Collecting Physicians' Preferences on Medical Devices: Are We Doing It Right? Evidence from Italian Orthopedists Using 2 Different Stated Preference Methods

OBJECTIVES

Physician preference items (PPIs) are high-cost medical devices for which clinicians express firm preferences with respect to a particular manufacturer or product. This study aims to identify the most important factors in the choice of new PPIs (hip or knee prosthesis) and infer about the existence of possible response biases in using 2 alternative stated preference techniques.

METHODS

Six key attributes with 3 levels each were identified based on a literature review and clinical experts' opinions. An online survey was administered to Italian hospital orthopedists using type 1 best-worst scaling (BWS) and binary discrete choice experiment (DCE). BWS data were analyzed through descriptive statistics and conditional logit model. A mixed logit regression model was applied to DCE data, and willingness-to-pay (WTP) was estimated. All analyses were conducted using Stata 16.

RESULTS

A sample of 108 orthopedists were enrolled. In BWS, the most important attribute was "clinical evidence," followed by "quality of products," while the least relevant items were "relationship with the sales representative" and "cost." DCE results suggested instead that orthopedists prefer high-quality products with robust clinical evidence, positive health technology assessment recommendation and affordable cost, and for which they have a consolidated experience of use and a good relationship with the sales representative.

CONCLUSIONS

The elicitation of preferences for PPIs using alternative methods can lead to different results. The BWS of type 1, which is similar to a ranking exercise, seems to be more affected by acquiescent responding and social desirability than the DCE, which introduces tradeoffs in the choice task and is likely to reveal more about true preferences.

HIGHLIGHTS

Physician preference items (PPIs) are medical devices particularly exposed to physicians' choice with regard to type of product and supplier.Some established techniques of collecting preferences can be affected by response biases such as acquiescent responding and social desirability.Discrete choice experiments, introducing more complex tradeoffs in the choice task, are likely to mitigate such biases and reveal true physicians' preferences for PPIs.

Clarifying the unmet clinical need during medical device innovation in women's health - A narrative review

Medical technologies are pervasive across women's health, spanning across obstetric and gynecological care. FemTech, the sector responsible for developing these technologies, is growing at 15.6% per annum. However, there are concerns of disconnects between new product development (NPD) and the care afforded to women in consequence of implementing these innovations. The most crucial stage of NPD involves understanding the clinical need. Without a clear need and clinical use case, innovators risk developing solutions which do not address the issues women and caregivers experience. Thus, the product will miss the market and experience limited uptake. Tools for performing clinical needs assessments and defining the use case are being developed. This review provides an analysis of their strengths and weaknesses to inform FemTech innovators of the available resources. We further discuss concepts for creating a unified approach to assessing unmet needs such that technologies have a higher chance of improving women's healthcare.

Use of Telemedicine Technology among General Practitioners during COVID-19: A Modified Technology Acceptance Model Study in Poland

During the COVID-19 pandemic, telehealth became a popular solution for the remote provision of primary care by General Practitioners (GPs) in Poland. This study aimed to assess the GPs' acceptance of telehealth during the COVID-19 pandemic in Poland and to explain the factors that drive GPs' need to implement a telehealth system in primary care using the modified Technology Acceptance Model (TAM). In Poland, 361 GPs from a representative sample of 361 clinics drawn from 21,500 outpatient institutions in Poland participated in the empirical study. Structural equation modelling (SEM) was used to evaluate the causal relationships that were formulated in the proposed model. Research has shown that Polish GPs reported a positive perception and high acceptance of the telehealth system during the COVID-19 pandemic. Overall, the results show that the social factors (image, decision autonomy, perception of patient interaction) significantly positively influence the technological factors (perceived ease of use and perceived usefulness) that influence the need to implement a telehealth system. The proposed socio-technological model can serve as a theoretical basis for future research and offer empirical predictions for practitioners and researchers in health departments, governments, and primary care settings.

Systematic Review of Health Economic Evaluations Focused on Artificial Intelligence in Healthcare: The Tortoise and the Cheetah

OBJECTIVES

This study aimed to systematically review recent health economic evaluations (HEEs) of artificial intelligence (AI) applications in healthcare. The aim was to discuss pertinent methods, reporting quality and challenges for future implementation of AI in healthcare, and additionally advise future HEEs.

METHODS

A systematic literature review was conducted in 2 databases (PubMed and Scopus) for articles published in the last 5 years. Two reviewers performed independent screening, full-text inclusion, data extraction, and appraisal. The Consolidated Health Economic Evaluation Reporting Standards and Philips checklist were used for the quality assessment of included studies.

RESULTS

A total of 884 unique studies were identified; 20 were included for full-text review, covering a wide range of medical specialties and care pathway phases. The most commonly evaluated type of AI was automated medical image analysis models (n = 9, 45%). The prevailing health economic analysis was cost minimization (n = 8, 40%) with the costs saved per case as preferred outcome measure. A total of 9 studies (45%) reported model-based HEEs, 4 of which applied a time horizon >1 year. The evidence supporting the chosen analytical methods, assessment of uncertainty, and model structures was underreported. The reporting quality of the articles was moderate as on average studies reported on 66% of Consolidated Health Economic Evaluation Reporting Standards items.

CONCLUSIONS

HEEs of AI in healthcare are limited and often focus on costs rather than health impact. Surprisingly, model-based long-term evaluations are just as uncommon as model-based short-term evaluations. Consequently, insight into the actual benefits offered by AI is lagging behind current technological developments.

What Promotes Surgeon Practice Change? A Scoping Review of Innovation Adoption in Surgical Practice

OBJECTIVE

The goal of this scoping review was to summarize the literature on facilitators and barriers to surgical practice change. This information can inform research to implement best practices and evaluate new surgical innovations.

BACKGROUND

In an era of accelerated innovations, surgeons face the difficult decision to either acknowledge and implement or forgo new advances. Although changing surgical practice to align with evidence is an imperative of health systems, evidence-based guidelines have not translated into consistent change. The literature on practice change is limited and has largely focused on synthesizing information on methods and trials to evaluate innovative surgical interventions. No reviews to date have grounded their analysis within an implementation science framework.

METHODS

A systematic review of the literature on surgical practice change was performed. Abstracts and full-text articles were reviewed for relevance using inclusion and exclusion criteria and data were extracted from each article. Cited facilitators and barriers were then mapped across domains within the implementation science Theoretical Domains Framework and expanded to the Capability, Opportunity, Motivation, and Behavior model.

RESULTS

Components of the Capability, Opportunity, Motivation, and Behavior model were represented across the Theoretical Domains Framework domains and acted as both facilitators and barriers to practice change depending on the circumstances. Domains that most affected surgical practice change, in order, were: opportunity (environmental context and resources and social influences), capability (knowledge and skills), and motivation (beliefs about consequences and reinforcement).

CONCLUSIONS

Practice change is predicated on a conducive environment with adequate resources, but once that is established, the surgeon's individual characteristics, including skills, motivation, and reinforcement determine the likelihood of successful change. Deficiencies in the literature underscore the need for further study of resource interventions and the role of surgical team dynamics in the adoption of innovation. A better understanding of these areas is needed to optimize our ability to disseminate and implement best practices in surgery.

The effect of primary care visits on other health care utilization: A randomized controlled trial of cash incentives offered to low income, uninsured adults in Virginia

We conducted a randomized controlled trial, enrolling low-income uninsured adults in Virginia (United States), to determine whether cash incentives are effective at encouraging a primary care provider (PCP) visit, and at lowering utilization and costs. Subjects were randomized to four groups: untreated controls, and one of three incentive arms with incentives of $0, $25, or $50 for visiting a PCP within six months of group assignment. We used the exogenous variation generated by the experiment to obtain causal evidence on the effects of a PCP visit. We observed modest reductions in non-urgent emergency department visits and increased outpatient visits, but no reductions in overall costs. These findings in utilization are consistent with the expectation that PCPs offer an alternative to the emergency department for non-emergent conditions. Total costs did not decline because any savings from avoiding the emergency department were offset by increased outpatient utilization.

Physicians' Decision Making on Adoption of New Technologies and Role of Coverage with Evidence Development: A Qualitative Study

OBJECTIVES

To foster value-based pricing and coverage with evidence development in Germany, certain new diagnostic and treatment methods have been subject to a benefit assessment since 2016 to determine their reimbursement. Although this is a paradigm shift, the German approach is limited to some few specific technologies for which reimbursement is requested. As physicians encounter this regulatory instrument, the aim of the study was to understand physicians' decision making regarding the adoption of new medical technologies and to identify their perspectives on the evidence base and financing with additional reimbursement systems.

METHODS

From April to August 2017, semistructured interviews with chief and senior physicians of vascular surgery and cardiology in inpatient care in Germany were conducted (N = 23). The interviews were carried out by one researcher in one-to-one appointments or via telephone. Data were analyzed inductively to identify factors and generate thematic categories using qualitative content analysis.

RESULTS

We identified 52 factors in eight categories influencing physicians' adoption of new technologies. The evidence base for new technologies was criticized (e.g., lack of available studies). Physicians' knowledge of the regulation of market approval and innovation payments varied. They recommended the utilization of new technologies in certain specialist centers and the facilitation of observational studies.

CONCLUSIONS

Physicians saw the need for the new approach and supported its aim. However, its design and implementation appeared to be questionable from their medical perspective. The provision of summarized information on the benefit of technologies might be a possibility to assist physicians' decision making.

New Breast Cancer Radiotherapy Technology Confers Higher Complications and Costs Before Effectiveness Proven: A Medicare Data Analysis

A new breast cancer treatment, brachytherapy-based accelerated partial breast radiotherapy (RT), was adopted before long-term effectiveness evidence, potentially increasing morbidity and costs compared with whole breast RT. The aim of this study was to estimate complication rates and RT-specific and 1-year costs for a cohort of female Medicare beneficiaries diagnosed with breast cancer (N = 47 969). We analyzed 2005-2007 Medicare claims using multivariable logistic regression for complications and generalized linear models (log link, gamma distribution) for costs. Overall, 11% (n = 5296) underwent brachytherapy-based RT; 9.4% had complications. Odds of any complication were higher (odds ratio [OR]: 1.62; 95% confidence interval [CI]: 1.49-1.76) for brachytherapy versus whole breast RT, similarly to seroma (OR: 2.85; 95% CI: 1.97-4.13), wound complication/infection (OR: 1.72; 95% CI: 1.52-1.95), cellulitis (OR: 1.48; 95% CI: 1.27-1.73), and necrosis (OR: 2.07; 95% CI: 1.55-2.75). Mean RT-specific and 1-year total costs for whole breast RT were $6375, and $19 917, $4886, and $4803 lower than brachytherapy ( P < .0001). Multivariable analyses indicated brachytherapy yielded 76% higher RT costs (risk ratio: 1.76; 95% CI: 1.74-1.78, P < .0001) compared with whole breast RT. Brachytherapy had higher complications and costs before long-term evidence proved its effectiveness. Policies should require treatment registries with reimbursement incentives to capture surveillance data for new technologies.

Multiple constraints compromise decision-making about implantable medical devices for individual patients: qualitative interviews with physicians

Background

Little research has examined how physicians choose medical devices for treating individual patients to reveal if interventions are needed to support decision-making and reduce device-associated morbidity and mortality. This study explored factors that influence choice of implantable device from among available options.

Methods

A descriptive qualitative approach was used. Physicians who implant orthopedic and cardiovascular devices were identified in publicly available directories and web sites. They were asked how they decided what device to use in a given patient, sources of information they consulted, and how patients were engaged in decision-making. Sampling was concurrent with data collection and analysis to achieve thematic saturation. Data were analyzed using constant comparative technique by all members of the research team.

Results

Twenty-two physicians from five Canadian provinces (10 cardiovascular, 12 orthopedic; 8, 10 and 4 early, mid and late career, respectively) were interviewed. Responses did not differ by specialty, geographic region or career stage. Five major categories of themes emerged that all influence decision-making about a range of devices, and often compromise choice of the most suitable device for a given patient, potentially leading to sub-optimal clinical outcomes: lack of evidence on device performance, patient factors, physician factors, organizational and health system factors, and device and device market factors. In the absence of evidence from research or device registries, tacit knowledge from trusted colleagues and less-trusted industry representatives informed device choice. Patients were rarely engaged in decision-making. Physician preference for particular devices was a barrier to acquiring competency in devices potentially more suitable for patients. Access to suitable devices was further limited to the number of comparable devices on the market, local inventory and purchasing contract specifications.

Conclusions

This study revealed that decision-making about devices is complex, cognitively challenging and constrained by several factors limiting access to and use of devices that could optimize patient outcomes. Further research is needed to assess the impact of these constraints on clinical outcomes, and develop interventions that optimize decision-making about device choice for treating given patients.

Electronic supplementary material

The online version of this article (10.1186/s12911-017-0577-3) contains supplementary material, which is available to authorized users.

The PMA Scale: A Measure of Physicians' Motivation to Adopt Medical Devices

BACKGROUND

Studies have often stated that individual-level determinants are important drivers for the adoption of medical devices. Empirical evidence supporting this claim is, however, scarce. At the individual level, physicians' adoption motivation was often considered important in the context of adoption decisions, but a clear notion of its dimensions and corresponding measurement scales is not available.

OBJECTIVES

To develop and subsequently validate a scale to measure the motivation to adopt medical devices of hospital-based physicians.

METHODS

The development and validation of the physician-motivation-adoption (PMA) scale were based on a literature search, internal expert meetings, a pilot study with physicians, and a three-stage online survey. The data collected in the online survey were analyzed using exploratory factor analysis (EFA), and the PMA scale was revised according to the results. Confirmatory factor analysis (CFA) was conducted to test the results from the EFA in the third stage. Reliability and validity tests and subgroup analyses were also conducted.

RESULTS

Overall, 457 questionnaires were completed by medical personnel of the National Health Service England. The EFA favored a six-factor solution to appropriately describe physicians' motivation. The CFA confirmed the results from the EFA. Our tests indicated good reliability and validity of the PMA scale.

CONCLUSIONS

This is the first reliable and valid scale to measure physicians' adoption motivation. Future adoption studies assessing the individual level should include the PMA scale to obtain more information about the role of physicians' motivation in the broader adoption context.

The determinants of medical technology adoption in different decisional systems: A systematic literature review

Studies of determinants of adoption of new medical technology have failed to coalesce into coherent knowledge. A flaw obscuring strong patterns may be a common habit of treating a wide range of health care innovations as a generic technology. We postulate three decisional systems that apply to different medical technologies with distinctive expertise, interest, and authority: medical-individualistic, fiscal-managerial, and strategic-institutional decisional systems. This review aims to examine the determinants of the adoption of medical technologies based on the corresponding decision-making system. We included quantitative and qualitative studies that analyzed factors facilitating or inhibiting the adoption of medical technologies. In total, 65 studies published between 1974 and 2014 met our inclusion criteria. These studies contained 688 occurrences of variables that were used to examine the adoption decisions, and we subsequently condensed these variables to 62 determinants in four main categories: organizational, individual, environmental, and innovation-related. The determinants and their empirical association with adoption were grouped and analyzed by the three decision-making systems. Although we did not identify substantial differences across the decision-making systems in terms of the direction of the determinants' influence on adoption, a clear pattern emerged in terms of the categories of determinants that were targeted in different decision-making systems.

Teaching Hospitals and the Disconnect Between Technology Adoption and Comparative Effectiveness Research: The Case of the Surgical Robot

The surgical robot, a costly technology for treatment of prostate cancer with equivocal marginal benefit, rapidly diffused into clinical practice. We sought to evaluate the role of teaching in the early adoption phase of the surgical robot. Teaching hospitals were the primary early adopters: data from the Healthcare Cost and Utilization Project showed that surgical robots were acquired by 45.5% of major teaching, 18.0% of minor teaching and 8.0% of non-teaching hospitals during the early adoption phase. However, teaching hospital faculty produced little comparative effectiveness research: By 2008, only 24 published studies compared robotic prostatectomy outcomes to those of conventional techniques. Just ten of these studies (41.7%) were more than minimally powered, and only six (25%) involved cross-institutional collaborations. In adopting the surgical robot, teaching hospitals fulfilled their mission to innovate, but failed to generate corresponding scientific evidence.