Summary of Recent Research References

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of Recent Research


McHugh,M. (2013). The Chi-Square Test of Independence. BiochemiaMedica,143-149.

Zhang,X., Wang, L., &amp Zhang, X. (2014). Application of Chi-Square toExplore the Effect of Public Reporting of Medicine Use Information onRational Drug Use in Health Facilities. BMCHealth Services Research,14(1).

Lehmkuhl,L. (2015). Nonparametric Statistics: Methods for Analyzing Data NotMeeting Assumptions Required for the Application of Parametric Tests.JPOJournal of Orthotics and Prosthetics,8(3),105-113.

of the Study

Inthe healthcare system globally, the concern on the clarity of medicalprocedure has been a widely contested debate. According to theInstitute of Medicine, health care transparency is defined asfacilitating the availability of health care to the public in acomprehensible and reliable manner, with the primary objective of thereporting of processes and information (McHugh, 2013). Thirty healthfacilities were divided into the control and intervention groups witha focus on their characteristics. The rankings and values of theaverage expenditure for each medicine, the percentage ofprescriptions requiring injections and antibiotics of each hospitalwere publicly released to patients in an applicable format monthly.Chi-square test was employed to investigate the outcome of publicreporting of medicine use statistics on rational drug use. Thissummary will argue and analyze information gathered through publicparticipation.

Whythe Nonparametric Test

Inthe model, the average expenditure per prescription of the thirtyhospitals was USD 7.12 the percentage of prescription requiringinjections was 72.49%, while that of antibiotics was 64.91%. Theprescription requiring injections was higher than the nationalaverage level and the standard recommended by CDC (Lehmkuhl, 2015).The dependent and independent variable were compared before theintervention (X&gt0.05), however after the interpolation asignificant difference (X&lt0.05) was discovered for the percentageof prescriptions needing injections between the intervention (67.27%)and control groups (71.09%). The propensity score for the dependentvariable was at 0.03 while that of the independent variable was 0.05.Non-parametric tests ought to be used when either one of thefollowing circumstances applies to the data (Zhang, Wang, &ampZhang, 2014):

  • Sample sizes of the research groups are unequal.

  • The level of the dimension of all the variables is ordinal or nominal.

Theaverage cost per prescription of the thirty health facilities beforethe intervention was USD 7.12 and after the intervention was USD8.32. The proportions of treatment requiring antibiotics of thethirty health facilities before and after the interpolation werefound to be 64.91% and 62.17% respectively. The fractions of theinjection before and after were 72.49% and 67.41% respectively. Thedata shows the intervention that drug use in the health facilities isirrational and needs an immediate response.


Irrationaldrug use is still a policy issue in health facilities in the studyarea. After controlling the difference of health centres in designingand using Chi-square to adjust the selection bias of facilitiesmoderately, it was validated that public reporting of prescriptioninformation could cut the percentage of injection prescriptions inhospitals. However, the same could not be ratified for antibioticsand prescription costs (Zhang, Wang, &amp Zhang, 2014). The studyfinding at 0.05 was significant for remedy requiring injections andhad no implications on antibiotics and expenditure per prescription.

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