DESIGNING A STUDY AND SUMMARY OF RECENT RESEARCH 6
DESIGNINGA STUDY AND SUMMARY OF RECENT RESEARCH
Designinga study: Quantitative nursing study
Inmy Nursing study project the research question would be examiningwhether Quality of life (QOL) scores would predict re-admission tohospital for chronic obstructive pulmonary diseases or patient deathswithin 12 months of original admission or whether quality of life(QOL) scores could predict Home care provision.
ResearchHypothesis Qualityof life and Hospital re-admission in patients with chronicobstructive pulmonary disease
Independentand Dependent Variables in the study
Inthis aspect, Qualityof life(QOL) is the independent variable tested. Statistically, qualityof lifescores is the ‘predictor variable’, ‘explanatory’, riskfactor’ or the ‘regressor’ which predicts if patients who werepreviously admitted with clinical chronic illness of obstructivepulmonary disease can be readmitted. Therefore, rate of readmissionin hospitals for COPD (Chronic Obstruction pulmonary diseases) is thedependent variable or the ‘regressed’, ‘measured variable’ orthe ‘responding variable’. The study would therefore seek toestablish to what extent patient re-admission to hospital depends onquality of life (patient coping and distress).
Totest this hypothesis and answer the study questions, the study wouldadopt regression and spearman correlation to analyze the data.Ideally, data would be collected in a 12 month span from carepatients admitted with critical COPD, a sample of these patients(with primary discharge diagnosis) would be identified and after oneyear and data would be collected for the re admission cases andreported deaths. Statistical scores of symptom, frequency, impact andactivity would be analyzed using the SPSS-PC while symptom frequency,impact and activity scores (SGRQ) would be distributed in thet-tests Spearman correlation coefficient would be calculated whilelogistic regression would be used to ascertain ratios of readmission, care provision, adjusting for age, lung function and sex(Bracken, 2013).
Theunderlying goal would be to estimate the relationship between qualityof life lived by patients and rate of hospital readmission due tochronic obstructive pulmonary diseases. As such, help inunderstanding the dynamics of readmissions with respect to qualityimprovement of patients’ life through palliative (home based care).The underlying assumptions would be that the sample is representativeof the whole population in making inference prediction and that theindependent variable is measured with no error (Bracken,2013).
of Recent Research
W-SKelvin Teo, Anusha Govinda Raj, Woan Shin Tan, Charis, Wei Ling Ng,Bee Hoon Heng, and Ian Yi-Onn Leong, (2014). ‘Economicimpact analysis of an end-of-life programme for Nursing homeresidents’,Vol.28(5) 430–437, Singapore Sage Publication.
Theobjective of this study was to measure the economic impact ofpalliative care project on the health care system of Singapore. Thestudy was done in hope that the results of the study could assistpolicymakers and healthcare providers on how to allocate health careresources. Specifically the study focused on evaluating the economicimpact of Project care at the end of life for the elderly careprogram on nursing home residents. The study used quasi experimentaldesign and inverse probability weighted (IPW) linear regression modelwas to predict end of life cost differences in the healthcare system.Project care was introduced in seven nursing homes to providepalliative care and planning for residents identified to be at risksof dying within one year. Nursing home residents enrolled in the CAREproject and the historic group of home residents not in any end oflife care program were chosen as matched controls and costdifferences between the two groups analyzed over three months oflife.
Thestudy results found that, in the 48 project care cases and 197controls, cases were found to be older, having more co morbiditiesand higher nursing needs. Results indicated that there were moresubstantial savings associated with end of life programme, with asizable population in Singapore. The study also revealed that savingswere due to the effects of ACP and palliative care support in nursinghomes. Cost differences between the two groups were due to lowerhospital admissions and shorter in patient (LOS)(Pedhazur, 1991).
Inthis study, aim was to investigate the economic impact of end of lifecare program for nursing home residents. As such, theeconomic impactis the dependent variable while ProjectCARE for end of life personswas the dependent variable. Using quasi experimental design and amatched historical control group the study was done in seven nursinghomes. In this case the dependence variable (economic impact, reducedcosts of healthcare and hospitalization) and the independent variablewere measured at 95% confidence interval and at t-test value of p<(chi-square). Comparison of direct medical costs incurred by the careproject and the controls were done using two sample t-test,Mann-Whitney U-tests and chi-squire for categorical variables(W-S Kelvin, et al. 2014).
Economicimpact was analyzed using inverse probability weighted (IPW) linearregression model to predict end of life cost differences to thehealth care system. Unadjusted comparison on utilization and costswere made with the two sample t-test levels of significance set at0.25 for baseline characteristics and 0.05 for utilization and costs(W-SKelvin, et al. 2014).Results of the IPW model on costs saving for Project care revealedthat the CARE project significantly reduced health care coast at endof life. The findings evidence was reflective that opportunity forcost saving rose with ACP (Advanced care planning), and palliativecare in nursing homes (Brumley, 2003).
Ingeneral, the IPW linear regression model used in testing the effectof Project care on and economic cost achieved the definite results ofthe study at 95% confidence level and significant level of p<0.05.Therefore,this model met the study assumption that palliative care program hassignificant economic impact on health care cost reduction for nursinghome patients. The statistical significance values obtained atp<0.05,tested the hypothesis on whether the null hypothesis could beaccepted or rejected. Values less than p<0.05,indicate that the study results were significant we accept the nullhypothesis that palliative care programs have significant effect inhealth care cost reduction for nursing patients (Serra-Prat, 2001).
Bracken,Michael B. (2013). ‘Risk,Chance, and Causation: Investigating the Origins and Treatment ofDisease’(1sted.). New Haven, CT: Yale University Press. pp. 260–276.ISBN 0-300-18884-6.
BrumleyRD, Enguidanos S and Cherin DA. 2003, ‘Effectivenessof a home-based palliative care program for end-of-life’.JPalliatMed6: 715–724
Serra-PratM, Gallo P and Picaza JM. 2001, ‘Homepalliative care as a cost-saving alternative: evidence fromCatalonia’.PalliatMed15: 271–278
Pedhazur,Elazar J. Schmelkin, Liora P. (1991). Measurement,Design, and Analysis: An Integrated Approach(Student ed.). New York, NY: Psychology Press. pp. 180–210.ISBN 0-805-81063-3
W-SKelvin Teo, Anusha Govinda Raj, Woan Shin Tan, Charis, Wei Ling Ng,Bee Hoon Heng, and Ian Yi-Onn Leong, (2014). ‘Economicimpact analysis of an end-of-life programme for Nursing homeresidents’,Vol. 28(5) 430–437, Singapore Sage Publication.