Reducing perceived barriers to scaling up overdose education and naloxone distribution and medications for opioid use disorder in the United States in the HEALing (Helping End Addiction Long-Term®) communities study.

BACKGROUND: Scaling up overdose education and naloxone distribution (OEND) and medications for opioid use disorder (MOUD) is needed to reduce opioid overdose deaths, but barriers are pervasive. This study examines whether the Communities That HEAL (CTH) intervention reduced perceived barriers to expanding OEND and MOUD in healthcare/behavioral health, criminal-legal, and other/non-traditional venues. METHODS: The HEALing (Helping End Addiction Long-Term®) Communities Study is a parallel, wait-list, cluster randomized trial testing the CTH intervention in 67 communities in the United States. Surveys administered to coalition members and key stakeholders measured the magnitude of perceived barriers to scaling up OEND and MOUD in November 2019-January 2020, May-June 2021, and May-June 2022. Multilevel linear mixed models compared Wave 1 (intervention) and Wave 2 (wait-list control) respondents. Interactions by rural/urban status and research site were tested. RESULTS: Wave 1 respondents reported significantly greater reductions in mean scores for three outcomes: perceived barriers to scaling up OEND in Healthcare/Behavioral Health Venues (-0.26, 95% confidence interval, CI: -0.48, -0.05, p = 0.015), OEND in Other/Non-traditional Venues (-0.53, 95% CI: - 0.84, -0.22, p = 0.001) and MOUD in Other/Non-traditional Venues (-0.34, 95% CI: -0.62, -0.05, p = 0.020). There were significant interactions by research site for perceived barriers to scaling up OEND and MOUD in Criminal-Legal Venues. There were no significant interactions by rural/urban status. DISCUSSION: The CTH Intervention reduced perceived barriers to scaling up OEND and MOUD in certain venues, with no difference in effectiveness between rural and urban communities. More research is needed to understand facilitators and barriers in different venues.

Implications for Electronic Surveys in Inpatient Settings Based on Patient Survey Response Patterns: Cross-Sectional Study.

BACKGROUND: Surveys of hospitalized patients are important for research and learning about unobservable medical issues (eg, mental health, quality of life, and symptoms), but there has been little work examining survey data quality in this population whose capacity to respond to survey items may differ from the general population. OBJECTIVE: The aim of this study is to determine what factors drive response rates, survey drop-offs, and missing data in surveys of hospitalized patients. METHODS: Cross-sectional surveys were distributed on an inpatient tablet to patients in a large, midwestern US hospital. Three versions were tested: 1 with 174 items and 2 with 111 items; one 111-item version had missing item reminders that prompted participants when they did not answer items. Response rate, drop-off rate (abandoning survey before completion), and item missingness (skipping items) were examined to investigate data quality. Chi-square tests, Kaplan-Meyer survival curves, and distribution charts were used to compare data quality among survey versions. Response duration was computed for each version. RESULTS: Overall, 2981 patients responded. Response rate did not differ between the 174- and 111-item versions (81.7% vs 83%, P=.53). Drop-off was significantly reduced when the survey was shortened (65.7% vs 20.2% of participants dropped off, P<.001). Approximately one-quarter of participants dropped off by item 120, with over half dropping off by item 158. The percentage of participants with missing data decreased substantially when missing item reminders were added (77.2% vs 31.7% of participants, P<.001). The mean percentage of items with missing data was reduced in the shorter survey (40.7% vs 20.3% of items missing); with missing item reminders, the percentage of items with missing data was further reduced (20.3% vs 11.7% of items missing). Across versions, for the median participant, each item added 24.6 seconds to a survey's duration. CONCLUSIONS: Hospitalized patients may have a higher tolerance for longer surveys than the general population, but surveys given to hospitalized patients should have a maximum of 120 items to ensure high rates of completion. Missing item prompts should be used to reduce missing data. Future research should examine generalizability to nonhospitalized individuals.

Examining the Dimensionality of Trust in the Inpatient Setting: Exploratory and Confirmatory Factor Analysis.

BACKGROUND: Trust in healthcare providers is associated with important outcomes, but has primarily been assessed in the outpatient setting. It is largely unknown how hospitalized patients conceptualize trust in their providers. OBJECTIVE: To examine the dimensionality of a measure of trust in the inpatient setting. DESIGN: Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). PARTICIPANTS: Hospitalized patients (N = 1756; 76% response rate) across six hospitals in the midwestern USA. The sample was randomly split such that approximately one half was used in the EFA, and the other half in the CFA. MAIN MEASURES: The Trust in Physician Scale, adapted for inpatient care. KEY RESULTS: Based on the Kaiser-Guttman criterion and parallel analysis, EFAs were inconclusive, indicating that trust may be comprised of either one or two factors in this sample. In follow-up CFAs, a 2-factor model fit best based on a chi-squared difference test (Δχ2 = 151.48(1), p < .001) and a Comparative Fit Index (CFI) difference test (CFI difference = .03). The overall fit for the 2-factor CFA model was good (χ2 = 293.56, df = 43, p < .01; CFI = .95; RMSEA = .081 [90% confidence interval = .072-.090]; TLI = .93; SRMR = .04). Items loaded onto two factors related to cognitive (i.e., whether patients view providers as competent) and affective (i.e., whether patients view that providers care for them) dimensions of trust. CONCLUSIONS: While measures of trust in the outpatient setting have been validated as unidimensional, in the inpatient setting, trust appears to be composed of two factors: cognitive and affective trust. This provides initial evidence that inpatient providers may need to work to ensure patients see them as both competent and caring in order to gain their trust.

Co-establishing an infrastructure for routine data collection to address disparities in infant mortality: planning and implementation.

BACKGROUND: Efforts to address infant mortality disparities in Ohio have historically been adversely affected by the lack of consistent data collection and infrastructure across the community-based organizations performing front-line work with expectant mothers, and there is no established template for implementing such systems in the context of diverse technological capacities and varying data collection magnitude among participating organizations. METHODS: Taking into account both the needs and limitations of participating community-based organizations, we created a data collection infrastructure that was refined by feedback from sponsors and the organizations to serve as both a solution to their existing needs and a template for future efforts in other settings. RESULTS: By standardizing the collected data elements across participating organizations, integration on a scale large enough to detect changes in a rare outcome such as infant mortality was made possible. Datasets generated through the use of the established infrastructure were robust enough to be matched with other records, such as Medicaid and birth records, to allow more extensive analysis. CONCLUSION: While a consistent data collection infrastructure across multiple organizations does require buy-in at the organizational level, especially among participants with little to no existing data collection experience, an approach that relies on an understanding of existing barriers, iterative development, and feedback from sponsors and participants can lead to better coordination and sharing of information when addressing health concerns that individual organizations may struggle to quantify alone.

Examining Patients' Capacity to Use Patient Portals: Insights for Telehealth.

BACKGROUND: The increase in telehealth in response to the coronavirus disease 2019 pandemic highlights the need to understand patients' capacity to utilize this care modality. Patient portals are a tool whose use requires similar resources and skills as those required for telehealth. Patients' capacity to use patient portals may therefore provide insight regarding patients' readiness and capacity to use telehealth. OBJECTIVE: The aim of this study was to examine factors related to patients' capacity to use a patient portal and test the impact of these factors on patients' portal use. RESEARCH DESIGN AND SUBJECTS: Using data from a large-scale pragmatic randomized controlled trial of patient portal use, 1081 hospitalized patients responded to survey items that were then mapped onto the 4 dimensions of the Engagement Capacity Framework: self-efficacy, resources, willingness, and capabilities. MEASURES: The outcome variable was frequency of outpatient portal use. We evaluated associations between Engagement Capacity Framework dimensions and patient portal use, using regression analyses. RESULTS: Patients with fewer resources, fewer capabilities, lower willingness, and lower overall capacity to use patient portals used the portal less; in contrast, those with lower perceived self-efficacy used the portal more. CONCLUSIONS: Our findings highlight differences in patients' capacity to use patient portals, which provide an initial understanding of factors that may influence the use of telehealth and offer important guidance in efforts to support patients' telehealth use. Offering patients training tailored to the use of telehealth tools may be particularly beneficial.

Differential Effects of Outpatient Portal User Status on Inpatient Portal Use: Observational Study.

BACKGROUND: The decision to use patient portals can be influenced by multiple factors, including individuals' perceptions of the tool, which are based on both their personal skills and experiences. Prior experience with one type of portal may make individuals more comfortable with using newer portal technologies. Experienced outpatient portal users in particular may have confidence in their ability to use inpatient portals that have similar functionality. In practice, the use of both outpatient and inpatient portal technologies can provide patients with continuity of access to their health information across care settings, but the influence of one type of portal use on the use of other portals has not been studied. OBJECTIVE: This study aims to understand how patients' use of an inpatient portal is influenced by outpatient portal use. METHODS: This study included patients from an academic medical center who were provided access to an inpatient portal during their hospital stays between 2016 and 2018 (N=1571). We analyzed inpatient portal log files to investigate how inpatient portal use varied by using 3 categories of outpatient portal users: prior users, new users, and nonusers. RESULTS: Compared with prior users (695/1571, 44.24%) of an outpatient portal, new users (214/1571, 13.62%) had higher use of a select set of inpatient portal functions (messaging function: incidence rate ratio [IRR] 1.33, 95% CI 1.06-1.67; function that provides access to the outpatient portal through the inpatient portal: IRR 1.34, 95% CI 1.13-1.58). Nonusers (662/1571, 42.14%), compared with prior users, had lower overall inpatient portal use (all active functions: IRR 0.68, 95% CI 0.60-0.78) and lower use of specific functions, which included the function to review vitals and laboratory results (IRR 0.51, 95% CI 0.36-0.73) and the function to access the outpatient portal (IRR 0.53, 95% CI 0.45-0.62). In comparison with prior users, nonusers also had lower odds of being comprehensive users (defined as using 8 or more unique portal functions; odds ratio [OR] 0.57, 95% CI 0.45-0.73) or composite users (defined as comprehensive users who initiated a 75th or greater percentile of portal sessions) of the inpatient portal (OR 0.42, 95% CI 0.29-0.60). CONCLUSIONS: Patients' use of an inpatient portal during their hospital stay appeared to be influenced by a combination of factors, including prior outpatient portal use. For new users, hospitalization itself, a major event that can motivate behavioral changes, may have influenced portal use. In contrast, nonusers might have lower self-efficacy in their ability to use technology to manage their health, contributing to their lower portal use. Understanding the relationship between the use of outpatient and inpatient portals can help direct targeted implementation strategies that encourage individuals to use these tools to better manage their health across care settings.

Odds of Meeting Cancer Prevention Behavior Recommendations by Health Information Seeking Behavior: a Cross-Sectional HINTS Analysis.

People who seek health information frequently may be more likely to meet health behavior goals; however, people use many different information sources. The purpose of this paper is to assess how different sources of health information influence likelihood of meeting cancer prevention behavior guidelines. Logistic regression of cross-sectional data from 6 years of the Health Information National Trends Survey (HINTS) was conducted. Independent variables included first source of health information, gender, age, race, education level, income, cancer history, general health, and data year; dependent variables were fruit and vegetable intake, exercise, smoking, mammography, Pap test, and colon cancer screening. Those who seek health information from doctors, the internet, or publications had higher odds of meeting more cancer prevention guidelines than those who do not seek health information. Those who used healthcare providers as an initial information source had higher odds of meeting diet, cervical, and colon cancer screening recommendations, while using the internet as an initial source of health information was associated with higher odds of meeting diet, smoking, and colon cancer screening recommendations. No health information source was associated with meeting either exercise or mammography recommendations. People should be encouraged to seek health information to help them meet their behavior goals, especially from sources that are more likely to be accurate and encourage cancer prevention behavior. Future research is needed to understand the accuracy of health information and what kinds of health information have positive influences on cancer prevention behavior.

Metrics for Outpatient Portal Use Based on Log File Analysis: Algorithm Development.

BACKGROUND: Web-based outpatient portals help patients engage in the management of their health by allowing them to access their medical information, schedule appointments, track their medications, and communicate with their physicians and care team members. Initial studies have shown that portal adoption positively affects health outcomes; however, early studies typically relied on survey data. Using data from health portal applications, we conducted systematic assessments of patients' use of an outpatient portal to examine how patients engage with the tool. OBJECTIVE: This study aimed to document the functionality of an outpatient portal in the context of outpatient care by mining portal usage data and to provide insights into how patients use this tool. METHODS: Using audit log files from the outpatient portal associated with the electronic health record system implemented at a large multihospital academic medical center, we investigated the behavioral traces of a study population of 2607 patients who used the portal between July 2015 and February 2019. Patient portal use was defined as having an active account and having accessed any portal function more than once during the study time frame. RESULTS: Through our analysis of audit log file data of the number and type of user interactions, we developed a taxonomy of functions and actions and computed analytic metrics, including frequency and comprehensiveness of use. We additionally documented the computational steps required to diagnose artifactual data and arrive at valid usage metrics. Of the 2607 patients in our sample, 2511 were active users of the patients portal where the median number of sessions was 94 (IQR 207). Function use was comprehensive at the patient level, while each session was instead limited to the use of one specific function. Only 17.45% (78,787/451,762) of the sessions were linked to activities involving more than one portal function. CONCLUSIONS: In discussing the full methodological choices made in our analysis, we hope to promote the replicability of our study at other institutions and contribute to the establishment of best practices that can facilitate the adoption of behavioral metrics that enable the measurement of patient engagement based on the outpatient portal use.

Exploring the Digital Divide: Age and Race Disparities in Use of an Inpatient Portal.

Background: Age and race disparities in the use of new technologies-the digital divide-may be limiting the potential of patient-facing health information technology to improve health and health care. Objective: To investigate whether disparities exist in the use of patient portals designed specifically for the inpatient environment. Methods: Patients admitted to the six hospitals affiliated with a large, Midwestern academic medical center from July 2017 to July 2018 were provided with access to a tablet equipped with an inpatient portal and recruited to participate in the study (n = 842). Demographic characteristics of study enrollees were obtained from patients' electronic health records and surveys given to patients during their hospital stay. Log files from the inpatient portal were used to create a global measure of use and calculate use rates for specific portal features.Results: We found both age and race disparities in use of the inpatient portal. Patients aged 60-69 (45.3% difference, p < 0.001) and those over age 70 (36.7% difference, p = 0.04) used the inpatient portal less than patients aged 18-29. In addition, African American patients used the portal less than White patients (40.4% difference, p = 0.004).Discussion: These findings suggest that the availability of the technology alone may be insufficient to overcome barriers to use and that additional intervention may be needed to close the digital divide. Conclusions: We identified lower use of the inpatient portal among African American and older patients, relative to White and younger patients, respectively.

Helping Patients Be Better Patients: A Qualitative Study of Perceptions About Inpatient Portal Use.

Introduction: As more hospitals introduce inpatient portals, it is increasingly important to understand their impact on patient experience and the care process. We conducted this study to learn from patients and care team members about their experience with an inpatient portal. Methods: We interviewed 120 patients and 433 care team members across a seven-hospital academic medical center that offers an inpatient portal to hospitalized patients. Interviewees were asked about their use of the inpatient portal and its impact on patient experience. Recorded interviews were transcribed and rigorously analyzed using both inductive and deductive methods. Results: We found that the inpatient portal was perceived to help patients be "better patients" by improving their ability to be informed about their health and by enabling them to be more involved in the care process. Care team members suggested portal use could be improved by addressing challenges with tablet administration, use of the patient education feature, and the functionality of the scheduling feature. Conclusions: Across interviewees, we found that inpatient portals were perceived to improve the hospital experience and increase empowerment for patients by offering information about care in a manner that allowed patients to join their care teams as active, participating members.

Improving Acceptance of Inpatient Portals: Patients' and Care Team Members' Perspectives.

Background: Inpatient portals are gaining interest as a means to increase patient-centered care during hospitalization. However, acceptance of a new technology such as the inpatient portal relies on perceptions of both its usefulness and ease of use. These factors have not been studied in the context of inpatient portal implementation. Methods: We interviewed patients (n = 123) and care team members (n = 447) about their experiences using an inpatient portal that had been implemented across a large, academic medical center. Interviews lasted 5-15 min, were audio-recorded, transcribed verbatim, and then analyzed using a combination of deductive and inductive methods. Results: Collectively, interviewees reported that the inpatient portal was a useful tool as it improved patients' access to information, enhanced communication, facilitated education, and appeared to promote patients' sense of control while in the hospital. Most interviewees also found the technology easy to use. However, there were concerns that the portal was not easy to use for those less experienced with technology. Interviewees identified the need to emphasize the value of the technology to both patients and care team members and the need to provide additional training to support portal use, as ways to promote acceptance of the tool. Discussion and Conclusions: Inpatient portals can improve patient-centered care, but such improvements require acceptance of the tool by both patients and care team members. Our findings about the usefulness and ease of use of an inpatient portal can inform future efforts to improve the implementation and acceptance of this new technology.

Likelihood of Smoking Among Cancer Survivors: An Updated Health Information National Trends Survey Analysis.

INTRODUCTION: Cancer survivors are at high risk for cancer reoccurrence, highlighting the importance of managing behavioral risk factors for cancer. Despite this risk, many cancer survivors continue to smoke cigarettes. This article describes the relationship between smoking behavior and demographic and clinical factors in cancer survivors. METHODS: Multinomial logistic regression of cross-sectional data from the Health Information National Trends Survey was conducted using combined data from years 2003, 2005, 2007, 2011, 2012, 2013, and 2014. Independent variables included age, cancer history, race, education level, marital status, insurance status, and data year; the dependent variable was smoking status (current vs. former or never). RESULTS: Cancer survivors were less likely to be current smokers but more likely to be former smokers than those with no history of cancer. Cancer survivors that currently smoked were more likely to have lower education levels, be divorced, separated, or single, or not have health insurance. Older cancer survivors, Hispanic, and non-Hispanic black survivors were less likely to smoke. Among cancer subgroups, prostate cancer survivors had the lowest rate (8.8%) of current smoking from 2011 to 2014, and cervical cancer survivors had the highest rate (31.1%). CONCLUSIONS: Although those with no history of cancer had higher rates of current smoking, many subgroups of cancer survivors continued to smoke at higher rates than average cancer survivors. Cancer survivors that were younger, had lower education levels, were any marital status other than married or widowed, were uninsured, or survived cervical cancer were more likely to be smokers than other survivors. IMPLICATIONS: It is important to understand which types of cancer survivors are at high risk of continued smoking to better inform tobacco dependence treatment interventions among those at high risk of cancer reoccurrence. Our findings suggest targeted tobacco dependence treatment efforts among cancer survivors should focus on survivors of cervical cancer and survivors that are young, unmarried, uninsured, or have lower education levels.

Patients' Perceptions of Portal Use Across Care Settings: Qualitative Study.

BACKGROUND: Patient portals are a promising instrument to improve patient-centered care, as they provide patients information and tools that can help them better manage their health. The implementation of portals in both the inpatient and outpatient setting gives health care providers an opportunity to support patients both during hospitalization and after discharge. Thus, there is a need to better understand how inpatient and outpatient portals are used across care contexts. OBJECTIVE: This study aimed to examine patients' perceptions of using inpatient and outpatient portals across the care settings, including how they used the portals and the benefits and concerns associated with portal use. METHODS: This study was conducted in a large Midwestern academic medical center consisting of seven hospitals. We interviewed 120 patients who had used an inpatient portal during their hospitalization, at 15 days and 6 months postdischarge, to determine their perspectives of portal use in both hospital and outpatient settings. Interview transcripts were analyzed inductively and deductively by using team coding processes consistent with a grounded theory approach. RESULTS: Interviews focused on three main areas of portal use: experience with the portal features, perceived benefits, and concerns. Responses at 15 days (n=60) and 6 months (n=60) postdischarge were consistent with respect to perceptions about portal use. Patients identified viewing their health information, managing their schedule, and communicating with providers as notable activities. Convenience, access to information, and better engagement in care were indicated as benefits. Concerns were related to technology issues and privacy/security risks. CONCLUSIONS: Implementation of inpatient portals as a complement to outpatient portals is increasing and can enable patients to better manage aspects of their care. Although care processes vary substantively across settings, the benefits of convenience, improved access to information, and better engagement in care provide opportunities for portal use across care settings to support patient-centered care.

Patient Engagement as Measured by Inpatient Portal Use: Methodology for Log File Analysis.

BACKGROUND: Inpatient portals (IPPs) have the potential to increase patient engagement and satisfaction with their health care. An IPP provides a hospitalized patient with similar functions to those found in outpatient portals, including the ability to view vital signs, laboratory results, and medication information; schedule appointments; and communicate with their providers. However, IPPs may offer additional functions such as meal planning, real-time messaging with the inpatient care team, daily schedules, and access to educational materials relevant to their specific condition. In practice, IPPs have been developed as websites and tablet apps, with hospitals providing the required technology as a component of care during the patient's stay. OBJECTIVE: This study aimed to describe how inpatients are using IPPs at the first academic medical center to implement a system-wide IPP and document the challenges and choices associated with this analytic process. METHODS: We analyzed the audit log files of IPP users hospitalized between January 2014 and January 2016. Data regarding the date/time and duration of interactions with each of the MyChart Bedside modules (eg, view lab results or medications and patient schedule) and activities (eg, messaging the provider and viewing educational videos) were captured as part of the system audit logs. The development of a construct to describe the length of time associated with a single coherent use of the tool-which we call a session-provides a foundational unit of analysis. We defined frequency as the number of sessions a patient has during a given provision day. We defined comprehensiveness in terms of the percentage of functions that an individual uses during a given provision day. RESULTS: The analytic process presented data challenges such as length of stay and tablet-provisioning factors. This study presents data visualizations to illustrate a series of data-cleaning issues. In the presence of these robust approaches to data cleaning, we present the baseline usage patterns associated with our patient panel. In addition to frequency and comprehensiveness, we present considerations of median data to mitigate the effect of outliers. CONCLUSIONS: Although other studies have published usage data associated with IPPs, most have not explicated the challenges and choices associated with the analytic approach deployed within each study. Our intent in this study was to be somewhat exhaustive in this area, in part, because replicability requires common metrics. Our hope is that future researchers in this area will avail themselves of these perspectives to engage in critical assessment moving forward.

Development and prospective validation of a model estimating risk of readmission in cancer patients.

INTRODUCTION: Hospital readmissions among cancer patients are common. While several models estimating readmission risk exist, models specific for cancer patients are lacking. METHODS: A logistic regression model estimating risk of unplanned 30-day readmission was developed using inpatient admission data from a 2-year period (n = 18 782) at a tertiary cancer hospital. Readmission risk estimates derived from the model were then calculated prospectively over a 10-month period (n = 8616 admissions) and compared with actual incidence of readmission. RESULTS: There were 2478 (13.2%) unplanned readmissions. Model factors associated with readmission included: emergency department visit within 30 days, >1 admission within 60 days, non-surgical admission, solid malignancy, gastrointestinal cancer, emergency admission, length of stay >5 days, abnormal sodium, hemoglobin, or white blood cell count. The c-statistic for the model was 0.70. During the 10-month prospective evaluation, estimates of readmission from the model were associated with higher actual readmission incidence from 20.7% for the highest risk category to 9.6% for the lowest. CONCLUSIONS: An unplanned readmission risk model developed specifically for cancer patients performs well when validated prospectively. The specificity of the model for cancer patients, EMR incorporation, and prospective validation justify use of the model in future studies designed to reduce and prevent readmissions.

Odds of talking to healthcare providers as the initial source of healthcare information: updated cross-sectional results from the Health Information National Trends Survey (HINTS).

BACKGROUND: People use a variety of means to find health information, including searching the Internet, seeking print sources, and talking to healthcare providers, family members, and friends. Doctors are considered the most trusted source of health information, but people may be underutilizing them in favor of searching the Internet. METHODS: A multinomial logistic regression of cross-sectional data from Cycle 4 of the Health Information National Trends Survey (HINTS) was conducted. Independent variables included gender, age, rurality, cancer history, general health, income, race, education level, insurance status, veteran status, Internet use, and data year; the dependent variable was the first chosen source of health information. RESULTS: The most frequent initial source of health information was the Internet, and the second most frequent was healthcare providers. There were significant differences in odds of using healthcare providers as the first source of health information. Those likely to use doctors as their initial source of health information were older adults, black adults, adults with health insurance, those who do not use the Internet, and adults who do not have a college degree. CONCLUSIONS: People who use healthcare providers as the first source of health information may have better access to health care and be those less likely to use the Internet. Doctors may have to provide more information to those who do not use the internet and spend time verifying information for those who do use health information from the internet.

Forecasting the Maturation of Electronic Health Record Functions Among US Hospitals: Retrospective Analysis and Predictive Model.

BACKGROUND: The Meaningful Use (MU) program has promoted electronic health record adoption among US hospitals. Studies have shown that electronic health record adoption has been slower than desired in certain types of hospitals; but generally, the overall adoption rate has increased among hospitals. However, these studies have neither evaluated the adoption of advanced functionalities of electronic health records (beyond MU) nor forecasted electronic health record maturation over an extended period in a holistic fashion. Additional research is needed to prospectively assess US hospitals' electronic health record technology adoption and advancement patterns. OBJECTIVE: This study forecasts the maturation of electronic health record functionality adoption among US hospitals through 2035. METHODS: The Healthcare Information and Management Systems Society (HIMSS) Analytics' Electronic Medical Record Adoption Model (EMRAM) dataset was used to track historic uptakes of various electronic health record functionalities considered critical to improving health care quality and efficiency in hospitals. The Bass model was used to predict the technological diffusion rates for repeated electronic health record adoptions where upgrades undergo rapid technological improvements. The forecast used EMRAM data from 2006 to 2014 to estimate adoption levels to the year 2035. RESULTS: In 2014, over 5400 hospitals completed HIMSS' annual EMRAM survey (86%+ of total US hospitals). In 2006, the majority of the US hospitals were in EMRAM Stages 0, 1, and 2. By 2014, most hospitals had achieved Stages 3, 4, and 5. The overall technology diffusion model (ie, the Bass model) reached an adjusted R-squared of .91. The final forecast depicted differing trends for each of the EMRAM stages. In 2006, the first year of observation, peaks of Stages 0 and 1 were shown as electronic health record adoption predates HIMSS' EMRAM. By 2007, Stage 2 reached its peak. Stage 3 reached its full height by 2011, while Stage 4 peaked by 2014. The first three stages created a graph that exhibits the expected "S-curve" for technology diffusion, with inflection point being the peak diffusion rate. This forecast indicates that Stage 5 should peak by 2019 and Stage 6 by 2026. Although this forecast extends to the year 2035, no peak was readily observed for Stage 7. Overall, most hospitals will achieve Stages 5, 6, or 7 of EMRAM by 2020; however, a considerable number of hospitals will not achieve Stage 7 by 2035. CONCLUSIONS: We forecasted the adoption of electronic health record capabilities from a paper-based environment (Stage 0) to an environment where only electronic information is used to document and direct care delivery (Stage 7). According to our forecasts, the majority of hospitals will not reach Stage 7 until 2035, absent major policy changes or leaps in technological capabilities. These results indicate that US hospitals are decades away from fully implementing sophisticated decision support applications and interoperability functionalities in electronic health records as defined by EMRAM's Stage 7.

Growth Dynamics of Patient-Provider Internet Communication: Trend Analysis Using the Health Information National Trends Survey (2003 to 2013).

BACKGROUND: Communication is key in chronic disease management, and the internet has altered the manner in which patients and providers can exchange information. Adoption of secure messaging differs among patients due to the digital divide that keeps some populations from having effective access to online resources. OBJECTIVE: This study aimed to examine the current state of online patient-provider communication, exploring trends over time in the use of online patient-provider communication tools. METHODS: A 3-part analytic process was used to study the following: (1) reanalysis, (2) close replication across years, and (3) trend analysis extension. During the reanalysis stage, the publicly available Health Information National Trends Survey (HINTS) 1 and 2 data were used with the goal of identifying the precise analytic methodology used in a prior study, published in 2007. The original analysis was extended to add 3 additional data years (ie, 2008, 2011, and 2013) using the original analytical approach with the purpose of identifying trends over time. Multivariate logistic regression was used to analyze pooled data across all years, with year as an added predictor, in addition to a model for each individual data year. RESULTS: The odds of internet users to communicate online with health care providers was significantly and increasingly higher year-over-year, starting in 2003 (2005: odds ratio [OR] 1.31, 95% CI 1.03-1.68; 2008: OR 2.14, 95% CI 1.76-2.59; 2011: OR 2.92, 95% CI 2.33-3.66; and 2013: OR 5.77; 95% CI 4.62-7.20). Statistically significant socio-economic factors found to be associated with internet users communicating online with providers included age, having health insurance, having a history of cancer, and living in an urban area of residence. CONCLUSIONS: The proportion of internet users communicating online with their health care providers has significantly increased since 2003. Although these trends are encouraging, access challenges still exist for some groups, potentially giving rise to a new set of health disparities related to communication.

Improving Clinical Documentation in an Academic Setting: A Multidisciplinary Team Approach Focused on the Physician's Perspective.

EXECUTIVE SUMMARY: This research article discusses the results of a pilot study at a large academic medical center to appropriately describe patient severity and the likelihood of mortality. In this study, we compare two projects, both of which use a clinical document specialist (CDS). The control case measures documentation quality using an attending physician-focused model. This model, supplemented by a CDS who requests additional documentation on a post hoc basis, is measured against an intervention where a CDS offers suggestions in real time during rounds with residents and attending physicians.Our findings indicate that documentation training with real-time feedback by a CDS results in higher levels of medical staff participation and a significant increase in submitted physician charges. Additionally, we note that documentation improvement projects do not eliminate coding problems; rather, they support a better alignment between patient state and documentation of that state. Although physicians are key players in the provision of care and the revenue cycle, the physician perspective is missing in the current discourse about documentation. Where quality, profitability, education, teamwork, and profiling drive documentation improvement, ensuring that we understand the problem from both ends is crucial to documentation improvement projects. Therefore, there is a need for more research on the impact of such programs beyond the facility.

Effectiveness of an infant mortality prevention home-visiting program on high-risk births in Ohio.

OBJECTIVES: The Ohio Infant Mortality Reduction Initiative (OIMRI) is a home-visiting program that aims to reduce infant mortality among infants of high-risk black women. This study examined birth outcomes among OIMRI participants and compared program participants to matched non-OIMRI women. DESIGN: Program data were linked to birth records, death records, and Medicaid claims data. Propensity score matching was used to match program participants with like women in Ohio. SAMPLE: The sample consisted of 2,837 black mothers from 14 counties in Ohio. MEASUREMENTS: Infant mortality, causes of death, and birth weight were examined. RESULTS: There were 25 deaths among 2,837 OIMRI participants from 2010 to 2015, for an infant mortality rate of 8.8 deaths per 1,000 live births (95% CI 5.4-12.2). Among those women who participated in OIMRI, three fewer deaths per 1,000 births within the first year of life were estimated compared to those not in OIMRI; however, this was not statistically significant. CONCLUSIONS: The number of infant deaths among women enrolled in the OIMRI program was not significantly different from those who did not participate in OIMRI. Programs like OIMRI cannot singlehandedly address the infant mortality disparity but may help prevent some infant mortality risks.