Gender health gap pre- and post-joint arthroplasty: identifying affected patient-reported health domains.

BACKGROUND: As patient-reported outcomes (PROs) gain prominence in hip and knee arthroplasty (HA and KA), studies indicate PRO variations between genders. Research on the specific health domains particularly impacted is lacking. Hence, we aim to quantify the gender health gap in PROs for HA/KA patients, differentiating between general health, health-related quality of life (HrQoL), physical functioning, pain, fatigue, and depression. METHODS: The study included 3,693 HA patients (1,627 men, 2,066 women) and 3,110 KA patients (1,430 men, 1,680 women) receiving surgery between 2020 to 2021 in nine German hospitals, followed up until March 2022. Questionnaires used were: EQ-VAS, EQ-5D-5L, HOOS-PS, KOOS-PS, PROMIS-F-SF, PROMIS-D-SF, and a joint-specific numeric pain scale. PROs at admission, discharge, 12-months post-surgery, and the change from admission to 12-months (PRO-improvement) were compared by gender, tested for differences, and assessed using multivariate linear regressions. To enable comparability, PROs were transformed into z-scores (standard deviations from the mean). RESULTS: Observed differences between genders were small in all health domains and differences reduced over time. Men reported significantly better health versus women pre-HA (KA), with a difference of 0.252 (0.224) standard deviations from the mean for pain, 0.353 (0.243) for fatigue (PROMIS-F-SF), 0.327 (0.310) for depression (PROMIS-D-SF), 0.336 (0.273) for functionality (H/KOOS-PS), 0.177 (0.186) for general health (EQ-VAS) and 0.266 (0.196) for HrQoL (EQ-5D-5L). At discharge, the gender health gap reduced and even disappeared for some health dimensions since women improved in health to a greater extent than men. No gender health gap was observed in most PRO-improvements and at month 12. CONCLUSIONS: Men experiencing slightly better health than women in all health dimensions before surgery while experiencing similar health benefits 12-months post-surgery, might be an indicator of men receiving surgery inappropriately early, women unnecessarily late or both. As studies often investigate the PRO-improvement, they miss pre-surgery gender differences, which could be an important target for improvement initiatives in patient-centric care. Moreover, future research on cutoffs for meaningful between-group PRO differences per measurement time would aid the interpretation of gender health disparities. TRIAL REGISTRATION: German Register for Clinical Trials, DRKS00019916, 26 November 2019.

Stability of hospital quality indicators over time: A multi-year observational study of German hospital data.

BACKGROUND: Retrospective hospital quality indicators can only be useful if they are trustworthy signals of current or future quality. Despite extensive longitudinal quality indicator data and many hospital quality public reporting initiatives, research on quality indicator stability over time is scarce and skepticism about their usefulness widespread. OBJECTIVE: Based on aggregated, widely available hospital-level quality indicators, this paper sought to determine whether quality indicators are stable over time. Implications for health policy were drawn and the limited methodological foundation for stability assessments of hospital-level quality indicators enhanced. METHODS: Two longitudinal datasets (self-reported and routine data), including all hospitals in Germany and covering the period from 2004 to 2017, were analysed. A logistic regression using Generalized Estimating Equations, a time-dependent, graphic quintile representation of risk-adjusted rates and Spearman's rank correlation coefficient were used. RESULTS: For a total of eight German quality indicators significant stability over time was demonstrated. The probability of remaining in the best quality cluster in the future across all hospitals reached from 46.9% (CI: 42.4-51.6%) for hip replacement reoperations to 80.4% (CI: 76.4-83.8%) for decubitus. Furthermore, graphical descriptive analysis showed that the difference in adverse event rates for the 20% top performing compared to the 20% worst performing hospitals in the two following years is on average between 30% for stroke and AMI and 79% for decubitus. Stability over time has been shown to vary strongly between indicators and treatment areas. CONCLUSION: Quality indicators were found to have sufficient stability over time for public reporting. Potentially, increasing case volumes per hospital, centralisation of medical services and minimum-quantity regulations may lead to more stable and reliable quality of care indicators. Finally, more robust policy interventions such as outcome-based payment, should only be applied to outcome indicators with a higher level of stability over time. This should be subject to future research.

Electronic Patient-Reported Outcome Monitoring to Improve Quality of Life After Joint Replacement: Secondary Analysis of a Randomized Clinical Trial.

Importance: Although remote patient-reported outcome measure (PROM) monitoring has shown promising results in cancer care, there is a lack of research on PROM monitoring in orthopedics. Objective: To determine whether PROM monitoring can improve health outcomes for patients with joint replacement compared with the standard of care. Design, Setting, and Participants: A 2-group, patient-level randomized clinical trial (PROMoting Quality) across 9 German hospitals recruited patients aged 18 years or older with primary hip or knee replacement from October 1, 2019, to December 31, 2020, with follow-up until March 31, 2022. Interventions: Intervention and control groups received the standard of care and PROMs at hospital admission, discharge, and 12 months after surgery. In addition, the intervention group received PROMs at 1, 3, and 6 months after surgery. Based on prespecified PROM score thresholds, at these times, an automated alert signaled critical recovery paths to hospital study nurses. On notification, study nurses contacted patients and referred them to their physicians if necessary. Main Outcomes and Measures: The prespecified outcomes were the mean change in PROM scores (European Quality of Life 5-Dimension 5-Level version [EQ-5D-5L; range, -0.661 to 1.0, with higher values indicating higher levels of health-related quality of life (HRQOL)], European Quality of Life Visual Analogue Scale [EQ-VAS; range, 0-100, with higher values indicating higher levels of HRQOL], Hip Disability and Osteoarthritis Outcome Score-Physical Function Shortform [HOOS-PS; range, 0-100, with lower values indicating lower physical impairment] or Knee Injury and Osteoarthritis Outcome Score-Physical Function Shortform [KOOS-PS; range, 0-100, with lower values indicating lower physical impairment], Patient-Reported Outcomes Measurement Information System [PROMIS]-fatigue [range, 33.7-75.8, with lower values indicating lower levels of fatigue], and PROMIS-depression [range, 41-79.4, with lower values indicating lower levels of depression]) from baseline to 12 months after surgery. Analysis was on an intention-to-treat basis. Results: The study included 3697 patients with hip replacement (mean [SD] age, 65.8 [10.6] years; 2065 women [55.9%]) and 3110 patients with knee replacement (mean [SD] age, 66.0 [9.2] years; 1669 women [53.7%]). Exploratory analyses showed significantly better health outcomes in the intervention group on all PROMs except the EQ-5D-5L among patients with hip replacement, with a 2.10-point increase on the EQ-VAS in the intervention group compared with the control group (HOOS-PS, -1.86 points; PROMIS-fatigue, -0.69 points; PROMIS-depression, -0.57 points). Patients in the intervention group with knee replacement had a 1.24-point increase on the EQ-VAS, as well as significantly better scores on the KOOS-PS (-0.99 points) and PROMIS-fatigue (-0.84 points) compared with the control group. Mixed-effect models showed a significant difference in improvement on the EQ-VAS (hip replacement: effect estimate [EE], 1.66 [95% CI, 0.58-2.74]; knee replacement: EE, 1.71 [95% CI, 0.53-2.90]) and PROMIS-fatigue (hip replacement: EE, -0.65 [95% CI, -1.12 to -0.18]; knee replacement: EE, -0.71 [95% CI, -1.23 to -0.20]). The PROMIS-depression score was significantly reduced in the hip replacement group (EE, -0.60 [95% CI, -1.01 to -0.18]). Conclusions and Relevance: In this randomized clinical trial, the PROM-based monitoring intervention led to a small improvement in HRQOL and fatigue among patients with hip or knee replacement, as well as in depression among patients with hip replacement. Trial registration: Deutsches Register Klinischer Studien ID: DRKS00019916.

Predicting whether patients will achieve minimal clinically important differences following hip or knee arthroplasty.

Aims: A substantial fraction of patients undergoing knee arthroplasty (KA) or hip arthroplasty (HA) do not achieve an improvement as high as the minimal clinically important difference (MCID), i.e. do not achieve a meaningful improvement. Using three patient-reported outcome measures (PROMs), our aim was: 1) to assess machine learning (ML), the simple pre-surgery PROM score, and logistic-regression (LR)-derived performance in their prediction of whether patients undergoing HA or KA achieve an improvement as high or higher than a calculated MCID; and 2) to test whether ML is able to outperform LR or pre-surgery PROM scores in predictive performance. Methods: MCIDs were derived using the change difference method in a sample of 1,843 HA and 1,546 KA patients. An artificial neural network, a gradient boosting machine, least absolute shrinkage and selection operator (LASSO) regression, ridge regression, elastic net, random forest, LR, and pre-surgery PROM scores were applied to predict MCID for the following PROMs: EuroQol five-dimension, five-level questionnaire (EQ-5D-5L), EQ visual analogue scale (EQ-VAS), Hip disability and Osteoarthritis Outcome Score-Physical Function Short-form (HOOS-PS), and Knee injury and Osteoarthritis Outcome Score-Physical Function Short-form (KOOS-PS). Results: Predictive performance of the best models per outcome ranged from 0.71 for HOOS-PS to 0.84 for EQ-VAS (HA sample). ML statistically significantly outperformed LR and pre-surgery PROM scores in two out of six cases. Conclusion: MCIDs can be predicted with reasonable performance. ML was able to outperform traditional methods, although only in a minority of cases.

Exploring treatment effect heterogeneity of a PROMs alert intervention in knee and hip arthroplasty patients: A causal forest application.

Patient reported outcome measures (PROMs) experience an uptake in use for hip (HA) and knee arthroplasty (KA) patients. As they may be used for patient monitoring interventions, it remains unclear whether their use in HA/KA patients is effective, and which patient groups benefit the most. Nonetheless, knowledge about treatment effect heterogeneity is crucial for decision makers to target interventions towards specific subgroups that benefit to a greater extend. Therefore, we evaluate the treatment effect heterogeneity of a remote PROM monitoring intervention that includes ∼8000 HA/KA patients from a randomized controlled trial conducted in nine German hospitals. The study setting gave us the unique opportunity to apply a causal forest, a recently developed machine learning method, to explore treatment effect heterogeneity of the intervention. We found that among both HA and KA patients, the intervention was especially effective for patients that were female, >65 years of age, had a blood pressure disease, were not working, reported no backpain and were adherent. When transferring the study design into standard care, policy makers should make use of the knowledge obtained in this study and allocate the treatment towards subgroups for which the treatment is especially effective.

Robotic-assisted surgery for prostatectomy - does the diffusion of robotic systems contribute to treatment centralization and influence patients' hospital choice?

BACKGROUND: Between 2008 and 2018, the share of robotic-assisted surgeries (RAS) for radical prostatectomies (RPEs) has increased from 3 to 46% in Germany. Firstly, we investigate if this diffusion of RAS has contributed to RPE treatment centralization. Secondly, we analyze if a hospital's use of an RAS system influenced patients' hospital choice. METHODS: To analyze RPE treatment centralization, we use (bi-) annual hospital data from 2006 to 2018 for all German hospitals in a panel-data fixed effect model. For investigating RAS systems' influence on patients' hospital choice, we use patient level data of 4614 RPE patients treated in 2015. Employing a random utility choice model, we estimate the influence of RAS as well as specialization and quality on patients' marginal utilities and their according willingness to travel. RESULTS: Despite a slight decrease in RPEs between 2006 and 2018, hospitals that invested in an RAS system could increase their case volumes significantly (+ 82% compared to hospitals that did not invest) contributing to treatment centralization. Moreover, patients are willing to travel longer for hospitals offering RAS (+ 22% than average travel time) and for specialization (+ 13% for certified prostate cancer treatment centers, + 9% for higher procedure volume). The influence of outcome quality and service quality on patients' hospital choice is insignificant or negligible. CONCLUSIONS: In conclusion, centralization is partly driven by (very) high-volume hospitals' investment in RAS systems and patient preferences. While outcome quality might improve due to centralization and according specialization, evidence for a direct positive influence of RAS on RPE outcomes still is ambiguous. Patients have been voting with their feet, but research yet has to catch up.

A composite measure for patient-reported outcomes in orthopedic care: design principles and validity checks.

BACKGROUND: The complex, multidimensional nature of healthcare quality makes provider and treatment decisions based on quality difficult. Patient-reported outcome (PRO) measures can enhance patient centricity and involvement. The proliferation of PRO measures, however, requires a simplification to improve comprehensibility. Composite measures can simplify complex data without sacrificing the underlying information. OBJECTIVE AND METHODS: We propose a five-step development approach to combine different PRO into one composite measure (PRO-CM): (i) theoretical framework and metric selection, (ii) initial data analysis, (iii) rescaling, (iv) weighting and aggregation, and (v) sensitivity and uncertainty analysis. We evaluate different rescaling, weighting, and aggregation methods by utilizing data of 3145 hip and 2605 knee replacement patients, to identify the most advantageous development approach for a PRO-CM that reflects quality variations from a patient perspective. RESULTS: The comparison of different methods within steps (iii) and (iv) reveals the following methods as most advantageous: (iii) rescaling via z-score standardization and (iv) applying differential weights and additive aggregation. The resulting PRO-CM is most sensitive to variations in physical health. Changing weighting schemes impacts the PRO-CM most directly, while it proves more robust towards different rescaling and aggregation approaches. CONCLUSION: Combining multiple PRO provides a holistic picture of patients' health improvement. The PRO-CM can enhance patient understanding and simplify reporting and monitoring of PRO. However, the development methodology of a PRO-CM needs to be justified and transparent to ensure that it is comprehensible and replicable. This is essential to address the well-known problems associated with composites, such as misinterpretation and lack of trust.

Effects of Hospital Digitization on Clinical Outcomes and Patient Satisfaction: Nationwide Multiple Regression Analysis Across German Hospitals.

BACKGROUND: The adoption of health information technology (HIT) by health care providers is commonly believed to improve the quality of care. Policy makers in the United States and Germany follow this logic and deploy nationwide HIT adoption programs to fund hospital investments in digital technologies. However, scientific evidence for the beneficial effects of HIT on care quality at a national level remains mostly US based, is focused on electronic health records (EHRs), and rarely accounts for the quality of digitization from a hospital user perspective. OBJECTIVE: This study aimed to examine the effects of digitization on clinical outcomes and patient experience in German hospitals. Hence, this study adds to the small stream of literature in this field outside the United States. It goes beyond assessing the effects of mere HIT adoption and also considers user-perceived HIT value. In addition, the impact of a variety of technologies beyond EHRs was examined. METHODS: Multiple linear regression models were estimated using emergency care outcomes, elective care outcomes, and patient satisfaction as dependent variables. The adoption and user-perceived value of HIT represented key independent variables, and case volume, hospital size, ownership status, and teaching status were included as controls. Care outcomes were captured via risk-adjusted, observed-to-expected outcome ratios for patients who had stroke, myocardial infarction, or hip replacement. The German Patient Experience Questionnaire of Weisse Liste provided information on patient satisfaction. Information on the adoption and user-perceived value of 10 subdomains of HIT and EHRs was derived from the German 2020 Healthcare IT Report. RESULTS: Statistical analysis was based on an overall sample of 383 German hospitals. The analyzed data set suggested no significant effect of HIT or EHR adoption on clinical outcomes or patient satisfaction. However, a higher user-perceived value or quality of the installed tools did improve outcomes. Emergency care outcomes benefited from user-friendly overall digitization (ß=-.032; P=.04), which was especially driven by the user-friendliness of admission HIT (ß=-.023; P=.07). Elective care outcomes were positively impacted by user-friendly EHR installations (ß=-.138; P=.008). Similarly, the results suggested user-friendly, overall digitization to have a moderate positive effect on patient satisfaction (ß=-.009; P=.01). CONCLUSIONS: The results of this study suggest that hospital digitization is not an end in itself. Policy makers and hospitals are well advised to not only focus on the mere adoption of digital technologies but also continuously work toward digitization that is perceived as valuable by physicians and nurses who rely on it every day. Furthermore, hospital digitization strategies should consider that the assumed benefits of single technologies are not realized across all care domains.

Toward System-Wide Implementation of Patient-Reported Outcome Measures: A Framework for Countries, States, and Regions.

OBJECTIVES: This study aimed to develop a framework facilitating (1) the maturity assessment of healthcare systems regarding patient-reported outcome measure (PROM) implementation and (2) the comparison of different healthcare systems' PROM implementation levels to guide discussions and derive lessons for regional, state-level, and national PROM initiatives. METHODS: Guided by the grounded theory methodology, a PROM healthcare system implementation framework was developed following multiple steps. Based on interviews with 28 experts from 12 countries and a literature review, a framework was drafted and refined through 29 additional validation interviews. RESULTS: The resulting framework comprises 5 implementation stages along 7 dimensions. Implementation stages range from "first experimentation" to "system-wide adoption and a vibrant ecosystem." The dimensions are grouped into patient-reported outcome (PRO) measurement and PRO utilization, the former with the dimensions "scope and condition coverage," "metric and process standardization," and "tools and information technology-based solutions" and the latter with "patient empowerment and clinical decision support," "reporting and quality improvement," and "rewarding and contracting." The "culture and stakeholder involvement" dimension connects both groups. Although a concerted implementation approach across dimensions can be observed in advanced countries, others show a more uneven adoption. CONCLUSIONS: The framework and its preliminary application to different healthcare systems demonstrate (1) the importance of coherent progress across complementing dimensions and (2) the relevance of PROM integration across clinical specialties and care sectors to strengthen patient-centered care. Overall, the framework can facilitate dialogues between stakeholders to analyze the current PROM implementation status and strategies to advance it.

Can competition improve hospital quality of care? A difference-in-differences approach to evaluate the effect of increasing quality transparency on hospital quality.

Public reporting on the quality of care is intended to guide patients to the provider with the highest quality and to stimulate a fair competition on quality. We apply a difference-in-differences design to test whether hospital quality has improved more in markets that are more competitive after the first public release of performance data in Germany in 2008. Panel data from 947 hospitals from 2006 to 2010 are used. Due to the high complexity of the treatment of stroke patients, we approximate general hospital quality by the 30-day risk-adjusted mortality rate for stroke treatment. Market structure is measured (comparatively) by the Herfindahl-Hirschman index (HHI) and by the number of hospitals in the relevant market. Predicted market shares based on exogenous variables only are used to compute the HHI to allow a causal interpretation of the reform effect. A homogenous positive effect of competition on quality of care is found. This effect is mainly driven by the response of non-profit hospitals that have a narrow range of services and private for-profit hospitals with a medium range of services. The results highlight the relevance of outcome transparency to enhance hospital quality competition.

Defining minimum volume thresholds to increase quality of care: a new patient-oriented approach using mixed integer programming.

A positive relationship between treatment volume and outcome quality has been demonstrated in the literature and is thus evident for a variety of procedures. Consequently, policy makers have tried to translate this so-called volume-outcome relationship into minimum volume regulation (MVR) to increase the quality of care-yet with limited success. Until today, the effect of strict MVR application remains unclear as outcome quality gains cannot be estimated adequately and restrictions to application such as patient travel time and utilization of remaining hospital capacity are not considered sufficiently. Accordingly, when defining MVR, its effectiveness cannot be assessed. Thus, we developed a mixed integer programming model to define minimum volume thresholds balancing utility in terms of outcome quality gain and feasibility in terms of restricted patient travel time and utilization of hospital capacity. We applied our model to the German hospital sector and to four surgical procedures. Results showed that effective MVR needs a minimum volume threshold of 125 treatments for cholecystectomy, of 45 and 25 treatments for colon and rectum resection, respectively, of 32 treatments for radical prostatectomy and of 60 treatments for total knee arthroplasty. Depending on procedure type and incidence as well as the procedure's complication rate, outcome quality gain ranged between 287 (radical prostatectomy) and 977 (colon resection) avoidable complications (11.7% and 11.9% of all complications). Ultimately, policy makers can use our model to leverage MVR's intended benefit: concentrating treatment delivery to improve the quality of care.

The use of digitally collected patient-reported outcome measures for newly operated patients with total knee and hip replacements to improve post-treatment recovery: study protocol for a randomized controlled trial.

BACKGROUND: The number of total knee replacements (TKRs) and total hip replacements (THRs) has been increasing noticeably in high-income countries, such as Germany. In particular, the number of revisions is expected to rise because of higher life expectancy and procedures performed on younger patients, impacting the budgets of health-care systems. Quality transparency is the basis of holistic patient pathway optimization. Nevertheless, a nation-wide cross-sectoral assessment of quality from a patient perspective does not yet exist. Several studies have shown that the use of patient-reported outcome measures (PROMs) is effective for measuring quality and monitoring post-treatment recovery. For the first time in Germany, we test whether early detection of critical recovery paths using PROMs after TKR/THR improves the quality of care in a cost-effective way and can be recommended for implementation into standard care. METHODS/DESIGN: The study is a two-arm multi-center patient-level randomized controlled trial. Patients from nine hospitals are included in the study. Patient-centered questionnaires are employed to regularly measure digitized PROMs of TKR/THR patients from the time of hospital admission until 12 months post-discharge. An expert consortium has defined PROM alert thresholds at 1, 3, and 6 months to signal critical recovery paths after TKR/THR. An algorithm alerts study assistants if patients are not recovering in line with expected recovery paths. The study assistants contact patients and their physicians to investigate and, if needed, adjust the post-treatment protocol. When sickness funds' claims data are added, the cost-effectiveness of the intervention can be analyzed. DISCUSSION: The study is expected to deliver an important contribution to test PROMs as an intervention tool and examine the determinants of high-quality endoprosthetic care. Depending on a positive and cost-effective impact, the goal is to transfer the study design into standard care. During the trial design phase, several insights have been discovered, and there were opportunities for efficient digital monitoring limited by existing legacy care models. Digitalization in hospital processes and the implementation of digital tools still represent challenges for hospital personnel and patients. Furthermore, data privacy regulations and the separation between the in- and outpatient sector are roadblocks to effectively monitor and assess quality along the full patient pathway. TRIAL REGISTRATION: German Clinical Trials Register: DRKS00019916. Registered November 26, 2019 - retrospectively registered.

Stroke units, certification, and outcomes in German hospitals: a longitudinal study of patient-based 30-day mortality for 2006-2014.

BACKGROUND: Treatment of stroke patients in stroke units has increased and studies have shown improved outcomes. However, a large share of patients in Germany is still treated in hospitals without stroke unit. The effects of stroke unit service line, and total hospital quality certification on outcomes remain unclear. METHODS: We employ annual hospital panel data for 1100-1300 German hospitals from 2006 to 2014, which includes structural data and 30-day standardized mortality. We estimate hospital- and time-fixed effects regressions with three main independent variables: (1) stroke unit care, (2) stroke unit certification, and (3) total hospital quality certification. RESULTS: Our results confirm the trend of decreasing stroke mortality ratios, although to a much lesser degree than previous studies. Descriptive analysis illustrates better stroke outcomes for non-certified and certified stroke units and hospitals with total hospital quality certification. In a fixed effects model, having a stroke unit has a significant quality-enhancing effect, lowering stroke mortality by 5.6%, while there is no significant improvement effect for stroke unit certification or total hospital quality certification. CONCLUSIONS: Patients and health systems may benefit substantially from stroke unit treatment expansion as installing a stroke unit appears more meaningful than getting it certified or obtaining a total hospital quality certification. Health systems should thus prioritize investment in stroke unit infrastructure and centralize stroke care in stroke units. They should also prioritize patient-based 30-day mortality data as it allows a more realistic representation of mortality than admission-based data.

Quality and resource efficiency in hospital service provision: A geoadditive stochastic frontier analysis of stroke quality of care in Germany.

We specify a Bayesian, geoadditive Stochastic Frontier Analysis (SFA) model to assess hospital performance along the dimensions of resources and quality of stroke care in German hospitals. With 1,100 annual observations and data from 2006 to 2013 and risk-adjusted patient volume as output, we introduce a production function that captures quality, resource inputs, hospital inefficiency determinants and spatial patterns of inefficiencies. With high relevance for hospital management and health system regulators, we identify performance improvement mechanisms by considering marginal effects for the average hospital. Specialization and certification can substantially reduce mortality. Regional and hospital-level concentration can improve quality and resource efficiency. Finally, our results demonstrate a trade-off between quality improvement and resource reduction and substantial regional variation in efficiency.

Hospital quality variation matters - A time-trend and cross-section analysis of outcomes in German hospitals from 2006 to 2014.

Awareness of care variation and associated differences in outcome quality is important for patients to recognize and leverage the benefits of hospital choice and for policy makers, providers, and suppliers to adapt initiatives to improve hospital quality of care. We examine panel data on outcome quality in German hospitals between 2006 and 2014 for cholecystectomy, pacemaker implantation, hip replacement, percutaneous coronary intervention (PCI), stroke, and acute myocardial infarction (AMI). We use risk-adjusted and unadjusted outcomes based on 16 indicators. Median outcome and outcome variation trends are examined via box plots, simple linear regressions and quintile differences. Outcome trends differ across treatment areas and indicators. We found positive quality trends for hip replacement surgery, stroke and AMI 30-day mortality, and negative quality trends for 90-day stroke and AMI readmissions and PCI inpatient mortality. Variation of risk-adjusted outcomes ranges by a factor of 3-12 between the 2nd and 5th quintile of hospitals, both at the national and regional level. Our results show that simply measuring and reporting hospital outcomes without clear incentives or regulation - "carrots and sticks" - to improve performance and to centralize care in high performing hospitals has not led to broad quality improvements. More substantial efforts must be undertaken to narrow the outcome spread between high- and low-quality hospitals.

Health care public reporting utilization - user clusters, web trails, and usage barriers on Germany's public reporting portal Weisse-Liste.de.

BACKGROUND: Quality of care public reporting provides structural, process and outcome information to facilitate hospital choice and strengthen quality competition. Yet, evidence indicates that patients rarely use this information in their decision-making, due to limited awareness of the data and complex and conflicting information. While there is enthusiasm among policy makers for public reporting, clinicians and researchers doubt its overall impact. Almost no study has analyzed how users behave on public reporting portals, which information they seek out and when they abort their search. METHODS: This study employs web-usage mining techniques on server log data of 17 million user actions from Germany's premier provider transparency portal Weisse-Liste.de (WL.de) between 2012 and 2015. Postal code and ICD search requests facilitate identification of geographical and treatment area usage patterns. User clustering helps to identify user types based on parameters like session length, referrer and page topic visited. First-level markov chains illustrate common click paths and premature exits. RESULTS: In 2015, the WL.de Hospital Search portal had 2,750 daily users, with 25% mobile traffic, a bounce rate of 38% and 48% of users examining hospital quality information. From 2013 to 2015, user traffic grew at 38% annually. On average users spent 7 min on the portal, with 7.4 clicks and 54 s between clicks. Users request information for many oncologic and orthopedic conditions, for which no process or outcome quality indicators are available. Ten distinct user types, with particular usage patterns and interests, are identified. In particular, the different types of professional and non-professional users need to be addressed differently to avoid high premature exit rates at several key steps in the information search and view process. Of all users, 37% enter hospital information correctly upon entry, while 47% require support in their hospital search. CONCLUSIONS: Several onsite and offsite improvement options are identified. Public reporting needs to be directed at the interests of its users, with more outcome quality information for oncology and orthopedics. Customized reporting can cater to the different needs and skill levels of professional and non-professional users. Search engine optimization and hospital quality advocacy can increase website traffic.