Value in Health最新文献

Objectives: Healthcare access is a significant barrier in neurodevelopmental care. Various ways or modalities, including virtual care models may bridge this gap. Although studies have explored individual virtual modalities, families' preferences across them remain unexamined. This study aims to elicit families' preferences for various modalities of accessing neurodevelopmental screening (eg, face to face and virtual) for children.

Methods: We used a Discrete Choice Experiment to elicit preferences from families (parents or caregivers) of children under 5. Alternatives (screening modalities), attributes, and levels were identified using literature and expert advice. Final alternatives included video conferencing, telephone consultation, mobile application, online portal, and face to face. Bayesian d-efficient, partial choice set design presented 3 of 5 alternatives in each choice task. Final survey was pretested and piloted before online administration, yielding 502 responses. Analysis used mixed logit and latent class models.

Results: Families preferred face-to-face screening over virtual options, including video conferencing (-1.53, 95% CI -2.45 to -0.60), mobile applications (-1.57, 95% CI -2.56 to -0.58), online portals (-1.72, 95% CI -2.58 to -0.86), and telephone consultations (-1.96, 95% CI -2.94 to -0.98). Across all alternatives, families preferred shorter duration appointments, automated feedback, and screening test administered together by parents and clinicians. Latent class analysis revealed a Digitally Oriented Class (25% probability) that preferred mobile applications and online portals over face-to-face screening.

Conclusions: Although virtual options may improve accessibility, they may not fully replace face-to-face neurodevelopmental screening for many families. Some families may be receptive to virtual care, particularly via mobile applications and online portals.

Objectives: To examine the impact of changing the basket of reference countries on ability to reference and on pharmaceutical launch prices in 6 markets, which approved International Reference Pricing (IRP) reference country basket changes in 2019.

Methods: Pre- and postreform IRP regulations in Austria, Bulgaria, Croatia, Canada, The Netherlands, and North Macedonia were examined. Policy-makers' objectives in pursuing basket reform were identified from public statements and-when unavailable-through primary research. IRP rules were applied strictly to calculate, using PharmOnLine International (POLI) data, the maximum allowed price (MAP) at launch of new chemical/molecular entity presentations-first priced in 2018 and subject to IRP-under the old and the new basket.

Results: Bulgaria and The Netherlands would each lose ability to price 1 new chemical/molecular entity presentation under IRP because of the reform, with the other countries unaffected. Consistent with policy-makers' expectations, launch prices would not be significantly affected in Austria (-0.45%), Bulgaria (0%), and Croatia (0%). Canada and The Netherlands, which targeted price reductions, would have had 39.19% and 2.16% lower average MAP across the sample, respectively. North Macedonian authorities did not reveal price rises as their objective in primary research, but the MAP at launch would have been 30.48% higher on average under the new basket.

Conclusions: This study demonstrates IRP's complexity and confirms that policy-makers need an in-depth understanding of IRP rules to adequately predict basket-change impact on prices. The pre-assessment undertaken by policy-makers in markets, whose basket reform outcome aligned with expectations, provides valuable lessons for other countries.

Objectives: The adoption of artificial intelligence (AI) technology holds significant potential to drive innovation for value-based healthcare for Victorian public oral healthcare, Australia. This pilot study compared the clinical triage decision outcome of experienced dentists in prioritizing consumers with urgent dental care at Your Community Health, a community health service in Victoria, Australia, with those generated by the CoTreat AI-driven tool (CoTreat Pty Ltd, Australia).

Methods: Consecutive sampling of consumers were recruited for the 6-month pilot. Five clinical criteria were established to determine consumers with urgent care: (1) requires urgent extraction causing loss of upper or lower anterior teeth, (2) multiple teeth (≥15% of remaining dentition) with moderate/extensive dental caries, (3) abscessed tooth/teeth, (4) root caries, and (5) missing upper and lower anterior teeth. Face validation was undertaken to compare the agreement between the triage output returned by CoTreat (index test) and 2 experienced dentists (reference standard) in determining urgent care.

Results: A total of 173 consumers were triaged in this pilot study (mean age 61.9 years [SD 18.]). One-third (n = 57) were identified needing urgent care. CoTreat achieved 98.3% agreement with dentist clinical triage outcome (Cohen's k = 0.96), 100% sensitivity, and 97.5% specificity, with positive predictive value of 94.7% and negative predictive value of 100%. The most common triage criteria were missing anterior teeth (60.3%) and abscesses (20.7%).

Conclusions: CoTreat demonstrated excellent agreement with dentists' clinical triage decisions. AI-driven tools, such as CoTreat, can advance value-based healthcare implementation by identifying consumers with urgent care needs for Victorian public oral healthcare.

Objectives: The value of information framework assesses whether further research is warranted, and recent approximation methods have made the value of information analysis more feasible. There is ongoing uncertainty regarding the cost-effectiveness of Australia's universal newborn hearing screening (UNHS) program. This study aimed to quantify the value of additional research to guide future research priorities, including estimating the value by type of evidence and sample size needed to maximize the value to decision making.

Methods: A decision-analytic model, comprising an initial decision tree followed by a Markov model, with a 26-year time horizon, was developed to evaluate the cost-effectiveness of UNHS compared with no screening. Model parameters, including costs, probabilities, and outcomes, were derived from 2 Australian longitudinal studies, alongside relevant published sources. The expected value of perfect information, the expected value of partial information, and the expected value of sample information were estimated.

Results: The incremental cost-effectiveness ratio was $39 400/quality-adjusted life-year, with approximately 50% probability of being cost-effective at the $40 900/quality-adjusted life-year threshold. The expected value of perfect information for 2.5 million newborns over 10 years was $130.30 million, and the expected value of partial information revealed that the utility values were the primary source of uncertainty, particularly the association between utilities and diagnosis age. The expected value of sample information indicated that collecting utility data from 300 to 500 additional children could significantly reduce uncertainty and be worth between $106.41 million and $113.91 million.

Conclusions: UNHS had an incremental cost-effectiveness ratio below the threshold, with some uncertainty in cost-effectiveness. Collecting additional utility data would reduce uncertainty and reduce decision uncertainty in Australia and elsewhere.

Background: Evidence that a healthcare intervention is clinically effective and cost-effective, and subsequently funded, does not guarantee adoption into routine clinical practice. Implementation science can improve adoption, although it also involves valuable resources. This study assessed the cost-effectiveness of a theory-based compared to an intuition-based implementation approach, using genetic testing for Lynch syndrome (LS) as a case-study.

Methods: A pragmatic two-arm cluster randomised controlled trial (the Hide and Seek Project, HaSP) compared the approaches across seven large Australian hospitals (N=3,321 patients). Costs associated with the implementation approaches and the strategies were collected during the trial, including initial once-off and ongoing strategy costs. Results were incorporated into a published microsimulation model (Policy1-Lynch). Costs were reported in 2021 Australian Dollars (AUD).

Results: Compared with the intuition-based approach, the theory-based approach was previously shown to significantly improve genetics services referral in high LS risk patients (p<0.0001). The within-trial analysis found that a theory-based approach reduced once-off plus ongoing implementation costs by AUD$0.75 per patient versus an intuition-based approach over five years. The modelled analysis estimated that a theory-based approach increased health system costs by AUD$103.74 per colorectal cancer patient, but resulted in fewer colorectal cancer deaths and more life years gained (LYG), and thus cost AUD$37,679 more per LYG than an intuition-based approach.

Conclusions: The theory-based approach resulted in more effective strategies and was cost-effective versus an intuition-based approach. Further research is needed to confirm these results in larger trials, other settings and conditions.

Objectives: We developed the methodology of welfare-based healthcare planning. For proof of concept, we empirically identified welfare-optimal hospital locations for thoracic surgical treatment of lung cancer (TSTLC) in Germany.

Methods: We used statutory health insurance data to estimate a volume-outcome model capturing the case-volume elasticity of the 1-year survival odds in patients with TSTLC. We conducted a discrete choice experiment to estimate the willingness to travel of representative (potential) patients for increases in the 1-year survival probability after TSTLC. Combining these results with a gravity model fitted to observed locations of patients and hospitals, we simulated different health planning scenarios (HPS) in 2035. For each HPS, we applied a Nash social welfare function to derive social welfare.

Results: Using data on 1449 patients with TSTLC treated in 189 hospitals, we estimated a case-volume elasticity of 0.27 (95% confidence interval [CI] = 0.07;0.46). The discrete choice experiment revealed that, for an increase in the 1-year survival probability from 90% to 91%, representative individuals would be willing to travel additional 66 minutes (95% CI = 45;93 minutes) when traveling 60 minutes and additional 23 minutes (95% CI = 18;33 minutes) when traveling 240 minutes. The top 1000 HPS according to welfare included between 15 and 22 hospitals. The welfare-optimal HPS included 19 hospitals with an average travel time of 54 minutes (status-quo HPS: 40 minutes) and a 1-year survival probability between 90.5% and 93.6% (status-quo HPS: 89.1%).

Conclusions: Our findings highlight the potential of welfare-based healthcare planning to increase the welfare of patients in Germany due to centralization of TSTLC.

Objectives: Existing personal health agency (ability to manage health on one's own) measures focus on adherence to disease-modifying treatments rather than accommodation of disease on one's own with optional visits, tests, and treatments as effective health strategy. This study aimed to develop a personal health agency measure with themes more relevant for discretionary care (taking control in self-management rather than adherence).

Methods: In this three-stage, cross-sectional study among 801 people seeking discretionary musculoskeletal specialty care, we performed sequential exploratory and confirmatory factor analyses starting with 33 items derived from legacy measures. We retained items that contributed to model fit (root mean square error of approximation < 0.05) accounting for favorable item discrimination, item difficulty, internal consistency, local dependencies, and differential item functioning. The findings were internally validated using 2 cohorts. We also assessed external validity (correlation with Patient Activation Measure [PAM]-13) and consistency (factors associated with new measure vs PAM-13).

Results: We identified 1 underlying theme and selected 9 items to represent the new Agency for Navigating Challenges, Health Ownership, and Resiliency (ANCHOR) measure. The 3-item, 6-item, and 9-item versions displayed excellent model fit (root mean square error of approximation < 0.001-0.035) and internal consistency (Cronbach alpha = 0.82-0.93) in internal validation. The floor effects were 2% to 3% and ceiling effects were 9% to 17%. The ANCHOR measures had moderate-to-strong correlations with PAM-13 (rho = 0.61-0.73) with similar external correlates, supporting external validity and consistency.

Conclusions: Enhancement of personal health agency-an important element of effective accommodation of symptoms over a lifetime-can be facilitated by routine measurement using ANCHOR. Agency-enhancing health strategies have the potential to support health while limiting discretionary use of resources.

Objectives: The diagnostic evaluation for abdominal and pelvic cancers without routine screening programs, such as pancreatic, liver, ovarian, and bladder cancers, can vary significantly in pathway and timing. Efficient and timely diagnosis is desirable in patients with a suspicion of cancer. We characterized real-world diagnostic pathways and examined the association of first imaging modality with measures of diagnostic efficiency in these cancers.

Methods: We conducted a retrospective cohort study using Surveillance, Epidemiology and End Results cancer registry data linked with Medicare claims from 2010 to 2019. Patients aged ≥65 years diagnosed with incident pancreatic, liver, ovarian, or bladder cancer were included. We estimated unadjusted timing, cost, and healthcare resource utilization from first imaging to diagnosis, and from diagnosis to treatment initiation by cancer type. Using negative binomial count models, we evaluated the association between computed tomography (CT) scan as the first imaging procedure and both time to diagnosis and number of imaging procedures used in the diagnostic pathway.

Results: Among 169 781 patients (48 751 pancreatic; 24 493 liver; 16 537 ovarian; and 80 000 bladder), CT scan was the most common initial imaging test (51%-65%). Patients who received a CT scan first experienced significantly shorter time to diagnosis (29-42 days faster) and required fewer imaging procedures (0.25-0.70 fewer) compared with other imaging modalities (P < .001). Higher comorbidity scores were associated with longer, more complex diagnostic pathways.

Conclusions: CT scans as the first imaging test were associated with greater diagnostic efficiency in abdominal and pelvic cancers. These findings provide a benchmark for evaluating emerging diagnostic technologies and optimizing cancer diagnostic pathways.