RESUMEN
In this column the author presents his thoughts on quality improvement (QI) as it relates to health care. Although the story of QI, combined with a drastic urgency for change, may have created the current state in its misapplication in health care, it is the QI tenets put forth by Deming that can redeem its promise. In this way, QI is a fractal, similar in makeup and application on various scales. This speaks to the universality of Deming's four tenets; the same tenets used for a successful QI project need to be employed in building the QI capacity of an organization (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Asunto(s)
Mejoramiento de la Calidad/clasificación , Mejoramiento de la Calidad/tendencias , Salud de la Familia , Humanos , Innovación OrganizacionalRESUMEN
STUDY DESIGN: Retrospective review of prospectively-collected, multicenter adult spinal deformity (ASD) databases. OBJECTIVE: To apply artificial intelligence (AI)-based hierarchical clustering as a step toward a classification scheme that optimizes overall quality, value, and safety for ASD surgery. SUMMARY OF BACKGROUND DATA: Prior ASD classifications have focused on radiographic parameters associated with patient reported outcomes. Recent work suggests there are many other impactful preoperative data points. However, the ability to segregate patient patterns manually based on hundreds of data points is beyond practical application for surgeons. Unsupervised machine-based clustering of patient types alongside surgical options may simplify analysis of ASD patient types, procedures, and outcomes. METHODS: Two prospective cohorts were queried for surgical ASD patients with baseline, 1-year, and 2-year SRS-22/Oswestry Disability Index/SF-36v2 data. Two dendrograms were fitted, one with surgical features and one with patient characteristics. Both were built with Ward distances and optimized with the gap method. For each possible n patient cluster by m surgery, normalized 2-year improvement and major complication rates were computed. RESULTS: Five hundred-seventy patients were included. Three optimal patient types were identified: young with coronal plane deformity (YC, nâ=â195), older with prior spine surgeries (ORev, nâ=â157), and older without prior spine surgeries (OPrim, nâ=â218). Osteotomy type, instrumentation and interbody fusion were combined to define four surgical clusters. The intersection of patient-based and surgery-based clusters yielded 12 subgroups, with major complication rates ranging from 0% to 51.8% and 2-year normalized improvement ranging from -0.1% for SF36v2 MCS in cluster [1,3] to 100.2% for SRS self-image score in cluster [2,1]. CONCLUSION: Unsupervised hierarchical clustering can identify data patterns that may augment preoperative decision-making through construction of a 2-year risk-benefit grid. In addition to creating a novel AI-based ASD classification, pattern identification may facilitate treatment optimization by educating surgeons on which treatment patterns yield optimal improvement with lowest risk. LEVEL OF EVIDENCE: 4.
Asunto(s)
Inteligencia Artificial/clasificación , Procedimientos Neuroquirúrgicos/clasificación , Mejoramiento de la Calidad/clasificación , Enfermedades de la Columna Vertebral/clasificación , Enfermedades de la Columna Vertebral/cirugía , Adulto , Anciano , Análisis por Conglomerados , Bases de Datos Factuales/clasificación , Femenino , Humanos , Masculino , Persona de Mediana Edad , Procedimientos Neuroquirúrgicos/métodos , Osteotomía/clasificación , Osteotomía/métodos , Valor Predictivo de las Pruebas , Estudios Prospectivos , Estudios Retrospectivos , Enfermedades de la Columna Vertebral/diagnóstico , Adulto JovenRESUMEN
OBJECTIVE: To demonstrate an approach to measuring the cost and value of quality improvement (QI) implementation in local health departments (LHDs). DESIGN: We conducted cost estimation for 4 LHD QI projects and return-on-investment (ROI) analysis for 2 selected LHD QI projects. SETTING AND PARTICIPANTS: Four Nebraska LHDs varying in rurality and jurisdiction size. MAIN OUTCOME MEASURES: Total costs, unit costs, incremental cost-effectiveness ratios, and ROI. RESULTS: The 4 QI projects vary significantly in their cost estimates. Estimated ROI ratios for 2 QI projects predicted significant savings in health care utilization for respective program participants. A QI project focused on improving breastfeeding rates in WIC (women, infants, and children) clients had a predicted ROI ratio of 3230% and a QI project for improving participation in a Chronic Disease Self-Management Program would need only 34 new participants to have a positive ROI. CONCLUSIONS: We demonstrated how data can be collected and analyzed for cost estimation and ROI analysis to quantify the economic value of QI for LHDs. Our ROI analysis shows that QI initiatives have great potential to enhance the value of LHDs' public health services. A better understanding of the costs and value of QI will enable LHDs to appropriately allocate and utilize their limited resources for suitable QI initiatives.
Asunto(s)
Salud Pública/economía , Salud Pública/normas , Mejoramiento de la Calidad/clasificación , Mejoramiento de la Calidad/economía , Análisis Costo-Beneficio , Humanos , Gobierno Local , Nebraska , Salud Pública/tendencias , Mejoramiento de la Calidad/tendenciasRESUMEN
OBJECTIVE: The purpose of this article was to describe a methodology to identify continuous quality improvement (CQI) priorities for one state's Maternal, Infant, and Early Childhood Home Visiting program from among the 40 required constructs associated with 6 program benchmarks. The authors discuss how the methodology provided consensus on system CQI quality measure priorities and describe variation among the 3 service delivery models used within the state. DESIGN: Q-sort methodology was used by home visiting (HV) service delivery providers (home visitors) to prioritize HV quality measures for the overall state HV system as well as their service delivery model. RESULTS: There was general consensus overall and among the service delivery models on CQI quality measure priorities, although some variation was observed. Measures associated with Maternal, Infant, and Early Childhood Home Visiting benchmark 1, Improved Maternal and Newborn Health, and benchmark 3, Improvement in School Readiness and Achievement, were the highest ranked. CONCLUSIONS: The Q-sort exercise allowed home visitors an opportunity to examine priorities within their service delivery model as well as for the overall First Teacher HV system. Participants engaged in meaningful discussions regarding how and why they selected specific quality measures and developed a greater awareness and understanding of a systems approach to HV within the state. The Q-sort methodology presented in this article can easily be replicated by other states to identify CQI priorities at the local and state levels and can be used effectively in states that use a single HV service delivery model or those that implement multiple evidence-based models for HV service delivery.
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Prioridades en Salud , Visita Domiciliaria/tendencias , Mejoramiento de la Calidad/clasificación , Servicios de Salud del Niño/clasificación , Humanos , Lactante , Recién Nacido , Servicios de Salud Materna/clasificación , Q-Sort , Encuestas y CuestionariosRESUMEN
This column shares the best evidence-based strategies and innovative ideas on how to facilitate the learning of EBP principles and processes by clinicians as well as nursing and interprofessional students. Guidelines for submission are available at http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1741--6787.
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Práctica Clínica Basada en la Evidencia/clasificación , Proceso de Enfermería/estadística & datos numéricos , Mejoramiento de la Calidad/clasificación , Práctica Clínica Basada en la Evidencia/educación , Humanos , Proceso de Enfermería/tendencias , Investigación/clasificación , Investigación/educación , EstudiantesRESUMEN
In the early service transactions, quality of service (QoS) information was published by service provider which was not always true and credible. For better verification the trust of the QoS information was provided by the Web service. In this paper, the factual QoS running data are collected by our WS-QoS measurement tool; based on these objectivity data, an algorithm compares the difference of the offered and measured quality data of the service and gives the similarity, and then a reputation evaluation method computes the reputation level of the Web service based on the similarity. The initial implementation and experiment with three Web services' example show that this approach is feasible and these values can act as the references for subsequent consumers to select the service.
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Comportamiento del Consumidor , Minería de Datos/métodos , Difusión de la Información , Internet/clasificación , Mejoramiento de la Calidad/clasificación , Medios de Comunicación Sociales/clasificaciónRESUMEN
Word frequency analysis has not been fully explored as an input to public health taxonomy development. We used document analysis, expert review, and user-centered design to develop a taxonomy of public health quality improvement concepts for an online exchange of quality improvement work (www.phqix.org). Online entries were made searchable using a faceted search approach. To present the most relevant facets to users, we analyzed 334 published public health quality improvement documents using word frequency analysis to identify the most prevalent clusters of word meanings. We reviewed the highest-weighted concepts and identified their relationships to quality improvement details in our taxonomy. The meanings were mapped to items in our taxonomy, and presented in order of their weighted percentages in the data. Using this combination of methods, we developed and sorted concepts in the faceted search presentation so that relevant search criteria were accessible to users of the online exchange. Word frequency analysis may be a useful method to incorporate in other taxonomy development and presentationwhen relevant data is available.
Asunto(s)
Clasificación/métodos , Diccionarios como Asunto , Documentación/normas , Intercambio de Información en Salud , Mejoramiento de la Calidad/clasificación , Terminología como Asunto , Vocabulario Controlado , Uso Significativo/normas , Registro Médico Coordinado/normas , Procesamiento de Lenguaje Natural , Sistemas en Línea , Informática en Salud Pública/normas , Estados UnidosRESUMEN
CONTEXT: Quality improvement (QI) methods have been used for almost a decade in public health departments to increase effectiveness and efficiency. Although results are rapidly accumulating, the evidence for the science of improvement is shallow and limited. To advance the use and effectiveness of QI in public health, it is important to develop a science of improvement using practice-based research to build an evidence base for QI projects. OBJECTIVES: This purpose of this study is to advance the science of improvement in public health departments with 3 objectives: (1) establish a taxonomy of QI projects in public health, (2) categorize QI projects undertaken in health departments using the taxonomy, and (3) create an opportunity modes and effects analysis. DESIGN: This study is a qualitative analysis of archival data from 2 separate large databases consisting of 51 QI projects undertaken in public health departments over the last 5 years. SETTING AND PARTICIPANTS: The study involves 2 separate QI collaboratives. One includes Minnesota health departments; the other is a national collaborative. MAIN OUTCOME MEASURES: We propose a standardized case definition, common metrics, and a taxonomy of QI projects to begin building the evidence base for QI in public health and to advance the science of continuous quality improvement. RESULTS: All projects created an aim statement and used metrics while 53% used a specific QI model with an average of 3.25 QI techniques per project. Approximately 40% of the projects incorporated a process control methodology, and 60% of the projects identified the process from beginning to end, while 11 of 12 PHAB (Public Health Accreditation Board) domains were included. CONCLUSIONS: The findings provide a baseline for QI taxonomy to operationalize a science of improvement for public health departments.
Asunto(s)
Práctica de Salud Pública/normas , Mejoramiento de la Calidad/clasificación , Humanos , Minnesota , Mejoramiento de la Calidad/organización & administraciónRESUMEN
Quality improvement (QI) research is often hampered by the complexity of the systems and context in which QI is attempted. Better classification of QI can alleviate this problem and help to build generalisable knowledge.