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

This is a case study of the implementation of a data and analytics-enabled Mission Control at one of the largest healthcare service providers in the state of Washington. Using data analytics and artificial intelligence, CHI-Franciscan (one of the largest healthcare organizations in state of Washington) is able to coordinate patient care more effectively and efficiently, improving safety for all its patients. This case study demonstrates tangible evidence from quantitative and qualitative analysis for return on investment for such a large project.

Introduction: Diabetes mellitus is known as a major chronic disease that has a number of consequences affecting individuals' health conditions and socioeconomic aspects of life. These challenges require innovative interventions, such as self-management to improve patients' health condition and reduce the economic burden of healthcare systems. The current research aimed to identify patients' and physicians' perspectives about the use of health information technology in diabetes management in Iran.

Methods: This was a qualitative study conducted in 2019. In order to collect data, semi-structured interviews were conducted with eight patients and 10 specialists in an endocrine and metabolism research center and in a teaching hospital. The interviews were digitally recorded and transcribed verbatim. Finally, data were analyzed by using framework analysis method and MAXQDA version 10.

Results: According to the results, both patients and physicians believed that while using health information technology can improve access to healthcare services, the high cost of technology may hinder its usage. Factors such as government and health system support can motivate users to use the technology, and factors such as lack of user training and technical problems may have a negative impact on technology usage.

Conclusion: As a number of motivational and inhibitory factors may influence the use of health information technology in diabetes management, it is imperative to take each of these factors into account before designing and implementing new technologies, especially for diabetes management.

We conducted a national survey of Health Information Exchanges (HIEs), targeting both not-for profit geographic and enterprise or federated exchanges. The aim of this study is to identify current best practices when exchanging information between Veterans Affairs (VA) systems and non-VA health systems. We identified and classified current interactions between HIEs and VA systems given recent passage of the MISSION Act. The MISSION Act allows veterans to seek care outside the VA health system, necessitating the need to reconcile care planning between VA systems and private care settings. We identified several differing best practices concerning information exchange between VA health systems and HIEs and assessed capabilities for HIEs to appropriately identify eligible VA participants within extant databases.

This article discusses the emerging trends and challenges related to automatic clinical coding. We introduce an automatic coding system, which assigns short ICD-10 codes (restricted to the first three symbols, which define the category of the disease) based only on drugs prescribed to patients. We show that even with limited input data, the accuracy levels are comparable to those achieved by entry-level clinical coders as depicted by Seyed Nouraei et al.¹ We also examine the standard method for performance estimation and speculate that the actual accuracy of our coding system is even higher than estimated.

An information technology governance (ITG) program has helped the National Institutes of Health (NIH) Clinical Center (CC) in the implementation of many systems and has guided the organization through the maturity of its project management methodology. The NIHCC Department of Clinical Research Informatics (DCRI) maintains an electronic health record (EHR) called the clinical research information system (CRIS) along with many clinical information systems (CIS) and research information systems, supporting approximately 3,200 users. ITG involves establishing processes to guide the review, selection, implementation, management, and setting of the IT strategy representing the business owners, stakeholders, and IT.¹ Research conducted by Levstek, Hovelja, and Pucihar² identified that different organizations may need different ITG structures, frameworks, and strategies. The path to achieving strong ITG is a continuous journey. This paper reviews the evolution of the NIHCC IT governance strategy.

Objective: Thirty-day readmission rates are closely monitored in today's healthcare ecosystem to prevent higher-than-average rates in inpatient settings. Excess readmission rates result in decreased reimbursement for healthcare facilities. Additionally, feedback from patients about their hospital experience may indicate areas of improvement for healthcare facilities. This feedback is a national survey that collects data on patient experience through a standardized survey called Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS). The objective of this study is to identify significant patterns between readmission rates and HCAHPS survey data through the application of association rules.

Materials and methods: Publically accessible HCAHPS survey data and 30-day readmission rates provided by the Centers for Medicare and Medicaid Services (CMS) were utilized for this study. Through the implementation of association rules using SAS Enterprise Miner, significant rules were identified in the data.

Results: Association rules were developed in SAS Enterprise Miner and produced three significant rules associated with high heart failure (HF) readmission as the right-hand rule. The rules indicated that a high pneumonia readmission, a low cleanliness star rating, and a low medication communication star rating were associated with a high readmission rate for heart failure.

Conclusions: The rules provided strong associations between HCAHPS star ratings and determining a high readmission rate for HF. It was interesting to find that pneumonia readmissions exist as well with a high HF readmission. Hospitals should work on improving their star ratings for the HCAHPS domains identified and work on lowering pneumonia readmissions to lower their HF readmissions.

In the World Health Congress in May 2019, ICD-11 was approved, This study aims to analyze the classification system of the 11th revision of the International Classification of Disease mapping with the ICD-10-KM-7th (ICD-10 Korean Modification 7th) to identify the characteristics of ICD-11 so that it can be flexibly linked to KCD-7 when introduced in Korea. The mapping was conducted based on the ICD-11 frozen version (April 2019). Most of the ICD-11 codes were mapped to a single ICD-10 or KCD-7 code. However, for the diabetes code, more than 80 percent of KCD-7 codes needed to be mapped to one or two post-coordination codes, along with one stem code in ICD-11. ICD-11 is a great classification that has an excellent taxonomy system to express detailed information. For the codes that have been changed or removed, a proper guideline might also be useful for users to understand the changes made in KCD-7 or ICD-10 code.

Insomnia and sleep apnea are associated with a variety of comorbid conditions and carry a symptom burden to patients. As the prevalence of insomnia and sleep apnea continue to rise, it is imperative that appropriate tools are implemented to accurately capture their prevalence in acute care settings. A retrospective chart review was conducted on 3,074 inpatient charts in Calgary, Alberta. The estimated prevalence of insomnia was 10.36 percent, and sleep apnea was 6.56 percent in inpatient visits between January 1, 2015, and June 30, 2015. The sensitivity of insomnia and sleep apnea were low, and the specificity was high when comparing the chart review to the ICD-10. As both insomnia and sleep apnea were associated with various comorbid conditions, it would be imperative that alternate methods are identified to capture and code them. This would enable clinicians to better identify and treat them, and ultimately improve patient care.