{"id":46745,"date":"2023-01-27T00:00:00","date_gmt":"2023-01-27T08:00:00","guid":{"rendered":"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/blog\/analysis-of-medicare-expenditure-associated-metrics-using-griddb\/"},"modified":"2025-11-13T12:56:27","modified_gmt":"2025-11-13T20:56:27","slug":"analysis-of-medicare-expenditure-associated-metrics-using-griddb","status":"publish","type":"post","link":"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/en\/blog\/analysis-of-medicare-expenditure-associated-metrics-using-griddb\/","title":{"rendered":"Analysis of Medicare Expenditure & Associated Metrics Using GridDB"},"content":{"rendered":"
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A Short Note on Medicare\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
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Initiated in 1965, Medicare <\/b> is one of the most revolutionary plans initiated by the the United States' National Health Insurance Program. Medicare was created to provide equal and adequate access to healthcare for senior citizens of the United States. Though the insurance is primarily offered to citizens aged 65 and older, it is also offered for younger people with disability, including those with chronic end-stage life conditions. Medicare coverage includes four parts - Part A, Part B, Part C and Part D. Read more about each of these coverages here. <\/a> To read more on claim types, refer to this resource <\/a>.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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Objectives of the Analysis\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
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There are several open source datasets related to Medicare available for research. Such datasets have been gathered and analyzed as part of this analysis to get a general idea of the demographics and associated metrics like spending, annual spending per user, and so on. Some of these datasets have data as of 2022 whereas some do not. However, though some data is not up-to-date, it still makes sense to use the information to get insights. Details of each dataset has been explained in the section below. We load these datasets into GridDB in order to use GridDB's fast query engine and then visualize the results using the Altair and Matplotlib libraries in Python.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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About the Datasets\u00b6<\/a><\/h2>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
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A small note on the excel datasets: if they are not being ingested by your pandas, you can re-save them as .xls<\/code> files and they should fix up your issue<\/p>\n

Dataset 1 - <\/b>
\nDataset 1 is obtained from the Social Security Administration.<\/a> This dataset provides details on decisions made by the Social Security Administration (SSA) for the Medicare Prescription Drug Program (Part D). Note that this data excludes individuals who applied through a State Medicaid agency or who automatically qualified because they were already receiving SSI benefits or Medicaid. There are 2 datasets to be downloaded in this case; one for 2016 - 2022, and another for 2010-2015.
\n Filenames: <\/b> fy16-onwards-MPD-Plan-Cost-Yrly.xls and Extra-Help-with-Medicare-Prescription-Drug-Plan-Cost.xls<\/p>\n

Dataset 2 - <\/b>
\nThe second part of the data is sourced from Data.World. This data offers an interesting compilation of medicare hospital expenditure. For more details on the dataset, refer https:\/\/data.world\/health\/medicare-hospital-spending<\/a>.
\n Filenames: <\/b> rows.csv (This was renamed to Medicare_Hospital_Spending)<\/p>\n

Dataset 3 - <\/b>
\nThe third part of the data is sourced from the Centers for Medicare & Medicaid Services. <\/a> This data provides drug spending metrics as part of the Part D Medicare program.
\n Filenames: <\/b> DSD_PTD_R21_P04_V21_D20_BGM.csv (This was renamed to Drug_Spending_Metrics_PartD)<\/p>\n

Dataset 4 - <\/b>
\nThe fourth part of the data is sourced from Data.world <\/a> and provides a detailed compilation of prescription drug spending as part of both the Medicare Part B and Medicare Part D.
Note that there are two methods to download the data file -
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