Jie Huang, PhD

 Continuity of patient information across settings can improve transitions after hospital discharge, but outpatient clinicians often have limited access to complete information from recent hospitalizations. We examined whether providers’ timely access to clinical information through shared inpatient-outpatient electronic health records (EHRs) was associated with follow-up visits, return emergency department (ED) visits, or readmissions after hospital discharge in patients with diabetes.

 As an integrated delivery system staggered implementation of a shared inpatient-outpatient EHR, we studied 241,510 hospital discharges in patients with diabetes (2005-2011), examining rates of outpatient follow-up office visits, telemedicine (phone visits and asynchronous secure messages), laboratory tests, and return ED visits or readmissions (as adverse events). We used multivariate logistic regression adjusting for time trends, patient characteristics, and medical center and accounting for patient clustering to calculate adjusted follow-up rates.

 For patients with diabetes, provider use of a shared inpatient-outpatient EHR was associated with a statistically significant shift toward follow-up delivered through a combination of telemedicine and outpatient laboratory tests, without a traditional in-person visit (from 22.9% with an outpatient-only EHR to 27.0% with a shared inpatient-outpatient EHR; 

 < .05). We found no statistically significant differences in 30-day return ED visits (odds ratio, 1.02; 95% CI, 0.96-1.09) or readmissions (odds ratio, 0.98; 95% CI, 0.91-1.06) with the shared EHR compared with the outpatient-only EHR.

 Real-time clinical information availability during transitions between health care settings, along with robust telemedicine access, may shift the method of care delivery without adversely affecting patient health outcomes. Efforts to expand interoperability and information exchange may support follow-up care efficiency.

Continuity in access to patient information across providers in different settings can improve patient transitions. We examined whether timely access to complete clinical information through a shared inpatient-outpatient electronic health record (EHR) was associated with changes in rates of in-person follow-up visits after hospital discharge in patients with diabetes.

Using the shared inpatient-outpatient EHR was associated with a shift toward 7-day follow-up delivered through a combination of telemedicine (telephone and patient-physician secure messages) and outpatient laboratory tests, without a traditional office visit.

Patient outcomes, as measured by 30-day return emergency department visits or hospital readmission, were comparable when using the shared EHR.

Timely availability of clinical information during health care transitions, in a setting with robust telemedicine access, can shift the method of care delivery without adversely affecting patient health outcomes.

For the growing number of patients with chronic conditions, care transitions, such as those after hospital discharge, require coordination among multiple clinicians practicing in different settings.

 Health information exchange (HIE) that ensures that patient health information follows each patient as they move between care settings is important to providing well-coordinated care.

 Still, developing widespread electronic health record (EHR) interoperability and HIE between settings remains challenging.

 Emerging health care payment models, coordination, and consolidation efforts are likely increasing information sharing among providers at follow-up visits.

 Still, there is limited evidence on the impact of sharing electronic patient information across settings on patient care transitions and outcomes, particularly on follow-up care and adverse events after a hospitalization.

With limited electronic data sharing, deficiencies in information availability and communication among providers after hospital discharge are regularly reported by both clinicians and patients—including inconsistent awareness of the hospitalization itself and limited communication of medications, orders, and laboratory results, leading to medical errors and increases in readmission.

 In the absence of broad clinical guidelines for optimal postdischarge follow-up interval or encounter type, differences in follow-up visit rates have been associated with mixed outcomes.

 Shared seamless access to EHRs can offer clinicians direct access to fully view and document detailed patient clinical information across health care settings without requiring shifts across systems, modalities (like paper), or capabilities (like limited snapshots or fragmented documentation).

 The timely exchange of patient information and communication is defined for this paper as data access to support clinical care at any time it is clinically needed, ideally in real time. Timely and seamless EHR access across providers can support patient transitions from hospital discharge to outpatient follow-up care, such as by facilitating coordination, risk stratification, and flexibility for telemedicine encounter types, with potential implications for clinical care quality and efficiency.

 Early evidence from other settings and patient populations about impacts of HIE is mixed; however, findings of some studies have suggested that electronic health information availability and exchange are associated with reductions in repeat tests or imaging, supporting the feasibility of telemedicine follow-up.

Building on previous findings of improved diabetes care and health outcomes after implementation of an outpatient-only EHR, we studied the subsequent implementation of a shared inpatient EHR that seamlessly integrates patient health information between hospital and outpatient providers.

 In patients with diabetes, this study examined the association between provider use of the shared inpatient-outpatient EHR and rates and types of outpatient follow-up, including office visits, telemedicine encounters (including asynchronous secure patient-physician messages and real-time telephone visits), and laboratory tests. We also examined the impact on adverse clinical events after hospital discharge, measured by emergency department (ED) visits and hospital readmissions.

This quasi-experimental study examined a historical natural experiment in which an integrated delivery system staggered implementation of an inpatient EHR, integrating it with an existing outpatient EHR, across 17 hospitalist-staffed hospitals (2006-2010). This created a stepped-wedge study design to study the impact of shared inpatient-outpatient EHR use (

). The implementation order was not associated with medical centers’ health care quality or readmission rates.

Prior to the study period, the outpatient EHR used by clinicians had already integrated all outpatient records, including primary and specialty care, laboratories, and pharmacy, but did not include complete clinical information from hospitalizations or ED visits. At baseline, providers also already had the capability to conduct scheduled real-time telephone telemedicine visits with patients and had access to a patient portal website that offered patient-provider asynchronous secure messaging tools. As such, our study examines a shift in provider-to-provider access to patient data across settings after implementation of the shared inpatient-outpatient EHR.

The commercially available complete hospital EHR replaced the inpatient paper medical record and a patchwork of optional health information technology tools, creating a shared inpatient-outpatient EHR. Before implementing the inpatient EHR, HIE between inpatient and outpatient providers was not consistent and was provider dependent. After the inpatient EHR was implemented, both inpatient and outpatient EHRs were seamlessly integrated. The hospital EHR automatically integrates patient history and clinical information (eg, clinical notes, procedures, imaging, laboratory tests, medications) with the outpatient EHR used by primary care providers and specialists, including order-entry capability for outpatient follow-up, medication reconciliation before discharge, secure messaging between providers and with patients, and notifications to outpatient providers that their patient had been hospitalized.

Between 2005 and 2011, we identified all hospitalizations among patients with diabetes (using the clinical diabetes registry) in medical centers where the outpatient EHR was already in use. We examined patients with diabetes as an example of the impact of shared EHR use in a common chronic condition that has associated complications. We excluded from our study analytic data set patients who were not health plan members in the year prior to the hospitalization and for 30 days after discharge in order to ensure complete capture of comorbidities and follow-up outcomes. We also excluded hospitalizations of patients who were not discharged home in order to ensure eligibility for outpatient follow-up.

Our data captured all outpatient office visits, telephone visits, secure electronic messages, and laboratory tests after hospital discharge. In the absence of broad evidence-based guidelines for any optimal postdischarge follow-up timing, we examined the encounters within 7 and 30 days after hospital discharge.

 We also examined any 30-day clinical events as a measure of adverse health events or outcomes, including ED visits or readmissions, based on the 30-day Medicare readmission measures.

Among hospitalizations with follow-up, we examined the rates of follow-up through a combination of only telemedicine and laboratory tests.

We used multivariate logistic regression models for each type of follow-up encounter outcome with EHR status as the main predictor and adjustment for patient characteristics (age, gender, neighborhood socioeconomic status [SES], race/ethnicity, co-payment, comorbidity score), seasonality (calendar month, categorical variable), time trend (year 1 for 2005, year 2 for 2006, and so on, as a continuous variable), quadratic term of the time trend, comorbidity score (centered), interaction term of comorbidity score and time trend, medical center, and medical center–specific time trend (interaction term of medical center with time trend and quadratic term of time trend), with standard errors corrected for patient clustering (using Stata SE 10.1 [StataCorp LP]). We defined a patient as having a low SES neighborhood using 2000 US census block groups with 20% of residents having household incomes below the federal poverty level or 25% of residents 25 years or older having less than a high school education.

 To adjust for comorbidity, we used the prospective diagnostic cost group score, which has been adopted by CMS for Medicare risk adjustment.

We reported adjusted odds ratios from these multivariate models. For easier interpretation, we also calculated the adjusted rates of each outcome by applying the coefficients from the logistic regression to the entire cohort as if everyone were in pre–inpatient EHR and post–inpatient EHR periods, respectively, so that patients in pre–inpatient EHR and post–inpatient EHR periods shared the exact same characteristics (margins command in Stata).

In sensitivity analyses, we examined the subset of hospitalizations categorized as nonelective and findings were comparable (see 

Among all 241,510 hospitalizations in 104,126 patients with diabetes from 2005 to 2011, 91,331 occurred before the shared inpatient EHR was implemented and 150,179 occurred after. 

After multivariate adjustment, the rate of any type of ambulatory follow-up encounter within 7 days of hospital discharge decreased from 72.8% to 69.2% after use of the shared EHR (

) and more modestly within 30 days after discharge, from 94.8% to 94.1% after use of the shared EHR (

 < .05). These patterns in care changes associated with shared EHR use were consistent when examining within the 30-day period after hospital discharge (eAppendix).

The type of follow-up care also changed after the shared EHR implementation. The proportion of 7-day follow-up delivered by a combination of telemedicine and laboratory tests and without an in-person office visit increased from 22.9% before use of the shared EHR to 27.0% after (

). Specifically, follow-up with an in-person office visit within 7 days dropped from 55.9% to 50.5% (

 < .05), and use of any laboratory testing within 7 days after discharge dropped from 32.0% to 30.7% (

 < .05). No statistically significant changes occurred in the rates of telephone visits or secure messages (

As a measure of adverse health events or outcomes, there were no statistically significant differences in the rates of ED visits or readmission in the 30 days after hospital discharge associated with use of the integrated hospital EHR. After the integrated EHR was in use, 16.7% of hospital discharges were followed by an ED visit (vs 16.4% before; 

 > .05) and 9.4% were followed by another hospitalization within 30 days (vs 9.5% before; 

In this natural experiment involving the staggered implementation of a commercially available inpatient-outpatient shared EHR that shares patient data across providers in inpatient and ambulatory settings, we found that after hospital discharge, patients with diabetes had a higher likelihood of receiving follow-up care delivered only by a combination of telemedicine (telephone visits and asynchronous secure messages) and laboratory monitoring without a traditional in-person visit. We found slightly lower overall rates of follow-up office visits and outpatient laboratory tests. As a measure of clinical events, we found no statistically significant association between inpatient-outpatient EHR use and rates of return ED visits or hospital readmissions. Together, these findings suggest that the timely availability of complete clinical information from using a shared inpatient-outpatient EHR after a hospital discharge in a setting with strong telemedicine access could shift the method of delivering follow-up care without adversely affecting patient health outcomes as measured by repeat ED visits or readmissions.

Although EHR interoperability and HIE functionality have been consistently promoted as policy priorities for improving the quality and efficiency of the American health care system, there is still limited research evidence to inform policy makers about the effects of continuity in provider access to patient information.

 Our study builds this evidence as one of the largest rigorously designed studies to examine the impact of shared health information access across providers during patient transitions between health care settings. Our findings from patients with diabetes also complement findings of previous studies in the same integrated delivery system, in patients with diabetes and in general patient populations, in which both providers and patients reported that EHR use facilitated care coordination both by providing informational continuity among providers and by supporting direct communication between clinicians and medical staff through electronic messaging tools.

 In a general patient population, primary care providers reported enhanced access to timely and complete patient information and better agreement on treatment goals and roles and responsibilities after the inpatient EHR was in use.

The optimal amount and timing of outpatient follow-up care after hospital discharge are not clear.

 Although some studies have found that follow-up visits or telephone calls after hospital discharge were associated with better patient outcomes, others have found no effect or worse outcomes associated with more follow-up care, and the evidence continues to be mixed.

 In the absence of broad evidence-based clinical guidelines for the optimal type or level of after-discharge follow-up, our study aimed to examine whether use of a shared inpatient-outpatient EHR was associated with shifts in the type of follow-up care delivered after hospital discharge. Because we found that follow-up care was more likely to be delivered through only telemedicine and laboratory tests, without any evidence of adverse changes in downstream health events as measured by ED visits and rehospitalizations, these changes in follow-up care represent potential improvements in the efficiency of health care delivery without adversely affecting quality. Similarly, because the rate of outpatient laboratory tests in this study was lower after using the shared inpatient-outpatient EHR without measurable impact on ED visits or hospitalizations, it appears that EHR-enabled information availability may have decreased unnecessary testing. Our findings are consistent with early evidence from other settings and across patient populations, which have found that electronic health information availability and exchange are associated with reductions in repeat tests and imaging and improve the feasibility of telemedicine follow-up.

Seamless and timely electronic HIE is still limited across the US health care delivery system. Calls for increases in exchange capabilities at hospital discharge are growing, but few settings have measured the large-scale impact of EHR-based information integration across delivery settings.

 Our study finds that movement toward more seamless health information access, even within an already integrated system, can affect the efficiency of follow-up care after hospital discharge without adversely affecting quality. These shifts may also potentially improve patient convenience through telemedicine follow-up without requiring the transportation and cost of making an in-person visit to health care providers. Although patient convenience and access are typically considered primary benefits of telemedicine, our finding of EHR-supported efficient posthospitalization follow-up through telemedicine may also be relevant as current crisis-based social distancing to protect patients and providers from infectious disease spread is rapidly shifting many medical office visits to telemedicine.

Although our study found modest average decreases in in-person visits, cumulative impacts of this magnitude may be substantial if replicated broadly across large numbers of annual hospitalizations in patient populations with chronic conditions. In addition, our finding of no statistically significant differences in clinical events can be interpreted as reassuring that negative impacts of care shifts were not detected. Further research is needed to explore patient follow-up care preferences and the clinical impacts of variations in follow-up care types in more detail.

There are several limitations to the interpretation and generalizability of our study design and setting. First, the natural experiment of shared inpatient-outpatient EHR implementation in this study is historical and may not fully generalize to current practice, which may vary across settings. Because the sharing of patient data across health care settings is still currently evolving, however, the study findings have potential relevance despite the historical study period. Further, the study relevance is supported by examining a study setting with relatively mature telemedicine and a patient portal in which patients could access a portal website to schedule a telemedicine visit to communicate with physicians and to review visit details and laboratory results. The follow-up care patterns we identified would not be feasible without the ability to follow up with patients readily by phone or through secure messages. In other settings, in-person follow-up office visits may be needed to share paper discharge summaries or to notify providers of a recent hospitalization.

 Also, the rates of follow-up care in our study at baseline were higher than previously reported in other settings, and the hospital readmission rates were somewhat lower; therefore, other settings with more limited follow-up patterns at baseline may experience different shifts with the availability of HIE across settings.

 Our study examined patterns in follow-up care after implementing a systemwide EHR system, and we are not able to characterize the clinical appropriateness of any specific follow-up care regimen. Further study of the clinical significance of changes in follow-up care encounter types is needed. This study examined only patients with diabetes, and we cannot generalize directly to other patient populations. Shared EHRs and HIE are only tools to increase information availability; their impact is dependent on the clinical workflow and delivery system context in which they are used.

Overall, in a setting that implemented a shared EHR with seamless HIE between inpatient and outpatient providers, patient follow-up care after hospital discharge was less likely to include an in-person office visit and instead was managed through exchange of asynchronous secure messages, telephone telemedicine, and outpatient laboratory tests. We found no statistically significant change in the rate of return ED visits or readmissions within 30 days after discharge, and we conclude that increased and timely information availability through the shared inpatient-outpatient EHR changed the pattern of follow-up care after discharge, enabling care delivery through non–office visit encounters without adversely affecting patient short-term outcomes.


 Kaiser Permanente Division of Research (MR, JHu, DB, RN, BF), Oakland, CA; Department of Epidemiology and Biostatistics, University of California at San Francisco (RB), San Francisco, CA; Department of Health Policy and Management, Emory University (IG), Atlanta, GA; Kaiser Permanente San Francisco Medical Center (MGJ), South San Francisco, CA; Kaiser Permanente San Rafael Medical Center (DB), San Rafael, CA; Mongan Institute for Health Policy, Massachusetts General Hospital (JHs), Boston, MA; Department of Health Care Policy, Harvard Medical School (JHs), Boston, MA.

 National Institute of Diabetes and Digestive and Kidney Diseases (R01DK085070). The study sponsor had no role in the design and conduct of the study, including the collection, analysis, and interpretation of data and the writing of the article and the decision to submit it for publication.

 Dr Hsu serves as a consultant for Cambridge Health Alliance, Columbia University, Community Servings, Delta Health Alliance, Robert Wood Johnson Foundation, and University of Southern California. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

 Concept and design (MR, JHu, RB, IG, MGJ, BF, JHs); acquisition of data (MR, JHu); analysis and interpretation of data (MR, JHu, RB, IG, MGJ, DB, RN, BF, JHs); drafting of the manuscript (MR, JHu, DB); critical revision of the manuscript for important intellectual content (MR, JHu, RB, IG, MGJ, DB, RN, BF, JHs); statistical analysis (JHu, RB, RN); obtaining funding (MR); administrative, technical, or logistic support (MR); and supervision (MR).

 Mary Reed, DrPH, Kaiser Permanente Division of Research, 2000 Broadway, Oakland, CA 94612. Email: Mary.E.Reed@kp.org.

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Articles

Using a seamlessly shared inpatient-outpatient electronic health record was associated with greater rates of postdischarge follow-up delivered through telemedicine or laboratory monitoring and without an in-person office visit.

Inpatient-Outpatient Shared Electronic Health Records: Telemedicine and Laboratory Follow-up After Hospital Discharge

Some patients lack regular computer access and experience a digital divide that causes them to miss internet-based health innovations. The diffusion of smartphones has increased internet access across the socioeconomic spectrum, and increasing the channels through which patients can access their personal health records (PHRs) could help bridge the divide in PHR use. We examined PHR use through a computer-based Web browser or mobile device.

Cross-sectional historical cohort analysis.

 Among adult patients in the diabetes registry of an integrated healthcare delivery system, we studied the devices used to access their PHR during 2016.

 Among 267,208 patients with diabetes, 68.1% used the PHR in 2016; 60.6% of all log-ins were via computer and 39.4% were via mobile device. Overall, 63.9% used it from both a computer and mobile device, 29.6% used only a computer, and 6.5% used only a mobile device. After adjustment, patients who were black, Hispanic, or Asian; lived in lower socioeconomic status (SES) neighborhoods; or had lower engagement were all significantly more likely to use the PHR only from a mobile device (

 <.05). Patients using the PHR only via mobile device used it less frequently.

 Mobile-ready PHRs may increase access among patients facing a digital divide in computer use, disproportionately reaching racial/ethnic minorities and lower SES patients. Nonetheless, even with a mobile-optimized and app-accessible PHR, differences in PHR use by race/ethnicity and SES remain. Continued efforts are needed to increase equitable access to PHRs among patients with chronic conditions.

In an integrated delivery system, mobile access to personal health records (PHRs) may increase their use among patients with limited computer access, but differences in PHR use by race/ethnicity and neighborhood socioeconomic status (SES) remain. 

Seventy percent of PHR users accessed it with a mobile device at least once in 2016, with nearly 40% of all log-ins done using a mobile device. 

Patients who were black, Hispanic, or Asian or who lived in lower SES neighborhoods were significantly more likely to use the PHR exclusively via a mobile device. Still, these groups of patients were less likely to use the PHR at all in 2016.

Although more than 200,000 health-promoting mobile apps are available for patient download, with 1.7 billion users worldwide, research is needed to identify the clinical usefulness of mobile tools in self-management and care quality for patients.

 Importantly, the majority of these apps lack any integration with patients’ ongoing healthcare services and providers.

 Apps that are integrated with a clinical electronic health record (EHR) and that make patient-reported data available to clinicians may hold the most promise to improve well-coordinated, high-quality healthcare delivery. Within healthcare, this timely expansion to mobile-connected devices complements the growing availability of personal health records (PHRs). PHRs could be particularly relevant for patients with chronic conditions, such as diabetes, who require ongoing self-management that can be facilitated via PHRs.

However, the long-standing digital divide, defined as the gulf between individuals with and without ready access to the internet, is well documented.

 EHR requirements from CMS (Stage 3 Meaningful Use objectives) include that physicians provide patients with electronic access to their health records and tailored patient education via a Web-based tethered PHR that is linked to the patient’s EHR, also known as a patient portal.

 Although Meaningful Use financial incentives continue to promote the widespread adoption of PHRs among eligible providers, they do not require that PHRs be easily accessible via mobile devices.

 Therefore, with only computer-based access, many patients might be left out.

Previous research shows that use of computer-based PHRs has been consistently lower among racial and ethnic minorities and patients with lower education and health literacy levels.

 Recently, the diffusion of smartphone technology has increased mobile access to the internet and apps among individuals most likely to be affected by the digital divide, including racial/ethnic minorities and those with lower socioeconomic status (SES).

 Mobile-accessible PHRs can help engage patients in managing their health through convenient and timely access to personal health data, provider messaging, refilling prescriptions, or scheduling appointments.

 With many healthcare innovations, specifically advancements in PHRs, changes have favored those who have social advantages, such as higher education, greater income or wealth, more knowledge of how to navigate the healthcare system, and nonminority race/ethnicity. In this manuscript, we focus specifically on a different type of technological innovation: the introduction of PHRs that are more easily accessible using mobile devices.

Diabetes is more prevalent among individuals of lower SES and racial/ethnic minorities.

 Patients with diabetes often have other chronic conditions with complex clinical needs that require ongoing self-management.

 Diabetes self-management is crucial and requires extensive self-monitoring, adherence to medications, proper diet, and adequate exercise.

 Any practical realization of a model for coordinated safe care must rely on timely availability and use of comprehensive electronic clinical information that is not only available to providers through an EHR, but also to patients through a PHR.

 Previous studies have found that PHR use was associated with improved diabetes quality measures.

 Thus, mobile-accessible PHRs could be particularly relevant for patients with diabetes. Yet, in the absence of mobile-accessible PHRs, we found that lack of computer access accounted for most of the variation in PHR use by race and income.

 Consequently, we expect that mobile access to PHRs may facilitate PHR use among individuals who are mobile dependent. Little is known about the use of PHRs that are easily accessible and optimized for use via mobile devices. 

Within an integrated delivery system that provided all members with multiple channels to access their PHR, we examined the channel through which an adult population of patients with diabetes used their PHR (ie, through a computer-based Web browser, smartphone-accessible website, or mobile apps). We also assessed the association between patient characteristics and PHR use via mobile device.

Kaiser Permanente Northern California is an integrated delivery system that provides comprehensive care, including inpatient, outpatient, and pharmacy services, to more than 3 million members via employer-sponsored, individual, or publicly sponsored insurance. Members who register to use the password-protected patient PHR can access it free of charge via computer browser, mobile-optimized website, or mobile app. The computer-based Web portal has been available to members for more than 10 years, and the mobile-optimized website and Android or iOS apps have been available to members since 2013. The PHR offers patients a number of services, including the ability to exchange secure messages with providers on their healthcare team, view lab results, request medication refills, view portions of their health records, schedule office visits, and pay bills. The mobile-accessible and computer browser versions of the PHR offer comparable functions, although features changed slightly over time.

Our study population included all adult (≥18 years) members of an integrated delivery system, Kaiser Permanente Northern California, who were in the health plan diabetes clinical registry as of the last quarter of 2015. We chose to focus on patients with diabetes in order to examine patients with a chronic condition who would likely have ongoing need for healthcare services and self-management functions available in PHRs. This analysis was part of a larger study focused on how patients with diabetes use technology to manage their care. We included all patients who maintained continuous health plan coverage in 2016. Because our study focused on patient characteristics, we excluded PHR use via designated proxies. 

We used automated datasets to capture PHR use by channel (mobile app, mobile website, or computer browser) in 2016 among the full study population. To calculate PHR use counts, we identified use episodes by counting the number of days during the year with any PHR use (eg, multiple log-ins in 1 day counted as a single episode). In addition, we measured if patients used 3 key PHR functions (order prescription refill, send secure message, or view lab result) at any time in 2016. We also used EHR data to capture patient characteristics (age, gender, race/ethnicity) and linked patients’ residential addresses to 2010 US Census measures of education and income to define neighborhood SES at the Census block group level. Census block groups are defined as neighborhoods of lower SES if at least 20% of residents have household incomes below the federal poverty level or at least 25% of residents 25 years or older have less than a high school education.

 We also identified patients’ additional chronic conditions, other than diabetes, during the last quarter of 2015 using the health plan’s clinical chronic condition registries for asthma, coronary artery disease, heart failure, and hypertension. As an indicator of patient engagement in 2015, we used clinical quality registries to create an overall measure of patients’ histories of adherence to chronic condition medications (with 80% or more days covered by medications) and to preventive care recommendations (up-to-date flu shot, blood pressure measure, low-density lipoprotein [LDL] cholesterol measure, and glycated hemoglobin [A1C] measure for those with diabetes). We categorized patients as being highly engaged in their care if they were adherent to their chronic condition oral medications for diabetes, hypertension, or cholesterol (≥80% of days covered) and recommended preventive care services (flu vaccine and A1C, LDL cholesterol, and blood pressure screening) in 2015.

We studied patient characteristics associated with the channel(s) used to access the PHR during 2016 (computer and mobile, computer only, and mobile only). We used multivariable logistic regression to measure the association between PHR use (any use in 2016 vs no use) and patient characteristics, as well as multinomial logistic regression to measure the association between device used (mobile only, computer only, or mobile and computer) among PHR users and patient characteristics (age, gender, race/ethnicity, neighborhood SES, number of chronic conditions, and health engagement). For both models, we calculated the adjusted percentage of patients using the PHR and device type by patient characteristics, assuming patients in the subgroup had the same other characteristics as the full study population (margins command in Stata). We included the main effects of each covariate and first order interaction of all covariates (except for age group and number of other chronic conditions due to an empty cell problem). All analyses were conducted using Stata 14 (StataCorp LP; College Station, Texas).

The Kaiser Foundation Research Institute Institutional Review Board reviewed and approved the study protocol.

 shows characteristics of the 267,208 patients with diabetes included in the study and their adjusted rates of PHR use in 2016. In that year, 49.1% were 65 years or older, 47.7% were female, 43.7% were white, 22.6% were Asian, 21.6% were Hispanic, 10.2% were black, 24.0% lived in low SES neighborhoods, and 75.1% had multiple chronic conditions. Nearly one-third of all study patients (31.9%) did not use the PHR in 2016. More than half (58.0%) of patients were categorized as highly engaged, meaning that they were adherent to their oral medications for chronic conditions and received the flu vaccine and recommended screenings for A1C, LDL cholesterol, and blood pressure in 2015. 

During 2016, 181,981 patients (68.1% of the total number) accessed their PHR 8.9 million times: 60.6% of log-ins were via a computer, 19.9% via mobile device browser, and 19.5% via smartphone apps. Of all PHR users, 6.5% used it only with a mobile device, 29.6% only with a computer, and 63.9% used both a computer and mobile device (

). Patients who accessed the PHR only via a mobile device used it less frequently (median of 11 days with PHR use) than those using only a computer (15 days) or both a computer and mobile device (30 days). Most PHR users used it to view lab results (81.0%), send a secure message (75.8%), and order a prescription refill (66.0%). For the 3 key functions, use was highest among patients who accessed the PHR via both a computer and mobile device and lowest among those who used only a mobile device (

Adjusted percentages of patients who used the PHR, calculated using results from the multivariable logistic regressions, are shown in Table 1. After adjustment, a larger percentage of patients who were younger (84.7% for ages 18-29 years), white (78.4%), living in higher SES neighborhoods (71.1%), and highly engaged (71.0%) used the PHR in 2016 compared with those who were older (60.9% for ≥65 years), black (57.8%), Hispanic (54.3%), Asian (67.7%), living in lower SES neighborhoods (59.5%), and not highly engaged in their care (64.2%) (all 

 shows the adjusted percentages of PHR users who accessed their PHR only from a mobile device by patient characteristics. After adjustment, a higher percentage of patients who were black (8.8%), Hispanic (9.6%), Asian (6.7%), living in lower SES neighborhoods (7.9%), younger (11.9% for ages 18-30 years), or not highly engaged in their health (7.2%) used the PHR only via a mobile device in 2016 relative to those who were white (4.7%), from higher SES neighborhoods (6.0%), older (4.3% for ≥65 years), or highly engaged (5.8%) (all 

In 2015, a Pew survey found that 64% of US adults owned a smartphone and 19% relied exclusively on smartphones for internet access.

 In our study of use of a mobile-accessible PHR among patients with diabetes, most users (70%) accessed their PHR with a mobile device at least once and nearly 40% of all PHR log-ins were done via a mobile device. Among PHR users, nearly 7% accessed the PHR exclusively via a mobile device. These users accessed the PHR less frequently than those who used computers. In addition, nearly one-third of patients did not use the PHR at all in 2016. Patients who were black, Hispanic, or Asian; who lived in lower SES neighborhoods; or who had lower engagement in their care were significantly more likely to access the PHR exclusively using a mobile device in 2016, which is consistent with findings from other reports of mobile-dependent individuals.

 It is possible that many of the patients who accessed the PHR only by mobile device were dependent on that device for internet access and would not have had convenient computer access to use the PHR if a mobile option had not been available. 

In our previous analysis conducted in 2010, before the PHR was mobile-accessible, we found that computer internet access explained most of the variation in use of secure messaging via the PHR by race/ethnicity and income.

 Thus, the current finding that mobile access is disproportionately reaching members living in lower SES neighborhoods and racial/ethnic minorities is encouraging and suggests that mobile PHR access may, in fact, be helping to bridge the digital divide by reducing disparities in PHR use. 

Of note, we found that patients with diabetes who were not considered to be highly engaged in their health (ie, not previously adherent to chronic condition medications and recommended preventive care services) were significantly more likely to use the PHR exclusively via a mobile device. For patients coping with diabetes and other chronic conditions, which require substantial self-management practices, health engagement is critical to maintaining their health.

 Recent studies of PHR use among patients with diabetes found that it is associated with improved self-management practices and glycemic control.

 Mobile PHR use could be an important gateway for potentially reaching those patients who previously had limited engagement with preventive care and medication adherence. 

The federal government has invested more than $30 billion to promote the widespread adoption of EHRs and tethered PHRs as a way to improve access and quality of care.

 However, these financial incentives do not require that PHRs be easily accessible via mobile devices. In fact, eligible providers caring for patients in regions with low broadband internet access are exempted from Meaningful Use objectives related to PHRs.

 Although it is possible for patients with smartphones to access any available computer-based PHR using their mobile devices, websites that are not optimized for mobile use can be exceedingly difficult to navigate using the relatively small-sized smartphone screens. To the extent that PHR use can improve chronic care management and clinical outcomes,

Racial/ethnic minorities and patients living in poorer neighborhoods were more likely to access their personal health record exclusively with a mobile device.

Jie Huang, PhD

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