diabetes clinical decision support

Conditions: Hyperglycemia; Hyperglycemia Stress; Diabetes; PreDiabetes; Hypoglycemia

Summary: the purpose of this study is to determine the impact of an electronic medical record clinical decision support tool on rates of dysglycemia in the hospital, and its clinical and economical outcomes. the study also evaluates the perspectives of providers regarding the tool's usefulness on disease management support, knowledge, and practice performance.

approximately 9 million patients with diabetes (dm) are hospitalized annually and over 30% of inpatients without dm experience high glucose (hg) due to their acute illness. hg increases the risk of infectious and non- infectious complications and death, hospital length of stay (los), utilization of hospital resources and overall healthcare costs. while glucose control reduces these risks, controlling hg in the hospital is difficult due to multiple barriers such as recognizing and proactively treating glucose abnormalities, and adequately ordering insulin to treat hg in the hospital. clinical decision support (cds) is a system that uses computerized person- specific data in the electronic medical record (emr) proven to improve hospital care. among the various modalities, alert-cds is shown to improve care delivery, providers' proactivity, and glucose control specifically in intensive care settings of academic institutions. however, alert-cds has not yet been studied outside of intensive care units (icu), or in community hospitals where most patients receive care. furthermore, its impact on patients' outcomes has not been tested in any setting. the proposed project uses an innovative alert-cds tool the investigators developed and validated which automatically identifies dysglycemia and inadequacies in insulin administration in the hospital. it alerts clinicians with recommendations to support decision making without superseding their clinical judgement. in the pilot study, it was found that this alert-cds tool reduced recurrent high glucose levels and shortened los. based on this promising preliminary data, in this project the investigators propose to study the impact of our cds tool on clinical, economic and providers' performance outcomes among non-intensive care patients both in an academic and a community hospital. this resource will be available intermittently in the emr every 3 months during 36 months, thus allowing the comparison of 18 months of intervention and 18 months of standard care. based on the pilot study, a sample size of 12,560 subjects will give an 80% power of detecting 0.34 days (\~ 8 hours) difference in length of stay, the primary endpoint of our study. the investigators propose the following aims: aim 1) to determine the impact of the alert-cds over conventional care on the clinical outcomes of non-icu patients in an academic and a community hospital. aim 2) to determine the impact of the alert-cds over conventional care on the economic outcomes of non-icu patients in an academic and a community hospital. aim 3) to determine the impact of alert-cds for inpatient glycemic control on providers' perspectives, competencies and practice performance between an academic and a community hospital. it is hypothesized that the tool will increase providers' knowledge about dysglycemia allowing them to make better decisions about insulin administration. the anticipated success of our study builds upon a well-established multidisciplinary team of investigators strongly supported by leadership stakeholders in both hospitals. the proposed study has the potential of establishing a new paradigm in the management of dysglycemia in hospitalized patients with a major positive impact on clinical and economic outcomes.

Eligibility criteria:
inclusion criteria: * hospitalized adult (\>18 years) patients at penn state health, hershey medical center, st. joseph's hospital, hampden medical center, and holy spirit medical center * ambulatory adult (\>18 years) patients at penn state health, hershey medical center * trigger of an alert or a disease management message exclusion criteria: * children (\<18 years)

Keywords: clinical decision support electronic medical records health systems science hospital management