Risk assessment of the hospital discharge process of high-risk patients with diabetes.

OBJECTIVES: Describe the application of a risk assessment to identify failures in the hospital discharge process of a high-risk patient group, liver transplant (LT) recipients with diabetes mellitus (DM) and/or hyperglycaemia who require high-risk medications. DESIGN: A Failure Modes, Effects and Criticality Analysis (FMECA) of the hospital discharge process of LT recipients with DM and/or hyperglycaemia who required DM education and training before discharge was conducted using information from clinicians, patients and data extraction from the electronic health records (EHR). Failures and their causes were identified and the frequency and characteristics (harm, detectability) of each failure were assigned using a score of low/best (1) to high/worst (10); a Criticality Index (CI=Harm×Frequency) and a Risk Priority Number (RPN=Harm×Frequency×Detection) were also calculated. SETTING: An academic, tertiary care centre in Chicago, Illinois. PARTICIPANTS: Healthcare providers (N=31) including physicians (n= 6), advanced practice providers (n=12), nurses (n=6), pharmacists (n= 4), staff (n=3) and patients (n=6) and caregivers (n=3) participated in the FMECA; EHR data for LT recipients with DM or hyperglycaemia (N=100) were collected. RESULTS: Of 78 identified failures, the most critical failures (n=15; RPNs=700, 630, 560; CI=70) were related to variability in delivery of diabetes education and training, care coordination and medication prescribing patterns of providers. Underlying causes included timing of patient education, lack of assessment of patients' knowledge and industry-level design failures of healthcare products (eg, EHR, insulin pen). CONCLUSION: Most identified critical failures are preventable and suggest the need for the design of interventions, informed by the failures identified by this FMECA, to mitigate safety risks and improve outcomes of high-risk patient populations.

Validation of data from electronic data warehouse in diabetic ketoacidosis: Caution is needed.

AIMS: This study validated enterprise data warehouse (EDW) data for a cohort of hospitalized patients with a primary diagnosis of diabetic ketoacidosis (DKA). METHODS: 247 patients with 319 admissions for DKA (ICD-9 code 250.12, 250.13, or 250.xx with biochemical criteria for DKA) were admitted to Northwestern Memorial Hospital from 1/1/2010 to 9/1/2013. Validation was performed by electronic medical record (EMR) review of 10% of admissions (N = 32). Classification of diabetes type (Type 1 vs. Type 2) and DKA clinical status were compared between the EMR review and EDW data. RESULTS: Key findings included incorrect classification of diabetes type in 5 of 32 (16%) admissions and indeterminable classification in 5 admissions. DKA was not present, based on the review, in 11 of 32 (34%) admissions. DKA was not present, based on biochemical criteria, in 15 of 32 (47%) admissions. CONCLUSIONS: This study found that EDW data have substantial errors. Some discrepancies can be addressed by refining the EDW query code, while others, related to diabetes classification and DKA diagnosis, cannot be corrected without improving clinical coding accuracy, consistency of medical record documentation, or EMR design. These results support the need for comprehensive validation of data for complex clinical populations obtained through data repositories such as the EDW.

Diabetes Care After Transplant: Definitions, Risk Factors, and Clinical Management.

Patients who undergo solid organ transplantation may have preexisting diabetes mellitus (DM), develop new-onset DM after transplantation (NODAT), or have postoperative hyperglycemia that resolves shortly after surgery. Although insulin is usually used to control hyperglycemia in the hospital, following discharge most of the usual diabetes oral and parenteral medications can be used in treatment. However, when there are comorbidities such as impaired kidney or hepatic function, or heart disease, special precautions may be necessary. In addition, drug-drug interactions, such as drugs interacting with CYP3A4 enzyme pathway, require additional consideration because of possible interaction with immunosuppressive drug metabolism.