In this monthly digest of recent peer-reviewed publications in applied clinical informatics, we cover notable articles in a field.
Google Glass did draw a lot of attention before being discontinued. In the last issue of the journal Applied Clinical Informatics (ACI), authors from the University of Chicago asked hospitalized patients about their familiarity with "Glass" technology, and their privacy and comfort levels if physicians wore such devices. Most respondents (73%) were unfamiliar with Glass. Privacy was a concern for 46% of respondents, but 64% would be comfortable with their doctor wearing Glass 1.
A number of interesting papers on mobile technologies were published recently. A systematic review of the impact of mobile health interventions on chronic disease outcomes in developing countries shows a positive impact on chronic disease outcomes, improved attendance rates, clinical outcomes, and health-related quality of life, and was cost-effective 2. Another systematic review and meta-analysis studied the effect of game-based interventions in the rehabilitation of diabetics. Only four studies met the following inclusion criteria: patients with diabetes (type 1 or type 2), game-based interventions, and randomized controlled trials. In three studies, game-based interventions show no effect on self-management of blood glucose levels as compared to usual care or waiting lists. However the authors mentioned that due to the weak methodological quality of the included studies, the real effect could potentially be substantially different 3. A randomized trial compared a smartphone mobile application vs. text messaging in terms of support for smoking cessation in young adult smokers 18-30 years old (n = 102), and used a 30-day smoking cessation endpoint. Overall, 60% of participants used mobile services. As a result, participants in text messaging abstained more after 30 days (p<0.05) than those who were dedicated to the mobile application 4.
Communication between providers in the hospital is critical. However, problems like interruption and one-way communication require better solutions. Pre-post evaluation of commercial mobile application was reported in ACI. Only utilization metrics and survey responses of clinicians’ perceptions were reported, limiting the generalizability of results. Residents and social workers/clinical resource coordinators were the largest per person users of this communication system, receiving 18 (IQR 5–36) and 14 (IQR 5–29) messages per person per day 5. As similar systems hit the market, a more robust evaluation targeting objective metrics is required to show differences as compared to routine standard messaging/communication systems.
A couple of excellent reviews were recently published in the special 25th anniversary edition of the IMIA Yearbook of Medical Informatics, 2016. In the article "Electronic Health Records: Then, Now, and in the Future," Dr. Evans, from Intermountain Healthcare, describes the state of EHRs in 1992, their evolution by 2015, and where EHRs are expected to be in 25 years 6. Another article systematically describes health-enabling and ambient assistive technologies in 1992, their evolution over the last 25 years, and a projection of where the field is expected to be in the next 25 years 7. The state-of-the-art article "Clinical Information Systems – From Yesterday to Tomorrow" from Dr. Gardner, a Clinical Informatics pioneer, includes 150 references, reviews the history of clinical information systems over the past twenty-five years, and projects anticipated changes to those systems over the next twenty-five years 8.
The availability of massive data sets allows easy use of modern tools and techniques to build prediction models and generate scores. The hospital readmission model was developed using data from over 1.1 million hospital admissions at 70 hospitals. However, such scores, even with relatively good calibration and performance, should still be used with caution to predict individual readmission risk. The utility of such predictive models could be beneficial in hospital comparison and outcome research 9.
Implementation of computerized physician order entry (CPOE) leads the improvement of safety in hospitals, even in light of controversial publications. A group of researchers published a study that evaluated the ability of pediatric CPOE systems to identify medication errors in test scenarios using the Leapfrog pediatric CPOE evaluation tool. This validated tool identified CPOE orders that could potentially harm the patient. In the present 2 year-study in 41 pediatric hospitals, CPOE identified, on average, 62% of errors ranging from 23 to 91% 10.
1. Prochaska MT, Press VG, Meltzer DO, Arora VM. Patient Perceptions of Wearable Face-Mounted Computing Technology and the Effect on the Doctor-Patient Relationship. Appl Clin Inform. 2016;7(4):946-953. PMID:27730249.
2. Beratarrechea A, Lee AG, Willner JM, Jahangir E, Ciapponi A, Rubinstein A. The impact of mobile health interventions on chronic disease outcomes in developing countries: a systematic review. Telemed J E Health. 2014;20(1):75-82. PMID:24205809.
3. Christensen J, Valentiner LS, Petersen RJ, Langberg H. The Effect of Game-Based Interventions in Rehabilitation of Diabetics: A Systematic Review and Meta-Analysis. Telemed J E Health. 2016;22(10):789-797. PMID:27042966.
4. Buller DB, Borland R, Bettinghaus EP, Shane JH, Zimmerman DE. Randomized trial of a smartphone mobile application compared to text messaging to support smoking cessation. Telemed J E Health. 2014;20(3):206-214. PMID:24350804.
5. Patel N, Siegler JE, Stromberg N, Ravitz N, Hanson CW. Perfect Storm of Inpatient Communication Needs and an Innovative Solution Utilizing Smartphones and Secured Messaging. Appl Clin Inform. 2016;7(3):777-789. PMID:27530155.
6. Evans RS. Electronic Health Records: Then, Now, and in the Future. Yearb Med Inform. 2016;Suppl 1:S48-61. PMID:27199197.
7. Haux R, Koch S, Lovell NH, Marschollek M, Nakashima N, Wolf K-H. Health-Enabling and Ambient Assistive Technologies: Past, Present, Future. Yearb Med Inform. 2016;Suppl 1(Suppl. 1):1-16. PMID:27362588.
8. Gardner RM. Clinical Information Systems - From Yesterday to Tomorrow. Yearb Med Inform. 2016;Suppl 1:S62-75. PMID:27362589.
9. Tabak YP, Sun X, Nunez CM, Gupta V, Johannes RS. Predicting Readmission at Early Hospitalization Using Electronic Clinical Data: An Early Readmission Risk Score. Med Care. 2016;0(0):1-9. PMID:27755391.
10. Chaparro JD, Classen DC, Danforth M, Stockwell DC, Longhurst CA. National trends in safety performance of electronic health record systems in children’s hospitals. J Am Med Inform Assoc. September 2016. PMID:27638908.
About the Contributor
Vitaly Herasevich, MD, PhD, MSc, FCCM, CPHIMS is Associate Professor of Anesthesiology and Medicine in Department of Anesthesiology at Mayo Clinic. His interest in the area of medical informatics extends back to 1995 with specific concentration on the applied clinical informatics in critical care and science of healthcare delivery. Dr. Herasevich has interest in studying and development clinical syndromic surveillance alerting systems ("sniffers"), clinical data visualization (novel patient-centered EMR) and complex large data warehousing for healthcare predictive and prescriptive analytics as well as outcome reporting. He is author of more than 60 Pubmed cited articles and wrote two editions of book "Computer for Physician". As a part of education effort Dr. Herasevich serves Clinical Informatics Fellowship program as Associate Program Director, appointed with full faculty privileges in Mayo Graduate School and teaching class “Health Information Technology evaluation”. He is active within informatics and professional societies serving number of committees.
More information at lab web page - http://www.mayo.edu/research/labs/clinical-informatics-intensive-care/