Quality Improvement Feature Series Article 4: Advanced Designs for Quality Improvement Studies

Ambroggio, Lilliam; Schondelmeyer, Amanda C.; Hoefgen, Erik R.; Brady, Patrick; Shaughnessy, Erin E.

doi:10.1093/jpids/pix082

Cited by 4 publications

(5 citation statements)

References 8 publications

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“…The use of pre-post quasi-experimental designs [ 28 , 29 ] and the PDSA model in health care [ 30 ] in general and in ophthalmology [ 31 ] in particular, has been widely reported. A similar study was conducted in Ethiopia using an appointment system [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

Waiting Time and Patient Satisfaction in a Subspecialty Eye Hospital Using a Mobile Data Collection Kit: Pre-Post Quality Improvement Intervention

Mbwogge¹,

Astbury²,

Nkumbe³

et al. 2022

JMIRx Med

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Background Waiting time can considerably increase the cost to both the clinic and the patient and be a major predictor of the satisfaction of eye care users. Efficient management of waiting time remains as a challenge in hospitals. Waiting time management will become even more crucial in the postpandemic era. A key consideration when improving waiting time is the involvement of eye care users. This study aimed at improving patient waiting time and satisfaction through the use of Plan-Do-Study-Act (PDSA) quality improvement cycles. Objective The objectives of this study were to determine the waiting time and patient satisfaction, measure the association between waiting time and patient satisfaction, and determine the effectiveness of the PDSA model in improving waiting time and satisfaction. Methods This was a pre-post quality improvement study among patients aged 19 to 80 years, who are consulting with the Magrabi International Council of Ophthalmology Cameroon Eye Institute. We used PDSA cycles to conduct improvement audits of waiting time and satisfaction over 6 weeks. A data collection app known as Open Data Kit (Get ODK Inc) was used for real-time tracking of waiting, service, and idling times at each service point. Participants were also asked whether they were satisfied with the waiting time at the point of exit. Data from 51% (25/49) preintervention participants and 49% (24/49) postintervention participants were analyzed using Stata 14 at .05 significance level. An unpaired 2-tailed t test was used to assess the statistical significance of the observed differences in times before and after the intervention. Logistic regression was used to examine the association between satisfaction and waiting time. Results In total, 49 participants were recruited with mean age of 49 (SD 15.7) years. The preintervention mean waiting, service, and idling times were 450 (SD 96.6), 112 (SD 47), and 338 (SD 98.1) minutes, respectively. There was no significant association between patient waiting time and satisfaction (odds ratio 1, 95% CI 0.99-1; P=.37; χ23=0.4). The use of PDSA led to 15% (66 minutes/450 minutes) improvement in waiting time (t47=2; P=.05) and nonsignificant increase in patient satisfaction from 32% (8/25) to 33% (8/24; z=0.1; P=.92). Conclusions Use of PDSA led to a borderline statistically significant reduction of 66 minutes in waiting time over 6 weeks and an insignificant improvement in satisfaction, suggesting that quality improvement efforts at the clinic have to be made over a considerable period to be able to produce significant changes. The study provides a good basis for standardizing the cycle (consultation) time at the clinic. We recommend shortening the patient pathway and implementing other measures including a phasic appointment system, automated patient time monitoring, robust ticketing, patient pathway supervision, standard triaging, task shifting, physician consultation planning, patient education, and additional registration staff.

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Section: Introductionmentioning

confidence: 99%

Waiting Time and Patient Satisfaction in a Subspecialty Eye Hospital Using a Mobile Data Collection Kit: Pre-Post Quality Improvement Intervention

Mbwogge¹,

Astbury²,

Nkumbe³

et al. 2022

JMIRx Med

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“…Besides, it is not easy to control various confounders over time. 21 However, measuring the intervention’s effectiveness over a long time may reduce the burden of these limitations, especially in continuous improvement.…”

Section: Resultsmentioning

confidence: 99%

Enhancing palliative care occupancy and efficiency: a quality improvement project that uses a healthcare pathway for service integration and policy development

2021

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This article described our experience in implementing a quality improvement project to overcome the bed overcapacity problem at a comprehensive cancer centre in a tertiary care centre. We formed a multidisciplinary team including a representative from patient and family support (six members), hospice care and home care services (four members), multidisciplinary team development (four members) and the national lead. The primary responsibility of the formulated team was implementing measures to optimise and manage patient flow. We used the plan–do–study–act cycle to engage all stakeholders from all service layers, test some interventions in simplified pilots and develop a more detailed plan and business case for further implementation and roll-out, which was used as a problem-solving approach in our project for refining a process or implementing changes. As a result, we observed a significant reduction in bed capacity from 35% in 2017 to 13.8% in 2018. While the original length of stay (LOS) was 28 days, the average LOS was 19 days in 2017 (including the time before and after the intervention), 10.8 days in 2018 (after the intervention was implemented), 10.1 days in 2019 and 16 days in 2020. The increase in 2020 parameters was caused by the COVID-19 pandemic, since many patients did not enrol in our new care model. Using a systematic care delivery approach by a multidisciplinary team improves significantly reduced bed occupancy and reduces LOS for palliative care patients.

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“…This is a prospective quality improvement study design, and the methodology adapted was based on the Model for Improvement with use of multiple plan-do-study-act (PDSA) cycles to test individual interventions over time for measurable change. 20…”

Section: Methodsmentioning

confidence: 99%

“…6,[10][11][12]17,18 A quality improvement (QI) study conducted at a children's hospital improved interpretative service use through educating healthcare providers on the use of the telephone interpretative services, providing widespread reminders, and ensuring dual-headset phones in every room. 19,20 Rationale Given the importance of medical interpreter services for equitable and safe healthcare distribution for LEP patients as demonstrated in the literature and the gap in performance identified in our clinical practice, it is imperative to optimize practices via QI methodology.…”

Section: Introductionmentioning

confidence: 99%

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Increasing Language Interpreter Services Use and Documentation: A Quality Improvement Project

et al. 2022

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Background/Purpose: Based on the Civil Rights Act of 1964, hospitals receiving funding from the Department of Human and Health Services must ensure adequate language assistance via a qualified interpreter for Limited English Proficiency (LEP) patients. Despite availability at our institution, official interpreter services were underutilized with inconsistent documentation of use. Baseline data over a 6-week period revealed a median of 43% of LEP parents reported use of official interpreter services, with a median of 0% documentation of use. We aimed to improve both over a 3-month period. Methods: This quality improvement project was conducted at a children's hospital between April and August 2020. Surveys were provided to inpatient LEP families. Four intervention periods were implemented with ongoing data collection for 12 weeks. Interventions included developing best practices, incorporating language identification into daily workflow, empowering families, and standardizing documentation. Data were analyzed by run chart and descriptive statistics. Results: After interventions and several plan-do-study-act cycles, a median of 73% reported use of official interpreter services, and a median of 59% were documented. Conclusions: After multiple interventions, specifically noted after intervention period #2, improvement of official interpreter service use and documentation were identified in all inpatient units.

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Quality Improvement Feature Series Article 4: Advanced Designs for Quality Improvement Studies

Cited by 4 publications

References 8 publications

Waiting Time and Patient Satisfaction in a Subspecialty Eye Hospital Using a Mobile Data Collection Kit: Pre-Post Quality Improvement Intervention

Waiting Time and Patient Satisfaction in a Subspecialty Eye Hospital Using a Mobile Data Collection Kit: Pre-Post Quality Improvement Intervention

Enhancing palliative care occupancy and efficiency: a quality improvement project that uses a healthcare pathway for service integration and policy development

Increasing Language Interpreter Services Use and Documentation: A Quality Improvement Project

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