Increased length of inpatient stay and poor clinical coding: audit of patients with diabetes

Author:

Daultrey Harriet1,Gooday Erine2,Dhatariya Ketan2

Affiliation:

1. Norwich Medical School, University of East Anglia, Norwich, Norfolk, UK

2. Diabetic Foot Clinic, Elsie Bertram Diabetes Centre, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich NR4 7UY, UK

Abstract

Objectives People with diabetes stay in hospital for longer than those without diabetes for similar conditions. Clinical coding is poor across all specialties. Inpatients with diabetes often have unrecognized foot problems. We wanted to look at the relationships between these factors. Design A single day audit, looking at the prevalence of diabetes in all adult inpatients. Also looking at their feet to find out how many were high-risk or had existing problems. Setting A 998-bed university teaching hospital. Participants All adult inpatients. Main outcome measures (a) To see if patients with diabetes and foot problems were in hospital for longer than the national average length of stay compared with national data; (b) to see if there were people in hospital with acute foot problems who were not known to the specialist diabetic foot team; and (c) to assess the accuracy of clinical coding. Results We identified 110 people with diabetes. However, discharge coding data for inpatients on that day showed 119 people with diabetes. Length of stay (LOS) was substantially higher for those with diabetes compared to those without (± SD) at 22.39 (22.26) days, vs. 11.68 (6.46) ( P < 0.001). Finally, clinical coding was poor with some people who had been identified as having diabetes on the audit, who were not coded as such on discharge. Conclusion Clinical coding – which is dependent on discharge summaries – poorly reflects diagnoses. Additionally, length of stay is significantly longer than previous estimates. The discrepancy between coding and diagnosis needs addressing by increasing the levels of awareness and education of coders and physicians. We suggest that our data be used by healthcare planners when deciding on future tariffs.

Publisher

SAGE Publications

Subject

General Medicine

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