Factors that Promote and Protect Against Financial Toxicity after Orthopaedic Trauma: A Qualitative Study.

INTRODUCTION: Financial toxicity is highly prevalent in patients after an orthopaedic injury. However, little is known regarding the conditions that promote and protect against this financial distress. Our objective was to understand the factors that cause and protect against financial toxicity after a lower extremity fracture. METHODS: A qualitative study was conducted using semi-structured interviews with 20 patients 3 months after surgical treatment of a lower extremity fracture. The interviews were audio-recorded, transcribed verbatim, and analyzed using thematic analysis to identify themes and subthemes. Data saturation occurred after 15 interviews. The percentage of patients who described the identified themes are reported. RESULTS: A total of 20 patients (median age, 44 years [IQR, 38 to 58]; 60% male) participated in the study. The most common injury was a distal tibia fracture (n = 8; 40%). Eleven themes that promoted financial distress were identified, the most common being work effects (n = 14; 70%) and emotional health (n = 12; 60%). Over half (n = 11; 55%) of participants described financial toxicity arising from an inability to access social welfare programs. Seven themes that protected against financial distress were also identified, including insurance (n = 17; 85%) and support from friends and family (n = 17; 85%). Over half (n = 13; 65%) of the participants discussed the support they received from their healthcare team, which encompassed expectation setting and connections to financial aid and other services. Employment protection and workplace flexibility were additional protective themes. CONCLUSION: This qualitative study of orthopaedic trauma patients found work and emotional health-related factors to be primary drivers of financial toxicity after injury. Insurance and support from friends and family were the most frequently reported protective factors. Many participants described the pivotal role of the healthcare team in establishing recovery expectations and facilitating access to social welfare programs.

Subgroups of High-cost Patients and Their Preventable Inpatient Cost in Rural China.

BACKGROUND: High-cost patients account for most healthcare costs and are highly heterogeneous. This study aims to classify high-cost patients into clinically homogeneous subgroups, describe healthcare utilization patterns of subgroups, and identify subgroups with relatively high preventable inpatient cost (PIC) in rural China. METHODS: A population-based retrospective study was performed using claims data in Xi County, Henan Province. 32,108 high-cost patients, representing the top 10% of individuals with the highest total spending, were identified. A density-based clustering algorithm combined with expert opinions were used to group high-cost patients. Healthcare utilization (including admissions, length of stay and outpatient visits) and spending characteristics (including total spending, and the proportion of PIC, inpatient and out-of-pocket spending on total spending) were described among subgroups. PIC was calculated based on potentially preventable hospitalizations which were identified according to the Agency for Healthcare Research and Quality Prevention Quality Indicators algorithm. RESULTS: High-cost patients were more likely to be older (M=51.87, SD=22.28), male (49.03%) and from poverty-stricken families (37.67%) than non-high-cost patients, with 2.49 (SD=2.47) admissions and 3.25 (SD=4.52) outpatient visits annually. Fourteen subgroups of high-cost patients were identified: chronic disease, non-trauma diseases which need surgery, female disease, cancer, eye disease, respiratory infection/inflammation, skin disease, fracture, liver disease, vertigo syndrome and cerebral infarction, mental disease, arthritis, renal failure, other neurological disorders. The annual admissions ranged from 1.83 (SD=1.23, fracture) to 12.21 (SD=9.26, renal failure), and the average length of stay ranged from 6.61 (SD=10.00, eye disease) to 32.11 (SD=28.78, mental disease) days among subgroups. The chronic disease subgroup showed the largest proportion of PIC on total spending (10.57%). CONCLUSION: High-cost patients were classified into 14 clinically distinct subgroups which had different healthcare utilization and spending characteristics. Different targeted strategies may be needed for subgroups to reduce preventable hospitalizations. Priority should be given to high-cost patients with chronic diseases.

Health system performance assessment: embedding resilience through performance intelligence.

Health systems around the world are facing challenges in achieving their goals. In the wake of the coronavirus disease pandemic, the need for resilient health systems has become even more apparent. This article argues that embedding resilience into health system performance assessment (HSPA) frameworks can be a valuable approach for improving health system performance. This perspective examines key challenges threatening health systems and makes a case for the continued relevance of HSPA by embedding resilience-related performance intelligence.

Acute care pathway assessed through performance indicators during the COVID-19 pandemic in OECD countries (2020-2021): a scoping review.

BACKGROUND: The COVID-19 pandemic severely impacted care for non-COVID patients. Performance indicators to monitor acute care, timely reported and internationally accepted, lacked during the pandemic in OECD countries. This study aims to summarize the performance indicators available in the literature to monitor changes in the quality of acute care in OECD countries during the first year and a half of the pandemic (2020-July 2021) and to assess their trends. METHODS: Scoping review. Search in Embase and MEDLINE (07-07-2022). Acute care performance indicators and indicators related to acute general surgery were collected and collated following a care pathway approach. Indicators assessing identical clinical measures were grouped under a common indicator title. The trends from each group of indicators were collated (increase/decrease/stable). RESULTS: A total of 152 studies were included. 2354 indicators regarding general acute care and 301 indicators related to acute general surgery were included. Indicators focusing on pre-hospital services reported a decreasing trend in the volume of patients: from 225 indicators, 110 (49%) reported a decrease. An increasing trend in pre-hospital treatment times was reported by most of the indicators (n = 41;70%) and a decreasing trend in survival rates of out-of-hospital cardiac arrest (n = 61;75%). Concerning care provided in the emergency department, most of the indicators (n = 752;71%) showed a decreasing trend in admissions across all levels of urgency. Concerning the mortality rate after admission, most of the indicators (n = 23;53%) reported an increasing trend. The subset of indicators assessing acute general surgery showed a decreasing trend in the volume of patients (n = 50;49%), stability in clinical severity at admission (n = 36;53%), and in the volume of surgeries (n = 14;47%). Most of the indicators (n = 28;65%) reported no change in treatment approach and stable mortality rate (n = 11,69%). CONCLUSION: This review signals relevant disruptions across the acute care pathway. A subset of general surgery performance indicators showed stability in most of the phases of the care pathway. These results highlight the relevance of assessing this care pathway more regularly and systematically across different clinical entities to monitor disruptions and to improve the resilience of emergency services during a crisis.

Exploring Inequalities in the Use, Quality, and Outcome of the Diabetes Management Program of Indonesian National Health Insurance.

Introduction: Access to diabetes management programs is crucial to control the increasing contribution of diabetes to the global burden of disease. However, evidence regarding whether such services are equally accessible for all population groups is still lacking, particularly in the context of low-middle-income countries and under the National Health Insurance (NHI). This study aimed to assess the extent of socioeconomic and geographical inequalities in the use, quality, and outcome of a diabetes management program for beneficiaries of Indonesian NHI. Methods: A total of 628 participants in the NHI diabetes management program in Banyumas District, Indonesia, were included in 2021 in this cross-sectional study. The main variables measured were regular visits to primary care facilities, standard medication, and glycemic control. The rate difference and rate ratio of age-sex standardized prevalence rates, as well as multiple logistic regressions, were used to measure the extent of inequalities. Results: Around 70% of participants regularly visited primary care facilities and received standard medication, but only 35% had good glycemic control. Highly educated participants were more likely to have regular visits compared to low-educated participants (odds ratio [OR] 1.92; 95% confidence interval [95% CI]: 1.04-3.56). Based on employment and type of NHI beneficiaries, a small extent and even reverse inequalities were found although these findings were insignificant statistically. Urban residents were also more likely to have regular visits (OR 6.61; 95% CI: 2.90-15.08), receive standard medication (OR 9.73; 95% CI: 3.66-25.90), and have good glycemic control (OR 3.85; 95% CI: 1.68-8.83) compared to rural residents. Conclusions: Evidence on the extent of socioeconomic inequalities is inconclusive but substantial geographical inequalities in the use, quality, and outcome of diabetes management programs exist among Indonesian NHI beneficiaries. Future implementation policies of the program should consider particularly the geographical characteristics of participants to avoid and reduce inequalities and, hence, the disease burden of diabetes.

Citizen engagement in healthcare procurement decision-making by healthcare insurers: recent experiences in the Netherlands.

BACKGROUND: In insurance-based healthcare systems, healthcare insurers are interested in engaging citizens in care procurement to contract healthcare services that matter to people. In the Netherlands, an amendment to the Health Insurance Act was set forth in 2021 to formalize and strengthen the engagement of the insured population with healthcare insurers' procurement cycles. This study explores the role of Dutch healthcare insurers in operationalizing citizen engagement in procurement cycles before changes occur linked to the amendment to the Health Insurance Act. METHODS: A phenomenological qualitative design was employed in two phases: (1) we consulted academics and policy experts on the role of healthcare insurers regarding citizen engagement; (2) we conducted focus groups with representatives of healthcare insurers to understand how citizens' engagement is being operationalized. Transcripts of the interviews with experts and detailed notes of focus group meetings were analysed using a qualitative inductive approach. Selected excerpts were analysed on discourse and content and organized by a coding scheme following a rigorous and accelerated data reduction technique. RESULTS: We identified four strategies used by healthcare insurers to operationalize citizen engagement: (1) broadening their population health orientation; (2) developing and improving mechanisms for engaging citizens; (3) strengthening features of data governance for effective use of value-driven data; (4) implementing financial and incentive mechanisms among healthcare providers in support of value-based healthcare. However, regulated market mechanisms and low institutional trust in healthcare insurers undermine their transition from merely funding healthcare towards becoming people-centred value-based healthcare purchasers. CONCLUSION: Dutch healthcare insurers seem to be strengthening the community orientation of their functioning while enhancing the end-to-end experience of the insured. The expected practical effects of the amendment to the Health Insurance Act include broadening the role of the council of insurees in decision-making processes and systematically documenting the efforts set forth by healthcare insurers in engaging citizens. Further research is needed to better understand how the regulated competitive market could be hampering the engagement of citizens in healthcare procurement decision-making and value creation from the citizens' perspective.

Status of the health information system in Ireland and its fitness to support health system performance assessment: a multimethod assessment based on stakeholder involvement.

BACKGROUND: Between 2019 and 2021, the first Irish health system performance assessment (HSPA) framework was developed. As routinely collected health data are necessary to continuously populate indicators of an HSPA framework, a purpose-driven assessment of the health information system (HIS) in Ireland and its fitness to support the implementation of an HSPA framework was conducted. This study reports on the status of the Irish HIS through a multimethod assessment based on continuous broad stakeholder involvement. METHODS: Between May and November 2020, over 50 informants were engaged in individual and group interviews and stakeholder consultation workshops as part of the HIS assessment process. Descriptive themes and high-level data availability heatmaps were derived from interview and workshop data using thematic analysis. Indicator "passports" for the HSPA framework were populated during stakeholder consultation workshops and analysed using univariate descriptive statistics. RESULTS: The HIS in Ireland was able to provide administrative, survey and registry-based data for public sector acute care services, focusing on structure, process and output metrics. Significant data availability gaps, most notably from primary care, private hospitals and community care, were reported, with little availability of electronic health record and people-reported data. Data on outcome metrics were mostly missing, as were linkage possibilities across datasets for care pathway monitoring. The COVID-19 pandemic highlighted the national HIS's shortcomings but also the capacity for rapid development and improvement. CONCLUSIONS: A tailor-made assessment of the HIS in Ireland, involving a broad set of relevant stakeholders, revealed strengths, weaknesses and areas for improvement in the Irish health data landscape. It also contributed to the development of a national HSPA framework and momentum to further strengthen data infrastructure and governance, while working towards a more data-driven and person-centred healthcare system. This work demonstrates the utility of an inclusive HIS assessment process and is applicable beyond Ireland, where this case study was conducted.

Characterizing Potentially Preventable Hospitalizations of High-Cost Patients in Rural China.

INTRODUCTION: High-cost patients are characterized by repeated hospitalizations, and inpatient cost accounts for a large proportion of their total health care spending. This study aimed to assess the occurrence and costs of potentially preventable hospitalizations and explore contributing factors among high-cost patients in rural China. METHODS: We examined a population-based sample of patients using the 2016 New Rural Cooperative Medical Scheme in Dangyang city, China. Eighteen thousand forty-three high-cost patients were identified. A validated tool and logistic regression analysis were used to determine preventable hospitalizations and their patient-level and supply-side factors. RESULTS: High-cost patients were older (average age of 54 years) than non-high-cost patients (50 years) and more likely to come from poverty-stricken families. The occurrence of preventable hospitalization was 21.65% among high-cost patients. The proportion of preventable inpatient cost in total inpatient and outpatient expenditure among high-cost patients (5.81%) was lower than that of non-high-cost patients (7.88%) but accounted for 75.87% of the overall preventable inpatient cost. High-cost patients with more hospitalizations were more likely to experience preventable hospitalization, and those with heart failure, COPD, diabetes and mixed conditions were at a higher risk of preventable hospitalization, while those with more outpatient visits were less likely to show preventable hospitalization. CONCLUSIONS: The occurrence of preventable hospitalization among high-cost patients in rural China was sizeable. The preventable inpatient cost of the overall population was concentrated among high-cost patients. Interventions such as improving preventive care and disease management targeting high-cost patients within counties may improve patients' health outcomes and quality of life and reduce overall preventable inpatient cost.

Implementing structured follow-up of neonatal and paediatric patients: an evaluation of three university hospital case studies using the functional resonance analysis method.

BACKGROUND: In complex critical neonatal and paediatric clinical practice, little is known about long-term patient outcomes and what follow-up care is most valuable for patients. Emma Children's Hospital, Amsterdam UMC (Netherlands), implemented a follow-up programme called Follow Me for neonatal and paediatric patient groups, to gain more insight into long-term outcomes and to use such outcomes to implement a learning cycle for clinical practice, improve follow-up care and facilitate research. Three departments initiated re-engineering and change processes. Each introduced multidisciplinary approaches to long-term follow-up, including regular standardised check-ups for defined age groups, based on medical indicators, developmental progress, and psychosocial outcomes in patients and their families. This research evaluates the implementation of the three follow-up programmes, comparing predefined procedures (work-as-imagined) with how the programmes were implemented in practice (work-as-done). METHODS: This study was conducted in 2019-2020 in the outpatient settings of the neonatal intensive care, paediatric intensive care and paediatric surgery departments of Emma Children's Hospital. It focused on the organisational structure of the follow-up care. The functional resonance analysis method (FRAM) was applied, using documentary analysis, semi-structured interviews, observations and feedback sessions. RESULTS: One work-as-imagined model and four work-as-done models were described. The results showed vast data collection on medical, developmental and psychosocial indicators in all work-as-done models; however, process indicators for programme effectiveness and performance were missing. In practice there was a diverse allocation of roles and responsibilities and their interrelations to create a multidisciplinary team; there was no one-size-fits-all across the different departments. Although control and feedback loops for long-term outcomes were specified with respect to the follow-up groups within the programmes, they were found to overlap and misalign with other internal and external long-term outcome monitoring practices. CONCLUSION: Implementing structured long-term follow-up may provide insights for improving daily practice and follow-up care, with the precondition of standardised measurements. Lessons learned from practice are (1) to address fragmentation in data collection and storage, (2) to incorporate the diverse ways to create a multidisciplinary team in practice, and (3) to include timely actionable indicators on programme effectiveness and performance, alongside medical, developmental and psychosocial indicators.

Engaging citizens in the development of a health system performance assessment framework: a case study in Ireland.

BACKGROUND: The launch in 2017 of the Irish 10-year reform programme Sláintecare represents a key commitment in the future of the health system. An important component of the programme was the development of a health system performance assessment (HSPA) framework. In 2019, the Department of Health of Ireland (DoH) and Health Service Executive (HSE) commissioned the technical support of researchers to develop an outcome-oriented HSPA framework which should reflect the shared priorities of multiple stakeholders, including citizens. This study describes the method applied in the Irish context and reflects on the added value of using a citizen panel in the development of an HSPA framework. METHODS: A panel of 15 citizens was convened, recruited by a third-party company using a sampling strategy to achieve a balanced mix representing the Irish society. Panellists received lay-language preparatory materials before the meeting. Panellists used a three-colour scheme to signal the importance of performance measures. An exit questionnaire was administered to understand how participants experienced being part of the panel. The citizen panel was the first in a series of three panels towards the development of the HSPA framework, followed by panels including representatives of the DoH and HSE, and representatives from professional associations and special interest groups. RESULTS: The citizen panel generated 249 health performance measures ranging across 13 domains. Top-ranking domains to the citizen panel (people-centredness, coordination of care, and coverage) were less prioritized by the other panels; domains less prioritized by the citizen panel, such as accessibility, responsiveness, efficiency, and effectiveness, were of higher priority in the other panels. Citizen panellists shared a similar understanding of what a citizen panel involves and described their experience at the panel as enjoyable, interesting, and informative. CONCLUSIONS: The priorities of the citizen panel were accounted for during all phases of developing the HSPA framework. This was possible by adopting an inclusive development process and by engaging citizens early on. Citizen engagement in HSPA development is essential for realizing citizen-driven healthcare system performance and generating trust and ownership in performance intelligence. Future research could expand the use of citizen panels to assess, monitor, and report on the performance of healthcare systems.

Development and Actionability of the Dutch COVID-19 Dashboard: Descriptive Assessment and Expert Appraisal Study.

BACKGROUND: Web-based public reporting by means of dashboards has become an essential tool for governments worldwide to monitor COVID-19 information and communicate it to the public. The actionability of such dashboards is determined by their fitness for purpose-meeting a specific information need-and fitness for use-placing the right information into the right hands at the right time and in a manner that can be understood. OBJECTIVE: The aim of this study was to identify specific areas where the actionability of the Dutch government's COVID-19 dashboard could be improved, with the ultimate goal of enhancing public understanding of the pandemic. METHODS: The study was conducted from February 2020 to April 2021. A mixed methods approach was carried out, using (1) a descriptive checklist over time to monitor changes made to the dashboard, (2) an actionability scoring of the dashboard to pinpoint areas for improvement, and (3) a reflection meeting with the dashboard development team to contextualize findings and discuss areas for improvement. RESULTS: The dashboard predominantly showed epidemiological information on COVID-19. It had been developed and adapted by adding more in-depth indicators, more geographic disaggregation options, and new indicator themes. It also changed in target audience from policy makers to the general public; thus, a homepage was added with the most important information, using news-like items to explain the provided indicators and conducting research to enhance public understanding of the dashboard. However, disaggregation options such as sex, socioeconomic status, and ethnicity and indicators on dual-track health system management and social and economic impact that have proven to give important insights in other countries are missing from the Dutch COVID-19 dashboard, limiting its actionability. CONCLUSIONS: The Dutch COVID-19 dashboard developed over time its fitness for purpose and use in terms of providing epidemiological information to the general public as a target audience. However, to strengthen the Dutch health system's ability to cope with upcoming phases of the COVID-19 pandemic or future public health emergencies, we advise (1) establishing timely indicators relating to health system capacity, (2) including relevant data disaggregation options (eg, sex, socioeconomic status), and (3) enabling interoperability between social, health, and economic data sources.

Exploring Changes to the Actionability of COVID-19 Dashboards Over the Course of 2020 in the Canadian Context: Descriptive Assessment and Expert Appraisal Study.

BACKGROUND: Public web-based COVID-19 dashboards are in use worldwide to communicate pandemic-related information. Actionability of dashboards, as a predictor of their potential use for data-driven decision-making, was assessed in a global study during the early stages of the pandemic. It revealed a widespread lack of features needed to support actionability. In view of the inherently dynamic nature of dashboards and their unprecedented speed of creation, the evolution of dashboards and changes to their actionability merit exploration. OBJECTIVE: We aimed to explore how COVID-19 dashboards evolved in the Canadian context during 2020 and whether the presence of actionability features changed over time. METHODS: We conducted a descriptive assessment of a pan-Canadian sample of COVID-19 dashboards (N=26), followed by an appraisal of changes to their actionability by a panel of expert scorers (N=8). Scorers assessed the dashboards at two points in time, July and November 2020, using an assessment tool informed by communication theory and health care performance intelligence. Applying the nominal group technique, scorers were grouped in panels of three, and evaluated the presence of the seven defined features of highly actionable dashboards at each time point. RESULTS: Improvements had been made to the dashboards over time. These predominantly involved data provision (specificity of geographic breakdowns, range of indicators reported, and explanations of data sources or calculations) and advancements enabled by the technologies employed (customization of time trends and interactive or visual chart elements). Further improvements in actionability were noted especially in features involving local-level data provision, time-trend reporting, and indicator management. No improvements were found in communicative elements (clarity of purpose and audience), while the use of storytelling techniques to narrate trends remained largely absent from the dashboards. CONCLUSIONS: Improvements to COVID-19 dashboards in the Canadian context during 2020 were seen mostly in data availability and dashboard technology. Further improving the actionability of dashboards for public reporting will require attention to both technical and organizational aspects of dashboard development. Such efforts would include better skill-mixing across disciplines, continued investment in data standards, and clearer mandates for their developers to ensure accountability and the development of purpose-driven dashboards.

Improving performance intelligence for governing an integrated health and social care delivery network: a case study on the Amsterdam Noord district.

BACKGROUND: A guiding principle of a successful integrated health and social care delivery network is to establish a governance approach based on learning, grounded in a data and knowledge infrastructure. The 'Krijtmolen Alliantie' is a network of health and social care providers with the ambition to realize such a performance intelligence driven governance model in line with the Triple Aim. This study seeks to identify what performance intelligence is available and how it can be improved. METHODS: This case study was conducted in the district of Amsterdam Noord, the Netherlands, and employed 23 semi-structured interviews with stakeholders in health and social care, a feasibility analysis of available administrative data, and a reflection meeting with board members of the 'Krijtmolen Alliantie'. Information needs for performance intelligence by the stakeholders were mapped and a data landscape of the district covered by the network was drafted. Finally, in the reflection meeting with board members of the 'Krijtmolen Alliantie' the information needs and data landscape were aligned with governing needs, resulting in priority domains around which to strengthen the data infrastructure for governance of the integrated health and social care delivery network. RESULTS: The 'Krijtmolen Alliantie' encompasses a network of providers with a diverse range of catchment areas. There are indicators on population health and welfare, however they have limited actionability for providers due to a misalignment with their respective catchment areas. There is a barrier in data exchange between health and social care providers. It is difficult to construct one indicator for per capita cost in the Dutch health data infrastructure as health and social care are subdivided in financing siloes. Priority domains for improvement of performance intelligence for the 'Krijtmolen Alliantie' are: 1) Per capita and per patient cost data integration that would allow combined accountability through aligning financial incentives to facilitate integrated care, and 2) combined patient experience and outcome measures to reflect network quality of care and patient experience performance. CONCLUSION: Available performance intelligence lacks actionability for the governance of integrated care networks. Our recommendation is to align performance intelligence with the regional governance responsibilities of stakeholders for health and social care delivery.

Association of Postoperative Infections After Fractures With Long-term Income Among Adults.

Importance: Postoperative infections after a fracture exert tremendous costs on the health care system. However, the patient economic burden associated with a postoperative infection is unclear. Objective: To evaluate the association between a postoperative infection and long-term income among patients with surgically treated fractures. Design, Setting, and Participants: A retrospective cohort study linked academic trauma center data with Maryland tax records using inverse probability of treatment weighting to estimate between-group differences among 11 673 adults who underwent surgery to treat fractures of the extremities or pelvis between January 1, 2003, and December 31, 2016. Statistical analysis was performed from November 5, 2019, to August 30, 2020. Exposure: A postoperative infection within 1 year of injury. Main Outcomes and Measures: The primary outcome was the annual household income up to 6 years after injury. Household income incorporates multiple types of income, including wage earnings, taxable Social Security benefits, workers' compensation, and disability benefits. Secondary outcomes included individual earnings, Social Security benefits, unemployment benefits, and catastrophic income loss. Results: The study included 11 673 patients (7756 male patients [66.4%]; mean [SD] age, 45.2 [19.2] years) with a mean (SD) preinjury household income of $30 505 ($89 030). A total of 403 patients (3.5%) had a postoperative infection. Postoperative infections were associated with a $6080 annual decrease (95% CI, -$12 114 to -$47; P = .048) in household income in the 6 years after injury. Postoperative infections were associated with a 6.6% increase (95% CI, 4.9%-8.3%; P < .001) in the risk of catastrophic wage loss within 2 years of the fracture and were associated with a 45% increase in the odds of receiving Social Security benefits (odds ratio, 1.45; 95% CI, 1.25-1.68; P < .001). However, incurring a postoperative infection was not associated with an increase in the value of the Social Security benefits received. Conclusions and Relevance: This study suggests that postoperative infections have significant and sustained income-associated implications for patients who experience a fracture. Current Social Security mechanisms may not offset the decreased income.

Self-Reported Waiting Times for Outpatient Health Care Services in Hungary: Results of a Cross-Sectional Survey on a National Representative Sample.

(1) Background: System-level data on waiting time in the outpatient setting in Hungary is scarce. The objective of the study was to explore self-reported waiting time for an appointment and at a doctor's office. (2) Methods: An online, cross-sectional, self-administered survey was carried out in 2019 in Hungary among a representative sample (n = 1000) of the general adult population. Chi-squared test and logistic regression analysis were carried out to explore if socioeconomic characteristics, health status, or residence were associated with waiting times and the perception of waiting time as a problem. (3) Results: Proportions of 90%, 41%, and 64% of respondents were seen within a week by family doctor, public specialist, and private specialist, respectively. One-third of respondents waited more than a month to get an appointment with a public specialist. Respondents in better health status reported shorter waiting times; those respondents were less likely to perceive a problem with: (1) waiting time to get an appointment (OR = 0.400) and (2) waiting time at a doctor's office (OR = 0.519). (4) Conclusions: Longest waiting times were reported for public specialist visits, but waiting times were favorable for family doctors and private specialists. Further investigation is needed to better understand potential inequities affecting people in worse health status.

Analysis of Patient Income in the 5 Years Following a Fracture Treated Surgically.

Importance: Orthopedic injury is assumed to bear negative socioeconomic consequences. However, the magnitude and duration of a fracture's impact on patient income and social insurance benefits remain poorly quantified. Objective: To characterize the association between orthopedic injury and patient income using state tax records. Design, Setting, and Participants: This cohort study included adult patients surgically treated for an orthopedic fracture at a US academic trauma center from January 2003 through December 2014. Hospital data were linked to individual-level state tax records using a difference-in-differences analysis performed from November 2019 through August 2020. The control group comprised of data resampled from fracture patients at least 6 years prior to injury. Exposures: An operatively treated fracture of the appendicular skeleton. Main Outcomes and Measures: The primary outcome was individual annual earnings up to 5 years postinjury. Secondary outcomes included annual household income and US Social Security benefits for 5 years postinjury and catastrophic wage loss within 2 years of injury. Results: A total of 9997 fracture patients (mean [SD] age, 44.6 [18.9] years; 6725 [67.3%] men) to 34 570 prefracture control participants (mean [SD] age, 40.0 [20.5] years; 21 666 [62.7%] men). The median (interquartile range) of preinjury wage earnings was $16 847 ($0 to $52 221). The mean annual decline in individual earnings during the 5 years following injury was $9865 (95% CI, -$10 686 to -$8862). Annual household income declined by $5259 (95% CI, -$6337 to -$4181) over the same period. A fracture was associated with a $206 (95% CI, $147 to $265) mean annual increase in Social Security benefits in the 5 years after injury. An injury increased the risk of catastrophic wage loss by 11.6% (95% CI, 10.5% to 12.7%). Substantial relative income loss was observed in patients with preinjury earnings in the top 3 quartiles, but changes in income were negligible for patients with preinjury earnings in the bottom quartile (19%; 95% CI, -4% to 48%). Conclusions and Relevance: In this cohort study of patients surgically treated for an orthopedic fracture at a US academic trauma center, fractures were associated with substantial individual and household income loss up to 5 years after injury, and 1 in 5 patients sustained catastrophic income loss in the 2 years after fracture. Gains in Social Security benefits offset less than 10% of annual income losses.

Features Constituting Actionable COVID-19 Dashboards: Descriptive Assessment and Expert Appraisal of 158 Public Web-Based COVID-19 Dashboards.

BACKGROUND: Since the outbreak of COVID-19, the development of dashboards as dynamic, visual tools for communicating COVID-19 data has surged worldwide. Dashboards can inform decision-making and support behavior change. To do so, they must be actionable. The features that constitute an actionable dashboard in the context of the COVID-19 pandemic have not been rigorously assessed. OBJECTIVE: The aim of this study is to explore the characteristics of public web-based COVID-19 dashboards by assessing their purpose and users ("why"), content and data ("what"), and analyses and displays ("how" they communicate COVID-19 data), and ultimately to appraise the common features of highly actionable dashboards. METHODS: We conducted a descriptive assessment and scoring using nominal group technique with an international panel of experts (n=17) on a global sample of COVID-19 dashboards in July 2020. The sequence of steps included multimethod sampling of dashboards; development and piloting of an assessment tool; data extraction and an initial round of actionability scoring; a workshop based on a preliminary analysis of the results; and reconsideration of actionability scores followed by joint determination of common features of highly actionable dashboards. We used descriptive statistics and thematic analysis to explore the findings by research question. RESULTS: A total of 158 dashboards from 53 countries were assessed. Dashboards were predominately developed by government authorities (100/158, 63.0%) and were national (93/158, 58.9%) in scope. We found that only 20 of the 158 dashboards (12.7%) stated both their primary purpose and intended audience. Nearly all dashboards reported epidemiological indicators (155/158, 98.1%), followed by health system management indicators (85/158, 53.8%), whereas indicators on social and economic impact and behavioral insights were the least reported (7/158, 4.4% and 2/158, 1.3%, respectively). Approximately a quarter of the dashboards (39/158, 24.7%) did not report their data sources. The dashboards predominately reported time trends and disaggregated data by two geographic levels and by age and sex. The dashboards used an average of 2.2 types of displays (SD 0.86); these were mostly graphs and maps, followed by tables. To support data interpretation, color-coding was common (93/158, 89.4%), although only one-fifth of the dashboards (31/158, 19.6%) included text explaining the quality and meaning of the data. In total, 20/158 dashboards (12.7%) were appraised as highly actionable, and seven common features were identified between them. Actionable COVID-19 dashboards (1) know their audience and information needs; (2) manage the type, volume, and flow of displayed information; (3) report data sources and methods clearly; (4) link time trends to policy decisions; (5) provide data that are "close to home"; (6) break down the population into relevant subgroups; and (7) use storytelling and visual cues. CONCLUSIONS: COVID-19 dashboards are diverse in the why, what, and how by which they communicate insights on the pandemic and support data-driven decision-making. To leverage their full potential, dashboard developers should consider adopting the seven actionability features identified.

Patients Place More of an Emphasis on Physical Recovery Than Return to Work or Financial Recovery.

BACKGROUND: Value-based healthcare models aim to incentivize healthcare providers to offer interventions that address determinants of health. Understanding patient priorities for physical and socioeconomic recovery after injury can help determine which services and resources are most useful to patients. QUESTIONS/PURPOSES: (1) Do trauma patients consistently identify a specific aspect/domain of recovery as being most important at 6 weeks, 6 months, and 12 months after an injury? (2) Does the relative importance of those domains change within the first year after injury? (3) Are differences in priorities greater between patients than for a given patient over time? (4) Are different recovery priorities associated with identifiable biopsychosocial factors? METHODS: Between June 2018 and December 2018, 504 adult patients with fractures of the extremities or pelvis were surgically treated at the study site. For this prospective longitudinal study, we purposefully sampled patients from 6 of the 12 orthopaedic attendings' postoperative clinics. The participating surgeons surgically treated 243 adult patients with fractures of the extremities or pelvis. Five percent (11 of 243) of patients met inclusion criteria but missed their appointments during the 6-week recruitment window and could not be consented. We excluded 4% (9 of 243) of patients with a traumatic brain injury, 1% (2) of patients with a spinal cord injury, and 5% (12) of non-English-speaking patients (4% Spanish speaking [10]; 1% other languages [2]). Eighty-six percent of eligible patients (209 of 243) were approached for consent, and 5% (11 of 209) of those patients refused to participate. All remaining 198 patients consented and completed the baseline survey; 83% (164 of 198 patients) completed at least 6 months of follow-up, and 68% (134 of 198 patients) completed the 12-month assessment. The study participants' mean age was 44 ± 17 years, and 63% (125 of 198) were men. The primary outcome was the patient's recovery priorities, assessed at 6 weeks, 6 months, and 12 months after fracture using a discrete choice experiment. Discrete choice experiments are a well-established method for eliciting decisional preferences. In this technique, respondents are presented with a series of hypothetical scenarios, described by a set of plausible attributes or outcomes, and asked to select their preferred scenario. We used hierarchical Bayesian modeling to calculate individual-level estimates of the relative importance of physical recovery, work-related recovery, and disability benefits, based on the discrete choice experiment responses. The hierarchical Bayesian model improves upon more commonly used regression techniques by accounting for the observed response patterns of individual patients and the sequence of scenarios presented in the discrete choice experiment when calculating the model estimates. We computed the coefficient of variation for the three recovery domains and compared the between-patient versus within-patient differences using asymptotic tests. Separate prognostic models were fit for each of the study's three recovery domains to assess marginal changes in the importance of the recovery domain based on patient characteristics and factors that remained constant over the study (such as sex or preinjury work status) and patient characteristics and factors that varied over the study (including current work status or patient-reported health status). We previously published the 6-week results. This paper expands upon the prior publication to evaluate longitudinal changes in patient recovery priorities. RESULTS: Physical recovery was the respondents' main priority at all three timepoints, representing 60% ± 9% of their overall concern. Work-related recovery and access to disability benefits were of secondary importance and were associated with 27% ± 6% and 13% ± 7% of the patients' concern, respectively. The patients' concern for physical recovery was 6% (95% CrI 4% to 7%) higher at 12 months after fracture that at 6 weeks postfracture. The mean concern for work-related recovery increased by 7% (95% CrI 6% to 8%) from 6 weeks to 6 months after injury. The mean importance of disability benefits increased by 2% (95% CrI 1% to 4%) from 6 weeks to 6 months and remained 2% higher (95% CrI 0% to 3%) at 12 months after the injury. Differences in priorities were greater within a given patient over time than between patients as measured using the coefficient of variation (physical recovery [245% versus 7%; p < 0.001], work-related recovery [678% versus 12%; p < 0.001], and disability benefits [620% versus 33%; p < 0.001]. There was limited evidence that biopsychosocial factors were associated with variation in recovery priorities. Patients' concern for physical recovery was 2% higher for every 10-point increase in their Patient-reported Outcome Measure Information System (PROMIS) physical health status score (95% CrI 1% to 3%). A 10-point increase in the patient's PROMIS mental health status score was associated with a 1% increase in concern for work-related recovery (95% CrI 0% to 2%). CONCLUSION: Work-related recovery and accessing disability benefits were a secondary concern compared with physical recovery in the 12 months after injury for patients with fractures. However, the importance of work-related recovery was elevated after the subacute phase. Priorities were highly variable within a given patient in the year after injury compared with between-patient differences. Given this variation, orthopaedic surgeons should consider assessing and reassessing the socioeconomic well-being of their patients throughout their continuum of care. LEVEL OF EVIDENCE: Level II, therapeutic study.

Understanding the use of patient-reported data by health care insurers: A scoping review.

BACKGROUND: Patient-reported data are widely used for many purposes by different actors within a health system. However, little is known about the use of such data by health insurers. Our study aims to map the evidence on the use of patient-reported data by health insurers; to explore how collected patient-reported data are utilized; and to elucidate the motives of why patient-reported data are collected by health insurers. METHODS: The study design is that of a scoping review. In total, 11 databases were searched on. Relevant grey literature was identified through online searches, reference mining and recommendations from experts. Forty-two documents were included. We synthesized the evidence on the uses of patient-reported data by insurers following a structure-process-outcome approach; we also mapped the use and function of those data by a health insurer. RESULTS: Health insurers use patient-reported data for assurance and improvement of quality of care and value-based health care. The patient-reported data most often collected are those of outcomes, experiences and satisfaction measures; structure indicators are used to a lesser extent and often combined with process indicators. These data are mainly used for the purposes of procurement and purchasing of services, quality assurance, improvement and reporting, and strengthening the involvement of insured people. CONCLUSIONS: The breadth to which insurers use patient-reported data in their business models varies greatly. Some hindering factors to the uptake of such data are the varying and overlapping terminology in use in the field and the limited involvement of insured people in a health insurer's business. Health insurers are advised to be more explicit in regard to the role they want to play within the health system and society at large, and accommodate implications for the use of patient-reported data accordingly.

The contribution of service density and proximity to geographical inequalities in health care utilisation in Indonesia: A nation-wide multilevel analysis.

BACKGROUND: Geographical inequalities in access to health care have only recently become a global health issue. Little evidence is available about their determinants. This study investigates the associations of service density and service proximity with health care utilisation in Indonesia and the parts they may play in geographic inequalities in health care use. METHODS: Using data from a nationally representative survey (N = 649 625), we conducted a cross-sectional study and employed multilevel logistic regression to assess whether supply-side factors relating to service density and service proximity affect the variability of outpatient and inpatient care utilisation across 497 Indonesian districts. We used median odds ratios (MORs) to estimate the extent of geographical inequalities. Changes in the MOR values indicated the role played by the supply-side factors in the inequalities. RESULTS: Wide variations in the density and proximity of health care services were observed between districts. Outpatient care utilisation was associated with travel costs (odds ratio (OR) = 0.82, 95% confidence interval (CI) = 0.70-0.97). Inpatient care utilisation was associated with ratios of hospital beds to district population (OR = 1.23, 95% CI = 1.05-1.43) and with travel times (OR = 0.72 95% CI = 0.61-0.86). All in all, service density and proximity provided little explanation for district-level geographic inequalities in either outpatient (MOR = 1.65, 95% CrI = 1.59-1.70 decreasing to 1.61, 95% CrI = 1.56-1.67) or inpatient care utilisation (MOR = 1.63, 95% CrI = 1.55-1.69 decreasing to 1.60 95% CrI = 1.54-1.66). CONCLUSIONS: Supply-side factors play important roles in individual health care utilisation but do not explain geographical inequalities. Variations in other factors, such as the price and responsiveness of services, may also contribute to the inequalities. Further efforts to address geographical inequalities in health care should go beyond the physical presence of health care infrastructures to target issues such as regional variations in the prices and responsiveness of services.