Medical Services Quality & Healthcare Providers

One of the most challenging issues encountered in the healthcare sector is the ability to obtain accurate information about the quality of healthcare services dispensed healthcare providers (McClellan & Staiger, 1999, p.1; Grandison & Bhatti, 2010, p.1). Moreover, the quality of care is affected by the number of care personnel in a given area (Dunn & Doeksen, 1977, p.95). In this paper, I will discuss the quality of healthcare services by analyzing three research articles.

In the article title, The Quality of Health Care Provider, Mark McClellan and Douglas Staiger (1999), conducted their study on heart disease among elderly American. According to them, the inability to obtain accurate information about the quality of healthcare services is attributed to three factors. First, it is hard to gather appropriate data on time, especially on patients with long-term illness. Second, the quality of medical care is multidimensional. It entails effects, procedures of healthcare, among others, which must be incorporated in a quality evaluation. Third, there is a systematic variation among healthcare providers that result in partiality with respect to the quality of care dispensed. McClellan & Staiger used the vector auto-regression (VAR) model to approximate the logical relationship across results and overtime and then employed this data to predict future results (1999, p.2). Their study employed longitudinal Medicare claims data to make out about 200,000 elderly recipients every year with new episodes of AMI. They also used hospital records together with death reports. Their sample was drawn from 3953 hospitals in the US between 1984 and 1994 (McClellan & Staiger, 1999, p.17). The results from their study suggested a negative correlation between the quality of care and outcomes. This is due to the fact that patients who receive high quality care are prone to experience heart failure (McClellan & Staiger, 1999, p.20).

The article Health Service Utilization and Insurance Coverage: A Multivariate Probit Analysis (1998) presents a detailed report on the study done by Robert D. Gibbons and Virginia Wilcox-Gok on the relationship between insurance coverage and the use of health service. The sample used in this study involved 4,657 persons aged above 65 years on Medicare program. The study used five health services as response variable: hospital outpatient visit; medical provider visit; hospital in-patient stay; hospital outpatient visits; home healthcare visits; and emergence room visit. Insurance coverage was classified as Medicaid, privately procured insurance and employer-related private insurance. Covariates comprised of health status, race, education, gender, age, marital status, among others. The multivariate probit model was used to approximate the relationship between insurance coverage variables and the five health service variable while holding constant the effects of the correlations and covariate amongst the health service utilization variables (Gibbons & Wilcox-gok, 1998, p.63). The result of their study revealed that individuals on Medicare program but lacking supplementary coverage were highly unlikely to use any of the five categories of medical services. Moreover, persons covered by both Medicaid and Medicare were 6% less likely to visit a medical provider compared to individuals under other insurance cover (Gibbons & Wilcox-gok, 1998, p.70).

The article Applying the Statistical Survey Method in Evaluating the Public Health Care System in Romania (2008) was written by Tudorel Andrei et al. The article is based on the study done by the author to analyze a number of attributes of the public reform process within the Romanian public healthcare system. A sample of 406 doctors was selected from clinics, healthcare centers and hospitals in the Bucharest municipality (Andrei et al, 2008, p.307). The researchers used a cumulative variable based on five main attributes in order to gauge the general opinion of the participants about the quality of the reform process within the public health care system. These attributes included: the reform process at medical centers; hiring and promotion of staff; procurement of drugs; the decentralization policy; and financial support accorded to the health care institution (Andrei et al, 2008, p.308). There are different situations that arise from the study. First, there is a negative correlation between the impact of the five factors and the provision of the medical equipment and other supplies. Second, there is a strong correlation between health care service and boosting education and salary remuneration of the medical staff (Andrei et al, 2008, p.311).

From the above discourse, it emerges that the study done by Robert D. Gibbons and Virginia Wilcox-Gok yields the most valid results because both the dependent and independent variables are clearly defined. In addition, the study uses a bigger sample (4,657) compared to the other two studies and therefore the outcome is much accurate. On the other hand, the study done by Tudorel Andrei et al is the weakest because the sample used in the study is very small (only 406) and thus cannot be used as a fair representative of the population.

References

Andrei, T., & Tusa, E. (2008). Applying the Statistical Survey Method in Evaluating the Public Health Care System in Romania. Journal of Applied Quantitative Methods, 3, 304-315.

Dunn, JW., & Doeksen, GA. (1977). Canonical Correlation Analysis of Selected Demographic and Health Personnel Variable. Southern Journal of Agricultural economics, 95-99.

Gibbons, RD., & Wilcox-Gok, V. (1998). Health Service Utilization and Insurance Coverage: A Multivariate Probit Analysis. Journal of the American Statistical Association, 93, 63-72.

Grandison, T., & Bhatti, R. (2010). Regulatory Compliance and the Correlation to Privacy Protection in Healthcare. California: IBM Almaden Research Center.

McClellan, M., & Staiger, D. (1999). The Quality of Health Care Providers. Cambridge, MA: National Bureau of Economic Research.

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