End-of-life quality metrics among medicare decedents at minority-serving cancer centers: A retrospective study.

BACKGROUND: We calculated the performance of National Cancer Institute (NCI)/National Comprehensive Cancer Network (NCCN) cancer centers' end-of-life (EOL) quality metrics among minority and white decedents to explore center-attributable sources of EOL disparities. METHODS: We conducted a retrospective cohort study of Medicare beneficiaries with poor-prognosis cancers who died between April 1, 2016 and December 31, 2016 and had any inpatient services in the last 6 months of life. We attributed patients' EOL treatment to the center at which they received the preponderance of EOL inpatient services and calculated eight risk-adjusted metrics of EOL quality (hospice admission ≤3 days before death; chemotherapy last 14 days of life; ≥2 emergency department (ED) visits; intensive care unit (ICU) admission; or life-sustaining treatment last 30 days; hospice referral; palliative care; advance care planning last 6 months). We compared performance between patients across and within centers. RESULTS: Among 126,434 patients, 10,119 received treatment at one of 54 NCI/NCCN centers. In aggregate, performance was worse among minorities for ED visits (10.3% vs 7.4%, P < .01), ICU admissions (32.9% vs 30.4%, P = .03), no hospice referral (39.5% vs 37.0%, P = .03), and life-sustaining treatment (19.4% vs 16.2%, P < .01). Despite high within-center correlation for minority and white metrics (0.61-0.79; P < .01), five metrics demonstrated worse performance as the concentration of minorities increased: ED visits (P = .03), ICU admission (P < .01), no hospice referral (P < .01), and life-sustaining treatments (P < .01). CONCLUSION: EOL quality metrics vary across NCI/NCCN centers. Within center, care was similar for minority and white patients. Minority-serving centers had worse performance on many metrics.

An update on tobacco control initiatives in comprehensive cancer control plans.

INTRODUCTION: Comprehensive cancer control (CCC) coalitions address tobacco use, the leading cause of preventable death in the United States, through formal plans to guide tobacco control activities and other cancer prevention strategies. Best Practices for Comprehensive Tobacco Control Programs (Best Practices) and The Guide to Community Preventive Services (The Community Guide) are used to assist with this effort. We examined CCC plans to determine the extent to which they followed the Centers for Disease Control and Prevention's (CDC's) tobacco control and funding recommendations. METHODS: We obtained 69 CCC plans, current as of August 1, 2011, to determine which CDC recommendations from Best Practices and The Community Guide were incorporated. Data were abstracted through a content review and key word search and then summarized across the plans with dichotomous indicators. Additionally, we analyzed plans for inclusion of tobacco control funding goals and strategies. RESULTS: CCC plans incorporated a mean 4.5 (standard deviation [SD], 2.1) of 5 recommendations from Best Practices and 5.2 (SD, 0.9) of 10 recommendations from The Community Guide. Two-thirds of plans (66.7%) addressed funding for tobacco control as a strategy or action item; 47.8% of those plans (31.9% of total) defined a specific, measurable funding goal. CONCLUSION: Although most CCC plans follow CDC-recommended tobacco control recommendations and funding levels, not all recommendations are addressed by every plan and certain recommendations are addressed in varying numbers of plans. Clearer prioritization of tobacco control recommendations by CDC may improve the extent to which they are followed and therefore maximize their public health benefit.

Managing drug-related morbidity and mortality in the patient-centered medical home.

BACKGROUND: The appropriate use of medications can influence quality performance measures and costs. Drug-related morbidity and mortality represents a public health challenge due to the ineffective and unsafe consequences of medication use. This article addresses the impact of team-based care that incorporates comprehensive medication therapy management on per capita expenditures, quality performance measures, and resolution of drug therapy problems. METHODS: A team-based medication therapy management system developed over 13 years in an integrated health system in 4 Minnesota innovation clinic sites was assessed in terms of: (1) differences in total median health expenditures compared with noninnovation clinics, (2) improvements on 5 performance benchmarks for patients with diabetes in comparison with statewide results, and (3) resolution of drug therapy problems. RESULTS: Spending growth was 11% less in innovation clinics than that in 38 noninnovation clinics. Median per member per month health care costs measured at 5 intervals over a 15-month period were significantly lower in innovation than in noninnovation sites (P=0.05). Forty percent of patients with diabetes in the innovation clinics achieved all 5 performance benchmark treatment goals in 2009, with a range from 34% to 45%, compared with the statewide result of 17.5% of patients achieving all 5 benchmarks. In addition, over 4000 drug therapy problems were reported to be resolved. CONCLUSIONS: Team-based care helped to achieve quality performance and control spending growth through medication therapy management in a patient-centered medical home innovation.

Employing post-DEA cross-evaluation and cluster analysis in a sample of Greek NHS hospitals.

To increase Data Envelopment Analysis (DEA) discrimination of efficient Decision Making Units (DMUs), by complementing "self-evaluated" efficiencies with "peer-evaluated" cross-efficiencies and, based on these results, to classify the DMUs using cluster analysis. Healthcare, which is deprived of such studies, was chosen as the study area. The sample consisted of 27 small- to medium-sized (70-500 beds) NHS general hospitals distributed throughout Greece, in areas where they are the sole NHS representatives. DEA was performed on 2005 data collected from the Ministry of Health and the General Secretariat of the National Statistical Service. Three inputs -hospital beds, physicians and other health professionals- and three outputs -case-mix adjusted hospitalized cases, surgeries and outpatient visits- were included in input-oriented, constant-returns-to-scale (CRS) and variable-returns-to-scale (VRS) models. In a second stage (post-DEA), aggressive and benevolent cross-efficiency formulations and clustering were employed, to validate (or not) the initial DEA scores. The "maverick index" was used to sort the peer-appraised hospitals. All analyses were performed using custom-made software. Ten benchmark hospitals were identified by DEA, but using the aggressive and benevolent formulations showed that two and four of them respectively were at the lower end of the maverick index list. On the other hand, only one 100% efficient (self-appraised) hospital was at the higher end of the list, using either formulation. Cluster analysis produced a hierarchical "tree" structure which dichotomized the hospitals in accordance to the cross-evaluation results, and provided insight on the two-dimensional path to improving efficiency. This is, to our awareness, the first study in the healthcare domain to employ both of these post-DEA techniques (cross efficiency and clustering) at the hospital (i.e. micro) level. The potential benefit for decision-makers is the capability to examine high and low "all-round" performers and maverick hospitals more closely, and identify and address problems typically overlooked by first-stage DEA.

Review of the application of risk-adjusted charts to analyse mortality outcomes in critical care.

This review describes the methods for displaying riskadjusted mortality data for critical care units. Two applications are considered. The comparison within a cohort of risk-adjusted mortality performance uses standardised mortality ratios (SMRs), league tables, caterpillar plots and funnel plots. Monitoring of riskadjusted performance over time is considered using SMRs, risk-adjusted p (RAP), observed minus expected outcome (VLAD), risk-adjusted cumulative sum (RACUSUM), riskadjusted sequential probability ratio test (RASPRT), and riskadjusted exponentially weighted moving average (RAEWMA) charts. Examples of the charts are provided, and calculation of the statistics and design of the charts are described in the Appendix. This overview is an introduction to the use of riskadjustment methods to track mortality rates. The importance of model performance and relevance of the risk-adjustment models is emphasised. The relative merits of different methods are discussed. Risk-adjusted monitoring plays a role in the context of a holistic quality development strategy. The importance of a planned approach to response and intervention is stressed.

Lymph node evaluation as a colon cancer quality measure: a national hospital report card.

BACKGROUND: Examination of 12 or more regional lymph nodes for colon cancer is associated with improved staging and survival, and the National Quality Forum recently endorsed lymph node examination for colon cancer as a quality surveillance measure. However, information regarding the extent of hospital compliance with the 12-node measure in the United States is lacking. METHODS: From the National Cancer Data Base, 1296 hospitals that performed 156 789 colectomies in 1996-1997 and 2004-2005 were identified, and rates of hospital-level compliance (defined as examination of >or=12 nodes in >or=75% of patients) in these two time periods were compared. Multivariable models were developed to determine if hospital type, volume, or differences in case mix were associated with 12-node measure compliance. All statistical tests were two-sided. RESULTS: In 1996-1997, 15% of hospitals were compliant with the 12-node measure; in 2004-2005 the percentage of compliant hospitals had increased to 38%. From 1996-1997 to 2004-2005, 12-node measure compliance increased at 980 hospitals, remained unchanged at 6 hospitals, and decreased at 310 hospitals. In 2004-2005, National Cancer Institute-designated Comprehensive Cancer Centers were more frequently compliant with the 12-node measure than other academic hospitals, Veterans' Administration hospitals, or community hospitals (78.1% versus 52.4%, 53.1%, and 33.7%, respectively, all P < .001), even after adjustment for differences in characteristics of the colon cancer patients at these hospitals. CONCLUSIONS: This study provides a national report card of nearly 1300 hospitals showing that more than 60% of institutions failed to achieve a compliance benchmark for the 12-node measure. Considerable improvement is needed in colon cancer nodal evaluation in the United States.

On the reliability of a dental OSCE, using SEM: effect of different days.

AIM: The first aim was to study the reliability of a dental objective structured clinical examination (OSCE) administered over multiple days, and the second was to assess the number of test stations required for a sufficiently reliable decision in three score interpretation perspectives of a dental OSCE administered over multiple days. MATERIALS AND METHODS: In four OSCE administrations, 463 students of the year 2005 and 2006 took the summative OSCE after a dental course in comprehensive dentistry. The OSCE had 16-18 5-min stations (scores 1-10), and was administered per OSCE on four different days of 1 week. ANOVA was used to test for examinee performance variation across days. Generalizability theory was used for reliability analyses. Reliability was studied from three interpretation perspectives: for relative (norm) decisions, for absolute (domain) and pass-fail (mastery) decisions. As an indicator of reproducibility of test scores in this dental OSCE, the standard error of measurement (SEM) was used. The benchmark of SEM was set at <0.51. This is corresponding to a 95% confidence interval (CI) of <1 on the original scoring scale that ranged from 1 to 10. RESULTS: The mean weighted total OSCE score was 7.14 on a 10-point scale. With the pass-fail score set at 6.2 for the four OSCE, 90% of the 463 students passed. There was no significant increase in scores over the different days the OSCE was administered. 'Wished' variance owing to students was 6.3%. Variance owing to interaction between student and stations and residual error was 66.3%, more than two times larger than variance owing to stations' difficulty (27.4%). The SEM norm was 0.42 with a CI of +/-0.83 and the SEM domain was 0.50, with a CI of +/-0.98. In order to make reliable relative decisions (SEM <0.51), the use of minimal 12 stations is necessary, and for reliable absolute and pass-fail decisions, the use of minimal 17 stations is necessary in this dental OSCE. CONCLUSIONS: It appeared reliable, when testing large numbers of students, to administer the OSCE on different days. In order to make reliable decisions for this dental OSCE, minimum 17 stations are needed. Clearly, wide sampling of stations is at the heart of obtaining reliable scores in OSCE, also in dental education.

[Evidence level Ia--is the gold standard of scientific evidence as attractive as its reputation?]. / Evidence Level I a--Ist die Königin der wissenschaftlichen Evidenz so attraktiv wie ihr Ruf?

Here we raise the question as to whether the highest standard of valid statements, the meta-analysis, really earns its reputation and needs no further testing. For that purpose we formulated the hypothesis that the evaluation of clinical studies and meta-analyses is largely based on subjective criteria, which have hitherto not been sufficiently standardised. To support this hypothesis, we present scientific evidence on three topics: 1) Studies included in meta-analyses do not always meet the quality demands for inclusion in a meta-analysis. 2) The comprehensive results of a meta-analysis, which is read by scientists, do not always correspond with the summary in the same meta-analysis, which is read by politicians and decision makers in the health-care system. 3) Every scientist who does not want to relinquish his/her autonomy will decide for him- / herself whether new scientific data (external evidence) is sufficiently valid and convincing to change his/her previous conviction (internal evidence) should this not coincide with the new data. This process is always subjective and individual. We believe we can prove with sufficiently valid methods that even meta-analyses require testing, which can only be guaranteed by the scientific community itself. This guarantee must be reliable, i. e., pseudoevidence must be avoided because society will otherwise lose trust in the achievements of the scientific community and orient itself towards other statements, which may be subject to less methodically stringent proof.

[Hemodialysis prospective multicentric quality study]. / Estudio prospectivo multicentrico de calidad en hemodialisis.

In medicine a considerable amount of resources are used in research, but very little attention is paid to ensuring that the findings of research are implemented in routine clinical practice. This prospective study has the aim to evaluate the efficiency of some clinical management strategies (feedback, benchmarking and improving plans) on haemodialysis treatment results in 4 different dialysis centres. We collected consensus data related to haemodialysis results every 6-8 months and informed each centre about its own results (feedback) and how these related to the others(benchmarking). We designed improving plans for any bad result detected. By the end of two years of follow up, 294 patients had been included in the study. The results obtained at the end of the study had improved in comparison with those obtained at the beginning (statistically significant) for the following indicators: % of patients with Hb< 11 g/dl, % patients with Kt/v < 1.2, mean Kt/v, mean albumin, % patients with albumin< 3.5 g/dl y % patients with C reactive protein (CRP) > 5 mg/dl. No statistical changes were found in: mean erythropoietin (EPO) doses, blood pressure (BP), phosphorus plasmatic,calcium-phosphorus product, parathormone (PTHi) and vascular access distribution. We explained the absence of any improvement because of adequate start indicators in some areas (BP and vascular access), therapy with limited efficiency (calcitriol, calcium carbonate and others), lack of support resources (dietetic unit) or inadequate design/implementation of improving plans.In conclusion, our intervention illustrates that combined clinical management strategies(feedback, benchmarking and improving plans) are efficiency in improving some areas of haemodialysis treatment (anaemia, dialysis dose, nutrition and inflammation), although it does not improve calcium phosphate metabolism related indicators.

The EFQM Excellence Model. German experiences with the EFQM approach in health care.

OBJECTIVE: To expand on previous reports by illustrating experiences German health services organizitions made in their assessment against the European Foundation for Quality Management (EFQM) Excellence Model. To provide an evaluation of the EFQM method compared to peer auditing and accreditation concepts within health care. DESIGN: To indicate the EFQM method and scoring system and draft the process of self-assessment in health services organizitions. To refer to the experiences of German health care pioneers during their early assessments. RESULTS: Using the EFQM approach, an organizition can earn up to 1.000 points. More than 50% of German hospitals scored 200-300 points and not a single organizition achieved over 450 points. To make a comparison, the best score obtained in an industrial setting was between 650-750 points. In addition to the numbers, this report describes success factors and best practices of self-assessments, as well as limitations, barriers and lessons learned during the implementation phase. CONCLUSION: The Excellence Model is a systematic quality management approach to gain competitive advantage. It is non-governmental, non-financier driven, and generic enough to address health care issues. Having its foundation in industry, however, it is not specific enough to cover all areas relevant to health care. Integrating the management-smart method of self-assessment with clinical standards as delivered by peer auditing and accreditation systems generates the potential to deliver excellence in health care.

'Best clinical practice': assessment of processes of care and of outcomes in the US Military Health Services System.

The National Quality Management Program of the Military Health Services System of the United States has undertaken a series of projects whose objective is the active, on-going monitoring and improvement of the effectiveness and efficiency of the care provided to a broad population that encompasses troops on active duty, retirees and dependents. The analytic activities consist of (1) identification by clinical panels of conditions and procedures of interest; (2) collection of data from electronic repositories and from charts to characterize the patients, how they are managed, the clinical outcomes they experience, the resource costs their care entails, and, from questionnaires, their functional status and level of satisfaction, and (3) generation of 'report cards' that inform organizational units down to the level of the hospital of the characteristics of their patients, their practices, and the risk-adjusted outcomes they achieve. The patterns of care employed by the hospitals that obtain the best risk-adjusted outcomes and resource utilization ('best clinical practice') are identified and made known. In addition, (4) a systematic process of developing outcomes-based practice guidelines has been devised. It intent is to serve as a decision-support tool for clinicians. Initial estimates have been obtained of the probable consequences of the application of this tool to operative interventions in childbirth. Use of the tool would result in a higher occurrence of elective Caesarean sections, a reduced rate of emergency Caesarean sections and much lower use of forceps, with an overall improvement in outcomes and lower resource costs. This program is currently in the early phases of implementation. The two principal requirements for the immediate future are (1) education of the clinical and administrative communities in the use of the data and the decision-support tools and (2) evaluation of the consequences of the use of the data by the clinical and administrative communities.