McCue, M., Virginia, R., & Diana, M. (2007). Assessing the performance of freestanding hospitals. Journal of Healthcare Management, 52(5), 299-308.
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The objective of the research was that of identifying what fundamental promotion, administration, and economic aspects are associated with the self-supporting hospices that generate large income. The sample was nonrandom, comprising 687 freestanding hospices with cash flow data. Within the sample, 268 (0.39) of the hospitals generated positive cash flow and were selected as the positive cash flow sample, while 419 (0.61) had a negative cash flow and were integrated in the comparison sample (McCue et al., 2007, p. 303). While that was a good sample size, the challenge stemmed from the distribution of the sample. The sample size for hospitals with positive cash flow, particularly, was quite small. A bigger number based on all sample groups would have assisted in the data measurement and evaluation (Shi, 2008).
A univariate analysis was utilized in analyzing the data for variations between hospitals with positive and hospitals with negative cash flow (McCue et al., 2007, p. 303). This was inconsistent with the kind of information gathered. The data comprised ordinal information, yet a univariate analysis would be most appropriate for evenly distributed data. While a multivariate regression was a good tool, the issue lies with the significance of the results. A multivariate regression framework based on the two groups would have helped in the analysis of the two market aspects – physicians per capita and marketplace segment (Hawkes & Marsh, 2005).
A multivariate analysis was utilized in analyzing statistical significance at the 0.05 and 0.01 standards (McCue et al., 2007, p. 305). A better investigation technique could have been selected focused on the kind of the data gathered. The outcomes showed that beds per capita were slightly significant at the 0.1 position (McCue et al., 2007, p. 305).
Ozgen, H. & Ozcan, A. (2002). A national study of efficiency for dialysis centers: An examination of market competition and facility characteristics for production of multiple dialysis outputs. Health Services Research, 37(3), 711-728.
The objective of the research was that of examining market rivalry and center features that could be associated with practical competence in the production of multi-dialysis results looked at the view of the manufacturing business model. The study population was random, comprising 840 Health-certified freestanding dialysis centers that presented cost reported to HCFA and generated 3 pre-identified dialysis results jointly. Out of the 840 centers, 797 (95%) of the centers had nonzero operating costs, while 43 (5%) of the centers had zero operating costs. while that was an excellent sample size, the issue originated from the distribution of the sample (Ozgen & Ozcan, 2002, p. 717). The population for centers with zero operating cost, particularly, was quite small (5% of the total centers). A bigger number as far as all groups were concerned would have assisted in the data evaluation, in particular when searching for potential relationships between centers and cost level.
A Data Development Analysis (DEA) method was utilized in measuring the comparative practical effectiveness marks of each center. Basically, that was not in line with the kind of information gathered. The DEA utilized a nonparametric frontier method, yet a DEA would be most suitable for maximum combinations of results and resources depending on the real performance of relative facilities. A descriptive analysis was utilized in the evaluation of effectiveness and the multi-variate analysis (Ozgen & Ozcan, 2002, p. 722). Since the data for the DEA was nonparametric, a descriptive analysis was not the best evaluation instrument. A better evaluation technique like ANOVA could have been selected depending on the information gathered (Shi, 2008).
In conclusion, while the two articles have credit, the techniques should be re-assessed. The strength of the studies should be improved by utilizing bigger sample sizes. Also, the various possible weaknesses regarding the reliability of the results should be dealt with and reduced where possible.
Hawkes, J., & Marsh, H. (2005). Discovering statistics (2nd ed.). Charleston, SC: Hawkes Learning Systems.
Shi, L. (2008). Health services research methods (2nd ed.). Clifton Park, NY: Delmar Cengage Learning.