[Text Comprehensibility of Hospital Report Cards]. / Verständlichkeit der Texte von Qualitätsvergleichen zu Krankenhausleistungen.

Objectives: Recently, the number of hospital report cards that compare quality of hospitals and present information from German quality reports has greatly increased. Objectives of this study were to a) identify suitable methods for measuring the readability and comprehensibility of hospital report cards, b) to obtain reliable information on the comprehensibility of texts for laymen, c) to give recommendations for improvements and d) to recommend public health actions. Methods: The readability and comprehensibility of the texts were tested with a) a computer-aided evaluation of formal text characteristics (readability indices Flesch (German formula) and 1. Wiener Sachtextformel formula), b) an expert-based heuristic analysis of readability and comprehensibility of texts (counting technical terms and analysis of text simplicity as well as brevity and conciseness using the Hamburg intelligibility model) and c) a survey of subjects about the comprehensibility of individual technical terms, the assessment of the comprehensibility of the presentations and the subjects' decisions in favour of one of the 5 presented clinics due to the better quality of data. In addition, the correlation between the results of the text analysis with the results from the survey of subjects was tested. Results: The assessment of texts with the computer-aided evaluations showed poor comprehensibility values. The assessment of text simplicity using the Hamburg intelligibility model showed poor comprehensibility values (-0.3). On average, 6.8% of the words used were technical terms. A review of 10 technical terms revealed that in all cases only a minority of respondents (from 4.4% to 39.1%) exactly knew what was meant by each of them. Most subjects (62.4%) also believed that unclear terms worsened their understanding of the information offered. The correlation analysis showed that presentations with a lower frequency of technical terms and better values for the text simplicity were better understood. Conclusion: The determination of the frequency of technical terms and the assessment of text simplicity using the Hamburg intelligibility model were suitable methods to determine the readability and comprehensibility of presentations of quality indicators. The analysis showed predominantly poor comprehensibility values and indicated the need to improve the texts of report cards.

[Structure of pain management facilities in Germany : Classification of medical and psychological pain treatment services-Consensus of the Joint Commission of the Professional Societies and Organizations for Quality in Pain Medicine]. / Struktur der schmerzmedizinischen Versorgung in Deutschland : Klassifikation schmerzmedizinischer Einrichtungen - Konsens der Gemeinsamen Kommission der Fachgesellschaften und Verbände für Qualität in der Schmerzmedizin.

On behalf of the Medical/Psychological Pain Associations, Pain Patients Alliance and the Professional Association of Pain Physicians and Psychologists, the Joint Commission of Professional Societies and Organizations for Quality in Pain Medicine, working in close collaboration with the respective presidents, has developed verifiable structural and process-related criteria for the classification of medical and psychological pain treatment facilities in Germany. Based on the established system of graded care in Germany and on existing qualifications, these criteria also argue for the introduction of a basic qualification in pain medicine. In addition to the first-ever comprehensive description of psychological pain facilities, the criteria presented can be used to classify five different levels of pain facilities, from basic pain management facilities, to specialized institutions, to the Centre for Interdisciplinary Pain Medicine. The recommendations offer binding and verifiable criteria for quality assurance in pain medicine and improved pain treatment.

Machine Learning for Patient-Specific Quality Assurance of VMAT: Prediction and Classification Accuracy.

PURPOSE: To assess the accuracy of machine learning to predict and classify quality assurance (QA) results for volumetric modulated arc therapy (VMAT) plans. METHODS AND MATERIALS: Three hundred three VMAT plans, including 176 gynecologic cancer and 127 head and neck cancer plans, were chosen in this study. Fifty-four complexity metrics were extracted from the QA plans and considered as inputs. Patient-specific QA was performed, and gamma passing rates (GPRs) were used as outputs. One Poisson lasso (PL) regression model was developed, aiming to predict individual GPR, and 1 random forest (RF) classification model was developed to classify QA results as "pass" or "fail." Both technical validation (TV) and clinical validation (CV) were used to evaluate the model reliability. GPR prediction accuracy of PL and classification performance of PL and RF were evaluated. RESULTS: In TV, the mean prediction error of PL was 1.81%, 2.39%, and 4.18% at 3%/3 mm, 3%/2 mm, and 2%/2 mm, respectively. No significant differences in prediction errors between TV and CV were observed. In QA results classification, PL had a higher specificity (accurately identifying plans that can pass QA), whereas RF had a higher sensitivity (accurately identifying plans that may fail QA). By using 90% as the action limit at a 3%/2 mm criterion, the specificity of PL and RF was 97.5% and 87.7% in TV and 100% and 71.4% in CV, respectively. The sensitivity of PL and RF was 31.6% and 100% in TV and 33.3% and 100% in CV, respectively. With 100% sensitivity, the QA workload of 81.2% of plans in TV and 62.5% of plans in CV could be reduced by RF. CONCLUSIONS: The PL model could accurately predict GPR for most VMAT plans. The RF model with 100% sensitivity was preferred for QA results classification. Machine learning can be a useful tool to assist VMAT QA and reduce QA workload.

Choosing a health plan: what information will consumers use?

Employers and policymakers are looking for ways to encourage competition among health plans, thus lowering costs and improving quality. Employers hope to foster competition among health plans by creating standardized measures of quality that supplement the traditional benefits and cost information employees use to compare plans and make choices. This DataWatch examines employees' interest in standardized measures of plan performance. Results from a survey of Massachusetts state employees show that cost and benefit information receive high rankings, but certain plan performance information does not.

The role of hospital infection control in the quality system of hospitals.

Like other highly specialized fields, quality systems have their own vocabulary which we must be familiar with; it has been internationally standardized. This standard should be adhered to in order to avoid unnecessary ambiguities and confusion, and to facilitate exchange of information between disciplines. We, in the infection control field, are quality pioneers in hospitals. We have, within our discipline, created quality systems and practised quality surveillance for decades. This must be recognized. Medical quality audits intended for comparisons between hospitals, services and wards require measurable quality criteria and comparable measures for the presence of all relevant patient-related risk factors. To specify quality within our field we need much more detailed information on the effect and cost of infection control practices, as well as the costs of the infections we intend to control. To progress one step further, patients or their representatives, politicians, need to express what monetary value should be put on health, namely freedom from infection and its consequences.

Clinical trial of umbilical artery Doppler waveform quality indices.

The ability of two Doppler waveform quality indices to discriminate between high- and low-quality waveforms was tested using 427 sets of umbilical artery Doppler waveforms from patients. The waveforms had been acquired using a 4-MHz continuous-wave Doppler unit. The quality indices (QI) were based on an assessment of the degree of noise of the maximum frequency envelope of the waveforms, and were first a correlation between successive waveform envelopes (QI1), and, second, a sum of local linearity measures (QI2). The sets of waveforms were graded subjectively according to the clarity of the outline of the waveforms, the degree of interference in the region of the spectrum above the outline, and in terms of the degree of variability caused by fetal breathing. At 90% sensitivity for detection of low-quality waveforms according to a high envelope clarity score, the specificities were 68.2% and 52.7%, respectively, for QI1 and QI2. QI1 was independent from pulsatility index and waveform length, but showed strong dependence on fetal breathing. QI2 showed strong independence from pulsatility and fetal breathing and reasonable independence from waveform length. Both QI1 and QI2 performed poorly when there was a large degree of noise in the region of the spectrum above the envelope; however, this poor performance was often related to the inability of the maximum frequency follower to estimate correctly the maximum frequency envelope in those conditions so that the high waveform quality values reflected the erroneous calculation of pulsatility index in those cases.

Measuring the quality of clinical audit projects.

The aim of the study was to develop and pilot a scale measuring the quality of audit projects through audit project reports. Statements about clinical audit projects were selected from existing instruments assessing the quality of clinical audit projects to form a Likert scale. Audit facilitators based in Scottish health boards and trusts piloted the scale. The participants were known to have over 2 years of experience of supporting clinical audit. The response at first test was 11 of 14 and at the second test 27 of 46. Audit facilitators tested the draft scale by expressing their strength of agreement or disagreement with each statement for three reports. Validity and reliability were assessed by test - re-test, item - total, and total - global indicator correlation. Of the 20 statements, 15 had satisfactory correlation with scale totals. Scale totals had good correlation with global indicators. Test re-test correlation was modest. The wide range of responses means further research is needed to measure the consistency of audit facilitators' interpretations, perhaps comparing a trained group with an untrained group. There may be a need for a separate scale for reaudits. Educational impact is distinct from project impact generally. It may be more meaningful to treat the selection of projects and aims, methodology and impact separately as subscales and take a project profiling approach rather than attempting to produce a global quality index.

Who needs clinical audit?

Clinical audit focuses on self--and, more importantly, peer assessments of the performance of practitioners and the service they provide to patients. Some practitioners may feel threatened by audit; however, when conducted as intended and viewed as a form of education, it may become recognised as an integral, cost-effective element of everyday clinical practice. This article highlights ways in which practitioners may increasingly appreciate the need to understand and apply clinical audit processes in their practice environments.

Differentiating among research, evaluation and measures to assure quality.

This article explores the similarities, differences and overlaps among research, evaluation and quality measurement. Criteria for determining the differences are offered as a quick guide to differentiating among them. These criteria are the purpose of the project, generalizability, intended use of the findings, intended subjects and intent to prove causation. Determining the key differences among research, evaluation and quality measurement facilitates the choice of restrictions, supports and reporting process that should be applied to each.

What quality measurements miss.

Measurable indices of health care quality are all the rage these days. But physicians know that not everything in health care can be quantified. If reportable numbers become our principal focus, what is in danger of falling through the cracks?

QA, CQI, TQM: what's the difference?

Total Quality Management (TQM) is not a program, but a process. It is a major cultural change of healthcare organizations. TQM should not be embraced as a "short term fix," but as the long term solution to the shortcomings in the delivery of patient care.

[Evaluating quality and effectiveness in the promotion of health: approaches and methods of public health and social sciences]. / Evaluer la qualité et l'efficacité de la promotion de la santé: approches et méthodes de santé publique et de science humaines.

Health promotion and health education have often been limited to evaluation of the effectiveness of actions and programmes. However, since 1996 with the Third European Conference on Health Promotion and Education Effectiveness, many researchers have become interested in "quality assessment" and new ways of thinking have emerged. Quality assurance is a concept and activity developed in industry with the objective of increasing production efficiency. There are two distinct approaches: External Standard Inspection (ESI) and Continuous Quality Improvement (CQI). ESI involves establishing criteria of quality, evaluating them and improving whatever needs improvement. CQI views the activity or service as a process and includes the quality assessment as part of the process. This article attempts to answer the questions of whether these methods are sufficient and suitable for operationalising the concepts of evaluation, effectiveness and quality in health promotion and education, whether it is necessary to complement them with other methods, and whether the ESI approach is appropriate. The first section of the article explains that health promotion is based on various paradigms from epidemiology to psychology and anthropology. Many authors warn against the exclusive use of public health disciplines for understanding, implementing and evaluating health promotion. The author argues that in practice, health promotion: -integrates preventive actions with those aiming to maintain and improve health, a characteristic which widens the actions of health promotion from those of classic public health which include essentially an epidemiological or "risk" focus; -aims to replace vertical approaches to prevention with a global approach based on educational sciences; -involves a community approach which includes the individual in a "central position of power" as much in the definition of needs as in the evaluation of services; -includes the participation and socio-political actions which necessitate the use of varied and specific instruments for action and evaluation. With the choice of health promotion ideology, there exist corresponding theories, concepts of quality, and therefore methods and techniques that differ from those used until now. The educational sciences have led to a widening of the definition of process to include both "throughput and input", which has meant that the methods of needs analysis, objective and priority setting and project development in health promotion have become objects of quality assessment. Also, the modes of action and interaction among actors are included, which has led to evaluation of ethical and ideological aspects of projects. The second section of the article discusses quality assessment versus evaluation of effectiveness. Different paradigms of evaluation such as the public health approach based on the measurement of (epidemiological) effectiveness, social marketing and communication, and the anthropological approach are briefly discussed, pointing out that there are many approaches which can both complement and contradict one another. The author explains the difference between impact (the intermediate effects, direct or indirect, planned or not planned, changes in practical or theoretical knowledge, perceptions, and attitudes) and results (final effects of mid to long term changes such as changes in morbidity, mortality, or access to services or cost of health care). He argues that by being too concerned with results of programmes, we have often ignored the issue of impact. Also, by limiting ourselves to evaluating effectiveness (i.e. that the expected effects were obtained), we ignore other possible unexpected, unplanned and positive and negative secondary effects. There are therefore many reasons to: -evaluate all possible effects rather than only those lined to objectives; -evaluate the entire process rather than only the resources, procedures and costs; -evaluate the impact rather than results; -evalu

Dissecting the HMO-benefits managers relationship: what to measure and why.

The relationship between health maintenance organizations (HMO) and employee benefits managers (EBM) is multidimensional and complex. Relationship marketing theory is used to illustrate its role in strengthening interorganizational bonds and reducing defections to other health plans. The importance of various service dimensions in the HMO-EBM relationship can change depending on whether the measure used is overall satisfaction, overall quality, and loyalty to the HMO. By dissecting relationships in this way, HMOs can develop strategies that take multiple routes for building and maintaining strong partnerships with employee benefits managers.

Surgical pathology report defects: a College of American Pathologists Q-Probes study of 73 institutions.

CONTEXT: The rate of surgical pathology report defects is an indicator of quality and it affects clinician satisfaction. OBJECTIVE: To establish benchmarks for defect rates and defect fractions through a large, multi-institutional prospective application of standard taxonomy. DESIGN: Participants in a 2011 Q-Probes study of the College of American Pathologists prospectively reviewed all surgical pathology reports that underwent changes to correct defects and reported details regarding the defects. RESULTS: Seventy-three institutions reported 1688 report defects discovered in 360,218 accessioned cases, for an aggregate defect rate of 4.7 per 1000 cases. Median institutional defect rate was 5.7 per 1000 (10th to 90th percentile range, 13.5-0.9). Defect rates were higher in institutions with a pathology training program (8.5 versus 5.0 per 1000, P = .01) and when a set percentage of cases were reviewed after sign-out (median, 6.7 versus 3.8 per 1000, P = .10). Defect types were as follows: 14.6% misinterpretations, 13.3% misidentifications, 13.7% specimen defects, and 58.4% other report defects. Overall, defects were most often detected by pathologists (47.4%), followed by clinicians (22.0%). Misinterpretations and specimen defects were most often detected by pathologists (73.5% and 82.7% respectively, P < .001), while misidentifications were most often discovered by clinicians (44.6%, P < .001). Misidentification rates were lower when all malignancies were reviewed by a second pathologist before sign-out (0.0 versus 0.6 per 1000, P < .001), and specimen defect rates were lower when intradepartmental review of difficult cases was conducted after sign-out (0.0 versus 0.4 per 1000, P = .02). CONCLUSION: This study provides benchmarking data on report defects and defect fractions using standardized taxonomy.

Orthopedics coding and funding.

The French tarification à l'activité (T2A) prospective payment system is a financial system in which a health-care institution's resources are based on performed activity. Activity is described via the PMSI medical information system (programme de médicalisation du système d'information). The PMSI classifies hospital cases by clinical and economic categories known as diagnosis-related groups (DRG), each with an associated price tag. Coding a hospital case involves giving as realistic a description as possible so as to categorize it in the right DRG and thus ensure appropriate payment. For this, it is essential to understand what determines the pricing of inpatient stay: namely, the code for the surgical procedure, the patient's principal diagnosis (reason for admission), codes for comorbidities (everything that adds to management burden), and the management of the length of inpatient stay. The PMSI is used to analyze the institution's activity and dynamism: change on previous year, relation to target, and comparison with competing institutions based on indicators such as the mean length of stay performance indicator (MLS PI). The T2A system improves overall care efficiency. Quality of care, however, is not presently taken account of in the payment made to the institution, as there are no indicators for this; work needs to be done on this topic.

Do popular media and internet-based hospital quality ratings identify hospitals with better cardiovascular surgery outcomes?

BACKGROUND: Several popular media and Internet-based hospital quality rankings have become increasingly publicized as a method for patients to choose better hospitals. It is unclear whether selecting highly rated hospitals will improve outcomes after cardiovascular surgery procedures. STUDY DESIGN: Using 2005 to 2006 Medicare data, we studied all patients undergoing abdominal aortic aneurysm repair, coronary artery bypass, aortic valve repair, and mitral valve repair (n = 312,813). Primary outcomes included risk-adjusted mortality, adjusting for patient characteristics and surgical acuity. We compared mortality at "Best Hospitals," according to US News and World Report and HealthGrades, with all other hospitals. We adjusted for hospital volume to determine whether hospital experience accounts for differences in mortality. RESULTS: Risk-adjusted mortality was considerably lower in US News and World Report's "Best Hospitals" for abdominal aortic aneurysm repair only (odds ratio [OR] = 0.76; 95% CI, 0.61 to 0.94). Risk-adjusted mortality was considerably lower in HealthGrades' "Best Hospitals" after all 4 procedures: abdominal aortic aneurysm repair (OR = 0.75; 95% CI, 0.58 to 0.97), coronary artery bypass (OR = 0.78; 95% CI, 0.68 to 0.89), aortic valve repair (OR = 0.71; 95% CI, 0.59 to 0.85), and mitral valve repair (OR = 0.77; 95% CI, 0.61 to 0.99). Accounting for hospital volume, risk-adjusted mortality was not substantially lower at the US News and World Report's "Best Hospitals," while risk-adjusted mortality was lower at HealthGrades' "Best Hospitals" after coronary artery bypass and aortic valve repair mortality rates were adjusted for hospital volume (OR = 0.77; 95% CI, 0.64 to 0.92 and OR = 0.81; 95% CI, 0.71 to 0.94). CONCLUSIONS: Popular hospital rating systems identify high-quality hospitals for cardiovascular operations. However, patients can experience equivalent outcomes by seeking care at high-volume hospitals.