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Accepted for/Published in: JMIR Diabetes

Date Submitted: Jan 30, 2021
Date Accepted: Jan 23, 2022

The final, peer-reviewed published version of this preprint can be found here:

Constructing an Adapted Cascade of Diabetes Care Using Inpatient Admissions Data: Cross-sectional Study

Ryan I, Herrick C, Ebeling MF, Foraker R

Constructing an Adapted Cascade of Diabetes Care Using Inpatient Admissions Data: Cross-sectional Study

JMIR Diabetes 2022;7(1):e27486

DOI: 10.2196/27486

PMID: 35333182

PMCID: 8994153

Constructing an Adapted Cascade of Diabetes Care Using Inpatient Admissions Data

  • Irene Ryan; 
  • Cynthia Herrick; 
  • Mary F.E. Ebeling; 
  • Randi Foraker

ABSTRACT

Background:

The diabetes mellitus cascade of care has been constructed to evaluate diabetes care at a population level, determining the percentage of individuals diagnosed, linked to care, and glycemic control.

Objective:

We sought to adapt the cascade to an inpatient setting using electronic health record (EHR) data of 81,633 patients with Type II diabetes. This construction seeks to use only inpatient records.

Methods:

In this adaptation, linkage to care was defined as prescription of diabetes medications within three months of discharge and control was defined as HbA1c below individual target levels, as these are most reliably captured in the inpatient setting. We applied the cascade model to assess differences in demographics and percent loss at each stage of the cascade, and conducted 2-sample Chi-square equality of proportions tests for each demographic. From findings in the previous literature, we hypothesized that women, Black patients, younger patients, uninsured patients, and patients living in economically deprived areas called Promise Zones would be disproportionately unlinked and uncontrolled. We also predicted that patients who received inpatient glycemic care would be more likely to reach glycemic control.

Results:

We found that women and younger patients were slightly less likely (<1%) to be linked to care than their male and older counterparts, while Black patients were as likely to be linked (23.4% vs 23.5%) as whites. Those living in underserved communities (Promise Zones) and uninsured patients were slightly overrepresented (>1%) in the linked population as compared to patients living in wealthier zip codes and those who were insured. Similar patterns were observed among those more likely to reach glycemic control via HbA1c. However, conclusions are limited by the relatively large amount of missing glycemic data.

Conclusions:

We conclude that inpatient EHR data do not adequately capture the care cascade as defined in the outpatient setting. In particular, missing data in this setting may preclude assessment of glycemic control. Future work should integrate inpatient and outpatient data sources to complete the picture of diabetes care.


 Citation

Please cite as:

Ryan I, Herrick C, Ebeling MF, Foraker R

Constructing an Adapted Cascade of Diabetes Care Using Inpatient Admissions Data: Cross-sectional Study

JMIR Diabetes 2022;7(1):e27486

DOI: 10.2196/27486

PMID: 35333182

PMCID: 8994153

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