International Journal of Respiratory Care

Blood Pressure Intervention and Family Implications

Dr. Laral Lamporez — 2021-06-07

For blood pressure patients, it is important to engage in timely and appropriate management of the condition to ensure that death and complications resulting from the condition are minimized. This investigation was conducted in the form of a cross-sectional prospective study. Particularly, 100 participants were selected for data collection, upon which analysis and interpretations were conducted to gain insight into the subject that was being investigation. The data collection process involved administering semi-structured questionnaires, with the participants’ case notes also reviewed to gain additional data, as well as validate their responses as obtained from the questionnaires. From the findings, the study established that when clinical pharmacists’ services are incorporated into the efforts of the rest of the healthcare teams, there is a significant improvement in the quality of blood pressure management. The improvement is reflected by beneficial attributes such as reduced morbidity, a decrease in the rate of hospitalization, and fewer causes of adverse events; including medication arises that could, otherwise, accrue due to poor coordination at the unit level.

Challenges of Healthcare Services and Implications for Country Legislation

Dr. Nike Zoneroz — 2021-06-07

In this investigation, most of the findings concur with the current literature in such a way that Brexit promises to pose mixed outcomes regarding NHS service provision. Whereas some of the sources consulted hold that the UK’s withdrawal from the EU promises positive outcomes, others contend that the move comes with negative effects. For the proponents of there being a positive effect between Brexit and NHS operations, the consensus is that the £19 billion that the UK has been channeling annually to the EU might be saved and used to fund public service and other government priorities, including the pharmacy sector. On the other hand, findings that point to a negative effect of Brexit on the pharmacy sector indicate that the withdrawal prompts an increase in the departure of pharmacists. In the majority of cases, this departure is attributed to the uncertainties surrounding the EU-origin staff’s future immigration statuses. Furthermore, findings suggest that most of the past scholarly studies contending that Brexit poses a negative effect on the NHS argue that the cost of training pharmacists and doctors to fill vacancies of the EU-based staff leaving the UK might outweigh that which the UK has been incurring to import skilled or already-trained workers, with other countries having incurred the training expenses. Hence, the relationship between Brexit and NHS reflects a complex issue but the dominant theme or pattern is that the withdrawal might pose a hit to the economy of the UK. In turn, this hit might worsen the country’s health outcomes − with the pharmacy service on focus.

Impact of Patient Condition Monitoring on Family Lived Experiences

Dr. Virat Nizom — 2021-08-26

In this study, the main research question was, during drug-related problems, what are some of the questions that patients might ask? The main aim of this study was to examine and describe the behaviors, activities, contextual factors, and attitudes associated with medication monitoring, with specific insights gained from community pharmacists. This case study employed a mixed methods technique in which qualitative and quantitative data was collected, analyzed, and interpreted. Whereas the initial number of participants in the qualitative phase entailed 12 individuals, saturation was reached after the ninth interview because the remaining three participants did not give any new insights, themes, or concepts.

Medical Framework Effectiveness during Hypertension Patient Intervention

Dr. Raizo K — 2021-08-26

In this study, it was documented that effective blood pressure control depends on various factors and lifestyle behaviors, having gained insights from most of the previous scholarly studies. Thus, the main aim of the investigation was to determine some of the lifestyle modifications and factors linked to the control of blood pressure among patients using antihypertensive agents. The research design that was implemented involved the use of a survey technique. With the period of data collection stretching from July 2008 to June 2010 and that research context being Korea’s 15 selected hospital-based family practices, prospective sampling and retrospective assessments were utilized. The number of patients assessed was 1,453. Whereas individual questions aided in gaining insight into the participants’ lifestyles, a follow-up questionnaire that was administered in the later stages of the investigation strived to discern issues surrounding the control of the patients’ blood pressure.

Technological Implementation towards Healthcare Condition Prediction

Dr. Nami OP — 2021-08-26

The aim of technological innovations has been to aid in useful data extraction for purposes of informed decision-making. Given that the big data section has seen predictive analytics emerge as a promising platform, with machine learning models incorporated, there has been a growing possibility of predicting the future behavior of parameters. In healthcare, this possibility has been felt in terms of disease prediction, as well as cure anticipation and development. The central purpose of this study was to apply a machine learning model on medical data sets in a big data environment. Specifically, the C4.5 algorithm was used towards chronic kidney disease prediction in a healthcare setting marked by big data presence.

Disease Prediction Efficacy on Community Healthcare and Population Lived Experiences

Dr. Namizo Kariya — 2021-08-26

Currently, trends in infectious disease occurrences, incidence, and prevalence are unknown in the majority of cases, complicating efforts geared towards disease prediction. In this study, the motivation was to contribute to infectious disease prediction through deep learning algorithms’ parameters’ optimization, with big data in the healthcare industry on consideration. Specifically, there was a comparison between the performances of the long-short term memory (LSTM) learning algorithm and deep neural network model with the performance of ARIMA (autoregressive integrated moving average) algorithm. Three infectious diseases were examined to discern model reliability and validity in under different experimental conditions. From the findings, this study established that the performance of LSTM and DNN frameworks is superior to that of ARIMA. Relative to chickenpox prediction, there was improvement by 19% and 25% after implementing LSTM and top-10 DNN models, respectively.