Complete Health Record Research Articles

A service-based RBAC & MAC approach incorporated into the FHIR standard

Health Information Exchange (HIE) provides a more complete health record with the aim to improve patient care with relevant data gathered from multiple Health Information Technology (HIT) systems. In support of HIE, the Health Level Seven (HL7) XML standard was developed to manage, exchange, integrate, and retrieve electronic health information. In 2011, the Fast Healthcare Interoperable Resources (FHIR) standard, based on HL7, was proposed to facilitate the development of mobile Health (mHealth) apps with HIT data sharing via a common modeling format. FHIR utilizes RESTful APIs enabled with a FHIR server for information usage and exchange in the cloud. FHIR has a security specification, but does not define actual security mechanisms for secure data exchange via service invocations. If services are the primary means of access, there must be a way to control who can invoke which service at which time. This paper proposes the use of Role-Based Access Control (RBAC) and Mandatory Access Control (MAC) to define permissions based on role and/or the sensitivity level of services. This is accomplished by evolving RBAC and MAC to support permissions on services (as opposed to the usual object view) at a model level applied to a setting where a mobile application is using RESTful APIs. The resulting service-based model is incorporated into the FHIR standard to control the access of who can invoke which services of FHIR RESTful APIs that manage the sensitive healthcare data; work is demonstrated via an mHealth application that interacts with the OpenEMR HIT system via the HAPI FHIR server.

Friday, September 28, 2018 3:00 PM–4:00 PM abstracts: the gravity of obesity: 232. The impact of body mass index on severity of cervical spine fracture

BACKGROUND CONTEXT Several studies have analyzed the impact of obesity on severity and specific injury predispositions due to MVA using the Abbreviated Injury Scale (AIS). Although AIS grades individual regions according to severity from minor to maximum, it does not reflect specific description of injury in each region. In the case of cervical spine injury, the type of fracture pattern and spinal cord injury (SCI) cannot be determined from the AIS score. Therefore, the knowledge on impact of obesity on severity of cervical spine injury is limited from prior trauma studies.This information will be useful for providers in the ED to ascertain risk of severe cervical spine injury due to patient's BMI. In addition to risk estimation, fracture pattern, SCI, and patient-specific comorbidities are among important considerations in deciding treatment strategy. PURPOSE The objective of our study was to study the impact of BMI on severity of cervical spine injury after adjusting for injury and patient related variables. STUDY DESIGN/SETTING Retrospective cohort study. PATIENT SAMPLE Patients with traumatic cervical spine fracture presenting to a level I trauma center between January 1, 2010 and December 31, 2014. OUTCOME MEASURES Severity of cervical spine fracture according to AO Spine sub-axial cervical spine fracture classification. METHODS Approval from Institutional Review Board (IRB) was taken before identifying patients for data collection. Review of electronic medical record (EMR) was done to collect patient information. Patients were selected per the following inclusion criteria: (i) traumatic injury that resulted in sub-axial cervical spinal fracture, (ii) patient age 18 to 80 years, (iii) availability of cervical computed tomography (CT) scan, (iv) complete health record of patient clinical and injury characteristics. Patients were excluded if they had isolated atlanto-axial injury or did not have a cervical CT scan. Patients who had suspected pathological fracture were also excluded. CT scans of the cervical spine were assessed by an observer blinded to clinical information.Cervical spine injuries were categorized as severe (S) if they had burst fracture involving both end plates, tension band injuries, and dislocation injuries (Types A4, B0, B1, B2, B3) and/or associated SCI. Injuries with insignificant fractures or single endplate burst morphology (Types A0, A1, A2, A3) and no SCI were categorized as less severe (LS) for our analysis. The association between BMI and severity of cervical spine fracture was studied by multiple-variable logistic regression analysis using a conditional stepwise backward elimination model. The dependent variable was severity of injury with less severe (LS) fracture serving as reference. Independent variable of interest included BMI which was entered as a continuous variable and forced to be in the model at all steps. Other covariates included in the model included age, gender, ethnicity, smoking status, medical comorbidities, mechanism of injury, and other significant organ system injury. All variables were initially entered in the model and backward elimination removal criteria was set at p>.1. RESULTS A total of 751 patients with cervical spine fracture were identified, out of which 291 patients met our inclusion criteria and had adequate records available for analysis. The mean age of included patients was 46.1±19.3 years, and 212 patients (75.8%) were males.Based on morphology of fracture and SCI, 106 (36.4%) were categorized as severe (S) injury. The remaining 185 (63.6%) patients were classified as less severe (LS) injury.%). MVA was the most common injury mechanism (n=177, 60.8%) followed by fall from height (n=85, 29.2%) and random traumatic events (n=29, 10.0%).Our multiple-variable logistic regression model found that increasing BMI was not associated with a likelihood of severe cervical spine injury after adjusting for other clinical and injury parameters (OR 1.03, 95% CI: 0.97–1.08, p=.34). A sub-analysis of MVA cases was done to include side of impact, rollover, protection, and ejection of occupant as covariates in addition to other patient variables. Although trending towards significance, the odds ratio of severe cervical spine injury due to increasing patient BMI was 1.08 (95% CI: 0.99–1.18, p=.06). In this analysis, the presence of rollover was also represented in the final model with OR 2.55 (95% CI: 0.98–6.66, p=.06). CONCLUSIONS In conclusion, our findings indicate that patients with higher BMI may be predisposed to more severe cervical spine fracture and/or SCI after MVA, especially when rollover is present. The same risk may not be present in other common modes of injury such as nonrollover MVA and falls. Further prospective studies with larger sample size, use of clinically relevant outcome parameters (fracture classification, neural deficit), and comprehensive measurement of injury related variables may be helpful to corroborate our findings.

Quality aspects of Dutch general practice–based data: a conceptual approach

General practice-based data, collected within general practice registration networks (GPRNs), are widely used in research. The quality of the data is important but the recording criteria about what type of information is collected and how this information should be recorded differ between GPRNs. We aim to identify aspects that describe the quality of general practice-based data in the Netherlands. To investigate the quality aspects, we used the method of concept mapping, a structured conceptualization process for a complex multi-dimensional topic. We explored the ideas of representatives from 10 Dutch GPRNs on the quality of general practice-based data in five steps: preparation, generation of statements, structuring, representation and interpretation. In a brainstorm session, 10 experts generated statements about good data quality from general practice, which we completed with information from the literature. In total, 18 experts participated in the ranking and clustering of the statements. These results were analysed using ARIADNE software, using a combination of principal component analysis and cluster analysis techniques. Finally, the clusters were labelled based on their content. A total of 72 statements were analysed, which resulted in a two-dimensional picture with six clusters, 'complete health record', 'coding of information', 'episode oriented recording', 'diagnostic validity', 'recording agreements' and 'residual category'. The quality of general practice-based data can be considered on five content-based aspects. These aspects determine the quality of recording.

Establishing the Centrality of Health Informatics in Physical Therapist Education: If Not Now, When?

Background and Purpose. Physical therapists increasingly struggle to manage the vast amount of information required to make sound clinical decisions. This struggle occurs, in part, because of a lack of knowledge and skills needed to effectively use the potent tool of information technology for systematically processing data and supporting information and knowledge. The field of health informatics has emerged as an interdisciplinary science that evaluates how health information and knowledge can be effectively used for clinical decision making. Health care leaders have recognized informatics competencies as essential in other health care education programs, especially as a foundation for evidence-based practice. The purpose of this article is to describe the current state of health informatics in physical therapist education, to summarize the rationale for incorporating informatics in physical therapist education, and to propose a framework for incorporating this content into physical therapist education. Position and Rationale. Physical therapist education should identify and incorporate health informatics as a foundational domain. Failing to prepare clinicians with technology competencies will hamper progress towards our profession's goals of fully availing ourselves of technologies that can facilitate more effective and efficient care. Because adopting health information technology is a top national priority, we must move quickly to ensure that physical therapists can continue to thrive in the emerging electronic infrastructure. Discussion and Conclusion. Although some concepts of health informatics are incorporated in physical therapist education program's core documents, this inclusion was not based on the perspective of health informatics as an applied scientific discipline. In conjunction with the APTA's concerted effort to adopt interoperable electronic health record systems, the profession should develop a strategic plan for ensuring that physical therapists have the knowledge and skills to use the tools of informatics effectively. We present specific recommendations to help strengthen the centrality of informatics within physical therapist education, such as including health informatics as a foundational domain and fully developing the set of core informatics competencies for physical therapy. We encourage the academic community to engage in activities and dialog that clarify the role of informatics in physical therapist education. Key Words. Health informatics, Physical therapist education, Informatics competencies. BACKGROUND AND PURPOSE Health professionals, including physical therapists, increasingly struggle to manage the vast amount of information required to make sound clinical decisions, in part because they often lack the knowledge and skills to effectively use the potent tool of information technology for systematically processing data and supporting information and knowledge management.1 The field of health informatics has emerged as an interdisciplinary science that evaluates how health information and knowledge can be effectively used for clinical decision-making. With timely access to a patient's complete health record and computerized systems that make patient-specific recommendations based on best evidence, physical therapists are likely to make better clinical decisions. Few of these systems have been evaluated within physical therapy,2 but systemic reviews from the broader health informatics field have convincingly demonstrated that computers can improve quality by increasing providers' adherence to guideline-based care, improving surveillance and monitoring in disease management, and decreasing medication errors.3'4 As just one example from many, a computerized reminder for contact isolation for patients known to be colonized or infected with resistant organisms improved the isolation rate from 33% to 89% while simultaneously decreasing the median time for contact isolation orders to be written from 16. …

Electronic Health Records

Forces are aligning to shift American health care into the Information Age: an age which financial institutions, airlines, supermarkets and most manufacturing industries have already entered. The shift, which these institutions have already experienced, will facilitate the establishment and widespread use of standardized databases in health care. The databases are known by the terms electronic medical records (EMRs), electronic health record (EHRs) or personal health records (PHRs). These forces underlie today's shift towards full use of a universally accepted electronic medical record, electronic health record and for a personal health record: An unprecedented revolution in computer and communication technologies The widespread availability of affordable electronic tools Burgeoning interest among patients in having access to their own medical information Rapid progress in understanding the human genome and proteosome The rising cost of health care The increasing administrative burden upon physicians A perception that medical errors are increasing Demands for widely comparable measures of quality care The need for post-marketing surveys of new drugs Our increasingly mobile society Greater emphasis upon evidence-based medicine Reimbursement incentives that pay for using EHRs and for providing quality care Reduced malpractice premiums for physicians that fully employ these technologies. What is an Electronic Health Record? An EMR contains the results of clinical and administrative encounters between a provider (physician, nurse, telephone triage nurse, and others) and a patient that occur during episodes of patient care. Consequently, the EMR reflects the practice style, job function, knowledge and skill of the providers who create it. It necessarily includes data structures and data elements that reflect those providers' systems. In an attempt to bring some structure to this emerging field, in 1991 the Institute of Medicine defined the basic functions of an EMR, then known as the computer-based patient record (CPR). The Institute of Medicine's definition remains the gold standard (see Table 1 on page 58). Table 1. EHR functions To supplement the provider-generated information in the EMR, the personal health record (PHR) is a medical record maintained by the patient. The PHR includes electronic copies of information patients have received from their providers. Finally, the concept of the EHR was formulated to integrate an individual's multiple, physician-generated, electronic medical records and the patient-generated personal health record. Intended to be comprehensive, the EHR should facilitate optimal management of the health of an individual or, when used in aggregate, of a population. EHRs should allow sharing of information about patients between any authorized providers. A patient should be able to enter any health care setting, provide authorization, and then consult with a provider who has ready access to his complete health record. EHRs should be securely linked over the Internet and should be integrated seamlessly with medical information for the education of both providers and patients. Table 2 lists common functions of an EHR divided by practice, clinical, system, and chemotherapy/drug management components. Table 2 lists some common medical and oncology-specific data elements (data fields) for an electronic health record. Table 2. Data elements for personal, provider, and oncology health records