scholarly journals Automated Cluster Detection of Health Care–Associated Infection Based on the Multisource Surveillance of Process Data in the Area Network: Retrospective Study of Algorithm Development and Validation (Preprint)

2019 ◽  
Author(s):  
Yunzhou Fan ◽  
Yanyan Wu ◽  
Xiongjing Cao ◽  
Junning Zou ◽  
Ming Zhu ◽  
...  
Keyword(s):  
Health Care ◽  
Cluster Detection ◽  
Utilization Rate ◽  
Area Network ◽  
Process Data ◽  
Single Indicator ◽  
Antibiotic Utilization ◽  
Positive Rate ◽  
Warning Model ◽  
Parallel Strategy

BACKGROUND The cluster detection of health care–associated infections (HAIs) is crucial for identifying HAI outbreaks in the early stages. OBJECTIVE We aimed to verify whether multisource surveillance based on the process data in an area network can be effective in detecting HAI clusters. METHODS We retrospectively analyzed the incidence of HAIs and 3 indicators of process data relative to infection, namely, antibiotic utilization rate in combination, inspection rate of bacterial specimens, and positive rate of bacterial specimens, from 4 independent high-risk units in a tertiary hospital in China. We utilized the Shewhart warning model to detect the peaks of the time-series data. Subsequently, we designed 5 surveillance strategies based on the process data for the HAI cluster detection: (1) antibiotic utilization rate in combination only, (2) inspection rate of bacterial specimens only, (3) positive rate of bacterial specimens only, (4) antibiotic utilization rate in combination + inspection rate of bacterial specimens + positive rate of bacterial specimens in parallel, and (5) antibiotic utilization rate in combination + inspection rate of bacterial specimens + positive rate of bacterial specimens in series. We used the receiver operating characteristic (ROC) curve and Youden index to evaluate the warning performance of these surveillance strategies for the detection of HAI clusters. RESULTS The ROC curves of the 5 surveillance strategies were located above the standard line, and the area under the curve of the ROC was larger in the parallel strategy than in the series strategy and the single-indicator strategies. The optimal Youden indexes were 0.48 (95% CI 0.29-0.67) at a threshold of 1.5 in the antibiotic utilization rate in combination–only strategy, 0.49 (95% CI 0.45-0.53) at a threshold of 0.5 in the inspection rate of bacterial specimens–only strategy, 0.50 (95% CI 0.28-0.71) at a threshold of 1.1 in the positive rate of bacterial specimens–only strategy, 0.63 (95% CI 0.49-0.77) at a threshold of 2.6 in the parallel strategy, and 0.32 (95% CI 0.00-0.65) at a threshold of 0.0 in the series strategy. The warning performance of the parallel strategy was greater than that of the single-indicator strategies when the threshold exceeded 1.5. CONCLUSIONS The multisource surveillance of process data in the area network is an effective method for the early detection of HAI clusters. The combination of multisource data and the threshold of the warning model are 2 important factors that influence the performance of the model.

scholarly journals Automated Cluster Detection of Health Care–Associated Infection Based on the Multisource Surveillance of Process Data in the Area Network: Retrospective Study of Algorithm Development and Validation

10.2196/16901 ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. e16901
Author(s):  
Yunzhou Fan ◽  
Yanyan Wu ◽  
Xiongjing Cao ◽  
Junning Zou ◽  
Ming Zhu ◽  
...  
Keyword(s):  
Health Care ◽  
Cluster Detection ◽  
Utilization Rate ◽  
Area Network ◽  
Process Data ◽  
Single Indicator ◽  
Antibiotic Utilization ◽  
Positive Rate ◽  
Warning Model ◽  
Parallel Strategy

Background The cluster detection of health care–associated infections (HAIs) is crucial for identifying HAI outbreaks in the early stages. Objective We aimed to verify whether multisource surveillance based on the process data in an area network can be effective in detecting HAI clusters. Methods We retrospectively analyzed the incidence of HAIs and 3 indicators of process data relative to infection, namely, antibiotic utilization rate in combination, inspection rate of bacterial specimens, and positive rate of bacterial specimens, from 4 independent high-risk units in a tertiary hospital in China. We utilized the Shewhart warning model to detect the peaks of the time-series data. Subsequently, we designed 5 surveillance strategies based on the process data for the HAI cluster detection: (1) antibiotic utilization rate in combination only, (2) inspection rate of bacterial specimens only, (3) positive rate of bacterial specimens only, (4) antibiotic utilization rate in combination + inspection rate of bacterial specimens + positive rate of bacterial specimens in parallel, and (5) antibiotic utilization rate in combination + inspection rate of bacterial specimens + positive rate of bacterial specimens in series. We used the receiver operating characteristic (ROC) curve and Youden index to evaluate the warning performance of these surveillance strategies for the detection of HAI clusters. Results The ROC curves of the 5 surveillance strategies were located above the standard line, and the area under the curve of the ROC was larger in the parallel strategy than in the series strategy and the single-indicator strategies. The optimal Youden indexes were 0.48 (95% CI 0.29-0.67) at a threshold of 1.5 in the antibiotic utilization rate in combination–only strategy, 0.49 (95% CI 0.45-0.53) at a threshold of 0.5 in the inspection rate of bacterial specimens–only strategy, 0.50 (95% CI 0.28-0.71) at a threshold of 1.1 in the positive rate of bacterial specimens–only strategy, 0.63 (95% CI 0.49-0.77) at a threshold of 2.6 in the parallel strategy, and 0.32 (95% CI 0.00-0.65) at a threshold of 0.0 in the series strategy. The warning performance of the parallel strategy was greater than that of the single-indicator strategies when the threshold exceeded 1.5. Conclusions The multisource surveillance of process data in the area network is an effective method for the early detection of HAI clusters. The combination of multisource data and the threshold of the warning model are 2 important factors that influence the performance of the model.

scholarly journals Effectiveness of Public and Co-operative Health Insurance Models in Nepal: A Concurrent Mixed Study

2016 ◽  
Author(s):  
Chhabi Ranabhat ◽  
Chun-Bae Kim ◽  
Myung-Bae Park
Keyword(s):  
Health Care ◽  
Health Insurance ◽  
Health Care Utilization ◽  
Health Care Service ◽  
Large Population ◽  
High Income ◽  
Care Utilization ◽  
Utilization Rate ◽  
Religious Minority ◽  
Mixed Study

Background: Health insurance (HI) run by government is providing health care service to large population. Due to poor accountability, participation and sustainability, cooperative health insurance is becoming more popular and effective in low and middle income and some high-income countries too. In Nepal, there are public and cooperative HI is in practice. The aim of this study is to compare the effectiveness of public (government) and cooperative HI in relation to benefit packages, population coverage, inclusiveness, health care utilization, and promptness for treatment in these two health insurance models in Nepal. Method: This is an institution based concurrent mixed study consists of qualitative and quantitative variables from public and cooperative groups. We included all public HI operated by government hospitals and cooperatives groups those purchased hospital service in contract. Two separate study tools were applied to access the effectiveness of insurance models. The key questions were asked for the representatives of government and private health insurance. The numeric information consisted of in quantitative data and subjective response was included in qualitative approach. Descriptive statistics and Mean Whitney U test was applied in numeric data and qualitative information were analyzed by inductive approach Results: The study revealed that new enrolment was not increased, health care utilization rate was increased and the benefit package was almost same in both groups. The overall inclusiveness was higher for the government HI, but enrolment from the religious minority, proportion of negotiated amount during treatment were significantly higher (p<0.05). During illness, the response time to reach hospital was significantly faster in cooperative health insurance than government health insurance. Qualitative findings showed that level of participation, accountability, transparency and recording system was better in cooperative health insurance than public. Conclusion: Cooperative HI could be more sustainable and accountable to the community for all; low, middle and high-income countries.

Lifetime Enhancement and Reliability in Wireless Body Area Network

2021 ◽  
pp. 88-101
Author(s):  
Saranya Vasanthamani ◽  
S. Shankar
Keyword(s):  
Health Care ◽  
Health Care Professionals ◽  
Health Care Service ◽  
Wireless Body Area Network ◽  
Body Area Network ◽  
Area Network ◽  
Body Area ◽  
Related Information ◽  
Critical Issues ◽  
Health Related

The wireless body area network (WBAN) consists of wearable or implantable sensor nodes, which is a technology that enables pervasive observing and delivery of health-related information and services. The network capability of body devices and integration with wireless infrastructure can result in pervasive environment deliver the information about the patients to health care service providers. WBAN has a major part in e-health observing system. Due to sensitivity and critical of the data carried and handled by WBAN, reliability becomes a critical issues. WBAN loads a high degree of reliability as it openly affects the quality of patient observing. A main requirement is that the health care professionals receive the monitored data correctly. Thus reliability can be measured to achieve reliable network are fault tolerance, QoS, and security. As WBAN is a special type of WSN. The objective is to achieve a reliable network with minimum delay and maximum throughput while considering power consumption by reducing unnecessary communication.

scholarly journals Pharmacist Clinical Interventions and Discharge Counseling in Medical Rehabilitation Wards in a Local Hospital: A Prospective Trial

Geriatrics ◽  
2018 ◽  
Vol 3 (3) ◽  
pp. 53 ◽  
Author(s):  
Rosanna Nga Suet Ip ◽  
Justin Wade Tenney ◽  
Angus Chun Kwok Chu ◽  
Pauline Lai Ming Chu ◽  
Grace Wai Man Young
Keyword(s):  
Health Care ◽  
Medication Adherence ◽  
Health Care Utilization ◽  
Usual Care Group ◽  
Medication Reconciliation ◽  
Intervention Group ◽  
Medical Rehabilitation ◽  
Care Group ◽  
Care Utilization ◽  
Utilization Rate

Patients undergoing rehabilitation experience numerous changes in medication regimens during care transitions, exposing these patients to an increased risk of drug-related problems (DRPs). A prospective, non-randomized, quasi-experimental study was conducted in medical rehabilitation wards to evaluate the impact of pharmacist-delivered interventions and counseling on 30-day unplanned health care utilization and medication adherence for selected rehabilitation patients. A pharmacist provided medication reconciliation and counseling before discharge. Phone follow-up was completed 30 days after discharge to assess for unplanned health care utilization rate and medication adherence. A total of 85 patients (n = 43 in prospective intervention group and n = 42 in historical usual care group) were included. Among the intervention group, 23 DRPs were identified in 14 (32.6%) patients, resulting in 51 interventions. The intervention group had a significantly lower unplanned health care utilization rate than the usual care group (25.6% vs. 47.6%, p = 0.035). The risk of unplanned health care utilization was reduced by over 60% (Odds ratio (OR) = 0.378; 95% CI = 0.15–0.94). Patients reporting medium to high medication adherence increased from 23.6% to 88.4% 30 days after counseling (p < 0.05). Pharmacist medication reconciliation and discharge counseling reduced unplanned health care utilization 30 days after discharge and improved medication adherence.

A High False-Positive Rate of Tuberculosis Associated with Aplisol: An Investigation among Health Care Workers

1994 ◽  
Vol 169 (3) ◽  
pp. 703-704 ◽  
Author(s):  
B. P. Lanphear ◽  
C. C. Linnemann ◽  
C. G. Cannon
Keyword(s):  
Health Care ◽  
Health Care Workers ◽  
False Positive ◽  
False Positive Rate ◽  
High False Positive Rate ◽  
Care Workers ◽  
Positive Rate

Attack-Tree Based Risk Assessment on Cloud-Oriented Wireless Body Area Network

2019 ◽  
Vol 11 (4) ◽  
pp. 63-79
Author(s):  
Theodoros Mavroeidakos ◽  
Nikolaos Peter Tsolis ◽  
Dimitrios D. Vergados ◽  
Stavros Kotsopoulos
Keyword(s):  
Risk Assessment ◽  
Health Care ◽  
Health Care Services ◽  
Wireless Body Area Network ◽  
Area Network ◽  
Body Area ◽  
Attack Tree ◽  
Care Services ◽  
Personally Identifiable Information

Machine-to-machine (M2M) communication is an emerging technology with unrivaled benefits in the fields of e Health and m-Health. The wireless body area networks (WBANs) consist of a major subdomain of M2M communications. The WBANs coupled with the Cloud Computing (CC) paradigm introduce a supreme infrastructure in terms of performance and Quality of Services (QoS) for the development of eHealth applications. In this article, a risk assessment aiming to disclose potential threats and highlight exploitation of health care services, is introduced. The proposed assessment is based upon the implementation of a series of steps. Initially, the health care WBAN-CC infrastructure is scrutinized; then, its threats' taxonomy is identified. Then, a risk assessment is carried out based on an attack-tree consisting of the most hazardous threats against Personally Identifiable Information (PII) disclosure. Thus, the implementation of several countermeasures is realized as a means to mitigate gaps.

The Development of a Local Area Network Communication Software Based on Peer-to-Peer Mode

2014 ◽  
Vol 905 ◽  
pp. 627-630
Author(s):  
Jing Ying Zhao ◽  
Hai Guo
Keyword(s):  
Local Area Network ◽  
Text Message ◽  
Local Area ◽  
Peer To Peer ◽  
Java Virtual Machine ◽  
Utilization Rate ◽  
Area Network ◽  
File Transfer ◽  
Communication Software ◽  
Socket Technology

Compared with traditional client/server modes, peer-to-peer (P2P) mode has obvious advantages in eliminating the performance bottleneck of server and enhancing the utilization rate of network resources. Based on P2P technology, local area network (LAN) communication software was well designed in this paper. By using the support function of Java for multithreading technology and socket technology, P2P mode was adopted to realize various communication functions, such as LAN text message transmission, file transfer and voice transmission. Though processing multicast messages, the software can detect the login and logout status of LAN users. Proved by testing, this software can operate stably in a system environment installed with Java Virtual Machine (JVM).

scholarly journals A Real-time Anomaly-based Intrusion Detection System for Automotive Controller Area Networks

2020 ◽  
Author(s):  
Luís Felipe Prado D'Andrada ◽  
Paulo Freitas de Araujo-Filho ◽  
Divanilson Rodrigo Campelo
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
True Positive Rate ◽  
Detection Algorithm ◽  
Cyber Attacks ◽  
Area Network ◽  
Controller Area Networks ◽  
Positive Rate ◽  
Promising Solution

The Controller Area Network (CAN) is the most pervasive in-vehiclenetwork technology in cars. However, since CAN was designed with no securityconcerns, solutions to mitigate cyber attacks on CAN networks have been pro-posed. Prior works have shown that detecting anomalies in the CAN networktraffic is a promising solution for increasing vehicle security. One of the mainchallenges in preventing a malicious CAN frame transmission is to be able todetect the anomaly before the end of the frame. This paper presents a real-timeanomaly-based Intrusion Detection System (IDS) capable of meeting this dead-line by using the Isolation Forest detection algorithm implemented in a hardwaredescription language. A true positive rate higher than 99% is achieved in testscenarios. The system requires less than 1μs to evaluate a frame’s payload, thusbeing able to detect the anomaly before the end of the frame.

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