Special Feature CKD as a Model for Improving Chronic Disease Care through Electronic Health Records

Abstract Electronic health records have the potential to improve the care of patients with chronic medical conditions. CKD provides a unique opportunity to show this potential: the disease is common in the United States, there is significant room to improve CKD detection and management, CKD and its related conditions are defined primarily by objective laboratory data, CKD care requires collaboration by a diverse team of health care professionals, and improved access to CKD-related data would enable identification of a group of patients at high risk for multiple adverse outcomes. However, to realize the potential for improvement in CKD-related care, electronic health records will need to provide optimal functionality for providers and patients and interoperability across multiple health care settings. The goal of the National Kidney Disease Education Program Health Information Technology Working Group is to enable and support the widespread interoperability of data related to kidney health among health care software applications to optimize CKD detection and management. Over the course of the last 2 years, group members met to identify general strategies for using electronic health records to improve care for patients with CKD. This paper discusses these strategies and provides general goals for appropriate incorporation of CKD-related data into electronic health records and corresponding design features that may facilitate (1) optimal care of individual patients with CKD through improved access to clinical information and decision support, (2) clinical quality improvement through enhanced population management capabilities, (3) CKD surveillance to improve public health through wider availability of population-level CKD data, and (4) research to improve CKD management practices through efficiencies in study recruitment and data collection. Although these strategies may be most effectively applied in the setting of CKD, because it is primarily defined by laboratory abnormalities and therefore, an ideal computable electronic health record phenotype, they may also apply to other chronic diseases

Factors Associated with Revision Surgery after Internal Fixation of Hip Fractures

Background: Femoral neck fractures are associated with high rates of revision surgery after management with internal fixation. Using data from the Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trial evaluating methods of internal fixation in patients with femoral neck fractures, we investigated associations between baseline and surgical factors and the need for revision surgery to promote healing, relieve pain, treat infection or improve function over 24 months postsurgery. Additionally, we investigated factors associated with (1) hardware removal and (2) implant exchange from cancellous screws (CS) or sliding hip screw (SHS) to total hip arthroplasty, hemiarthroplasty, or another internal fixation device. Methods: We identified 15 potential factors a priori that may be associated with revision surgery, 7 with hardware removal, and 14 with implant exchange. We used multivariable Cox proportional hazards analyses in our investigation. Results: Factors associated with increased risk of revision surgery included: female sex, [hazard ratio (HR) 1.79, 95% confidence interval (CI) 1.25-2.50; P = 0.001], higher body mass index (fo

Understanding the functions and operations of data monitoring committees: Survey and focus group findings

Background: The use of data monitoring committees in the conduct of clinical trials has increased and evolved, but there is a lack of published information on when data monitoring committees are needed and utilized, the acceptable range of data monitoring committee practices, and appropriate qualifications of data monitoring committee members. Methods: To gain a better understanding of data monitoring committee operations and areas for improvement, the Clinical Trials Transformation Initiative conducted a survey and set of focus groups. A total of 143 respondents completed the online survey: 76 data monitoring committee members, 52 sponsors involved with organization of data monitoring committees, and 15 statistical data analysis center representatives. There were 42 focus group participants, including data monitoring committee members; patients and/or patient advocate data monitoring committee members; institutional review board and US Food and Drug Administration representatives; industry, government, and non-profit sponsors; and statistical data analysis center representatives. Results: Participants indicated that the primary responsibility of a data monitoring committee is to be an independent advisory body representing the interests of trial participants by assessing the risk and benefit ratio in ongoing trials. They noted that data monitoring committees must have access to unmasked data in order to perform this role. No clear consensus emerged regarding specific criteria for requiring a data monitoring committee for a given trial, and some participants felt data monitoring committees may be overused. Respondents offered suggestions for the data monitoring committee charter and communications with sponsors, institutional review boards, and regulators. Overall, data monitoring committee members reported that they are able to function independently and their recommendations are almost always accepted by the sponsor. Participants indicated that there are no standards or guidelines pertaining to qualifications of data monitoring committee members. Furthermore, only 8% (6/72) of data monitoring committee member survey respondents received any formal training, and 94% (68/72) were not aware of any training programs. Conclusion: Findings from the survey and focus groups provide a better understanding of contemporary data monitoring committee operations and insights regarding challenges and best practices. Overall, it was clear that increased training will be needed to prepare the next generation of qualified data monitoring committee members to meet the growing demand. These findings can be used by Clinical Trials Transformation Initiative and others to develop recommendations and tools to improve data monitoring committee operations and the overall quality of trial oversight. </jats:sec