Statistical disclosure limitation of health data based on Pk-anonymity.

The Act for the Protection of Personal Information in Japan considers as personal information any quasi-identifier that may be used to obtain information that identifies individuals through comparisons with datasets. Studies using health records are not widely conducted because of the concern regarding the safety of anonymized health records. To increase the safety of such records, we used the Pk-anonymity method. In this method, attributes are probabilistically randomized and then reconstructions are performed on the basis of statistical information from perturbed data. Hence, it is expected to provide more precise statistics and more reliably preserve privacy than the traditional "k-anonymity" method. We anonymized health records, performed cross tabulation, and assessed the error rate using original data. This study shows that the Pk-anonymity method can be used to perform safety statistical disclosures with low error rates, even in small cases.

Evaluation of the Anonymity and Utility of De-Identified Clinical Data Based on Japanese Anonymization Criteria.

We analyze the deterioration of clinical data quality due to anonymization. The result shows that data quality remained high with micro-aggregation and also verify the availability of noise addition to prevent illegal re-identification by matching another personal data.

Fatal fungal endocarditis by Aspergillus udagawae: an emerging cause of invasive aspergillosis.

Aspergillus udagawae has morphological similarities to Aspergillusfumigatus; however, it shows a low susceptibility to common antifungal drugs and poor in vitro sporulation. We present the first reported case of infectious endocarditis caused by A. udagawae. An awareness of this newly described Aspergillus species is vital for further clarification.

Evaluation of Secure Computation in a Distributed Healthcare Setting.

Issues related to ensuring patient privacy and data ownership in clinical repositories prevent the growth of translational research. Previous studies have used an aggregator agent to obscure clinical repositories from the data user, and to ensure the privacy of output using statistical disclosure control. However, there remain several issues that must be considered. One such issue is that a data breach may occur when multiple nodes conspire. Another is that the agent may eavesdrop on or leak a user's queries and their results. We have implemented a secure computing method so that the data used by each party can be kept confidential even if all of the other parties conspire to crack the data. We deployed our implementation at three geographically distributed nodes connected to a high-speed layer two network. The performance of our method, with respect to processing times, suggests suitability for practical use.

Implementation and evaluation of an efficient secure computation system using 'R' for healthcare statistics.

BACKGROUND AND OBJECTIVE: While the secondary use of medical data has gained attention, its adoption has been constrained due to protection of patient privacy. Making medical data secure by de-identification can be problematic, especially when the data concerns rare diseases. We require rigorous security management measures. MATERIALS AND METHODS: Using secure computation, an approach from cryptography, our system can compute various statistics over encrypted medical records without decrypting them. An issue of secure computation is that the amount of processing time required is immense. We implemented a system that securely computes healthcare statistics from the statistical computing software 'R' by effectively combining secret-sharing-based secure computation with original computation. RESULTS: Testing confirmed that our system could correctly complete computation of average and unbiased variance of approximately 50,000 records of dummy insurance claim data in a little over a second. Computation including conditional expressions and/or comparison of values, for example, t test and median, could also be correctly completed in several tens of seconds to a few minutes. DISCUSSION: If medical records are simply encrypted, the risk of leaks exists because decryption is usually required during statistical analysis. Our system possesses high-level security because medical records remain in encrypted state even during statistical analysis. Also, our system can securely compute some basic statistics with conditional expressions using 'R' that works interactively while secure computation protocols generally require a significant amount of processing time. CONCLUSIONS: We propose a secure statistical analysis system using 'R' for medical data that effectively integrates secret-sharing-based secure computation and original computation.

Age-related mitochondrial DNA deletion in human heart: its relationship with cardiovascular diseases.

BACKGROUND AND AIMS: Accumulation of damage to mitochondrial DNA (mtDNA) occurs in myocardial tissue with advancing age. However, despite higher incidence of cardiac diseases in the elderly, little attempt has been made to detect deletions of mtDNA in the myocardial tissue of aged individuals. The aim of the present study was to clarify the relationship between aging, mtDNA deletion and cardiovascular (CV) diseases. METHODS: We examined 163 autopsy cases, aged 60 years or older, using two different kinds of polymerase chain reaction (PCR): highly sensitive PCR to detect a common 4977-bp deletion and long-PCR for multiple deletions, which could be detected in case that deleted mtDNA accounted for more than several percents in total mtDNA. RESULTS: The common 4977-bp deletion was detected in 156 cases (95.7%), showing no significant difference among these age groups and no relation to CV diseases. By long-PCR, multiple deletions in cardiac mtDNA were found in 33 (20.2%) of 163 cases. The proportion of the mtDNA deletion in the nineties (46.2%) was significantly higher than those in the younger (15.3%, p < 0.05). Female predominance was significantly found in the group with the mtDNA deletion (p < 0.05). Multiple deletions of mtDNA were not significantly related to ischemic change, valvular diseases, left ventricular hypertrophy, congestive heart failure, coronary sclerosis, or heart weight except for right ventricular hypertrophy. CONCLUSIONS: These findings suggest that there is a close relationship between aging and deletion of mtDNA, and that the ratio of deleted mtDNA to total mtDNA increases with advancing age. Age-related deletion of mtDNA may have little influence on CV diseases except for right ventricular hypertrophy.