Perspectives in health information management / AHIMA, American Health Information Management Association最新文献

The healthcare sector continues to be the industry suffering one of the highest costs of a data security breach. Healthcare lags behind other industries in cybersecurity preparedness despite advances in cybersecurity technologies. Technical safeguards to protect electronic health records must be combined with human behavioral interventions to promote a robust cybersecurity plan. Using data from the United States Department of Health and Human Services, we conducted an exploratory analysis of past data breaches in healthcare organizations from January 2015 to December 2020 to explore the extent to which human elements played a role in data security incidents. We found that a vast majority of health records were compromised due to poor human security. The mean number of records affected by a breach due to unintentional insider threats is more than twice that of breaches caused by malicious intent such as external cyberattacks and theft. Our findings also indicate that, on average, more patient records are compromised from falling for a phishing scam than any other reason. We argue that proper cybersecurity contingency plans in healthcare must include human behavioral interventions that go beyond technical controls.

This case study describes use of health information technology for enhanced team-based care and care coordination between primary care providers and infectious disease specialists for curing and eventually eliminating hepatitis C in West Virginia. This program, the West Virginia Hepatitis Academic Mentoring Partnership, aims to improve outcomes of West Virginians with chronic hepatitis C infection by training and supporting primary care providers to screen, diagnose, evaluate, treat, cure, and follow patients in the community rather than referring them to distant specialists with long wait times. This initiative supports health equity by increasing access to quality care in severely under-resourced rural areas. Primary care providers engage with hepatitis C experts in a web-based training and mentoring process, combined with informatics training in use of a customized Research Electronic Data Capture (REDCAP) platform for secure data tracking and bidirectional communication. This use of an informatics platform available to all partners supports shared decision-making between primary care providers and specialists, fostering a primary care learning network for improved hepatitis C care in West Virginia.

Community pharmacies provide the convenience and ease of administrating vaccinations outside traditional settings. Vaccinations are health initiatives that protect communities and improve health outcomes in all populations. Despite their accessibility and supporting clinical data, various influential factors contribute to the current suboptimal rates of vaccine administration. Given the common barriers to vaccine administration, this research narrows down to address a specific barrier and attempts to implement a method that focuses on improving vaccine rates in community pharmacies. This research is a case study that utilizes the Define, Measure, Analyze, Improve, Control (DMAIC) model of Lean Six Sigma and aims to use this quality improvement process to identify, measure, analyze, and implement a training program to facilitate pharmacists in high-quality vaccine recommendations to promote higher rates of pneumococcal vaccinations in community settings.

Introduction: Recently, several technologies have been developed for being used in the field of geriatric emergency medicine. As a large number of elderly patients visit emergency departments, the use of health information technology in this department can help to improve patient care and control the outcome of diseases. The present study aimed to identify opportunities for using various health information technologies for elderly care in the emergency department.

Methods: This qualitative study was conducted in 2020. The participants included geriatricians, geriatric nurses, emergency medicine specialists, and nurses who worked in the emergency department. In total, 33 semi-structured interviews were conducted, and data were analyzed by using framework analysis method and MAXQDA software.

Results: The findings of the qualitative study included four main themes, nine subthemes, and 20 categories. The main themes were the common process of elderly care in the emergency departments, data required for elderly care in the emergency departments, the elderly treatment team, and current information technologies used in the emergency departments for elderly care. Overall, the results showed that there was no specific workflow for elderly care in the emergency departments; the great workload of this department prevents the clinicians to conduct cognitive and functional assessments; geriatricians were not involved in the care process; and none of the current information systems were designed specifically for elderly patients. It seems that using specific heath information technology for elderly care in the emergency department can help to overcome current challenges.

Conclusion: Identifying opportunities for using health information technologies for geriatric patients in the emergency department can lead to better use of financial, physical, and human resources, and improve staff performance. These systems can be designed and used for different purposes such as reducing work load, readmissions, and hospitalization. Improving access to data and better collaboration between different specialties are other benefits of using these systems. However, more research is required to evaluate the effectiveness of technology in this area.

On October 1, 2012, as part of the Affordable Care Act, the Centers for Medicare and Medicaid Services began to reduce payments to hospitals with excessive rehospitalization rates through the Hospital Readmissions Reduction Program. These financial penalties have intensified hospital leaders' efforts to implement strategies to reduce readmission rates. The purpose of this multiple case study was to explore organizational strategies that leaders use to reduce readmission rates in hospitals located in a non-Medicaid-expansion state. The data collection included semistructured interviews with 15 hospital leaders located in five metropolitan and rural hospitals in southwest Missouri. Consistent with prior research, the use of predictive analytics stratified by patient population was acknowledged as a key strategy to help reduce avoidable rehospitalization. Study findings suggest that leveraging data from the electronic health records to identify at-risk patients provides comprehensive health information to reduce readmissions. Hospital leaders also revealed the need to understand and address the health needs of their local population, including social determinants such as lack of access to transportation as well as food and housing.

In this study, the relationship between data breach characteristics and the number of individuals affected by these violations was considered. Data were acquired from the Department of Health and Human Services breach reporting database and analyzed using SPSS. Regression analyses revealed that the hacking/IT incident breach type and network server breach location were the most significant predictors of the number of individuals affected; however, they were not predictive when combined. Moreover, network server location and unauthorized access/disclosure breach type were predictive when combined. Additional analyses of variance revealed that covered entity type and business associate presence were significant predictors, while the geographic region of a breach occurrence was insignificant. The results of this study revealed several associations between healthcare breach characteristics and the number of individuals affected, suggesting that more individuals are affected in hacking/IT incidents and network server breaches independently and that network server breach location and unauthorized access/disclosure breach type were predictive in combination.