New Coding Guidelines Reduce Emergency Department Note Bloat But More Work Is Needed.

STUDY OBJECTIVE: The length and redundancy of notes authored by clinicians has significantly increased, giving rise to the term "note bloat." We analyzed the impact of new coding guidelines and documentation best practices on the length of emergency department (ED) notes and the amount of time clinicians spent documenting. METHODS: In a large, multisite health care delivery organization, we retrospectively evaluated the length of all ED provider notes and the amount of time clinicians spent documenting between February 2018 and June 2023. In January 2023, we implemented changes to the standardized note template to align with the new coding guidelines from the American Medical Association and the Centers for Medicare & Medicaid Services. The primary outcomes were the length of provider notes and the amount of time spent documenting. RESULTS: Our study sample consisted of 1,679,762 ED provider notes. Six months after the intervention, the average note length decreased by 872 words (95% confidence interval 867 to 877 words), whereas the amount of time clinicians spent documenting did not change. CONCLUSIONS: Embracing new guidelines and practices, we reduced the length of ED provider notes by 872 words. Despite this, the time clinicians spent documenting did not change significantly. We provide an early report of success in reducing note bloat in the ED to help guide future efforts to reduce overall documentation burden.

Analyzing Patient-Provided Responses to Improve Collection of Health Equity Data Elements.

Self-report is purported to be the gold standard for collecting demographic information. Many entry forms include a free-text "write-in" option in addition to structured responses. Balancing the flexibility of free-text with the value of collecting data in a structured format is a challenge if the data are to be useful for measuring and mitigating health disparities. While much work has been done to improve collection of race and ethnicity information, how to best collect data related to sexual and gender minority status and military veteran status has been less commonly studied. We analyzed 3,381 patient-provided free-text responses collected via a patient portal for gender identity, sexual orientation, pronouns, and veteran experiences. We identified common responses to better understand our patient population and help improve future iterations of data collection tools.

Overcoming technical and cultural challenges to delivering equitable care for LGBTQ+ individuals in a rural, underserved area.

The lesbian, gay, bisexual, transgender, queer, or questioning (LGBTQ+) community is vulnerable to health-care disparities. Many health-care organizations are working to collect sexual orientation and gender identity in their electronic health records (EHRs), with the goal of providing more inclusive care to their LGBTQ+ patients. There are significant human and technical barriers to making these efforts successful. Based on our 5-year experience at Geisinger (an integrated health system located in a rural, generally conservative area), this case report provides insights to overcome challenges in 4 critical areas: (1) enabling the EHR to collect and use information to support the health-care needs of LGBTQ+ patients, (2) building a culture of awareness and caring, empowering members of the health-care team to break down barriers of misunderstanding and mistrust, (3) developing services to support the needs of LGBTQ+ patients, and (4) partnering with local communities to become a trusted health-care provider.

Bringing Cultural Competency to the EHR: Lessons Learned Providing Respectful, Quality Care to the LGBTQ Community.

The lesbian, gay, bisexual, transgender, queer (LGBTQ) community is vulnerable to healthcare disparities. Many healthcare organizations are contemplating efforts to collect sexual orientation and gender identity in the electronic health record (EHR), with a goal of providing more respectful, inclusive, high-quality care to their LGBTQ patients. There are significant human and technical barriers that must be overcome to make these efforts successful. Based on our four-year experience at Geisinger (an integrated health system located in a rural, generally conservative area), we provide insights to overcome challenges in two critical areas: 1) enabling the EHR to collect and use information to support the healthcare needs of LGBTQ patients, and 2) building a culture of awareness and caring, empowering members of the healthcare team to break down barriers of misunderstanding and mistrust.

Medication stewardship using computerized clinical decision support: A case study on intravenous immunoglobulins.

Background: Healthcare delivery organizations face increasing pressure to manage the use of medications in terms of safety, waste reduction, and cost containment. Objective: To describe a computerized provider order entry (CPOE) system intervention to optimize use of a commonly ordered, high-cost therapeutic: intravenous immune globulin (IVIG). Design: Description of IVIG order configuration, medication use patterns, and subsequent order set configuration development in a CPOE system. Measurements: IVIG orders were extracted from the CPOE system before and after the implementation of a specialty orderset to determine the indications for use, dosing, and duration of therapy. Orders were compared to a theoretical dosing schedule created from published evidence and data from a prior medication use evaluation. Results: During 36 months before the implementation of the IVIG order set, 1965 IVIG orders were reviewed. The prescribed IVIG dose varied considerably from the expected dose (mean = -1.8, range = -4.9-1.5). In the 27 months after order set implementation, 848 IVIG orders were reviewed. The prescribed IVIG dose was closer to the expected dose (mean = -1.2, range = -3.9-2.6, P < .0001). Conclusions: Order configuration processes are cumbersome and time-consuming, but can be streamlined to enhance a medication's usage in the healthcare system. A better understanding of institution-specific ordering patterns may facilitate more efficient and effective order configuration and optimize drug use.

Challenges with quality of race and ethnicity data in observational databases.

OBJECTIVE: We sought to assess the quality of race and ethnicity information in observational health databases, including electronic health records (EHRs), and to propose patient self-recording as an improvement strategy. MATERIALS AND METHODS: We assessed completeness of race and ethnicity information in large observational health databases in the United States (Healthcare Cost and Utilization Project and Optum Labs), and at a single healthcare system in New York City serving a racially and ethnically diverse population. We compared race and ethnicity data collected via administrative processes with data recorded directly by respondents via paper surveys (National Health and Nutrition Examination Survey and Hospital Consumer Assessment of Healthcare Providers and Systems). Respondent-recorded data were considered the gold standard for the collection of race and ethnicity information. RESULTS: Among the 160 million patients from the Healthcare Cost and Utilization Project and Optum Labs datasets, race or ethnicity was unknown for 25%. Among the 2.4 million patients in the single New York City healthcare system's EHR, race or ethnicity was unknown for 57%. However, when patients directly recorded their race and ethnicity, 86% provided clinically meaningful information, and 66% of patients reported information that was discrepant with the EHR. DISCUSSION: Race and ethnicity data are critical to support precision medicine initiatives and to determine healthcare disparities; however, the quality of this information in observational databases is concerning. Patient self-recording through the use of patient-facing tools can substantially increase the quality of the information while engaging patients in their health. CONCLUSIONS: Patient self-recording may improve the completeness of race and ethnicity information.

Interventions to increase patient portal use in vulnerable populations: a systematic review.

BACKGROUND: More than 100 studies document disparities in patient portal use among vulnerable populations. Developing and testing strategies to reduce disparities in use is essential to ensure portals benefit all populations. OBJECTIVE: To systematically review the impact of interventions designed to: (1) increase portal use or predictors of use in vulnerable patient populations, or (2) reduce disparities in use. MATERIALS AND METHODS: A librarian searched Ovid MEDLINE, EMBASE, CINAHL, and Cochrane Reviews for studies published before September 1, 2018. Two reviewers independently selected English-language research articles that evaluated any interventions designed to impact an eligible outcome. One reviewer extracted data and categorized interventions, then another assessed accuracy. Two reviewers independently assessed risk of bias. RESULTS: Out of 18 included studies, 15 (83%) assessed an intervention's impact on portal use, 7 (39%) on predictors of use, and 1 (6%) on disparities in use. Most interventions studied focused on the individual (13 out of 26, 50%), as opposed to facilitating conditions, such as the tool, task, environment, or organization (SEIPS model). Twelve studies (67%) reported a statistically significant increase in portal use or predictors of use, or reduced disparities. Five studies (28%) had high or unclear risk of bias. CONCLUSION: Individually focused interventions have the most evidence for increasing portal use in vulnerable populations. Interventions affecting other system elements (tool, task, environment, organization) have not been sufficiently studied to draw conclusions. Given the well-established evidence for disparities in use and the limited research on effective interventions, research should move beyond identifying disparities to systematically addressing them at multiple levels.

Technology Access, Technical Assistance, and Disparities in Inpatient Portal Use.

BACKGROUND: Disadvantaged populations, including minorities and the elderly, use patient portals less often than relatively more advantaged populations. Limited access to and experience with technology contribute to these disparities. Free access to devices, the Internet, and technical assistance may eliminate disparities in portal use. OBJECTIVE: To examine predictors of frequent versus infrequent portal use among hospitalized patients who received free access to an iPad, the Internet, and technical assistance. MATERIALS AND METHODS: This subgroup analysis includes 146 intervention-arm participants from a pragmatic randomized controlled trial of an inpatient portal. The participants received free access to an iPad and inpatient portal while hospitalized on medical and surgical cardiac units, together with hands-on help using them. We used logistic regression to identify characteristics predictive of frequent use. RESULTS: More technology experience (adjusted odds ratio [OR] = 5.39, p = 0.049), less severe illness (adjusted OR = 2.07, p = 0.077), and private insurance (adjusted OR = 2.25, p = 0.043) predicted frequent use, with a predictive performance (area under the curve) of 65.6%. No significant differences in age, gender, race, ethnicity, level of education, employment status, or patient activation existed between the frequent and infrequent users in bivariate analyses. Significantly more frequent users noticed medical errors during their hospital stay. DISCUSSION AND CONCLUSION: Portal use was not associated with several sociodemographic characteristics previously found to limit use in the inpatient setting. However, limited technology experience and high illness severity were still barriers to frequent use. Future work should explore additional strategies, such as enrolling health care proxies and improving usability, to reduce potential disparities in portal use.

Engaging hospital patients in the medication reconciliation process using tablet computers.

Objective: Unintentional medication discrepancies contribute to preventable adverse drug events in patients. Patient engagement in medication safety beyond verbal participation in medication reconciliation is limited. We conducted a pilot study to determine whether patients' use of an electronic home medication review tool could improve medication safety during hospitalization. Materials and Methods: Patients were randomized to use a tool before or after hospital admission medication reconciliation to review and modify their home medication list. We assessed the quantity, potential severity, and potential harm of patients' and clinicians' medication changes. We also surveyed clinicians to assess the tool's usefulness. Results: Of 76 patients approached, 65 (86%) participated. Forty-eight (74%) made changes to their home medication list [before: 29 (81%), after: 19 (66%), p = .170]. Before group participants identified 57 changes that clinicians subsequently missed on admission medication reconciliation. Thirty-nine (74%) had a significant or greater potential severity, and 19 (36%) had a greater than 50-50 chance of harm. After group patients identified 68 additional changes to their reconciled medication lists. Fifty-one (75%) had a significant or greater potential severity, and 33 (49%) had a greater than 50-50 chance of harm. Clinicians reported believing that the tool would save time, and patients would supply useful information. Discussion: The results demonstrate a high willingness of patients to engage in medication reconciliation, and show that patients were able to identify important medication discrepancies and often changes that clinicians missed. Conclusion: Engaging patients in admission medication reconciliation using an electronic home medication review tool may improve medication safety during hospitalization.

Challenges Associated With Using Large Data Sets for Quality Assessment and Research in Clinical Settings.

The rapidly expanding use of electronic records in health-care settings is generating unprecedented quantities of data available for clinical, epidemiological, and cost-effectiveness research. Several challenges are associated with using these data for clinical research, including issues surrounding access and information security, poor data quality, inconsistency of data within and across institutions, and a paucity of staff with expertise to manage and manipulate large clinical data sets. In this article, we describe our experience with assembling a data-mart and conducting clinical research using electronic data from four facilities within a single hospital network in New York City. We culled data from several electronic sources, including the institution's admission-discharge-transfer system, cost accounting system, electronic health record, clinical data warehouse, and departmental records. The final data-mart contained information for more than 760,000 discharges occurring from 2006 through 2012. Using categories identified by the National Institutes of Health Big Data to Knowledge initiative as a framework, we outlined challenges encountered during the development and use of a domain-specific data-mart and recommend approaches to overcome these challenges.

Measuring Mortality Information in Clinical Data Warehouses.

The ability to track and report long-term outcomes, especially mortality, is essential for advancing clinical research. The purpose of this study was to present a framework for assessing the quality of mortality information in clinical research databases. Using the clinical data warehouse (CDW) at Columbia University Medical Center as a case study, we measured: 1) agreement in vital status between our institution's patient registration system and the U.S. Social Security Administration's Death Master File (DMF), 2) the proportion of patients marked as deceased according to the DMF records who had subsequent visits to our institution, and 3) the proportion of patients still living according to Columbia's CDW who were over 100 and 120 years of age. Of 33,295 deaths recorded in our institution's patient registration system, 13,167 (39.5%) did not exist in the DMF. Of 315,037 patients in our CDW who marked as deceased according to the DMF, 2.1% had a subsequent clinical encounter at our institution. The proportion of patients still living according to Columbia's CDW who were over 100 and 120 years of age was 43.6% and 43.1%, respectively. These measures may be useful to other clinical research investigators seeking to assess the quality of mortality data (1-4).

A Global Analysis of Approaches to Sharing Clinical Data with Patients.

Engaging patients in their care has become a topic of increasing importance, and enabling patients to have access to their clinical data is a key aspect of such engagement. To investigate on an international scale the current state of approaches for providing patients with access to their own clinical information, individuals from 16 countries, across six continents, participated in cross-sectional semi-structured interviews. Interview questions focused on social and cultural influences that affected patient engagement activities, government support for current and planned initiatives, data ownership models, and technical issues. Substantive initiatives for providing information to patients in the majority of countries interviewed are present; however, these initiatives were diverse in nature and stage of implementation. Efforts to improve patient access to data are active on a global-scale. There are many open questions about best practices and much can be learned by adopting an international perspective to guide future implementation efforts.

An Assessment of Family History Information Captured in an Electronic Health Record.

Family history is considered a core element of clinical care. In this study we assessed the quality of family history data captured in an established commercial electronic health record (EHR) at a large academic medical center. Because the EHR had no centralized location to store family history information, it was collected as part of clinical notes in structured or free-text format. We analyzed differences between 10,000 free-text and 9,121 structured family history observations. Each observation was classified according to disease presence/absence and family member affected (e.g., father, mother, etc.). The structured notes did not collect a complete family history as defined by standards endorsed by the U.S. Agency for Healthcare Research and Quality; the free-text notes contained more information than the structured notes, but still not enough to be considered "complete." Several barriers remain for collecting complete, useful family history data in electronic health records.

An integrated billing application to streamline clinician workflow.

Between 2008 and 2010, our academic medical center transitioned to electronic provider documentation using a commercial electronic health record system. For attending physicians, one of the most frustrating aspects of this experience was the system's failure to support their existing electronic billing workflow. Because of poor system integration, it was difficult to verify the supporting documentation for each bill and impractical to track whether billable notes had corresponding charges. We developed and deployed in 2011 an integrated billing application called "iCharge" that streamlines clinicians' documentation and billing workflow, and simultaneously populates the inpatient problem list using billing diagnosis codes. Each month, over 550 physicians use iCharge to submit approximately 23,000 professional service charges for over 4,200 patients. On average, about 2.5 new problems are added to each patient's problem list. This paper describes the challenges and benefits of workflow integration across disparate applications and presents an example of innovative software development within a commercial EHR framework.

Enabling claims-based decision support through non-interruptive capture of admission diagnoses and provider billing codes.

The patient problem list, like administrative claims data, has become an important source of data for decision support, patient cohort identification, and alerting systems. A two-fold intervention to increase capture of problems on the problem list automatically - with minimal disruption to admitting and provider billing workflows - is described. For new patients with no prior data in the electronic health record, the intervention resulted in a statistically significant increase in the number of problems recorded to the problem list (3.8 vs 2.9 problems post-and pre-intervention respectively, p value 2×10(-16)). The majority of problems were recorded in the first 24 hours of admission. The proportion of patients with at least one problem coded to the problem list within the first 24 hours increased from 94% to 98% before and after intervention (chi square 344, p value 2×10(-16)). ICD9 "V codes" connoting circumstances beyond disease were captured at a higher rate post intervention than before. Deyo/Charlson comorbidities derived from problem list data were more similar to those derived from claims data after the intervention than before (Jaccard similarity 0.3 post- vs 0.21 pre-intervention, p value 2×10(-16)). A workflow-sensitive, non-interruptive means of capturing provider-entered codes early in admission can improve both the quantity and content of problems on the patient problem list.

The future state of clinical data capture and documentation: a report from AMIA's 2011 Policy Meeting.

Much of what is currently documented in the electronic health record is in response toincreasingly complex and prescriptive medicolegal, reimbursement, and regulatory requirements. These requirements often result in redundant data capture and cumbersome documentation processes. AMIA's 2011 Health Policy Meeting examined key issues in this arena and envisioned changes to help move toward an ideal future state of clinical data capture and documentation. The consensus of the meeting was that, in the move to a technology-enabled healthcare environment, the main purpose of documentation should be to support patient care and improved outcomes for individuals and populations and that documentation for other purposes should be generated as a byproduct of care delivery. This paper summarizes meeting deliberations, and highlights policy recommendations and research priorities. The authors recommend development of a national strategy to review and amend public policies to better support technology-enabled data capture and documentation practices.

An application for monitoring order set usage in a commercial electronic health record.

Organizations that use electronic health records (EHRs) often maintain a considerable amount of clinical content in the form of order sets, documentation templates, and decision support rules. EHR vendors seldom provide analytic tools for customers to maintain such content and monitor its usage. We developed an application for tracking order sets, documentation templates and clinical alerts in a commercial electronic health record. Using the application, we compared trends in order set creation and usage at two academic medical centers over a three-year period. In January 2012, one medical center had 873 order sets available to clinicians; the other had 787. Approximately 50-75 new order sets were added each year at each medical center. We found that 46% of order sets at the first medical center and 39% at the second medical center were unused over the three-year period.