Geographic variation in ambulatory electronic health record adoption: implications for underserved communities

The Impact of Market Factors on Meaningful Use of Electronic Health Records Among Primary Care Providers: Evidence From Florida Using Resource Dependence Theory and Information Uncertainty Perspective

BACKGROUND

Using federal funds from the 2009 Health Information Technology for Economic and Clinical Health Act, the Centers for Medicare and Medicaid Services funded the 2011-2021 Medicaid electronic health record (EHR) incentive programs throughout the country.

OBJECTIVE

Identify the market factors associated with Meaningful Use (MU) of EHRs after primary care providers (PCPs) enrolled in the Florida-EHR incentives program through Adopting, Improving, or Upgrading (AIU) an EHR technology.

RESEARCH DESIGN

Retrospective cohort study using 2011-2018 program records for 8464 Medicaid providers.

MAIN OUTCOME

MU achievement after first-year incentives.

INDEPENDENT VARIABLES

The resource dependence theory and the information uncertainty perspective were used to generate key-independent variables, including the county's rurality, educational attainment, poverty, health maintenance organization penetration, and number of PCPs per capita.

ANALYTICAL APPROACH

All the county rates were converted into 3 dichotomous measures corresponding to high, medium, and low terciles. Descriptive and bivariate statistics were calculated. A generalized hierarchical linear model was used because MU data were clustered at the county level (level 2) and measured at the practice level (level 1).

RESULTS

Overall, 41.9% of Florida Medicaid providers achieved MU after receiving first-year incentives. Rurality was positively associated with MU ( P <0.001). Significant differences in MU achievements were obtained when we compared the "high" terciles with the "low" terciles for poverty rates ( P =0.002), health maintenance organization penetration rates ( P =0.02), and number of PCPs per capita ( P =0.01). These relationships were negative.

CONCLUSIONS

Policy makers and health care managers should not ignore the contribution of market factors in EHR adoption.

Better Nurse Practitioner Primary Care Practice Environments Reduce Hospitalization Disparities Among Dually-Enrolled Patients

BACKGROUND

Over 12 million Americans are dually enrolled in Medicare and Medicaid. These individuals experience over twice as many hospitalizations for chronic diseases such as coronary artery disease and diabetes compared with Medicare-only patients. Nurse practitioners (NPs) are well-positioned to address the care needs of dually-enrolled patients, yet NPs often work in unsupportive clinical practice environments. The purpose of this study was to examine the association between the NP primary care practice environment and hospitalization disparities between dually-enrolled and Medicare-only patients with chronic diseases.

METHODS

Using secondary cross-sectional data from the Nurse Practitioner Primary Care Organizational Climate Questionnaire and Medicare claims files, we examined 135,648 patients with coronary artery disease and/or diabetes (20.0% dually-eligible, 80.0% Medicare-only), cared for in 450 practices employing NPs across 4 states (PA, NJ, CA, FL) in 2015. We compared dually-enrolled patients' odds of being hospitalized when cared for in practice environments characterized as poor, mixed, and good based on practice-level Nurse Practitioner Primary Care Organizational Climate Questionnaire scores.

RESULTS

After adjusting for patient and practice characteristics, dually-enrolled patients in poor practice environments had the highest odds of being hospitalized compared with their Medicare-only counterparts [odds ratio (OR): 1.48, CI: 1.37, 1.60]. In mixed environments, dually-enrolled patients had 27% higher odds of a hospitalization (OR: 1.27, CI: 1.12, 1.45). However, in the best practice environments, hospitalization differences were nonsignificant (OR: 1.02, CI: 0.85, 1.23).

CONCLUSIONS

As policymakers look to improve outcomes for dually-enrolled patients, addressing a modifiable aspect of care delivery in NPs' clinical practice environment is a key opportunity to reduce hospitalization disparities.

The impact of county-level factors on meaningful use of electronic health records (EHRs) among primary care providers

This study examines the impact of county-level factors on "meaningful use" (MU) of electronic health records (EHRs) for 8415 primary care providers (PCPs) that enrolled in the Florida Medicaid EHR Incentive Program through adopting, improving, or upgrading (AIU) a certified EHR technology. PCPs received incentive payments at enrollment and if they used their EHRs in meaningful ways; ways that benefit patients and providers alike they received additional payments. We conducted a retrospective cohort study of these providers over the 2011-2018 period while linking their records to other state data. We used the core constructs of the resource dependence theory (RDT), a well-established organization theory in business management, to operationalize the county-level variables. These variables were rurality, poverty, educational attainment, managed care penetration, changes in population, and number of PCPs per capita. The unit of analysis was provider-years. For practical and computational purposes, all the county variables were dichotomized. We used analysis of variance (ANOVA) to test for differences in MU attestation rates across each county variable. Odds ratios and corresponding 95% confidence intervals were derived from pooled logistic regressions using generalized estimated equations (GEE) with the binomial family and logit link functions. Clustered standard errors were used. Approximately 42% of these providers attested to MU after receiving first-year incentives. Rurality and poverty were significantly associated with MU. To some degree, managed care penetration, change in population size, and number of PCPs per capita were also associated with MU. Policy makers and healthcare managers should not ignore the contribution of county-level factors in the diffusion of EHRs among physician practices. These county-level findings provide important insights about EHR diffusion in places where traditionally underserved populations live. This county-perspective is particularly important because of the potential for health IT to enable public health monitoring and population health management that might benefit individuals beyond the patients treated by the Medicaid providers.

Patient portal utilization: before and after stage 2 electronic health record meaningful use

OBJECTIVE

Patient portal functionalities, such as patient-physician e-communication, can benefit patients by improving clinical outcomes. Utilization has historically been low but may have increased in recent years due to the implementation of Stage 2 Meaningful Use for electronic health records. This study has 2 objectives: 1) to compare patient portal utilization rates before Stage 2 (2011-2013) and after Stage 2 (2014-2017), and 2) to examine whether disparities in patient portal utilization attenuate after Stage 2.

MATERIALS AND METHODS

We conducted an observational study using a pooled cross-sectional analysis of 2011-2017 National Health Interview Survey data (n = 254 183).

RESULTS

The mean percent use of patient portals significantly increased from the pre-Stage 2 to the post-Stage 2 period (6.9%, 95% CI, 6.2-7.5; P < .001). Non-Hispanic Black individuals (OR 0.81, 95% CI, 0.76-0.86; P < .0001) and Hispanic individuals (OR 0.79, 95% CI, 0.74-0.84; P < .0001) have lower odds of using patient portals compared to non-Hispanic White individuals. Although we found independent effects of race/ethnicity, we did not find a statistically significant interaction between race/ethnicity and time. We found a similar level of increase in patient portal utilization from the pre- to postperiod across racial and ethnic groups.

DISCUSSION

Health care policies such as Stage 2 Meaningful Use are likely contributing to increased patient portal utilization across all patients and helping to attenuate disparities in utilization between subgroups of patients.

CONCLUSION

Further research is needed to explore which patient portal functionalities are perceived as most beneficial to patients and whether patients have access to those functionalities.

The efficiency analysis and spatial implications of health information technology: A regional exploratory study in China

The new adoption of healthcare information technology is costly, and effects on healthcare performance can be questionable. This nationwide study in China investigated the efficient performance of healthcare information technology and examined its spatial correlation. Panel data were extracted from the Annual Investigation Report on Hospital Information in China and the China Health Statistics Yearbook for 2007 through 2015 (279 observations). Stochastic frontier analysis was employed to estimate the technical efficiency of healthcare information technology performance and related factors at the regional level. Healthcare information technology performance was positively associated with electronic medical records, total input, and cost of inpatient stay, while picture archiving and communication systems and net assets were negatively related. Local Indicators of Spatial Association showed that there existed significant spatial autocorrelation. Governmental policies would best make distinctions among different forms of healthcare information technology, especially between electronic medical records and picture archiving and communication systems. Policies should be formulated to improve healthcare information technology adoption and reduce regional differences.

Focal fields in literature on the information divide

Purpose

The purpose of this paper is to identify key countries and their focal research fields on the information divide.

Design/methodology/approach

Literature was retrieved to identify key countries and their primary focus. The literature research method was adopted to identify aspects of the primary focus in each key country.

Findings

The key countries with literature on the information divide are the USA, China, the UK and India. The problem of health is prominent in the USA, and solutions include providing information, distinguishing users’ profiles and improving eHealth literacy. Economic and political factors led to the urban–rural information divide in China, and policy is the most powerful solution. Under the influence of humanism, research on the information divide in the UK focuses on all age groups, and solutions differ according to age. Deep-rooted patriarchal concepts and traditional marriage customs make the gender information divide prominent in India, and increasing women’s information consciousness is a feasible way to reduce this divide.

Originality/value

This paper is an extensive review study on the information divide, which clarifies the key countries and their focal fields in research on this topic. More important, the paper innovatively analyzes and summarizes existing literature from a country perspective.

Facility and Regional Factors Associated With the New Adoption of Electronic Medical Records in Japan: Nationwide Longitudinal Observational Study

Background

The rate of adoption of electronic medical record (EMR) systems has increased internationally, and new EMR adoption is currently a major topic in Japan. However, no study has performed a detailed analysis of longitudinal data to evaluate the changes in the EMR adoption status over time.

Objective

This study aimed to evaluate the changes in the EMR adoption status over time in hospitals and clinics in Japan and to examine the facility and regional factors associated with these changes.

Methods

Secondary longitudinal data were created by matching data in fiscal year (FY) 2011 and FY 2014 using reference numbers. EMR adoption status was defined as “EMR adoption,” “specified adoption schedule,” or “no adoption schedule.” Data were obtained for hospitals (n=4410) and clinics (n=67,329) that had no adoption schedule in FY 2011 and for hospitals (n=1068) and clinics (n=3132) with a specified adoption schedule in FY 2011. The EMR adoption statuses of medical institutions in FY 2014 were also examined. A multinomial logistic model was used to investigate the associations between EMR adoption status in FY 2014 and facility and regional factors in FY 2011. Considering the regional variations of these models, multilevel analyses with second levels were conducted. These models were constructed separately for hospitals and clinics, resulting in four multinomial logistic models. The odds ratio (OR) and 95% Bayesian credible interval (CI) were estimated for each variable.

Results

A total of 6.9% of hospitals and 14.82% of clinics with no EMR adoption schedules in FY 2011 had adopted EMR by FY 2014, while 10.49% of hospitals and 33.65% of clinics with specified adoption schedules in FY 2011 had cancelled the scheduled adoption by FY 2014. For hospitals with no adoption schedules in FY 2011, EMR adoption/scheduled adoption was associated with practice size characteristics, such as number of outpatients (from quantile 4 to quantile 1: OR 1.67, 95% CI 1.005-2.84 and OR 2.40, 95% CI 1.80-3.21, respectively), and number of doctors (from quantile 4 to quantile 1: OR 4.20, 95% CI 2.39-7.31 and OR 2.02, 95% CI 1.52-2.64, respectively). For clinics with specified EMR adoption schedules in FY 2011, the factors negatively associated with EMR adoption/cancellation of scheduled EMR adoption were the presence of beds (quantile 4 to quantile 1: OR 0.57, 95% CI 0.45-0.72 and OR 0.74, 95% CI 0.58-0.96, respectively) and having a private establisher (quantile 4 to quantile 1: OR 0.27, 95% CI 0.13-0.55 and OR 0.43, 95% CI 0.19-0.91, respectively). No regional factors were significantly associated with the EMR adoption status of hospitals with no EMR adoption schedules; population density was positively associated with EMR adoption in clinics with no EMR adoption schedule (quantile 4 to quantile 1: OR 1.49, 95% CI 1.32-1.69).

Conclusions

Different approaches are needed to promote new adoption of EMR systems in hospitals as compared to clinics. It is important to induce decision making in small- and medium-sized hospitals, and regional postdecision technical support is important to avoid cancellation of scheduled EMR adoption in clinics.

Assessment of Personal Health Care Management and Chronic Disease Prevalence: Comparative Analysis of Demographic, Socioeconomic, and Health-Related Variables

Background

The use of personal health care management (PHM) is increasing rapidly within the United States because of implementation of health technology across the health care continuum and increased regulatory requirements for health care providers and organizations promoting the use of PHM, particularly the use of text messaging (short message service), Web-based scheduling, and Web-based requests for prescription renewals. Limited research has been conducted comparing PHM use across groups based on chronic conditions.

Objective

This study aimed to describe the overall utilization of PHM and compare individual characteristics associated with PHM in groups with no reported chronic conditions, with 1 chronic condition, and with 2 or more such conditions.

Methods

Datasets drawn from the National Health Interview Survey were analyzed using multiple logistic regression to determine the level of PHM use in relation to demographic, socioeconomic, or health-related factors. Data from 47,814 individuals were analyzed using logistic regression.

Results

Approximately 12.19% (5737/47,814) of respondents reported using PHM, but higher rates of use were reported by individuals with higher levels of education and income. The overall rate of PHM remained stable between 2009 and 2014, despite increased focus on the promotion of patient engagement initiatives. Demographic factors predictive of PHM use included people who were younger, non-Hispanic, and who lived in the western region of the United States. There were also differences in PHM use based on socioeconomic factors. Respondents with college-level education were over 2.5 times more likely to use PHM than respondents without college-level education. Health-related factors were also predictive of PHM use. Individuals with health insurance and a usual place for health care were more likely to use PHM than individuals with no health insurance and no usual place for health care. Individuals reporting a single chronic condition or multiple chronic conditions reported slightly higher levels of PHM use than individuals reporting no chronic conditions. Individuals with no chronic conditions who did not experience barriers to accessing health care were more likely to use PHM than individuals with 1 or more chronic conditions.

Conclusions

The findings of this study illustrated the disparities in PHM use based on the number of chronic conditions and that multiple factors influence the use of PHM, including economics and education. These findings provide evidence of the challenge associated with engaging patients using electronic health information as the health care industry continues to evolve.

Regional differences in electronic medical record adoption in Japan: A nationwide longitudinal ecological study

PURPOSE

Regional differences in the adoption of electronic medical records (EMR) are a major problem, yet little is known about these differences internationally. We analyzed regional differences in EMR adoption in Japan and evaluated factors associated with these differences.

METHODS

This nationwide ecological study used secondary data from all secondary medical service areas (SMSAs) in fiscal years 2008 (n = 348) and 2014 (n = 344). For each SMSA we collected the following information from a Japanese national database: the number of medical facilities that had adopted EMR, the population density, the average per capita income, the number of working doctors per 1000 people, and the proportion of interns to all working doctors. To adjust for medical facility characteristics in each SMSA, such as number of beds, public versus private hospital, and hospital type (psychiatric or other), we estimated the standardized adoption ratio (SAR) for EMR adoption, modeled on the standardized mortality ratio. We calculated Moran's I for the SAR and investigated whether the SAR had spatial autocorrelations. We evaluated the association between the SAR and regional factors with a conditional autoregressive model. We compared these results in 2008 and 2014, for both hospitals and clinics.

RESULTS

While the EMR adoption rate in SMSAs increased, Moran's I of the SAR in hospitals was close to 1 in both 2008 and 2014, and Moran's I of the SAR in clinics increased from 2008 to 2014. For hospitals, there was a significant association between the proportion of interns to all working doctors and the SAR only in 2008. For clinics, average income in the SMSA was positively associated with the SAR, whereas the number of working doctors was negatively associated with the SAR in both 2008 and 2014. Population density was positively associated with the SAR only in 2014.

CONCLUSION

From 2008 to 2014, EMR adoption in Japan generally increased, but geographical differences did not improve. Regional factors associated with the SAR were different for hospitals than for clinics. Therefore, the government should take different approaches for clinics and hospitals to improve regional differences in EMR adoption, especially in providing financial and technical support.

Physician report of industry gifts and quality of care

BACKGROUND

Physician financial conflict of interest is a concern in the delivery of medicine because of its possible influence on the cost and the quality of patient care. There has been an extensive discussion of the ethical, economic, and legal aspects of this issue but little direct empirical evidence of its magnitude or effects.

METHODOLOGY

A nationally representative survey (n = 4,720) was used to empirically examine physician self-report of receipt of financial gifts from the pharmaceutical and medical devices industry and its association with their ability to provide quality care.

FINDINGS

Results indicate that the vast majority of physicians receive industry gifts in various forms, and the receipt of gifts is associated with lower perceived quality of patient care. There is also an inverse relationship between the frequency of received gifts and the perceived quality of care.

PRACTICE IMPLICATIONS

Physicians need to be aware of the widespread receipt of industry gifts in medical practice and the potential adverse impact of such receipts on the delivery of care.

Effects of Regulation and Payment Policies on Nurse Practitioners' Clinical Practices

Increasing patient demand following health care reform has led to concerns about provider shortages, particularly in primary care and for Medicaid patients. Nurse practitioners (NPs) represent a potential solution to meeting demand. However, varying state scope of practice regulations and Medicaid reimbursement rates may limit efficient distribution of NPs. Using a national sample of 252,657 ambulatory practices, we examined the effect of state policies on NP employment in primary care and practice Medicaid acceptance. NPs had 13% higher odds of working in primary care in states with full scope of practice; those odds increased to 20% if the state also reimbursed NPs at 100% of the physician Medicaid fee-for-service rate. Furthermore, in states with 100% Medicaid reimbursement, practices with NPs had 23% higher odds of accepting Medicaid than practices without NPs. Removing scope of practice restrictions and increasing Medicaid reimbursement may increase NP participation in primary care and practice Medicaid acceptance.

Physician Competition in the Era of Accountable Care Organizations

OBJECTIVE

To calculate physician concentration levels for all U.S. markets using detailed data on integration and accountable care organization (ACO) participation.

DATA SOURCE

2015 SK&A office-based physician survey linked to all commercial and public payer ACOs.

STUDY DESIGN

We construct three separate Herfindahl-Hirschman Index (HHI) measures and plot their distributions. We then investigate how prevailing levels of concentration change when incorporating more detailed organizational features into the HHI measure.

PRINCIPAL FINDINGS

Horizontal and vertical integration strongly influences measures of physician concentration; however, ACOs have limited impact overall. ACOs are often present in competitive markets, and only in a minority of these markets do ACOs substantively increase physician concentration.

CONCLUSIONS

Monitoring ACO effects on physician competition will likely have to proceed on a case-by-case basis.

Physician and Practice-Level Drivers and Disparities around Meaningful Use Progress

OBJECTIVE

To identify physician and practice characteristics that are markers of success for meaningful use of electronic health records (EHRs).

DATA SOURCES

American Medical Association survey, Centers for Medicare & Medicaid Services' (CMS) EHR Incentive, Pioneer Accountable Care Organization, and PECOS Programs, the Office of the National Coordinator for Health IT's Regional Extension Center Program, and National Committee for Quality Assurance Patient-centered Medical Home certification program.

STUDY DESIGN

Retrospective analysis of 865,370 physicians' participation in CMS's EHR Incentive Program and progress to stage 1 Meaningful Use between 2011 and 2013. Physician specialty, age, practice size, geographic markers, delivery reform participation, and technical assistance receipt were predictive elements.

PRINCIPAL FINDINGS

Medicaid physicians were progressing more slowly to Meaningful Use than Medicare physicians: by 2013, 8 in 10 physicians registered with Medicare had achieved meaningful use, compared to one-third of Medicaid-registered physicians. The strongest predictors of meaningful use were technical assistance (79 percent more likely) and delivery reform participation (34 percent more likely).

CONCLUSIONS

Continued outreach and technical assistance that demonstrates strong interactions between meaningful use of health IT and delivery reform may facilitate further adoption of both initiatives.

Informatics-based Challenges of Building Collaborative Healthcare Research and Analysis Networks from Rural Community Health Centers

We discuss informatics-based challenges of constructing large-scale collaborative networks for healthcare research and analysis from rural community health centers. These types of networks provide data access and analytic insights across multiple heterogeneous health centers for both healthcare professionals and biomedical researchers. Challenges fall into three general categories: data access, data integration, and technical infrastructure. Data access issues arise in balancing patient privacy, security, and utility; data integration issues persist from each site independently operating its desired electronic medical record; technical infrastructure challenges include creating an analysis and reporting hub capable of scaling across a large collaborative network. Other challenges, such as the difficulty of site recruitment, are important to discuss, but cannot be solved directly through informatics alone. We discuss these challenges and their potential solutions in the context of our implementation of the Kentucky Diabetes and Obesity Collaborative (KDOC). KDOC is a network of Federally-Qualified Community Health Centers (FQHCs) that established a collaborative infrastructure for research and analysis of obesity and diabetes in rural and under-served communities.

Using Technology to Improve Cancer Care: Social Media, Wearables, and Electronic Health Records

Digital engagement has become pervasive in the delivery of cancer care. Internet- and cellular phone-based tools and systems are allowing large groups of people to engage with each other and share information. Health systems and individual health professionals are adapting to this revolution in consumer and patient behavior by developing ways to incorporate the benefits of technology for the purpose of improving the quality of medical care. One example is the use of social media platforms by oncologists to foster interaction with each other and to participate with the lay public in dialogue about science, medicine, and cancer care. In addition, consumer devices and sensors (wearables) have provided a new, growing dimension of digital engagement and another layer of patient-generated health data to foster better care and research. Finally, electronic health records have become the new standard for oncology care delivery, bringing new opportunities to measure quality in real time and follow practice patterns, as well as new challenges as providers and patients seek ways to integrate this technology along with other forms of digital engagement to produce more satisfaction in the process of care along with measurably better outcomes.

Using i2b2 to Bootstrap Rural Health Analytics and Learning Networks

We demonstrate that the open-source i2b2 (Informatics for Integrating Biology and the Bedside) data model can be used to bootstrap rural health analytics and learning networks. These networks promote communication and research initiatives by providing the infrastructure necessary for sharing data and insights across a group of healthcare and research partners. Data integration remains a crucial challenge in connecting rural healthcare sites with a common data sharing and learning network due to the lack of interoperability and standards within electronic health records. The i2b2 data model acts as a point of convergence for disparate data from multiple healthcare sites. A consistent and natural data model for healthcare data is essential for overcoming integration issues, but challenges such as those caused by weak data standardization must still be addressed. We describe our experience in the context of building the West Virginia/Kentucky Health Analytics and Learning Network, a collaborative, multi-state effort connecting rural healthcare sites.

Meaningful Use of the Indian Health Service Electronic Health Record

OBJECTIVE

To understand the use of electronic health record (EHR) functionalities by physicians practicing in an underserved setting.

DATA SOURCE/STUDY SETTING

A total of 333 Indian Health Service physicians (55 percent response rate) in August 2012.

STUDY DESIGN

Cross-sectional.

DATA COLLECTION

The survey assessed routine use of EHR functionalities, perceived usefulness, and barriers to adoption.

PRINCIPAL FINDINGS

Physicians routinely used a median 7 of 10 EHR functionalities targeted by the Meaningful Use program, but only 5 percent used all 10. Most (63 percent) felt the EHR improved quality of care. Many (76 percent) reported increased documentation time and poorer quality patient-physician interactions (45 percent). Primary care specialty and time using the EHR were positively associated with use of EHR functionalities, while perceived productivity loss was negatively associated.

CONCLUSIONS

Significant opportunities exist to increase use of EHR functionalities and preserve physician-patient interactions and productivity in a resource-limited environment.

Adoption and use of electronic health records among federally qualified health centers grew substantially during 2010-12

Federally qualified health centers play an important role in providing health care to underserved populations. Recent substantial federal investments in health information technology have enabled health centers to expand their use of electronic health record (EHR) systems, but factors associated with adoption are not clear. We examined 2010-12 administrative data from the Health Resources and Services Administration's Uniform Data System for more than 1,100 health centers. We found that in 2012 nine out of ten health centers had adopted a EHR system, and half had adopted EHRs with basic capabilities. Seven in ten health centers reported that their providers were receiving meaningful-use incentive payments from the Centers for Medicare and Medicaid Services (CMS). Only one-third of health centers had EHR systems that could meet CMS's stage 1 meaningful-use core requirements. Health centers that met the stage 1 requirements had more than twice the odds of receiving quality recognition, compared with centers with less than basic EHRs. Policy initiatives should focus assistance on EHR capabilities with slower uptake; connect providers with technical assistance to support implementation; and leverage the connection between meaningful use and quality recognition programs.

The Influence of the Degree of Rurality on EMR Adoption, by Physician Specialty

OBJECTIVE

To explore the influence of varying degrees of remoteness on practice-level electronic medical record (EMR) adoption, including whether the effect differs across practice specialty.

DATA SOURCES

Survey data on over 270,000 office-based physician practices (representing over 1,250,000 providers) collected by SK&A information services during 2012.

STUDY DESIGN

This study examined differences in EMR adoption by practices located across the nine-category rural-urban continuum. Logistic regressions and associated marginal effects are used to assess how much a move up or down the rural-urban continuum code impacts the likelihood of EMR adoption, after controlling for characteristics likely to affect EMR adoption such as practice size and specialty.

PRINCIPAL FINDINGS

Overall practice-level EMR adoption rates generally increase with the degree of rurality and range from 47 percent in the most urban counties to over 60 percent in the most rural. Moving from the most urban county to the most rural corresponded to a 7 percent increase in the likelihood of EMR adoption (p < .01).

CONCLUSIONS

EMR adoption rates do vary significantly across nonmetropolitan counties, and they generally increase as a practice becomes more rural. From a policy perspective, this suggests that urban practices may in fact be the lowest hanging remaining fruit for increasing EMR adoption rates.

Electronic health records and health care quality over time in a federally qualified health center

The longitudinal effects of electronic health records (EHRs) on ambulatory quality are not clear. It is not known whether adoption and meaningful use of EHRs result in a brief period of quality improvement that then plateaus, or whether with ongoing use quality improvement continues. We studied health care quality at six sites of a Federally Qualified Health Center in New York State over 3 years (2008–2010) for 25 290 unique patients. Patients were twice as likely to receive recommended care on a set of 12 quality measures (11 of which are included in Stage 1 Meaningful Use) 3 years post-EHR implementation, compared to 1-year post-implementation (odds ratio 1.97; 95% confidence interval, 1.91–2.03). The magnitude of absolute improvement ranged from 5% to 20% per measure. EHRs were associated with continuing improvement in health care quality for at least 3 years post-implementation in the safety-net setting of a Federally Qualified Health Center.

Rural EMR adoption rates overtake those in urban areas

OBJECTIVE

To assess rural-urban differences in electronic medical record (EMR) adoption among office-based physician practices in the United States.

METHODS

Survey data on over 270 000 office-based physician sites (representing over 1 280 000 physicians) in the United States from 2012 was used to assess differences in EMR adoption rates among practices in rural and urban areas. Logistic regression tests for differences in the determinants of EMR adoption by geography, and a nonlinear decomposition is used to quantify how much of the rural-urban gap is due to differences in measureable characteristics (such as type of practice or affiliation with a health system).

RESULTS

Overall EMR adoption rates were significantly higher for practices in rural areas (56%) vs those in urban areas (49%) in 2012 (P < 0.001). Twenty-nine states had statistically significantly different adoption rates between rural and urban areas, with only two states demonstrating higher rates in urban areas. EMR adoption continues to be higher for primary care practices when compared to specialists (51% vs 49%, P < 0.001), and state-level rural-urban differences in adoption are more pronounced for specialists. The decomposition technique finds that only 14% of the rural-urban gap can be explained by differences in measurable characteristics between practices.

CONCLUSIONS

At the national level, rates of EMR adoption are higher for rural practices than for their urban counterparts, reversing earlier trends. This suggests that outreach efforts, namely the Regional Extension Centers created by the Office of the National Coordinator, have been particularly effective in increasing EMR adoption in rural areas.

Area-level factors associated with electronic health record adoption and meaningful use in the Regional Extension Center Program

OBJECTIVE

To identify area-level correlates of electronic health record (EHR) adoption and meaningful use (MU) among primary care providers (PCPs) enrolled in the Regional Extension Center (REC) Program.

MATERIALS AND METHODS

County-level data on 2013 EHR adoption and MU among REC-enrolled PCPs were obtained from the Office of the National Coordinator for Health Information Technology and linked with other county-level data sources including the Area Resource File, American Community Survey, and Federal Communications Commission's broadband availability database. Hierarchical models with random intercepts for RECs were employed to assess associations between a broad set of area-level factors and county-level rates of EHR adoption and MU.

RESULTS

Among the 2715 counties examined, the average county-level EHR adoption and MU rates for REC-enrolled PCPs were 87.5% and 54.2%, respectively. Community health center presence and Medicaid enrollment concentration were positively associated with EHR adoption, while metropolitan status and Medicare Advantage enrollment concentration were positively associated with MU. Health professional shortage area status and minority concentration were negatively associated with EHR adoption and MU.

DISCUSSION

Increased financial incentives in areas with greater concentrations of Medicaid and Medicare enrollees may be encouraging EHR adoption and MU among REC-enrolled PCPs. Disparities in EHR adoption and MU in some low-resource and underserved areas remain a concern.

CONCLUSIONS

Federal efforts to spur EHR adoption and MU have demonstrated some early success; however, some geographic variations in EHR diffusion indicate that greater attention needs to be paid to ensuring equitable uptake and use of EHRs throughout the US.

Electronic medical record adoption in Oklahoma practices: rural-urban differences and the role of broadband availability

PURPOSE

Most recent research has not found significant differences in electronic medical record (EMR) adoption rates between rural and urban physicians. However, few studies have assessed rural/urban differences at a lower level--for instance, by specialty or size of practice. Determinants of EMR adoption by physician practices in Oklahoma are explored, including the potential role of broadband availability (which is required for EMR interoperability).

METHODS

Surveys of 2,800 unique Oklahoma physician practices in 2011 were meshed with data from the National Broadband Map for that same year. Summary statistics from the survey data allowed for comparison of EMR adoption rates by sub category. Logistic regressions were used to tease out the impact of location, specialty, and broadband availability on the EMR adoption decision.

FINDINGS

Similar overall EMR adoption rates in rural and urban practices masked significant differences among specific subcategories. In particular, solo practices in rural areas are much more likely to adopt EMRs than are their urban counterparts (41% vs 33%, P < .01); rural psychiatric practices also have measurably higher adoption rates (59% vs 25%, P < .01). Logistic regression results demonstrate that determinants of adoption do vary between rural and urban practices. No statistical relationship between EMR adoption and measures of broadband availability was found.

CONCLUSIONS

Measurable differences in EMR adoption rates do exist between rural and urban practices for specific physician categories in Oklahoma. Targeted policies may be important for increasing EMR adoption, but policy efforts focusing solely on broadband availability for private practices are likely misguided.

Geographic variation in health IT and health care outcomes: A snapshot before the meaningful use incentive program began

BACKGROUND

The 2009 Health Information Technology for Economic and Clinical Health (HITECH) Act, which includes the Meaningful Use (MU) incentive program, was designed to increase the adoption of health information technology (IT) by physicians and hospitals. Policymakers hope that increased use of health IT to exchange health information will in turn enhance the quality and efficiency of health care delivery. In this study, we analyze the extent to which key outcomes vary based on the levels of health ITness among physicians and hospitals before the HITECH and MU programs led to increases in adoption and changes in use. Our findings provide an important baseline for a future evaluation of the impact of these programs on population-level outcomes.

METHODS

We constructed measures of the degree of hospital and physician adoption and use ("health ITness") at the level of the hospital referral region (HRR). We used data from the 2010 IT Supplement of the American Hospital Association (AHA) Annual Survey of Hospitals to capture hospital health ITness and data from the 2010 survey of ambulatory health care sites produced by SK&A Information Services for the physician measure. We conducted cross-sectional analyses of the relationship between market-level Medicare costs and use and three measures: (1) physician health ITness, (2) hospital health ITness, and (3) an overall measure of health ITness.

RESULTS

In general, greater levels of physician health ITness are associated with decreasing costs and use. Many of these relationships lose statistical significance, however, when we control for population and market characteristics such as the average age and health status of Medicare beneficiaries, mean household income, and the HMO penetration rate. Several of the relationships also change according to the level of hospital health ITness.

CONCLUSIONS

Our findings suggest that greater levels of physician health ITness are associated with decreasing costs and use for a number of services, including inpatient costs and stays, imaging services, and lab tests, in 2010. Our health ITness and outcomes measures are aggregated at the HRR level; as such, these results do not suggest that the adoption and use of health IT by individual physicians or hospitals leads to decreases in costs or use for their individual patients. Nevertheless, these baseline findings provide important information to be considered in future research analyzing the impact of HITECH and the MU incentives.