Background Overuse of diagnostic testing substantially contributes to healthcare expenses and potentially exposes patients to unnecessary harm. Our objective was to systematically identify and examine studies that assessed the prevalence of diagnostic testing overuse across healthcare settings to estimate the overall prevalence of low-value diagnostic overtesting. Methods PubMed, Web of Science and Embase were searched from inception until 18 February 2020 to identify articles published in the English language that examined the prevalence of diagnostic testing overuse using database data. Each of the assessments was categorised as using a patient-indication lens, a patient-population lens or a service lens. Results 118 assessments of diagnostic testing overuse, extracted from 35 studies, were included in this study. Most included assessments used a patient-indication lens (n=67, 57%), followed by the service lens (n=27, 23%) and patient-population lens (n=24, 20%). Prevalence estimates of diagnostic testing overuse ranged from 0.09% to 97.5% (median prevalence of assessments using a patient-indication lens: 11.0%, patient-population lens: 2.0% and service lens: 30.7%). The majority of assessments (n=85) reported overuse of diagnostic testing to be below 25%. Overuse of diagnostic imaging tests was most often assessed (n=96). Among the 33 assessments reporting high levels of overuse (≥25%), preoperative testing (n=7) and imaging for uncomplicated low back pain (n=6) were most frequently examined. For assessments of similar diagnostic tests, major variation in the prevalence of overuse was observed. Differences in the definitions of low-value tests used, their operationalisation and assessment methods likely contributed to this observed variation. Conclusion Our findings suggest that substantial overuse of diagnostic testing is present with wide variation in overuse. Preoperative testing and imaging for non-specific low back pain are the most frequently identified low-value diagnostic tests. Uniform definitions and assessments are required in order to obtain a more comprehensive understanding of the magnitude of diagnostic testing overuse.

Overuse of unnecessary care is widespread around the world. This so-called low-value care provides no benefit for the patient, wastes resources and can cause harm. The concept of low-value care is broad and there are different reasons for care to be of low-value. Hence, different strategies might be necessary to reduce it and awareness of this may help in designing a de-implementation strategy. Based on a literature scan and discussions with experts, we identified three types of low-value care. The type ineffective care is proven ineffective, such as antibiotics for a viral infection. Inefficient care is in essence effective, but is of low-value through inefficient provision or inappropriate intensity, such as chronic benzodiazepine use. Unwanted care is in essence appropriate for the clinical condition it targets, but is low-value since it does not fit the patients’ preferences, such as a treatment aimed to cure a patient that prefers palliative care. In this paper, we argue that these three types differ in their most promising strategy for de-implementation and that our typology gives direction in choosing whether to limit, lean or listen. We developed a typology that provides insight in the different reasons for care to be of low-value. We believe that this typology is helpful in designing a tailor-made strategy for reducing low-value care.

It is challenging to use shared decision-making with patients who have a chronic health condition or, especially, multimorbidity. A patient-goal-oriented approach can thus be beneficial. This study aims to identify and evaluate studies on the effects of interventions that support collaborative goal setting or health priority setting compared to usual care for elderly people with a chronic health condition or multimorbidity. This systematic review was based on EPOC, PRISMA and MOOSE guidelines. Pubmed, PsychInfo, CINAHL, Web of Science, Embase and the Cochrane Central Register of Controlled Trials were searched systematically. The following eligibility criteria were applied: 1. Randomised (cluster) controlled trials, non-randomised controlled trials, controlled before-after studies, interrupted time series or repeated measures study design; 2. Single intervention directed specifically at collaborative goal setting or health priority setting or a multifactorial intervention including these elements; 3. Study population of patients with multimorbidity or at least one chronic disease (mean age ± standard deviation (SD) incl. age 65). 4. Studies reporting on outcome measures reducible to outcomes for collaborative goal setting or health priority setting. A narrative analysis was performed. Eight articles describing five unique interventions, including four cluster randomised controlled trials and one randomised controlled trial, were identified. Four intervention studies, representing 904, 183, 387 and 1921 patients respectively, were multifactorial and showed statistically significant effects on the application of goal setting (Patient Assessment of Chronic Illness Care (PACIC) goal setting subscale), the number of advance directives or the inclusion of goals in care plans. Explicit attention for goal setting or priority setting by a professional was a common element in these multifactorial interventions. One study, which implemented a single-factor intervention on 322 patients, did not have significant effects on doctor-patient agreement. All the studies had methodological concerns in varying degrees. Collaborative goal setting and/or priority setting can probably best be integrated in complex care interventions. Further research should determine the mix of essential elements in a multifactorial intervention to provide recommendations for daily practice. In addition, the necessity of methodological innovation and the application of mixed evaluation models must be highlighted to deal with the complexity of goal setting and/or priority setting intervention studies.

Patient-Reported Outcome (PRO) measurement is a method for measuring perceptions of patients on their health and quality of life. The aim of this paper is to present the results of PRO measurements in total hip and knee replacement as routinely collected during 20 years of surgery in a university hospital setting. Data of consecutive patients between 1993 and 2014 were collected. Health outcomes were measured pre-surgery and at 3, 6, and 12 months post-surgery. Outcomes for hip replacement were measured with the Harris Hip Score (HHS) and Oxford Hip Score (OHS). Outcomes for knee replacement were measured with the Western Ontario and McMaster Universities Arthritis Index (WOMAC) and the Knee Society Score (KSS). A Visual Analog Scale (VAS) for pain was used. Absolute and relative Minimal Clinically Important Differences (MCID) were estimated. Generalized estimating equation analysis was used for estimating mean outcomes. Trends over time were analyzed. The database contained 2,089 patients with hip replacement, and 704 patients with knee replacement. Mean HHS and OHS scores in primary hip replacement at 12 months post-surgery were 86.7 (SD: 14.5) and 41.1 (SD: 7.5) respectively. Improvements on the HHS based on absolute MCID was lower for revisions compared to primary hip replacements, with 72.4% and 87.0% respectively. Mean WOMAC and KSS scores in knee replacement at 12 months post-surgery were 21.5 (SD: 18.2) and 67.0 (SD: 26.4) respectively. Improvements based on absolute MCID were lowest for the KSS (62.6%) and highest for VAS pain (85.6%). Trend analysis showed a difference in 1 out of 24 comparisons in hip replacement and in 2 out of 9 comparisons in knee replacement. The functional status of a large cohort of patients significantly improved after hip and knee replacement based on routine data collection. Our study shows the feasibility of the routine collection of PRO data in patients with total hip and knee replacement. The use of PRO data provides opportunities for continuous quality improvement.

Using outcome measures to advance healthcare continues to be of widespread interest. The goal is to summarize the results of studies which use outcome measures from clinical registries to implement and monitor QI initiatives. The second objective is to identify a) facilitators and/or barriers that contribute to the realization of QI efforts, and b) how outcomes are being used as a catalyst to change outcomes over time. We searched the PubMed, EMBASE and Cochrane databases for relevant articles published between January 1995 and March 2017. We used a standardized data abstraction form. Studies were included when the following three criteria were fulfilled: 1) they relied on structural data collection, 2) when a structural and comprehensive QI intervention had been implemented and evaluated, and 3) impact on improving clinical and/or patient-reported outcomes was described. Data on QI strategies, QI initiatives and the impact on outcomes was extracted using standardized assessment tools. We included 21 articles, of which eight showed statistically significant improvements on outcomes using data from clinical registries. Out of these eight studies, the Chronic Care Model, IT application as feedback, benchmarking and the Collaborative Care Model were used as QI methods. Encouraging trends in realizing improved outcomes through QI initiatives were observed, ranging from improving teamwork, implementation of clinical guidelines, implementation of physician alerts and development of a decision support system. Facilitators for implementing QI initiatives included a high quality database, audits, frequent reporting and feedback, patient involvement, communication, standardization, engagement, and leadership. This review suggests that outcomes collected in clinical registries are supportive to realize QI initiatives. Organizational readiness and an active approach are key in achieving improved outcomes.