Compliance with surgical care improvement project blood glucose--a marker for euglycemia, but does it put our patients at risk?

To improve outcomes in open heart surgery (OHS) patients, the Surgical Care Improvement Project (SCIP) requires 6 am postoperative day (POD) 1 and 2 blood glucose (BG) to be ≤200mg/dL. This study examined risk factors for SCIP noncompliance when using an insulin infusion protocol (IIP) and evaluated this SCIP metric as a surrogate for glycemic control. The authors divided 99 consecutive OHS patients, all subjected to 1 uniform IIP, into 2 groups: Group 1-SCIP compliant (n=79) and Group 2-SCIP noncompliant (n=20). They determined mean BG for the first 48 postoperative hours, percent of total time with hyperglycemia (% time BG >200mg/dL) for each group, and assessed risk of SCIP noncompliance as relates to multiple risk factors including intensity of IIP application, and switching to subcutaneous (SQ) insulin prior to 6 am on POD 2. Group 1 had lower mean BG than Group 2 and percent of total time with hyperglycemia, P<0.0001. Multivariate analysis showed diabetes, obesity in nondiabetics, and switching to SQ insulin prior to 6 am on POD 2 to be risk factors for SCIP noncompliance. The 6 am BG values on POD 1 or POD 2 each correlated with average postoperative BG, and compliance with the SCIP BG metric was associated with virtually uniform BG ≤200mg/dL. IIP application was not significantly different between groups (P=0.2). Only patients who had been switched to SQ insulin prior to 6 am POD 2 were noncompliant at 6 am on POD 2. There were hypoglycemic events (BG <70mg/dL) in 15 of 99 patients (15%), 12 of whom (80%) were in Group 1. Noncompliance with this SCIP measure occurred more frequently in patients with diabetes or, if nondiabetic, in those patients with obesity. A trend toward increased insulin assessments in the SCIP noncompliant group suggests that 1 uniform IIP for all patients may not be effective. By not requiring the reporting of hypoglycemia, SCIP may inadvertently be exposing patients to harm.

Intense implementation of a strict insulin infusion protocol does not guarantee postoperative glycemic control.

BACKGROUND: The Surgical Care Improvement Project (SCIP) has benchmarked 6:00 AM blood sugars on postoperative days (PODs) 1 and 2 at <200 mg/dL as an indicator of overall glycemic control (GC) in postoperative cardiac surgery patients. However, even in demonstration hospitals that publicly report for incentive payments, only 10% are compliant with this benchmark. The objectives of this study were to validate that the SCIP indicator correlates with overall GC, and relate the intensity of implementation of an insulin infusion protocol (IIP) (goal, blood sugar 100 to 140 mg/dL) to effective GC. STUDY DESIGN: All postoperative cardiac surgery patients for 12 consecutive months on the IIP were divided into 2 groups: group 1 included patients who were SCIP compliant (n = 98), and group 2 were patients who were not SCIP compliant (n = 10). For each patient, we determined average blood sugar, duration of hyperglycemia (percent of time with blood sugar >200mg/dL), and intensity of implementation of the IIP, defined as (number of blood sugar checks/hours on IIP), with 0.5 = minimum intensity of implementation dictated by the IIP, ie, an insulin adjustment every 2 hours. RESULTS: The average blood sugar for each of the 110 patients was no different than the SCIP 6:00 AM blood sugar: 146 versus 154 mg/dL, p = 0.18. SCIP noncompliance correlated with more intense implementation of the IIP, 0.72 ± 0.03 versus 0.83 ± 0.06 blood sugar checks/hour. CONCLUSIONS: The SCIP 6:00 AM blood sugar metric does correlate with average blood sugar on POD 1. Compliance with SCIP 6:00 AM blood sugar measurement is a valid surrogate for GC, though duration of hyperglycemia was still 14% in the compliant group. Use of an IIP does not guarantee GC, despite increased intensity of its application. Even intense use of an IIP may be ineffective when it fails to account for patient risk factors for hyperglycemia.

Effectiveness of a clinical-decision-support system in improving compliance with cardiac-care quality measures and supporting resident training.

Many of the quality measures for patients with heart failure (HF) or acute myocardial infarction (AMI) require the completion of comprehensive discharge instructions, including instructions about medications to be taken after discharge. To improve compliance in a tertiary care teaching hospital with these evidence-based quality measures, a clinical-decision-support system (CDSS) that uses an electronic checklist was developed. The CDSS prompts clinicians at every training level to consistently create comprehensive discharge instructions addressing quality measures. The authors compared compliance during the 15-month preintervention and postintervention periods. Compliance with discharge measures for AMI (i.e., aspirin, beta-blocker, angiotensin-converting enzyme inhibitor [ACEI], or angiotensin receptor blocker [ARB] use) and for HF (i.e., discharge instructions, left ventricular systolic function [LVSF] evaluation, and ACEI/ARB use) was assessed. The delivery of discharge instructions showed significant improvement from the preintervention period to the postintervention period (37.2% to 93.0%; P < .001). Compliance with prescription of ACEI or ARB also improved significantly for HF (80.7% to 96.4%; P < .001) and AMI (88.1% to 100%; P = .014) patients. Compliance with the remaining measures was higher before intervention, and, thus, the modest improvement in the postintervention period was not statistically significant (AMI patients: aspirin, 97.5% to 98.8%; P = .43; and beta-blocker, 97.9% to 98.7%; P = .78; HF patients: LVSF, 99.3% to 99.1%; P = .78). Implementation of a CDSS with computerized electronic prompts improved compliance with selected cardiac-care quality measures. The design of quality-improvement decision-support tools should incorporate educational missions in their message and design.

Prescription drug use in the elderly: a descriptive analysis.

In the current policy debate, pharmaceutical use in the elderly has been characterized largely by its economic impact, with little discussion of what drugs the elderly are taking. Based on data from the Medicare Current Beneficiary Survey (MCBS), this study defines subgroups of the community-dwelling elderly using health and functional status, and provides a comprehensive description of the composition of prescription drug use in this population. Drugs are classified into 16 primary therapeutic classes, with further breakdown into secondary classes and characterization by chronic versus acute use. Utilization is reported by age and health status categories.

Developing a quality measurement tool and reporting format for long- term care.

BACKGROUND: Quality measurement in long term care (LTC) presents many challenges: the lack of a uniform definition of quality, the existence of multiple domains for measurement, a multitude of potential perspectives, and regulatory influences that emphasize measurement only of poor quality. Research efforts have yet to solve the issues of measurement; however, operators of long term care facilities must use the current state of the art in quality measurement as the basis for their quality improvement efforts. A project was commissioned by management of a large integrated delivery system with a robust network of LTC facilities who wished to implement a continuous quality improvement process on the basis of a measurement tool that provides a comprehensive resident-centered assessment of quality. The objectives of this project, therefore, were to identify domains of quality, to select and adapt validated instruments for measurement within each domain, to pilot test a data collection process, and to develop an operational quality profiling report format for LTC facilities. DESIGN AND METHODS: Using an expert panel and the LTC research literature, an operational measurement tool was developed, consisting of four domains of quality: organizational, clinical, environmental, and social. DISCUSSION: A pilot study conducted in two nursing facilities demonstrated that the data collection process could be operationalized within tight resource and budgetary constraints. The development of an operational quality assessment tool enables management to take a consistent view of diverse institutions, focusing in detail on quality of care as it is perceived by residents. The tool allows evaluation of trends over time and comparison to external norms.