To document current practices on long-term maintenance of quality measures and to develop a consensus framework to guide the design of maintenance systems.
Survey of 10 organisations developing measures and selected researchers in the USA about current policies and procedures and desirable properties for a comprehensive system for measures maintenance. Panel discussions with all respondents to arrive at consensus recommendations for a framework for maintenance of measures.
Five measures developers, two provider and three purchaser organisations. Six were private sector organisations, two were governmental agencies, and two were accreditation institutions.
All organisations had procedures for measures maintenance, but the degree of formalisation of the procedures varied. Three key functions for a measures maintenance system emerged: ad hoc review to deal with unexpected problems; annual maintenance to incorporate changes in coding conventions; and regular re-evaluation to thoroughly review measures at predefined intervals. Importance, scientific soundness, feasibility and usability were universally used as evaluation criteria. The panel discussions yielded a consensus set of recommendations for relationships between maintenance functions, evaluation criteria and measures disposition.
A sufficient degree of implicit consensus was found among leading measures developers to arrive at a consensus framework for policies and procedures for measures maintenance. Although organisations may choose to implement the framework in a way that is most consistent with their mission and structure, it provides guidance regarding which components should be included.
To investigate the utility of the GMC patient and colleague questionnaires in assessing the professional performance of a large sample of UK doctors.
Cross-sectional questionnaire surveys.
Range of UK clinical practice settings.
541 doctors gave preliminary agreement to take part in the study. Responses were received from 13 754 patients attending one of 380 participant doctors, and from 4269 colleagues of 309 participant doctors.
Questionnaire performance and standardised scores for each doctor derived from patient and colleague responses.
Participant doctors were similar to non-participants in respect of age and gender. The patient and colleague questionnaires were acceptable to participants as evidenced by low levels of missing data. One patient questionnaire item seemed to cause confusion for respondents and requires rewording. Both patient and colleague responses were highly skewed towards favourable impressions of doctor performance, with high internal consistency. To achieve acceptable levels of reliability, a minimum of 8 colleague questionnaires and 22 patient questionnaires are required. G coefficients for both questionnaires were comparable with internationally recognised survey instruments of broadly similar intent. Patient and colleague assessments provided complementary perspectives of doctors’ performance. Older doctors had lower patient-derived and colleague-derived scores than younger doctors. Doctors from a mental health trust and doctors providing care in a variety of non-NHS settings had lower patient scores compared with doctors providing care in acute or primary care trust settings.
The GMC patient and colleague questionnaires offer a reliable basis for the assessment of professionalism among UK doctors. If used in the revalidation of doctors’ registration, they would be capable of discriminating a range of professional performance among doctors, and potentially identifying a minority whose practice should to subjected to further scrutiny.
Little is known about the types and outcomes of testing process errors that occur in primary care.
To describe types, predictors and outcomes of testing errors reported by family physicians and office staff.
Events were reported anonymously. Each office completed a survey describing their testing processes prior to event reporting.
243 clinicians and office staff of eight family medicine offices.
Distribution of error types, associations with potential predictors; predictors of harm and consequences of the errors.
Participants submitted 590 event reports with 966 testing process errors. Errors occurred in ordering tests (12.9%), implementing tests (17.9%), reporting results to clinicians (24.6%), clinicians responding to results (6.6%), notifying patient of results (6.8%), general administration (17.6%), communication (5.7%) and other categories (7.8%). Charting or filing errors accounted for 14.5% of errors. Significant associations (p<0.05) existed between error types and type of reporter (clinician or staff), number of labs used by the practice, absence of a results follow-up system and patients’ race/ethnicity. Adverse consequences included time lost and financial consequences (22%), delays in care (24%), pain/suffering (11%) and adverse clinical consequence (2%). Patients were unharmed in 54% of events; 18% resulted in some harm, and harm status was unknown for 28%. Using multilevel logistic regression analyses, adverse consequences or harm were more common in events that were clinician-reported, involved patients aged 45–64 years and involved test implementation errors. Minority patients were more likely than white, non-Hispanic patients to suffer adverse consequences or harm.
Errors occur throughout the testing process, most commonly involving test implementation and reporting results to clinicians. While significant physical harm was rare, adverse consequences for patients were common. The higher prevalence of harm and adverse consequences for minority patients is a troubling disparity needing further investigation.
Little research has focused on preventing harm from errors that occur in primary care. We studied mitigation of patient harm by analysing error reports from family physicians’ offices.
The data for this analysis come from reports of testing process errors identified by family physicians and their office staff in eight practices in the American Academy of Family Physicians National Research Network. We determined how often reported error events were mitigated, described factors related to mitigation and assessed the effect of mitigation on the outcome of error events.
We identified mitigation in 123 (21%) of 597 testing process event reports. Of the identified mitigators, 79% were persons from inside the practice, and 7% were patients or patient’s family. Older age was the only patient demographic attribute associated with increased likelihood of mitigation occurring (unadjusted OR 18–44 years compared with 65 years of age or older = 0.27; p = 0.007). Events that included testing implementation errors (11% of the events) had lower odds of mitigation (unadjusted OR = 0.40; p = 0.001), and events containing reporting errors (26% of the events) had higher odds of mitigation (unadjusted OR = 1.63; p = 0.021). As the number of errors reported in an event increased, the odds of that event being mitigated decreased (unadjusted OR = 0.58; p = 0.001). Multivariate logistic regression showed that an event had higher odds of being mitigated if it included an ordering error or if the patient was 65 years of age or older, and lower odds of being mitigated if the patient was between age 18 and 44, or if the event included an implementation error or involved more than one error. Mitigated events had lower odds of patient harm (unadjusted OR = 0.16; p<0.0001) and negative consequences (unadjusted OR = 0.28; p<0.0001). Mitigated events resulted in less severe and fewer detrimental outcomes compared with non-mitigated events.
Nearly a quarter of testing process errors reported by family physicians and their staff had evidence of mitigation, and mitigated errors resulted in less frequent and less serious harm to patients. Vigilance throughout the testing process is likely to detect and correct errors, thereby preventing or reducing harm.
To assess the utility of data already existing within hospitals for monitoring patient safety.
An acute hospital in southern England.
Mapping of data sources proposed by staff as potentially able to identify patient safety issues followed by an in-depth analysis of the content of seven key sources.
For each data source: scope and depth of content in relation to patient safety, number and type of patient safety incidents identified, degree of overlap with incidents identified by different sources, levels of patient harm associated with incidents.
A wide range of data sources existing within the hospital setting have the potential to provide information about patient safety incidents. Poor quality of coding, delays in reports reaching databases, the narrow focus of some data sources, limited data-collection periods and lack of central collation of findings were some of the barriers to making the best use of routine data sources for monitoring patient safety. An in-depth analysis of seven key data sources (Clinical Incident database, Health and Safety Incident database, Complaints database, Claims database and Inquest database, the Patient Administration System and case notes) indicated that case notes have the potential to identify the largest number of incidents and provide the richest source of information on such incidents. The seven data sources identified different types of incidents with differing levels of patient harm. There was little overlap between the incidents identified by different sources.
Despite issues related to the quality of coding, depth of information available and accessibility, triangulating information from more than one source can identify a broader range of incidents and provide additional information related to professional groups involved, types of patients affected and important contributory factors. Such an approach can provide a focus for further work and ultimately contributes to the identification of appropriate interventions that improve patient safety.
Adverse events in hospitals constitute a serious problem with grave consequences. Many studies have been conducted to gain an insight into this problem, but a general overview of the data is lacking. We performed a systematic review of the literature on in-hospital adverse events.
A formal search of Embase, Cochrane and Medline was performed. Studies were reviewed independently for methodology, inclusion and exclusion criteria and endpoints. Primary endpoints were incidence of in-hospital adverse events and percentage of preventability. Secondary endpoints were adverse event outcome and subdivision by provider of care, location and type of event.
Eight studies including a total of 74 485 patient records were selected. The median overall incidence of in-hospital adverse events was 9.2%, with a median percentage of preventability of 43.5%. More than half (56.3%) of patients experienced no or minor disability, whereas 7.4% of events were lethal. Operation- (39.6%) and medication-related (15.1%) events constituted the majority. We present a summary of evidence-based interventions aimed at these categories of events.
Adverse events during hospital admission affect nearly one out of 10 patients. A substantial part of these events are preventable. Since a large proportion of the in-hospital events are operation- or drug-related, interventions aimed at preventing these events have the potential to make a substantial difference.