IT-based Patient Interventions for Opioid Abuse: Evaluation using Analytical Model

The number of people in the US with opioid abuse exceeds 2 million and the total cost is approximately $100B per year. In this study, we focus on patient-level interventions and present three IT-based interventions: (a) mobile reminders, (b) electronic monitoring, and (c) composite intervention. We have developed an analytical model for evaluating interventions using Return-on-Investment (ROI). The interventions are cost-effective for higher values of intervention effectiveness, hospital, and emergency room cost. However, with QoL improvement, cost-effectiveness improves significantly. We also explored the use of financial incentives for increasing the adoption of interventions. These results will help patients, healthcare professionals, decision-makers, and family members to choose the most suitable intervention to address opioid abuse

Study to assess knowledge attitude and practices of antenatal care among antenatal women attending outdoor clinic in tertiary care hospital

Background: Maternal mortality rate in India continues to be a national challenge despite of the various measures taken by the Indian government, Non profit organizations in and outside the country including the World Health Organization. To find out the gaps between the providers and beneficiaries we tried to find out what actually prevents our pregnant women to seek Regular Antenatal Care by evaluating their knowledge, attitudes and practices towards antenatal care.Methods: All antenatal women attending outpatient clinic of department of obstetrics and gynae Gandhi medical college Bhopal over a period of one year were included in the study. Study group was of unbooked antenatal women and control group consisted of booked women at the hospital. All subjects were given a predesigned, pretested questionnaire to fill in their local language and the data thus obtained was analysed statistically.Results: 86.16% subjects visited ANC clinic during first trimester, 66.33% knew correctly about frequency of antenatal visits, 97.50% knew about Tetanus immunization. Likewise, 78.33% had positive attitude towards antenatal checkups and early registration. Similarly, 70.4% took adequate antenatal care, 93.33% took iron folic acid tablets.Conclusions: Thus, the study shows that the knowledge, attitude and practice of antenatal care is good in the booked subject the same is not the case in unbooked subjects coming to the hospital with complications or being referred to the hospital

Synthetic routes to new core/shell nanogels:design and application in biomaterials

A very interesting class of nanoparticles extensively used for bio-applications is that of hydrogel particles, also called nanogels. There is an increasing interest in the design of hydrogel nanoparticles that have biofunctionality for applications in cell targeting, drug delivery, and biomedicine. The dissertation focuses on developing synthetic strategies for making diverse hydrogel nanoparticles customized to have desirable properties for various bio-applications. We have also investigated the potential of such nanoparticles as coatings for biomedical implants. Chapter 1 gives a brief introduction to hydrogel nanoparticles and the properties that make them attractive for various applications. The details of the syntheses of well defined, stable nanoparticles, commonly used in literature, are described in Chapter 2. Chapter 3 describes our synthesis of hollow sub-50 nm nanogels, which are otherwise difficult to synthesize based on the strategy discussed in Chapter 2. Chapter 4 also demonstrates how simple strategies borrowed from organic chemistry help in producing nanogels with multiple functionalities that are otherwise difficult to obtain, which also is an important advance over the synthetic methods discussed in Chapter 2. Chapter 5 describes how a general strategy based on photoaffinity labeling can yield materials with many applications ranging from optical materials, drug delivery, to biosensing. The latter part of the dissertation describes applications of various nanogels in biology especially as coatings that can control inflammation caused by biomaterials. Chapter 6 describes a method to functionalize flexible biomaterials with the nanogels, thus enabling in vivo investigations of the nanogels as potential coatings for controlling inflammation. Chapter 7 describes the biological studies performed (in collaboration with Garcia Group in the School of Mechanical Engineering at Georgia Tech) on various nanogels, aimed towards obtaining the most functional and efficient materials for implant applications. Chapter 8 describes application of hollow nanogels for covalently immobilizing biomolecules. This chapter also demonstrates how simple non-functional materials can be made unique and functional by means of traditional organic reactions. Finally, in order to broaden the applications of nanogel based materials.Ph.D.Committee Chair: Prof. L. Andrew Lyon; Committee Member: Prof. Laren Tolbert; Committee Member: Prof. Marcus Weck; Committee Member: Prof. Niren Murthy; Committee Member: Prof. Seth Marde

Smart Interventions for Effective Medication Adherence

In this research we present a model for medication adherence from information systems and technologies (IS/IT) perspective. Information technology applications for healthcare have the potential to improve cost-effectiveness, quality and accessibility of healthcare. To date, measurement of patient medication adherence and use of interventions to improve adherence are rare in routine clinical practice. IS/IT perspective helps in leveraging the technology advancements to develop a health IT system for effectively measuring medication adherence and administering interventions. Majority of medication adherence studies have focused on average medication adherence. Average medication adherence is the ratio of the number of doses consumed and the number of doses prescribed. It does not matter in which order or pattern patients consume the dose. Patients with enormously diverse dosing behavior can achieve the same average levels of medication adher­ence. The same outcomes with different levels of ad­herence raise the possibility that patterns of adherence affect the effectiveness of medication adherence. We propose that medication adherence research should utilize effective medication adherence (EMA), derived by including both the pattern and average medication adherence for a patient. Using design science research (DSR) approach we have developed a model as an artifact for smart interventions. We have leveraged behavior change techniques (BCTs) based on the behavior change theories to design smart intervention. Because of the need for real time requirements for the system, we are also focusing on hierarchical control system theory and reference model architecture (RMA). The benefit of using this design is to enable an intervention to be administered dynamically on a need basis. A key distinction from existing systems is that the developed model leverages probabilistic measure instead of static schedule. We have evaluated and validated the model using formal proofs and by domain experts. The research adds to the IS knowledge base by providing the theory based smart interventions leveraging BCTs and RMA for improving the medication adherence. It introduces EMA as a measurement of medication adherence to healthcare systems. Smart interventions based on EMA will further lead to reducing the healthcare cost by improving prescription outcomes

Smart Interventions for Effective Medication Adherence

In this research we present a model for medication adherence from information systems and technologies (IS/IT) perspective. Information technology applications for healthcare have the potential to improve cost-effectiveness, quality and accessibility of healthcare. To date, measurement of patient medication adherence and use of interventions to improve adherence are rare in routine clinical practice. IS/IT perspective helps in leveraging the technology advancements to develop a health IT system for effectively measuring medication adherence and administering interventions. Majority of medication adherence studies have focused on average medication adherence. Average medication adherence is the ratio of the number of doses consumed and the number of doses prescribed. It does not matter in which order or pattern patients consume the dose. Patients with enormously diverse dosing behavior can achieve the same average levels of medication adher­ence. The same outcomes with different levels of ad­herence raise the possibility that patterns of adherence affect the effectiveness of medication adherence. We propose that medication adherence research should utilize effective medication adherence (EMA), derived by including both the pattern and average medication adherence for a patient. Using design science research (DSR) approach we have developed a model as an artifact for smart interventions. We have leveraged behavior change techniques (BCTs) based on the behavior change theories to design smart intervention. Because of the need for real time requirements for the system, we are also focusing on hierarchical control system theory and reference model architecture (RMA). The benefit of using this design is to enable an intervention to be administered dynamically on a need basis. A key distinction from existing systems is that the developed model leverages probabilistic measure instead of static schedule. We have evaluated and validated the model using formal proofs and by domain experts. The research adds to the IS knowledge base by providing the theory based smart interventions leveraging BCTs and RMA for improving the medication adherence. It introduces EMA as a measurement of medication adherence to healthcare systems. Smart interventions based on EMA will further lead to reducing the healthcare cost by improving prescription outcomes

Automated conflation framework for integrating transportation big datasets

The constant merging of the data, commonly known as Conflation, from various sources, has been a vital part for any phase of development, be it planning, governing the existing system or to study the effects of any intervention in the system. Conflation allows enriching the existing data by integrating information through numerous sources available out there. This process becomes unusually critical because of the complexities these diverse data bring along such as, distinct accuracies with which data has been collected, projections, diverse nomenclature adaption, etc., and hence demands special attention. Although conflation has always been a topic of interest among researchers, this area has witnessed a significant enthusiasm recently due to current advancements in the data collection methods. Even though with this escalation in interest, the developed methods didn't justify the expansions field of data collections has made. Contemporary conflation algorithms still lack an efficient automated technique; most of the existing system demands some sort of human involvement for the analysis to achieve higher accuracy. Through this work, an effort has been made to establish a fully automated process to conflate the road segments of Missouri state from two big data sources. Taking the traditional conflation a step further, this study has also focused on enriching the road segments with traffic information like delay, volume, route safety, etc., by conflating with available traffic data and crash data. The accuracy of the conflation rate achieved through this algorithm was 80-95 percent for the different data sources. The final conflated layer gives detailed information about road networks coupled with traffic parameters like delay, travel time, route safety, travel time reliability, etc.by Neetu ChoubeyIncludes bibliographical reference

Image Processing Techniques: A Review

In today’s scenario image processing is one of the vast growing fields. It is a method which is commonly used to improve raw images which are received from various resources. It is a kind of signal processing. This paper provides an overview of image processing methods. The main concern of this paper is to define various techniques used in different phases of image processing.   Most Searchable Keywords on Web image processing techniques, image processing methods, image processing techniques pdf, image processing papers, types of image processing techniques, image processing technique, digital image processing techniques pdf, digital image processing techniques, latest image processing techniques, research papers on image processing, analog image processin

Size of cervical lesion in locally advanced carcinoma cervix and response to neoadjuvant chemotherapy

Background: Recently neoadjuvant chemotherapy has started being considered for advanced stage of carcinoma cervix. Drug delivery to pelvic tumour is optimal with neoadjuvant chemotherapy since tumour vascular supply has not been damaged by any previous pelvic interference. Tumor size and parametrial involvement have been reported to be important predictor of NACT response. Objective of this study was to find out association between size of cervical lesion in locally advanced carcinoma cervix and response to neoadjuvant chemotherapy.Methods: The present prospective cohort study was carried out in the Department of Obstetrics and Gynaecology with the collaboration of Department of Radiotherapy, Chhatrapati Shahuji Maharaj Medical University Lucknow for a period of 1-year august 2010 to august 2011. 26 patients with histologically proven locally advanced carcinoma cervix were studied. In all cases Cisplatin 75 mg/m2 and paclitaxel 135 mg/m2 on day one was given at 14 days interval up to maximum of three courses. Evaluation of operability status was done two weeks after second course of chemotherapy. Those found operable were taken up for radical hysterectomy and rest were given 3rd course of chemotherapy. After two weeks of 3rd course again operability assessment was done and patient was taken up either for surgery or radiotherapy.Results: It was observed that out of 14 patients who had tumour size 4 cm, 4 (33.3%) responded completely (CR) and rest 8 (66.6%) response was partial (PR).Conclusions: Response to chemotherapy was modified by pre-treatment volume of the tumour