A conceptual framework and protocol for defining clinical decision support objectives applicable to medical specialties.

BackgroundThe U.S. Centers for Medicare and Medicaid Services established the Electronic Health Record (EHR) Incentive Program in 2009 to stimulate the adoption of EHRs. One component of the program requires eligible providers to implement clinical decision support (CDS) interventions that can improve performance on one or more quality measures pre-selected for each specialty. Because the unique decision-making challenges and existing HIT capabilities vary widely across specialties, the development of meaningful objectives for CDS within such programs must be supported by deliberative analysis.DesignWe developed a conceptual framework and protocol that combines evidence review with expert opinion to elicit clinically meaningful objectives for CDS directly from specialists. The framework links objectives for CDS to specialty-specific performance gaps while ensuring that a workable set of CDS opportunities are available to providers to address each performance gap. Performance gaps may include those with well-established quality measures but also priorities identified by specialists based on their clinical experience. Moreover, objectives are not constrained to performance gaps with existing CDS technologies, but rather may include those for which CDS tools might reasonably be expected to be developed in the near term, for example, by the beginning of Stage 3 of the EHR Incentive program. The protocol uses a modified Delphi expert panel process to elicit and prioritize CDS meaningful use objectives. Experts first rate the importance of performance gaps, beginning with a candidate list generated through an environmental scan and supplemented through nominations by panelists. For the highest priority performance gaps, panelists then rate the extent to which existing or future CDS interventions, characterized jointly as "CDS opportunities," might impact each performance gap and the extent to which each CDS opportunity is compatible with specialists' clinical workflows. The protocol was tested by expert panels representing four clinical specialties: oncology, orthopedic surgery, interventional cardiology, and pediatrics

Examining the Relationship between Clinical Decision Support and Performance Measurement

In concept and practice, clinical decision support (CDS) and performance measurement represent distinct approaches to organizational change, yet these two organizational processes are interrelated. We set out to better understand how the relationship between the two is perceived, as well as how they jointly influence clinical practice. To understand the use of CDS at benchmark institutions, we conducted semistructured interviews with key managers, information technology personnel, and clinical leaders during a qualitative field study. Improved performance was frequently cited as a rationale for the use of clinical reminders. Pay-for-performance efforts also appeared to provide motivation for the use of clinical reminders. Shared performance measures were associated with shared clinical reminders. The close link between clinical reminders and performance measurement causes these tools to have many of the same implementation challenges

Quality systems in health care: A sociotechnical approach

In this paper, we explore a sociotechnical approach to construct quality systems as an alternative to the traditional, ISO orientated approach. A sociotechnical approach is characterised as bottom-up, incremental, information technology facilitated and indicator driven. Its purpose is to ground quality assurance in medical practice and to provide meaning to those directly involved (patients, health care providers and medical professionals). Meaning depends on information. According to contemporary theory of meaning, facts become information on quality if the structure of data represents the structure of the quality concept. The structure of the quality concept is exemplified by definitions of the quality of care, most of them comparing actual properties of care with requirements, expectations, standards or guidelines. So, raw data or measurements have to be compared with a normative frame of reference in order to become information on the quality of care. Quality indicators conceptualise this theory of meaning. Therefore, constructing quality systems by developing quality indicators is important for the meaning of quality assurance in health care. It makes a system to a quality system and suits a sociotechnical approach by grounding the formal structure of the system in a social reality

The safety implications of missed test results for hospitalised patients: a systematic review

Background: Failure to follow-up test results is a critical safety issue. The objective was to systematically review evidence quantifying the extent of failure to follow-up test results and the impact on patient outcomes. Methods: The authors searched Medline, CINAHL, Embase, Inspec and the Cochrane Database from 1990 to March 2010 for English-language articles which quantified the proportion of diagnostic tests not followed up for hospital patients. Four reviewers independently reviewed titles, abstracts and articles for inclusion. Results: Twelve studies met the inclusion criteria and demonstrated a wide variation in the extent of the problem and the impact on patient outcomes. A lack of follow-up of test results for inpatients ranged from 20.04% to 61.6% and for patients treated in the emergency department ranged from 1.0% to 75% when calculated as a proportion of tests. Two areas where problems were particularly evident were: critical test results and results for patients moving across healthcare settings. Systems used to manage followup of test results were varied and included paperbased, electronic and hybrid paper-and-electronic systems. Evidence of the effectiveness of electronic test management systems was limited. Conclusions: Failure to follow up test results for hospital patients is a substantial problem. Evidence of the negative impacts for patients when important results are not actioned, matched with advances in the functionality of clinical information systems, presents a convincing case for the need to explore solutions. These should include interventions such as on-line endorsement of results.6 page(s

Quality of care: analyzing the relationship between hospital quality score and total hospital costs

As healthcare costs and premiums have increased in the recent past, hospitals are forced to try to provide healthcare on tight budgets. In many cases, quality is often sacrificed in an effort to manage patient wait-times and costs. This research attempted to add to the existing body of knowledge of quality of care by defining a relationship between quality of care provided and total hospital costs. This study used the 2006 American Hospital Association’s Annual Survey Database and the 2006 Hospital Compare dataset to meet the data requirements for the study. A log-log, as well as a translog, cost function was used to estimate the relationship between quality of care provisioned for community acquired pneumonia and heart failure and total hospital costs. Regressors for the cost function included hospital outputs, inputs and wages as well as variables for patient-mix, case-mix, ownership status and medical school affiliation. Ultimately this study concluded that by increasing the quality of care score associated with community-acquired pneumonia by ten percent would decrease total hospital costs by 2.44 percent. However, several improvements were found that would improve the ability of the quality of care data and estimation methodologies to more comprehensively represent quality