A national study of challenges to electronic health record adoption and meaningful use.

BACKGROUND: Adoption and implementation of electronic health records (EHRs) has not been without challenges as it infuses technology into what has been a historically manual process of recording patient information. In an effort to identify these challenges, the Office of the National Coordinator for Health Information Technology leveraged the Regional Extension Center population of over 140,000 providers to develop a structured way to track challenges to EHR adoption and Meaningful Use (MU). OBJECTIVES: This report summarizes challenges to EHR adoption and MU based on nationwide data supplied by 55 Regional Extension Centers reporting over 19,000 issues representing over 43,000 unique health care providers. Practices were grouped on the basis of their place in the lifecycle of EHR adoption and MU achievement. RESULTS: Provider engagement and administrative issues were among the more common issues reported across all cohorts. The most challenging MU measure was the clinical summaries measure, but MU Measure challenges varied by practice setting. CONCLUSIONS: EHR adoption and MU challenges are unique to practice setting and stage of the adoption process.

Evaluation of a pilot respiratory virus surveillance system linking electronic health record and diagnostic data.

CONTEXT: During the onset of 2009 pandemic influenza A (H1N1) (pH1N1), the New York City Department of Health and Mental Hygiene implemented a pilot respiratory virus surveillance system. OBJECTIVES: We evaluated the performance of this pilot system, which linked electronic health record (EHR) clinical, epidemiologic, and diagnostic data to monitor influenza-like illness (ILI) in the community. DESIGN: Surveillance was conducted at 9 community health centers with EHRs. Clinical decision support system alerts encouraged diagnostic testing of patients. Rapid influenza diagnostic testing (RIDT) and multiplex polymerase chain reaction assay (MassTag PCR) were performed sequentially. SETTING: Nine Institute for Family Health (IFH) clinics in Manhattan and the Bronx during May 26 to June 30, 2009, the pH1N1 outbreak peak. PARTICIPANTS: Adult and pediatric patients presenting to IFH clinics during May 26 to June 30, 2009. MAIN OUTCOME MEASURES: By using Centers for Disease Control and Prevention guidelines, we evaluated the system's completeness, sensitivity, timeliness, and epidemiologic usefulness. RESULTS: Of 537 ILI visits (5.7% of all visits), 17% underwent diagnostic testing. Of the 132 specimens with both a RIDT and MassTag PCR result, 90 (68%) had a MassTag PCR-identified respiratory virus, most commonly pH1N1 (n = 69; 77%). Of the 81 specimens that met the ILI case definition, 58 (72%) were positive for a respiratory virus tested for by MassTag PCR; 48 (59%) were positive for pH1N1. Ninety-four percent of ILI patients positive for pH1N1 were 45 years or younger. Sensitivity and specificity of RIDT (29% and 94%) and ILI case definition (70% and 48%) for pH1N1 were calculated using MassTag PCR as the standard. Results of RIDT took a median of 6 days. CONCLUSIONS: Despite low RIDT sensitivity for pH1N1 and limited timeliness, integration of EHR and diagnostic data has potential to provide valuable epidemiologic information, guide public health response, and represents a new model for community surveillance for influenza and respiratory viruses.

Impact of integrating public health clinical decision support alerts into electronic health records on testing for gastrointestinal illness.

Laboratory testing by clinicians is essential to outbreak investigations. Electronic health records may increase testing through clinical decision support that alerts providers about existing outbreaks and facilitates laboratory ordering. The impact on laboratory testing was evaluated for foodborne disease outbreaks between 2006 and 2009. After controlling for standard public health messaging and season, decision support resulted in a significant increase in laboratory testing and may be useful in enhancing public health messaging and provider action.

Longitudinal molecular microbial analysis of influenza-like illness in New York City, May 2009 through May 2010.

BACKGROUND: We performed a longitudinal study of viral etiology in samples collected in New York City during May 2009 to May 2010 from outpatients with fever or respiratory disease symptoms in the context of a pilot respiratory virus surveillance system. METHODS: Samples were assessed for the presence of 13 viruses, including influenza A virus, by MassTag PCR. RESULTS: At least one virus was detected in 52% of 940 samples analyzed, with 3% showing co-infections. The most frequently detected agents were rhinoviruses and influenza A, all representing the 2009 pandemic H1N1 strain. The incidence of influenza H1N1-positive samples was highest in late spring 2009, followed by a decline in summer and early fall, when rhinovirus infections became predominant before H1N1 reemerged in winter. Our study also identified a focal outbreak of enterovirus 68 in the early fall of 2009. CONCLUSION: MassTag multiplex PCR affords opportunities to track the epidemiology of infectious diseases and may guide clinicians and public health practitioners in influenza-like illness and outbreak management. Nonetheless, a substantial proportion of influenza-like illness remains unexplained underscoring the need for additional platforms.

Using health information exchange to improve public health.

Public health relies on data reported by health care partners, and information technology makes such reporting easier than ever. However, data are often structured according to a variety of different terminologies and formats, making data interfaces complex and costly. As one strategy to address these challenges, health information organizations (HIOs) have been established to allow secure, integrated sharing of clinical information among numerous stakeholders, including clinical partners and public health, through health information exchange (HIE). We give detailed descriptions of 11 typical cases in which HIOs can be used for public health purposes. We believe that HIOs, and HIE in general, can improve the efficiency and quality of public health reporting, facilitate public health investigation, improve emergency response, and enable public health to communicate information to the clinical community.

The regional extension center program: helping physicians meaningfully use health information technology.

Many physicians face financial and organizational barriers that inhibit their adoption of electronic health record (EHR) systems. The 2009 Health Information Technology for Economic and Clinical Health Act included provisions to facilitate the transition from paper to electronic records, including Medicare and Medicaid incentive payments to support the adoption and meaningful use of EHR systems. It also created the Health Information Technology Regional Extension Center (REC) program to ease the barriers faced by primary care physicians and rural and critical-access hospitals seeking to implement EHRs. The 60 RECs will administer individualized assistance to primary care practices and rural and critical-access hospitals as they implement new EHR systems or upgrade existing ones. In aggregate, the RECs aim to help 100 000 primary care physicians, physician assistants, and nurse practitioners to effectively implement EHR systems and qualify for incentive payments for meaningful use. This article describes the rationale for the REC program and describes how the 60 RECs promote the meaningful use of EHR systems.

Decreasing primary care use and blood pressure monitoring during COVID-19.

Among a group of primary care accountable care organizations, patients with hypertension were 50% less likely to have a blood pressure recorded in April compared with February.

The business end of health information technology. Can a fully integrated electronic health record increase provider productivity in a large community practice?

Electronic health records (EHRs) are expected to transform and improve the way medicine is practiced. However, providers perceive many barriers toward implementing new health information technology. Specifically, they are most concerned about the potentially negative impact on their practice finances and productivity. This study compares the productivity of 75 providers at a large urban primary care practice from January 2005 to February 2009, before and after implementing an EHR system, using longitudinal mixed model analyses. While decreases in productivity were observed at the time the EHR system was implemented, most providers quickly recovered, showing increases in productivity per month shortly after EHR implementation. Overall, providers had significant productivity increases of 1.7% per month per provider from pre- to post-EHR adoption. The majority of the productivity gains occurred after the practice instituted a pay-for-performance program, enabled by the data capture of the EHRs. Coupled with pay-for-performance, EHRs can spur rapid gains in provider productivity.

Estimating the early death toll of COVID-19 in the United States.

BACKGROUND: Efforts to track the severity and public health impact of the novel coronavirus, COVID-19, in the US have been hampered by testing issues, reporting lags, and inconsistency between states. Evaluating unexplained increases in deaths attributed to broad outcomes, such as pneumonia and influenza (P&I) or all causes, can provide a more complete and consistent picture of the burden caused by COVID-19. METHODS: We evaluated increases in the occurrence of deaths due to P&I above a seasonal baseline (adjusted for influenza activity) or due to any cause across the United States in February and March 2020. These estimates are compared with reported deaths due to COVID-19 and with testing data. RESULTS: There were notable increases in the rate of death due to P&I in February and March 2020. In a number of states, these deaths pre-dated increases in COVID-19 testing rates and were not counted in official records as related to COVID-19. There was substantial variability between states in the discrepancy between reported rates of death due to COVID-19 and the estimated burden of excess deaths due to P&I. The increase in all-cause deaths in New York and New Jersey is 1.5-3 times higher than the official tally of COVID-19 confirmed deaths or the estimated excess death due to P&I. CONCLUSIONS: Excess P&I deaths provide a conservative estimate of COVID-19 burden and indicate that COVID-19-related deaths are missed in locations with inadequate testing or intense pandemic activity.

Estimation of Excess Deaths Associated With the COVID-19 Pandemic in the United States, March to May 2020.

Importance: Efforts to track the severity and public health impact of coronavirus disease 2019 (COVID-19) in the United States have been hampered by state-level differences in diagnostic test availability, differing strategies for prioritization of individuals for testing, and delays between testing and reporting. Evaluating unexplained increases in deaths due to all causes or attributed to nonspecific outcomes, such as pneumonia and influenza, can provide a more complete picture of the burden of COVID-19. Objective: To estimate the burden of all deaths related to COVID-19 in the United States from March to May 2020. Design, Setting, and Population: This observational study evaluated the numbers of US deaths from any cause and deaths from pneumonia, influenza, and/or COVID-19 from March 1 through May 30, 2020, using public data of the entire US population from the National Center for Health Statistics (NCHS). These numbers were compared with those from the same period of previous years. All data analyzed were accessed on June 12, 2020. Main Outcomes and Measures: Increases in weekly deaths due to any cause or deaths due to pneumonia/influenza/COVID-19 above a baseline, which was adjusted for time of year, influenza activity, and reporting delays. These estimates were compared with reported deaths attributed to COVID-19 and with testing data. Results: There were approximately 781 000 total deaths in the United States from March 1 to May 30, 2020, representing 122 300 (95% prediction interval, 116 800-127 000) more deaths than would typically be expected at that time of year. There were 95 235 reported deaths officially attributed to COVID-19 from March 1 to May 30, 2020. The number of excess all-cause deaths was 28% higher than the official tally of COVID-19-reported deaths during that period. In several states, these deaths occurred before increases in the availability of COVID-19 diagnostic tests and were not counted in official COVID-19 death records. There was substantial variability between states in the difference between official COVID-19 deaths and the estimated burden of excess deaths. Conclusions and Relevance: Excess deaths provide an estimate of the full COVID-19 burden and indicate that official tallies likely undercount deaths due to the virus. The mortality burden and the completeness of the tallies vary markedly between states.

Syndromic surveillance using ambulatory electronic health records.

OBJECTIVE: To assess the performance of electronic health record data for syndromic surveillance and to assess the feasibility of broadly distributed surveillance. DESIGN: Two systems were developed to identify influenza-like illness and gastrointestinal infectious disease in ambulatory electronic health record data from a network of community health centers. The first system used queries on structured data and was designed for this specific electronic health record. The second used natural language processing of narrative data, but its queries were developed independently from this health record. Both were compared to influenza isolates and to a verified emergency department chief complaint surveillance system. MEASUREMENTS: Lagged cross-correlation and graphs of the three time series. RESULTS: For influenza-like illness, both the structured and narrative data correlated well with the influenza isolates and with the emergency department data, achieving cross-correlations of 0.89 (structured) and 0.84 (narrative) for isolates and 0.93 and 0.89 for emergency department data, and having similar peaks during influenza season. For gastrointestinal infectious disease, the structured data correlated fairly well with the emergency department data (0.81) with a similar peak, but the narrative data correlated less well (0.47). CONCLUSIONS: It is feasible to use electronic health records for syndromic surveillance. The structured data performed best but required knowledge engineering to match the health record data to the queries. The narrative data illustrated the potential performance of a broadly disseminated system and achieved mixed results.

Integration of self-management tools in personal and provider e-health records.

Development and evaluation of research-quality informatics tools for self-management support in personal and provider electronic health records (PHRs and EHRs) may improve patient outcomes by facilitating patient and provider education and communication around goal-setting, prompting consistent evidence-based treatment, and providing reminders and feedback. Nurses on primary care teams are well-positioned to advocate for self-management and monitor the use of these informatics tools. This paper presents a design for integrating goal-setting tools into PHRs and EHRs. Keeping in mind the potential of enhanced self-management support, challenges in basic issues such as user characteristics, practice traditions of data ownership and workflow, and financing are discussed.

Medicare Annual Wellness Visit association with healthcare quality and costs.

OBJECTIVES: Although use of the Medicare Annual Wellness Visit (AWV) is increasing nationally, it remains unclear whether it can help contain healthcare costs and improve quality. In the context of 2 primary care physician-led accountable care organizations (ACOs), we tested the hypothesis that AWVs can improve healthcare costs and clinical quality. STUDY DESIGN: A retrospective cohort study using propensity score matching and quasi-experimental difference-in-differences regression models comparing the differential changes in cost, emergency department (ED) visits, and hospitalizations for those who received an AWV versus those who did not from before until after the AWV. Logistic regressions were used for quality measures. METHODS: Between 2014 and 2016, we examined the association of an AWV with healthcare costs, ED visits, hospitalizations, and clinical quality measures. The sample included Medicare beneficiaries attributed to providers across 44 primary care clinics participating in 2 ACOs. RESULTS: Among 8917 Medicare beneficiaries, an AWV was associated with significantly reduced spending on hospital acute care and outpatient services. Patients who received an AWV in the index month experienced a 5.7% reduction in adjusted total healthcare costs over the ensuing 11 months, with the greatest effect seen for patients in the highest hierarchical condition category risk quartile. AWVs were not associated with ED visits or hospitalizations. Beneficiaries who had an AWV were also more likely to receive recommended preventive clinical services. CONCLUSIONS: In a setting that prioritizes care coordination and utilization management, AWVs have the potential to improve healthcare quality and reduce cost.