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PubMed2002

An integrated care pathway for the last two days of life: Wales-wide benchmarking in palliative care.

Functional benchmarking assesses performance and practice across a broad range of settings and carries the potential to effect change in practice. An integrated care pathway (ICP) can assist in the benchmarking process, defining desired outcomes for specific patient groups over a designated time frame. Any variations to the agreed course of care are documented using the 'variance sheet'. This article describes the Wales-wide implementation of an ICP for the last two days of life. The project has enabled an ongoing centralized collection and analysis of variance sheets, which reflect the care of the dying patient in four different care settings crossing the voluntary and statutory sectors. Initial analysis of the first 500 variance sheets to be generated by the ICP for the last two days of life indicates that the management of pain, agitation, excess respiratory secretions and mouth care may be problematic. The same problems were experienced across acute, hospice, specialist inpatient units and community care. Closing the audit cycle involves incorporating the information from the variance analysis into clinical practice.

Analysis of Variance↗
PubMed2002

Improving Pap test turnaround time using external benchmark data and engineering process improvement tools.

Turnaround time for Papanicolaou (Pap) tests became an important service quality issue at our institution. We studied Pap test turnaround time using engineering process improvement tools and benchmarked turnaround time against data published as a College of American Pathologists Q-Probes study. An IDEF3 process map revealed the complexity of the Pap test process and the opportunities for process improvement. We used these data and the action-research method to initiate changes in cytopathology laboratory operations with the goal of reducing turnaround time. Before intervention, mean Pap test turnaround time was highly variable; during a 6-month period, monthly means ranged from 2.5 to 10.8 days. A cycle time study conducted over a 2-week period validated these data. After system improvements were implemented, the monthly mean turnaround time decreased and became more consistent, with 11 of 12 months having a mean turnaround time of 3 days or less (range, 1.5-3.9 days). Our study illustrates the value of publishing Q-Probes data for use as external benchmarks and the benefits of using tools from other disciplines to improve laboratory processes.

Benchmarking↗
PubMed2006

Benchmark for evaluating the quality of DNA sequencing: proposal from an international external quality assessment scheme.

BACKGROUND: In the past 15 years, clinical laboratory science has been transformed by the use of technologies that cross the traditional boundaries between laboratory disciplines. However, during this period, issues of quality have not always been given adequate attention. The European Molecular Genetics Quality Network (EMQN) has developed a novel external quality assessment scheme for evaluation of DNA sequencing. We report the results of an international survey of the quality of DNA sequencing among 64 laboratories from 21 countries. METHODS: Current practice for DNA sequence analysis was established by use of an online questionnaire. Participating laboratories were provided with 4 DNA samples of validated genotype. Evaluation of the results included assessing the quality of sequence data, variant genotypes, and mutation nomenclature. To accommodate variations in mutation nomenclature, variants indicated by participants were scored for compliance with 3 acceptable marking schemes. RESULTS: A total of 346 genotypes were analyzed. Of these, 19 (5%) genotyping errors were made. Of these, 10 (53%) were false-negative and 9 (47%) were false-positive results. A further 27 (8%) errors were made in naming mutations. Results were analyzed for 3 indicators of data quality: PHRED quality scores, Quality Read Length, and Quality Read Overlap. Most laboratories produced results of acceptable diagnostic quality as judged by these indicators. The results were used to calculate a consensus benchmark for DNA sequencing against which individual laboratories could rank their performance. CONCLUSIONS: We propose that the consensus benchmark can be used as a baseline against which the aggregate and individual laboratory standard of DNA sequencing may be tracked from year to year.

Benchmarking↗
PubMed2005

Evaluating the performance of an institution using an intensive care unit benchmark.

OBJECTIVES: To describe the performances of selected intensive care units (ICUs) in a single institution using the Acute Physiology and Chronic Health Evaluation (APACHE) III benchmark and to propose interventions that may improve performance. PATIENTS AND METHODS: In this retrospective study, we analyzed APACHE III data from critically ill patients admitted to ICUs at the Mayo Clinic in Rochester, Minn, between October 1994 and December 2003. We retrieved ICU performance measures based on first ICU day APACHE III values. Standardized ratios were defined as ratios of measured to predicted values. The primary performance measure was the standardized mortality ratio, and secondary performance measures were length of stay (LOS) ratios, low-risk monitor ICU admission rates, and ICU readmission rates. We calculated 95% confidence intervals (CIs) for each performance, graded as good, average, or poor. RESULTS: Among 46,381 patients admitted during the study period, 57.5% were in surgical ICUs, 24.8% in a medical ICU, and 17.7% in a surgical-medical ICU. Low-risk monitoring accounted for 37.2% of admissions. Hospital standardized mortality ratios (95% CI) were 0.95 (0.90-0.99), 0.86 (0.81-0.91), and 0.70 (0.66-0.74) for medical, multispecialty, and surgical ICUs, respectively. Hospital LOS ratios (95% CI) were 0.83 (0.81-0.85), 0.91 (0.88-0.93), and 0.99 (0.97-1.00) for medical, multispecialty, and surgical ICUs, respectively. The ICU readmission rate for each ICU was higher than the 6.7% reported in the medical literature. Performances were good in mortality, average to good in LOS, average in low-risk admission, and poor in ICU readmission. CONCLUSIONS: A national benchmarking database can highlight the strengths and weaknesses of ICUs. The performances of ICUs in a single institution may differ; therefore, the performance of each unit should be evaluated individually.

APACHE↗
PubMedDate not supplied

Making a difference to practice: clinical benchmarking. Part 1.

In the first of two articles, the authors describe how an internal clinical practice benchmarking group was established in Preston to compare and share examples of best practice. The aim was to ensure consistent high standards of care practice across the trust. Activity related to discharge planning and visiting is used here to illustrate the effectiveness of clinical practice benchmarking as a continuous quality improvement tool. The second article will appear in Nursing Standard on May 3.

Benchmarking↗
PubMedDate not supplied

Making a difference to practice: clinical benchmarking. Part 2.

In the second of two articles, the authors explore further the use of clinical practice benchmarking. In particular, practice related to improving nutritional care for patients, caring for patients with mental health needs and safely transferring critically ill patients is examined. The authors conclude by summarising the value of clinical practice benchmarking and how it made a difference to practice in their trust. The first article appeared in Nursing Standard last week.

Acute Disease↗
PubMedDate not supplied

Benchmarking: implementing the process in practice.

Government guidance and policy promotes the use of benchmarks as measures against which practice and care can be measured. This provides the motivation for practitioners to make changes to improve patient care. Adopting a systematic approach, practitioners can implement changes in practice quickly. The process requires motivation and communication between professionals of all disciplines. It provides a forum for sharing good practice and developing a support network. In this article the authors outline the initial steps taken by three PCGs in implementing the benchmarking process as they move towards primary care trust status.

Attitude of Health Personnel↗
PubMed1999

Benchmarking guide '99.

The right data: You can't benchmark without it. For our third annual guide to benchmarking under managed care, we turned to six prominent organizations. We've tapped their databases and creativity to help you gauge your performance on financial, operational, and service targets by degree of managed care penetration.

Benchmarking↗
PubMed1997

Cardiovascular benchmarking saves hospital nearly $897,000.

When Chattanooga, TN-based Erlanger Medical Center wanted to implement care paths for cardiac patients, its benchmarking team found it had to treat its cardiovascular surgeons as one unit rather than as individual practitioners. Best practices emerged as a combination of internal benchmarking and study of care paths from top performing hospitals in the region and nationally. When incorporated in Erlanger's new care plans, these practices netted savings of $896,000 through reduced stays, utilization, and standardization of supplies and processes.

Benchmarking↗
PubMed1998

How does your organization compare to nation's Top 100 benchmark hospitals?

Data Benchmarks: How does your organization stack up to the nation's top 100 hospitals? A new study of the country's top 100 hospitals that achieved great clinical and financial benchmarks reveals they are doing much more than reducing length of stay and shifting care to the outpatient setting. Other factors, including managed care penetration and location, play important roles, too. Here are the details, plus tips from a top performer.

Benchmarking↗
PubMed1998

Compare your Medicare utilization to these geographic, DRG-based benchmarks.

Data File: Medicare inpatient utilization benchmarks. Actuarial consultants Milliman & Robertson find 53% of Medicare inpatient bed days nationally are medically unnecessary or better spent in other health care settings. Here are benchmark data on inpatient admission and bed days per 1,000 members in optimally managed health systems.

Actuarial Analysis↗
PubMedDate not supplied

Value decision-making: staff benchmarking.

Benchmarking is becoming a more important management tool--especially for setting staff levels. MGMA data, from Cost Surveys and Physician Compensation and Productivity Surveys, can help group managers set realistic goals. However, if taken simply at face value, the data may not provide adequate specificity; it may not convey the quality and value staff provide a particular organization. This paper show how to use MGMA data to perform staff benchmarking.

Benchmarking↗
PubMed1995

Outcome-based management and public health: the Oregon Benchmarks experience.

Oregon is taking major steps toward monitoring health and nonhealth issues through the use of an outcome-based management approach called Benchmarks. Developed through a lengthy statewide consensus-building process, there are currently 272 goals, or Benchmarks, for the years 1995, 2000, and 2010, of which 54 are health related. Major effects on both the state and the local health departments include enhanced assessment activities, increased health planning, and improved collaboration both among health agencies and with other governmental and nongovernmental organizations.

Benchmarking↗
PubMedDate not supplied

Using benchmarking to support performance improvement efforts.

Successful benchmarking can create opportunities to improve performance through discovering best practices. The author offers an overview of benchmarking and best practices and how they apply to HIM--and ways to get started on your own.

Benchmarking↗
PubMedDate not supplied

Benchmarking hospital lengths of stay using histograms.

The authors demonstrated that length of stay histograms can provide considerably more benchmark information concerning hospital lengths of stay than numerical benchmarks. Examples of histograms described the complete distribution of hospital stays, as well as levels of outliers, rather than simple numerical averages. Gathering such data led to a clearer understanding of the significant LOS impact of certain DRG outliers in the two different hospitals in Syracuse, NY. Given that the other two communities represented, Seattle, Washington and San Diego, California, were more influenced by extensive managed care penetration, variations in histogram data were less in evidence there. Histograms were designed with bars to show LOS distributions at the 50th, 75th, and 90th percentiles for each of the above DRGs. The greatest variations could be shown when comparing the 1997 LOS data on the various DRGs at the two Syracuse hospitals. At both hospitals the presence of a large contingent of outliers (for different types of mostly medical patients) could be seen as the major factor in driving up their overall LOS.

Benchmarking↗
PubMed1999

Benchmarking in home health care: a collaborative approach.

Benchmarking outcome data and constructing "best practices" to meet patient care needs are emerging trends and new mandates on the horizon in home care. The Arizona Association for Home Care Continuous Quality Improvement Forum embarked on a journey to develop standards to define and monitor urinary tract infections in the home. A collaborative process among six home care agencies allowed for comparison of urinary tract infection rates and a beginning step toward establishing benchmarking standards in home care.

Arizona↗
PubMedDate not supplied

Benchmarking: the key to influencing physicians.

Managing physicians to achieve cost reductions can seem impossible, especially when managed care penetration is low. Physicians feel little pressure to change when asked merely to cut costs, especially when their boat is not rocking. But physicians will respond to benchmarking data on CPT-coded procedures that are directly comparable to their own practices. When surgeons see that others take less time to perform a procedure and/or use fewer and lower cost supplies, their competitive spirits are aroused. They become inquisitive about why this is so and then are eager to change by trying new methods and improving their techniques. Science is the key motivator, not savings. When benchmarking recommendations are implemented in a facility, better practice and substantial cost savings are the positive results.

Benchmarking↗
PubMed2000

Benchmarks for health expenditures, services and outcomes in Africa during the 1990s.

There is limited information on national health expenditures, services, and outcomes in African countries during the 1990s. We intend to make statistical information available for national level comparisons. National level data were collected from numerous international databases, and supplemented by national household surveys and World Bank expenditure reviews. The results were tabulated and analysed in an exploratory fashion to provide benchmarks for groupings of African countries and individual country comparison. There is wide variation in scale and outcome of health care spending between African countries, with poorer countries tending to do worse than wealthier ones. From 1990-96, the median annual per capita government expenditure on health was nearly US$ 6, but averaged US$ 3 in the lowest-income countries, compared to US$ 72 in middle-income countries. Similar trends were found for health services and outcomes. Results from individual countries (particularly Ethiopia, Ghana, Côte d'Ivoire and Gabon) are used to indicate how the data can be used to identify areas of improvement in health system performance. Serious gaps in data, particularly concerning private sector delivery and financing, health service utilization, equity and efficiency measures, hinder more effective health management. Nonetheless, the data are useful for providing benchmarks for performance and for crudely identifying problem areas in health systems for individual countries.

Africa↗