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Little is known about “new media” use, defined as media content created or consumed on demand on an electronic device, by patients in emergency department (ED) settings. The application of this technology has the potential to enhance health care beyond the index visit.
The objectives are to determine the prevalence and characteristics of ED patients’ use of new media and to then define and identify the potential of new media to transcend health care barriers and improve the public’s health.
Face-to-face, cross-sectional surveys in Spanish and English were given to 5,994 patients who were sequentially enrolled from July 12 to August 30, 2012. Data were collected from across a Southern Connecticut health care system’s 3 high-volume EDs for 24 hours a day, 7 days a week for 6 weeks. The EDs were part of an urban academic teaching hospital, an urban community hospital, and an academic affiliate hospital.
A total of 5,994 (89% response rate) ED patients reported identical ownership of cell phones (85%,
There is a critical mass of ED patients who use new media. Older persons are less comfortable texting and using smartphone apps. Income status has a positive relationship with smartphone ownership and use of smartphone apps. Regardless of income, however, texting and ownership of smartphones was highest for Latinos and black non-Latinos. These findings have implications for expanding health care beyond the ED visit through the use of cell phones, smartphones, texting, the Internet, and health care apps to improve the health of the public.
New media is part of the communication science lexicon—yet it is frequently omitted from the health care literature and often is incorrectly interchanged with cell phones. “New media” is defined as media content created or consumed on demand on an electronic device (eg, mobile phones, computers, tablets, etc) [
According to Jenkins, new media can be thought of “as the convergence of 3 concepts—media convergence, participatory culture, and collective intelligence” [
We designed and administered a cross-sectional survey of patients presenting to 3 EDs in southern Connecticut that are part of the Yale-New Haven Health System (YNHHS). Data were collected over 24 hours a day, 7 days a week for a total of 6 weeks. During the study period, the annual census for Yale-New Haven Hospital York Street Campus, an urban academic teaching hospital, was approximately 81,000 adult visits per year and serves a population that is 52% white, 28% black, and 18% Hispanic, with 40% receiving Medicaid. Bridgeport Hospital, an urban academic affiliate of YNHHS, receives approximately 45,000 adult visits per year and serves a population that is 44% white, 38% black, and 15% Hispanic, with 46% receiving Medicaid. The annual census for the Saint Raphael Campus ED, best described as an urban community ED, was approximately 45,000 visits per year and serves a population that is 36% white, 31% black, and 34% Hispanic, with 50% receiving Medicaid.
Research assistants (RAs) enrolled patients presenting to 1 of the 3 EDs. Twenty-two trained RAs enrolled patients on every ED shift, 24 hours a day, 7 days a week, during a 6-week period (July 12 to August 30, 2012). Patients were excluded if they were 17 years of age or younger; alcohol or drug impaired; had a condition that precluded interview; were in police custody; had active psychosis, suicidal, or homicidal ideation; or were unwilling to consent. RAs entered patient data into the electronic data capture system based on time of patient arrival (
Patient flow diagram.
Our research consortium reviewed and selected questions from the information technology study conducted at Brown University’s ED [
The survey was pilot tested over the course of 1 month (with observers) and tested for fourth grade Flesch-Kincaid readability. Some data regarding race were missing (<1%) due to confusion between “race” and “ethnicity.” Thus, participants who reported Latino/Hispanic as a racial category were corrected using hot deck imputation [
We compared ED patients’ new media use between 3 urban EDs in southern Connecticut. The survey was conducted in English and Spanish. We derived point estimates with 95% confidence intervals (CI) using the normal-theory method for a binomial parameter. Variables of interest include
A total of 5994 (89% response rate) ED patients consented to participate in the study from southern Connecticut (
While not directly comparable, as these 2 surveys are from 2 different sampling frames, the Pew Foundation and the California HealthCare Foundation (CHCF) conducted a similar media health care study during the same time period [
Demographic breakdown of 3 emergency departments, July 12 to August 30, 2012.
|
ED #1 | ED #2 | ED #3 | Total |
Demographic | Yale-New Haven Hospital York Street Campus | Yale-New Haven Hospital Saint Raphael Campus | Bridgeport Hospital | All EDs, combined (N=5788) |
Female | 1081/1922 (56.24%) | 1177/1966 (59.87%) | 1124/1900 (59.16%) | 3382/5788 (58.43%) |
Mean age, year (SD) | 45 (18) | 48 (21) | 44 (19) | 46 (20) |
White, Non-Hispanic | 891/1888 (47.19%) | 889/1954 (45.50%) | 630/1877 (33.56%) | 2410/5719 (42.14%) |
Black, Non-Hispanic | 567/1888 (30.03%) | 774/1954 (39.61%) | 610/1877 (32.50%) | 1951/5719 (34.11%) |
Hispanic | 430/1888 (22.78%) | 291/1954 (14.89%) | 637/1877 (33.94%) | 1358/5719 (23.75%) |
Spanish language survey | 68/1922 (3.54%) | 51/1966 (2.59%) | 52/1900 (2.74%) | 171/5788 (2.95%) |
None to some schooling | 253/1922 (13.16%) | 304/1966 (15.46%) | 288/1900 (15.16%) | 845/5788 (14.60%) |
Income <$15,000 | 583/1667 (34.97%) | 674/1431 (47.10%) | 518/1409 (36.76%) | 1775/4507 (39.38%) |
New media use prevalence and taxonomies, July 12 to August 30, 2012.
|
|
ED #1 | ED #2 | ED #3 | Total |
New media profile |
|
Yale-New Haven Hospital York Street Campus | Yale-New Haven Hospital Saint Raphael Campus | Bridgeport Hospital | All EDs combined (N=5788) |
Cell phone ownership |
|
1677/1922 (87.25%) | 1591/1966 (80.93%) | 1666/1900 (88.68%) | 4934/5788 (85.25%, 95% CI 84-86) |
Cell phone use | Calling | 1666/1677 (99.34%) | 1572/1591 (98.81%) | 1654/1666 (99.28%) | 4892/4934 (99.15%, 95% CI 98.9-99.4) |
|
Texting | 1235/1677 (73.64%) | 1141/1592 (71.72%) | 1219/1666 (73.17%) | 3595/4935 (72.86%, 95% CI 72-74) |
|
E-mailing | 654/1677 (39.00%) | 624/1591 (39.22%) | 803/1666 (48.20%) | 2081/4934 (42.18%, 95% CI 41-44) |
|
Surfing Internet | 762/1677 (45.44%) | 652/1591 (40.98%) | 869/1666 (52.16%) | 2283/4934 (46.27%, 95% CI 45-48) |
|
Social networking | 664/1677 (39.59%) | 545/1591 (34.26%) | 694/1666 (41.66%) | 1903/4934 (38.57%, 95% CI 37-40) |
|
Playing games | 422/1677 (25.16%) | 430/1591 (27.03%) | 564/1666 (33.85%) | 1416/4934 (28.70%, 95% CI 27-30) |
Mobile phone ownership |
|
837/1677 (49.91%) | 716/1591 (45.00%) | 947/1666 (56.84%) | 2500/4934 (50.67%, 95% CI 49-52) |
Mobile phone operating system | iPhone | 404/837 (48.27%) | 278/716 (38.83%) | 411/947 (43.40%) | 1093/2500 (43.72%, 95% CI 42-46) |
|
Android | 333/837 (39.78%) | 333/716 (46.51%) | 451/947 (47.62%) | 1117/2500 (45.88%, 95% CI 43-47) |
Mobile phone contract type | Contract, Limited Min | 909/1677 (54.20%) | 687/1591 (43.18%) | 850/1666 (51.02%) | 2446/4934 (49.57%, 95% CI 48-51) |
|
Contract, Unlimited Min | 909/1677 (54.20%) | 687/1591 (43.18%) | 850/1666 (51.02%) | 2446/4934 (49.57%, 95% CI 48-51) |
|
Medicaid phone (aka Obama phone) | 66/1677 (3.94%) | 84/1591 (5.28%) | 63/1666 (3.78%) | 213/4934 (4.32%, 95% CI 4-5) |
|
Pay-as-you-go | 255/1677 (15.21%) | 391/1591 (25.58%) | 353/1666 (21.19%) | 999/4934 (20.25%, 95% CI 19-21) |
New media device ownership and use by ED survey participants versus Pew-CHCF study data, July 12 to August 30, 2012.
Demographic (N=5788) |
|
Text Messaging, 73% (CI 95% 72-74) | Mobile Phone Ownership, 51% (CI 95% 49-52) | Use of Health Apps, 19% (CI 95% 17-21) | Health Info Seeking, 60% (CI 95% 58-62) | Personal Health Records, 6% (CI 95% 6-8) | ||||||||
|
|
EDs | Pew-CHCF |
|
EDs | Pew-CHCF |
|
EDs | Pew-CHCF |
|
EDs | Pew-CHCF |
|
EDs |
Gender | Men | 68 |
81 | <.001 | 47 |
46 | >.05 | 17 |
16 | >.05 | 53 |
29 | <.001 | 7 |
|
Women | 76 |
80 | <.001 | 53 |
45 | <.001 | 20 |
23 | .007 | 64 |
33 | <.001 | 6 |
Age | 18-29 | 96 |
97 | .04 | 79 |
66 | <.001 | 18 |
24 | <.001 | 65 |
42 | <.001 | 7 |
|
30-49 | 84 |
92 | <.001 | 54 |
59 | <.001 | 20 |
19 | >.05 | 57 |
39 | <.001 | 8 |
|
50-64 | 55 |
72 | <.001 | 30 |
34 | .004 | 17 |
16 | >.05 | 53 |
19 | <.001 | 7 |
|
65+ | 16 |
34 | <.001 | 10 |
11 | >.05 | 16 |
10 | >.05 | 33 |
9 | <.001 | 2 |
Race/Ethnicity | White, Non-Hispanic | 65 |
79 | <.001 | 44 |
42 | >.05 | 21 |
19 | >.05 | 61 |
27 | <.001 | 8 |
|
Black, Non-Hispanic | 77 |
80 | .008 | 54 |
47 | <.001 | 17 |
21 | .01 | 57 |
35 | <.001 | 5 |
|
Hispanic | 79 |
85 | <.001 | 56 |
49 | <.001 | 18 |
15 | .03 | 61 |
38 | <.001 | 6 |
Annual Household Income | <$30,000 | 71 |
78 | <.001 | 45 |
35 | <.001 | 16 |
14 | >.05 | 63 |
28 | <.001 | 3 |
|
$30,000-$59,999 | 76 |
78 | >.05 | 56 |
42 | <.001 | 21 |
21 | >.05 | 59 |
30 | <.001 | 8 |
|
$60,000-$89,999 | 78 |
89 | <.001 | 60 |
56 | >.05 | 23 |
21 | >.05 | 61 |
37 | <.001 | 11 |
|
≥$90,000 | 80 |
90 | <.001 | 70 |
68 | >.05 | 26 |
23 | >.05 | 67 |
37 | <.001 | 22 |
Education Level | No HS Diploma | 55 |
65 | <.001 | 33 |
21 | <.001 | ------ | Not reported |
|
54 |
17 | <.001 | 2 |
|
High School Graduate | 69 |
75 | <.001 | 42 |
36 | <.001 | 14 |
11 | .04 | 55 |
26 | <.001 | 3 |
|
Some College | 83 |
85 | .01 | 62 |
50 | <.001 | 20 |
24 | .02 | 62 |
33 | <.001 | 9 |
|
College+ | 78 |
86 | <.001 | 63 |
61 | >.05 | 24 |
22 | >.05 | 65 |
38 | <.001 | 15 |
While the conventional main focus of hospital EDs has been to provide immediate treatment to patients with acute conditions, the use of new media could extend the reach of the ED visit. These clinical encounters provide unique and important opportunities to the clinicians and system of health care to positively influence individual health behavior beyond the emergency department setting.
We sought to define and differentiate new media from cell phone ownership to bring health care operationalization of electronic devices consistent with the communication literature. Furthermore, because information technology is already playing an increasing role in improving health care, delivering interventions, navigating the health care system, and improving the public’s health at large, we wanted to determine (beyond the anecdotal) that sufficient numbers of ED patients own and use new media. Survey participants’ ownership of cell phones (4934/5788, 85.25%) and device usage for calling (4892/4934, 99.15%) and texting (3595/4935, 72.86%) were high. Among all cell phone owners, mobile phone ownership was moderate (2500/4934, 50.67%) with minorities reporting the highest rate of ownership. Benchmarked against the Pew-CHCF study [
EDs are concerned with enhancing continuity of care throughout an entire health system and optimizing cost containment. As a result, they have generally heightened and expanded their attention to pre-hospital and post-discharge care implications of acute care. Finding new forms of effective communication facilitates expanding the scope of prevention, health promotion, health maintenance, and disease management services [
ED patients are segmented in this study to those most likely to own and use new media technology. Hence, we determined the characteristics of ED patients that own and use new media to tailor intervention strategies. Text messaging can be used to provide health information to most cell phone users (depending on their phone plan). We examined the relationship between ED patients’ use of text messaging and individual patient characteristics. A higher prevalence of text messaging was reported by ED patients who were female, younger, nonwhite, and more educated (
While mobile phone ownership is not as ubiquitous as overall cell phone ownership, mobile phone technology is important for behavioral interventions (eg, mobile phone health apps). Thus, we examined the relationship between ED patients’ mobile phone ownership and individual patient characteristics. Participants who were female, younger, nonwhite, and had higher income reported greater ownership of mobile phone technology (
Female and younger ED patients who owned mobile phones, as well as those with greater educational attainment, reported higher online searching for health or medical information. Consistently, ED participants reported greater health information seeking than the general population as measured by Pew-CHCF.
We found similar patterns of usage of cell and mobile phones in both the ED patient population and the general population with the exception that ED patients are more likely to use desktop and laptop computers to seek health information than a mobile phone and the general population is more likely to rely on e-mail to communicate through a laptop or desktop computer.
We compared the prevalence of health information seeking by ED patients with that of the general population. ED participants invariably reported greater health information seeking than participants in the Pew-CHCF survey. Individuals presenting to the emergency department likely have health conditions that trigger new media use to manage disease and seek information on treatment and care.
Racial/ethnic minorities and persons of lower socioeconomic status were overrepresented in the EDs as compared to the general US catchment area. Compared to the benchmark Pew-CHCF survey, our ED sample was similar in terms of gender but (predictably) was made up of more nonwhite participants who were poorer and had less schooling.
Our study formally defines new media and disambiguates cell phones from mobile phones. We established a scientifically derived baseline of new media use for ED patients and determined that a critical mass of patients use new media and would perhaps benefit from new media technology to manage their health and seek information. Most importantly, we found that more marginalized populations—such as the poor, homeless [
emergency department
California HealthCare Foundation
confidence interval
research assistant
Yale-New Haven Health System
The authors thank the RAs who recruited survey participants and collected data from the hospital emergency departments. The authors also thank the members of the Pew Foundation for allowing the use of their data.
None declared.