Journal:Use of handheld computers in clinical practice: A systematic review

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Full article title Use of handheld computers in clinical practice: A systematic review
Journal BMC Medical Informatics & Decision Making
Author(s) Mickan, Sharon; Atherton, Helen; Roberts, Nia Wyn; Heneghan, Carl; Tilson, Julie K
Author affiliation(s) Nuffield Department of Primary Care Health Sciences, University of Oxford;
Division of Biokinesiology and Physical Therapy, University of Southern California
Primary contact Email: Sharon.mickan@phc.ox.ac.uk
Year published 2014
Volume and issue 14
Page(s) 56
DOI 10.1186/1472-6947-14-56
ISSN 1472-6947
Distribution license Creative Commons Attribution 2.0
Website http://www.biomedcentral.com/1472-6947/14/56

Abstract

Background

Many healthcare professionals use smartphones and tablets to inform patient care. Contemporary research suggests that handheld computers may support aspects of clinical diagnosis and management. This systematic review was designed to synthesise high quality evidence to answer the question; Does healthcare professionals’ use of handheld computers improve their access to information and support clinical decision making at the point of care?

Methods

A detailed search was conducted using Cochrane, MEDLINE, EMBASE, PsycINFO, Science and Social Science Citation Indices since 2001. Interventions promoting healthcare professionals seeking information or making clinical decisions using handheld computers were included. Classroom learning and the use of laptop computers were excluded. Two authors independently selected studies, assessed quality using the Cochrane Risk of Bias tool and extracted data. High levels of data heterogeneity negated statistical synthesis. Instead, evidence for effectiveness was summarised narratively, according to each study’s aim for assessing the impact of handheld computer use.

Results

We included seven randomised trials investigating medical or nursing staffs’ use of Personal Digital Assistants. Effectiveness was demonstrated across three distinct functions that emerged from the data: accessing information for clinical knowledge, adherence to guidelines and diagnostic decision making. When healthcare professionals used handheld computers to access clinical information, their knowledge improved significantly more than peers who used paper resources. When clinical guideline recommendations were presented on handheld computers, clinicians made significantly safer prescribing decisions and adhered more closely to recommendations than peers using paper resources. Finally, healthcare professionals made significantly more appropriate diagnostic decisions using clinical decision making tools on handheld computers compared to colleagues who did not have access to these tools. For these clinical decisions, the numbers need to test/screen were all less than 11.

Conclusion

Healthcare professionals’ use of handheld computers may improve their information seeking, adherence to guidelines and clinical decision making. Handheld computers can provide real time access to and analysis of clinical information. The integration of clinical decision support systems within handheld computers offers clinicians the highest level of synthesised evidence at the point of care. Future research is needed to replicate these early results and to identify beneficial clinical outcomes.

Keywords: Handheld computers; Smartphone; Information-seeking behaviour; Evidence-based practice; Knowledge translation; Clinical decision support systems; Clinical guidelines; Diagnostic decision making

Background

Increasing numbers of healthcare professionals use handheld computers that offer instant access to vast amounts of information via the internet and healthcare applications (apps).[1] Over the last 10 years there has been a rapid and accelerating rate of innovation in handheld computers, from personal digital assistants (PDAs) towards more powerful, versatile and internet connected devices. As the rate of adoption of handheld computers has increased, individual patterns of usage have moved from that of communication and personal diary management towards information seeking and decision support.[2] Today’s clinicians can use handheld computers to search the internet for evidence and guidance on drugs and clinical conditions, use clinical decision support systems (CDSS) and access highly detailed patient information from clinical and laboratory investigations.

At the same time, there has been a change in the acceptance of using handheld computers in healthcare settings. Now, most students and many professionals are enthusiastic about using smartphones and tablet computers, and they take them wherever they go.[3] Along with this increasing adoption of handheld computers, there has been a massive growth in the volume of synthesized research information, healthcare oriented apps, databases and CDSSs.

This has also sparked an increased production of feasibility research, which has yet to recommend strategies for engagement, efficacy or effectiveness of mobile health initiatives.[4] While both early and current systematic reviews offer tentative and sceptical conclusions, there is equipoise in the literature. A systematic review of the use of PDAs in clinical decision making reported an increase in data collection quality and concluded that the use of decision support software improved the appropriateness of diagnostic and treatment decisions.[2] In a broader and contemporary systematic review of mHealth technologies, modest benefits were reported for improved clinical diagnosis and management support, and mixed outcomes were reported for efficient and accurate documentation.[3] Further, there was no clear benefit for educational interventions and some evidence of reduced quality of clinical assessment, when using mobile technology based photos.

When healthcare professionals communicate with patients, there is high quality evidence to support the use of mobile phones to transmit short message service (SMS) reminders to improve attendance at health care appointments.[5][6] Further, text messaging interventions were shown to increase adherence to antiretroviral therapy in low-income settings and increased smoking cessation in high income settings.[7]

References

  1. Mosa, A.S.; Yoo, I.; Sheets, L. (2012). "A systematic review of healthcare applications for smartphones". BMC Medical Informatics & Decision Making 12: 67. doi:10.1186/1472-6947-12-67. PMID 22781312. 
  2. 2.0 2.1 Divall, P.; Camosso-Stefinovic, J.; Baker, R. (2013). "The use of personal digital assistants in clinical decision making by health care professionals: a systematic review". Health Informatics Journal 19 (1): 16-28. doi:10.1177/1460458212446761. PMID 23486823. 
  3. 3.0 3.1 Free, C.; Phillips, G.; Watson, L.; Galli, L.; Felix, L.; Edwards, P.; Patel, V.; Haines, A. (2013). "The effectiveness of mobile-health technologies to improve health care service delivery processes: a systematic review and meta-analysis". PLoS Medicine 10 (1): e1001363. doi:10.1371/journal.pmed.1001363. PMC PMC3566926. PMID 23458994. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3566926. 
  4. Tomlinson, M.; Rotheram-Borus, M.J.; Swartz, L.; Tsai, A.C. (2013). "Scaling up mHealth: where is the evidence?". PLoS Medicine 10 (2): e1001382. doi:10.1371/journal.pmed.1001382. PMC PMC3570540. PMID 23424286. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3570540. 
  5. Car, J.; Gurol-Urganci, I.; de Jongh, T.; Vodopivec-Jamsek, V.; Atun, R. (2012). "Mobile phone messaging reminders for attendance at healthcare appointments". Cochrane Database of Systematic Reviews 7: Cd007458. doi:10.1002/14651858.CD007458. PMID 22786507. 
  6. Guy, R.; Hocking, J.; Wand, H.; Stott, S.; Ali, H.; Kaldor, J. (2012). "How effective are short message service reminders at increasing clinic attendance? a meta-analysis and systematic review". Health Services Research 47 (2): 614-632. doi:10.1111/j.1475-6773.2011.01342.x. PMC PMC3419880. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3419880. 
  7. Free, C.; Phillips, G.; Galli, L.; Watson, L.; Felix, L.; Edwards, P.; Patel, V.; Haines, A. (2013). "The effectiveness of mobile-health technology-based health behaviour change or disease management interventions for health care consumers: a systematic review". PloS Medicine 10 (1): e1001362. doi:10.1371/journal.pmed.1001362. PMC PMC3548655. PMID 23349621. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3548655. 

Notes

This presentation is faithful to the original, with only a few minor changes to presentation. In most of the article's references DOIs and PubMed IDs were not given; they've been added to make the references more useful.