Different Seasonal Variations of Potassium in Hemodialysis Patients with High Longitudinal Potassium Levels: A Multicenter Cohort Study Using DialysisNet

Purpose@#To determine seasonal variations in serum potassium levels among hemodialysis patients. @*Materials and Methods@#This was a multicenter cohort study of patients whounderwent hemodialysis and were registered in DialysisNet at our four associated general hospitals between January and December 2016. Month-to-month potassium variability was quantified as SD/√{n/(n-1)}, and a non-hierarchical method was used to cluster groups according to potassium trajectories. Seasonal variations in potassium levels were analyzed using a cosinor analysis. @*Results@#The analysis was performed on 279 patients with a mean potassium level of 5.08±0.58 mmol/L. After clustering, 52.3% (n=146) of patients were included in the moderate group (K+ , 4.6±0.4 mmol/L) and 47.7% (n=133) in the high group (K+ , 5.6±0.4 mmol/L). The mean potassium level peaked in January in the moderate group (4.83±0.74 mmol/L) and in August in the high group (5.51±0.70 mmol/L). In the high potassium group, potassium levels were significantly higher in summer than in autumn (p<0.001) and spring (p=0.007). Month-to-month potassium variability was greater in the high group than in the moderate group (0.59±0.19 mmol/L vs. 0.52±0.21 mmol/L, respectively, p=0.012). Compared to patients in the first quartile of potassium variability (≤0.395 mmol/L), those with higher variability (2nd–4th quartiles) were 2.8–4.2 fold more likely to be in the high potassium group. @*Conclusion@#Different seasonal patterns of serum potassium were identified in the moderate and high potassium groups, with potassium levels being significantly higher in the summer season in the high potassium group and in winter for the moderate potassium group.

HealthTWITTER Initiative: Design of a Social Networking Service Based Tailored Application for Diabetes Self-Management / 대한의료정보학회지

OBJECTIVES: Diabetes is a chronic disease of continuously increasing prevalence. It is a disease with risks of serious complications, thus warranting its long-term management. However, current health management and education programs for diabetes mainly consist of one-way communication, and systematic social support backup to solve diabetics' emotional problems is insufficient. METHODS: According to individual behavioral changes based on the Transtheoretical Model, we designed a non-drug intervention, including exercise, and applied it to a mobile based application. For effective data sharing between patients and physicians, we adopted an SNS function for our application in order to offer a social support environment. RESULTS: To induce continual and comprehensive care for diabetes, rigorous self-management is essential during the diabetic's life; this is possible through a collaborative patient-physician healthcare model. We designed and developed an SNS-based diabetes self-management mobile application that supports the use of social groups, which are present in three social GYM types. With simple testing of patients in their 20s and 30s, we were able to validate the usefulness of our application. CONCLUSIONS: Mobile gadget-based chronic disease symptom management and intervention has the merit that health management can be conducted anywhere and anytime in order to cope with increases in the demand for health and medical services that are occurring due to the aging of the population and to cope with the surge of national medical service costs. This patient-driven and SNS-based intervention program is expected to contribute to promoting the health management habits of diabetics, who need to constantly receive health guidance.

Clinical Data Element Ontology for Unified Indexing and Retrieval of Data Elements across Multiple Metadata Registries / 대한의료정보학회지

OBJECTIVES: Classification of data elements (DEs), which is used in clinical documents is challenging, even in across ISO/IEC 11179 compliant clinical metadata registries (MDRs) due to no existence of reliable standard for identifying DEs. We suggest the Clinical Data Element Ontology (CDEO) for unified indexing and retrieval of DEs across MDRs. METHODS: The CDEO was developed through harmonization of existing clinical document models and empirical analysis of MDRs. For specific classification as using data element concept (DEC), The Simple Knowledge Organization System was chosen to represent and organize the DECs. Six basic requirements also were set that the CDEO must meet, including indexing target to be a DEC, organizing DECs using their semantic relationships. For evaluation of the CDEO, three indexers mapped 400 DECs to more than 1 CDEO term in order to determine whether the CDEO produces a consistent index to a given DEC. The level of agreement among the indexers was determined by calculating the intraclass correlation coefficient (ICC). RESULTS: We developed CDEO with 578 concepts. Through two application use-case scenarios, usability of the CDEO is evaluated and it fully met all of the considered requirements. The ICC among the three indexers was estimated to be 0.59 (95% confidence interval, 0.52-0.66). CONCLUSIONS: The CDEO organizes DECs originating from different MDRs into a single unified conceptual structure. It enables highly selective search and retrieval of relevant DEs from multiple MDRs for clinical documentation and clinical research data aggregation.

A SWOT Analysis of the Various Backup Scenarios Used in Electronic Medical Record Systems / 대한의료정보학회지

OBJECTIVES: Electronic medical records (EMRs) are increasingly being used by health care services. Currently, if an EMR shutdown occurs, even for a moment, patient safety and care can be seriously impacted. Our goal was to determine the methodology needed to develop an effective and reliable EMR backup system. METHODS: Our "independent backup system by medical organizations" paradigm implies that individual medical organizations develop their own EMR backup systems within their organizations. A "personal independent backup system" is defined as an individual privately managing his/her own medical records, whereas in a "central backup system by the government" the government controls all the data. A "central backup system by private enterprises" implies that individual companies retain control over their own data. A "cooperative backup system among medical organizations" refers to a networked system established through mutual agreement. The "backup system based on mutual trust between an individual and an organization" means that the medical information backup system at the organizational level is established through mutual trust. RESULTS: Through the use of SWOT analysis it can be shown that cooperative backup among medical organizations is possible to be established through a network composed of various medical agencies and that it can be managed systematically. An owner of medical information only grants data access to the specific person who gave the authorization for backup based on the mutual trust between an individual and an organization. CONCLUSIONS: By employing SWOT analysis, we concluded that a linkage among medical organizations or between an individual and an organization can provide an efficient backup system.