Unravelling Elements of Value of Healthcare and Assessing their Importance Using Evidence from Two Discrete-Choice Experiments in England.

BACKGROUND: Health systems are moving towards value-based care, implementing new care models that allegedly aim beyond patient outcomes. Therefore, a policy and academic debate is underway regarding the definition of value in healthcare, the inclusion of costs in value metrics, and the importance of each value element. This study aimed to define healthcare value elements and assess their relative importance (RI) to the public in England. METHOD: Using data from 26 semi-structured interviews and a literature review, and applying decision-theory axioms, we selected a comprehensive and applicable set of value-based elements. Their RI was determined using two discrete choice experiments (DCEs) based on Bayesian D-efficient DCE designs, with one DCE incorporating healthcare costs expressed as income tax rise. Respondent preferences were analysed using mixed logit models. RESULTS: Six value elements were identified: additional life-years, health-related quality of life, patient experience, target population size, equity, and cost. The DCE surveys were completed by 402 participants. All utility coefficients had the expected signs and were statistically significant (p < 0.05). Additional life-years (25.3%; 95% confidence interval [CI] 22.5-28.6%) and patient experience (25.2%; 95% CI 21.6-28.9%) received the highest RI, followed by target population size (22.4%; 95% CI 19.1-25.6%) and quality of life (17.6%; 95% CI 15.0-20.3%). Equity had the lowest RI (9.6%; 95% CI 6.4-12.1%), decreasing by 8.8 percentage points with cost inclusion. A similar reduction was observed in the RI of quality of life when cost was included. CONCLUSION: The public prioritizes value elements not captured by conventional metrics, such as quality-adjusted life-years. Although cost inclusion did not alter the preference ranking, its inclusion in the value metric warrants careful consideration.

The Association between Blood Test Trends and Undiagnosed Cancer: A Systematic Review and Critical Appraisal.

Clinical guidelines include monitoring blood test abnormalities to identify patients at increased risk of undiagnosed cancer. Noting blood test changes over time may improve cancer risk stratification by considering a patient's individual baseline and important changes within the normal range. We aimed to review the published literature to understand the association between blood test trends and undiagnosed cancer. MEDLINE and EMBASE were searched until 15 May 2023 for studies assessing the association between blood test trends and undiagnosed cancer. We used descriptive summaries and narratively synthesised studies. We included 29 articles. Common blood tests were haemoglobin (24%, n = 7), C-reactive protein (17%, n = 5), and fasting blood glucose (17%, n = 5), and common cancers were pancreatic (29%, n = 8) and colorectal (17%, n = 5). Of the 30 blood tests studied, an increasing trend in eight (27%) was associated with eight cancer types, and a decreasing trend in 17 (57%) with 10 cancer types. No association was reported between trends in 11 (37%) tests and breast, bile duct, glioma, haematological combined, liver, prostate, or thyroid cancers. Our review highlights trends in blood tests that could facilitate the identification of individuals at increased risk of undiagnosed cancer. For most possible combinations of tests and cancers, there was limited or no evidence.

GPs' perspectives on diagnostic tests for children: a qualitative interview study.

BACKGROUND: Most healthcare contacts for children in the UK occur in general practice. Diagnostic tests can be beneficial in narrowing differential diagnoses; however, there is substantial variation in the use of tests for children in general practice. Unwarranted variation in testing can lead to variation in quality of care and may exacerbate health inequities. To our knowledge, no previous study has tried to understand why variation in testing exists for children in general practice. AIM: To explore GPs' perspectives on using diagnostic tests for children in primary care and the underlying drivers of variation. DESIGN AND SETTING: Qualitative study in which semi-structured interviews were conducted with GPs and trainee GPs in England. METHOD: Interviews were conducted with 18 GPs and two trainee GPs between April and June 2023. The interviews were transcribed and analysed using reflexive thematic analysis. RESULTS: GPs reflected that their approach to testing in children differed from their approach to testing in adults: their threshold to test was higher, and their threshold to refer to specialists was lower. GPs' perceptions of test utility varied, including objective testing for asthma. Perceived drivers of variation in testing were intrinsic (clinician-specific) factors relating to their risk tolerance and experience; and extrinsic factors, including disease prevalence, parental concern and expectations of health care, workforce changes leading to fragmentation in care, time constraints, and differences in guidelines. CONCLUSION: The findings of this study identify actionable issues for clinicians, researchers, and policymakers to address gaps in education, evidence, and guidance, reduce unwarranted differences in test use, and improve the quality of health care delivered to children in general practice.

Digital Medication Management in Polypharmacy.

BACKGROUND: Inappropriate drug prescriptions for patients with polypharmacy can have avoidable adverse consequences. We studied the effects of a clinical decision-support system (CDSS) for medication management on hospitalizations and mortality. METHODS: This stepped-wedge, cluster-randomized, controlled trial involved an open cohort of adult patients with polypharmacy in primary care practices (=clusters) in Westphalia-Lippe, Germany. During the period of the intervention, their medication lists were checked annually using the CDSS. The CDSS warns against inappropriate prescriptions on the basis of patient-related health insurance data. The combined primary endpoint consisted of overall mortality and hospitalization for any reason. The secondary endpoints were mortality, hospitalizations, and high-risk prescription. We analyzed the quarterly health insurance data of the intention- to-treat population with a mixed logistic model taking account of clustering and repeated measurements. Sensitivity analyses addressed effects of the COVID-19 pandemic and other effects. RESULTS: 688 primary care practices were randomized, and data were obtained on 42 700 patients over 391 994 quarter years. No significant reduction was found in either the primary endpoint (odds ratio [OR] 1.00; 95% confidence interval [0.95; 1.04]; p = 0.8716) or the secondary endpoints (hospitalizations: OR 1.00 [0.95; 1.05]; mortality: OR 1.04 [0.92; 1.17]; high-risk prescription: OR 0.98 [0.92; 1.04]). CONCLUSION: The planned analyses did not reveal any significant effect of the intervention. Pandemicadjusted analyses yielded evidence that the mortality of adult patients with polypharmacy might potentially be lowered by the CDSS. Controlled trials with appropriate follow-up are needed to prove that a CDSS has significant effects on mortality in patients with polypharmacy.

Diagnostic accuracy of a point-of-care antigen test for SARS-CoV-2 and influenza in a primary care population (RAPTOR-C19).

OBJECTIVES: Limited evidence exists for the diagnostic performance of point-of-care tests for SARS-CoV-2 and influenza in community healthcare. We carried out a prospective diagnostic accuracy study of the LumiraDx™ SARS-CoV-2 and influenza A or B assay in primary care. METHODS: Total of 913 adults and children with symptoms of current SARS-CoV-2 infection were recruited from 18 UK primary care practices during a period when Omicron was the predominant COVID variant of concern (June 2022 to December 2022). Trained health care staff performed the index test, with diagnostic accuracy parameters estimated for SARS-CoV-2 and influenza against real-time reverse-transcription PCR (rtRT-PCR). RESULTS: 151/887 participants were SARS-CoV-2 rtRT-PCR positive, 109 positive for Influenza A, 6 for Influenza B. Index test sensitivity for SARS-CoV-2 was 80.8% (122 of the 151, 95% CI, 73.6-86.7%) and specificity 98.9% (728 of the 736, 95% CI, 97.9-99.5%). For influenza A, sensitivity was 61.5% (67 of the 109, 95% CI, 51.7-70.6%) and specificity 99.4% (771 of the 776, 95% CI, 98.5-99.8%). Sensitivity to detect SARS-CoV-2 and influenza dropped sharply at rtRT-PCR cycle thresholds (Ct) > 30. DISCUSSIONS: The LumiraDx™ SARS-CoV-2 and influenza A/B assay had moderate sensitivity for SARS-CoV-2 in symptomatic patients in primary care, with lower performance with high rtRT-PCR Ct. Negative results in this patient group cannot definitively rule out SARS-CoV-2 or influenza.