Quality Management in Health Care最新文献

Background and objectives: Developing research capacity and supporting research engagement among health professionals are essential parts of bridging the evidence-to-practice gap. The objective of this study was to describe and assess the impact of research seed funding in promoting the engagement of nursing and allied health professionals in leading practice-based research studies within a health care organization.

Methods: An impact assessment survey was administered to health professional grant recipients (n = 30) to collect self-reported observations of changes related to clinical practice, patient care, and organizational priorities as a result of the funded research projects. The electronic survey was developed in collaboration with an interprofessional advisory committee and contained 23 closed- and open-ended questions. Survey data were analyzed descriptively, and responses to open-ended survey questions were used to characterize the funded research activities and the perceived successes and challenges experienced by the research teams.

Results: A large proportion of health professional grant recipients reported observing impact from their research studies on clinical practice, organizational priorities, and external networks. The grant funds were used to carry out knowledge dissemination activities such as conference presentations, publications, and sharing findings at professional meetings and networks. The majority of grant expenditures were used for research personnel, and the most common challenge to conducting research was related to the need for protected research time. Most grant recipients were interested in participating in another grant-funded research project in the future.

Conclusion: Organizational funding and support for research led by health professionals have potential impact on clinical practice, patient care, and organizational priorities. This study provides evidence to support the value of investing in continued and expanded research funding programs for health professionals.

Background and objectives: Clinician workload is a key contributor to burnout and well-being as well as overtime and staff shortages, particularly in the primary care setting. Appointment volume is primarily driven by the size of patient panels assigned to clinicians. Thus, finding the most appropriate panel size for each clinician is essential to optimization of patient care.

Methods: One year of appointment and panel data from the Department of Family Medicine were used to model the optimal panel size. The data consisted of 82 881 patients and 105 clinicians. This optimization-based modeling approach determines the panel size that maximizes clinician capacity while distributing heterogeneous appointment types among clinician groups with respect to their panel management time (PMT), which is the percent of clinic work.

Results: The differences between consecutive PMT physician groups in total annual appointment volumes per clinician for the current practice range from 176 to 348. The optimization-based approach for the same PMT physician group results in having a range from 211 to 232 appointments, a relative reduction in variability of 88%. Similar workload balance gains are also observed for advanced practice clinicians and resident groups. These results show that the proposed approach significantly improves both patient and appointment workloads distributed among clinician groups.

Conclusion: Appropriate panel size has valuable implications for clinician well-being, patients' timely access to care, clinic and health system productivity, and the quality of care delivered. Results demonstrate substantial improvements with respect to balancing appointment workload across clinician types through strategic use of an optimization-based approach.

Background and objectives: The American Board of Internal Medicine's Choosing Wisely campaign recommends against ordering repetitive complete blood counts (CBC) in the face of clinical and laboratory stability.

Methods: Consecutive patients admitted to a teaching team were included. Intervention 1 was an educational lecture outlining costs of and indications for CBC ordering. Intervention 2 added a simplified algorithm to help providers determine the need for a daily CBC. The primary outcome measure was the number of CBCs ordered per number of patients per day. The secondary outcome measure was net cost saved. The process measures were lecture/poster and algorithm utilization rates. The balancing measure was emergency department visits/readmissions within 7 days of discharge. A statistical process control chart was generated to assess special cause variation. Using R software version 3.5.2, a 2-sample t test and Fisher exact test differences between groups in the outcome and balancing measures.

Results: One hundred ten patients were included over a 62-day period. The difference between the pre-intervention group and both interventions combined was significant ( P = .000317). Special cause variation was observed after institution of both interventions in conjunction. Net costs saved totaled $43 482. Emergency department visits/readmissions within 7 days were similar between the groups ( P = .1403).

Conclusions: Complete blood count ordering patterns and costs were improved through education and providing a decision support tool in the form of a simplified algorithm, without increasing 7-day emergency department visits/readmissions. The algorithm, far less detailed than that previously published, still resulted in significant improvement without unintended consequences, making for a safe and potentially sustainable intervention.

Background and objectives: Population health management (PHM) dashboards using electronic health record (EHR) data can teach trainees about the population they serve while also delivering data on their clinical practice. Yet, few studies have demonstrated their use. In this pilot study, we assessed baseline resident perceptions of population health metrics for continuity clinic panels by comparing resident estimates with EHR-reported values delivered by individualized PHM dashboards.

Methods: A descriptive, comparative study was conducted at a primary continuity clinic site for pediatric residents in January 2018. Residents were surveyed about population health metrics for their patient panels, including demographics, utilization, and medical diagnoses. We compared resident estimates to corresponding EHR-reported values using 2-tailed paired t tests.

Results: A total of 42 out of 55 eligible residents (76%) completed the survey. Compared with EHR-reported values, residents estimated higher percentages of emergency department utilization (22.1% vs 10.3%, P < .01) and morbidity, including medical complexity (15.6% vs 5.9%, P < .01), overweight (38.1% vs 11.7%, P < .01), obesity (20.5% vs 15.8%, P = .02), and asthma (34.6% vs 21.4%, P < .01).

Conclusions: In this pilot study of PHM dashboards, resident perceptions of continuity clinic population health metrics did not align with EHR data. Estimates were higher for measures of utilization and morbidity. PHM dashboards may help trainees better understand their patient populations and serve as a consistent source of objective practice data. However, further research and investment is needed to evaluate dashboard implementation and impact on trainee and patient outcomes.