Publications by authors named "Christoph U Lehmann"

141 Publications

Survey of Hospital Chargemaster Transparency.

Appl Clin Inform 2021 Mar 5;12(2):391-398. Epub 2021 May 5.

Clinical Informatics Center, University of Texas Southwestern Medical Center, Dallas, Texas, United States.

Background:  In January 2019, the Centers for Medicare & Medicaid Services (CMS) required hospitals to list their standard charges (chargemasters) publicly in an effort to increase price transparency in health care. Surveying hospital chargemasters may be informative to assess the implementation of this rule and its utility to consumers.

Objective:  We aimed to compare hospital chargemaster data within a local hospital market where patients would reasonably try to shop or compare services.

Methods:  We identified and aggregated Dallas County hospital chargemasters available in a database compatible format in May 2019. We manually examined a convenience sampling of 10 common laboratory tests, medications, and procedures.

Results:  Thirteen hospital chargemasters were identified. Eleven hospitals had chargemasters available in a database compatible format (xlsx or csv). These 11 chargemasters were aggregated into a single file containing 155,576 chargeable items, prices, and descriptions. We observed heterogeneous names and descriptions of synonymous items across institutions, preventing automated comparisons. The examined items revealed a high variation in charges. The largest charge variation for laboratory tests examined included a 2,606% difference (partial thromboplastin time: $18.70-506.00), for medications an 18,617% difference (5-mg tablet of amlodipine: $0.23-43.05), and for procedures a 2,889% difference (circumcision: $252.00-7,532.10). One institution accounted for 27% of the lowest prices and another accounted for 60% of the highest prices.

Conclusion:  Chargemaster data presentation varied among the hospitals surveyed, making automatic comparison impossible. Chargemaster data are difficult to interpret for health care decisions. Refining the minimum requirements for publishing chargemaster data could increase their utility.
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http://dx.doi.org/10.1055/s-0041-1729168DOI Listing
March 2021

Managing Pandemics with Health Informatics: Successes and Challenges.

Yearb Med Inform 2021 Apr 21. Epub 2021 Apr 21.

Clinical Informatics Center, UT Southwestern, Medical Center, Dallas, TX, USA.

Introduction: The novel COVID-19 pandemic struck the world unprepared. This keynote outlines challenges and successes using data to inform providers, government officials, hospitals, and patients in a pandemic.

Methods: The authors outline the data required to manage a novel pandemic including their potential uses by governments, public health organizations, and individuals.

Results: An extensive discussion on data quality and on obstacles to collecting data is followed by examples of successes in clinical care, contact tracing, and forecasting. Generic local forecast model development is reviewed followed by ethical consideration around pandemic data. We leave the reader with thoughts on the next inevitable outbreak and lessons learned from the COVID-19 pandemic.

Conclusion: COVID-19 must be a lesson for the future to direct us to better planning and preparing to manage the next pandemic with health informatics.
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http://dx.doi.org/10.1055/s-0041-1726478DOI Listing
April 2021

Understanding timely STEMI treatment performance: A 3-year retrospective cohort study using diagnosis-to-balloon-time and care subintervals.

J Am Coll Emerg Physicians Open 2021 Feb 17;2(1):e12379. Epub 2021 Feb 17.

Department of Biostatistics Vanderbilt University Medical Center Nashville Tennessee USA.

Objective: From the perspective of percutaneous coronary intervention (PCI) centers, locations of ST-segment elevation myocardial infarction (STEMI) diagnosis can include a referring facility, emergency medical services (EMS) transporting to a PCI center, or the PCI center's emergency department (ED). This challenges the use of door-to-balloon-time as the primary evaluative measure of STEMI treatment pathways. Our objective was to identify opportunities to improve care by quantifying differences in the timeliness of STEMI treatment mobilization based on the location of the diagnostic ECG.

Methods: This 3-year, single-center, retrospective cohort study classified patients by diagnostic ECG location: referring facility, EMS, or PCI center ED. We quantified door-to-balloon-time and diagnosis-to-balloon-time with its care subintervals.

Results: Of 207 ED STEMI patients, 180 (87%) received PCI. Median diagnosis-to-balloon-times were shortest among the ED-diagnosed (78 minutes [interquartile range (IQR), 61-92]), followed by EMS-identified patients (89 minutes [IQR, 78-122]), and longest among those referred (140 minutes [IQR, 119-160]), reflecting time for transport to the PCI center. Conversely, referred patients had the shortest median door-to-balloon-times (38 minutes [IQR, 34-43]), followed by the EMS-identified (64 minutes [IQR, 47-77]), whereas ED-diagnosed patients had the longest (89 minutes [IQR, 70-114]), reflecting diagnosis and catheterization lab activation frequently occurring before PCI center ED arrival for referred and EMS-identified patients.

Conclusions: Diagnosis-to-balloon-time and its care subintervals are complementary to the traditional door-to-balloon-times as measures of the STEMI treatment process. Together, they highlight opportunities to improve timely identification among ED-diagnosed patients, use of out-of-hospital cath lab activation for EMS-identified patients, and encourage pathways for referred patients to bypass PCI center EDs.
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http://dx.doi.org/10.1002/emp2.12379DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890036PMC
February 2021

Evaluating short-term forecasting of COVID-19 cases among different epidemiological models under a Bayesian framework.

Gigascience 2021 02;10(2)

Lyda Hill Department of Bioinformatics, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.

Background: Forecasting of COVID-19 cases daily and weekly has been one of the challenges posed to governments and the health sector globally. To facilitate informed public health decisions, the concerned parties rely on short-term daily projections generated via predictive modeling. We calibrate stochastic variants of growth models and the standard susceptible-infectious-removed model into 1 Bayesian framework to evaluate and compare their short-term forecasts.

Results: We implement rolling-origin cross-validation to compare the short-term forecasting performance of the stochastic epidemiological models and an autoregressive moving average model across 20 countries that had the most confirmed COVID-19 cases as of August 22, 2020.

Conclusion: None of the models proved to be a gold standard across all regions, while all outperformed the autoregressive moving average model in terms of the accuracy of forecast and interpretability.
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http://dx.doi.org/10.1093/gigascience/giab009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7928884PMC
February 2021

Early Crowdfunding Response to the COVID-19 Pandemic: Cross-sectional Study.

J Med Internet Res 2021 02 9;23(2):e25429. Epub 2021 Feb 9.

Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States.

Background: As the number of COVID-19 cases increased precipitously in the United States, policy makers and health officials marshalled their pandemic responses. As the economic impacts multiplied, anecdotal reports noted the increased use of web-based crowdfunding to defray these costs.

Objective: We examined the web-based crowdfunding response in the early stage of the COVID-19 pandemic in the United States to understand the incidence of initiation of COVID-19-related campaigns and compare them to non-COVID-19-related campaigns.

Methods: On May 16, 2020, we extracted all available data available on US campaigns that contained narratives and were created between January 1 and May 10, 2020, on GoFundMe. We identified the subset of COVID-19-related campaigns using keywords relevant to the COVID-19 pandemic. We explored the incidence of COVID-19-related campaigns by geography, by category, and over time, and we compared the characteristics of the campaigns to those of non-COVID-19-related campaigns after March 11, when the pandemic was declared. We then used a natural language processing algorithm to cluster campaigns by narrative content using overlapping keywords.

Results: We found that there was a substantial increase in overall GoFundMe web-based crowdfunding campaigns in March, largely attributable to COVID-19-related campaigns. However, as the COVID-19 pandemic persisted and progressed, the number of campaigns per COVID-19 case declined more than tenfold across all states. The states with the earliest disease burden had the fewest campaigns per case, indicating a lack of a case-dependent response. COVID-19-related campaigns raised more money, had a longer narrative description, and were more likely to be shared on Facebook than other campaigns in the study period.

Conclusions: Web-based crowdfunding appears to be a stopgap for only a minority of campaigners. The novelty of an emergency likely impacts both campaign initiation and crowdfunding success, as it reflects the affective response of a community. Crowdfunding activity likely serves as an early signal for emerging needs and societal sentiment for communities in acute distress that could be used by governments and aid organizations to guide disaster relief and policy.
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http://dx.doi.org/10.2196/25429DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7879716PMC
February 2021

International Comparison of Six Basic eHealth Indicators Across 14 Countries: An eHealth Benchmarking Study.

Methods Inf Med 2020 12 18;59(S 02):e46-e63. Epub 2020 Nov 18.

Clinical Informatics Center, Department of Pediatrics, Bioinformatics, and Population and Data Sciences, University of Texas Southwestern, Dallas, Texas, United States.

Background: Many countries adopt eHealth applications to support patient-centered care. Through information exchange, these eHealth applications may overcome institutional data silos and support holistic and ubiquitous (regional or national) information logistics. Available eHealth indicators mostly describe usage and acceptance of eHealth in a country. The eHealth indicators focusing on the cross-institutional availability of patient-related information for health care professionals, patients, and care givers are rare.

Objectives: This study aims to present eHealth indicators on cross-institutional availability of relevant patient data for health care professionals, as well as for patients and their caregivers across 14 countries (Argentina, Australia, Austria, Finland, Germany, Hong Kong as a special administrative region of China, Israel, Japan, Jordan, Kenya, South Korea, Sweden, Turkey, and the United States) to compare our indicators and the resulting data for the examined countries with other eHealth benchmarks and to extend and explore changes to a comparable survey in 2017. We defined "availability of patient data" as the ability to access data in and to add data to the patient record in the respective country.

Methods: The invited experts from each of the 14 countries provided the indicator data for their country to reflect the situation on August 1, 2019, as date of reference. Overall, 60 items were aggregated to six eHealth indicators.

Results: Availability of patient-related information varies strongly by country. Health care professionals can access patients' most relevant cross-institutional health record data fully in only four countries. Patients and their caregivers can access their health record data fully in only two countries. Patients are able to fully add relevant data only in one country. Finland showed the best outcome of all eHealth indicators, followed by South Korea, Japan, and Sweden.

Conclusion: Advancement in eHealth depends on contextual factors such as health care organization, national health politics, privacy laws, and health care financing. Improvements in eHealth indicators are thus often slow. However, our survey shows that some countries were able to improve on at least some indicators between 2017 and 2019. We anticipate further improvements in the future.
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http://dx.doi.org/10.1055/s-0040-1715796DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7728164PMC
December 2020

An "Infodemic": Leveraging High-Volume Twitter Data to Understand Early Public Sentiment for the Coronavirus Disease 2019 Outbreak.

Open Forum Infect Dis 2020 Jul 30;7(7):ofaa258. Epub 2020 Jun 30.

University of Texas Southwestern Medical Center, Clinical Informatics Center, Dallas, Texas, USA.

Background: Twitter has been used to track trends and disseminate health information during viral epidemics. On January 21, 2020, the Centers for Disease Control and Prevention activated its Emergency Operations Center and the World Health Organization released its first situation report about coronavirus disease 2019 (COVID-19), sparking significant media attention. How Twitter content and sentiment evolved in the early stages of the COVID-19 pandemic has not been described.

Methods: We extracted tweets matching hashtags related to COVID-19 from January 14 to 28, 2020 using Twitter's application programming interface. We measured themes and frequency of keywords related to infection prevention practices. We performed a sentiment analysis to identify the sentiment polarity and predominant emotions in tweets and conducted topic modeling to identify and explore discussion topics over time. We compared sentiment, emotion, and topics among the most popular tweets, defined by the number of retweets.

Results: We evaluated 126 049 tweets from 53 196 unique users. The hourly number of COVID-19-related tweets starkly increased from January 21, 2020 onward. Approximately half (49.5%) of all tweets expressed fear and approximately 30% expressed surprise. In the full cohort, the economic and political impact of COVID-19 was the most commonly discussed topic. When focusing on the most retweeted tweets, the incidence of fear decreased and topics focused on quarantine efforts, the outbreak and its transmission, as well as prevention.

Conclusions: Twitter is a rich medium that can be leveraged to understand public sentiment in real-time and potentially target individualized public health messages based on user interest and emotion.
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http://dx.doi.org/10.1093/ofid/ofaa258DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7337776PMC
July 2020

Policy Statement on Clinical Informatics Fellowships and the Future of Informatics-Driven Medicine.

Appl Clin Inform 2020 10 28;11(5):710-713. Epub 2020 Oct 28.

Pediatrics, Data & Population Science, And Biomedical Informatics, UT Southwestern Medical Center, Dallas, Texas, United States.

Board certified clinical informaticians provide expertise in leveraging health IT (HIT) and health data for patient care and quality improvement. Clinical Informatics experts possess the requisite skills and competencies to make systems-level improvements in care delivery using HIT, workflow and data analytics, knowledge acquisition, clinical decision support, data visualization, and related informatics tools. However, these physicians lack structured and sustained funding because they have no billing codes. The sustainability and growth of this new and promising medical subspecialty is threatened by outdated and inconsistent funding models that fail to support the education and professional growth of clinical informaticians. The Clinical Informatics Program Directors' Community is calling upon the Centers for Medicare and Medicaid Services to consider novel funding structures and programs through its Innovation Center for Clinical Informatics Fellowship training. Only through structural and sustained funding for Clinical Informatics fellows will be able to fully develop the potential of electronic health records to improve the quality, safety, and cost of clinical care.
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http://dx.doi.org/10.1055/s-0040-1717117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7593113PMC
October 2020

A Comparison of Online Medical Crowdfunding in Canada, the UK, and the US.

JAMA Netw Open 2020 10 1;3(10):e2021684. Epub 2020 Oct 1.

Department of Internal Medicine, The University of Texas Southwestern Medical Center, Dallas.

Importance: Despite major differences in their health care systems, medical crowdfunding is increasingly used to finance personal health care costs in Canada, the UK, and the US. However, little is known about the campaigns designed to raise monetary donations for medical expenses, the individuals who turn to crowdfunding, and their fundraising intent.

Objective: To examine the demographic characteristics of medical crowdfunding beneficiaries, campaign characteristics, and their association with funding success in Canada, the UK, and the US.

Design, Setting, And Participants: This cross-sectional study extracted and manually reviewed data from GoFundMe campaigns discoverable between February 2018 and March 2019. All available campaigns on each country domain's GoFundMe medical discovery webpage that benefitted a unique patient(s) were included from Canada, the UK, and the US. Data analysis was performed from March to December 2019.

Exposures: Campaign and beneficiary characteristics.

Main Outcomes And Measures: Log-transformed amount raised in US dollars.

Results: This study examined 3396 campaigns including 1091 in Canada, 1082 in the UK, and 1223 in the US. Campaigns in the US (median [IQR], $38 204 [$31 200 to $52 123]) raised more funds than campaigns in Canada ($12 662 [$9377 to $19 251]) and the UK ($6285 [$4028 to $12 348]). In the overall cohort per campaign, Black individuals raised 11.5% less (95% CI, -19.0% to -3.2%; P = .006) than non-Black individuals, and male individuals raised 5.9% more (95% CI, 2.2% to 9.7%; P = .002) than female individuals. Female (39.4% of campaigns vs 50.8% of US population; difference, 11.3%; 95% CI, 8.6% to 14.1%; P < .001) and Black (5.3% of campaigns vs 13.4% of US population; difference, 8.1%; 95% CI, 6.8% to 9.3%; P < .001) beneficiaries were underrepresented among US campaigns. Campaigns primarily for routine treatment expenses were approximately 3 times more common in the US (77.9% [272 of 349 campaigns]) than in Canada (21.9% [55 of 251 campaigns]; difference, 56.0%; 95% CI, 49.3-62.7%; P < .001) or the UK (26.6% [127 of 478 campaigns]; difference, 51.4%; 95% CI, 45.5%-57.3%; P < .001). However, campaigns for routine care were less successful overall. Approved, inaccessible care and experimental care raised 35.7% (95% CI, 25.6% to 46.7%; P < .001) and 20.9% (95% CI, 13.3% to 29.1%; P < .001), respectively, more per campaign than routine care. Campaigns primarily for alternative treatment expenses (16.1% [174 of 1079 campaigns]) were nearly 4-fold more common for cancer (23.5% [144 of 614 campaigns]) vs noncancer (6.5% [30 of 465 campaigns]) diagnoses.

Conclusions And Relevance: Important differences were observed in the reasons individuals turn to medical crowdfunding in the 3 countries examined that suggest racial and gender disparities in fundraising success. More work is needed to understand the underpinnings of these findings and their implications on health care provision in the countries examined.
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http://dx.doi.org/10.1001/jamanetworkopen.2020.21684DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7588935PMC
October 2020

International Academy of Health Sciences Informatics (IAHSI): Strategy and Focus Areas, 1st Version.

Yearb Med Inform 2020 Aug 21;29(1):15-25. Epub 2020 Aug 21.

Peter L. Reichertz Institute for Medical Informatics of TU Braunschweig and Hannover Medical School, Germany.

Background: The International Academy of Health Sciences Informatics (IAHSI) is the Academy of the International Medical Informatics Association (IMIA). As an international forum for peers in biomedical and health informatics, the Academy shall play an important role in exchanging knowledge, providing education and training, and producing policy documents.

Objectives: A major priority of the Academy's activities in its inaugural phase was to define its strategy and focus areas in accordance with its objectives and to prioritize the Academy's work, which can then be transferred to respective taskforces.

Method: This document reflects the major outcomes of intensive discussions that occurred during 2019. It was presented at the Academy's 3rd Plenary on August 25th, 2019, in Lyon, France.

Results: Regardless of the 'living nature' of the strategy and focus areas document, it was concluded during the Plenary that the first version, which will be used as a base for decisions on the Academy's future activities, should be made available to a broad audience. Three out of eight 'Visions for IAHSI', presented in the IMIA Yearbook of Medical Informatics 2018, were identified as central for developing, implementing, and evaluating the Academy's strategic directions: (1) advise governments and organizations on developing health and health sciences through informatics, (2) stimulate progress in biomedical and health informatics research, education, and practice, and (3) share and exchange knowledge. Taskforces shall be implemented to work in the following areas, which were considered as priority themes: (1) artificial intelligence in health: future collaboration of entities with natural and with artificial intelligence in health care, and (2) current landscape of standards for digital health.

Conclusions: Taskforces are now being established. Besides specific key performance indicators, suggested for monitoring the work of theses taskforces, the strategy to monitor the progress of the Academy itself has to be measured by relevant and acceptable metrics.
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http://dx.doi.org/10.1055/s-0040-1701992DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442516PMC
August 2020

Understanding public perception of coronavirus disease 2019 (COVID-19) social distancing on Twitter.

Infect Control Hosp Epidemiol 2021 Feb 6;42(2):131-138. Epub 2020 Aug 6.

Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas.

Objective: Social distancing policies are key in curtailing severe acute respiratory coronavirus virus 2 (SARS-CoV-2) spread, but their effectiveness is heavily contingent on public understanding and collective adherence. We studied public perception of social distancing through organic, large-scale discussion on Twitter.

Design: Retrospective cross-sectional study.

Methods: Between March 27 and April 10, 2020, we retrieved English-only tweets matching two trending social distancing hashtags, #socialdistancing and #stayathome. We analyzed the tweets using natural language processing and machine-learning models, and we conducted a sentiment analysis to identify emotions and polarity. We evaluated the subjectivity of tweets and estimated the frequency of discussion of social distancing rules. We then identified clusters of discussion using topic modeling and associated sentiments.

Results: We studied a sample of 574,903 tweets. For both hashtags, polarity was positive (mean, 0.148; SD, 0.290); only 15% of tweets had negative polarity. Tweets were more likely to be objective (median, 0.40; IQR, 0-0.6) with ~30% of tweets labeled as completely objective (labeled as 0 in range from 0 to 1). Approximately half of tweets (50.4%) primarily expressed joy and one-fifth expressed fear and surprise. Each correlated well with topic clusters identified by frequency including leisure and community support (ie, joy), concerns about food insecurity and quarantine effects (ie, fear), and unpredictability of coronavirus disease 2019 (COVID-19) and its implications (ie, surprise).

Conclusions: Considering the positive sentiment, preponderance of objective tweets, and topics supporting coping mechanisms, we concluded that Twitter users generally supported social distancing in the early stages of their implementation.
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http://dx.doi.org/10.1017/ice.2020.406DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7450231PMC
February 2021

Ethics and informatics in the age of COVID-19: challenges and recommendations for public health organization and public policy.

J Am Med Inform Assoc 2021 01;28(1):184-189

University of Pittsburgh, Pittsburgh, Pennsylvania, USA.

The COVID-19 pandemic response in the United States has exposed significant gaps in information systems and processes that prevent timely clinical and public health decision-making. Specifically, the use of informatics to mitigate the spread of SARS-CoV-2, support COVID-19 care delivery, and accelerate knowledge discovery bring to the forefront issues of privacy, surveillance, limits of state powers, and interoperability between public health and clinical information systems. Using a consensus-building process, we critically analyze informatics-related ethical issues in light of the pandemic across 3 themes: (1) public health reporting and data sharing, (2) contact tracing and tracking, and (3) clinical scoring tools for critical care. We provide context and rationale for ethical considerations and recommendations that are actionable during the pandemic and conclude with recommendations calling for longer-term, broader change (beyond the pandemic) for public health organization and policy reform.
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http://dx.doi.org/10.1093/jamia/ocaa188DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7454584PMC
January 2021

A Clinical Informatics Program Directors' Proposal to the American Board of Preventive Medicine.

Appl Clin Inform 2020 05 15;11(3):483-486. Epub 2020 Jul 15.

Clinical Informatics Center, UT Southwestern, Dallas, Texas, United States.

In 2013, the American Board of Preventive Medicine (ABPM) and the American Board of Pathology (ABPath) offered the first board certification examination in Clinical Informatics to eligible physicians in the United States. In 2022, the Practice Pathway will expire and in 2023 only candidates eligible through the Fellowship Pathway will be eligible for the board certification. To date, Clinical Informatics as a specialty has not had a regular match process and used a controlled offer-acceptance process that does not meet candidates' or programs' needs. Fellows may not be offered a position with their top choice program initially, and they may accept offers from other programs to avoid risk by ensuring that they have a fellowship position. Programs have to consider losing an applicant in the first round in the ranking of applicants. The process is open to manipulation including early agreements between program directors and candidates. In this open letter to the ABPM, program directors make the case for a third-party match and are calling on the ABPM to leverage its status as the Clinical Informatics certifying body and its existing infrastructure to implement a Clinical Informatics match.
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http://dx.doi.org/10.1055/s-0040-1714348DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363483PMC
May 2020

Provider Networks in the Neonatal Intensive Care Unit Associate with Length of Stay.

IEEE Conf Collab Internet Comput 2019 Dec 13;2019:127-134. Epub 2020 Feb 13.

Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN.

We strive to understand care coordination structures of multidisciplinary teams and to evaluate their effect on post-surgical length of stay (PSLOS) in the Neonatal Intensive Care Unit (NICU). Electronic health record (EHR) data were extracted for 18 neonates, who underwent gastrostomy tube placement surgery at the Vanderbilt University Medical Center NICU. Based on providers' interactions with the EHR (e.g. viewing, documenting, ordering), provider-provider relations were learned and used to build patient-specific provider networks representing the care coordination structure. We quantified the networks using standard network analysis metrics (e.g., in-degree, out-degree, betweenness centrality, and closeness centrality). Coordination structure effectiveness was measured as the association between the network metrics and PSLOS, as modeled by a proportional-odds, logistical regression model. The 18 provider networks exhibited various team compositions and various levels of structural complexity. Providers, whose patients had lower PSLOS, tended to disperse patient-related information to more colleagues within their network than those, who treated higher PSLOS patients (P = 0.0294). In the NICU, improved dissemination of information may be linked to reduced PSLOS. EHR data provides an efficient, accessible, and resource-friendly way to study care coordination using network analysis tools. This novel methodology offers an objective way to identify key performance and safety indicators of care coordination and to study dissemination of patient-related information within care provider networks and its effect on care. Findings should guide improvements in the EHR system design to facilitate effective clinical communications among providers.
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http://dx.doi.org/10.1109/CIC48465.2019.00024DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7339831PMC
December 2019

The International Academy of Health Sciences Informatics (IAHSI): IMIAs Academy is Now Established and on Track.

Yearb Med Inform 2020 Aug 17;29(1):11-14. Epub 2020 Apr 17.

Clinical Informatics Center, University of Texas Southwestern Medical Center, Dallas, USA.

Objectives: To summarize the major activities of the International Academy of Health Sciences Informatics (IAHSI) from 2018 until 2019, and to provide an outline of actions planned for 2020.

Method: Reporting about these activities and actions by the members of the Academy's first Board.

Results: Academy bylaws were accepted by the Academy Plenary and the IMIA General Assembly on August 25th, 2019 and August 26th, 2019, respectively. Academy's strategy and focus areas were developed. Based on the Academy's eligibility criteria, the 2018/2019 Class made of 26 new Academy Fellows was elected. Future activities will concentrate on building taskforces for developing and implementing major Academy focus areas.

Conclusions: We are glad to report that the Academy is strong and thriving.
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http://dx.doi.org/10.1055/s-0040-1701971DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442511PMC
August 2020

Modeling Care Team Structures in the Neonatal Intensive Care Unit through Network Analysis of EHR Audit Logs.

Methods Inf Med 2019 Nov 13;58(4-05):109-123. Epub 2020 Mar 13.

Department of Anesthesiology, Center for Research and Innovation in Systems Safety, Vanderbilt University Medical Center, Nashville, Tennessee, United States.

Background:  In the neonatal intensive care unit (NICU), predefined acuity-based team care models are restricted to core roles and neglect interactions with providers outside of the team, such as interactions that transpire via electronic health record (EHR) systems. These unaccounted interactions may be related to the efficiency of resource allocation, information flow, communication, and thus impact patient outcomes. This study applied network analysis methods to EHR audit logs to model the interactions of providers beyond their core roles to better understand the interaction network patterns of acuity-based teams and relationships of the network structures with postsurgical length of stay (PSLOS).

Methods:  The study used the EHR log data of surgical neonates from a large academic medical center. The study included 104 surgical neonates, for whom 9,206 unique actions were performed by 457 providers in their EHRs. We applied network analysis methods to model EHR provider interaction networks of acuity-based teams in NICU postoperative care. We partitioned each EHR network into three subnetworks based on interaction types: (1) interactions between known core providers who were documented in scheduling records (core subnetwork); (2) interactions between core and noncore providers (extended subnetwork); and (3) interactions between noncore providers (extended subnetwork). For each core subnetwork, we assessed its capability to replicate predefined core-provider relations as documented in scheduling records. We further compared each EHR network, as well as its subnetworks, using standard network measures to determine its differences in network topologies. We conducted a case study to learn provider interaction networks taking care of 15 neonates who underwent gastrostomy tube placement surgery from EHR log data and measure the effectiveness of the interaction networks on PSLOS by the proportional-odds model.

Results:  The provider networks of four acuity-based teams (two high and two low acuity), along with their subnetworks, were discovered. We found that beyond capturing the predefined core-provider relations, EHR audit logs can also learn a large number of relations between core and noncore providers or among noncore providers. Providers in the core subnetwork exhibited a greater number of connections with each other than with providers in the extended subnetworks. Many more providers in the core subnetwork serve as a hub than those in the other types of subnetworks. We also found that high-acuity teams exhibited more complex network structures than low-acuity teams, with high-acuity team generating 6,416 interactions between 407 providers compared with 931 interactions between 124 providers, respectively. In addition, we discovered that high-acuity and low-acuity teams shared more than 33 and 25% of providers with each other, respectively, but exhibited different collaborative structures demonstrating that NICU providers shift across different acuity teams and exhibit different network characteristics. Results of case study show that providers, whose patients had lower PSLOS, tended to disperse patient-related information to more colleagues within their network than those who treated higher PSLOS patients ( = 0.03).

Conclusion:  Network analysis can be applied to EHR log data to model acuity-based NICU teams capturing interactions between providers within the predesigned core team as well as those outside of the core team. In the NICU, dissemination of information may be linked to reduced PSLOS. EHR log data provide an efficient, accessible, and research-friendly way to study provider interaction networks. Findings should guide improvements in the EHR system design to facilitate effective interactions between providers.
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http://dx.doi.org/10.1055/s-0040-1702237DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7356932PMC
November 2019

Defining the Epidemiology of Safety Risks in Neonatal Intensive Care Unit Patients Requiring Surgery.

J Patient Saf 2020 Mar 11. Epub 2020 Mar 11.

Department of Pediatric Surgery.

Objective: The aim of the study was to determine the incidence, type, severity, preventability, and contributing factors of nonroutine events (NREs)-events perceived by care providers or skilled observers as a deviations from optimal care based on the clinical situation-in the perioperative (i.e., preoperative, operative, and postoperative) care of surgical neonates in the neonatal intensive care unit and operating room.

Methods: A prospective observational study of noncardiac surgical neonates, who received preoperative and postoperative neonatal intensive care unit care, was conducted at an urban academic children's hospital between November 1, 2016, and March 31, 2018. One hundred twenty-nine surgical cases in 109 neonates were observed. The incidence and description of NREs were collected via structured researcher-administered survey tool of involved clinicians. Primary measurements included clinicians' ratings of NRE severity and contributory factors and trained research assistants' ratings of preventability.

Results: One or more NREs were reported in 101 (78%) of 129 observed cases for 247 total NREs. Clinicians reported 2 (2) (median, interquartile range) NREs per NRE case with a maximum severity of 3 (1) (possible range = 1-5). Trained research assistants rated 47% of NREs as preventable and 11% as severe and preventable. The relative risks for National Surgical Quality Improvement Program - pediatric major morbidity and 30-day mortality were 1.17 (95% confidence interval = 0.92-1.48) and 1.04 (95% confidence interval = 1.00-1.08) in NRE cases versus non-NRE cases.

Conclusions: The incidence of NREs in neonatal perioperative care at an academic children's hospital was high and of variable severity with a myriad of contributory factors.
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http://dx.doi.org/10.1097/PTS.0000000000000680DOI Listing
March 2020

Is the Climb Worth the View? The Savings/Alert Ratio for Reducing Vitamin D Testing.

Appl Clin Inform 2020 01 26;11(1):160-165. Epub 2020 Feb 26.

Health Information Technology, Vanderbilt University Medical Center, Nashville, Tennessee, United States.

Background: Despite guideline recommendations, vitamin D testing has increased substantially. Clinical decision support (CDS) presents an opportunity to reduce inappropriate laboratory testing.

Objectives And Methods: To reduce inappropriate testing of vitamin D at the Vanderbilt University Medical Center, a CDS assigned providers to receive or not receive an electronic alert each time a 25-hydroxyvitamin D assay was ordered for an adult patient unless the order was associated with a diagnosis in the patient's chart for which vitamin D testing is recommended. The CDS ran for 80 days, collecting data on number of tests, provider information, and basic patient demographics.

Results: During the 80 days, providers placed 12,368 orders for 25-hydroxyvitamin D. The intervention group ordered a vitamin D assay and received the alert for potentially inappropriate testing 2,181 times and completed the 25-hydroxyvitamin D order in 89.9% of encounters, while the control group ordered a vitamin D assay (without receiving an alert) 2,032 times and completed the order in 98.1% of encounters, for an absolute reduction of testing of 8% ( < 0.001).

Conclusion: This CDS reduced vitamin D ordering by utilizing a soft-stop approach. At a charge of $179.00 per test and a cost to the laboratory of $4.20 per test, each display of the alert led to an average reduction of $14.70 in charges and of $0.34 in spending by the laboratory (the savings/alert ratio). By describing the effectiveness of an electronic alert in terms of the savings/alert ratio, the impact of this intervention can be better appreciated and compared with other interventions.
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http://dx.doi.org/10.1055/s-0040-1701678DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7043952PMC
January 2020

Commercial Interests in Continuing Medical Education: Where Do Electronic Health Record Vendors Fit?

Acad Med 2020 11;95(11):1674-1678

C.U. Lehmann is professor, Departments of Pediatrics, Population and Data Sciences, and Bioinformatics, University of Texas Southwestern Medical Center, Dallas, Texas; ORCID: https://orcid.org/0000-0001-9559-4646.

The Accreditation Council for Continuing Medical Education (ACCME) will not accredit an organization that it defines as a commercial interest, that is an entity that produces, markets, resells, or distributes health care goods or services consumed by, or used on, patients. Thus, commercial interests are not eligible to be accredited organizations offering continuing medical education (CME) credit to physicians. This decision is based on the concern that commercial interests may use CME events to market their products or services to physicians, who then might inappropriately prescribe or administer those products or services to patients. Studies have shown that CME events supported by pharmaceutical companies, for example, have influenced physicians' prescribing behaviors.Currently, however, the ACCME does not recognize electronic health record (EHR) vendors, which are part of a multi-billion-dollar business, as commercial interests, and it accredits them to provide or directly influence CME events. Like pharmaceutical company-sponsored CME events, EHR vendor activities, which inherently only focus on use of the sponsoring vendor's EHR system despite its potential intrinsic limitations, can lead to physician reciprocity. Such events also may inappropriately influence EHR system purchases, upgrades, and implementation decisions. These actions can negatively influence patient safety and care. Thus, the authors of this Perspective call on the ACCME to recognize EHR vendors as commercial interests and remove them from the list of accredited CME providers.
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http://dx.doi.org/10.1097/ACM.0000000000003190DOI Listing
November 2020

Project RedDE: Cluster Randomized Trial to Reduce Missed or Delayed Abnormal Laboratory Value Actions.

Pediatr Qual Saf 2019 Sep-Oct;4(5):e218. Epub 2019 Sep 30.

Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey Veterans Affairs Medical Center, Department of Medicine, Baylor College of Medicine, Center of Innovation, Houston, Tex.

Failure of timely abnormal laboratory result follow-up is relatively common and may lead to harm. This study hypothesized that a quality improvement collaborative (QIC) could reduce the frequency of missed or delayed action on abnormal laboratory values.

Methods: A national cohort of pediatric practices was cluster-randomized to sequentially receive a QIC intervention: video conferences, transparent data sharing, a "focus on failures," QI coaching, and tools to help reduce missed or delayed action on abnormal laboratory values. Practices recorded the percentage of patients with 5 specific abnormal laboratory values who received an appropriate provider action (control), and then, during an 8-month intervention phase, implemented QI strategies to reduce errors (intervention). Subsequently, practices collected data on laboratory errors while working to reduce unrelated second (sustain phase), and third (maintenance phase) errors. Generalized mixed-effects regression models compared the mean percentage of patients with appropriate actions.

Results: We randomized 43 practices, of which 31 were included in analyses. Control and intervention phases included 1,357 and 1,426 patients with abnormal laboratory values, respectively. The mean percentage of patients who received appropriate actions did not change comparing control and intervention phases [risk difference (RD) 1%; 95% CI -1%, 3%]. In analyses, practices significantly improved comparing control to sustain (RD 3%; 95% CI 0.3%, 6%) and maintenance phases (RD 6%; 95% CI 3%, 9%).

Conclusion: Implementation of a QIC did not reduce the frequency of abnormal laboratory errors in the initial 8-month intervention phase. A significant reduction was appreciated comparing sustain and maintenance phases (months 9-24) to the control phase.
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http://dx.doi.org/10.1097/pq9.0000000000000218DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805103PMC
September 2019

Data breach remediation efforts and their implications for hospital quality.

Health Serv Res 2019 10;54(5):971-980

Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee.

Objective: To estimate the relationship between breach remediation efforts and hospital care quality.

Data Sources: Department of Health and Human Services' (HHS) public database on hospital data breaches and Medicare Compare's public data on hospital quality measures for 2012-2016.

Materials And Methods: Data breach data were merged with the Medicare Compare data for years 2012-2016, yielding a panel of 3025 hospitals with 14 297 unique hospital-year observations.

Study Design: The relationship between breach remediation and hospital quality was estimated using a difference-in-differences regression. Hospital quality was measured by 30-day acute myocardial infarction mortality rate and time from door to electrocardiogram.

Principal Findings: Hospital time-to-electrocardiogram increased as much as 2.7 minutes and 30-day acute myocardial infarction mortality increased as much as 0.36 percentage points during the 3-year window following a breach.

Conclusion: Breach remediation efforts were associated with deterioration in timeliness of care and patient outcomes. Thus, breached hospitals and HHS oversight should carefully evaluate remedial security initiatives to achieve better data security without negatively affecting patient outcomes.
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http://dx.doi.org/10.1111/1475-6773.13203DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6736905PMC
October 2019

Physician Perspectives on Training for an EHR Implementation.

Stud Health Technol Inform 2019 Aug;264:1318-1322

Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA.

In 2017, a US academic medical center switched to a commercial EHR system using the "specialist training the specialist" model, which combines peer-to-peer training, classroom based training, and web-based training. We conducted semi-structured interviews with physicians at multiple training levels to investigate the impact of this EHR switch and to explore the training experience of physicians and their perception of the training quality pre and post Go-Live. Our team used Grounded Theory methodology to classify the interview information. Themes that emerged from the interviews included stress and anxiety, the desire for more realistic training environments tailored to specialty needs, and concerns about the duration of time between training and implementation. In future implementations, we recommend more data-rich test patients and the demonstration of real-world workflows during training.
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http://dx.doi.org/10.3233/SHTI190440DOI Listing
August 2019

On the Right to Science: Recommendations of Selection Criteria for IMIA Scientific Meetings.

Yearb Med Inform 2019 Aug 16;28(1):11-13. Epub 2019 Aug 16.

IMIA President Elect.

The International Medical Informatics Association (IMIA), a non-governmental, not-for-profit, global organization promoting health and biomedical informatics, is committed to the right of communities/populations and individuals to science, comprised of three separate constituent rights: 1) the right to participate in science, 2) the right to benefit from science, and 3) the right to benefit from a person's own contribution to science or inventions. As such, IMIA provides a global platform where scientists, researchers, health information users, vendors, developers, consultants, health care consumers, and suppliers can meet in an environment of cooperation and sharing. In the context of IMIA's conferences, the IMIA board has discussed and identified the important central factors, which are essential considerations to host a scientific meeting. These factors will be used to help vet future contenders applying for the honor to host an IMIA conference: Reasonable safety and security, commitment by the host member society, freedom of travel, scientific freedom, and freedom from discrimination.
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http://dx.doi.org/10.1055/s-0039-1677924DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697513PMC
August 2019

A Call to Action.

Yearb Med Inform 2019 08 16;28(1):1-2. Epub 2019 Aug 16.

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http://dx.doi.org/10.1055/s-0039-1677923DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697494PMC
August 2019

Pediatric Hospitalizations: Are We Missing an Opportunity to Immunize?

Hosp Pediatr 2019 09 5;9(9):673-680. Epub 2019 Aug 5.

Department of Pediatrics.

Objectives: Fewer than half of children receive all recommended immunizations on time. Hospitalizations may be opportunities to address delayed immunizations. Our objectives were to assess (1) prevalence of delayed immunizations among hospitalized patients, (2) missed opportunities to administer delayed immunizations, and (3) time to catch up after discharge.

Methods: We conducted a retrospective cohort study investigating immunization status of patients 0 to 21 years of age admitted to an academic children's center from 2012 to 2013 at the time of admission, at discharge, and 18 months postdischarge. Immunization catch-up at 18 months postdischarge was defined as having received immunizations due on discharge per Centers for Disease Control and Prevention recommendations. χ and test analyses compared characteristics among patients caught up and not caught up at 18 months postdischarge. Analysis of variance and logistic regression analyses compared mean number of immunizations needed and odds of immunization catch-up among age groups. Kaplan-Meier and Cox proportional hazards analyses compared catch-up time by age, race, sex, and insurance.

Results: Among 166 hospitalized patients, 80 were not up to date on immunizations at admission, and only 1 received catch-up immunizations before discharge. Ninety-nine percent (79 of 80) were not up to date on discharge per Centers for Disease Control and Prevention recommendations. Thirty percent (24 of 79), mostly adolescents, were not caught up at 18 months postdischarge. Median postdischarge catch-up time was 3.5 months (range: 0.03-18.0 months). Patients 0 to 35 months of age were more likely to catch up compared with those of other ages (hazard ratio = 2.73; = .001), with no differences seen when comparing race, sex, or insurance.

Conclusions: Pediatric hospitalizations provide important opportunities to screen and immunize children.
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http://dx.doi.org/10.1542/hpeds.2018-0180DOI Listing
September 2019

Leveraging Knowledge Representation to Maintain Immunization Clinical Decision Support.

AMIA Annu Symp Proc 2018 5;2018:789-798. Epub 2018 Dec 5.

Vanderbilt University Medical Center, Nashville, TN, USA.

Immunizations are one of the most cost-effective interventions for preventing morbidity and mortality. As vaccines, related clinical knowledge and requirements change, clinical applications must be updated in a timely manner to avoid practicing outdated medicine. We use the Centers for Disease Control and Prevention (CDC) as a source for immunization knowledge for our Clinical Information Systems (CIS). After identifying knowledge management related gaps in the CDC's content and email notification service, we developed and adapted a knowledge management tool chain - called COMET - for facilitating automatic processing of the available immunization content to implement mature knowledge lifecycle management practices locally. The implemented features include error and change tracking, content discovery and analytics, and tracking of dependencies to dependent downstream CISs. We demonstrate the creation of a tool that enables content curators to visualize, track, and implement immunization changes.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371352PMC
December 2019

Characteristics of the National Applicant Pool for Clinical Informatics Fellowships (2016-2017).

AMIA Annu Symp Proc 2018 5;2018:225-231. Epub 2018 Dec 5.

David Geffen School of Medicine at UCLA, Los Angeles, CA.

We conducted a national study to assess the numbers and diversity of applicants for 2016 and 2017 clinical informatics fellowship positions. In each year, we collected data on the number of applications that programs received from candidates who were ultimately successful vs. unsuccessful. In 2017, we also conducted an anonymous applicant survey. Successful candidates applied to an average of 4.2 and 5.5 programs for 2016 and 2017, respectively. In the survey, unsuccessful candidates reported applying to fewer programs. Assuming unsuccessful candidates submitted between 2-5 applications each, the total applicant pool numbered 42-69 for 2016 (competing for 24 positions) and 52-85 for 2017 (competing for 30 positions). Among survey respondents (n=33), 24% were female, 1 was black and none were Hispanic. We conclude that greater efforts are needed to enhance interest in clinical informatics among medical students and residents, particularly among women and members of underrepresented minority groups.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371309PMC
September 2019

The design and conduct of Project RedDE: A cluster-randomized trial to reduce diagnostic errors in pediatric primary care.

Clin Trials 2019 04 5;16(2):154-164. Epub 2019 Feb 5.

3 Department of Pediatrics, Albert Einstein College of Medicine and Children's Hospital at Montefiore, Bronx, NY, USA.

Background: Diagnostic errors contribute to the large burden of healthcare-associated harm experienced by children. Primary care settings involve high diagnostic uncertainty and limited time and information, creating ideal conditions for diagnostic errors. We report on the design and conduct of Project RedDE, a stepped-wedge, cluster-randomized controlled trial of a virtual quality improvement collaborative aimed at reducing diagnostic errors in pediatric primary care.

Methods: Project RedDE cluster-randomized pediatric primary care practices into one of three groups. Each group participated in a quality improvement collaborative targeting the same three diagnostic errors (missed diagnoses of elevated blood pressure and adolescent depression and delayed diagnoses of abnormal laboratory studies), but in a different sequence. During the quality improvement collaborative, practices worked both independently and collaboratively, leveraging general quality improvement strategies (e.g. process mapping) in addition to error-specific content (e.g. pocket guides for blood pressure norms) delivered during the intervention phase for each error. The quality improvement collaborative intervention included interactive learning sessions and webinars, quality improvement coaching at the team level, and repeated evaluation of failures via root cause analyses. Pragmatic data were collected monthly, submitted to a centralized data aggregator, and returned to the practices in the form of run charts comparing each practice's progress over time to that of the group. The primary analysis used patients as the unit of analysis and compared diagnostic error proportions between the intervention and baseline periods, while secondary analyses evaluated the sustainability of observed reductions in diagnostic errors after the intervention period ended.

Results: A total of 43 practices were recruited and randomized into Project RedDE. Eleven practices withdrew before submitting any data, and one practice merged with another participating practice, leaving 31 practices that began work on Project RedDE. All but one of the diverse, national pediatric primary care practices that participated ultimately submitted complete data. Quality improvement collaborative participation was robust, with an average of 63% of practices present on quality improvement collaborative webinars and 85% of practices present for quality improvement collaborative learning sessions. Complete data included 30 months of outcome data for the first diagnostic error worked on, 24 months of outcome data for the second, and 16 months of data for the third.

Lessons Learned And Limitations: Contamination across study groups was a recurring concern; concerted efforts were made to mitigate this risk. Electronic health records played a large role in teams' success.

Conclusion: Project RedDE, a virtual quality improvement collaborative aimed at reducing diagnostic errors in pediatric primary care, successfully recruited and retained a diverse, national group of pediatric primary care practices. The stepped-wedge, cluster-randomized controlled trial design allowed for enhanced scientific efficiency.
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http://dx.doi.org/10.1177/1740774518820522DOI Listing
April 2019

Rebuilding the Standing Prescription Renewal Orders.

Appl Clin Inform 2019 01 30;10(1):77-86. Epub 2019 Jan 30.

Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States.

Background: Managing prescription renewal requests is a labor-intensive challenge in ambulatory care. In 2009, Vanderbilt University Medical Center developed clinic-specific standing prescription renewal orders that allowed nurses, under specific conditions, to authorize renewal requests. Formulary and authorization changes made maintaining these documents very challenging.

Objective: This article aims to review, standardize, and restructure legacy standing prescription renewal orders into a modular, scalable, and easier to manage format for conversion and use in a new electronic health record (EHR).

Methods: We created an enterprise-wide renewal domain model using modular subgroups within the main institutional standing renewal order policy by extracting metadata, medication group names, medication ingredient names, and renewal criteria from approved legacy standing renewal orders. Instance-based matching compared medication groups in a pairwise manner to calculate a similarity score between medication groups. We grouped and standardized medication groups with high similarity by mapping them to medication classes from a medication terminology vendor and filtering them by intended route (e.g., oral, subcutaneous, inhalation). After standardizing the renewal criteria to a short list of reusable criteria, the Pharmacy and Therapeutics (P&T) committee reviewed and approved candidate medication groups and corresponding renewal criteria.

Results: Seventy-eight legacy standing prescription renewal orders covered 135 clinics (some applied to multiple clinics). Several standing orders were perfectly congruent, listing identical medications for renewal. We consolidated 870 distinct medication classes to 164 subgroups and assigned renewal criteria. We consolidated 379 distinct legacy renewal criteria to 21 criteria. After approval by the P&T committee, we built subgroups in a structured and consistent format in the new EHR, where they facilitated chart review and standing order adherence by nurses. Additionally, clinicians could search an autogenerated document of the standing order content from the EHR data warehouse.

Conclusion: We describe a methodology for standardizing and scaling standing prescription renewal orders at an enterprise level while transitioning to a new EHR.
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http://dx.doi.org/10.1055/s-0038-1675813DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6353649PMC
January 2019