Quality management in health care (Qual Manag Health Care )


This peer-reviewed quarterly journal provides a forum to explore the theoretical, technical, and strategic elements of total quality management in health care. Each issue of Quality Management in Health Care (QMHC) features a timely symposium that addresses a key issue in health care quality management. Also included in each issue is an in-depth interview with a key individual in health care quality management, an educational tutorial on basic quality management tools and processes, an information clearinghouse to encourage informal communication among those involved in the field of health care quality management, and a reference center that reviews books, journal articles, seminars, and videos of interest.

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    Quality management in health care, QMHC
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Publications in this journal

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    Quality management in health care 06/2009; 18(3):149-50.
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    ABSTRACT: Following the landmark Leuven study in 2001, health care organizations implemented intensive insulin therapy (IIT) as the standard of care for critically ill patients. However, a recent meta-analysis showed no mortality benefit and an increased safety risk for patients treated with IIT. IIT affects labor and capital decisions related to nurses, physicians, pharmacists, managers, laboratory personnel, and informatics staff. The expenditure of labor and capital to provide IIT without corresponding outcome improvements suggests the adoption of IIT produces inefficiency in hospital. In sociology and organizational studies, the tendency for organizations to become more similar without necessarily becoming more efficient is called normalfont institutional isomorphism. Institutional isomorphism examines the pressure that organizations encounter from peers, regulators, and professions through mimetic, coercive, and normative mechanisms, respectively. To enhance their prospects of survival, organizations establish and maintain legitimacy by adopting socially acceptable approaches to work endorsed by successful peer organizations, regulatory agencies, and professional societies. ORGANIZATIONAL INFLUENCE IN THE ADOPTION OF IIT: This paper describes how organizational influence-through the Leuven study, the Joint Commission, and professional organizations-played a role in the widespread adoption of IIT. Divergence from institutionalized forms may explain variation in IIT studies following Leuven. Health care researchers practitioners, and managers should consider organizational influence when implementing large-scale clinical activities.
    Quality management in health care 01/2009; 18(2):115-9.
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    ABSTRACT: Quality improvement in health care organizations requires structural reorganization and system reform and the development of an appropriate organizational "culture." In 2007, the Division of Quality and Excellence in Civil Service in Israel developed a concept to improve quality management in governmental institutions throughout the country. To put this strategy into practice, Western Galilee Hospital, a governmental hospital, in northern Israel, developed a plan to advance the quality management system where each department and unit is autonomously responsible for its own quality and excellence. Since the hospital has been certificated by ISO 9001 for more than 10 years (the only hospital in Israel to have this certificate), the main challenge now is to improve the quality and excellence system in every department. The aim of this article is to describe the implementation of a comprehensive program designed to raise the ability of managers and workers in Western Galilee Hospital in addressing all of the government's requirements for quality and excellence in service in Israel.
    Quality management in health care 01/2009; 18(2):141-5.
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    ABSTRACT: Medical students, nursing students, and other health care professionals in training were integrated with health care workers on interprofessional quality improvement (QI) teams at our academic health center. Teams received training in QI, accompanied by expert QI mentoring, with dual goals of increasing expertise in improvement while improving care. Eighty-six learners and health system workers participated in 12 improvement teams in 2 years. Upon completion of the training, participants expressed that the program enhanced QI and teamwork skills and increased understanding of other health care professions. At the end of the program, fourth-year medical students showed greater ability to apply QI skills, as measured by the QI Knowledge Assessment Tool than did control students who did not participate in the program (P < .0001 in 2006-2007 and P < .0005 in 2007-2008). Many teams were successful in improving care processes. The design of "learning QI by doing," accompanied by just-in-time training and ongoing expert mentoring in QI, was identified by faculty as the most important factor contributing to success. This model successfully improved application of QI skills by learners while improving care within our academic health center. Testing of the model at other academic health centers and in other training environments is warranted.
    Quality management in health care 01/2009; 18(3):194-201.
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    ABSTRACT: To create an index that would serve as a simple tool to measure the quality of hospital care by race and ethnicity. Following extensive review of existing disparities indices, we created a disparities quality index (DQI) designed to easily measure differences in the quality of care hospitals deliver to different populations. The DQI uses performance data already collected by virtually all hospitals. It highlights areas where there are large numbers of patients in a specific population receiving potentially lower-quality care. Data were collected from 2 acute care hospitals that participated in a multihospital collaborative. We applied the DQI to 2 hospitals' quality data, specifically to their performance on the Hospital Quality Alliance measure for patients with heart failure who were receiving angiotensin-converting enzyme inhibitor or angiotensin receptor blocker. The DQI was simple to apply and was able to measure differences in the care of different ethnic groups. It also detected changes in disparities over time. The DQI can help hospitals and other providers focus on the domain of equity in their quality-improvement efforts. Further testing is required to determine its applicability for community-wide equity projects.
    Quality management in health care 01/2009; 18(2):84-90.
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    ABSTRACT: The Centers for Disease Control and Prevention (CDC) defines influenza-like illness (ILI) for its sentinel providers as fever (temperature > or =100.5 degrees F or 37.8 degrees C) and a cough and/or a sore throat in the absence of a known cause other than influenza. For electronic disease surveillance systems, classifying ILI with clinical data that identify only individual aspects of the case definition may add excessive levels of unwanted noise to the system; however, the capability to analyze a patient's body temperature along with other available clinical data (International Classification of Diseases, Ninth Revision codes) could improve diagnostic precision and more accurately classify cases of ILI in a syndromic surveillance system. Developing Boolean algorithms to properly classify true cases of influenza plays an important role toward understanding accurate levels of disease in a community and can also be a key tool for allocating urgent prophylaxis such as antiviral medications during severe outbreaks and pandemics. Results for this study show that elevated body temperature was 40% efficient in correctly predicting laboratory-positive confirmations of influenza (sensitivity) but at the same time was 76% efficient in ruling out influenza (specificity) in the group of sampled members who were tested for influenza.
    Quality management in health care 01/2009; 18(2):91-102.
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    ABSTRACT: The Institute of Medicine called for the integration of interprofessional education (IPE) into health professions curricula, in order to improve health care quality. In response, we developed, implemented, and evaluated a campus wide IPE program, shifting from traditional educational silos to greater collaboration. Students (155) and faculty (30) from 6 academic programs (nursing, medicine, public health, allied health, dentistry, and pharmacy) engaged with a university hospital partner to deliver this program. The content addressed principles of IPE, teamwork development and 2 common quality care problems: hospital-acquired infections and communication errors. Pre-/post-surveys, the Readiness for Interprofessional Learning Scale, and the Interprofessional Education Perception Scale, were used for descriptive assessment of student learning. Students demonstrated increased understanding of health care quality and interprofessional teamwork principles and reported positive attitudes toward shared learning. While responses to the Readiness for Interprofessional Learning Scale grew more positive after the program, scores on the Interprofessional Education Perception Scale were more homogeneous. Both students and faculty highly evaluated the experience. This program was a first step in preparing individuals for collaborative learning, fostering awareness and enthusiasm for IPE among students and faculty, and demonstrating the feasibility of overcoming common barriers to IPE such as schedule coordination and faculty buy-in.
    Quality management in health care 01/2009; 18(3):165-73.
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    ABSTRACT: In response to the Institute of Medicine challenge to improve patient safety and quality of care, an office directing patient safety/quality of care at an academic medical center and faculty from health professions schools collaborated on design, delivery, and evaluation of an interprofessional student curriculum on patient safety, quality, and teamwork. Annually for 6 years, second-year medical students, senior baccalaureate nursing students, second-year masters in health administration students, and junior baccalaureate respiratory therapy students participated. A pre-/postsurvey assessing students' attitudes about quality, safety, and teamwork was developed and modified to reflect course revisions. Survey items were grouped into 1 of the 6 subscales: human fallibility, disclosure, teamwork/communication, error reporting, systems of care, and curricular time spent with other professionals. At pretest, there were significant professional group differences in all the 6 subscales. At completion, differences in 4 subscales were resolved with the exception of human fallibility (P < .001) and curricular time spent together (P < .001). Interprofessional exercises within our curriculum mediated most differences among student groups. As more interprofessional curricular experiences are designed, examining baseline group differences is essential to optimize learning outcomes.
    Quality management in health care 01/2009; 18(3):182-93.
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    ABSTRACT: In response to growing concerns about patient safety, many hospitals are implementing rapid response teams (RRTs). Although the staff nurse plays a critical role in recognizing the need for the RRT and initiating the call, little is known about actions of staff nurses in relation to the RRT. The purpose of this study was to examine relationships between nurse educational preparation, years of experience, degree of engagement, and the RRT call status (independent vs dependent). Nurse engagement was measured by the Manifestations of Early Recognition Scale. A descriptive correlational design was used. The sample comprised 75 staff nurses at an academic medical center who cared for patients for whom the RRT was called. Educational level and nursing experience were independent predictors of call status, after controlling for effects of other independent variables. Independent callers were almost 5 times more likely to have a BSN degree, and almost 4 times more likely to have more than 3 years of experience, than did RNs who called because someone asked them to call. High levels of engagement were also significantly associated with call status, but after controlling for educational level and nursing experience, the relationship was not significant. This study has implications for clinicians and managers in health care facilities that rely on RRTs.
    Quality management in health care 01/2009; 18(1):40-7.
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    ABSTRACT: The ways in which tailored interventions foster sustained improvement in the quality of health care delivery across different practice settings are not well understood. Using the empirically developed Practice Change Model (PCM), we identify and describe assessment and tailoring activities with potential to enhance the fit between proposed interventions and practice settings. We obtained quantitative and qualitative data from 2 quality improvement trials conducted in diverse primary care practices in northeast Ohio. A multidisciplinary team used a PCM-based template to identify features of practice assessment and tailoring associated with practices' willingness and ability to change. Our results suggest that intervention tailoring requires assessment of key stakeholders' motivations, external influences, resources and opportunities for change, and the interactions between these factors. Using this information, intervention tailoring then includes seeking and working with key stakeholders, building assets, providing options, keeping change processes flexible, offering feedback, providing exposure to scientific evidence, facilitating group processes, involving new partners, brainstorming, using stories/play acting/humor, assuming a consultant role, reframing, moving meetings off-site, and stepping back or pausing. A model-driven approach guiding practice assessment enables tailored responses to the unique and emerging conditions that distinguish health care practices and influence implementation of quality management interventions.
    Quality management in health care 01/2009; 18(4):268-77.
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    ABSTRACT: Capacity for change, or the ability and willingness to undertake change, is an organizational characteristic with potential to foster quality management in health care. We report on the development and psychometric properties of a quantitative measure of capacity for change for use in primary care settings. Following review of previous conceptual and empirical studies, we generated 117 items that assessed organizational structure, climate, and culture. Using information from direct observation and key informant interviews, a research team member rated these items for 15 primary care practices engaged in a quality improvement intervention. Distributional statistics, pairwise correlation analysis, Rasch modeling, and item content review guided item reduction and instrument finalization. Reliability and convergent validity were assessed. Ninety-two items were removed because of limited response distributions and redundancy or because of poor Rasch model fit. The final instrument comprising 25 items had excellent reliability (alpha = .94). A Rasch model-derived capacity for change score correlated well with an independently determined, qualitatively derived summary assessment of each practice's capacity for change (rhoS = 0.82), suggesting good convergent validity. We describe a new instrument for quantifying organizational capacity for change in primary care settings. The ability to quantify capacity for change may enable better recognition of practices likely to be successful in their change efforts and those first requiring capacity building prior to change interventions.
    Quality management in health care 01/2009; 18(4):278-84.
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    ABSTRACT: To improve processes in hospitals, a case study was conducted at a German university hospital, which consists of more than 30 clinics and institutes on a large campus. The case study focused on the analysis of the patient flow and of machine utilization in the radiology department. Radiological devices are spread over the campus and located in different buildings. Patients with restricted mobility have to be transported by a vehicle transportation service across the campus. However, a vehicle transport can considerably influence the patients' punctual arrival to their appointments. The observations of the case study showed that the current organization of the radiology department results in high patient waiting times and machine idle times. The university hospital is planning to conduct significant organizational changes, especially with regard to the organization of the radiology department. This case study was conducted to support the planning processes of the clinic and to reveal and estimate optimization potential. To analyze the patient flow, a discrete event multicriteria simulation model was designed and implemented. By modeling different scenarios, it was possible to easily compare and assess distinct alternatives. This led to improved machine utilization and reduced waiting times.
    Quality management in health care 01/2009; 18(4):326-38.
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    ABSTRACT: Clinical guidelines call for more exercise than many patients are willing to undertake. More modest goals are more acceptable but may not improve overall self-rated health (SRH) in primary care patients. Furthermore, whether exercise should be measured in minutes per week, times per week, or both is unclear. A random sample of 939 primary care patients met criteria for the study. Exercise was measured in self-reported minutes and times per week. Multiple logistic regression analysis was used to test for the independent effects of minutes and times per week of exercise on SRH in primary care patients. Exercising 1 to 150 minutes per week was independently related to good SRH (odds ratio = 3.41, confidence interval = 1.73-6.73) as was exercising 151 to 300 minutes per week (odds ratio = 4.13, confidence interval = 1.45-11.71). The number of exercise times per week was not significant. In our sample of relatively healthy primary care patients, exercising 1 to 300 minutes per week appears to promote good SRH.
    Quality management in health care 01/2009; 18(2):135-40.
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    ABSTRACT: We originally examined the effectiveness of strategies, proven successful in improving appointment availability in primary care, at a large tertiary-care academic medical center. We then sought to describe the reasons for the initial failure of these strategies. Clinics participating in an access improvement initiative were matched to control clinics. Intervention clinics used a variety of techniques to improve access. Run charts were used to determine the impact of the interventions on appointment availability. Linear models, control charts, and other graphic displays were used to understand the relationship among supply, demand, and appointment availability. Access did not improve in intervention clinics. Neither a linear models approach nor the use of control charts resulted in a simple tool to help clinics better understand the relationship among supply, demand, and days to third next available appointment. However, the development of a single clinic chart that incorporated supply and demand, plus estimates of future supply and demand, made it clear that current supply would not be able to meet demand. This helped teams focus their efforts on improving supply. Use of detailed data-based tools to guide choices of interventions, coupled with new and explicit institutional expectations for physician attendance at clinics, appears to be a promising strategy for enhancing access.
    Quality management in health care 09/2008; 17(4):320-9.
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    ABSTRACT: A previously published analysis of an interesting dataset consisting of time intervals between medication errors is replicated and some errors in the original analysis are discussed. The dataset is then analyzed using well-known methods from the field of statistical process control. The results and conclusions of the analysis are not consistent with those of the original analysis. The need for future collaborations between health care and quality management professionals are discussed.
    Quality management in health care 01/2008; 17(4):349-52.
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    ABSTRACT: Accredited medical care organizations are expected to assess pain levels in their patients. Appropriate responses to high pain levels have not been specified. This study was a retrospective analysis of information abstracted from medical records of 673 adult patients utilizing family medicine. Pain was measured using a scale ranging from 0 to 10. Scores of 7 and above were judged to represent high levels of pain. Multiple logistic regression was used to test the relationship between body mass index (BMI) and general pain, after adjustment for co-morbidity, physical limitations, and demographic characteristics. Multiple logistic regression analysis revealed that, in comparison with patients with normal body mass, patients with BMI greater than 35 had higher odds of experiencing pain scored 7 or over after adjusting for physical limitations, co-morbidity, age, and gender (adjusted odds ratio [AOR] = 1.89, P = .03). Odds ratios also were significant for subjects with any (vs none) physical limitations (AOR = 1.91, P = .01) and for men relative to women (AOR = 0.65, P = .04). co-morbidity, common diagnoses, and moderate BMI scores were not independently related to high pain levels. In our sample of patients utilizing family medicine, BMI greater than 35 is a risk factor for elevated pain scores. This relationship appears to be independent of orthopedic consequences of obesity. Referral to weight management programs might be useful as a quality indicator for obese adults reporting high levels of general pain.
    Quality management in health care 01/2008; 17(3):204-9.
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    ABSTRACT: Given the important functions that hospital quality departments perform or support (including regulatory readiness, team facilitation, and submission of data for mandatory reporting), insuring sufficient resources in the quality department to support those functions is an important task for hospital leaders. Yet, currently there is little information available to assist leaders in determining optimal staffing for hospital quality departments. This article reports the results of several benchmarking surveys conducted to examine staffing levels and functions for quality departments.
    Quality management in health care 01/2008; 17(4):341-8.