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Comparative effectiveness for oral anti-diabetic treatments among newly diagnosed type 2 diabetics: data-driven predictive analytics in healthcare

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Health Systems

Abstract

A difficult problem in healthcare is predicting who will become very sick in the near future. In our case, we find that the top 10% of newly diagnosed type 2 diabetes patients account for 68% of healthcare utilization. In this paper, we demonstrate how the U.S. healthcare system can provide improved healthcare quality per unit of spend through better predictive data-based analytics applied to the increasingly available troves of healthcare claims data. Specifically, we demonstrate the effectiveness of data mining by applying machine learning methods to large-scale medical and pharmacy claims data for over 65,000 patients newly diagnosed with type 2 diabetes, a common and costly disease globally. This analysis reveals some important heretofore unknown patterns in the cost and quality among of the disease's common treatments and demonstrates the potential for using large-scale data mining for efficiently focusing further inquiry.

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Correspondence to Jon Maguire.

Appendices

Appendix A

Medical claim coding for uncomplicated type 2 diabetes

ICD9-CM diagnosis codes

250.00:

Diabetes mellitus without mention of complication, Type II, Controlled

250.02:

Diabetes mellitus without mention of complication, Type II, Uncontrolled

Appendix B

Medical claim coding for type 1 diabetes

ICD9-CM diagnosis codes

250.x1:

Diabetes mellitus with or without mention of complication, Type I, Controlled

250.x3:

Diabetes mellitus with or without mention of complication, Type I, Uncontrolled

Appendix C

Medical claim coding for diabetes complications

ICD9-CM diagnosis codes

250.1x:

Diabetes with ketoacidosis

250.2x:

Diabetes with hyperosmolarity

250.3x:

Diabetes with other coma

250.4x:

Diabetes with renal manifestations

585.xx:

Chronic kidney disease

58381:

Nephritis and nephropathy, not specified as acute or chronic, in diseases classified elsewhere

58181:

Nephrotic syndrome in diseases classified elsewhere

250.5x:

Diabetes with ophthalmic manifestations

369.xx:

Blindness and low vision

362.xx:

Other retinal disorders

36641:

Diabetic cataract

36544:

Glaucoma associated with systemic syndromes

250.6x:

Diabetes with neurological manifestations

337.1x:

Peripheral autonomic neuropathy in disorders classified elsewhere

353.5x:

Thoracic root lesions, not elsewhere classified

354.xx:

Mononeuritis of upper limb and mononeuritis multiplex

355.xx:

Mononeuritis of lower limb

357.2x:

Polyneuropathy in diabetes

536.3x:

Gastroparesis

713.5x:

Arthropathy associated with neurological disorders

250.7x:

Diabetes with peripheral circulatory disorders

44381:

Peripheral angiopathy in diseases classified elsewhere

785.4x:

Gangrene

250.8x:

Diabetes with other specified manifestations

707.1x:

Ulcer of lower limbs, except pressure ulcer

707.2x:

Pressure ulcer stages

707.8x:

Chronic ulcer of other specified sites

707.9x:

Chronic ulcer of unspecified site

731.8x:

Other bone involvement in diseases classified elsewhere

250.9x:

Diabetes with unspecified complication

ICD9-CM procedure codes

84.0x:

Amputation of upper limb

84.1x:

Amputation of lower limb

CPT4 procedure codes

26910:

Amputate metacarpal bone

26951:

Amputation of finger/thumb

26952:

Amputation of finger/thumb

27590:

Amputate leg at thigh

27591:

Amputate leg at thigh

27592:

Amputate leg at thigh

27594:

Amputation follow-up surgery

27596:

Amputation follow-up surgery

27598:

Amputate lower leg at knee

27880:

Amputation of lower leg

27881:

Amputation of lower leg

27882:

Amputation of lower leg

27884:

Amputation follow-up surgery

27886:

Amputation follow-up surgery

27888:

Amputation of foot at ankle

27889:

Amputation of foot at ankle

28800:

Amputation of midfoot

28805:

Amputation through metatarsal

28810:

Amputation toe and metatarsal

28820:

Amputation of toe

28825:

Partial amputation of toe

Appendix D

Table D1

Table D1 Insulin medications

Appendix E

Table E1

Table E1 Oral antidiabetic medications

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Maguire, J., Dhar, V. Comparative effectiveness for oral anti-diabetic treatments among newly diagnosed type 2 diabetics: data-driven predictive analytics in healthcare. Health Syst 2, 73–92 (2013). https://doi.org/10.1057/hs.2012.20

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