Modeling Water Quality in Watersheds: From Here to the Next Generation

In this synthesis, we assess present research and anticipate future development needs in modeling water quality in watersheds. We first discuss areas of potential improvement in the representation of freshwater systems pertaining to water quality, including representation of environmental interfaces, in-stream water quality and process interactions, soil health and land management, and (peri-)urban areas. In addition, we provide insights into the contemporary challenges in the practices of watershed water quality modeling, including quality control of monitoring data, model parameterization and calibration, uncertainty management, scale mismatches, and provisioning of modeling tools. Finally, we make three recommendations to provide a path forward for improving watershed water quality modeling science, infrastructure, and practices. These include building stronger collaborations between experimentalists and modelers, bridging gaps between modelers and stakeholders, and cultivating and applying procedural knowledge to better govern and support water quality modeling processes within organizations.

Physician explanations for failing to comply with "best practices"

CONTEXT

Substantial effort has been devoted to improving physician compliance with evidence-based guidelines.

OBJECTIVE

To explore physicians' reasons for not following so-called "best practices" in caring for patients with type 2 diabetes.

DESIGN

Descriptive study of self-assessed compliance with five measures of performance.

PARTICIPANTS

Eighty-five internists who volunteered to participate in a practice-based research network created to improve clinical practice.

DATA COLLECTION

Physicians reviewed their own charts of patients with type 2 diabetes mellitus (1755 patient encounters) to assess compliance and offered open-ended comments concerning their reasons for not complying with "best practices."

RESULTS

The physician volunteers reported not complying with the annual foot examination in 13% of encounters. A similar level of noncompliance was reported for the annual lipid profile (15%) and retinal examination (17%). Among the five measures examined, noncompliance was most common for screening urinalysis (26%) and screening microalbuminuria (46%). The physicians' open-ended comments suggested that physician oversight, patient nonadherence, and systems issues were common reasons for noncompliance. However, noncompliance also resulted from a conscious decision by the physician, as indicated by comments about patient age and comorbid illness or, with nephropathy screening, established renal disease or current therapy with angiotensin-converting enzyme inhibitors.

CONCLUSIONS

Even among a self-selected group of physicians, noncompliance with best practices in diabetes is common. Although physician forgetfulness and external factors are frequently offered as reasons for noncompliance, it may also result from a conscious decision, as physicians may disagree about what constitutes "best practices."