Isabella Chu, MPH

Intervention

This study utilized Medigram (Medigram, Inc., https://medigram.com), a free HCGM application for smartphones (available on iOS and Android) that allows users to send and receive encrypted, password‐protected text messages via the hospital wireless fidelity (Wi‐Fi) network, using commercial cellular networks as backup.

Study Design

In an eight‐week prospective, cluster‐randomized, controlled trial conducted at Stanford Hospital (June 25, 2012August 17, 2012), three of five inpatient medicine teams were randomized to use Medigram in addition to the existing hospital paging system (HCGM teams); the remaining two teams were assigned to use hospital paging only (control teams). Each team included one attending physician, one resident, two interns, two medical students, and a case manager. According to prescheduled rotations, attendings rotated every two weeks, and residents, interns, and medical students rotated every four weeks. All rotations were either off‐service or off‐site, with the exception of two attendings who rotated between study teams but within their experimental designations. Case managers remained with the same team. Additionally, the satellite pharmacy was provided with an HCGM‐equipped smartphone to communicate with experimental teams.

Participation was voluntary, with a 96% participation rate (n=75). HCGM teams downloaded the free application onto their smartphones. Participants without smartphones were provided with one for the duration of the study. Proper application use was demonstrated by one researcher in a 10‐minute standardized presentation. HCGM teams were encouraged to use the application in lieu of paging, except when patient care could be compromised.

All participants completed linked baseline and post‐study surveys. Gift cards valued at $10 were provided on completion of each survey. Though participants were assigned to either HCGM or control groups based on the randomized assignment of their preset cluster (hospital team) to an HCGM or control group, analysis was performed on the individual level due to the hospital's set rotation schedule, which resulted in dynamic, frequently changing clusters. We also compared average length of stay and time of discharge for patients treated by control versus HCGM teams. Clinical outcome data were obtained from the hospital's database using Midas+ Statit Solutions (Midas+ Statit Solutions Group, Tucson, AZ). Survey and clinical outcome data were analyzed in Stata (StataCorp, College Station, TX) and R (R Foundation for Statistical Computing, Vienna, Austria).

Survey Design and Analysis

Identical, anonymous baseline surveys were administered to control and HCGM teams. These surveys assessed attitudes toward the hospital paging system using a 5‐point Likert scale (1=low, 5=high) to evaluate perceived measures of effectiveness, workflow integration, and overall satisfaction. Wilcoxon rank sum tests were used to compare control and HCGM group responses to these questions. Free response questions asked participants to list the most effective and ineffective aspects of the paging system.

Post‐study surveys included all baseline survey questions, as well as questions about personal texting behavior. Post‐study HCGM surveys also included a parallel set of questions rating the HCGM application on the same measures of perceived effectiveness, workflow integration, and overall satisfaction. Wilcoxon signed rank tests were used to compare HCGM participants' baseline evaluations of paging to their post‐study evaluations of the HCGM application. Baseline and post‐study surveys were linked by the last four digits of respondent cell phone numbers. To compare control and HCGM group perceptions of the hospital paging system at study completion, post‐study survey responses were evaluated using Wilcoxon rank sum tests. The family‐wise error rate was left unadjusted due to concerns around inflated type II errors, given the high degree of correlation between survey questions.

All free response questions were analyzed using thematic analysis and grounded theory. After reviewing responses to each question, a list of overarching themes was constructed. Two researchers then independently reviewed each free‐response entry to assign it to one or more of these themes (some responses included several ideas with distinct themes). Entries with concordant theme assignments (90%) were coded as such; nonconcordant entries required an additional round of review to reach concordance. Finally, objective outcome measures including length of stay and time of discharge were analyzed by two‐sample t test.

Information Security

The HCGM application in this study features 256‐bit encryption technology and requires a six‐digit password to access texts. For added security, a study‐dedicated server (HP ProLiant DL 180 G6; Hewlett‐Packard Co., Palo Alto, CA) with 4‐TB hard drive capacity (4 Seagate Barracuda ST1000DM003 1 TB 7200 RPM internal hard drives; Seagate Technology PLC, Cupertino, CA) was installed in the Stanford School of Medicine Data Center to store encrypted text messages. Data stored on the phones/server were accessible only to study participants, not researchers. These security measures were approved by Stanford Hospital and Stanford School of Medicine's security and privacy review process.

Hospital Paging System

Stanford Hospital and Clinics is a quaternary care academic medical center with 613 beds, 49 operating rooms, and over 25,000 inpatient admissions per year.[8] The institution uses one‐way alphanumeric pagers (primary model: Daviscomm BR802 Flex Pager from USA Mobility, secondary model: Sun Telecom Titan 3 Plus from USA Mobility; USA Mobility Inc., Springfield, VA). USA Mobility operates the largest one‐ and two‐way paging networks in the United States.[9]

Control and HCGM Group Characteristics

Control and HCGM groups were well matched demographically (Table 1). The average ages of control and HCGM group members were 30.10 and 30.95, respectively. Both groups were 59% male and 41% female.

A similar distribution of team member roles was observed in both groups, with two exceptions. First, the proportion of attending respondents in the HCGM group was lower than in the control group. This was due to the fact that several HCGM attendings entered discrepant ID codes on their surveys, thus making it impossible to link baseline and post‐study responses; these data were excluded. Additionally, two HCGM attendings were on service for four, rather than the standard two weeks, meaning two additional data points from unique attendings could not be obtained. Second, the experimental group included four pharmacists, whereas the control group did not. As a sensitivity test, we analyzed the data excluding the pharmacists, and this did not change our results.

Baseline Evaluations of the Hospital Paging System

At baseline, there were no significant differences between control and HCGM participants' perceptions of paging effectiveness (see Supporting Table 1, in the online version of this article). On a 5‐point rating scale (1=low, 5=high), 63 subjects rated their overall satisfaction with the paging system an average of 2.79 (95% confidence interval: 2.55‐3.03).

In free response questions, components of the paging system most frequently cited as effective included: reliability of message transmission, alphanumeric text paging, and ease of use (30.4%, 25.0%, and 14.3% of 56 respondents, respectively) (Table 2). Ineffective aspects included: time wasted waiting for responses to pages, the unidirectional nature of pagers, and needing to find a computer to send a text page (29.3%, 24.1%, and 20.7% of 58 respondents, respectively) (Table 2).

Baseline Utilization of Text Messaging

The majority of participants were familiar with text messaging and regularly used it personally and professionally prior to the start of the study. 90.5% of participants (n = 63) reported sending an average of 1 personal text messages per day, with the largest proportion (39.7%) sending 1‐5 texts per day (see Supporting Figure 1A in the online version of this article). 58.1% of respondents (n=62) reported sending an average of 1 text messages per day related to patient care (see Supporting Figure 1B in the online version of this article), with the largest fraction (58.3%) sending 1‐5 texts per day.

HCGM Adoption and Usage Patterns

Active use of HCGM was defined as using the application to send or receive an average of 1 text messages per day. Of HCGM participants, 67% self‐reported 1 week of active use of the application, indicating a strong compliance rate. Among non‐attendings, 70% reported sending 1 or more texts to other team members per day; this percentage increased to 86% among those whose attendings texted them at least once per day (47% of non‐attendings). Respondents who text frequently in their personal lives (>5 texts/day) were more likely to use the application; 90% of these respondents sent 1 or more HCGM texts per day.

Among 12 subjects who did not report sending or receiving 1 HCGM text/day, the top three reasons were: other team members were not using it (67%), no need to use it given the close proximity of other team members (67%), and other (33%). A Wilcoxon rank sum test was used to compare the ages of active versus nonactive users; no significant age difference was found (P=0.200).

To provide an objective measure of application adoption, usage data for each HCGM participant were obtained from the application developers. Because much of the study's first week was spent onboarding and instructing participant, the first week was not included in the analysis. Of 43 individuals enrolled in the study for at least one of the seven remaining weeks, 56% sent a total of 5 texts, 44% sent 10 texts, and 28% sent 20 texts. HCGM users on three teams sent an aggregate mean of 123 texts/week. Data on number of messages received by each user were not available.

Perceived Effectiveness: Paging Versus HCGM

In post‐study surveys, HCGM participants rated HCGM significantly higher (P<0.05) than paging (Table 3) in terms of ability to communicate thoughts clearly (P=0.010) and efficiently (P=0.009). HCGM was also deemed more effective at integrating into workflow during rounds (P=0.018) and patient discharge (P=0.012). Overall satisfaction with HCGM was also significantly higher (P=0.003).

Comparison of Pre‐ and Post‐study Perceived Effectiveness of the Hospital Paging System

In post‐study evaluations, both control and HCGM participants rated the paging system's effectiveness less favorably (P<0.05) compared to baseline in terms of ability to receive messages/stay informed in real time (control P=0.002, HCGM P=0.031) (Table 4). Controls also reported a decrease from baseline in perceived effectiveness of paging in terms of ability to send messages (P=0.019) and integrate into workflow during patient admissions (P=0.020). HCGM participants found paging less effective at communicating thoughts clearly (P=0.004) and efficiently (P=0.018). No significant differences existed between control and HCGM groups' average assessments of paging at the conclusion of the study (see Supporting Table 2, in the online version of this article).

HCGM User Experience

When asked if they would recommend using an HCGM system to facilitate communication on the internal medicine wards, 85% of HCGM participants replied yes, 15% reported not sure, and 0% reported no. Based on free response entries, HCGM's most effective features (Table 5) included ease of use, group texting capacity, and speed (32.4%, 32.4%, and 23.5% of 34 respondents, respectively); its most ineffective aspects (Table 5) included lack of ubiquity, inconsistent usage by those with access to the application, and reliability of message transmission (30.3%, 24.2%, and 15.2% of 33 respondents, respectively).

Limitations

Our study had several limitations. HCGM was available only to individuals in the experimental arm of the study; most members of the internal medicine department and all other departments were not reachable through the application. This lack of ubiquity was a frequently cited frustration. Among individuals to whom HCGM was made available, barriers to adoption included: close proximity to would‐be message recipients, concern that smartphone usage in front of patients might appear unprofessional, and inconsistent or dropped service (weak or no Wi‐Fi signal in some areas). A technical problem with the Android platform midway through the study served as a potential frustration to several participants.

Due to the aforementioned issues, some participants used the HCGM application in a very limited way. We also did not replace hospital pagers (infeasible in this hospital setting); the HCGM application was added as a supplemental system. Future studies might explore the replacement of paging systems with HCGM‐type applications, as well as delve further into quantitative patient care outcomes.

It should be noted that the start of the study unintentionally coincided with the start of new interns and medical students in the hospital. Although it is possible that their relative unfamiliarity with the hospital may have made them more amenable to adopting a new technology, it is also possible that they may have been less likely to do so in the midst of such a major transitional period. Finally, this was a single‐site study, and as such, its findings may not be broadly generalizable. More research on such interventions is warranted, particularly in the context of current insecure communication methods such as paging that may make hospital‐wide adoption of new methods of secure communication, such as HCGM, mandatory.

Intervention

This study utilized Medigram (Medigram, Inc., https://medigram.com), a free HCGM application for smartphones (available on iOS and Android) that allows users to send and receive encrypted, password‐protected text messages via the hospital wireless fidelity (Wi‐Fi) network, using commercial cellular networks as backup.

Study Design

In an eight‐week prospective, cluster‐randomized, controlled trial conducted at Stanford Hospital (June 25, 2012August 17, 2012), three of five inpatient medicine teams were randomized to use Medigram in addition to the existing hospital paging system (HCGM teams); the remaining two teams were assigned to use hospital paging only (control teams). Each team included one attending physician, one resident, two interns, two medical students, and a case manager. According to prescheduled rotations, attendings rotated every two weeks, and residents, interns, and medical students rotated every four weeks. All rotations were either off‐service or off‐site, with the exception of two attendings who rotated between study teams but within their experimental designations. Case managers remained with the same team. Additionally, the satellite pharmacy was provided with an HCGM‐equipped smartphone to communicate with experimental teams.

Participation was voluntary, with a 96% participation rate (n=75). HCGM teams downloaded the free application onto their smartphones. Participants without smartphones were provided with one for the duration of the study. Proper application use was demonstrated by one researcher in a 10‐minute standardized presentation. HCGM teams were encouraged to use the application in lieu of paging, except when patient care could be compromised.

All participants completed linked baseline and post‐study surveys. Gift cards valued at $10 were provided on completion of each survey. Though participants were assigned to either HCGM or control groups based on the randomized assignment of their preset cluster (hospital team) to an HCGM or control group, analysis was performed on the individual level due to the hospital's set rotation schedule, which resulted in dynamic, frequently changing clusters. We also compared average length of stay and time of discharge for patients treated by control versus HCGM teams. Clinical outcome data were obtained from the hospital's database using Midas+ Statit Solutions (Midas+ Statit Solutions Group, Tucson, AZ). Survey and clinical outcome data were analyzed in Stata (StataCorp, College Station, TX) and R (R Foundation for Statistical Computing, Vienna, Austria).

Survey Design and Analysis

Identical, anonymous baseline surveys were administered to control and HCGM teams. These surveys assessed attitudes toward the hospital paging system using a 5‐point Likert scale (1=low, 5=high) to evaluate perceived measures of effectiveness, workflow integration, and overall satisfaction. Wilcoxon rank sum tests were used to compare control and HCGM group responses to these questions. Free response questions asked participants to list the most effective and ineffective aspects of the paging system.

Post‐study surveys included all baseline survey questions, as well as questions about personal texting behavior. Post‐study HCGM surveys also included a parallel set of questions rating the HCGM application on the same measures of perceived effectiveness, workflow integration, and overall satisfaction. Wilcoxon signed rank tests were used to compare HCGM participants' baseline evaluations of paging to their post‐study evaluations of the HCGM application. Baseline and post‐study surveys were linked by the last four digits of respondent cell phone numbers. To compare control and HCGM group perceptions of the hospital paging system at study completion, post‐study survey responses were evaluated using Wilcoxon rank sum tests. The family‐wise error rate was left unadjusted due to concerns around inflated type II errors, given the high degree of correlation between survey questions.

All free response questions were analyzed using thematic analysis and grounded theory. After reviewing responses to each question, a list of overarching themes was constructed. Two researchers then independently reviewed each free‐response entry to assign it to one or more of these themes (some responses included several ideas with distinct themes). Entries with concordant theme assignments (90%) were coded as such; nonconcordant entries required an additional round of review to reach concordance. Finally, objective outcome measures including length of stay and time of discharge were analyzed by two‐sample t test.

Information Security

The HCGM application in this study features 256‐bit encryption technology and requires a six‐digit password to access texts. For added security, a study‐dedicated server (HP ProLiant DL 180 G6; Hewlett‐Packard Co., Palo Alto, CA) with 4‐TB hard drive capacity (4 Seagate Barracuda ST1000DM003 1 TB 7200 RPM internal hard drives; Seagate Technology PLC, Cupertino, CA) was installed in the Stanford School of Medicine Data Center to store encrypted text messages. Data stored on the phones/server were accessible only to study participants, not researchers. These security measures were approved by Stanford Hospital and Stanford School of Medicine's security and privacy review process.

Hospital Paging System

Stanford Hospital and Clinics is a quaternary care academic medical center with 613 beds, 49 operating rooms, and over 25,000 inpatient admissions per year.[8] The institution uses one‐way alphanumeric pagers (primary model: Daviscomm BR802 Flex Pager from USA Mobility, secondary model: Sun Telecom Titan 3 Plus from USA Mobility; USA Mobility Inc., Springfield, VA). USA Mobility operates the largest one‐ and two‐way paging networks in the United States.[9]

Control and HCGM Group Characteristics

Control and HCGM groups were well matched demographically (Table 1). The average ages of control and HCGM group members were 30.10 and 30.95, respectively. Both groups were 59% male and 41% female.

A similar distribution of team member roles was observed in both groups, with two exceptions. First, the proportion of attending respondents in the HCGM group was lower than in the control group. This was due to the fact that several HCGM attendings entered discrepant ID codes on their surveys, thus making it impossible to link baseline and post‐study responses; these data were excluded. Additionally, two HCGM attendings were on service for four, rather than the standard two weeks, meaning two additional data points from unique attendings could not be obtained. Second, the experimental group included four pharmacists, whereas the control group did not. As a sensitivity test, we analyzed the data excluding the pharmacists, and this did not change our results.

Baseline Evaluations of the Hospital Paging System

At baseline, there were no significant differences between control and HCGM participants' perceptions of paging effectiveness (see Supporting Table 1, in the online version of this article). On a 5‐point rating scale (1=low, 5=high), 63 subjects rated their overall satisfaction with the paging system an average of 2.79 (95% confidence interval: 2.55‐3.03).

In free response questions, components of the paging system most frequently cited as effective included: reliability of message transmission, alphanumeric text paging, and ease of use (30.4%, 25.0%, and 14.3% of 56 respondents, respectively) (Table 2). Ineffective aspects included: time wasted waiting for responses to pages, the unidirectional nature of pagers, and needing to find a computer to send a text page (29.3%, 24.1%, and 20.7% of 58 respondents, respectively) (Table 2).

Baseline Utilization of Text Messaging

The majority of participants were familiar with text messaging and regularly used it personally and professionally prior to the start of the study. 90.5% of participants (n = 63) reported sending an average of 1 personal text messages per day, with the largest proportion (39.7%) sending 1‐5 texts per day (see Supporting Figure 1A in the online version of this article). 58.1% of respondents (n=62) reported sending an average of 1 text messages per day related to patient care (see Supporting Figure 1B in the online version of this article), with the largest fraction (58.3%) sending 1‐5 texts per day.

HCGM Adoption and Usage Patterns

Active use of HCGM was defined as using the application to send or receive an average of 1 text messages per day. Of HCGM participants, 67% self‐reported 1 week of active use of the application, indicating a strong compliance rate. Among non‐attendings, 70% reported sending 1 or more texts to other team members per day; this percentage increased to 86% among those whose attendings texted them at least once per day (47% of non‐attendings). Respondents who text frequently in their personal lives (>5 texts/day) were more likely to use the application; 90% of these respondents sent 1 or more HCGM texts per day.

Among 12 subjects who did not report sending or receiving 1 HCGM text/day, the top three reasons were: other team members were not using it (67%), no need to use it given the close proximity of other team members (67%), and other (33%). A Wilcoxon rank sum test was used to compare the ages of active versus nonactive users; no significant age difference was found (P=0.200).

To provide an objective measure of application adoption, usage data for each HCGM participant were obtained from the application developers. Because much of the study's first week was spent onboarding and instructing participant, the first week was not included in the analysis. Of 43 individuals enrolled in the study for at least one of the seven remaining weeks, 56% sent a total of 5 texts, 44% sent 10 texts, and 28% sent 20 texts. HCGM users on three teams sent an aggregate mean of 123 texts/week. Data on number of messages received by each user were not available.

Perceived Effectiveness: Paging Versus HCGM

In post‐study surveys, HCGM participants rated HCGM significantly higher (P<0.05) than paging (Table 3) in terms of ability to communicate thoughts clearly (P=0.010) and efficiently (P=0.009). HCGM was also deemed more effective at integrating into workflow during rounds (P=0.018) and patient discharge (P=0.012). Overall satisfaction with HCGM was also significantly higher (P=0.003).

Comparison of Pre‐ and Post‐study Perceived Effectiveness of the Hospital Paging System

In post‐study evaluations, both control and HCGM participants rated the paging system's effectiveness less favorably (P<0.05) compared to baseline in terms of ability to receive messages/stay informed in real time (control P=0.002, HCGM P=0.031) (Table 4). Controls also reported a decrease from baseline in perceived effectiveness of paging in terms of ability to send messages (P=0.019) and integrate into workflow during patient admissions (P=0.020). HCGM participants found paging less effective at communicating thoughts clearly (P=0.004) and efficiently (P=0.018). No significant differences existed between control and HCGM groups' average assessments of paging at the conclusion of the study (see Supporting Table 2, in the online version of this article).

HCGM User Experience

When asked if they would recommend using an HCGM system to facilitate communication on the internal medicine wards, 85% of HCGM participants replied yes, 15% reported not sure, and 0% reported no. Based on free response entries, HCGM's most effective features (Table 5) included ease of use, group texting capacity, and speed (32.4%, 32.4%, and 23.5% of 34 respondents, respectively); its most ineffective aspects (Table 5) included lack of ubiquity, inconsistent usage by those with access to the application, and reliability of message transmission (30.3%, 24.2%, and 15.2% of 33 respondents, respectively).

Limitations

Our study had several limitations. HCGM was available only to individuals in the experimental arm of the study; most members of the internal medicine department and all other departments were not reachable through the application. This lack of ubiquity was a frequently cited frustration. Among individuals to whom HCGM was made available, barriers to adoption included: close proximity to would‐be message recipients, concern that smartphone usage in front of patients might appear unprofessional, and inconsistent or dropped service (weak or no Wi‐Fi signal in some areas). A technical problem with the Android platform midway through the study served as a potential frustration to several participants.

Due to the aforementioned issues, some participants used the HCGM application in a very limited way. We also did not replace hospital pagers (infeasible in this hospital setting); the HCGM application was added as a supplemental system. Future studies might explore the replacement of paging systems with HCGM‐type applications, as well as delve further into quantitative patient care outcomes.

It should be noted that the start of the study unintentionally coincided with the start of new interns and medical students in the hospital. Although it is possible that their relative unfamiliarity with the hospital may have made them more amenable to adopting a new technology, it is also possible that they may have been less likely to do so in the midst of such a major transitional period. Finally, this was a single‐site study, and as such, its findings may not be broadly generalizable. More research on such interventions is warranted, particularly in the context of current insecure communication methods such as paging that may make hospital‐wide adoption of new methods of secure communication, such as HCGM, mandatory.

Intervention

This study utilized Medigram (Medigram, Inc., https://medigram.com), a free HCGM application for smartphones (available on iOS and Android) that allows users to send and receive encrypted, password‐protected text messages via the hospital wireless fidelity (Wi‐Fi) network, using commercial cellular networks as backup.

Study Design

In an eight‐week prospective, cluster‐randomized, controlled trial conducted at Stanford Hospital (June 25, 2012August 17, 2012), three of five inpatient medicine teams were randomized to use Medigram in addition to the existing hospital paging system (HCGM teams); the remaining two teams were assigned to use hospital paging only (control teams). Each team included one attending physician, one resident, two interns, two medical students, and a case manager. According to prescheduled rotations, attendings rotated every two weeks, and residents, interns, and medical students rotated every four weeks. All rotations were either off‐service or off‐site, with the exception of two attendings who rotated between study teams but within their experimental designations. Case managers remained with the same team. Additionally, the satellite pharmacy was provided with an HCGM‐equipped smartphone to communicate with experimental teams.

Participation was voluntary, with a 96% participation rate (n=75). HCGM teams downloaded the free application onto their smartphones. Participants without smartphones were provided with one for the duration of the study. Proper application use was demonstrated by one researcher in a 10‐minute standardized presentation. HCGM teams were encouraged to use the application in lieu of paging, except when patient care could be compromised.

All participants completed linked baseline and post‐study surveys. Gift cards valued at $10 were provided on completion of each survey. Though participants were assigned to either HCGM or control groups based on the randomized assignment of their preset cluster (hospital team) to an HCGM or control group, analysis was performed on the individual level due to the hospital's set rotation schedule, which resulted in dynamic, frequently changing clusters. We also compared average length of stay and time of discharge for patients treated by control versus HCGM teams. Clinical outcome data were obtained from the hospital's database using Midas+ Statit Solutions (Midas+ Statit Solutions Group, Tucson, AZ). Survey and clinical outcome data were analyzed in Stata (StataCorp, College Station, TX) and R (R Foundation for Statistical Computing, Vienna, Austria).

Survey Design and Analysis

Identical, anonymous baseline surveys were administered to control and HCGM teams. These surveys assessed attitudes toward the hospital paging system using a 5‐point Likert scale (1=low, 5=high) to evaluate perceived measures of effectiveness, workflow integration, and overall satisfaction. Wilcoxon rank sum tests were used to compare control and HCGM group responses to these questions. Free response questions asked participants to list the most effective and ineffective aspects of the paging system.

Post‐study surveys included all baseline survey questions, as well as questions about personal texting behavior. Post‐study HCGM surveys also included a parallel set of questions rating the HCGM application on the same measures of perceived effectiveness, workflow integration, and overall satisfaction. Wilcoxon signed rank tests were used to compare HCGM participants' baseline evaluations of paging to their post‐study evaluations of the HCGM application. Baseline and post‐study surveys were linked by the last four digits of respondent cell phone numbers. To compare control and HCGM group perceptions of the hospital paging system at study completion, post‐study survey responses were evaluated using Wilcoxon rank sum tests. The family‐wise error rate was left unadjusted due to concerns around inflated type II errors, given the high degree of correlation between survey questions.

All free response questions were analyzed using thematic analysis and grounded theory. After reviewing responses to each question, a list of overarching themes was constructed. Two researchers then independently reviewed each free‐response entry to assign it to one or more of these themes (some responses included several ideas with distinct themes). Entries with concordant theme assignments (90%) were coded as such; nonconcordant entries required an additional round of review to reach concordance. Finally, objective outcome measures including length of stay and time of discharge were analyzed by two‐sample t test.

Information Security

The HCGM application in this study features 256‐bit encryption technology and requires a six‐digit password to access texts. For added security, a study‐dedicated server (HP ProLiant DL 180 G6; Hewlett‐Packard Co., Palo Alto, CA) with 4‐TB hard drive capacity (4 Seagate Barracuda ST1000DM003 1 TB 7200 RPM internal hard drives; Seagate Technology PLC, Cupertino, CA) was installed in the Stanford School of Medicine Data Center to store encrypted text messages. Data stored on the phones/server were accessible only to study participants, not researchers. These security measures were approved by Stanford Hospital and Stanford School of Medicine's security and privacy review process.

Hospital Paging System

Stanford Hospital and Clinics is a quaternary care academic medical center with 613 beds, 49 operating rooms, and over 25,000 inpatient admissions per year.[8] The institution uses one‐way alphanumeric pagers (primary model: Daviscomm BR802 Flex Pager from USA Mobility, secondary model: Sun Telecom Titan 3 Plus from USA Mobility; USA Mobility Inc., Springfield, VA). USA Mobility operates the largest one‐ and two‐way paging networks in the United States.[9]

Control and HCGM Group Characteristics

Control and HCGM groups were well matched demographically (Table 1). The average ages of control and HCGM group members were 30.10 and 30.95, respectively. Both groups were 59% male and 41% female.

A similar distribution of team member roles was observed in both groups, with two exceptions. First, the proportion of attending respondents in the HCGM group was lower than in the control group. This was due to the fact that several HCGM attendings entered discrepant ID codes on their surveys, thus making it impossible to link baseline and post‐study responses; these data were excluded. Additionally, two HCGM attendings were on service for four, rather than the standard two weeks, meaning two additional data points from unique attendings could not be obtained. Second, the experimental group included four pharmacists, whereas the control group did not. As a sensitivity test, we analyzed the data excluding the pharmacists, and this did not change our results.

Baseline Evaluations of the Hospital Paging System

At baseline, there were no significant differences between control and HCGM participants' perceptions of paging effectiveness (see Supporting Table 1, in the online version of this article). On a 5‐point rating scale (1=low, 5=high), 63 subjects rated their overall satisfaction with the paging system an average of 2.79 (95% confidence interval: 2.55‐3.03).

In free response questions, components of the paging system most frequently cited as effective included: reliability of message transmission, alphanumeric text paging, and ease of use (30.4%, 25.0%, and 14.3% of 56 respondents, respectively) (Table 2). Ineffective aspects included: time wasted waiting for responses to pages, the unidirectional nature of pagers, and needing to find a computer to send a text page (29.3%, 24.1%, and 20.7% of 58 respondents, respectively) (Table 2).

Baseline Utilization of Text Messaging

The majority of participants were familiar with text messaging and regularly used it personally and professionally prior to the start of the study. 90.5% of participants (n = 63) reported sending an average of 1 personal text messages per day, with the largest proportion (39.7%) sending 1‐5 texts per day (see Supporting Figure 1A in the online version of this article). 58.1% of respondents (n=62) reported sending an average of 1 text messages per day related to patient care (see Supporting Figure 1B in the online version of this article), with the largest fraction (58.3%) sending 1‐5 texts per day.

HCGM Adoption and Usage Patterns

Active use of HCGM was defined as using the application to send or receive an average of 1 text messages per day. Of HCGM participants, 67% self‐reported 1 week of active use of the application, indicating a strong compliance rate. Among non‐attendings, 70% reported sending 1 or more texts to other team members per day; this percentage increased to 86% among those whose attendings texted them at least once per day (47% of non‐attendings). Respondents who text frequently in their personal lives (>5 texts/day) were more likely to use the application; 90% of these respondents sent 1 or more HCGM texts per day.

Among 12 subjects who did not report sending or receiving 1 HCGM text/day, the top three reasons were: other team members were not using it (67%), no need to use it given the close proximity of other team members (67%), and other (33%). A Wilcoxon rank sum test was used to compare the ages of active versus nonactive users; no significant age difference was found (P=0.200).

To provide an objective measure of application adoption, usage data for each HCGM participant were obtained from the application developers. Because much of the study's first week was spent onboarding and instructing participant, the first week was not included in the analysis. Of 43 individuals enrolled in the study for at least one of the seven remaining weeks, 56% sent a total of 5 texts, 44% sent 10 texts, and 28% sent 20 texts. HCGM users on three teams sent an aggregate mean of 123 texts/week. Data on number of messages received by each user were not available.

Perceived Effectiveness: Paging Versus HCGM

In post‐study surveys, HCGM participants rated HCGM significantly higher (P<0.05) than paging (Table 3) in terms of ability to communicate thoughts clearly (P=0.010) and efficiently (P=0.009). HCGM was also deemed more effective at integrating into workflow during rounds (P=0.018) and patient discharge (P=0.012). Overall satisfaction with HCGM was also significantly higher (P=0.003).

Comparison of Pre‐ and Post‐study Perceived Effectiveness of the Hospital Paging System

In post‐study evaluations, both control and HCGM participants rated the paging system's effectiveness less favorably (P<0.05) compared to baseline in terms of ability to receive messages/stay informed in real time (control P=0.002, HCGM P=0.031) (Table 4). Controls also reported a decrease from baseline in perceived effectiveness of paging in terms of ability to send messages (P=0.019) and integrate into workflow during patient admissions (P=0.020). HCGM participants found paging less effective at communicating thoughts clearly (P=0.004) and efficiently (P=0.018). No significant differences existed between control and HCGM groups' average assessments of paging at the conclusion of the study (see Supporting Table 2, in the online version of this article).

HCGM User Experience

When asked if they would recommend using an HCGM system to facilitate communication on the internal medicine wards, 85% of HCGM participants replied yes, 15% reported not sure, and 0% reported no. Based on free response entries, HCGM's most effective features (Table 5) included ease of use, group texting capacity, and speed (32.4%, 32.4%, and 23.5% of 34 respondents, respectively); its most ineffective aspects (Table 5) included lack of ubiquity, inconsistent usage by those with access to the application, and reliability of message transmission (30.3%, 24.2%, and 15.2% of 33 respondents, respectively).

Limitations

Our study had several limitations. HCGM was available only to individuals in the experimental arm of the study; most members of the internal medicine department and all other departments were not reachable through the application. This lack of ubiquity was a frequently cited frustration. Among individuals to whom HCGM was made available, barriers to adoption included: close proximity to would‐be message recipients, concern that smartphone usage in front of patients might appear unprofessional, and inconsistent or dropped service (weak or no Wi‐Fi signal in some areas). A technical problem with the Android platform midway through the study served as a potential frustration to several participants.

Due to the aforementioned issues, some participants used the HCGM application in a very limited way. We also did not replace hospital pagers (infeasible in this hospital setting); the HCGM application was added as a supplemental system. Future studies might explore the replacement of paging systems with HCGM‐type applications, as well as delve further into quantitative patient care outcomes.

It should be noted that the start of the study unintentionally coincided with the start of new interns and medical students in the hospital. Although it is possible that their relative unfamiliarity with the hospital may have made them more amenable to adopting a new technology, it is also possible that they may have been less likely to do so in the midst of such a major transitional period. Finally, this was a single‐site study, and as such, its findings may not be broadly generalizable. More research on such interventions is warranted, particularly in the context of current insecure communication methods such as paging that may make hospital‐wide adoption of new methods of secure communication, such as HCGM, mandatory.