+ Site Statistics
+ Search Articles
+ PDF Full Text Service
How our service works
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ Translate
+ Recently Requested

A Tale of Two Eras: Mining Big Data from Electronic Health Records to Determine Limb Salvage Rates with Podiatry



A Tale of Two Eras: Mining Big Data from Electronic Health Records to Determine Limb Salvage Rates with Podiatry



Current Diabetes Reviews 15(6): 497-502



Diabetic foot complications remain very prevalent in the US and worldwide, and a major risk for devastating amputations. We evaluated the impact of establishing a fully integrated and specialized Podiatry service into a large tertiary academic health system to implement structured and targeted preventative foot care on limb salvage rates. Cross-sectional cohorts' data mining analysis was conducted of all encounters for diabetes and any foot complications between 2000-2005 and 2010-2015, preceding and after full implementation of podiatry service, respectively. The primary outcome was the change in major non-traumatic lower extremity amputations. Secondary outcomes included minor non-traumatic lower extremity amputations, other diabetic foot complications, limb salvage procedures as documented by procedural coding, and location (outpatient, inpatient, ED) of service rendered. We analyzed 100 million patient encounters that met the above criteria. Compared with the initial cohort, integration of specialized podiatry services resulted in a significant decrease in the number of major amputations from 127 to 85/year (p<0.05), and halved the amputations rate from 0.004% to 0.002% (p<0.05). Rates of minor lower extremity amputations remained unchanged (p>0.10), while the rates of preventative procedures including foot ulcer debridement doubled (0.0002% to 0.0004% ; p<0.03). Diagnoses of diabetic foot complications increased significantly (p<0.05) and shifted toward the outpatient setting. Full integration of specialized Podiatry service led to a significant decrease in major amputation rates, supporting teamwork between podiatry and diabetes health-care providers is essential to performing timely diabetic foot complications management, preventative procedures leading to limb salvage, and a shift in the care location.

Please choose payment method:






(PDF emailed within 1 workday: $29.90)

Accession: 065706348

Download citation: RISBibTeXText

PMID: 30332970


Related references

Mining Electronic Health Records using Linked Data. AMIA Joint Summits on Translational Science Proceedings. AMIA Joint Summits on Translational Science 2015: 217-221, 2015

Mining Electronic Health Records Data: Domestic Violence and Adverse Health Effects. Journal of Family Violence 32(1): 79-87, 2017

Analysis of length of hospital stay using electronic health records: A statistical and data mining approach. Plos one 13(4): E0195901, 2018

Novel use and utility of integrated electronic health records to assess rates of prediabetes recognition and treatment: brief report from an integrated electronic health records pilot study. Diabetes Care 37(2): 565-568, 2014

Application of process mining to assess the data quality of routinely collected time-based performance data sourced from electronic health records by validating process conformance. Health Informatics Journal 22(4): 1017-1029, 2016

Using linked data for mining drug-drug interactions in electronic health records. Studies in Health Technology and Informatics 192: 682-686, 2013

Calcium channel blockers as drug repurposing candidates for gestational diabetes: Mining large scale genomic and electronic health records data to repurpose medications. Pharmacological Research 130: 44-51, 2018

Cost-benefit assessment of using electronic health records data for clinical research versus current practices: Contribution of the Electronic Health Records for Clinical Research (EHR4CR) European Project. Contemporary Clinical Trials 46: 85-91, 2016

Multicentre clinical trials' data management: a hybrid solution to exploit the strengths of electronic data capture and electronic health records systems. Informatics for Health and Social Care 38(4): 313-329, 2013

Harnessing electronic healthcare data for wound care research: Standards for reporting observational registry data obtained directly from electronic health records. Wound Repair and Regeneration 25(2): 192-209, 2017

Electronic health records in academic family medicine practices: a tale of progress and opportunity. Annals of Family Medicine 6(1): 87-88, 2008

Study of electronic prescribing rates and barriers identified among providers using electronic health records in New York City. Informatics in Primary Care 19(2): 91-97, 2011

Bias associated with mining electronic health records. Journal of Biomedical Discovery and Collaboration 6: 48-52, 2011

Exchanging personal health data with electronic health records: A standardized information model for patient generated health data and observations of daily living. International Journal of Medical Informatics 120: 116-125, 2018

Chapter 13: Mining electronic health records in the genomics era. Plos Computational Biology 8(12): E1002823, 2012