RESUMEN
PROBLEM: Need for improved sedation strategy for adults receiving ventilator support. DESIGN: Observational study of effect of introduction of guidelines to improve the doctors' and nurses' performance. The project was a prospective improvement and was part of a national quality improvement collaborative. BACKGROUND AND SETTING: A general mixed surgical intensive care unit in a university hospital; all doctors and nurses in the unit; all adult patients (>18 years) treated by intermittent positive pressure ventilation for more than 24 hours. KEY MEASURES FOR IMPROVEMENT: Reduction in patients' mean time on a ventilator and length of stay in intensive care over a period of 11 months; anonymous reporting of critical incidents; staff perceptions of ease and of consequences of changes. STRATEGIES FOR CHANGE: Multiple measures (protocol development, educational presentations, written guidelines, posters, flyers, emails, personal discussions, and continuous feedback) were tested, rapidly assessed, and adopted if beneficial. EFFECTS OF CHANGE: Mean ventilator time decreased by 2.1 days (95% confidence interval 0.7 to 3.6 days) from 7.4 days before intervention to 5.3 days after. Mean stay decreased by 1.0 day (-0.9 to 2.9 days) from 9.3 days to 8.3 days. No accidental extubations or other incidents were identified. LESSONS LEARNT: Relatively simple changes in sedation practice had significant effects on length of ventilator support. The change process was well received by the staff and increased their interest in identifying other areas for improvement.
Asunto(s)
Protocolos Clínicos , Utilización de Medicamentos/normas , Hipnóticos y Sedantes/administración & dosificación , Unidades de Cuidados Intensivos/normas , Ventilación con Presión Positiva Intermitente/estadística & datos numéricos , Adulto , Anciano , Hospitales Universitarios , Humanos , Tiempo de Internación , Persona de Mediana Edad , Noruega , Cuidados Posoperatorios/métodos , Cuidados Posoperatorios/normas , Guías de Práctica Clínica como Asunto , Garantía de la Calidad de Atención de Salud/métodosRESUMEN
Improvement of health care requires making changes in processes of care and service delivery. Although process performance is measured to determine if these changes are having the desired beneficial effects, this analysis is complicated by the existence of natural variation-that is, repeated measurements naturally yield different values and, even if nothing was done, a subsequent measurement might seem to indicate a better or worse performance. Traditional statistical analysis methods account for natural variation but require aggregation of measurements over time, which can delay decision making. Statistical process control (SPC) is a branch of statistics that combines rigorous time series analysis methods with graphical presentation of data, often yielding insights into the data more quickly and in a way more understandable to lay decision makers. SPC and its primary tool-the control chart-provide researchers and practitioners with a method of better understanding and communicating data from healthcare improvement efforts. This paper provides an overview of SPC and several practical examples of the healthcare applications of control charts.
Asunto(s)
Atención a la Salud/normas , Gestión de la Calidad Total/métodos , Toma de Decisiones en la Organización , Humanos , Innovación Organizacional , Satisfacción del Paciente , Esterilización , Infección de la Herida Quirúrgica/prevención & control , Análisis de SistemasRESUMEN
OBJECTIVE: To make measurable improvements in the quality and cost of neonatal intensive care using a multidisciplinary collaborative quality improvement model. DESIGN: Interventional study. Patient demographic and clinical information for infants with birth weight 501 to 1500 g was collected using the Vermont Oxford Network Database for January 1, 1994 to December 31, 1997. SETTING: Ten self-selected neonatal intensive care units (NICUs) received the intervention. They formed 2 subgroups (6 NICUs working on infection, 4 NICUs working on chronic lung disease). Sixty-six other NICUs served as a contemporaneous comparison group. PATIENTS: Infants with birth weight 501 to 1500 g born at or admitted within 28 days of birth between 1994 and 1997 to the 6 study NICUs in the infection group (n = 3063) and the 66 comparison NICUs (n = 21 509); infants with birth weight 501 to 1000 g at the 4 study NICUs in the chronic lung disease group (n = 738). INTERVENTIONS: NICUs formed multidisciplinary teams that worked together under the direction of a trained facilitator over a 3-year period beginning in January 1995. They received instruction in quality improvement, reviewed performance data, identified common improvement goals, and implemented "potentially better practices" developed through analysis of the processes of care, literature review, and site visits. MAIN OUTCOME MEASURES: The rates of infection after the third day of life with coagulase-negative staphylococcal or other bacterial pathogens for infants with birth weight 501 to 1500 g, and the rates of oxygen supplementation or death at 36 weeks' adjusted gestational age for infants with birth weight 501 to 1000 g. RESULTS: Between 1994 and 1996, the rate of infection with coagulase-negative staphylococcus decreased from 22.0% to 16.6% at the 6 project NICUs in the infection group; the rate of supplemental oxygen at 36 weeks' adjusted gestational age decreased from 43.5% to 31.5% at the 4 NICUs in the chronic lung disease group. There was heterogeneity in the effects among the NICUs in both project groups. The changes observed at the project NICUs for these outcomes were significantly larger than those observed at the 66 comparison NICUs over the 4-year period from 1994 to 1997. CONCLUSION: We conclude that multidisciplinary collaborative quality improvement has the potential to improve the outcomes of neonatal intensive care.
Asunto(s)
Infección Hospitalaria/epidemiología , Recién Nacido de muy Bajo Peso , Unidades de Cuidado Intensivo Neonatal/normas , Enfermedades Pulmonares/epidemiología , Garantía de la Calidad de Atención de Salud , Infecciones Estafilocócicas/epidemiología , Enfermedad Crónica , Infección Hospitalaria/terapia , Humanos , Incidencia , Recién Nacido , Unidades de Cuidado Intensivo Neonatal/economía , Enfermedades Pulmonares/terapia , Evaluación de Resultado en la Atención de Salud , Estudios Prospectivos , Infecciones Estafilocócicas/terapia , Tasa de Supervivencia , Vermont/epidemiologíaRESUMEN
OBJECTIVE: To make measurable improvements in the quality and cost of neonatal intensive care using a multidisciplinary collaborative quality improvement model. DESIGN: Interventional study. Data on treatment costs were collected for infants with birth weight 501 to 1500 g for the period of January 1, 1994 to December 31, 1997. Data on resources expended by hospitals to conduct this project were collected in a survey for the period January 1, 1995 to December 31, 1996. SETTING: Ten self-selected neonatal intensive care units (NICUs) received the intervention. They formed 2 subgroups (6 NICUs working on infection, 4 NICUs working on chronic lung disease). Nine other NICUs served as a contemporaneous comparison group. PATIENTS: Infants with birth weight 501 to 1500 g born at or admitted within 28 days of birth between 1994 and 1997 to the 6 study NICUs in the infection group (N = 2993) and the 9 comparison NICUs (N = 2203); infants with birth weight 501 to 1000 g at the 4 study NICUs in the chronic lung disease group (N = 663) and the 9 comparison NICUs (N = 1007). INTERVENTIONS: NICUs formed multidisciplinary teams which worked together to undertake a collaborative quality improvement effort between January 1995 and December 1996. They received instruction in quality improvement, reviewed performance data, identified common improvement goals, and implemented "potentially better practices" developed through analysis of the processes of care, literature review, and site visits. MAIN OUTCOME MEASURES: Treatment cost per infant is the primary economic outcome measure. In addition, the resources spent by hospitals in undertaking the collaborative quality improvement effort were determined. RESULTS: Between 1994 and 1996, the median treatment cost per infant with birth weight 501 to 1500 g at the 6 project NICUs in the infection group decreased from $57 606 to $46 674 (a statistical decline); at the 4 chronic lung disease hospitals, for infants with birth weights 501 to 1000 g, it decreased from $85 959 to $77 250. Treatment costs at hospitals in the control group rose over the same period. There was heterogeneity in the effects among the NICUs in both project groups. Cost savings were maintained in the year following the intervention. On average, hospitals spent $68 206 in resources to undertake the collaborative quality improvement effort between 1995 and 1996. Two thirds of these costs were incurred in the first year, with the remaining third in the second year. The average savings per hospital in patient care costs for very low birth weight infants in the infection group was $2.3 million in the post-intervention year (1996). There was considerable heterogeneity in the cost savings across hospitals associated with participation in the collaborative quality improvement project. CONCLUSION: Cost savings may be achieved as a result of collaborative quality improvement efforts and when they occur, they appear to be sustainable, at least in the short run. In high-cost patient populations, such as infants with very low birth weights, cost savings can quickly offset institutional expenditures for quality improvement efforts.
Asunto(s)
Recién Nacido de muy Bajo Peso , Unidades de Cuidado Intensivo Neonatal/economía , Unidades de Cuidado Intensivo Neonatal/normas , Garantía de la Calidad de Atención de Salud/economía , Enfermedad Crónica , Control de Costos , Femenino , Investigación sobre Servicios de Salud , Costos de Hospital , Humanos , Recién Nacido , Infecciones/terapia , Tiempo de Internación/economía , Enfermedades Pulmonares/terapia , Masculino , Modelos Económicos , Tasa de Supervivencia , Estados UnidosRESUMEN
Mr. Plsek is an independent consultant with 20 years of diverse experience in the field of quality management. He has written numerous articles, presented papers at a variety of conferences, and led seminars for more than 10,000 managers and executives in diverse companies. His seminar, "Creative Thinking for Serious People," has taught people that there can be a serious approach to innovation. He also has served in a variety of engineering and management positions at AT&T and Bell Laboratories and is a senior fellow with the Institute for Healthcare Improvement. Mr. Plsek has BS and MS degrees in electrical engineering from Texas A & M University and the Polytechnic Institute of New York (Brooklyn).
Asunto(s)
Creatividad , Administración de los Servicios de Salud/normas , Innovación Organizacional , Gestión de la Calidad Total , Humanos , MinnesotaRESUMEN
This article surveys the methods and tools of quality improvement used today in health care. Specifically, we describe how clinicians can use these methods to impact the clinical practice of medicine. Improvement teams from a variety of health care organizations have reported the successful use of basic methods such as group work, flowcharting, data collection, and graphical data analysis. In addition to these incremental, problem-solving methods borrowed from the industrial practice of improvement, we have also seen the use of specific process design methods in health care applications such as care path development. The pace of change in health care has also led to the practical development of newer methods for rapid cycle improvement. We will review the basic approach behind these methods and illustrate key elements such as the ideas of change concepts and small-scale tests of change. Unfortunately, whereas these methods have been very successful and highly appealing to improvement practitioners, they may also have inadvertently widened a gulf between these practitioners and traditional health-services and clinical researchers. We offer an assessment of this issue and suggest ways to narrow the communication gap. Measurement has also traditionally been a part of the thinking about quality assurance and improvement in health care. We review the new philosophy of measurement that has emerged from recent improvement thinking and describe the use of control charts in clinical improvement. Benchmarking and multiorganizational collaboratives are more recent innovations in the ways we approach improvement in health care. These efforts go beyond simple measurement and explore the why and how associated with the widespread variation in performance in health care. We explore a variety of health care examples to illustrate these methods and the lessons learned in their use. We conclude the article with an overview of four habits that we believe are essential for health care organizations and individual clinicians to adopt to bring about real improvement in the clinical practice of medicine. These are the habits for: 1) viewing clinical practice as a process; 2) evidence-based practice; 3) collaborative learning; and 4) change.
Asunto(s)
Medicina Clínica/organización & administración , Medicina Clínica/normas , Innovación Organizacional , Gestión de la Calidad Total/métodos , Conducta Cooperativa , Recolección de Datos/métodos , Modelos Organizacionales , Técnicas de Planificación , Evaluación de Procesos, Atención de SaludRESUMEN
How can physician executives interested in promoting change be more effective at the task? This article explores how to create an attraction towards change, as opposed to viewing change as overcoming resistance. Learning to recognize naturally occurring change, identify attractors, explore the rationality of others' points of view, and reduce risk are clear and constructive insights from research and emerging systems science. Other ideas to consider are: Understand the issues of those you wish to change, create changes that are "exothermic," produce system changes, accept responsibility, learn from failed efforts, and focus on building relationships of trust.
Asunto(s)
Difusión de Innovaciones , Innovación Organizacional , Conducta , Humanos , Relaciones Interprofesionales , Liderazgo , Motivación , Ejecutivos Médicos , Administración de la Práctica Médica/organización & administración , Cambio SocialRESUMEN
The paradigm of modern quality management is in wide use in health care. Although much of the initial effort in health care has focused on improving service, administrative, and support processes, many organizations are also using these concepts to improve clinical care. The analysis of data on clinical outcomes has undoubtedly led to many local improvements, but such analysis is inevitably limited by three issues: small samples, lack of detailed knowledge of what others are doing, and paradigm paralysis. These issues can be partially overcome when multiple health care organizations work together on focused clinical quality improvement efforts. Through the use of multiorganizational collaborative groups, literature reviews, expert panels, best-practice conferences, multiorganizational databases, and bench-marking groups, organizations can effectively pool data and learn from the many natural experiments constantly underway in the health care community. This article outlines the key concepts behind such collaborative improvement efforts and describes pioneering work in the application of these techniques in health care. A better understanding and wider use of collaborative improvement efforts may lead to dramatic breakthroughs in clinical outcomes in the coming years.
Asunto(s)
Relaciones Interinstitucionales , Gestión de la Calidad Total/organización & administración , Instituciones de Salud , Humanos , Modelos Organizacionales , Evaluación de Procesos y Resultados en Atención de Salud , Valores de Referencia , Proyectos de Investigación , Estados UnidosAsunto(s)
Prestación Integrada de Atención de Salud/normas , Evaluación de Procesos, Atención de Salud/organización & administración , Prestación Integrada de Atención de Salud/organización & administración , Necesidades y Demandas de Servicios de Salud , Participación en las Decisiones , Modelos Organizacionales , Garantía de la Calidad de Atención de Salud , Análisis de Sistemas , Análisis y Desempeño de Tareas , Estados UnidosRESUMEN
The science of quality management is an eclectic collection of concepts and methods primarily borrowed from other fields. Techniques roughly fall into three categories involving quality improvement, planning, and measurement. Improvement techniques include models to guide team-based efforts, tools for process description, and tools for data analysis. These methods are the most visible artifacts of CQI efforts in health care organizations today. Less widely known, but equally powerful, are the techniques of quality planning. There are models to guide both process design and strategic planning, methods for identifying customer needs, and tools to support these efforts. Finally, while measurement is a traditionally well-developed area in health care, industrial quality management science broadens our outlook about what is important to measure. It also provides the technique of benchmarking, which suggests that we look beyond our own organization when we measure performance.
Asunto(s)
Administración Hospitalaria/normas , Modelos Organizacionales , Gestión de la Calidad Total/organización & administración , Presentación de Datos , Interpretación Estadística de Datos , Documentación , Control de Formularios y Registros , Investigación sobre Servicios de Salud/métodos , Participación en las Decisiones , Técnicas de Planificación , Estados UnidosRESUMEN
While data collection is fundamental to any scientifically based effort, health care improvement teams often report that it is one of the most frustrating aspects of their work. Groups that do succeed in gathering some data can also sometimes find that the data they have worked so hard to obtain does not really help them or deepen their understanding of the process. The root of many of these problems can be traced to insufficient planning for data collection and to fundamental misunderstandings about the eventual goals of such studies. In this tutorial, we will explore a systematic way of thinking through the planning for data collection that will result in a higher probability of generating useful information.
Asunto(s)
Recolección de Datos/métodos , Evaluación de Procesos y Resultados en Atención de Salud/organización & administración , Participación en las Decisiones , Técnicas de Planificación , Desarrollo de Programa/métodos , Proyectos de InvestigaciónRESUMEN
Part II of this three-part tutorial focuses on the logistics of data collection. The author presents a checklist of things to consider when planning the details of a data collection effort; touches on the topics of bias and stratification; discusses examples of popular data collection methods; and points out some common pitfalls in data collection, offering practical tips on how to avoid them.
Asunto(s)
Recolección de Datos/métodos , Calidad de la Atención de Salud/normas , Estudios de Tiempo y Movimiento , Educación Continua , Sistemas de Información Administrativa , Servicio de Farmacia en Hospital/estadística & datos numéricos , Técnicas de Planificación , Calidad de la Atención de Salud/estadística & datos numéricos , Diseño de Software , Estados UnidosRESUMEN
While we recognize the need for creative approaches to nagging problems and new opportunities, generating practical new ideas is often a challenge. Many people have convinced themselves that they are simply not creative thinkers; they can only marvel at those who seem to possess "the gift." However, research over the last few decades in the field of cognitive science has indicated that the capacity for creative thought is a basic mental ability that we all possess. We will review these new theories about creativity and discuss actions that we can take to direct our thoughts towards novel ends.
Asunto(s)
Creatividad , Innovación Organizacional , Evaluación de Procesos, Atención de Salud/organización & administración , Humanos , Modelos Psicológicos , Solución de Problemas , Desarrollo de Personal , Estados UnidosRESUMEN
There is no simple answer to the question, "how large a sample should I take?" Sample size depends on various data collection design details and on how we intend to use the data in future decision making. But with careful thought and some basic statistical knowledge, even nonstatisticians can determine the appropriate sample size for achieving useful results from data collection efforts.
Asunto(s)
Recolección de Datos/estadística & datos numéricos , Investigación sobre Servicios de Salud/normas , Muestreo , Recolección de Datos/métodos , Toma de Decisiones , Investigación sobre Servicios de Salud/métodos , Humanos , Modelos Estadísticos , Sesgo de Selección , Estados UnidosRESUMEN
Quality improvement teams function best when all team members agree to a unifying model to guide their effort. Unfortunately, there are many quality improvement project models to choose from in the literature. And while it seems that they are quite different, all effective models are built on the same conceptual base. In this tutorial, we will explain these basic concepts and then show how to use them to examine and enhance our understanding of some widely used models. We will also discuss the need for these models, describe how teams can learn from projects that followed different models, and provide guidance to organizations that are choosing one.
Asunto(s)
Participación en las Decisiones/organización & administración , Modelos Organizacionales , Gestión de la Calidad Total/organización & administración , Desarrollo de Programa/métodos , Evaluación de Programas y Proyectos de Salud , Gestión de la Calidad Total/normas , Estados UnidosRESUMEN
While most leaders recognize the value of good planning, most lack the experience and methods to do it systematically. As a result, group planning efforts are often frustrating, generating plans that are shallow and poorly understood by those who must carry them out. The seven management and planning tools are a set of easy to use, systematic methods from the quality management literature that can help planning teams in the same way that the familiar quality improvement tools like flow charts and histograms aid problem-solving teams.
Asunto(s)
Administración Hospitalaria/métodos , Participación en las Decisiones/organización & administración , Técnicas de Planificación , Gestión de la Calidad Total/organización & administración , Toma de Decisiones en la Organización , Liderazgo , Modelos Organizacionales , Instituciones de Cuidados Especializados de Enfermería/organización & administración , Estados UnidosRESUMEN
Variation in outcome is a natural result from any complex biological or production process. Unfortunately, this variation can cloud our decision making and lead us to take inappropriate action. The control chart is a basic quality management tool that helps managers and clinicians make statistically sound decisions when analyzing outcome data from processes. In this tutorial, we will illustrate the problems inherent in taking action based on data that displays variation. We will then develop the statistical foundation for control charts and show an example of its use to analyze data from a pharmacy process.
Asunto(s)
Interpretación Estadística de Datos , Evaluación de Procesos y Resultados en Atención de Salud/estadística & datos numéricos , Comportamiento del Consumidor/estadística & datos numéricos , Recolección de Datos/métodos , Toma de Decisiones en la Organización , Métodos , Servicios Farmacéuticos/normas , Solución de Problemas , Factores de Tiempo , Listas de EsperaRESUMEN
The lack of consistency in the performance of the processes which implement clinical decisions is an important problem in ambulatory care. Since delayed or neglected actions in patient care may have serious consequences, we studied the use of industrial quality management techniques to determine where three clinical processes could be improved. These quantitative and graphical tools were useful in showing that in some processes, the failure rate could be as high as 33%. However, lack of readily available process data prevented a full analysis of the extent of the failures, so specific suggestions for improvement could not be made. Medical informatics and management specialists have an important role in designing enhanced medical information systems with which to examine and improve patient care processes. This new generation of MIS's should include order entry systems with flags for selected transactions, audit trails for all automated processes, functional integration of the separate departmental information systems, and enhanced communications features.