devices (MEDs) and a range of compatible media: mobile phone; personal digital assistant (PDA); handheld computer (e.g. tablet PC); PDA phone (e.g. BlackBerry, Palm Pilot); Smartphone; enterprise digital assistant; portable media player (i.e. MP3 or MP4 player); handheld video game console. No terms for health or health service outcomes will be included, to ensure that all applications of mobile technology in public health and health services are identified. Bibliographies of primary studies and review articles meeting the inclusion criteria will be searched manually to identify further eligible studies. Data on objective and self-reported outcomes and study quality will be independently extracted by two review authors. Where there are sufficient numbers of similar interventions, we will calculate and report pooled risk ratios or standardised mean differences using meta-analysis. DISCUSSION: This systematic review will provide recommendations on the use of mobile computing and communication technology in health care and public health and will guide future work on intervention development and primary research in this field.