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Background Successful implementation and utilization of Computerized Clinical Decision Support Systems (CDSS) in hospitals is complex and challenging. Implementation science, and in particular the Nonadoption, Abandonment, Scale-up, Spread and Sustainability (NASSS) framework, may offer a systematic approach for identifying and addressing these challenges. This review aimed to identify, categorize, and describe barriers and facilitators to CDSS implementation in hospital settings and map them to the NASSS framework. Exploring the applicability of the NASSS framework to CDSS implementation was a secondary aim. Methods Electronic database searches were conducted (21 July 2020; updated 5 April 2022) in Ovid MEDLINE, Embase, Scopus, PyscInfo, and CINAHL. Original research studies reporting on measured or perceived barriers and/or facilitators to implementation and adoption of CDSS in hospital settings, or attitudes of healthcare professionals towards CDSS were included. Articles with a primary focus on CDSS development were excluded. No language or date restrictions were applied. We used qualitative content analysis to identify determinants and organize them into higher-order themes, which were then reflexively mapped to the NASSS framework. Results Forty-four publications were included. These comprised a range of study designs, geographic locations, participants, technology types, CDSS functions, and clinical contexts of implementation. A total of 227 individual barriers and 130 individual facilitators were identified across the included studies. The most commonly reported influences on implementation were fit of CDSS with workflows (19 studies), the usefulness of the CDSS output in practice (17 studies), CDSS technical dependencies and design (16 studies), trust of users in the CDSS input data and evidence base (15 studies), and the contextual fit of the CDSS with the user’s role or clinical setting (14 studies). Most determinants could be appropriately categorized into domains of the NASSS framework with barriers and facilitators in the “Technology,” “Organization,” and “Adopters” domains most frequently reported. No determinants were assigned to the “Embedding and Adaptation Over Time” domain. Conclusions This review identified the most common determinants which could be targeted for modification to either remove barriers or facilitate the adoption and use of CDSS within hospitals. Greater adoption of implementation theory should be encouraged to support CDSS implementation.

Background The growth in online qualitative research and data collection provides several advantages for health service researchers and participants, including convenience and extended geographic reach. However, these online processes can also present unexpected challenges, including instances of participant fraud or scam behaviour. This study describes an incident of participant fraud identified during online focus group discussions and interviews for a PhD health services research project on paediatric neurodevelopmental care. Methods We aimed to recruit carers of Australian children with neurodevelopmental disorders. Potential participants were recruited via a publicly available social media advert on Facebook offering $50 AUD compensation. Those who expressed interest via email ( n  = 254) were sent a pre-interview Qualtrics survey to complete. We identified imposters at an early stage via inconsistencies in their self-reported geographical location and that captured by the survey as well as recognition of suspicious actions before, during and after focus group discussions and interviews. Results Interest in participation was unexpectedly high. We determined that all potential participants were likely imposters, posing as multiple individuals and using different IP addresses across Nigeria, Australia, and the United States. In doing so, we were able to characterise several “red flags” for identifying imposter participants, particularly those posing as multiple individuals. These comprise a combination of factors including large volumes and strange timings of email responses, unlikely demographic characteristics, short or vague interviews, a preference for nonvisual participation, fixation on monetary compensation, and inconsistencies in reported geographical location. Additionally, we propose several strategies to combat this issue such as providing proof of location or eligibility during recruitment and data collection, examining email and consent form patterns, and comparing demographic data with regional statistics. Conclusions The emergent risk of imposter participants is an important consideration for those seeking to conduct health services research using qualitative approaches in online environments. Methodological design choices intended to improve equity and access for the target population may have an unintended consequence of improving access for fraudulent actors unless appropriate risk mitigation strategies are also employed. Lessons learned from this experience are likely to be valuable for novice health service researchers involved in online focus group discussions and interviews.

Falls are the most frequent adverse events that are reported in hospitals. We examined the effectiveness of individualised falls-prevention education for patients, supported by training and feedback for staff, delivered as a ward-level programme. Eight rehabilitation units in general hospitals in Australia participated in this stepped-wedge, cluster-randomised study, undertaken during a 50 week period. Units were randomly assigned to intervention or control groups by use of computer-generated, random allocation sequences. We included patients admitted to the unit during the study with a Mini-Mental State Examination (MMSE) score of more than 23/30 to receive individualised education that was based on principles of changes in health behaviour from a trained health professional, in addition to usual care. We provided information about patients' goals, feedback about the ward environment, and perceived barriers to engagement in falls-prevention strategies to staff who were trained to support the uptake of strategies by patients. The coprimary outcome measures were patient rate of falls per 1000 patient-days and the proportion of patients who were fallers. All analyses were by intention to treat. This trial is registered with the Australian New Zealand Clinical Trials registry, number ACTRN12612000877886). Between Jan 13, and Dec 27, 2013, 3606 patients were admitted to the eight units (n=1983 control period; n=1623 intervention period). There were fewer falls (n=196, 7·80/1000 patient-days vs n=380, 13·78/1000 patient-days, adjusted rate ratio 0·60 [robust 95% CI 0·42–0·94], p=0·003), injurious falls (n=66, 2·63/1000 patient-days vs 131, 4·75/1000 patient-days, 0·65 [robust 95% CI 0·42–0·88], p=0·006), and fallers (n=136 [8·38%] vs n=248 [12·51%] adjusted odds ratio 0·55 [robust 95% CI 0·38 to 0·81], p=0·003) in the intervention compared with the control group. There was no significant difference in length of stay (intervention median 11 days [IQR 7–19], control 10 days [6–18]). Individualised patient education programmes combined with training and feedback to staff added to usual care reduces the rates of falls and injurious falls in older patients in rehabilitation hospital-units. State Health Research Advisory Council, Department of Health, Government of Western Australia.

Background It is important to determine the relative value of health innovations when allocating limited healthcare resources. Implementation strategies require and consume healthcare resources yet are often excluded from published economic evaluations. This paper reports on the development of a pragmatic implementation costing instrument to assist with the planning, delivery, and evaluation of digital health implementation strategies. Methods A modified e-Delphi process was adopted to develop an implementation costing instrument. Purposive sampling was used to recruit a panel of experts in implementation science, health economic evaluations and/or digital health from the academic, government, clinical or health service sectors. In each round, participants were sent an electronic questionnaire and a prototype of the implementation costing instrument. The prototype in the initial round was informed from a literature review and qualitative interview findings. The prototype was updated iteratively between rounds in response to the panel’s feedback. In subsequent rounds, participants also received the anonymous results of items that did not reach consensus in the previous round. Termination occurred once consensus was reached on integral questions (those pertaining specifically to the instrument design) or when three rounds were completed, to prevent sample fatigue. Consensus was defined as at least 75% of experts in agreement for any item. Results Consensus was reached on the core components and design of the instrument from a panel of twelve experts in implementation science, health economic evaluations and/or digital health. Areas where consensus was not reached included users’ level of implementation science knowledge, specificity of the tool to digital health and accessibility via digital formats. Conclusions Cost-IS is a pragmatic data collection instrument designed to estimate the costs of implementation strategies for digital health solutions. Further piloting of Cost-IS is required to establish its feasibility and generalisability.

Patient non-attendance remains a major challenge for health services. Few studies have examined how health service providers think about, potentially address, and prioritise non-attendance within the scope of their practice. This study aimed to (1) explore healthcare professionals' perspectives, beliefs, and opinions about the impact of patient non-attendance within a publicly-funded outpatient physiotherapy clinic context; (2) explore perceived barriers and facilitators associated with the implementation of non-attendance mitigation strategies; and (3) identify health service staff generated solutions to address perceived barriers and enhance facilitators. A focus group discussion and semi-structured interviews were conducted between June 2023 to January 2024 with 27 physiotherapy department clinic outpatient staff involved in operationalising clinic referral processing, appointment scheduling, or providing care to patients. Data was analysed using a hybrid inductive/deductive framework analysis approach. Participants indicated that non-attendance had predominantly negative implications for the health service, healthcare provider, and patient. The interconnected issue of non-attendance encompassed multiple areas and were broadly categorised into five inductively identified themes: impact of non-attendance, perceptions of value, material deprivation, service delivery and built environment, and professional role and identity. Non-attendance mitigation strategies generated by participants were deductively mapped to the theoretical domains framework (TDF) to explore behavioural determinants that may influence successful implementation. This included knowledge, reinforcement, goals, optimism, memory, attention and decision-making, environmental resources and context, and emotions. Staff identified multiple strategies for reducing non-attendance; implementing many of these strategies would require additional resourcing. Research determining the effectiveness of such strategies both in the short-term and long-term following implementation into practice remains a priority for future investigation.

Optimal burn scar management has the potential to markedly improve the lives of children, but can require substantial healthcare resources. The study aimed to examine the cost-effectiveness of three scar management interventions: pressure garment; topical silicone gel; combined pressure garment and topical silicone gel therapy, alongside a randomised controlled trial of these interventions. Participants were children (n = 153) referred for burn scar management following grafting, spontaneous healing after acute burn injury, or reconstructive surgery. Healthcare resource use was costed from a health service perspective (6-months post-burn time-horizon). The mean total scar management cost was lowest in the topical silicone gel group ($382.87 (95% CI $337.72, $443.29)) compared to the pressure garment ($1327.02 (95% CI $1081.46, $1659.95)) and combined intervention $1605.97 ($1077.65, $2694.23)) groups. There were no significant between-group differences in Quality Adjusted Life Year estimates. There was a 70% probability that topical silicone gel dominated pressure garment therapy (was cheaper and more effective), a 29% probability that pressure garment therapy dominated combined therapy, and a 63% probability that topical silicone gel dominated combined therapy. In conclusion, topical silicone gel was the cheaper intervention, and may be favoured in the absence of clear clinical effect favouring pressure garment therapy or a combination of these management approaches. Trial registration: ACTRN12616001100482 (prospectively registered).

Computerized clinical decision support systems (CDSSs) are essential components of modern health system service delivery, particularly within acute care settings such as hospitals. Theories, models, and frameworks may assist in facilitating the implementation processes associated with CDSS innovation and its use within these care settings. These processes include context assessments to identify key determinants, implementation plans for adoption, promoting ongoing uptake, adherence, and long-term evaluation. However, there has been no prior review synthesizing the literature regarding the theories, models, and frameworks that have informed the implementation and adoption of CDSSs within hospitals. This scoping review aims to identify the theory, model, and framework approaches that have been used to facilitate the implementation and adoption of CDSSs in tertiary health care settings, including hospitals. The rationales reported for selecting these approaches, including the limitations and strengths, are described. A total of 5 electronic databases were searched (CINAHL via EBSCOhost, PubMed, Scopus, PsycINFO, and Embase) to identify studies that implemented or adopted a CDSS in a tertiary health care setting using an implementation theory, model, or framework. No date or language limits were applied. A narrative synthesis was conducted using full-text publications and abstracts. Implementation phases were classified according to the \"Active Implementation Framework stages\": exploration (feasibility and organizational readiness), installation (organizational preparation), initial implementation (initiating implementation, ie, training), full implementation (sustainment), and nontranslational effectiveness studies. A total of 81 records (42 full text and 39 abstracts) were included. Full-text studies and abstracts are reported separately. For full-text studies, models (18/42, 43%), followed by determinants frameworks (14/42,33%), were most frequently used to guide adoption and evaluation strategies. Most studies (36/42, 86%) did not list the limitations associated with applying a specific theory, model, or framework. Models and related quality improvement methods were most frequently used to inform CDSS adoption. Models were not typically combined with each other or with theory to inform full-cycle implementation strategies. The findings highlight a gap in the application of implementation methods including theories, models, and frameworks to facilitate full-cycle implementation strategies for hospital CDSSs.

Effective and resource-efficient long-term management of multimorbidity is one of the greatest health-related challenges facing patients, health professionals, and society more broadly. The purpose of this review was to provide a synthesis of literature examining multimorbidity and resource utilization, including implications for cost-effectiveness estimates and resource allocation decision making. In summary, previous literature has reported substantially greater, near exponential, increases in health care costs and resource utilization when additional chronic comorbid conditions are present. Increased health care costs have been linked to elevated rates of primary care and specialist physician occasions of service, medication use, emergency department presentations, and hospital admissions (both frequency of admissions and bed days occupied). There is currently a paucity of cost-effectiveness information for chronic disease interventions originating from patient samples with multimorbidity. The scarcity of robust economic evaluations in the field represents a considerable challenge for resource allocation decision making intended to reduce the burden of multimorbidity in resource-constrained health care systems. Nonetheless, the few cost-effectiveness studies that are available provide valuable insight into the potential positive and cost-effective impact that interventions may have among patients with multiple comorbidities. These studies also highlight some of the pragmatic and methodological challenges underlying the conduct of economic evaluations among people who may have advanced age, frailty, and disadvantageous socioeconomic circumstances, and where long-term follow-up may be required to directly observe sustained and measurable health and quality of life benefits. Research in the field has indicated that the impact of multimorbidity on health care costs and resources will likely differ across health systems, regions, disease combinations, and person-specific factors (including social disadvantage and age), which represent important considerations for health service planning. Important priorities for research include economic evaluations of interventions, services, or health system approaches that can remediate the burden of multimorbidity in safe and cost-effective ways.

Background The importance of accurately costing implementation strategies is increasingly recognised within the field of implementation science. However, there is a lack of methodological guidance for costing implementation, particularly within digital health settings. This study reports on a systematic review of costing analyses conducted alongside implementation of hospital-based computerised decision support systems. Methods PubMed, Embase, Scopus and CINAHL databases were searched between January 2010 and August 2021. Two reviewers independently screened and selected original research studies that were conducted in a hospital setting, examined the implementation of a computerised decision support systems and reported implementation costs. The Expert Recommendations for Implementing Change Framework was used to identify and categorise implementation strategies into clusters. A previously published costing framework was applied to describe the methods used to measure and value implementation costs. The reporting quality of included studies was assessed using the Consolidated Health Economic Evaluation Reporting Standards checklist. Results Titles and abstracts of 1836 articles were screened, with nine articles eligible for inclusion in the review. Implementation costs were most frequently reported under the ‘evaluative and iterative strategies’ cluster, followed by ‘provide interactive assistance’. Labour was the largest implementation-related cost in the included papers, irrespective of implementation strategy. Other reported costs included consumables, durable assets and physical space, which was mostly associated with stakeholder training. The methods used to cost implementation were often unclear. There was variation across studies in the overall quality of reporting. Conclusions A relatively small number of papers have described computerised decision support systems implementation costs, and the methods used to measure and value these costs were not well reported. Priorities for future research should include establishing consistent terminology and appropriate methods for estimating and reporting on implementation costs. Trial registration The review protocol is registered with PROSPERO (ID: CRD42021272948).

Hospital in the home (HITH) provides home-based care as an alternative to traditional hospitalization. In response to the COVID-19 Omicron wave, a public hospital in the rural Western portion of Southeast Queensland implemented a virtual HITH service to support adults, maternity patients, and children with moderate COVID-19 symptoms and additional health concerns. Although the pandemic accelerated the uptake of virtual care within HITH models, existing literature has focused on clinical outcomes, with limited evidence on key implementation outcomes. Using the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework, this study evaluated the implementation of the virtual COVID-19 HITH service and identified factors influencing its implementation, to inform ongoing service development and support potential scaling of this model of care. The RE-AIM implementation science framework was selected to guide the evaluation, capturing both clinical and contextual dimensions of implementation at both individual and organizational levels. Quantitative data on service usage and costs were retrospectively extracted from electronic medical records and finance records, while patient experience data were drawn from patient-reported experience measures surveys. Qualitative data were collected through one-on-one interviews with patients and staff. All data sources were analyzed separately and then triangulated within the RE-AIM framework to understand what occurred, how, and why. The service admitted 3192 patients, most of whom were female (2027/3192, 63.5%), English-speaking (3140/3192, 98.4%), and residing in socioeconomically disadvantaged areas (1879/3192, 58.9%) (reach). The model was feasible and safe to implement, managing 3240 admissions with no reported deaths. Patients valued continuous access to care and described better recovery experiences at home (effectiveness). Staff viewed the model as appropriate for identifying and managing high-risk patients in the community, easing pressure on hospital beds (adoption). The service cost Aus $ 5.4 million (US $3.5 million) over 11 months. Implementation barriers included the urgency of the pandemic scenario, limited infrastructure and human resources, and changing requirements in relation to COVID-19. These were mitigated by several people factors that were critical to its successful implementation, including a consultant-led structure, staff commitment, and adaptability (implementation). The service saved 16,651 inpatient bed days before being integrated into core HITH operations. The experience strengthened staff capabilities in emergency response, virtual care delivery, and strategic planning. The model shows promise for broader application into pediatric care, though further work is needed to enhance interdepartmental collaboration and staff recognition (maintenance). This study demonstrated that a virtual HITH model can be implemented effectively and safely at scale. Findings support its potential for integration into routine care, provided that adequate resource planning, a skilled and multidisciplinary workforce, well-defined care pathways, and equity-focused strategies are in place.