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Impacts of mobile tablet computing on provider productivity, communications, and the process of care
International Journal of Medical Informatics 88 (2016) 62–70
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International Journal of Medical Informatics journal homepage: www.ijmijournal.com
Impacts of mobile tablet computing on provider productivity, communications, and the process of care Benjamin Schooley a,∗ , Steven Walczak a,b , Neset Hikmet a , Nitin Patel c a b c
Integrated Information Technology Department, University of South Carolina, 1301 Gervais St., Columbia, SCS, USA School of Information & Florida Center for Cybersecurity, University of South Florida, Tampa, FL, USA Midlands Internal Medicine, Palmetto Health Richland, Columbia, SC, USA
a r t i c l e
i n f o
Article history: Received 23 September 2015 Received in revised form 15 January 2016 Accepted 22 January 2016 Keywords: Mobile computing Provider productivity Provider-patient Communications Usability Electronic health record Technology acceptanc eHealth Evaluation and assessment Health service research Human-computer interaction Mobile applications Mobile health
a b s t r a c t Objective: Health information technology investments continue to increase while the value derived from their implementation and use is mixed. Mobile device adoption into practice is a recent trend that has increased dramatically and formal studies are needed to investigate consequent benefits and challenges. The objective of this study is to evaluate practitioner perceptions of improvements in productivity, provider-patient communications, care provision, technology usability and other outcomes following the adoption and use of a tablet computer connected to electronic health information resources. Methods: A pilot program was initiated in June 2013 to evaluate the effect of mobile tablet computers at one health provider organization in the southeast United States. Providers were asked to volunteer for the evaluation and were each given a mobile tablet computer. A total of 42 inpatient and outpatient providers were interviewed in 2015 using a survey style questionnaire that utilized yes/no, Likert-style, and open ended questions. Each had previously used an electronic health record (EHR) system a minimum of one year outside of residency, and were regular users of personal mobile devices. Each used a mobile tablet computer in the context of their practice connected to the health system EHR. Results: The survey results indicate that more than half of providers perceive the use of the tablet device as having a positive effect on patient communications, patient education, patient’s perception of the provider, time spent interacting with patients, provider productivity, process of care, satisfaction with EHR when used together with the device, and care provision. Providers also reported feeling comfortable using the device (82.9%), would recommend the device to colleagues (69.2%), did not experience increased information security and privacy concerns (95%), and noted significant reductions in EHR login times (64.1%). Less than 25% of participants reported negative impacts on any of these areas as well as on time spent on order submission, note completion time, overall workload, patient satisfaction with care experience and patient outcomes. Gender, number of years in practice, practice type (general practitioner vs. specialist), and service type (inpatient/outpatient) were found to have a significant effect on perceptions of patient satisfaction, care process, and provider productivity. Conclusions: Providers found positive gains from utilizing mobile devices in overall productivity, improved communications with their patients, the process of care, and technology efficiencies when used in combination with EHR and other health information resources. Demographic and health care work environment play a role in how mobile technologies are integrated into practice by providers. © 2016 Published by Elsevier Ireland Ltd.
1. Introduction
∗ Corresponding author. E-mail addresses: [email protected] (B. Schooley), [email protected] (S. Walczak), [email protected] (N. Hikmet), [email protected] (N. Patel). http://dx.doi.org/10.1016/j.ijmedinf.2016.01.010 1386-5056/© 2016 Published by Elsevier Ireland Ltd.
Despite significant investments in health information technology, the impact on health care remains mixed and regarded by many as disappointing [1]. Some health care providers have experienced modest productivity improvements over time resulting from EHR implementations [2,3], while others have found negative effects, including one study that reported an average of 25–33% decrease in productivity with deployment of a new EHR [4]. Many
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reasons have been given, including systems that are not well integrated with health care processes, are inefficient, overly complex, not easy to use or otherwise causing providers to spend more time documenting and conducting electronic transactions, and less time with patients and collaborating with colleagues [1,5]. Health care providers continue searching for more efficient and effective methods to accomplish their required electronic workload. The implementation and use of mobile device technology is advancing rapidly and market forces are pushing it as one potential solution to productivity challenges [6]. Indeed, these devices offer mobility and convenience for data entry and retrieval and are becoming more widely adopted into medical practice [7,8]. Most providers expect handheld computers to become more useful and are generally interested in gaining value from their use [8–10]. Patient perceptions on the use of desktop computers in medical offices has been studied and shown that patients are generally amenable to the presence of these devices [11,12]. Prior studies have noted potential benefits of mobile handheld computing including the devices being perceived as a portable, relatively inexpensive, integrated platform for point-of-care clinical reference that provides access to Internet-based resources, enables improved patient and data management, rapid response, and error prevention, and can facilitate communications and workflow to enhance clinical practice [7,8,13–15]. Perceived barriers include discomfort with technology and devices, concerns about over-dependency on technology, ineffectiveness of a device to improve workflow or processes, concern about lack of integration with EHRs, usability barriers (e.g., size, weight, screen size, form factor), information privacy and security concerns, negative patient perceptions, lack of organizational support, lack of motivation, and insufficient training [7,9,13,15,16]. Research has also shown that providers desire and require access to information for clinical decision making [17] and that this information access is typically needed within a very short space of time in patient care settings [18]. Mobile devices are one way to answer this information need [7], but research is needed to examine perspectives based on real-world use, how mobile devices are actually used and not just examine what the devices were designed to do [19]. Due to their relative newness, there is a need to conduct studies on mobile tablet adoption and use by providers in clinical settings, including barriers and benefits of use in different clinical contexts. Gagnon et al. [20] systematic review on the barriers of m-health by health providers identified an initial 4223 articles of which 65 were on the topic of m-health adoption, 33 of which were focused on healthcare professionals, and just 2 of which focused on tablet-like computing devices. A broader literature search including live pilot study evaluations of tablet use reveals additional articles. Horng et al. [21] conducted a live pilot study with 13 physicians using both tablets with computers and computers without tablets in an emergency room (ER) setting. Results showed that physicians spent less time interacting with the ED information system when using tablets combined with computers versus computers alone resulting in 38 min per shift average time savings. The authors projected that the time savings could allow for more patient time bedside [21]. In a study of 27 nurses and 8 doctors, researchers observed clinician choice between stationary computers, computers on wheels (COWs), and tablet computers for a wide range of clinical tasks in an Australian teaching hospital. Doctors on ward rounds conducted 35.9% of clinical tasks on tablet computers with the majority of tasks being completed using COWs. Doctors not on ward rounds conducted over 93% of tasks on stationary computers. The study concludes that when selecting computing devices for clinicians, consideration should be given to who will be using the devices, the nature of the work, and the physical layout of the clinical environment [22]. One live field study conducted in 1999 with eleven physicians, nine nurses and four information technol-
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ogy professionals found that a pen (stylus) based mobile system did not provide significant benefits over computer workstations in clinical settings. The most significant drawback was that most of the applications being used at that time required adaptation to be considered effective for pen input. Access to patient data was found to be the most useful feature, while users also wanted access to email and documentation tasks [23]. As mobile technology continues to adapt and mature, a range of software, hardware, and input and output features may prove more useful in clinical settings than these prior findings revealed and thus require ongoing assessment. Several studies have been conducted with residents in inpatient (hospital) settings. In one study of resident neurologists (n = 9), the impact of tablet computers running an electronic medical record on ward round performance was examined. Results indicated that tablet use led to time savings during preparing and post-processing of ward rounds and checking of medical data, and an increase in physicians’ bedside time [10]. In another study with internal medicine residents (n = 115), implementation of tablet computers was associated with improvements in both perceived and actual clinical efficiency measured by timeliness of order placing [24]. In other studies, pediatric residents (n = 94) indicated that obtaining, management, and display of information were primary uses of the devices for clinical training [25], and internal medicine residents (n = 115) reported expectations of the impacts of the tablet on patient care and overall efficiency was higher pre deployment than four months after deployment [26]. The above studies were conducted in inpatient (hospital) as opposed to outpatient (out of hospital) settings. In one study conducted with five physicians, participants used iPads in a rural outpatient physician practice. Results indicated that perceived usefulness of the iPad was mixed but generally positive with some physicians utilizing the device more than others. The iPads were primarily used by the physicians to access medical information from online resources (e.g., Epocrates and UpToDate) for reference and diagnostic purposes, although they were also used for some interaction with patients. All participants felt that resources available through the iPad were limited and that better applications would improve the usefulness of the iPad [27]. In a different study, 5 first year residents working at an outpatient clinic used an Android tablet computer to aid in patient education and discharge tasks. Results were compared with 5 residents who did not use tablets. The device was perceived as helpful for improving patient understanding and communication between physicians and patients [28]. Taken together, these prior studies indicate that few live field examinations have taken place on provider benefits and barriers of using mobile tablet computers to access critical organizational information resources (e.g., EHR), particularly for the outpatient setting and comparisons between inpatient and outpatient settings. The objective of this research is to examine provider perceptions of workflow and documentation efficiencies, interaction with and education of patients, and overall productivity perceptions of providers utilizing mobile tablet computers. These perceptions represent real world utilization.
2. Methods The participants in this study were 42 care providers working at Palmetto Health, a single health care organization with multiple inpatient and outpatient facilities located in the greater Columbia, South Carolina U.S.A. region. Each provider volunteered to participate in a live pilot test to use a Microsoft SurfaceTM tablet computer within his/her daily practice of medicine. Participant demographics are shown in Table 1. The tablet devices were first introduced into practice in June 2013 and extended for 18 months prior to
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Table 1 Participant demographics. Frequency
Percent
Gender Female Male
19 23
45.20% 54.80%
Practice type General practitioner Specialist
30 12
71.40% 28.60%
Service type Inpatient Outpatient Both in/out patient
5 22 14
11.90% 52.40% 33.30%
Years in practice 10 years or less 11 to 15 years 16 or more years
13 12 17
31.00% 28.60% 40.50%
devices were version 3 of the device with the following differences: 12 touchscreen, Intel x64Haswell Core i3 processor, 128 GB of storage, 6 GB memory. All devices weighed less than 2 pounds. Email and office productivity software came pre-loaded, while security suite and software to connect to the virtualized EHR, CPOE, and PACS systems were installed by the Palmetto information technology department.
2.2. Survey instrument
conducting a post pilot test evaluation in early 2015. All participants had a mobile device to use for at least six months prior to conducting the evaluation. No providers were consulted prior to roll out and training was not provided. Participants were recruited by one physician at the health care institution whom invited his outpatient colleagues via email and in-person communications. Inclusion criteria included providers with strong familiarity with existing EHR systems and interest in mobile computing in medical practice. Participation was limited to 42 volunteers due to limited available technology resources, including the number of available tablet computers and the virtualization computing infrastructure required to serve existing electronic information resources to the devices. Existing electronic resources made available to participants via application virtualization technology included electronic health record (EHR) systems, computerized physician order entry (CPOE), picture archiving and communication systems (PACS), email, and Internet access. All 42 pilot test participants also participated in a post pilot evaluation that began in January and concluded in April 2015. No financial support was provided to carry out the evaluation either by Palmetto Health or any other organization. 2.1. Study setting Palmetto Health operates six hospitals (1138 beds) and 38 provider practices with just over 1000 physicians and dentists providing care for nearly a half million patients per year across more than 15 different medical specialties. The health system is present in 15 counties in South Carolina. The providers in the study represented 2 hospitals and 18 different practices in two South Carolina counties. Palmetto Health’s current EHR system was implemented in January 2012 for the outpatient setting, and 2007 for the inpatient setting. The organization uses the 2014 software version from a major EHR vendor that scored 13 out of 15 on the user-centered design best practices framework developed by the American Medical Association and MedStar Health’s National Center for Human Factors in Healthcare. Palmetto Health has been using PACS since 2000, CPOE since 2010 for inpatient and 2012 for ambulatory, each provided by large software vendors. All of these systems were made available to the appropriate providers that participated in this study. The mobile devices used for the pilot study were Microsoft SurfaceTM tablet computers. The first 28 devices acquired were the first version device that included 10.6 high definition touchscreens, Windows 8 Professional operating systems, 64 gigabytes (GB) of storage, 4 GB of memory, quad core Nvidia Tegra 3 processors, active pens (stylus), ambient light sensors, 3-axis accelerometers, full size USB 3.0 port, Wi-Fi only connectivity, detachable keyboard, and front and rear cameras. The latter 13
A 31 question author generated survey protocol was designed to evaluate improvements and challenges to utilization, provider productivity, process of care, provider-patient interactions, and satisfaction resulting from tablet computer use. The instrument was developed based on literature review on utilization, usability, and acceptance of mobile computing devices in health care settings. An expert panel of researchers and health practitioners, none of whom was a participant in the pilot evaluation, was used to examine questions and pilot test the survey prior to conducting the evaluation. The survey and interview methodology was approved by both the University of South Carolina and also Palmetto Health’s Institutional Review Board. The interviews were conducted in person, took approximately 30–40 min to complete, and were scheduled at the convenience of each participant (typically lunch time or after hours). The survey instrument was used by the interviewer as a guide for discussion and was not given to the participant to complete. Each Likert and yes/no question was followed by an open-ended question for the participant to provide further detail or explanations regarding the answers given. Respondents were permitted to skip or not respond to any question that they did not feel comfortable answering. Responses were recorded manually on the instrument and, if approved of by the participant, also via audio tape. The results were then transcribed into a spreadsheet for import and analysis in the IBM SPSS version 22 statistical package. After analysis was completed an additional 5 question survey was developed and administered online to further clarify the possible benefits. The response rate to the second survey is 65.85 percent of the original interviews that represented 100 percent of the population of provider tablet computer users. Significance was considered at the p < 0.01 and 0.05 level. Descriptive statistics, cross-tab analysis, one-way between subjects ANOVA, and qualitative analysis of open-ended responses were used to analyze data.
3. Results Study participant demographics are shown in Table 1. All participants reported at least one year of prior experience using an EHR system before pilot rollout (average 5.6 years outside of residency), and all but one reported using either a smartphone, tablet computer, or both on a regular basis for personal use (average 6.7 years’ experience). There are distinct differences between Practice Type and Service Type demographics for this study. General practitioners (n = 30) included those trained to provide primary health care covering a variety of medical conditions to patients of either sex or any age. Specialists (n = 12) included providers who have completed advanced education and clinical training in a specific area of medicine including cardiology, pulmonary disease, obstetrics and gynecology, oncology, surgery, gastroenterology, pediatric specialties, and others. In terms of Service Type, those that identified as inpatient providers (5) were those that practice medicine on patients admitted to a hospital, while those that identified as outpatient providers (22) practice medicine on patients without being admitted to a hospital, with the remaining participants practicing in both settings (14). Of the 42 participants, 35 identified as Medical
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Table 2 Provider perspectives on mobile device use. Likert responses—impact of device on:
Negative
No change
Positive
Patient communications Patient education Patient’s perception of provider Time spent interacting with patients Provider productivity Time spent on order submission Note completion Process of care Workload Improve workday Care provision Patient outcomes Patient satisfaction with care experience Device comfort rating User (provider) satisfaction with EHR together with device Security concerns Would you recommend the device to colleagues?
17.9% 0.0% 11.1% 10.5% 23.1% 23.7% 27.0% 21.1% 21.9% 17.9% 25.7% 2.4% 13.2% 7.3% 29.3% 5.0% 12.8%
28.2% 48.6% 33.3% 34.2% 23.1% 44.7% 27.0% 26.3% 43.8% 25.0% 14.3% 65.9% 42.1% 9.8% 14.6% 87.5% 17.9%
53.8% 51.4% 55.6% 55.3% 53.8% 31.6% 45.9% 52.6% 34.4% 57.1% 60.0% 31.7% 44.7% 82.9% 56.1% 7.5% 69.2%
Yes 25.6% 64.1% 53.6% 57.1% 57.1%
No 74.4% 35.9% 46.4% 42.9% 42.9%
Yes/No items Nurse interaction improved EHR log in decrease Does the use of the device reduce the amount of time spent after work completing documentation? Does use of the device improve your overall efficiency at work? Would you feel more comfortable seeing an increased number of patients using the mobile device vs. a traditional computer desktop?
Doctors, 3 as Doctor of Osteopathy, 3 as a Nurse Practitioners, and 1Certified Medical-Surgical Registered Nurse (CMSRN). The abbreviated interview questions and results are shown in Table 2. As may be seen from Table 2, provider perceptions were mixed. Results from descriptive statistics showed providers responded positively to various impacts that they believed the device had on provider-patient relations, productivity, process of care, and technology efficiency. More than half of participants reported use of the device had positive impacts on areas related to provider-patient relations including patient communications (53.8%), patient education (51.4%), patient’s perception of provider (55.6%), and time spent interacting with patients (55.3%), with the vast majority reporting no negative impact across each area (82%, 100%, 88.9%, 89.5% respectively). In terms of provider productivity, the majority of participants reported improvements in overall efficiency at work (57.1%), reduction of time spent after work completing documentation (53.6%), and that overall they were more productive (53.8%) by using the device. Participants reported that patient order submission time (76.3%) and note completion times (73.9%) did not increase as a result of using the device. The majority of results showed either improvement (31.6%) or no change (44.7%) in the time spent on order submission, and either improvement (45.9%) or no change (27%) in note completion times. Finally, most providers reported that using the device did not improve their interactions with nurses. In terms of impacts on provider care provision, 52.6% reported the process of care improved (52.6%), 43.8% reported no change to daily workload, 57.1% believed using the device helped improve their workday, and 60% perceived the device to positively impact care provision while 25.7% reported a negative impact. Further, participants believed using the device had either a positive effect (31.6%) or had no change (65.9%) on patient outcomes. Providers believed that patient satisfaction with their care experience was either positive (44.7%) or that there was no overall change in satisfaction (42.1%) since using the device. Finally, when asked if they would feel more comfortable seeing an increased number of patients using the mobile device versus a traditional desktop computer, 57.1% responded yes. Several technology usability questions were also asked. The majority of respondents answered positively in terms of their comfort level using the device (82.9%), and satisfaction with the EHR
increased when used together with the device (56.1%). Most did not experience increased security concerns as a result of using the device (95%), and 64.1% reported that EHR login times decreased as a result. When asked if they would recommend the device to their colleagues, 68.2% responded positively, with 17.9% feeling unsure (noted as “no change” in Table 2).
3.1. Cross-tab and ANOVA results Participant responses were further analyzed by conducting cross-tab and one-way analysis of variance (ANOVA) to compare statistical differences across demographic categories including gender; number of years in practice; service type (inpatient vs. outpatient vs. both); and practice type (general practitioner vs. specialist). Results from ANOVA are shown in Table 3, and crosstab results are shown in Appendix A. Results indicated that there was a statistically significant difference between inpatient and outpatient providers for two questionnaire items. These included provider beliefs about the impact of the mobile device use on the process of care (F(2, 34) = 7.900, p = 0.002), and improved nurse interaction (F(2, 35) = 3.502, p = 0.041), with inpatient providers generally showing more positive responses in the first category and both inpatient only and inpatient/outpatient providers reporting more positive perspectives than outpatient only providers. Statistically significant differences between general practitioner and specialty providers included perceptions about patients being satisfied since using the mobile device (F(1, 36) = 5.890, p = 0.020), with general practitioners responding more positively. Further, beliefs about the patient’s perception of the providers were significantly different (F(1, 34) = 4.515, p = 0.041), with general practitioners reporting more positively in this regard (64.0% vs. 36.4%). Number of years in practice also showed statistical differences for survey items related to the use of the device impacting process of care improvement (F(2, 35) = 7.028, p = 0.003), satisfaction with device when used together with the EHR (F(2, 38) = 3.724, p = 0.033), perceptions about patients being satisfied since using the mobile device (F(2, 35) = 3.261, p = 0.050), and the provision of care (F(2, 32 = 3.823 p = 0.032)). For each of these items, providers who had reported practicing longer responded more positively.
B. Schooley et al. / International Journal of Medical Informatics 88 (2016) 62–70
1.813 4.655 5.161 1.918 6.295 4.754 2.001 0.006 0.003** 0.033* 0.050* 0.032* 0.993 0.246 0.380 0.570 7.028 3.724 3.261 3.823 0.007* 1.458 0.996 0.571
.187 .037* .029* .175 .019* .036* .166 .941
F Sig. F
0.002** 0.754 0.599 0.101 0.613 0.293 0.061 0.041* Sig at p < 0.05. Sig at p < 0.01. *
3.863 0.584 5.890 1.921 3.250 3.657 4.515 0.708 Process of care** Satisfaction with EHR together with device* Patient satisfaction with care experience* Care provision* Comfortable seeing more patients using the device vs. desktop computer* Time spent on order submission* Patient’s perception of provider* Nurse interaction improved*
**
Sig.
3.2. Mixed-method results
7.900 0.284 0.521 2.470 0.500 1.273 3.063 3.502
F F Survey item
Sig.
Service type Practice type Table 3 ANOVA results for practice type, service type, years in practice, and gender.
Finally statistically significant differences between gender groups were found including satisfaction with the mobile device when used together with the EHR (F(1, 39) = 4.655, p = 0.037), perceptions about patients being more satisfied since using the mobile device (F(1, 36) = 5.161, p = 0.029), comfort level seeing more patients using the device over a desktop computer (F(1, 26) = 6.295, p = 0.019), and time spent on order submission since using the device (F(1, 36) = 4.754, p = 0.036). Crosstab analysis showed males reported more positive results regarding time spent on order submission. However, females reported more positive beliefs for each of the other three question items including satisfaction using the device with the EHR, beliefs in device use impacting patient satisfaction, and comfort level seeing more patients using the device over a desktop computer. No other statistically significant differences were found between groups.
0.057 0.449 0.020* 0.175 0.083 0.064 0.041* 0.406
Years in practice
Gender
Sig.
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Open-ended questions about the use of the device were also asked. First, comments revealed that several respondents who had received an earlier version of the device with a smaller screen would not recommend it to their colleagues. However, those same respondents noted that they would recommend the newer versions of the tablet computer to their colleagues. Comments revealed a number of benefits of using the device including showing patients their pathology results, diagrams for patient education, and looking up information on the web directly on the computer. The two most reported benefits from using tablet computers were (1) its portability, and (2) its personalization to the provider user. Fifteen percent of the respondents indicated they used the tablet computer primarily at home. Furthermore, 32% indicated they completed notes or used the tablet to prepare for patient visits at home, on the road, or while traveling. Five providers specifically stated that the portability of the device, allowing for note writing and documentation at their convenience, resulted in significant efficiencies that allowed for leaving work and arriving home at the end of the day earlier than without the device. These process changes improved their quality of life. In a follow up online survey sent to the respondents, they were asked to rank order from 1 to 6 the order of their satisfaction with system features: touch screen, stylus, portability, ability to run the full EHR application, camera and video, and detachable keyboard. Portability was ranked as the number one choice by 64% of the respondents with an overall ranking of 1.68. The touchscreen and ability to run the full EHR application were ranked second and third highest with an overall score of 2.76 and 2.8 respectively. The remainder were ranked in order: stylus (3.64), detachable keyboard (4.64), and finally camera/video (5.48). Some additional analysis was conducted on provider responses to the open-ended question “What improvements could be made to the device that would increase your satisfaction?” Three main answers occurred to this question for the 33 providers responding: over 45% indicated a larger screen was desirable. It should be noted that only one provider desiring a larger screen used a Surface 3 (12 in. display), with all the others using earlier smaller screen versions (10 in.). The majority of respondents (74%) noted EHR (Electronic Health Record) integration issues on the tablet, including the version of the EHR that was in-use was not mobile friendly. Further, 21% indicated that voice recognition or improvements in the voice recognition program were desired; 18% indicated longer battery life would improve usability; and 15% indicated issues with the current keyboard configuration including size, angle, and physical flexibility. All other recommendations had less than 15% response and included issues such as network connectivity issues,
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preference for another device or operating system, or lack of IT (information technology) training and support for the tablets.
4. Discussion The results indicate that slightly more than half of respondents reported positively about the impact of using the mobile tablet device on a range of measures including provider-patient communications, patient education, patient satisfaction, provider productivity, process of care, and technological improvements. Similar findings have been reported in other studies, including those mentioned in the introduction of this text. The mixed findings in this and across prior studies may be in part due to the many barriers and facilitators of adoption of technology in healthcare settings as found by [20]. They identified 51 different traits that were mentioned as being barriers or facilitators of adoption. Of these, 14 were pure barriers, 12 were pure facilitators, and the remaining 25 were listed as being both barriers and facilitators [20]. Similarly, [22] conducted an observational study of physician tasks and concluded that device implementation for providers should consider who will be using the devices, the nature of the work, and the physical layout of the clinical environment [22]. This study confirms these findings and extends the work of these researchers to show that gender, number of years in practice, service type and practice type play a role in how mobile tablet computing devices are used and perceived by providers. A significant finding in this study is that the device was, for the vast majority of providers, not perceived to have a negative impact across question items including time spent on order submission, note completion time, and overall workload. The literature is replete with studies showing provider resistance to implementing new information technologies in patient care, low levels of trust and belief that these technologies will have a positive impact on care processes, and a wide variety of factors that influence negative provider beliefs toward using computing based solutions in patient care [1,15,16,20,26]. The reasoning behind such beliefs may be very well justified. However, the results of this study did not seem to indicate such. This may be because many of the prior studies on adoption and use of health IT discuss large and complex software systems such as EHRs, CPOE, clinical decision support, and others, whereas, according to provider comments, the mobile device represents a single and integrated medium whereby the existing complex systems can be more conveniently accessed and utilized. This may be one important reason why providers did not link efficiency, workflow, and productivity benefits achieved directly to affecting patient outcomes—as the device itself does not impact clinical decision making, or other areas for which the provider has direct influence. It may be important for future studies on complex health IT systems to delineate between the software being used (e.g., EHR) and the mode of access (e.g., PC, tablet, COW, smartphone). While some field studies address usability in terms of more objective task performance [15,21,24], this study addresses usability in terms of provider perspectives, showing positive results for comfort using the device, satisfaction, and recommendation to colleagues. Acceptance and future use of mobile technologies may be promising when looking at these results. A specific type of mobile tablet computer was used for this study, but the device itself is very similar in function, size, weight, and features as many other mobile tablet computers that can be found in the marketplace. Thus, the specific device itself should not be considered the primary factor associated with these findings. Rather, device mobility and features (pen/stylus, form factor, and other common features) connected to essential health information resources should be the primary factors for consideration. For example, the finding of portability
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and larger screen size as highly useful features is consistent with previous research [28,29]. Other integrated features, including the pen/stylus, seem to be perceived as more useful than reported in prior research [23], likely due to technology advances. Various add-on devices to mobile tablets, such as voice recognition systems, should be investigated in the future as a range of efficiencies have been found through the use of speech recognition software [30]. Prior studies, including Suominen et al. [31] pilot of 8 participants found that provider preference was for tablet computers, as opposed to small stand-alone voice recording devices that could be used for multiple different tasks beyond voice recognition. It should be noted that the DragonTM voice recognition system was not made available to users during the first year of the field study and starting in summer 2014 was installed for providers only upon request. This should be considered in light of the 21% of respondents whom desired better integration between voice recognition and tablet devices. With low participation and use of this particular technology integration for this study, these results should be further investigated in the future. Another important aspect of this study is that providers were not given any training or instruction on how to use the device in the practice of medicine. This may be considered a limitation of this study as the duration and quality of training has long been known to positively impact perceptions and utilization of new information technologies. The study by Abbott [19] in which nurses rated the capabilities of a different mobile computing device very highly differs from the current study in an important way. Abbott’s subjects received extensive training on their mobile device. This training is critical to enable providers to fully understand the capabilities and applications of the devices and to gain an even higher level of comfort in using a newer technology in a clinical setting. However, training can also impede self-learning, which can impede innovative and creative uses of new information technologies. The decision was made in this study to provide a device to providers and allow each of them to determine appropriate use. Future studies may determine best practice use cases and integrate those into provider technology training, conduct a live pilot test, and then assess perspectives. Some providers also noted a lack of IT (information technology) support for this project. This can also serve to frustrate providers attempting to utilize newer mobile technologies to their fullest capabilities but who have questions regarding technology functionality. Thus, while portable tablet computing devices are generally perceived to be beneficial, IT must plan appropriately to train and respond to inquiries in order to maximize this potential. Another contribution of this study was the real-world use of the mobile technology together with the EHR. As previously mentioned, Palmetto Health has been using the same EHR vendor for the past 8 years. Several of the interviewed providers indicated dissatisfaction with the EHR’s functionality, which is a distinct issue from satisfaction and benefit of using the mobile platform. This was evident in participant responses to the question “Satisfaction with the EHR together with device.” This question received the largest percent of negative responses from participants than any other Likert scale question. Further, the responses to this question significantly differed based on number of years in practice and gender. In practice, it may not be easy for all users to clearly delineate between the EHR software application and the device that accesses the technology as both are used together to accomplish essential tasks. Thus, improvements to EHRs may influence future studies assessing mobile device impacts and vice versa. One relevant discussion point from this study may be the importance of EHR companies creating more usable mobile versions of their software systems or responsive interfaces. Such improvements may significantly influence provider perceptions about the positive impacts of EHR systems, the mobile devices used to access them, and the integrated EHR/mobile device experience.
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5. Limitations A known limitation of survey research is that it is based on the participants’ opinions. This is a cross-sectional study and therefore represents a snapshot in time, and is limited to inpatient and outpatient, general practitioner and specialist providers working for the same health care system in the Southeast United States, with mobile devices having been connected to a large vendor EHR system. The results of this study may not be generalizable to all providers and health care systems as the number and combination of medical specialties, work environments, and EHR vendor systems varies significantly across the United States. While the number of users that participated in the pilot is significant for a live field test in this context, the population nevertheless is relatively small (n = 42) in terms of statistical significance and impacts on generalizability. Nevertheless, responses may be representative of some health care systems in a variety of settings. A larger and broader sample may reveal differences among different regions. As with other survey studies, this study used subjective, selfreported measures. It is possible that response bias contributed to our findings. Another important limitation common with technology studies is that new mobile technologies were released to the marketplace during the period of this project. Thus, those who received and tested earlier version devices may have responded differently to questions had they used a newer version. 6. Conclusion The reported results indicate that the users found positive gains from utilizing the tablet device in overall productivity, improved communications with their patients, the process of care, and efficiencies. Additionally, some positive outcomes were perceived, specifically with the patients’ positive perception of the provider and in overall improved patient satisfaction. Further, the vast majority of responses showed that providers believed that the device produced no negative impact in every category, including workload, order submission time, patient outcomes, patient education, to name a few. However it should also be noted that while no change was the predominant answer for these questions, in most cases a percentage of the users indicated that benefits in these categories did occur, and was generally positive for 25% or higher of the respondents. Few participants reported negative impacts on survey question items including time spent on order submission, note completion time, overall workload, patient satisfaction with care experience and patient outcomes. Gender, number of years in practice, practice type (general practitioner vs. specialist), and service type (inpatient/outpatient) were found to have a significant effect
Summary Points What was already known: • Most healthcare providers expect increased access to information resources, believe handheld computers connected to those resources (e.g., EHR, CPOE, PACS) will become more useful in this regard, and are generally interested in gaining value from their use. • Prior studies have noted potential benefits and perceived barriers of mobile handheld computing in areas such as workflow, technology usability, patient satisfaction, EHR integration, and provider productivity. • The few live field studies that have been conducted show some productivity improvements, such as less time at a computer and increased provider availability. What this study has added: • Live field study and evaluation of actual use for extended period of time in both outpatient and inpatient settings. • Reported improvements in patient communications, patient education, patient’s perception of the provider, time spent interacting with patients, provider productivity, process of care, satisfaction with EHR when used together with the device, and care provision. • Providers reported feeling comfortable using the device (82.9%), would recommend the device to colleagues (69.2%), did not experience increased information security and privacy concerns (95%), and noted significant reductions in EHR login times (64.1%).
on perceptions of patient satisfaction, care process, and provider productivity. Mobile tablet computers may provide significant benefits of personalization, portability, flexibility, and productivity to providers depending on the care environment. Individuals responsible for rolling out information technologies to health care practitioners should consider the factors associated with adoption reported herein, including the need for a well-functioning interplay between the device, the provider, and the EHR. Acknowledgments We are grateful to the administrators and providers at Palmetto Health for their time in coordinating and participating in this research. In particular, Jose Delcastillo Jr., Project Manager, provided a significant amount of work scheduling and coordinating interviews, and collating responses.
Appendix A. : Crosstab Analysis Practice type
How satisfied do you think your patients are since MS use?
Total
Patient’s perception of provider
Negative
No change
Positive
General practitioner Sub-specialty
1 (3.7%) 4 (36.4%)
12 (44.4%) 4 (36.4%)
14 (51.9%) 3 (27.3%)
27 (100%) 11 (100%)
Total
5 (13.2%)
16 (42.1%)
17 (44.7%)
38 (100%)
Service type
Process of care improved?
Total Years in practice
No change
Positive
1 (4%) 3 (27.3%)
8 (32%) 4 (36.4%)
16 (64%) 4 (36.4%)
25 (100%) 11 (100%)
12 (33.3%)
20 (55.6%)
36 (100%)
4 (11.1%) Total
Negative
No change
Positive
0 (0%) 2 (10.53%) 6 (46.15%)
1 (20%) 4 (21.05%) 5 (38.46%)
4 (80%) 13 (68.42%) 2 (15.38%)
8 (21.62%)
10 (27.03%)
19 (51.35%)
Process of care improved?
Nurse interaction improved
Total
Yes
No
5 (100%) 19 (100%) 13 (100%)
0 (0%) 8 (40%) 1 (7.69%)
5 (100%) 12 (60%) 12 (92.31%)
5 (100%) 20 (100%) 13 (100%)
37 (100%)
9 (23.68%)
29 (76.32%)
38 (100%)
Total
How satisfied are you using MS with cerner system?
Total
Negative
No change
Positive
Negative
No change
Positive
10 Years or less 11–15 16 or more
1 (8.3%) 6 (50%) 1 (7.1%)
6 (50%) 3 (25%) 1 (7.1%)
5 (41.7%) 3 (25%) 12 (85.7%)
12 (100%) 12 (100%) 14 (100%)
7 (53.8%) 4 (33.3%) 1 (6.3%)
1 (7.7%) 2 (16.7%) 3 (18.8%)
5 (38.5%) 6 (50%) 12 (75%)
13 (100%) 12 (100%) 16 (100%)
Total
8 (21.1%)
10 (26.3%)
20 (52.6%)
38 (100%)
12 (29.3%)
6 (14.6%)
23 (56.1%)
41 (100%)
Years in practice
How satisfied do you think your patients are since MS use?
10 Years or less 11–15 16 or more Gender
Negative
No change
Positive
2 (16.7%) 2 (20%) 1 (6.3%) 5 (13.2%)
8 (66.7%) 4 (40%) 4 (25%) 16 (42.1%)
2 (16.7%) 4 (40%) 11 (68.8%) 17 (44.7%)
Total
Do you think you are providing better care since MS use?
12 (100%) 10 (100%) 16 (100%) 38 (100%)
Time spent on order submit
Negative
No change
Positive
4 (36.4%) 4 (40%) 1 (7.1%) 9 (25.7%)
1 (9.1%) 3 (30%) 1 (7.1%) 5 (14.3%)
6 (54.5%) 3 (30%) 12 (85.7%) 21 (60%)
Total
How satisfied are you using MS with cerner system?
Total
11 (100%) 10 (100%) 14 (100%) 35 (100%) Total
Negative
No change
Positive
Negative
No change
Positive
Male Female
4 (18.2%) 8 (50%)
11 (50%) 6 (37.5%)
7 (31.8%) 2 (12.5%)
22 (100%) 16 (100%)
10 (45.5%) 2 (10.5%)
2 (9.1%) 4 (21.1%)
10 (45.5%) 13 (68.4%)
22 (100%) 19 (100%)
Total
12 (31.6%)
17 (44.7%)
9 (23.7%)
38 (100%)
12 (29.3%)
6 (14.6%)
23 (56.1%)
41 (100%)
Gender
How satisfied do you think your patients are since MS use?
Total
Negative
No change
Positive
Male Female
4 (19%) 1 (5.9%)
11 (52.4%) 5 (29.4%)
6 (28.6%) 11 (64.7%)
Total
5 (13.2%)
16 (42.1%)
17 (44.7%)
Comfortable seeing more patients using the SP vs. DC?
B. Schooley et al. / International Journal of Medical Informatics 88 (2016) 62–70
Inpatient Outpatient Both in/out-patient
Total
Negative
Total
Yes
No
21 (100%) 17 (100%)
8 (42.1%) 8 (88.9%)
11 (57.9%) 1 (11.1%)
19 (100%) 9 (100%)
38 (100%)
16 (57.1%)
12 (42.9%)
28 (100%)
69
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Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.ijmedinf.2016. 01.010. References [1] A.L. Kellermann, S.S. Jones, What it will take to achieve the as-yet-unfulfilled promises of health information technology, Health Affairs 32 (1) (2013) 63–68, http://dx.doi.org/10.1377/hlthaff.2012.0693. [2] A.D. Cheriff, A.G. Kapur, M. Qiu, C.L. Cole, Physician productivity and the ambulatory EHR in a large academic multi-specialty physician group, Int. J. Med. Informatics 79 (7) (2010) 492–500, http://dx.doi.org/10.1016/j.ijmedinf. 2010.04.006. [3] N.S. Fleming, E.R. Becker, S.D. Culler, D. Cheng, R. McCorkle, B. da Graca, D.J. Ballard, The impact of electronic health records on workflow and financial measures in primary care practices, Health Serv. Res. 49 (1pt2) (2014) 405–420, http://dx.doi.org/10.1111/1475-6773.12133. [4] H.K. Bhargava, A.N. Mishra, Electronic medical records and physician productivity: evidence from panel data analysis, Manag. Sci. 60 (10) (2014) 2543–2562, http://dx.doi.org/10.1287/mnsc.2014.1934. [5] M.E. Flanagan, J.J. Saleem, L.G. Millitello, A.L. Russ, B.N. Doebbeling, Paper-and computer-based workarounds to electronic health record use at three benchmark institutions, J. Am. Med. Informatics Assoc. 20 (1) (2013) e59–e66, http://dx.doi.org/10.1136/amiajnl-2012-000982. [6] N. Jaria-Chacon, D. Arias-Aranda, Mobile device platforms and servitization: towards an integrative model, DYNA Manag. 2 (2014) 1, http://dx.doi.org/10. 6036/MN7047. [7] Y.-C. Lu, Y. Xiao, A. Sears, J.A. Jacko, A review and a framework of handheld computer adoption in health care, Int. J. Med. Informatics 74 (5) (2005) 409–422, http://dx.doi.org/10.1016/j.ijmedinf.2005.03.001.2. [8] J. Sclafani, T.F. Tirrell, O.I. Franko, Mobile tablet use among academic providers and trainees, J. Med. Syst. 37 (1) (2013) 1–6, http://dx.doi.org/10. 1007/s10916-012-9903-6. [9] K.F.B. Payne, H. Wharrad, K. Watts, Smartphone and medical related App use among medical students and junior doctors in the United Kingdom (UK): a regional survey, BMC Med. Informatics Decis. Mak. 12 (2012) 121, http://dx. doi.org/10.1186/1472-6947-12-121. [10] R. Fleischmann, J. Duhm, H. Hupperts, S.A. Brandt, Tablet computers with mobile electronic medical records enhance clinical routine and promote bedside time: a controlled prospective crossover study, J. Neurol. 262 (3) (2015) 532–540, http://dx.doi.org/10.1007/s00415-014-7581-7. [11] C.N. Sciamanna, S.P. Novak, B.H. Marcus, Effects of using a computer in a doctor’s office on patient attitudes toward using computerized prompts in routine care, Int. J. Med. Informatic 74 (5) (2005) 357–365, 10.1016/j.ijmedinf.2005.03.003. [12] C. Sibona, S. Walczak, J. Brickey, M. Parthasarathy, Patient perceptions of electronic medical records: provider satisfaction, portability, security, and quality of care, Int. J. Biomed. Eng. Technol. 12 (1) (2011) 62–84, http://dx.doi. org/10.1504/IJHTM. [13] A. Holzinger, P. Kosec, G. Schwantzer, M. Debevc, R. Hofmann-Wellenhof, J. Frühauf, Design and development of a mobile computer application to reengineer workflows in the hospital and the methodology to evaluate its effectiveness, J. Biomed. Informatics 44 (6) (2011) 968–977, http://dx.doi.org/ 10.1016/j.jbi.2011.07.003. [14] M. Prgomet, A. Georgiou, J.I. Westbrook, The impact of mobile handheld technology on hospital providers’ work practices and patient care: a systematic review, J. Am. Med. Informatics Assoc. 16 (6) (2009) 792–801, http://dx.doi.org/10.1197/jamia.M3215.
[15] O. Alsos, A. Das, D. Svanaes, Mobile health IT: the effect of user interface and form factor on doctor-patient communication, Int. J. Med. Informatics 81 (1) (2012) 12–28, http://dx.doi.org/10.1016/j.ijmedinf.2011.09.004. [16] A.S. McAlearney, S.B. Schweikhart, M.A. Medow, Doctors’ experience with handheld computers in clinical practice: qualitative study, Br. Med. J. 328 (7449) (2004) 1162, http://dx.doi.org/10.1136/bmj.328.7449.1162. [17] D.L. Sackett, S.E. Straus, Finding and applying evidence during clinical rounds: the evidence cart, J. Am. Med. Assoc. 280 (15) (1998) 1336–1338, http://dx. doi.org/10.1001/jama.280.15.1336. [18] M.A. Ellsworth, J.M. Homan, J.J. Cimino, S.G. Peters, B.W. Pickering, V. Herasevich, Point-of-care knowledge-based resource needs of clinicians a survey from a large academic medical center, Appl. Clin. Informatics 6 (2) (2015) 305–317, http://dx.doi.org/10.4338/ACI-2014-11-RA-0104. [19] P.A. Abbott, The effectiveness and clinical usability of a handheld information appliance, Nurs. Res. Pract. 2012 (2012) 307258, http://dx.doi.org/10.1155/ 2012/307258. [20] M.P. Gagnon, P. Ngangue, J. Payne-Gagnon, M. Desmartis, m-Health adoption by healthcare professionals: a systematic review, J. Am. Med. Informatics Assoc. (2015), http://dx.doi.org/10.1093/jamia/ocv052. [21] S. Horng, F.R. Goss, R.S. Chen, L.A. Nathanson, Prospective pilot study of a tablet computer in an emergency department, Int. J. Med. Informatics 81 (5) (2012) 314–319, http://dx.doi.org/10.1016/j.ijmedinf.2011.12.007. [22] P. Andersen, A.M. Lindgaard, M. Prgomet, N. Creswick, J.I. Westbrook, Mobile and fixed computer use by doctors and nurses on hospital wards: multi-method study on the relationships between clinician role, clinical task, and device choice, J. Med. Intern. Res. 11 (2009) 3, http://dx.doi.org/10.2196/ jmir.1221. [23] A. Buchauer, U. Pohl, N. Kurzel, R. Haux, Mobilizing a health professional’s workstation-results of an evaluation study, Int. J. Med. Informatics 54 (2) (1999) 105–114, http://dx.doi.org/10.1016/S1386-5056(98) 00170-1. [24] B.K. Patel, C.G. Chapman, N. Luo, J.N. Woodruff, V.M. Arora, Impact of mobile tablet computers on internal medicine resident efficiency, Arch. Intern. Med. 172 (5) (2012) 436–438, http://dx.doi.org/10.1001/archinternmed.2012.45. [25] Howard, D.J., Coovert, S.A., Coovert, M.D., Nelson, RM. Telemedicine and e-Health. 2015; 21(7): 588-592. http://dx.Doi.org/10.1089/tmj.2014.0130. [26] N. Luo, C.G. Chapman, B.K. Patel, J.N. Woodruff, V.M. Arora, Expectations of iPad use in an internal medicine residency program: is it worth the hype? J. Med. Intern. Res. 15 (2013) 5, http://dx.doi.org/10.2196/jmir.2524. [27] C. Anderson, T. Henner, J. Burkey, Tablet computers in support of rural and frontier clinical practice, Int. J. Med. Informatics 82 (November (11)) (2013) 1046–1058, http://dx.doi.org/10.1016/j.ijmedinf.2013.08.006. [28] B. Schooley, T. San Nicolas-Rocca, R. Burkhard, Patient-provider communications in outpatient clinic settings: a clinic-based evaluation of mobile device and multimedia mediated communications for patient education, JMIR MHealth UHealth 3 (January (1)) (2015) http://mhealth.jmir. org/2015/1/e2/. [29] H. Friederichs, B. Marschall, A. Weissenstein, Practicing evidence based medicine at the bedside: a randomized controlled pilot study in undergraduate medical students assessing the practicality of tablets, smartphones, and computers in clinical life, BMC Med. Informatics Decis. Mak. 14 (2014) 113, http://dx.doi.org/10.1186/s12911-014-0113-7. [30] T. Hodgson, E. Colera, Risks and benefits of speech recognition for clinical documentation: a systematic review, J. Am. Med. Informatics Assoc. (2015), http://dx.doi.org/10.1093/jamia/ocv152. [31] H. Suominen, M. Johnson, L. Zhou, P. Sanchez, R. Sirel, J. Basilakis, L. Hanien, D. Estival, L. Dawson, B. Kelly, Capturing patient information at nursing shift changes: methodological evaluation of speech recognition and information extraction, J. Am. Med. Informatics Assoc. 22 (1) (2015) e48–e66, http://dx. doi.org/10.1136/amiajnl-2014-002868.
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International Journal of Medical Informatics journal homepage: www.ijmijournal.com
Impacts of mobile tablet computing on provider productivity, communications, and the process of care Benjamin Schooley a,∗ , Steven Walczak a,b , Neset Hikmet a , Nitin Patel c a b c
Integrated Information Technology Department, University of South Carolina, 1301 Gervais St., Columbia, SCS, USA School of Information & Florida Center for Cybersecurity, University of South Florida, Tampa, FL, USA Midlands Internal Medicine, Palmetto Health Richland, Columbia, SC, USA
a r t i c l e
i n f o
Article history: Received 23 September 2015 Received in revised form 15 January 2016 Accepted 22 January 2016 Keywords: Mobile computing Provider productivity Provider-patient Communications Usability Electronic health record Technology acceptanc eHealth Evaluation and assessment Health service research Human-computer interaction Mobile applications Mobile health
a b s t r a c t Objective: Health information technology investments continue to increase while the value derived from their implementation and use is mixed. Mobile device adoption into practice is a recent trend that has increased dramatically and formal studies are needed to investigate consequent benefits and challenges. The objective of this study is to evaluate practitioner perceptions of improvements in productivity, provider-patient communications, care provision, technology usability and other outcomes following the adoption and use of a tablet computer connected to electronic health information resources. Methods: A pilot program was initiated in June 2013 to evaluate the effect of mobile tablet computers at one health provider organization in the southeast United States. Providers were asked to volunteer for the evaluation and were each given a mobile tablet computer. A total of 42 inpatient and outpatient providers were interviewed in 2015 using a survey style questionnaire that utilized yes/no, Likert-style, and open ended questions. Each had previously used an electronic health record (EHR) system a minimum of one year outside of residency, and were regular users of personal mobile devices. Each used a mobile tablet computer in the context of their practice connected to the health system EHR. Results: The survey results indicate that more than half of providers perceive the use of the tablet device as having a positive effect on patient communications, patient education, patient’s perception of the provider, time spent interacting with patients, provider productivity, process of care, satisfaction with EHR when used together with the device, and care provision. Providers also reported feeling comfortable using the device (82.9%), would recommend the device to colleagues (69.2%), did not experience increased information security and privacy concerns (95%), and noted significant reductions in EHR login times (64.1%). Less than 25% of participants reported negative impacts on any of these areas as well as on time spent on order submission, note completion time, overall workload, patient satisfaction with care experience and patient outcomes. Gender, number of years in practice, practice type (general practitioner vs. specialist), and service type (inpatient/outpatient) were found to have a significant effect on perceptions of patient satisfaction, care process, and provider productivity. Conclusions: Providers found positive gains from utilizing mobile devices in overall productivity, improved communications with their patients, the process of care, and technology efficiencies when used in combination with EHR and other health information resources. Demographic and health care work environment play a role in how mobile technologies are integrated into practice by providers. © 2016 Published by Elsevier Ireland Ltd.
1. Introduction
∗ Corresponding author. E-mail addresses: [email protected] (B. Schooley), [email protected] (S. Walczak), [email protected] (N. Hikmet), [email protected] (N. Patel). http://dx.doi.org/10.1016/j.ijmedinf.2016.01.010 1386-5056/© 2016 Published by Elsevier Ireland Ltd.
Despite significant investments in health information technology, the impact on health care remains mixed and regarded by many as disappointing [1]. Some health care providers have experienced modest productivity improvements over time resulting from EHR implementations [2,3], while others have found negative effects, including one study that reported an average of 25–33% decrease in productivity with deployment of a new EHR [4]. Many
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reasons have been given, including systems that are not well integrated with health care processes, are inefficient, overly complex, not easy to use or otherwise causing providers to spend more time documenting and conducting electronic transactions, and less time with patients and collaborating with colleagues [1,5]. Health care providers continue searching for more efficient and effective methods to accomplish their required electronic workload. The implementation and use of mobile device technology is advancing rapidly and market forces are pushing it as one potential solution to productivity challenges [6]. Indeed, these devices offer mobility and convenience for data entry and retrieval and are becoming more widely adopted into medical practice [7,8]. Most providers expect handheld computers to become more useful and are generally interested in gaining value from their use [8–10]. Patient perceptions on the use of desktop computers in medical offices has been studied and shown that patients are generally amenable to the presence of these devices [11,12]. Prior studies have noted potential benefits of mobile handheld computing including the devices being perceived as a portable, relatively inexpensive, integrated platform for point-of-care clinical reference that provides access to Internet-based resources, enables improved patient and data management, rapid response, and error prevention, and can facilitate communications and workflow to enhance clinical practice [7,8,13–15]. Perceived barriers include discomfort with technology and devices, concerns about over-dependency on technology, ineffectiveness of a device to improve workflow or processes, concern about lack of integration with EHRs, usability barriers (e.g., size, weight, screen size, form factor), information privacy and security concerns, negative patient perceptions, lack of organizational support, lack of motivation, and insufficient training [7,9,13,15,16]. Research has also shown that providers desire and require access to information for clinical decision making [17] and that this information access is typically needed within a very short space of time in patient care settings [18]. Mobile devices are one way to answer this information need [7], but research is needed to examine perspectives based on real-world use, how mobile devices are actually used and not just examine what the devices were designed to do [19]. Due to their relative newness, there is a need to conduct studies on mobile tablet adoption and use by providers in clinical settings, including barriers and benefits of use in different clinical contexts. Gagnon et al. [20] systematic review on the barriers of m-health by health providers identified an initial 4223 articles of which 65 were on the topic of m-health adoption, 33 of which were focused on healthcare professionals, and just 2 of which focused on tablet-like computing devices. A broader literature search including live pilot study evaluations of tablet use reveals additional articles. Horng et al. [21] conducted a live pilot study with 13 physicians using both tablets with computers and computers without tablets in an emergency room (ER) setting. Results showed that physicians spent less time interacting with the ED information system when using tablets combined with computers versus computers alone resulting in 38 min per shift average time savings. The authors projected that the time savings could allow for more patient time bedside [21]. In a study of 27 nurses and 8 doctors, researchers observed clinician choice between stationary computers, computers on wheels (COWs), and tablet computers for a wide range of clinical tasks in an Australian teaching hospital. Doctors on ward rounds conducted 35.9% of clinical tasks on tablet computers with the majority of tasks being completed using COWs. Doctors not on ward rounds conducted over 93% of tasks on stationary computers. The study concludes that when selecting computing devices for clinicians, consideration should be given to who will be using the devices, the nature of the work, and the physical layout of the clinical environment [22]. One live field study conducted in 1999 with eleven physicians, nine nurses and four information technol-
63
ogy professionals found that a pen (stylus) based mobile system did not provide significant benefits over computer workstations in clinical settings. The most significant drawback was that most of the applications being used at that time required adaptation to be considered effective for pen input. Access to patient data was found to be the most useful feature, while users also wanted access to email and documentation tasks [23]. As mobile technology continues to adapt and mature, a range of software, hardware, and input and output features may prove more useful in clinical settings than these prior findings revealed and thus require ongoing assessment. Several studies have been conducted with residents in inpatient (hospital) settings. In one study of resident neurologists (n = 9), the impact of tablet computers running an electronic medical record on ward round performance was examined. Results indicated that tablet use led to time savings during preparing and post-processing of ward rounds and checking of medical data, and an increase in physicians’ bedside time [10]. In another study with internal medicine residents (n = 115), implementation of tablet computers was associated with improvements in both perceived and actual clinical efficiency measured by timeliness of order placing [24]. In other studies, pediatric residents (n = 94) indicated that obtaining, management, and display of information were primary uses of the devices for clinical training [25], and internal medicine residents (n = 115) reported expectations of the impacts of the tablet on patient care and overall efficiency was higher pre deployment than four months after deployment [26]. The above studies were conducted in inpatient (hospital) as opposed to outpatient (out of hospital) settings. In one study conducted with five physicians, participants used iPads in a rural outpatient physician practice. Results indicated that perceived usefulness of the iPad was mixed but generally positive with some physicians utilizing the device more than others. The iPads were primarily used by the physicians to access medical information from online resources (e.g., Epocrates and UpToDate) for reference and diagnostic purposes, although they were also used for some interaction with patients. All participants felt that resources available through the iPad were limited and that better applications would improve the usefulness of the iPad [27]. In a different study, 5 first year residents working at an outpatient clinic used an Android tablet computer to aid in patient education and discharge tasks. Results were compared with 5 residents who did not use tablets. The device was perceived as helpful for improving patient understanding and communication between physicians and patients [28]. Taken together, these prior studies indicate that few live field examinations have taken place on provider benefits and barriers of using mobile tablet computers to access critical organizational information resources (e.g., EHR), particularly for the outpatient setting and comparisons between inpatient and outpatient settings. The objective of this research is to examine provider perceptions of workflow and documentation efficiencies, interaction with and education of patients, and overall productivity perceptions of providers utilizing mobile tablet computers. These perceptions represent real world utilization.
2. Methods The participants in this study were 42 care providers working at Palmetto Health, a single health care organization with multiple inpatient and outpatient facilities located in the greater Columbia, South Carolina U.S.A. region. Each provider volunteered to participate in a live pilot test to use a Microsoft SurfaceTM tablet computer within his/her daily practice of medicine. Participant demographics are shown in Table 1. The tablet devices were first introduced into practice in June 2013 and extended for 18 months prior to
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Table 1 Participant demographics. Frequency
Percent
Gender Female Male
19 23
45.20% 54.80%
Practice type General practitioner Specialist
30 12
71.40% 28.60%
Service type Inpatient Outpatient Both in/out patient
5 22 14
11.90% 52.40% 33.30%
Years in practice 10 years or less 11 to 15 years 16 or more years
13 12 17
31.00% 28.60% 40.50%
devices were version 3 of the device with the following differences: 12 touchscreen, Intel x64Haswell Core i3 processor, 128 GB of storage, 6 GB memory. All devices weighed less than 2 pounds. Email and office productivity software came pre-loaded, while security suite and software to connect to the virtualized EHR, CPOE, and PACS systems were installed by the Palmetto information technology department.
2.2. Survey instrument
conducting a post pilot test evaluation in early 2015. All participants had a mobile device to use for at least six months prior to conducting the evaluation. No providers were consulted prior to roll out and training was not provided. Participants were recruited by one physician at the health care institution whom invited his outpatient colleagues via email and in-person communications. Inclusion criteria included providers with strong familiarity with existing EHR systems and interest in mobile computing in medical practice. Participation was limited to 42 volunteers due to limited available technology resources, including the number of available tablet computers and the virtualization computing infrastructure required to serve existing electronic information resources to the devices. Existing electronic resources made available to participants via application virtualization technology included electronic health record (EHR) systems, computerized physician order entry (CPOE), picture archiving and communication systems (PACS), email, and Internet access. All 42 pilot test participants also participated in a post pilot evaluation that began in January and concluded in April 2015. No financial support was provided to carry out the evaluation either by Palmetto Health or any other organization. 2.1. Study setting Palmetto Health operates six hospitals (1138 beds) and 38 provider practices with just over 1000 physicians and dentists providing care for nearly a half million patients per year across more than 15 different medical specialties. The health system is present in 15 counties in South Carolina. The providers in the study represented 2 hospitals and 18 different practices in two South Carolina counties. Palmetto Health’s current EHR system was implemented in January 2012 for the outpatient setting, and 2007 for the inpatient setting. The organization uses the 2014 software version from a major EHR vendor that scored 13 out of 15 on the user-centered design best practices framework developed by the American Medical Association and MedStar Health’s National Center for Human Factors in Healthcare. Palmetto Health has been using PACS since 2000, CPOE since 2010 for inpatient and 2012 for ambulatory, each provided by large software vendors. All of these systems were made available to the appropriate providers that participated in this study. The mobile devices used for the pilot study were Microsoft SurfaceTM tablet computers. The first 28 devices acquired were the first version device that included 10.6 high definition touchscreens, Windows 8 Professional operating systems, 64 gigabytes (GB) of storage, 4 GB of memory, quad core Nvidia Tegra 3 processors, active pens (stylus), ambient light sensors, 3-axis accelerometers, full size USB 3.0 port, Wi-Fi only connectivity, detachable keyboard, and front and rear cameras. The latter 13
A 31 question author generated survey protocol was designed to evaluate improvements and challenges to utilization, provider productivity, process of care, provider-patient interactions, and satisfaction resulting from tablet computer use. The instrument was developed based on literature review on utilization, usability, and acceptance of mobile computing devices in health care settings. An expert panel of researchers and health practitioners, none of whom was a participant in the pilot evaluation, was used to examine questions and pilot test the survey prior to conducting the evaluation. The survey and interview methodology was approved by both the University of South Carolina and also Palmetto Health’s Institutional Review Board. The interviews were conducted in person, took approximately 30–40 min to complete, and were scheduled at the convenience of each participant (typically lunch time or after hours). The survey instrument was used by the interviewer as a guide for discussion and was not given to the participant to complete. Each Likert and yes/no question was followed by an open-ended question for the participant to provide further detail or explanations regarding the answers given. Respondents were permitted to skip or not respond to any question that they did not feel comfortable answering. Responses were recorded manually on the instrument and, if approved of by the participant, also via audio tape. The results were then transcribed into a spreadsheet for import and analysis in the IBM SPSS version 22 statistical package. After analysis was completed an additional 5 question survey was developed and administered online to further clarify the possible benefits. The response rate to the second survey is 65.85 percent of the original interviews that represented 100 percent of the population of provider tablet computer users. Significance was considered at the p < 0.01 and 0.05 level. Descriptive statistics, cross-tab analysis, one-way between subjects ANOVA, and qualitative analysis of open-ended responses were used to analyze data.
3. Results Study participant demographics are shown in Table 1. All participants reported at least one year of prior experience using an EHR system before pilot rollout (average 5.6 years outside of residency), and all but one reported using either a smartphone, tablet computer, or both on a regular basis for personal use (average 6.7 years’ experience). There are distinct differences between Practice Type and Service Type demographics for this study. General practitioners (n = 30) included those trained to provide primary health care covering a variety of medical conditions to patients of either sex or any age. Specialists (n = 12) included providers who have completed advanced education and clinical training in a specific area of medicine including cardiology, pulmonary disease, obstetrics and gynecology, oncology, surgery, gastroenterology, pediatric specialties, and others. In terms of Service Type, those that identified as inpatient providers (5) were those that practice medicine on patients admitted to a hospital, while those that identified as outpatient providers (22) practice medicine on patients without being admitted to a hospital, with the remaining participants practicing in both settings (14). Of the 42 participants, 35 identified as Medical
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Table 2 Provider perspectives on mobile device use. Likert responses—impact of device on:
Negative
No change
Positive
Patient communications Patient education Patient’s perception of provider Time spent interacting with patients Provider productivity Time spent on order submission Note completion Process of care Workload Improve workday Care provision Patient outcomes Patient satisfaction with care experience Device comfort rating User (provider) satisfaction with EHR together with device Security concerns Would you recommend the device to colleagues?
17.9% 0.0% 11.1% 10.5% 23.1% 23.7% 27.0% 21.1% 21.9% 17.9% 25.7% 2.4% 13.2% 7.3% 29.3% 5.0% 12.8%
28.2% 48.6% 33.3% 34.2% 23.1% 44.7% 27.0% 26.3% 43.8% 25.0% 14.3% 65.9% 42.1% 9.8% 14.6% 87.5% 17.9%
53.8% 51.4% 55.6% 55.3% 53.8% 31.6% 45.9% 52.6% 34.4% 57.1% 60.0% 31.7% 44.7% 82.9% 56.1% 7.5% 69.2%
Yes 25.6% 64.1% 53.6% 57.1% 57.1%
No 74.4% 35.9% 46.4% 42.9% 42.9%
Yes/No items Nurse interaction improved EHR log in decrease Does the use of the device reduce the amount of time spent after work completing documentation? Does use of the device improve your overall efficiency at work? Would you feel more comfortable seeing an increased number of patients using the mobile device vs. a traditional computer desktop?
Doctors, 3 as Doctor of Osteopathy, 3 as a Nurse Practitioners, and 1Certified Medical-Surgical Registered Nurse (CMSRN). The abbreviated interview questions and results are shown in Table 2. As may be seen from Table 2, provider perceptions were mixed. Results from descriptive statistics showed providers responded positively to various impacts that they believed the device had on provider-patient relations, productivity, process of care, and technology efficiency. More than half of participants reported use of the device had positive impacts on areas related to provider-patient relations including patient communications (53.8%), patient education (51.4%), patient’s perception of provider (55.6%), and time spent interacting with patients (55.3%), with the vast majority reporting no negative impact across each area (82%, 100%, 88.9%, 89.5% respectively). In terms of provider productivity, the majority of participants reported improvements in overall efficiency at work (57.1%), reduction of time spent after work completing documentation (53.6%), and that overall they were more productive (53.8%) by using the device. Participants reported that patient order submission time (76.3%) and note completion times (73.9%) did not increase as a result of using the device. The majority of results showed either improvement (31.6%) or no change (44.7%) in the time spent on order submission, and either improvement (45.9%) or no change (27%) in note completion times. Finally, most providers reported that using the device did not improve their interactions with nurses. In terms of impacts on provider care provision, 52.6% reported the process of care improved (52.6%), 43.8% reported no change to daily workload, 57.1% believed using the device helped improve their workday, and 60% perceived the device to positively impact care provision while 25.7% reported a negative impact. Further, participants believed using the device had either a positive effect (31.6%) or had no change (65.9%) on patient outcomes. Providers believed that patient satisfaction with their care experience was either positive (44.7%) or that there was no overall change in satisfaction (42.1%) since using the device. Finally, when asked if they would feel more comfortable seeing an increased number of patients using the mobile device versus a traditional desktop computer, 57.1% responded yes. Several technology usability questions were also asked. The majority of respondents answered positively in terms of their comfort level using the device (82.9%), and satisfaction with the EHR
increased when used together with the device (56.1%). Most did not experience increased security concerns as a result of using the device (95%), and 64.1% reported that EHR login times decreased as a result. When asked if they would recommend the device to their colleagues, 68.2% responded positively, with 17.9% feeling unsure (noted as “no change” in Table 2).
3.1. Cross-tab and ANOVA results Participant responses were further analyzed by conducting cross-tab and one-way analysis of variance (ANOVA) to compare statistical differences across demographic categories including gender; number of years in practice; service type (inpatient vs. outpatient vs. both); and practice type (general practitioner vs. specialist). Results from ANOVA are shown in Table 3, and crosstab results are shown in Appendix A. Results indicated that there was a statistically significant difference between inpatient and outpatient providers for two questionnaire items. These included provider beliefs about the impact of the mobile device use on the process of care (F(2, 34) = 7.900, p = 0.002), and improved nurse interaction (F(2, 35) = 3.502, p = 0.041), with inpatient providers generally showing more positive responses in the first category and both inpatient only and inpatient/outpatient providers reporting more positive perspectives than outpatient only providers. Statistically significant differences between general practitioner and specialty providers included perceptions about patients being satisfied since using the mobile device (F(1, 36) = 5.890, p = 0.020), with general practitioners responding more positively. Further, beliefs about the patient’s perception of the providers were significantly different (F(1, 34) = 4.515, p = 0.041), with general practitioners reporting more positively in this regard (64.0% vs. 36.4%). Number of years in practice also showed statistical differences for survey items related to the use of the device impacting process of care improvement (F(2, 35) = 7.028, p = 0.003), satisfaction with device when used together with the EHR (F(2, 38) = 3.724, p = 0.033), perceptions about patients being satisfied since using the mobile device (F(2, 35) = 3.261, p = 0.050), and the provision of care (F(2, 32 = 3.823 p = 0.032)). For each of these items, providers who had reported practicing longer responded more positively.
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1.813 4.655 5.161 1.918 6.295 4.754 2.001 0.006 0.003** 0.033* 0.050* 0.032* 0.993 0.246 0.380 0.570 7.028 3.724 3.261 3.823 0.007* 1.458 0.996 0.571
.187 .037* .029* .175 .019* .036* .166 .941
F Sig. F
0.002** 0.754 0.599 0.101 0.613 0.293 0.061 0.041* Sig at p < 0.05. Sig at p < 0.01. *
3.863 0.584 5.890 1.921 3.250 3.657 4.515 0.708 Process of care** Satisfaction with EHR together with device* Patient satisfaction with care experience* Care provision* Comfortable seeing more patients using the device vs. desktop computer* Time spent on order submission* Patient’s perception of provider* Nurse interaction improved*
**
Sig.
3.2. Mixed-method results
7.900 0.284 0.521 2.470 0.500 1.273 3.063 3.502
F F Survey item
Sig.
Service type Practice type Table 3 ANOVA results for practice type, service type, years in practice, and gender.
Finally statistically significant differences between gender groups were found including satisfaction with the mobile device when used together with the EHR (F(1, 39) = 4.655, p = 0.037), perceptions about patients being more satisfied since using the mobile device (F(1, 36) = 5.161, p = 0.029), comfort level seeing more patients using the device over a desktop computer (F(1, 26) = 6.295, p = 0.019), and time spent on order submission since using the device (F(1, 36) = 4.754, p = 0.036). Crosstab analysis showed males reported more positive results regarding time spent on order submission. However, females reported more positive beliefs for each of the other three question items including satisfaction using the device with the EHR, beliefs in device use impacting patient satisfaction, and comfort level seeing more patients using the device over a desktop computer. No other statistically significant differences were found between groups.
0.057 0.449 0.020* 0.175 0.083 0.064 0.041* 0.406
Years in practice
Gender
Sig.
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Open-ended questions about the use of the device were also asked. First, comments revealed that several respondents who had received an earlier version of the device with a smaller screen would not recommend it to their colleagues. However, those same respondents noted that they would recommend the newer versions of the tablet computer to their colleagues. Comments revealed a number of benefits of using the device including showing patients their pathology results, diagrams for patient education, and looking up information on the web directly on the computer. The two most reported benefits from using tablet computers were (1) its portability, and (2) its personalization to the provider user. Fifteen percent of the respondents indicated they used the tablet computer primarily at home. Furthermore, 32% indicated they completed notes or used the tablet to prepare for patient visits at home, on the road, or while traveling. Five providers specifically stated that the portability of the device, allowing for note writing and documentation at their convenience, resulted in significant efficiencies that allowed for leaving work and arriving home at the end of the day earlier than without the device. These process changes improved their quality of life. In a follow up online survey sent to the respondents, they were asked to rank order from 1 to 6 the order of their satisfaction with system features: touch screen, stylus, portability, ability to run the full EHR application, camera and video, and detachable keyboard. Portability was ranked as the number one choice by 64% of the respondents with an overall ranking of 1.68. The touchscreen and ability to run the full EHR application were ranked second and third highest with an overall score of 2.76 and 2.8 respectively. The remainder were ranked in order: stylus (3.64), detachable keyboard (4.64), and finally camera/video (5.48). Some additional analysis was conducted on provider responses to the open-ended question “What improvements could be made to the device that would increase your satisfaction?” Three main answers occurred to this question for the 33 providers responding: over 45% indicated a larger screen was desirable. It should be noted that only one provider desiring a larger screen used a Surface 3 (12 in. display), with all the others using earlier smaller screen versions (10 in.). The majority of respondents (74%) noted EHR (Electronic Health Record) integration issues on the tablet, including the version of the EHR that was in-use was not mobile friendly. Further, 21% indicated that voice recognition or improvements in the voice recognition program were desired; 18% indicated longer battery life would improve usability; and 15% indicated issues with the current keyboard configuration including size, angle, and physical flexibility. All other recommendations had less than 15% response and included issues such as network connectivity issues,
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preference for another device or operating system, or lack of IT (information technology) training and support for the tablets.
4. Discussion The results indicate that slightly more than half of respondents reported positively about the impact of using the mobile tablet device on a range of measures including provider-patient communications, patient education, patient satisfaction, provider productivity, process of care, and technological improvements. Similar findings have been reported in other studies, including those mentioned in the introduction of this text. The mixed findings in this and across prior studies may be in part due to the many barriers and facilitators of adoption of technology in healthcare settings as found by [20]. They identified 51 different traits that were mentioned as being barriers or facilitators of adoption. Of these, 14 were pure barriers, 12 were pure facilitators, and the remaining 25 were listed as being both barriers and facilitators [20]. Similarly, [22] conducted an observational study of physician tasks and concluded that device implementation for providers should consider who will be using the devices, the nature of the work, and the physical layout of the clinical environment [22]. This study confirms these findings and extends the work of these researchers to show that gender, number of years in practice, service type and practice type play a role in how mobile tablet computing devices are used and perceived by providers. A significant finding in this study is that the device was, for the vast majority of providers, not perceived to have a negative impact across question items including time spent on order submission, note completion time, and overall workload. The literature is replete with studies showing provider resistance to implementing new information technologies in patient care, low levels of trust and belief that these technologies will have a positive impact on care processes, and a wide variety of factors that influence negative provider beliefs toward using computing based solutions in patient care [1,15,16,20,26]. The reasoning behind such beliefs may be very well justified. However, the results of this study did not seem to indicate such. This may be because many of the prior studies on adoption and use of health IT discuss large and complex software systems such as EHRs, CPOE, clinical decision support, and others, whereas, according to provider comments, the mobile device represents a single and integrated medium whereby the existing complex systems can be more conveniently accessed and utilized. This may be one important reason why providers did not link efficiency, workflow, and productivity benefits achieved directly to affecting patient outcomes—as the device itself does not impact clinical decision making, or other areas for which the provider has direct influence. It may be important for future studies on complex health IT systems to delineate between the software being used (e.g., EHR) and the mode of access (e.g., PC, tablet, COW, smartphone). While some field studies address usability in terms of more objective task performance [15,21,24], this study addresses usability in terms of provider perspectives, showing positive results for comfort using the device, satisfaction, and recommendation to colleagues. Acceptance and future use of mobile technologies may be promising when looking at these results. A specific type of mobile tablet computer was used for this study, but the device itself is very similar in function, size, weight, and features as many other mobile tablet computers that can be found in the marketplace. Thus, the specific device itself should not be considered the primary factor associated with these findings. Rather, device mobility and features (pen/stylus, form factor, and other common features) connected to essential health information resources should be the primary factors for consideration. For example, the finding of portability
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and larger screen size as highly useful features is consistent with previous research [28,29]. Other integrated features, including the pen/stylus, seem to be perceived as more useful than reported in prior research [23], likely due to technology advances. Various add-on devices to mobile tablets, such as voice recognition systems, should be investigated in the future as a range of efficiencies have been found through the use of speech recognition software [30]. Prior studies, including Suominen et al. [31] pilot of 8 participants found that provider preference was for tablet computers, as opposed to small stand-alone voice recording devices that could be used for multiple different tasks beyond voice recognition. It should be noted that the DragonTM voice recognition system was not made available to users during the first year of the field study and starting in summer 2014 was installed for providers only upon request. This should be considered in light of the 21% of respondents whom desired better integration between voice recognition and tablet devices. With low participation and use of this particular technology integration for this study, these results should be further investigated in the future. Another important aspect of this study is that providers were not given any training or instruction on how to use the device in the practice of medicine. This may be considered a limitation of this study as the duration and quality of training has long been known to positively impact perceptions and utilization of new information technologies. The study by Abbott [19] in which nurses rated the capabilities of a different mobile computing device very highly differs from the current study in an important way. Abbott’s subjects received extensive training on their mobile device. This training is critical to enable providers to fully understand the capabilities and applications of the devices and to gain an even higher level of comfort in using a newer technology in a clinical setting. However, training can also impede self-learning, which can impede innovative and creative uses of new information technologies. The decision was made in this study to provide a device to providers and allow each of them to determine appropriate use. Future studies may determine best practice use cases and integrate those into provider technology training, conduct a live pilot test, and then assess perspectives. Some providers also noted a lack of IT (information technology) support for this project. This can also serve to frustrate providers attempting to utilize newer mobile technologies to their fullest capabilities but who have questions regarding technology functionality. Thus, while portable tablet computing devices are generally perceived to be beneficial, IT must plan appropriately to train and respond to inquiries in order to maximize this potential. Another contribution of this study was the real-world use of the mobile technology together with the EHR. As previously mentioned, Palmetto Health has been using the same EHR vendor for the past 8 years. Several of the interviewed providers indicated dissatisfaction with the EHR’s functionality, which is a distinct issue from satisfaction and benefit of using the mobile platform. This was evident in participant responses to the question “Satisfaction with the EHR together with device.” This question received the largest percent of negative responses from participants than any other Likert scale question. Further, the responses to this question significantly differed based on number of years in practice and gender. In practice, it may not be easy for all users to clearly delineate between the EHR software application and the device that accesses the technology as both are used together to accomplish essential tasks. Thus, improvements to EHRs may influence future studies assessing mobile device impacts and vice versa. One relevant discussion point from this study may be the importance of EHR companies creating more usable mobile versions of their software systems or responsive interfaces. Such improvements may significantly influence provider perceptions about the positive impacts of EHR systems, the mobile devices used to access them, and the integrated EHR/mobile device experience.
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5. Limitations A known limitation of survey research is that it is based on the participants’ opinions. This is a cross-sectional study and therefore represents a snapshot in time, and is limited to inpatient and outpatient, general practitioner and specialist providers working for the same health care system in the Southeast United States, with mobile devices having been connected to a large vendor EHR system. The results of this study may not be generalizable to all providers and health care systems as the number and combination of medical specialties, work environments, and EHR vendor systems varies significantly across the United States. While the number of users that participated in the pilot is significant for a live field test in this context, the population nevertheless is relatively small (n = 42) in terms of statistical significance and impacts on generalizability. Nevertheless, responses may be representative of some health care systems in a variety of settings. A larger and broader sample may reveal differences among different regions. As with other survey studies, this study used subjective, selfreported measures. It is possible that response bias contributed to our findings. Another important limitation common with technology studies is that new mobile technologies were released to the marketplace during the period of this project. Thus, those who received and tested earlier version devices may have responded differently to questions had they used a newer version. 6. Conclusion The reported results indicate that the users found positive gains from utilizing the tablet device in overall productivity, improved communications with their patients, the process of care, and efficiencies. Additionally, some positive outcomes were perceived, specifically with the patients’ positive perception of the provider and in overall improved patient satisfaction. Further, the vast majority of responses showed that providers believed that the device produced no negative impact in every category, including workload, order submission time, patient outcomes, patient education, to name a few. However it should also be noted that while no change was the predominant answer for these questions, in most cases a percentage of the users indicated that benefits in these categories did occur, and was generally positive for 25% or higher of the respondents. Few participants reported negative impacts on survey question items including time spent on order submission, note completion time, overall workload, patient satisfaction with care experience and patient outcomes. Gender, number of years in practice, practice type (general practitioner vs. specialist), and service type (inpatient/outpatient) were found to have a significant effect
Summary Points What was already known: • Most healthcare providers expect increased access to information resources, believe handheld computers connected to those resources (e.g., EHR, CPOE, PACS) will become more useful in this regard, and are generally interested in gaining value from their use. • Prior studies have noted potential benefits and perceived barriers of mobile handheld computing in areas such as workflow, technology usability, patient satisfaction, EHR integration, and provider productivity. • The few live field studies that have been conducted show some productivity improvements, such as less time at a computer and increased provider availability. What this study has added: • Live field study and evaluation of actual use for extended period of time in both outpatient and inpatient settings. • Reported improvements in patient communications, patient education, patient’s perception of the provider, time spent interacting with patients, provider productivity, process of care, satisfaction with EHR when used together with the device, and care provision. • Providers reported feeling comfortable using the device (82.9%), would recommend the device to colleagues (69.2%), did not experience increased information security and privacy concerns (95%), and noted significant reductions in EHR login times (64.1%).
on perceptions of patient satisfaction, care process, and provider productivity. Mobile tablet computers may provide significant benefits of personalization, portability, flexibility, and productivity to providers depending on the care environment. Individuals responsible for rolling out information technologies to health care practitioners should consider the factors associated with adoption reported herein, including the need for a well-functioning interplay between the device, the provider, and the EHR. Acknowledgments We are grateful to the administrators and providers at Palmetto Health for their time in coordinating and participating in this research. In particular, Jose Delcastillo Jr., Project Manager, provided a significant amount of work scheduling and coordinating interviews, and collating responses.
Appendix A. : Crosstab Analysis Practice type
How satisfied do you think your patients are since MS use?
Total
Patient’s perception of provider
Negative
No change
Positive
General practitioner Sub-specialty
1 (3.7%) 4 (36.4%)
12 (44.4%) 4 (36.4%)
14 (51.9%) 3 (27.3%)
27 (100%) 11 (100%)
Total
5 (13.2%)
16 (42.1%)
17 (44.7%)
38 (100%)
Service type
Process of care improved?
Total Years in practice
No change
Positive
1 (4%) 3 (27.3%)
8 (32%) 4 (36.4%)
16 (64%) 4 (36.4%)
25 (100%) 11 (100%)
12 (33.3%)
20 (55.6%)
36 (100%)
4 (11.1%) Total
Negative
No change
Positive
0 (0%) 2 (10.53%) 6 (46.15%)
1 (20%) 4 (21.05%) 5 (38.46%)
4 (80%) 13 (68.42%) 2 (15.38%)
8 (21.62%)
10 (27.03%)
19 (51.35%)
Process of care improved?
Nurse interaction improved
Total
Yes
No
5 (100%) 19 (100%) 13 (100%)
0 (0%) 8 (40%) 1 (7.69%)
5 (100%) 12 (60%) 12 (92.31%)
5 (100%) 20 (100%) 13 (100%)
37 (100%)
9 (23.68%)
29 (76.32%)
38 (100%)
Total
How satisfied are you using MS with cerner system?
Total
Negative
No change
Positive
Negative
No change
Positive
10 Years or less 11–15 16 or more
1 (8.3%) 6 (50%) 1 (7.1%)
6 (50%) 3 (25%) 1 (7.1%)
5 (41.7%) 3 (25%) 12 (85.7%)
12 (100%) 12 (100%) 14 (100%)
7 (53.8%) 4 (33.3%) 1 (6.3%)
1 (7.7%) 2 (16.7%) 3 (18.8%)
5 (38.5%) 6 (50%) 12 (75%)
13 (100%) 12 (100%) 16 (100%)
Total
8 (21.1%)
10 (26.3%)
20 (52.6%)
38 (100%)
12 (29.3%)
6 (14.6%)
23 (56.1%)
41 (100%)
Years in practice
How satisfied do you think your patients are since MS use?
10 Years or less 11–15 16 or more Gender
Negative
No change
Positive
2 (16.7%) 2 (20%) 1 (6.3%) 5 (13.2%)
8 (66.7%) 4 (40%) 4 (25%) 16 (42.1%)
2 (16.7%) 4 (40%) 11 (68.8%) 17 (44.7%)
Total
Do you think you are providing better care since MS use?
12 (100%) 10 (100%) 16 (100%) 38 (100%)
Time spent on order submit
Negative
No change
Positive
4 (36.4%) 4 (40%) 1 (7.1%) 9 (25.7%)
1 (9.1%) 3 (30%) 1 (7.1%) 5 (14.3%)
6 (54.5%) 3 (30%) 12 (85.7%) 21 (60%)
Total
How satisfied are you using MS with cerner system?
Total
11 (100%) 10 (100%) 14 (100%) 35 (100%) Total
Negative
No change
Positive
Negative
No change
Positive
Male Female
4 (18.2%) 8 (50%)
11 (50%) 6 (37.5%)
7 (31.8%) 2 (12.5%)
22 (100%) 16 (100%)
10 (45.5%) 2 (10.5%)
2 (9.1%) 4 (21.1%)
10 (45.5%) 13 (68.4%)
22 (100%) 19 (100%)
Total
12 (31.6%)
17 (44.7%)
9 (23.7%)
38 (100%)
12 (29.3%)
6 (14.6%)
23 (56.1%)
41 (100%)
Gender
How satisfied do you think your patients are since MS use?
Total
Negative
No change
Positive
Male Female
4 (19%) 1 (5.9%)
11 (52.4%) 5 (29.4%)
6 (28.6%) 11 (64.7%)
Total
5 (13.2%)
16 (42.1%)
17 (44.7%)
Comfortable seeing more patients using the SP vs. DC?
B. Schooley et al. / International Journal of Medical Informatics 88 (2016) 62–70
Inpatient Outpatient Both in/out-patient
Total
Negative
Total
Yes
No
21 (100%) 17 (100%)
8 (42.1%) 8 (88.9%)
11 (57.9%) 1 (11.1%)
19 (100%) 9 (100%)
38 (100%)
16 (57.1%)
12 (42.9%)
28 (100%)
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Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.ijmedinf.2016. 01.010. References [1] A.L. Kellermann, S.S. Jones, What it will take to achieve the as-yet-unfulfilled promises of health information technology, Health Affairs 32 (1) (2013) 63–68, http://dx.doi.org/10.1377/hlthaff.2012.0693. [2] A.D. Cheriff, A.G. Kapur, M. Qiu, C.L. Cole, Physician productivity and the ambulatory EHR in a large academic multi-specialty physician group, Int. J. Med. Informatics 79 (7) (2010) 492–500, http://dx.doi.org/10.1016/j.ijmedinf. 2010.04.006. [3] N.S. Fleming, E.R. Becker, S.D. Culler, D. Cheng, R. McCorkle, B. da Graca, D.J. Ballard, The impact of electronic health records on workflow and financial measures in primary care practices, Health Serv. Res. 49 (1pt2) (2014) 405–420, http://dx.doi.org/10.1111/1475-6773.12133. [4] H.K. Bhargava, A.N. Mishra, Electronic medical records and physician productivity: evidence from panel data analysis, Manag. Sci. 60 (10) (2014) 2543–2562, http://dx.doi.org/10.1287/mnsc.2014.1934. [5] M.E. Flanagan, J.J. Saleem, L.G. Millitello, A.L. Russ, B.N. Doebbeling, Paper-and computer-based workarounds to electronic health record use at three benchmark institutions, J. Am. Med. Informatics Assoc. 20 (1) (2013) e59–e66, http://dx.doi.org/10.1136/amiajnl-2012-000982. [6] N. Jaria-Chacon, D. Arias-Aranda, Mobile device platforms and servitization: towards an integrative model, DYNA Manag. 2 (2014) 1, http://dx.doi.org/10. 6036/MN7047. [7] Y.-C. Lu, Y. Xiao, A. Sears, J.A. Jacko, A review and a framework of handheld computer adoption in health care, Int. J. Med. Informatics 74 (5) (2005) 409–422, http://dx.doi.org/10.1016/j.ijmedinf.2005.03.001.2. [8] J. Sclafani, T.F. Tirrell, O.I. Franko, Mobile tablet use among academic providers and trainees, J. Med. Syst. 37 (1) (2013) 1–6, http://dx.doi.org/10. 1007/s10916-012-9903-6. [9] K.F.B. Payne, H. Wharrad, K. Watts, Smartphone and medical related App use among medical students and junior doctors in the United Kingdom (UK): a regional survey, BMC Med. Informatics Decis. Mak. 12 (2012) 121, http://dx. doi.org/10.1186/1472-6947-12-121. [10] R. Fleischmann, J. Duhm, H. Hupperts, S.A. Brandt, Tablet computers with mobile electronic medical records enhance clinical routine and promote bedside time: a controlled prospective crossover study, J. Neurol. 262 (3) (2015) 532–540, http://dx.doi.org/10.1007/s00415-014-7581-7. [11] C.N. Sciamanna, S.P. Novak, B.H. Marcus, Effects of using a computer in a doctor’s office on patient attitudes toward using computerized prompts in routine care, Int. J. Med. Informatic 74 (5) (2005) 357–365, 10.1016/j.ijmedinf.2005.03.003. [12] C. Sibona, S. Walczak, J. Brickey, M. Parthasarathy, Patient perceptions of electronic medical records: provider satisfaction, portability, security, and quality of care, Int. J. Biomed. Eng. Technol. 12 (1) (2011) 62–84, http://dx.doi. org/10.1504/IJHTM. [13] A. Holzinger, P. Kosec, G. Schwantzer, M. Debevc, R. Hofmann-Wellenhof, J. Frühauf, Design and development of a mobile computer application to reengineer workflows in the hospital and the methodology to evaluate its effectiveness, J. Biomed. Informatics 44 (6) (2011) 968–977, http://dx.doi.org/ 10.1016/j.jbi.2011.07.003. [14] M. Prgomet, A. Georgiou, J.I. Westbrook, The impact of mobile handheld technology on hospital providers’ work practices and patient care: a systematic review, J. Am. Med. Informatics Assoc. 16 (6) (2009) 792–801, http://dx.doi.org/10.1197/jamia.M3215.
[15] O. Alsos, A. Das, D. Svanaes, Mobile health IT: the effect of user interface and form factor on doctor-patient communication, Int. J. Med. Informatics 81 (1) (2012) 12–28, http://dx.doi.org/10.1016/j.ijmedinf.2011.09.004. [16] A.S. McAlearney, S.B. Schweikhart, M.A. Medow, Doctors’ experience with handheld computers in clinical practice: qualitative study, Br. Med. J. 328 (7449) (2004) 1162, http://dx.doi.org/10.1136/bmj.328.7449.1162. [17] D.L. Sackett, S.E. Straus, Finding and applying evidence during clinical rounds: the evidence cart, J. Am. Med. Assoc. 280 (15) (1998) 1336–1338, http://dx. doi.org/10.1001/jama.280.15.1336. [18] M.A. Ellsworth, J.M. Homan, J.J. Cimino, S.G. Peters, B.W. Pickering, V. Herasevich, Point-of-care knowledge-based resource needs of clinicians a survey from a large academic medical center, Appl. Clin. Informatics 6 (2) (2015) 305–317, http://dx.doi.org/10.4338/ACI-2014-11-RA-0104. [19] P.A. Abbott, The effectiveness and clinical usability of a handheld information appliance, Nurs. Res. Pract. 2012 (2012) 307258, http://dx.doi.org/10.1155/ 2012/307258. [20] M.P. Gagnon, P. Ngangue, J. Payne-Gagnon, M. Desmartis, m-Health adoption by healthcare professionals: a systematic review, J. Am. Med. Informatics Assoc. (2015), http://dx.doi.org/10.1093/jamia/ocv052. [21] S. Horng, F.R. Goss, R.S. Chen, L.A. Nathanson, Prospective pilot study of a tablet computer in an emergency department, Int. J. Med. Informatics 81 (5) (2012) 314–319, http://dx.doi.org/10.1016/j.ijmedinf.2011.12.007. [22] P. Andersen, A.M. Lindgaard, M. Prgomet, N. Creswick, J.I. Westbrook, Mobile and fixed computer use by doctors and nurses on hospital wards: multi-method study on the relationships between clinician role, clinical task, and device choice, J. Med. Intern. Res. 11 (2009) 3, http://dx.doi.org/10.2196/ jmir.1221. [23] A. Buchauer, U. Pohl, N. Kurzel, R. Haux, Mobilizing a health professional’s workstation-results of an evaluation study, Int. J. Med. Informatics 54 (2) (1999) 105–114, http://dx.doi.org/10.1016/S1386-5056(98) 00170-1. [24] B.K. Patel, C.G. Chapman, N. Luo, J.N. Woodruff, V.M. Arora, Impact of mobile tablet computers on internal medicine resident efficiency, Arch. Intern. Med. 172 (5) (2012) 436–438, http://dx.doi.org/10.1001/archinternmed.2012.45. [25] Howard, D.J., Coovert, S.A., Coovert, M.D., Nelson, RM. Telemedicine and e-Health. 2015; 21(7): 588-592. http://dx.Doi.org/10.1089/tmj.2014.0130. [26] N. Luo, C.G. Chapman, B.K. Patel, J.N. Woodruff, V.M. Arora, Expectations of iPad use in an internal medicine residency program: is it worth the hype? J. Med. Intern. Res. 15 (2013) 5, http://dx.doi.org/10.2196/jmir.2524. [27] C. Anderson, T. Henner, J. Burkey, Tablet computers in support of rural and frontier clinical practice, Int. J. Med. Informatics 82 (November (11)) (2013) 1046–1058, http://dx.doi.org/10.1016/j.ijmedinf.2013.08.006. [28] B. Schooley, T. San Nicolas-Rocca, R. Burkhard, Patient-provider communications in outpatient clinic settings: a clinic-based evaluation of mobile device and multimedia mediated communications for patient education, JMIR MHealth UHealth 3 (January (1)) (2015) http://mhealth.jmir. org/2015/1/e2/. [29] H. Friederichs, B. Marschall, A. Weissenstein, Practicing evidence based medicine at the bedside: a randomized controlled pilot study in undergraduate medical students assessing the practicality of tablets, smartphones, and computers in clinical life, BMC Med. Informatics Decis. Mak. 14 (2014) 113, http://dx.doi.org/10.1186/s12911-014-0113-7. [30] T. Hodgson, E. Colera, Risks and benefits of speech recognition for clinical documentation: a systematic review, J. Am. Med. Informatics Assoc. (2015), http://dx.doi.org/10.1093/jamia/ocv152. [31] H. Suominen, M. Johnson, L. Zhou, P. Sanchez, R. Sirel, J. Basilakis, L. Hanien, D. Estival, L. Dawson, B. Kelly, Capturing patient information at nursing shift changes: methodological evaluation of speech recognition and information extraction, J. Am. Med. Informatics Assoc. 22 (1) (2015) e48–e66, http://dx. doi.org/10.1136/amiajnl-2014-002868.