Databases for statistical information on healthcare

Databases for statistical information on healthcare

Databases for statistical information on healthcare include the Medicare Provider Analysis and Review (MEDPAR) and the Healthcare Cost and Utilization Project (HCUP). These databases serve as the national patient information resource as they offer information on utilization rates and measurements of performance (Leonard, Brensinger,  Nam, Bilker, Barosso Mangaali  & Hennessy, 2017). An example is a statistic that claims that 87.3% of adults in the U.S used health services in 2108.

Just under 90% of adults in the U.S used medical services in 2018, with 76.6% having at least one medical visit to a health provider, and 10.7% spent at least night at the hospital. This statistic was calculated by dividing the number of adults who utilized hospital services by the entire population of adults in the country. Medical service utilization captured the nights spent in the hospital as well as the rate of rehospitalizations in the inpatients.

Research questions are handy tools essential for the research process because they offer a focus on where the research starts. Research questions define what the researcher is trying to find out by influencing most of the rest of the steps to be taken when carrying out the research. For instance, a research question aimed at finding the incidence of a disease in a population leads to the conducting of a survey to find the risk factors of that disease. Data obtained from the research questions are then made available for more extensive applications in health life leading to the formulation of policies that benefit the broader population

Hypothesis testing refers to a statistical method that uses experimental data when making logical decisions about a parameter in a population. Therefore, hypothesis testing is about determining whether an assumption about something is acceptable or not. When carrying out research, hypothesis testing is used through a series of four steps. These are; stating the hypothesis, developing an analysis plan, examining the data, and interpreting the results.

The hypothesis is that an inpatient advocacy program will reduce the rate of rehospitalization.80% of the patients under the inpatient advocacy program recorded a lower vrate compared to the 20% who were not in the program. A significant test on the data results in a P-value = .04, implying the difference is statistically significant (P < .05). However, theoretical knowledge offers ground for believing that an inpatient advocacy program improves hospital performance; thus, the truth of the null hypothesis is 99.99%, while that of the alternative hypothesis is 0.01%. Hence, the null hypothesis is accepted.

Reference

Leonard, C. E., Brensinger, C. M., Nam, Y. H., Bilker, W. B., Barosso, G. M., Mangaali, M. J., & Hennessy, S. (2017). The quality of Medicaid and Medicare data obtained from CMS and its contractors: implications for pharmacoepidemiology. BMC Health Services Research, 17(1). doi: 10.1186/s12913-017-2247-7