Cost-Effectiveness of a Comprehensive Primary Care Smoking Treatment Program

INTRODUCTION

Smoking is the leading preventable cause of death and disease in the U.S. This study evaluates the cost-effectiveness from a healthcare system perspective of a comprehensive primary care intervention to reduce smoking rates.

METHODS

This pragmatic trial implemented electronic health record prompts during primary care visits and employed certified tobacco cessation specialists to offer proactive outreach and smoking cessation treatment to patients who smoke. The data, analyzed in 2022, included 10,683 patients in the smoking registry from 2017 to 2020. Pre-post analyses compared intervention costs to treatment engagement, successful self-reported smoking cessation, and acute health care utilization (urgent care, emergency department visits, and inpatient hospitalization). Cost per quality-adjusted life year was determined by applying conversion factors obtained from the tobacco research literature to the cost per patient who quit smoking.

RESULTS

Tobacco cessation outreach, medication, and counseling costs increased from $2.64 to $6.44 per patient per month, for a total post-implementation intervention cost of $500,216. Smoking cessation rates increased from 1.3% pre-implementation to 8.7% post-implementation, for an incremental effectiveness of 7.4%. The incremental cost-effectiveness ratio was $628 (95% CI: $568, $695) per person who quit smoking, and $905 (95% CI: $822, $1,001) per quality-adjusted life year gained. Acute health care costs decreased by an average of $42 (95% CI: -$59, $145) per patient per month for patients in the smoking registry.

CONCLUSIONS

Implementation of a comprehensive and proactive smoking cessation outreach and treatment program for adult primary care patients who smoke meets typical cost-effectiveness thresholds for healthcare.

Identifying Contributing Factors Associated With Dental Adverse Events Through a Pragmatic Electronic Health Record-Based Root Cause Analysis

OBJECTIVE

This study assessed contributing factors associated with dental adverse events (AEs).

METHODS

Seven electronic health record-based triggers were deployed identifying potential AEs at 2 dental institutions. From 4106 flagged charts, 2 reviewers examined 439 charts selected randomly to identify and classify AEs using our dental AE type and severity classification systems. Based on information captured in the electronic health record, we analyzed harmful AEs to assess potential contributing factors; harmful AEs were defined as those that resulted in temporary moderate to severe harm, required hospitalization, or resulted in permanent moderate to severe harm. We classified potential contributing factors according to (1) who was involved (person), (2) what were they doing (tasks), (3) what tools/technologies were they using (tools/technologies), (4) where did the event take place (environment), (5) what organizational conditions contributed to the event? (organization), (6) patient (including parents), and (7) professional-professional collaboration. A blinded panel of dental experts conducted a second review to confirm the presence of an AE.

RESULTS

Fifty-nine cases had 1 or more harmful AEs. Pain occurred most frequently (27.1%), followed by nerve injury (16.9%), hard tissue injury (15.2%), and soft tissue injury (15.2%). Forty percent of the cases were classified as "temporary not moderate to severe harm." Person (training, supervision, and fatigue) was the most common contributing factor (31.5%), followed by patient (noncompliance, unsafe practices at home, low health literacy, 17.1%), and professional-professional collaboration (15.3%).

CONCLUSIONS

Pain was the most common harmful AE identified. Person, patient, and professional-professional collaboration were the most frequently assessed factors associated with harmful AEs.

Accelerated curation of checkpoint inhibitor-induced colitis cases from electronic health records

Objective

Automatically identifying patients at risk of immune checkpoint inhibitor (ICI)-induced colitis allows physicians to improve patientcare. However, predictive models require training data curated from electronic health records (EHR). Our objective is to automatically identify notes documenting ICI-colitis cases to accelerate data curation.

Materials and Methods

We present a data pipeline to automatically identify ICI-colitis from EHR notes, accelerating chart review. The pipeline relies on BERT, a state-of-the-art natural language processing (NLP) model. The first stage of the pipeline segments long notes using keywords identified through a logistic classifier and applies BERT to identify ICI-colitis notes. The next stage uses a second BERT model tuned to identify false positive notes and remove notes that were likely positive for mentioning colitis as a side-effect. The final stage further accelerates curation by highlighting the colitis-relevant portions of notes. Specifically, we use BERT’s attention scores to find high-density regions describing colitis.

Results

The overall pipeline identified colitis notes with 84% precision and reduced the curator note review load by 75%. The segment BERT classifier had a high recall of 0.98, which is crucial to identify the low incidence (<10%) of colitis.

Discussion

Curation from EHR notes is a burdensome task, especially when the curation topic is complicated. Methods described in this work are not only useful for ICI colitis but can also be adapted for other domains.

Conclusion

Our extraction pipeline reduces manual note review load and makes EHR data more accessible for research.

User-Centered Design to Reduce Inappropriate Blood Transfusion Orders

BACKGROUND

To improve blood transfusion practices, we applied user-centered design (UCD) to evaluate potential changes to blood transfusion orders.

OBJECTIVES

The aim of the study is to build effective transfusion orders with different designs to improve guideline adherence.

METHODS

We developed three different versions of transfusion orders that varied how information was presented to clinicians ordering blood transfusions. We engaged 14 clinicians (residents, advanced practice providers [APPs], and attending physicians) from different specialties. We used the think aloud technique and rapid qualitative analysis to generate themes to incorporate into our modified orders.

RESULTS

Most end-users who participated in the semi-structured interviews preferred the interruptive alert design plus behavioral nudges (n = 8/14, 57%). The predominant rationale was that the in-line alert was not visually effective in capturing the end-user's attention, while the interruptive alert forced a brief stop in the workflow to consider the guidelines. All users supported the general improvements, though for different reasons, and as a result, the general improvements remained in the designs for the forthcoming trial.

CONCLUSION

The user experience uncovered through the think aloud approach produced a clear and rich understanding of potentially confounding factors in the initial design of different intervention versions. Input from end-users guided the creation of all three designs so each was addressing human factors with parity, which ensured that the results of our study reflected differences in interruptive properties of the alerts and not differences in design.

An AI Approach for Identifying Patients With Cirrhosis

GOAL

The goal of this study was to evaluate an artificial intelligence approach, namely deep learning, on clinical text in electronic health records (EHRs) to identify patients with cirrhosis.

BACKGROUND AND AIMS

Accurate identification of cirrhosis in EHR is important for epidemiological, health services, and outcomes research. Currently, such efforts depend on International Classification of Diseases (ICD) codes, with limited success.

MATERIALS AND METHODS

We trained several machine learning models using discharge summaries from patients with known cirrhosis from a patient registry and random controls without cirrhosis or its complications based on ICD codes. Models were validated on patients for whom discharge summaries were manually reviewed and used as the gold standard test set. We tested Naive Bayes and Random Forest as baseline models and a deep learning model using word embedding and a convolutional neural network (CNN).

RESULTS

The training set included 446 cirrhosis patients and 689 controls, while the gold standard test set included 139 cirrhosis patients and 152 controls. Among the machine learning models, the CNN achieved the highest area under the receiver operating characteristic curve (0.993), with a precision of 0.965 and recall of 0.978, compared with 0.879 and 0.981 for the Naive Bayes and Random Forest, respectively (precision 0.787 and 0.958, and recalls 0.878 and 0.827). The precision by ICD codes for cirrhosis was 0.883 and recall was 0.978.

CONCLUSIONS

A CNN model trained on discharge summaries identified cirrhosis patients with high precision and recall. This approach for phenotyping cirrhosis in the EHR may provide a more accurate assessment of disease burden in a variety of studies.

Implementing a Novel Interprofessional Clinical Informatics Curriculum

A novel interprofessional clinical informatics curriculum was developed, piloted, and implemented, using an academic medical record. Targeted learners included undergraduate, graduate, and professional students across five health science colleges. A team of educators and practitioners representing those five health science colleges was formed in 2016, to design, develop, and refine educational modules covering the essentials of clinical informatics. This innovative curriculum consists of 10 online learning modules and 18 unique imbedded exercises that use standardized patient charts and tailored user views. The exercises allow learners to adopt the role of various providers who document in EMRs. Students are exposed to the unique perspectives of an attending physician, nurse, radiological technician, and health information manager, with the goal of developing knowledge and skills necessary for efficient and effective interprofessional communication within the EMR. The campus-wide clinical informatics curriculum is online, flexible, asynchronous, and well-established within each college, allowing faculty to select and schedule content based on discipline-specific learner and course needs. Program modifications over the past 4 years have correlated with a positive impact on the students' experience.

An Innovative Approach to Remote Electronic Health Onboarding Record Education Amid a Global Pandemic

The COVID-19 pandemic required social and physical distancing to reduce the spread of disease. The reduction in meeting sizes made it difficult to offer traditional in-person EHR training to new and transferring employees. This paper aims to share how one nurse educator team used an innovative approach to transition traditional EHR onboarding education to synchronous remote learning during the global pandemic. Participants in the remote learning course (n = 94) were compared with those who had previously completed the traditional course (n = 110). Postcourse evaluations for each group were comparable. Remote learning participants found the technology conducive to training and reported higher scores for locating and reviewing patient information than those in the traditional course. Providing remote EHR education is comparable with traditional classroom education. Remote learning provided a safe, effective way to onboard new staff during the pandemic.

Facilitating the Implementation of Standardized Care Plans in Municipal Healthcare

Standardized care plans have the potential to enhance the quality of nursing records in terms of content and completeness, thereby better supporting workflow, easing the documentation process, facilitating continuity of care, and permitting systematic data gathering to build evidence from practice. Despite these potential benefits, there may be challenges associated with the successful adoption and use of standardized care plans in municipal healthcare information practices. Using a participatory approach, two workshops were conducted with nurses and nursing leaders (n = 11) in two Norwegian municipalities, with the objective of identifying success criteria for the adoption and integration of standardized care plans into practice. Three themes were found to describe the identified success criteria: (1) "facilitating system level support for nurses' workflow"; (2) "engaged individuals creating a culture for using standardized care plans"; and (3) "developing system level safety nets." The findings suggest success criteria that could be useful to address to facilitate the integration of standardized care plans in municipal healthcare information practice and provide useful knowledge for those working with implementation and further development of standardized care plans.

Use of electronic health records to support a public health response to the COVID-19 pandemic in the United States: a perspective from 15 academic medical centers

Our goal is to summarize the collective experience of 15 organizations in dealing with uncoordinated efforts that result in unnecessary delays in understanding, predicting, preparing for, containing, and mitigating the COVID-19 pandemic in the US. Response efforts involve the collection and analysis of data corresponding to healthcare organizations, public health departments, socioeconomic indicators, as well as additional signals collected directly from individuals and communities. We focused on electronic health record (EHR) data, since EHRs can be leveraged and scaled to improve clinical care, research, and to inform public health decision-making. We outline the current challenges in the data ecosystem and the technology infrastructure that are relevant to COVID-19, as witnessed in our 15 institutions. The infrastructure includes registries and clinical data networks to support population-level analyses. We propose a specific set of strategic next steps to increase interoperability, overall organization, and efficiencies.

DrugWAS: Leveraging drug-wide association studies to facilitate drug repurposing for COVID-19

Importance: There is an unprecedented need to rapidly identify safe and effective treatments for the novel coronavirus disease 2019 (COVID-19). Objective: To systematically investigate if any of the available drugs in Electronic Health Record (EHR), including prescription drugs and dietary supplements, can be repurposed as potential treatment for COVID-19. Design, Setting, and Participants: Based on a retrospective cohort analysis of EHR data, drug-wide association studies (DrugWAS) were performed on COVID-19 patients at Vanderbilt University Medical Center (VUMC). For each drug study, multivariable logistic regression with overlap weighting using propensity score was applied to estimate the effect of drug exposure on COVID-19 disease outcomes. Exposures: Patient exposure to a drug during 1-year prior to the pandemic and COVID-19 diagnosis was chosen as exposure of interest. Natural language processing was employed to extract drug information from clinical notes, in addition to the prescription drug data available in structured format. Main Outcomes and Measures: All-cause of death was selected as primary outcome. Hospitalization, admission to the intensive care unit (ICU), and need for mechanical ventilation were identified as secondary outcomes. Results: The study included 7,768 COVID-19 patients, of which 509 (6.55%) were hospitalized, 82 (1.06%) were admitted to ICU, 64 (0.82%) received mechanical ventilation, and 90 (1.16%) died. Overall, 15 drugs were significantly associated with decreased COVID-19 severity. Previous exposure to either Streptococcus pneumoniae vaccines (adjusted odds ratio [OR], 0.38; 95% CI, 0.14-0.98), diphtheria toxoid vaccine (OR, 0.39; 95% CI, 0.15-0.98), and tetanus toxoid vaccine (OR, 0.39; 95% CI, 0.15-0.98) were significantly associated with a decreased risk of death (primary outcome). Secondary analyses identified several other significant associations showing lower risk for COVID-19 outcomes: 2 vaccines (acellular pertussis, Streptococcus pneumoniae), 3 dietary supplements (turmeric extract, flaxseed extract, omega-3 fatty acids), methylprednisolone acetate, pseudoephedrine, ethinyl estradiol, estradiol, ibuprofen, and fluticasone. Conclusions and Relevance: This cohort study leveraged EHR data to identify a list of drugs that could be repurposed to improve COVID-19 outcomes. Further randomized clinical trials are needed to investigate the efficacy of the proposed drugs.

Data Quality Challenges in a Learning Health System

This paper discusses the topic of data quality, which concerns the global research and business community and constitutes a challenging task. The data quality prerequisite becomes even more critical when it pertains to critical and sensitive data, such as the healthcare domain data. To begin with, the paper outlines the basic definitions and concepts of data quality and its dimensions. The related research work on data quality assessment is presented and our approach for data quality assurance is introduced. This approach is implemented in our designed cloud platform, called MODELHealth, which is intended for supporting clinical work and administrative decision-making process.

Electronic Health Record Implementation: A Review of Resources and Tools

Implementing an electronic health record (EHR) can be a difficult task to take on and planning the process is of utmost importance to minimize errors. Evaluating the selection criteria and implementation plan of an EHR system, intending interoperability, confidentiality, availability, and integrity of the patient health information data, while ensuring timely, accurate, and regulatory compliant generation of reports is a critical task.

This article discusses the selection and implementation plan that will primarily consist of assessing existing institutional workflows for each department, and it outlines the necessities and inclinations of the institution to include in the EHR system for the organization to function properly. Resources and tools are included to assist in the selection of the product as well as ideas on how to train staff and evaluate staff readiness. Regulatory requirements are also included for consideration during the initial process.

EHR increases the logistic productivity of workflows and offers a safer way to care for patients. To ensure efficiency, there is a series of steps the provider’s staff must follow to ensure proper implementation and handling of the EHR system. Before using the implemented EHR, it is recommended to have a testing protocol in place to ensure areas of possible staff confusion are identified and controlled. Using a proper implementation strategy for a new EHR system can facilitate success, minimize delays, and increase health care worker’s satisfaction and decrease the chances of usability being compromised.

Novel electronic health record (EHR) education intervention in large healthcare organization improves quality, efficiency, time, and impact on burnout

A novel approach to advanced electronic health record (EHR) skills training was developed in a large healthcare organization to improve high-quality EHR documentation, while reducing stressors linked to physician burnout.The 3-day intensive EHR education intervention covered best practices in EHR documentation and physician well-being. The specialty physician faculty used interactive teaching including demonstration, facilitation, and individual coaching. Laptops were provided for hands-on practice. Mixed-method evaluation included real-time feedback, daily surveys, and post-activity surveys to measure participant learning and satisfaction, and also collection of performance data from the EHR to measure use of order sets designed to improve quality of care.Since 2014, 46 trainings were held with 3500 physicians. Most physicians (85%-98% across all programs) reported improved quality, readability, and clinical accuracy of documentation; fewer medical errors; and increased efficiency in chart review and data retrieval due to the training. Seventy-eight per cent estimated a time savings of 4 to 5 minutes or more per hour. Physician performance data from the EHR showed significant improvement in use of order sets for several critical health conditions such as sepsis, stroke, and chest pain of possible cardiac cause.This advanced EHR training for physicians was well-received and improved physicians' use of several order sets designed to improve quality of care. EHR training programs such as this may have impact on the safety, quality, accuracy, and timeliness of care and may also help reduce physician burnout by improving critical skills and reducing time interfacing with all aspects of a patient's health record.

Transition to a new electronic health record and pediatric medication safety: lessons learned in pediatrics within a large academic health system

Objective

While the electronic health record (EHR) has become a standard of care, pediatric patients pose a unique set of risks in adult-oriented systems. We describe medication safety and implementation challenges and solutions in the pediatric population of a large academic center transitioning its EHR to Epic.

Methods

Examination of the roll-out of a new EHR in a mixed neonatal, pediatric and adult tertiary care center with staggered implementation. We followed the voluntarily reported medication error rate for the neonatal and pediatric subsets and specifically monitored the first 3 months after the roll-out of the new EHR. Data was reviewed and compiled by theme.

Results

After implementation, there was a 5-fold increase in the overall number of medication safety reports; by the third month the rate of reported medication errors had returned to baseline. The majority of reports were near misses. Three major safety themes arose: (1) enterprise logic in rounding of doses and dosing volumes; (2) ordering clinician seeing a concentration and product when ordering medications; and (3) the need for standardized dosing units through age contexts created issues with continuous infusions and pump library safeguards.

Conclusions

Future research and work need to be focused on standards and guidelines on implementing an EHR that encompasses all age contexts.

Using big data from health records from four countries to evaluate chronic disease outcomes: a study in 114 364 survivors of myocardial infarction

AIMS

To assess the international validity of using hospital record data to compare long-term outcomes in heart attack survivors.

METHODS AND RESULTS

We used samples of national, ongoing, unselected record sources to assess three outcomes: cause death; a composite of myocardial infarction (MI), stroke, and all-cause death; and hospitalized bleeding. Patients aged 65 years and older entered the study 1 year following the most recent discharge for acute MI in 2002-11 [n = 54 841 (Sweden), 53 909 (USA), 4653 (England), and 961 (France)]. Across each of the four countries, we found consistent associations with 12 baseline prognostic factors and each of the three outcomes. In each country, we observed high 3-year crude cumulative risks of all-cause death (from 19.6% [England] to 30.2% [USA]); the composite of MI, stroke, or death [from 26.0% (France) to 36.2% (USA)]; and hospitalized bleeding [from 3.1% (France) to 5.3% (USA)]. After adjustments for baseline risk factors, risks were similar across all countries [relative risks (RRs) compared with Sweden not statistically significant], but higher in the USA for all-cause death [RR USA vs. Sweden, 1.14 (95% confidence interval 1.04-1.26)] and hospitalized bleeding [RR USA vs. Sweden, 1.54 (1.21-1.96)].

CONCLUSION

The validity of using hospital record data is supported by the consistency of estimates across four countries of a high adjusted risk of death, further MI, and stroke in the chronic phase after MI. The possibility that adjusted risks of mortality and bleeding are higher in the USA warrants further study.

Comparing electronic health record portals to obtain patient-entered family health history in primary care

BACKGROUND

There is growing interest in developing systems to overcome barriers for acquiring and interpreting family health histories in primary care.

OBJECTIVE

To examine the capacity of three different electronic portals to collect family history from patients and deposit valid data in an electronic health record (EHR).

DESIGN

Pilot trial.

PARTICIPANTS, INTERVENTION

Patients were enrolled from four primary care practices and were asked to collect family health history before a physical exam using either telephone-based interactive voice response (IVR) technology, a secure Internet portal, or a waiting room laptop computer, with portal assigned by practice. Intervention practices were compared to a "usual care" practice, where there was no standard workflow to document family history (663 participants in the three intervention arms were compared to 296 participants from the control practice).

MAIN MEASURES

New documentation of any family history in a coded EHR field within 30 days of the visit. Secondary outcomes included participation rates and validity.

KEY RESULTS

Demographics varied by clinic. Documentation of new family history data was significantly higher, but modest, in each of the three intervention clinics (7.5 % for IVR clinic, 20.3 % for laptop clinic, and 23.1 % for patient portal clinic) versus the control clinic (1.7 %). Patient-entered data on common conditions in first degree relatives was confirmed as valid by a genetic counselor for the majority of cases (ranging from 64 to 82 % in the different arms).

CONCLUSIONS

Within primary care practices, valid patient entered family health history data can be obtained electronically at higher rates than a standard of care that depends on provider-entered data. Further research is needed to determine how best to match different portals to individual patient preference, how the tools can best be integrated with provider workflow, and to assess how they impact the use of screening and prevention.

Utility of Syndromic Surveillance Using Novel Clinical Data Sources

Objective

To document the current evidence base for the use of electronic health record (EHR) data for syndromic surveillance using emergency department, urgent care clinic, hospital inpatient, and ambulatory clinical care data.

Introduction

Historically, syndromic surveillance has primarily involved the use of near real-time data sent from hospital emergency department (EDs) and urgent care (UC) clinics to public health agencies. The use of data from inpatient and ambulatory settings is now gaining interest and support throughout the United States, largely as a result of the Stage 2 and 3 Meaningful Use regulations [1]. Questions regarding the feasibility and utility of applying a syndromic approach to these data sources are hampering the development of systems to collect, analyze, and share this potentially valuable information. Solidifying the evidence base and communicating the results to the public health surveillance community may help to initiate and build support for using these data to advance surveillance functions.

Methods

We conducted a literature search in the published and grey literature that scanned for relevant articles in the Google Scholar, Pub Med, and EBSCO Information Services databases. Search terms included: “inpatient/ambulatory electronic health record”; “ambulatory/inpatient/hospital/outpatient/chronic disease syndromic surveillance”; and “EHR syndromic surveillance”. Information gleaned from each article included data use, data elements extracted, and data quality indicators. In addition, several stakeholders who provided input on the September 2012 ISDS Recommendations [2] also provided articles that were incorporated into the literature review.

ISDS also invited speakers from existing inpatient and ambulatory syndromic surveillance systems to give webinar presentations on how they are using data from these novel sources.

Results

The number of public health agencies (PHAs) routinely receiving ambulatory and inpatient syndromic surveillance data is substantially smaller than the number receiving ED and UC data. Some health departments, private medical organizations (including HMOs), and researchers are conducting syndromic surveillance and related research with health data captured in these clinical settings [2].

In inpatient settings, many of the necessary infrastructure and analytic tools are already in place. Syndromic surveillance with inpatient data has been used for a range of innovative uses, from monitoring trends in myocardial infarction in association with risk factors for cardiovascular disease [3] to tracking changes in incident-related hospitalizations following the 2011 Joplin, Missouri tornado [3].

In contrast, ambulatory systems face a need for new infrastructure, as well as pose a data volume challenge. The existing systems vary in how they address data volume and what types of encounters they capture. Ambulatory data has been used for a variety of uses, from monitoring gastrointestinal infectious disease [3], to monitoring behavioral health trends in a population, while protecting personal identities [4].

Conclusions

The existing syndromic surveillance systems and substantial research in the area indicate an interest in the public health community in using hospital inpatient and ambulatory clinical care data in new and innovative ways. However, before inpatient and ambulatory syndromic surveillance systems can be effectively utilized on a large scale, the gaps in knowledge and the barriers to system development must be addressed. Though the potential use cases are well documented, the generalizability to other settings requires additional research, workforce development, and investment.

Recommendations for Syndromic Surveillance Using Inpatient and Ambulatory EHR Data

Objective

To develop national Stage 2 Meaningful Use (MUse) recommendations for syndromic surveillance using hospital inpatient and ambulatory clinical care electronic health record (EHR) data.

Introduction

MUse will make EHR data increasingly available for public health surveillance. For Stage 2, the Centers for Medicare & Medicaid Services (CMS) regulations will require hospitals and offer an option for eligible professionals to provide electronic syndromic surveillance data to public health. Together, these data can strengthen public health surveillance capabilities and population health outcomes (Figure 1).

To facilitate the adoption and effective use of these data to advance population health, public health priorities and system capabilities must shape standards for data exchange. Input from all stakeholders is critical to ensure the feasibility, practicality, and, hence, adoption of any recommendations and data use guidelines.

Methods

ISDS, in collaboration with the Division of Informatics Solutions and Operations at the Centers for Disease Control and Prevention (CDC), and HLN Consulting, convened a multi-stakeholder Work-group of clinicians, technologists, epidemiologists, and public health officials with expertise in syndromic surveillance. Recommended MUse guidelines were developed by performing an environmental scan of current practice and by using an iterative, expert and community input-driven process. The Workgroup developed initial guidelines and then solicited and received feedback from the stakeholder community via interview, e-mail, and structured surveys. Stakeholder feedback was analyzed using quantitative and qualitative methods and used to revise the recommendations.

Results

The MUse Workgroup defined electronic syndromic surveillance (ESS) characteristics. Specifically, data are characterized by their timeliness, sensitivity rather than specificity, population focus, limited personally identifiable information, and inclusion of all patient encounters within a specific healthcare setting (e.g., emergency department, inpatient, outpatient). Based on stakeholder input (n=125) and Workgroup expertise, the guidelines identify priority syndromic surveillance uses that can assist with:

Monitoring population health;

Informing public health services; and

Informing interventions, health education, and policy by characterizing the burden of chronic disease and health disparities.

Similarly, the Workgroup identified data elements to support these uses in the hospital inpatient setting and possibly in the ambulatory care setting. They were aligned to previously identified emergency department and urgent care center data elements and Stage 1–2 clinical MUse objectives. Core data elements (required for certification) cover treating facility; patient demographics; subjective and objective clinical findings, including chief complaint, body mass index, smoking history, diagnoses; and outcomes. Other data elements were designated as extended (not required for certification) or future (for future consideration). The data elements and their specifications are subject to change based on applicable state and local laws and practices.

Based on their findings and recommended guidelines detailed in the report, the Workgroup also identified community activities and additional investments that would best support public health agencies in using EHR technology with syndromic surveillance methodologies.

Conclusions

The widespread adoption of EHRs, catalyzed by MUse, has the potential to improve population health. By identifying and describing potential ESS uses of new sources of EHR data and associated data elements with the greatest utility for public health, the recommendations set forth by the ISDS MUse Workgroup will serve to facilitate the adoption of MUse policy by both healthcare and public health agencies.

Healthcare provider attitudes towards the problem list in an electronic health record: a mixed-methods qualitative study

BACKGROUND

The problem list is a key part of the electronic health record (EHR) that allows practitioners to see a patient's diagnoses and health issues. Yet, as the content of the problem list largely represents the subjective decisions of those who edit it, patients' problem lists are often unreliable when shared across practitioners. The lack of standards for how the problem list is compiled in the EHR limits its effectiveness in improving patient care, particularly as a resource for clinical decision support and population management tools. The purpose of this study is to discover practitioner opinions towards the problem list and the logic behind their decisions during clinical situations.

MATERIALS AND METHODS

An observational cross-sectional study was conducted at two major Boston teaching hospitals. Practitioners' opinions about the problem list were collected through both in-person interviews and an online questionnaire. Questions were framed using vignettes of clinical scenarios asking practitioners about their preferred actions towards the problem list.

RESULTS

These data confirmed prior research that practitioners differ in their opinions over managing the problem list, but in most responses to a questionnaire, there was a common approach among the relative majority of respondents. Further, basic demographic characteristics of providers (age, medical experience, etc.) did not appear to strongly affect attitudes towards the problem list.

CONCLUSION

The results supported the premise that policies and EHR tools are needed to bring about a common approach. Further, the findings helped identify what issues might benefit the most from a defined policy and the level of restriction a problem list policy should place on the addition of different types of information.

Transmitting and processing electronic prescriptions: experiences of physician practices and pharmacies

OBJECTIVE

A core feature of e-prescribing is the electronic exchange of prescription data between physician practices and pharmacies, which can potentially improve the efficiency of the prescribing process and reduce medication errors. Barriers to implementing this feature exist, but they are not well understood. This study's objectives were to explore recent physician practice and pharmacy experiences with electronic transmission of new prescriptions and renewals, and identify facilitators of and barriers to effective electronic transmission and pharmacy e-prescription processing.

DESIGN

Qualitative analysis of 114 telephone interviews conducted with representatives from 97 organizations between February and September 2010, including 24 physician practices, 48 community pharmacies, and three mail-order pharmacies actively transmitting or receiving e-prescriptions via Surescripts.

RESULTS

Practices and pharmacies generally were satisfied with electronic transmission of new prescriptions but reported that the electronic renewal process was used inconsistently, resulting in inefficient workarounds for both parties. Practice communications with mail-order pharmacies were less likely to be electronic than with community pharmacies because of underlying transmission network and computer system limitations. While e-prescribing reduced manual prescription entry, pharmacy staff frequently had to complete or edit certain fields, particularly drug name and patient instructions.

CONCLUSIONS

Electronic transmission of new prescriptions has matured. Changes in technical standards and system design and more targeted physician and pharmacy training may be needed to address barriers to e-renewals, mail-order pharmacy connectivity, and pharmacy processing of e-prescriptions.

Beyond health information technology: critical factors necessary for effective diabetes disease management

BACKGROUND

Electronic health records (EHRs) have been implemented throughout the United States with varying degrees of success. Past EHR implementation experiences can inform health systems planning to initiate new or expand existing EHR systems. Key "critical success factors," e.g., use of disease registries, workflow integration, and real-time clinical guideline support, have been identified but not fully tested in practice.

METHODS

A pre/postintervention cohort analysis was conducted on 495 adult patients selected randomly from a diabetes registry and followed for 6 years. Two intervention phases were evaluated: a "low-dose" period targeting primary care provider (PCP) and patient education followed by a "high-dose" EHR diabetes management implementation period, including a diabetes disease registry and office workflow changes, e.g., diabetes patient preidentification to facilitate real-time diabetes preventive care, disease management, and patient education.

RESULTS

Across baseline, "low-dose," and "high-dose" postintervention periods, a significantly greater proportion of patients (a) achieved American Diabetes Association (ADA) guidelines for control of blood pressure (26.9 to 33.1 to 43.9%), glycosylated hemoglobin (48.5 to 57.5 to 66.8%), and low-density lipoprotein cholesterol (33.1 to 44.4 to 56.6%) and (b) received recommended preventive eye (26.2 to 36.4 to 58%), foot (23.4 to 40.3 to 66.9%), and renal (38.5 to 53.9 to 71%) examinations or screens.

CONCLUSIONS

Implementation of a fully functional, specialized EHR combined with tailored office workflow process changes was associated with increased adherence to ADA guidelines, including risk factor control, by PCPs and their patients with diabetes. Incorporation of previously identified "critical success factors" potentially contributed to the success of the program, as did use of a two-phase approach.