Search

Introduction: There is an urgent need for scalable strategies for treating overweight and obesity in clinical settings. PROPS 2.0 (Partnerships for Reducing Overweight and Obesity with Patient-Centered Strategies 2.0) aims to adapt and implement the combined intervention from the PROPS Study at scale, in a diverse cross-section of patients and providers., Methods and Analysis: We are implementing PROPS 2.0 across a variety of clinics at Brigham and Women's Hospital, targeting enrolment of 5000 patients. Providers can refer patients or patients can self-refer. Eligible patients must be ≥20 years old and have a body mass index (BMI) of ≥30 kg/m 2 or a BMI of 25-29.9 kg/m 2 plus another cardiovascular risk factor or obesity-related condition. After enrolment, patients register for the RestoreHealth online programme/app (HealthFleet Inc.) and participate for 12 months. Patients can engage with the programme and receive personalized feedback from a coach. Patient navigators help to enrol patients, enter updates in the electronic health record, and refer patients to additional resources. The RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework is guiding the evaluation., Ethics and Dissemination: The Mass General Brigham Human Research Committee approved this protocol. An implementation guide will be created and disseminated, to help other sites adopt the intervention in the future., Trial Registration Number: NCT0555925., Competing Interests: Competing interests: HealthFleet Inc. has provided in-kind support for the RestoreHealth programme, but will not be involved in the analysis of the data. AJB reports research grants from Novo Nordisk, General Electric Health and Boehringer Ingelheim. He receives consulting fees from Walgreens Health, Color Health and Arsenal Capital Partners. He has equity in Knownwell. CMA has participated on advisory boards for Altimmune, Cowen and Company, Currax Pharmaceuticals, EPG Communication Holdings, Form Health, Gelesis, Srl., L-Nutra, NeuroBo Pharmaceuticals, Novo Nordisk, Pain Script, Pursuit By You, ReShape Lifesciences, Riverview School and Xeno Biosciences. CMA has received research funding from the NIH, PCORI and GI Dynamics. JP reports research grants from Boehringer Ingelheim, and Novo Nordisk, consulting fees from Altimmune, Amgen, Esperion, Merck, Novo Nordisk and MJH Health. RR reports having equity in Hospitech Respiration, TRI-O, AEYE Health, RxE2, OtheReality, Co-Patient Support and Medyx.ai, all of which are unrelated to this project. He is also receiving research funding from Boston Scientific Corporation, Telem, Calosense Health, Breath of Health, Merative and BriefCam; these are unrelated to this project. WJG discloses consulting income from Novocardia, and Great Point Ventures, both unrelated to this topic. BMS reports institutional research grants to Brigham and Women’s Hospital from Better Therapeutics, Boehringer Ingelheim, Merck, NovoNordisk and Pfizer. Consulting fees from Abbvie (DSMB), AstraZeneca (DSMB), Boehringer Ingelheim, Better Therapeutics, Bristol Myers-Squibb, Elsevier Practice Update Cardiology, Esperion, Hanmi (DSMB), Lexeo (DSMB), Lexicon, NovoNordisk, and equity in Health (at) Scale and Doximity. DWB reports grants and personal fees from EarlySense, personal fees from CDI Negev, equity from ValeraHealth, equity from Clew, equity from MDClone, personal fees and equity from AESOP, personal fees and equity from FeelBetter, personal fees and equity from Guided Clinical Solutions, and grants from IBM Watson Health, outside this project., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Growing evidence has shown that applying machine learning models to large clinical data sources may exceed clinician performance in suicide risk stratification. However, many existing prediction models either suffer from "temporal bias" (a bias that stems from using case-control sampling) or require training on all available patient visit data. Here, we adopt a "landmark model" framework that aligns with clinical practice for prediction of suicide-related behaviors (SRBs) using a large electronic health record database. Using the landmark approach, we developed models for SRB prediction (regularized Cox regression and random survival forest) that establish a time-point (e.g., clinical visit) from which predictions are made over user-specified prediction windows using historical information up to that point. We applied this approach to cohorts from three clinical settings: general outpatient, psychiatric emergency department, and psychiatric inpatients, for varying prediction windows and lengths of historical data. Models achieved high discriminative performance (area under the Receiver Operating Characteristic curve 0.74-0.93 for the Cox model) across different prediction windows and settings, even with relatively short periods of historical data. In short, we developed accurate, dynamic SRB risk prediction models with the landmark approach that reduce bias and enhance the reliability and portability of suicide risk prediction models., Competing Interests: Declaration of Competing Interest Dr. Smoller is a member of the the Scientific Advisory Board of Sensorium Therapeutics (with equity), and has received grant support from Biogen, Inc. He is PI of a collaborative study of the genetics of depression and bipolar disorder sponsored by 23andMe for which 23andMe provides analysis time as in-kind support but no payments., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background The COVID-19 pandemic disrupted traditional health care; one fallout was a drastic decrease in blood pressure (BP) assessment. We analyzed the pandemic's impact on our existing remote hypertension management program's effectiveness and adaptability. Methods and Results This retrospective observational analysis evaluated BP control in an entirely remote management program before and during the pandemic. A team of pharmacists, nurse practitioners, physicians, and nonlicensed navigators used an evidence-based clinical algorithm to optimize hypertensive treatment. The algorithm was adapted during the pandemic to simplify BP control. Overall, 1256 patients (605 enrolled in the 6 months before the pandemic shutdown in March 2020 and 651 in the 6 months after) were a median age of 63 years old, 57% female, and 38.2% non-White. Among enrolled patients with sustained hypertension, 51.1% reached BP goals. Within this group, rates of achieving goal BP improved to 94.6% during the pandemic from 75.8% prepandemic ( P <0.0001). Mean baseline home BP was 141.7/81.9 mm Hg during the pandemic and 139.8/82.2 prepandemic, and fell ≈16/9 mm Hg in both periods ( P <0.0001). Maintenance during the pandemic was achieved earlier (median 11.8 versus 19.6 weeks, P <0.0001), with more frequent monthly calls (8.2 versus 3.1, P <0.0001) and more monthly home BP recordings per patient (32.4 versus 18.9, P <0.0001), compared with the prepandemic period. Conclusions A remote clinical management program was successfully adapted and delivered significant improvements in BP control and increased home BP monitoring despite a nationally observed disruption of traditional hypertension care. Such programs have the potential to transform hypertension management and care delivery.

Digital Health Technologies (DHTs) such as connected sensors offer particular promise for improving data collection and patient empowerment in neurology research and care. This study analyzed the recent evolution of the use of DHTs in trials registered on ClinicalTrials.gov for four chronic neurological disorders: epilepsy, multiple sclerosis, Alzheimer's, and Parkinson's disease. We document growth in the collection of both more established digital measures (e.g., motor function) and more novel digital measures (e.g., speech) over recent years, highlighting contexts of use and key trends., (© 2023. The Author(s).)

Importance: Blood pressure (BP) and cholesterol control remain challenging. Remote care can deliver more effective care outside of traditional clinician-patient settings but scaling and ensuring access to care among diverse populations remains elusive., Objective: To implement and evaluate a remote hypertension and cholesterol management program across a diverse health care network., Design, Setting, and Participants: Between January 2018 and July 2021, 20 454 patients in a large integrated health network were screened; 18 444 were approached, and 10 803 were enrolled in a comprehensive remote hypertension and cholesterol program (3658 patients with hypertension, 8103 patients with cholesterol, and 958 patients with both). A total of 1266 patients requested education only without medication titration. Enrolled patients received education, home BP device integration, and medication titration. Nonlicensed navigators and pharmacists, supported by cardiovascular clinicians, coordinated care using standardized algorithms, task management and automation software, and omnichannel communication. BP and laboratory test results were actively monitored., Main Outcomes and Measures: Changes in BP and low-density lipoprotein cholesterol (LDL-C)., Results: The mean (SD) age among 10 803 patients was 65 (11.4) years; 6009 participants (56%) were female; 1321 (12%) identified as Black, 1190 (11%) as Hispanic, 7758 (72%) as White, and 1727 (16%) as another or multiple races (including American Indian or Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, unknown, other, and declined to respond; consolidated owing to small numbers); and 142 (11%) reported a preferred language other than English. A total of 424 482 BP readings and 139 263 laboratory reports were collected. In the hypertension program, the mean (SD) office BP prior to enrollment was 150/83 (18/10) mm Hg, and the mean (SD) home BP was 145/83 (20/12) mm Hg. For those engaged in remote medication management, the mean (SD) clinic BP 6 and 12 months after enrollment decreased by 8.7/3.8 (21.4/12.4) and 9.7/5.2 (22.2/12.6) mm Hg, respectively. In the education-only cohort, BP changed by a mean (SD) -1.5/-0.7 (23.0/11.1) and by +0.2/-1.9 (30.3/11.2) mm Hg, respectively (P < .001 for between cohort difference). In the lipids program, patients in remote medication management experienced a reduction in LDL-C by a mean (SD) 35.4 (43.1) and 37.5 (43.9) mg/dL at 6 and 12 months, respectively, while the education-only cohort experienced a mean (SD) reduction in LDL-C of 9.3 (34.3) and 10.2 (35.5) mg/dL at 6 and 12 months, respectively (P < .001). Similar rates of enrollment and reductions in BP and lipids were observed across different racial, ethnic, and primary language groups., Conclusions and Relevance: The results of this study indicate that a standardized remote BP and cholesterol management program may help optimize guideline-directed therapy at scale, reduce cardiovascular risk, and minimize the need for in-person visits among diverse populations.

Motivation: The i2b2 platform is used at major academic health institutions and research consortia for querying for electronic health data. However, a major obstacle for wider utilization of the platform is the complexity of data loading that entails a steep curve of learning the platform's complex data schemas. To address this problem, we have developed the i2b2-etl package that simplifies the data loading process, which will facilitate wider deployment and utilization of the platform., Results: We have implemented i2b2-etl as a Python application that imports ontology and patient data using simplified input file schemas and provides inbuilt record number de-identification and data validation. We describe a real-world deployment of i2b2-etl for a population-management initiative at MassGeneral Brigham., Availability and Implementation: i2b2-etl is a free, open-source application implemented in Python available under the Mozilla 2 license. The application can be downloaded as compiled docker images. A live demo is available at https://i2b2clinical.org/demo-i2b2etl/ (username: demo, password: Etl@2021)., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2022. Published by Oxford University Press.)

Objective: Improving health data interoperability through application programming interfaces (APIs) is a focus of US policy initiatives and could have tremendous impact on many aspects of care delivery, such as innovation, operational efficiency, and patient-centered care. To better understand the landscape of API use cases, we interviewed US thought leaders involved in developing and implementing standard-based APIs., Materials and Methods: We conducted semi-structured virtual interviews with US subject matter experts (SMEs) on APIs. SMEs were asked to describe API use cases along with value and barriers for each use case. Written summaries were checked by the SME and analyzed by the study team to identify findings and themes., Results: We interviewed 12 SMEs representing diverse sectors of the US healthcare system, including academia, industry, public health agencies, electronic health record vendors, government, and standards organizations. Use cases for standards-based APIs fell into six categories: patient-facing, clinician-facing, population health and value-based care, public health, administrative, and social services. The value across use cases was viewed as unrealized to date, and barriers to the use of APIs varied by use case., Conclusions: SMEs identified a diverse set of API use cases where standard-based APIs had the potential to generate value. As policy efforts seek to increase API adoption, our work provides an early look at the landscape of API use cases, value propositions, and barriers. Additional effort is needed to better understand the barriers and how to overcome them to create value, such as through demonstration projects and rigorous evaluations for specific use cases., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

In recent years, the number of digital health tools with the potential to significantly improve delivery of healthcare services has grown tremendously. However, the use of these tools in large, complex health systems remains comparatively limited. The adoption and implementation of digital health tools at an enterprise level is a challenge; few strategies exist to help tools cross the chasm from clinical validation to integration within the workflows of a large health system. Many previously proposed frameworks for digital health implementation are difficult to operationalize in these dynamic organizations. In this piece, we put forth nine dimensions along which clinically validated digital health tools should be examined by health systems prior to adoption, and propose strategies for selecting digital health tools and planning for implementation in this setting. By evaluating prospective tools along these dimensions, health systems can evaluate which existing digital health solutions are worthy of adoption, ensure they have sufficient resources for deployment and long-term use, and devise a strategic plan for implementation., (© 2022. The Author(s).)

Analysis of health data typically requires development of queries using structured query language (SQL) by a data-analyst. As the SQL queries are manually created, they are prone to errors. In addition, accurate implementation of the queries depends on effective communication with clinical experts, that further makes the analysis error prone. As a potential resolution, we explore an alternative approach wherein a graphical interface that automatically generates the SQL queries is used to perform the analysis. The latter allows clinical experts to directly perform complex queries on the data, despite their unfamiliarity with SQL syntax. The interface provides an intuitive understanding of the query logic which makes the analysis transparent and comprehensible to the clinical study-staff, thereby enhancing the transparency and validity of the analysis. This study demonstrates the feasibility of using a user-friendly interface that automatically generate SQL for analysis of health data. It outlines challenges that will be useful for designing user-friendly tools to improve transparency and reproducibility of data analysis., Competing Interests: Declaration of competing interest The authors declare that they have no conflict of interest.

Objectives: Hypertension is a modifiable risk factor for numerous comorbidities and treating hypertension can greatly improve health outcomes. We sought to increase the efficiency of a virtual hypertension management program through workflow automation processes., Methods: We developed a customer relationship management (CRM) solution at our institution for the purpose of improving processes and workflow for a virtual hypertension management program and describe here the development, implementation, and initial experience of this CRM system., Results: Notable system features include task automation, patient data capture, multi-channel communication, integration with our electronic health record (EHR), and device integration (for blood pressure cuffs). In the five stages of our program (intake and eligibility screening, enrollment, device configuration/setup, medication titration, and maintenance), we describe some of the key process improvements and workflow automations that are enabled using our CRM platform, like automatic reminders to capture blood pressure data and present these data to our clinical team when ready for clinical decision making. We also describe key limitations of CRM, like balancing out-of-the-box functionality with development flexibility. Among our first group of referred patients, 76% (39/51) preferred email as their communication method, 26/51 (51%) were able to enroll electronically, and 63% of those enrolled (32/51) were able to transmit blood pressure data without phone support., Conclusion: A CRM platform could improve clinical processes through multiple pathways, including workflow automation, multi-channel communication, and device integration. Future work will examine the operational improvements of this health information technology solution as well as assess clinical outcomes., Competing Interests: W.J.G. reports consulting income from the Office of the National Coordinator for Health IT and Novocardia, Inc., both outside the scope of this work. B.M.S. reports institutional research grants to Brigham and Women's Hospital from AstraZeneca, Eisai, Merck, Novartis, NovoNordisk, and Pfizer and consulting fees from Allergan, Boehringer Ingelheim, Elsevier Practice Update Cardiology, Esperion, Hamni, Lexicon, Medtronic, and NovoNordisk., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Objectives: Medication use in the perioperative setting presents many patient safety challenges that may be improved with electronic clinical decision support (CDS). The objective of this paper is to describe the development and analysis of user feedback for a robust, real-time medication-related CDS application designed to provide patient-specific dosing information and alerts to warn of medication errors in the operating room (OR)., Methods: We designed a novel perioperative medication-related CDS application in four phases: (1) identification of need, (2) alert algorithm development, (3) system design, and (4) user interface design. We conducted group and individual design feedback sessions with front-line clinician leaders and subject matter experts to gather feedback about user requirements for alert content and system usability. Participants were clinicians who provide anesthesia (attending anesthesiologists, nurse anesthetists, and house staff), OR pharmacists, and nurses., Results: We performed two group and eight individual design feedback sessions, with a total of 35 participants. We identified 20 feedback themes, corresponding to 19 system changes. Key requirements for user acceptance were: Use hard stops only when necessary; provide as much information as feasible about the rationale behind alerts and patient/clinical context; and allow users to edit fields such as units, time, and baseline values (e.g., baseline blood pressure)., Conclusion: We incorporated user-centered design principles to build a perioperative medication-related CDS application that uses real-time patient data to provide patient-specific dosing information and alerts. Emphasis on early user involvement to elicit user requirements, workflow considerations, and preferences during application development can result in time and money efficiencies and a safer and more usable system., Competing Interests: K.C.N. receives author royalties from UpToDate, Inc. (Waltham, Massachusetts, United States). A.B. is a stockholder in Elimu Informatics, Inc. D.W.B. reports grants and personal fees from EarlySense (Ramat Gan, Israel), personal fees from CDI Negev (Beer-Sheva, Israel), equity from ValeraHealth, equity from Clew (Netanya Israel), equity from MDClone (Beer-Sheva, Israel), personal fees and equity from AESOP (Cambridge, Massachusetts, United States), and grants from IBM Watson Health (New York, New York, United States), outside the submitted work. The remaining authors have no competing interests., (Thieme. All rights reserved.)

The 21st Century Cures Act, passed in 2016, and the Final Rules it called for create a roadmap for enabling patient access to their electronic health information. The set of data to be made available, as determined by the Office of the National Coordinator for Health IT through the US Core Data for Interoperability expansion process, will impact the value creation of this improved data liquidity. In this commentary, we look at the potential for significant value creation from USCDI in the context of clinical bioinformatics research and advocate for the research community's involvement in the USCDI process to propel this value creation forward. We also describe 1 mechanism-using existing required APIs for full data export capabilities-that could pragmatically enable this value creation at minimal additional technical lift beyond the current regulatory requirements., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objectives: In an effort to mitigate COVID-19 related challenges for clinical research, the US Food and Drug Administration (FDA) issued new guidance for the conduct of 'virtual' clinical trials in late March 2020. This study documents trends in the use of connected digital products (CDPs), tools that enable remote patient monitoring and telehealth consultation, in clinical trials both before and after the onset of the pandemic., Design: We applied a comprehensive text search algorithm to clinical trial registry data to identify trials that use CDPs for remote monitoring or telehealth. We compared CDP use in the months before and after the issuance of FDA guidance facilitating virtual clinical trials., Setting: All trials registered on ClinicalTrials.gov with start dates from May 2019 through February 2021., Outcome Measures: The primary outcome measure was the overall percentage of CDP use in clinical trials started in the 10 months prior to the pandemic onset (May 2019-February 2020) compared with the 10 months following (May 2020-February 2021). Secondary outcome measures included CDP usage by trial type (interventional, observational), funder type (industry, non-industry) and diagnoses (COVID-19 or non-COVID-19 participants)., Results: CDP usage in clinical trials increased by only 1.65 percentage points, from 14.19% (n=23 473) of all trials initiated in the 10 months prior to the pandemic onset to 15.84% (n=26 009) of those started in the 10 months following (p<0.01). The increase occurred primarily in observational studies and non-industry funded trials and was driven entirely by CDP usage in trials for COVID-19., Conclusions: These findings suggest that in the short-term, new options created by regulatory guidance to stimulate telehealth and remote monitoring were not widely incorporated into clinical research. In the months immediately following the pandemic onset, CDP adoption increased primarily in observational and non-industry funded studies where virtual protocols are likely medically necessary due to the participants' COVID-19 diagnosis., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

The 21st Century Cures Act and the recently published "final rule" define standardized methods for obtaining electronic copies of electronic health record (EHR) data through application programming interfaces. The rule is meant to create an ecosystem of reusable, substitutable apps that can be built once but run at any hospital system "without special effort." Yet, despite numerous provisions around information blocking in the final rule, there is concern that the business practices that govern EHR vendors and health care organizations in the United States could still stifle innovation. We describe potential app ecosystems that may form. We caution that misaligned incentives may result in anticompetitive behavior and purposefully limited functionality. Closed proprietary ecosystems may result, limiting the value derived from interoperability. The 21st Century Cures Act and final rule are an exciting step in the direction of improved interoperability. However, realizing the vision of a truly interoperable app ecosystem is not predetermined., (©William J Gordon, Kenneth D Mandl. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 11.12.2020.)

Objective: We deployed a Remote Patient Monitoring (RPM) program to monitor patients with coronavirus disease 2019 (COVID-19) upon hospital discharge. We describe the patient characteristics, program characteristics, and clinical outcomes of patients in our RPM program., Methods: We enrolled COVID-19 patients being discharged home from the hospital. Enrolled patients had an app, and were provided with a pulse oximeter and thermometer. Patients self-reported symptoms, O 2 saturation, and temperature daily. Abnormal symptoms or vital signs were flagged and assessed by a pool of nurses. Descriptive statistics were used to describe patient and program characteristics. A mixed-effects logistic regression model was used to determine the odds of a combined endpoint of emergency department (ED) or hospital readmission., Results: A total of 295 patients were referred for RPM from five participating hospitals, and 225 patients were enrolled. A majority of enrolled patients (66%) completed the monitoring period without triggering an abnormal alert. Enrollment was associated with a decreased odds of ED or hospital readmission (adjusted odds ratio: 0.54; 95% confidence interval: 0.3-0.97; p  = 0.039). Referral without enrollment was not associated with a reduced odds of ED or hospital readmission., Conclusion: RPM for COVID-19 provides a mechanism to monitor patients in their home environment and reduce hospital utilization. Our work suggests that RPM reduces readmissions for patients with COVID-19 and provides scalable remote monitoring capabilities upon hospital discharge. RPM for postdischarge patients with COVID-19 was associated with a decreased risk of readmission to the ED or hospital, and provided a scalable mechanism to monitor patients in their home environment., Competing Interests: W.J.G. reports research funding from IBM, outside the scope of this study. W.J.G. reports consulting income from the Office of the National Coordinator, U.S. Department of Health and Human Services, outside the scope of this study. D.M.L. reports grants from Biofourmis, outside the submitted work., (Thieme. All rights reserved.)

Background: Vasopressin is used in conjunction with norepinephrine during treatment of patients with septic shock. Serum lactate is often used in monitoring of patients with sepsis; however, its importance as a therapeutic target is unclear. The objective of this study is to examine the relationship of vasopressin use on serum lactate levels in patients with sepsis., Methods: This study uses electronic heath records available via the Medical Information Mart for Intensive Care III. Patients were required to have a serum lactate monitoring during the intensive care unit (ICU) stay. The treatment was the administration of vasopressin between hours 3 and 18 of the ICU stay. Analysis was performed using a matched design., Results: Patients receiving vasopressin were more likely to have their serum lactate levels rise when compared to matched patients who did not receive vasopressin (odds ratio: 6.6; 95% confidence interval: 3.0-14.6, P < .001). Patients who received vasopressin had a median increase in serum lactate of 0.3 mmol/L, while patients who did not receive vasopressin had a median decrease in serum lactate of 0.7 mmol/L ( P < .001). There was no statistically significant difference between the control and treated groups' lactate trajectories prior to possible administration of vasopressin ( P = .15). The results did not change significantly when norepinephrine initiation was used as the index time., Conclusions: In patients with sepsis, the administration of vasopressin was associated with a statistically significant difference in lactate change over the course of 24 hours when compared to matched patients who did not receive vasopressin.

Importance: Although the Health Information Technology for Economic and Clinical Health (HITECH) Act has accelerated electronic health record (EHR) adoption since its passage, clinician satisfaction with EHRs remains low, and the association of HITECH with health care information technology (IT) entrepreneurship has remained largely unstudied., Objective: To determine whether the passage of the HITECH Act was associated with an increase in key measures of health care IT entrepreneurship., Design, Setting, and Participants: This economic evaluation of venture capital (VC) activity in the US from 2000 to 2019 examined funding trends in health care IT, EHR-related companies, and all VC investments before and after the passage of HITECH. A difference-in-differences analysis compared investments in health care IT companies with those of companies in 3 categories: general health care (non-IT), IT (non-health care), and all US VC transactions. Data were analyzed from September 2018 to August 2019., Exposures: Venture capital funding received by US companies before and after the HITECH Act., Main Outcomes and Measures: Venture capital investment in health care IT companies and the proportion of those investments going to seed-stage companies, a proxy for very early-stage entrepreneurship and innovation., Results: The data included 70 982 investments, of which 9425 (13.3%) were seed stage, 10 706 (15.1%) were early stage, and 50 851 (71.6%) were growth stage. After passage of the HITECH Act, investment in both health care IT companies and EHR-related companies increased at a rate much faster (13.0% and 11.4%, respectively) than VC as a whole (6.9%). In addition, the proportion of investments going to seed-stage health care IT companies increased compared with both overall VC investments and non-IT health care investments. Health care IT companies saw increased probabilities of transactions being seed-stage of 5.1% (SE, 2.2%; 95% CI, 0.8% to 9.3%; P = .02) compared with the entire sample of VC transactions and 13.6% (SE, 1.9%; 95% CI, 9.9% to 17.2%; P < .001) compared with non-IT health care VC transactions. Health care IT had essentially 0 increased probability of a transaction being seed stage compared with IT companies outside health care (-0.8% probability; SE, 2.4%; 95% CI, -5.4% to 3.9%; P = .75)., Conclusions and Relevance: Although widespread clinician dissatisfaction with EHR systems remains a challenge, the HITECH Act's incentive program may have catalyzed early-stage entrepreneurship in health care IT, suggesting an important role for incentives in promoting innovation.

Fueled by advances in technology, increased access to smartphones, and capital investment, the number of available health "apps" has exploded in recent years. Patients use their smartphones for many things, but not as much as they might for health, especially for managing their chronic conditions. Moreover, while significant work is ongoing to develop, validate, and evaluate these apps, it is less clear how to effectively disseminate apps into routine clinical practice. We propose a framework for prescribing apps and outline the key issues that need to be addressed to enable app dissemination in clinical care. This includes: education and awareness, creating digital formularies, workflow and EHR integration, payment models, and patient/provider support. As work in digital health continues to expand, integrating health apps into clinical care delivery will be critical if digital health is to achieve its potential., Competing Interests: Competing interestsW.J.G. reported research funding from IBM, for work unrelated to this manuscript. A.L. reported receiving personal fees from Abbott Medical Device Cybersecurity Council outside the submitted work. H.Z. reported employment at Cake, an end-of-life planning technology company. DWB reported consulting for EarlySense, which makes patient safety monitoring systems. He receives cash compensation from CDI-Negev Ltd, which is a not-for-profit incubator for health information technology startups. He receives equity from ValeraHealth, which makes software to help patients with chronic diseases, from Clew, which makes software to support clinical decision-making in intensive care, and from MDClone, which produces deidentified versions of clinical data., (© The Author(s) 2020.)

Background: While individual access to health records has traditionally been through paper and other physical media, there has been a recent push toward digitizing this process. Direct patient access to health data through application programming interfaces (APIs) is an important part of current United States policy initiatives, and Apple has created the product "Health Records on iPhone" to leverage APIs for this purpose., Objective: The objective of this study was to examine the characteristics of patients at our institution who connected their personal iPhone devices to our electronic health records (EHRs) system through "Health Records on iPhone", as compared to patients at our institution who used our patient portal but did not connect a personal device to our system., Methods: We examined adult patients at our institution who had authorized an iPhone device to download their health data from the Partners HealthCare EHR via APIs through "Health Records on iPhone" from February 18, 2018 (the date this feature was enabled at our health system) until February 17, 2019. We compared these patients to adult patients who used our portal at least once during this period but did not authorize an iPhone device to download their data via APIs., Results: Variables associated with an increased likelihood of using "Health Records on iPhone" included male gender (adjusted OR 3.36; 95% CI 3.11-3.62; P<.001) and younger age, particularly below 50 years of age. With each decade of age over 50, people were less likely to be "Health Records on iPhone" product users. Asian patients were more likely to use the product than Caucasian patients (adjusted OR 1.32; 95% CI 1.16-1.51; P<.001), though there was no significant difference between African Americans and Caucasians (adjusted OR 1.15; 95% CI 0.94-1.41; P=.17). Patients who resided in higher ZIP code income quartiles were more likely to be users than those in the lowest quartile., Conclusions: Early results from the implementation of patient-facing APIs at a single institution suggest that there are opportunities for expanding these technologies to ensure all patients are aware of, and have access to, their health data on their personal devices. More work is needed on expanding these technologies to different patient populations., (©William J Gordon, David W Bates, Daniel Fuchs, John Pappas, Sara Silacci, Adam Landman. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.08.2019.)

Background: Calculated panel reactive antibody (cPRA) scoring is used to assess whether platelet refractoriness is mediated by human leukocyte antigen (HLA) antibodies in the recipient. cPRA testing uses a national sample of US kidney donors to estimate the population frequency of HLA antigens, which may be different than HLA frequencies within local platelet inventories. We aimed to determine the impact on patient cPRA scores of using HLA frequencies derived from typing local platelet donations rather than national HLA frequencies., Methods: We built an open-source web service to calculate cPRA scores based on national frequencies or custom-derived frequencies. We calculated cPRA scores for every hematopoietic stem cell transplantation (HSCT) patient at our institution based on the United Network for Organ Sharing (UNOS) frequencies and local frequencies. We compared frequencies and correlations between the calculators, segmented by gender. Finally, we put all scores into three buckets (mild, moderate, and high sensitizations) and looked at intergroup movement., Results: 2531 patients that underwent HSCT at our institution had at least 1 antibody and were included in the analysis. Overall, the difference in medians between each group's UNOS cPRA and local cPRA was statistically significant, but highly correlated (UNOS vs. local total: 0.249 and 0.243, ρ = 0.994; UNOS vs. local female: 0.474 and 0.463, ρ = 0.987, UNOS vs. local male: 0.165 and 0.141, ρ = 0.996; P < 0.001 for all comparisons). The median difference between UNOS and cPRA scores for all patients was low (male: 0.014, interquartile range [IQR]: 0.004-0.029; female: 0.0013, IQR: 0.003-0.028). Placement of patients into three groups revealed little intergroup movement, with 2.96% (75/2531) of patients differentially classified., Conclusions: cPRA scores using local frequencies were modestly but significantly different than those obtained using national HLA frequencies. We released our software as open source, so other groups can calculate cPRA scores from national or custom-derived frequencies. Further investigation is needed to determine whether a local-HLA frequency approach can improve outcomes in patients who are immune-refractory to platelets., Competing Interests: There are no conflicts of interest.

Objectives: To more clearly define the landscape of digital medical devices subject to US Food and Drug Administration (FDA) oversight, this analysis leverages publicly available regulatory documents to characterise the prevalence and trends of software and cybersecurity features in regulated medical devices., Design: We analysed data from publicly available FDA product summaries to understand the frequency and recent time trends of inclusion of software and cybersecurity content in publicly available product information., Setting: The full set of regulated medical devices, approved over the years 2002-2016 included in the FDA's 510(k) and premarket approval databases., Primary and Secondary Outcome Measures: The primary outcome was the share of devices containing software that included cybersecurity content in their product summaries. Secondary outcomes were differences in these shares (a) over time and (b) across regulatory areas., Results: Among regulated devices, 13.79% were identified as including software. Among these products, only 2.13% had product summaries that included cybersecurity content over the period studied. The overall share of devices including cybersecurity content was higher in recent years, growing from an average of 1.4% in the first decade of our sample to 5.5% in 2015 and 2016, the most recent years included. The share of devices including cybersecurity content also varied across regulatory areas from a low of 0% to a high of 22.2%., Conclusions: To ensure the safest possible healthcare delivery environment for patients and hospitals, regulators and manufacturers should work together to make the software and cybersecurity content of new medical devices more easily accessible., Competing Interests: Competing interests: ABL is a member of the Abbott Medical Device Cybersecurity Council. DK is supported by the Greenwall Faculty Scholars Program in Bioethics, is a consultant to Circulatory Systems Advisory Panel of the Food and Drug Administration, and has provided consulting to the Baim Institute for Clinical Research for clinical trials of medical devices (unrelated to the study topic)., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: The study sought to understand the impact of a phishing training program on phishing click rates for employees at a single, anonymous US healthcare institution., Materials and Methods: We stratified our population into 2 groups: offenders and nonoffenders. Offenders were defined as those that had clicked on at least 5 simulated phishing emails and nonoffenders were those that had not. We calculated click rates for offenders and nonoffenders, before and after a mandatory training program for offenders was implemented., Results: A total of 5416 unique employees received all 20 campaigns during the intervention period; 772 clicked on at least 5 emails and were labeled offenders. Only 975 (17.9%) of our set clicked on 0 phishing emails over the course of the 20 campaigns; 3565 (65.3%) clicked on at least 2 emails. There was a decrease in click rates for each group over the 20 campaigns. The mandatory training program, initiated after campaign 15, did not have a substantial impact on click rates, and the offenders remained more likely to click on a phishing simulation., Discussion: Phishing is a common threat vector against hospital employees and an important cybersecurity risk to healthcare systems. Our work suggests that, under simulation, employee click rates decrease with repeated simulation, but a mandatory training program targeted at high-risk employees did not meaningfully decrease the click rates of this population., Conclusions: Employee phishing click rates decrease over time, but a mandatory training program for the highest-risk employees did not decrease click rates when compared with lower-risk employees., (© The Author(s) 2019. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

MedHistory is a web-based software module that graphically displays medication usage (y-axis) against time (x-axis). We set out to examine whether MedHistory would improve clinician's interactions with the medical record system. The authors invited house-officers at our institution to complete a survey about inpatient medication administration before and after using MedHistory. Detailed logs were also kept for 1 year after the study period. Compared to the pre-intervention survey, the post-intervention survey found that reviewing medication history was easier (pre: 13.2% vs post: 32.4%, p = .008), that medication review now fit within resident workflow (38.9% vs 75.7%, p < .001), and that there was increased satisfaction with the electronic health records software (2.6% vs 29.7%, p = .002). Additionally, determining the timing (29% vs 50.1%, p = .045) and dosing history (21.1% vs. 43.2%, p = .036) of inpatient medication administration was easier with MedHistory. Anti-infective agents and drugs requiring frequent adjustments were the most commonly reviewed. A graphical timeline of inpatient medications (MedHistory) was met with favorable response across multiple areas, including efficiency, speed, safety, and workflow.

Importance: Cybersecurity is an increasingly important threat to health care delivery, and email phishing is a major attack vector against hospital employees., Objective: To describe the practice of phishing simulation and the extent to which health care employees are vulnerable to phishing simulations., Design, Setting, and Participants: Retrospective, multicenter quality improvement study of a convenience sample of 6 geographically dispersed US health care institutions that ran phishing simulations from August 1, 2011, through April 10, 2018. The specific institutions are anonymized herein for security and privacy concerns., Exposures: Simulated phishing emails received by employees at US health care institutions., Main Outcomes and Measures: Date of phishing campaign, campaign number, number of emails sent, number of emails clicked, and email content. Emails were classified into 3 categories (office related, personal, or information technology related)., Results: The final study sample included 6 anonymized US health care institutions, 95 simulated phishing campaigns, and 2 971 945 emails, 422 062 of which were clicked (14.2%). The median institutional click rates for campaigns ranged from 7.4% (interquartile range [IQR], 5.8%-9.6%) to 30.7% (IQR, 25.2%-34.4%), with an overall median click rate of 16.7% (IQR, 8.3%-24.2%) across all campaigns and institutions. In the regression model, repeated phishing campaigns were associated with decreased odds of clicking on a subsequent phishing email (adjusted OR, 0.511; 95% CI, 0.382-0.685 for 6-10 campaigns; adjusted OR, 0.335; 95% CI, 0.282-0.398 for >10 campaigns)., Conclusions and Relevance: Among a sample of US health care institutions that sent phishing simulations, almost 1 in 7 simulated emails sent were clicked on by employees. Increasing campaigns were associated with decreased odds of clicking on a phishing email, suggesting a potential benefit of phishing simulation and awareness. With cyberattacks increasing against US health care systems, these click rates represent a major cybersecurity risk for hospitals.

Background: Connected medical devices and electronic health records have added important functionality to patient care, but have also introduced a range of cybersecurity concerns. When a healthcare organization suffers from a cybersecurity incident, its incident response strategies are critical to the success of its recovery., Objective: In this article, we identify gaps in research concerning cybersecurity response plans in healthcare. Through a systematic literature review, we develop aggregated strategies that professionals can use to construct better response strategies in their organizations., Methods: We reviewed journal articles on cyber incident response plans in healthcare published in PubMed and Web of Science. We sought to collect articles on the intersection of cybersecurity and healthcare that focused on incident response strategies., Results: We identified and reviewed 13 articles for cybersecurity response recommendations. We then extracted information such as research methods, findings, and implications. Finally, we synthesized the recommendations into a framework of eight aggregated response strategies (EARS) that fall under managerial and technological categories., Conclusions: We conducted a systematic review of the literature on cybersecurity response plans in healthcare and developed a novel framework for response strategies that could be deployed by healthcare organizations. More work is needed to evaluate incident response strategies in healthcare.

Interoperability in healthcare has traditionally been focused around data exchange between business entities, for example, different hospital systems. However, there has been a recent push towards patient-driven interoperability, in which health data exchange is patient-mediated and patient-driven. Patient-centered interoperability, however, brings with it new challenges and requirements around security and privacy, technology, incentives, and governance that must be addressed for this type of data sharing to succeed at scale. In this paper, we look at how blockchain technology might facilitate this transition through five mechanisms: (1) digital access rules, (2) data aggregation, (3) data liquidity, (4) patient identity, and (5) data immutability. We then look at barriers to blockchain-enabled patient-driven interoperability, specifically clinical data transaction volume, privacy and security, patient engagement, and incentives. We conclude by noting that while patient-driving interoperability is an exciting trend in healthcare, given these challenges, it remains to be seen whether blockchain can facilitate the transition from institution-centric to patient-centric data sharing.

Background: Fast Facts Mobile (FFM) was created to be a convenient way for clinicians to access the Fast Facts and Concepts database of palliative care articles on a smartphone or tablet device. We analyzed usage patterns of FFM through an integrated analytics platform on the mobile versions of the FFM application., Objective: The primary objective of this study was to evaluate the usage data from FFM as a way to better understand user behavior for FFM as a palliative care educational tool., Design: This is an exploratory, retrospective analysis of de-identified analytics data collected through the iOS and Android versions of FFM captured from November 2015 to November 2016., Measurements: FFM App download statistics from November 1, 2015, to November 1, 2016, were accessed from the Apple and Google development websites. Further FFM session data were obtained from the analytics platform built into FFM., Results: FFM was downloaded 9409 times over the year with 201,383 articles accessed. The most searched-for terms in FFM include the following: nausea, methadone, and delirium. We compared frequent users of FFM to infrequent users of FFM and found that 13% of all users comprise 66% of all activity in the application., Conclusions: Demand for useful and scalable tools for both primary palliative care and specialty palliative care will likely continue to grow. Understanding the usage patterns for FFM has the potential to inform the development of future versions of Fast Facts. Further studies of mobile palliative care educational tools will be needed to further define the impact of these educational tools.

Platelet transfusions are a cornerstone of therapy for patients who develop thrombocytopenia while undergoing Hematopoietic Stem Cell Transplantation (HSCT). Many patients who develop Platelet Transfusion Refractoriness (PTR) require HLA-matched platelets. Identifying these patients early could lead to better utilization of platelets as well as increased platelet counts. We built a SMART on FHIR visualization tool to aid the oncology, blood bank, and blood donor center teams in identifying these patients by showing trends in thrombocytopenia along with a computer generated calculated Panel Reactive Antibody (cPRA) level. To do this, we required a FHIR interface to our HLA database. We describe our methods and outcome for constructing this FHIR interface, as well as the architecture and data flow of HLA data from its proprietary database to the SMART on FHIR environment and application database along with RESTful cPRA web service calculator. Future work will evaluate the clinical impact of this platelet visualization tool and overall success of our FHIR implementation.

Background: US cholesterol guidelines use original and simplified versions of the Framingham model to estimate future coronary risk and thereby classify patients into risk groups with different treatment strategies. We sought to compare risk estimates and risk group classification generated by the original, complex Framingham model and the simplified, point-based version., Methods: We assessed 2,543 subjects age 20-79 from the 2001-2006 National Health and Nutrition Examination Surveys (NHANES) for whom Adult Treatment Panel III (ATP-III) guidelines recommend formal risk stratification. For each subject, we calculated the 10-year risk of major coronary events using the original and point-based Framingham models, and then compared differences in these risk estimates and whether these differences would place subjects into different ATP-III risk groups (<10% risk, 10-20% risk, or >20% risk). Using standard procedures, all analyses were adjusted for survey weights, clustering, and stratification to make our results nationally representative., Results: Among 39 million eligible adults, the original Framingham model categorized 71% of subjects as having "moderate" risk (<10% risk of a major coronary event in the next 10 years), 22% as having "moderately high" (10-20%) risk, and 7% as having "high" (>20%) risk. Estimates of coronary risk by the original and point-based models often differed substantially. The point-based system classified 15% of adults (5.7 million) into different risk groups than the original model, with 10% (3.9 million) misclassified into higher risk groups and 5% (1.8 million) into lower risk groups, for a net impact of classifying 2.1 million adults into higher risk groups. These risk group misclassifications would impact guideline-recommended drug treatment strategies for 25-46% of affected subjects. Patterns of misclassifications varied significantly by gender, age, and underlying CHD risk., Conclusions: Compared to the original Framingham model, the point-based version misclassifies millions of Americans into risk groups for which guidelines recommend different treatment strategies.

Mesenchymal stem cells or chondrocytes have been implanted into joints in biodegradable matrices in order to improve the quality of healing cartilage defects; however, insufficient biomechanical strength of the construct at implantation is a limiting factor for clinical application. Logically, a construct with better biomechanical characteristics would provide better results. Tantalum trabecular metal (TTM) is osteoconductive and mechanically similar to subchondral bone. The objective of this pilot study was to determine if TTM is also chondroconductive. Small sections of TTM were cultured with emu and canine chondrocytes in static and dynamic culture environments. The sections cultured in dynamic bioreactors were diffusely covered with a cartilaginous matrix. Sections cultured in static conditions had no growth. Histologic evaluation from emu and canine dynamic cultures showed tissue that was heavily populated with mesenchymal cells that resembled chondrocytes, and glycosaminoglycan staining that was distributed throughout the matrix. Type II collagen content in the canine dynamic culture was 84% by SDS-PAGE. Tantalum trabecular metal is chondroconductive in vitro in a dynamic environment when cultured with adult canine or emu chondrocytes. This technology could be expanded to determine if cartilaginous-metallic constructs may be used for joint resurfacing of osteoarthritic joints., (Copyright (c) 2005 Wiley Periodicals, Inc.)

Objective: To evaluate the analgesic effects of topical administration of bupivacaine, i.m. administration of butorphanol, and transdermal administration of fentanyl in cats undergoing onychectomy., Design: Prospective study., Animals: 27 healthy adult cats., Procedure: Cats were randomly assigned to 1 of 3 treatment groups, and unilateral (left forefoot) onychectomy was performed. Gait analysis was performed before and 1, 2, 3, and 12 days after surgery. All forces were expressed as a percentage of the cat's body weight., Results: On day 2, peak vertical force (PVF) was significantly decreased in cats treated with bupivacaine, compared with cats treated with butorphanol or fentanyl. The ratio of left forelimb PVF to PVF of the other 3 limbs was significantly lower on day 2 in cats treated with bupivacaine than in cats treated with fentanyl. No significant differences in vertical impulse (VI) were found between groups on any day. Values for PVF, VI, and the PVF ratio increased progressively following surgery. However, for all 3 groups, values were still significantly decreased, compared with baseline values, 12 days after surgery., Conclusions and Clinical Relevance: Results suggest that limb function following onychectomy is significantly better in cats treated with fentanyl transdermally or butorphanol i.m. than in cats treated with bupivacaine topically. Regardless of the analgesic regimen, limb function was still significantly reduced 12 days after surgery, suggesting that long-term analgesic treatment should be considered for cats undergoing onychectomy. Irrigation of the surgical incisions with bupivacaine prior to wound closure cannot be recommended as the sole method for providing postoperative analgesia in cats undergoing onychectomy.

Objective: To determine the outcome and effect of surgical technique on limb function after surgery for rupture of the cranial cruciate ligament (RCCL) and injury to the medial meniscus in Labrador Retrievers., Study Design: Prospective clinical study., Animals: 131 Labrador Retrievers with unilateral RCCL and injury to the medial meniscus and 17 clinically normal Labrador Retrievers., Procedure: Affected dogs had partial or complete medial meniscectomy and lateral suture stabilization (LSS), intracapsular stabilization (ICS), or tibial plateau leveling osteotomy (TPLO). Limb function was measured before surgery and 2 and 6 months after surgery. Treated dogs were evaluated to determine the probability that they could be differentiated from clinically normal dogs and tested to determine the likelihood that they achieved improvement., Results: No difference was found between LSS or TPLO groups, but dogs treated with ICS had significantly lower ground reaction forces at 2 and 6 months. Compared with clinically normal dogs only, 14.9% of LSS-, 15% of ICS-, and 10.9% of TPLO-treated dogs had normal limb function. Improvement was seen in only 15% of dogs treated via ICS, 34% treated via TPLO, and 40% treated via LSS., Conclusions and Clinical Relevance: Surgical technique can influence limb function after surgery. Labrador Retrievers treated via LSS, ICS, or TPLO for repair for of RCCL and medial meniscal injury managed with partial or complete meniscectomy infrequently achieve normal function. Results of LSS and TPLO are similar and superior to ICS.

Objective: To determine peak vertical force (PVF) and vertical impulse (VI) in cats that had or had not undergone bilateral forelimb onychectomy., Animals: 26 healthy adult cats., Procedure: Onychectomized cats (n = 13) had undergone surgery more than 6 months prior to the study. The PVF and VI were collected from all limbs of each cat with a 2-m pressure platform walkway. Cats were allowed to walk at a comfortable velocity, and acceleration was restricted to +/- 0.5 m/s2. Five valid trials were recorded for each cat with all trials collected in a single 1-hour session. All forces were normalized to and expressed as a percentage of the cat's body weight., Results: Gait data were successfully collected in all cats. No significant difference was found for PVF or VI between cats that had or had not had onychectomy. Limb loads were greater in forelimbs than hind limbs for all trials. Mean PVF and VI in the forelimbs of cats in the nononychectomy group were 56.41% and 18.85%, respectively. Mean PVF and VI in the hind limbs of cats in the nononychectomy group were 50.22% and 14.56%, respectively., Conclusions and Clinical Relevance: Gait analysis was successfully performed in cats with a pressure platform walkway. The absence of differences in PVF and VI between the 2 groups of cats suggests that bilateral forelimb onychectomy did not result in altered vertical forces measured more than 6 months after surgery in cats.

Objective: To document, using pressure platform gait analysis, the effect of perioperative oral carprofen on limb function and pain after cranial cruciate ligament surgery in dogs., Study Design: Blinded, prospective clinical investigation., Animals: Twenty dogs with naturally occurring unilateral cranial cruciate disease., Procedure: Physiologic indices, subjective pain scoring, and pressure platform gait analyses were performed before and 24, 48, and 72 hours after surgery. Correlations were assessed between methods of evaluation and the data was compared across treatment groups., Results: No strong correlations were noted between physiologic data, subjective scoring systems, or gait analysis data at a walk or stance. Although average measures of limb function were nearly twice as large in dogs treated with carprofen, no significant differences between groups over time were identified. No significant differences were noted in any other measure of pain or limb function. Power analysis of peak vertical force at a walk indicated that significant difference would have been detected had the number of dogs in each group been increased to 35., Conclusion: When limb function was assessed with pressure platform gait analysis no statistical difference was noted between groups with respect to PVF and VI at a walk or stance, although average ground reaction forces for dogs in the carprofen group were greater than the traditional pain management group at all time points., Clinical Relevance: Oral carprofen appears to provide some benefit for the treatment of postoperative orthopedic pain.

Objective: To evaluate the relationship between limb function and radiographic evidence of stifle osteoarthrosis (OA) in dogs., Study Design: The relationship between force platform data and radiographic OA score was evaluated on 2 separate days using regression analysis. Interday variation was also assessed., Animals: Forty-one dogs with visible lameness and radiographic evidence of stifle OA., Methods: Force platform data were collected at a velocity of 1.7 to 2.0 m/s for 5 trials on day 1 and day 8. Radiographs taken on day 1 were scored using a previously reported OA scoring system., Results: No significant relationship was found between force platform data and OA score. No significant differences were found between any day 1 and day 8 force platform values., Conclusions: Although radiographic evidence of stifle OA provides evidence of pathology, it does a poor job of representing limb function. In addition, the absence of significant differences between day 1 and day 8 values in this population of dogs supports use of only a single force platform evaluation before measuring a treatment effect., Clinical Relevance: The presence of OA in the stifle joint does not correlate with clinical function; radiographic outcome should be used cautiously as a predictor of clinical outcome., (Copyright 2003 by The American College of Veterinary Surgeons)

A method is given for constructing simple new "finite elements" that seem well-suited to approximating smooth functions in rectangular polygons decomposed into rectangular cells. Some of the key properties of the elements are derived, and analogous three-dimensional "bricks" are constructed.