The National Institutes of Health Patient-Reported Outcomes Measurement Information System (PROMIS): a view from the UK.

This is the final version. Available from Dove Medical Press via the DOI in this record.The interest in patient-reported outcome measures (PROMs) continues to increase as recognition of their potential utility rises in an effort to make health systems more patient-centered. The US National Institutes of Health (NIH) Patient-Reported Outcomes Measurement Information System® (PROMIS®) has used state of the art psychometric and statistical techniques to create a universal PROMs language, with potential application across the whole spectrum of health conditions, languages, and geographic locations. PROMIS offers a versatile platform where specific health domains are assessed using both standardized short forms and computerized adaptive tests, which are automatically tailored to individual patients. The scores of each health domain or a standardized profile of multiple domains are all scored on a common metric scale. PROMIS is increasingly recognized as the international gold standard for patient-centered assessment, although the use of these tools in the UK is limited. In this review, the developmental methodology of the PROMIS is described with discussion of its relevant strengths and limitations for use in the UK. We provide a case study of the largest application of the PROMIS tools in the UK as an example of straightforward integration into health-care research. Barriers to the uptake of PROMIS in the UK include the technology requirement, measurement tradition, and lack of a clear understanding of its benefits, and although potential stakeholders should cautiously consider its use, its impressive potential and increasing international utilization should be recognized

Safety and effectiveness of shoulder arthroplasties in Spain: a systematic review.

The effectiveness and safety of shoulder arthroplasties in the general context of a Spanish patient population remains unclear. The aim of this study was to ascertain both the effectiveness and safety of primary shoulder arthroplasties and the prosthesis types used in Spain. A systematic review of all the available literature evaluating the effectiveness and safety of primary shoulder arthroplasties in Spain was performed. A narrative synthesis was performed, and evidence tables were created in four dimensions: study design, arthroplasty characteristics, safety, and effectiveness. Orthopaedic Data Evaluation Panel (ODEP) scores were used to evaluate prosthesis types. Twenty-one studies were selected that included a total of 1293 arthroplasties. The most common indication was fractures, while the prosthesis most frequently used was the Delta Xtend (ODEP 10A). The most common complication was scapular notching. Prosthesis revision rate was approximately 6% for follow-ups between 12 and 79 months. In addition, significant improvements were observed in the Constant-Murley test score after the intervention. Currently in Spain, shoulder arthroplasty can be considered a safe and effective procedure with functional recovery and pain reduction for eligible patients with humeral fracture, rotator cuff arthropathy, fracture sequelae and malunion of the proximal humerus, and degenerative disease. Future longitudinal research and population-based studies could serve to confirm these results and identify points of improvement.The article is freely available via the publisher's site, click on the Publisher URL to access

Influence of hospital volume of procedures by year on the risk of revision of total hip and knee arthroplasties: a propensity score-matched cohort study

The volume of total hip (THA) and knee arthroplasties (TKA) performed in a hospital per year could be an influential factor on the revision of these procedures. The aims of this study were: To obtain comparable cohorts in higher- and lower-volume hospitals; and to assess the association between the hospital volume and the incidence of revision. Data from patients undergoing THA and TKA caused by osteoarthritis and recorded in the Catalan Arthroplasty Register (RACat) between January 2005 and December 2016 were used. The main explanatory variable was hospital volume by year (higher/lower). The cut-off point was fixed, based on previous research, at 50 THA and 125 TKA procedures/year. To obtain comparable populations, a propensity-score matching method (1:1) was used. Patient characteristics prior to and after matching were compared. To assess differences by volume, subhazard ratios (SHRs) from competing risks models were obtained. After matching, 13,772 THA and 36,316 TKA patients remained in the study. Prior to matching, in both joints, significant differences in all confounders were observed between volume groups. After matching, none of them remained significant. Both in THA and TKA, a higher risk of revision in higher-volume hospitals was observed (THA SHR: 1.25, 95%CI: 1.02-1.53; and TKA SHR: 1.29, 95%CI: 1.16-1.44). Unlike other contexts, currently in Catalonia, higher-volume hospitals have a greater risk of revision than lower-volume hospitals. Further research could be valuable to define context-dependent measures to reduce the incidence of revision.This article is freely available via Open Access. Click on the Publisher URL to access it from the publisher's site

Addressing the evolution of automated user behaviour patterns by runtime model interpretation

The final publication is available at Springer via http://dx.doi.org/10.1007/s10270-013-0371-3The use of high-level abstraction models can facilitate and improve not only system development but also runtime system evolution. This is the idea of this work, in which behavioural models created at design time are also used at runtime to evolve system behaviour. These behavioural models describe the routine tasks that users want to be automated by the system. However, users¿ needs may change after system deployment, and the routine tasks automated by the system must evolve to adapt to these changes. To facilitate this evolution, the automation of the specified routine tasks is achieved by directly interpreting the models at runtime. This turns models into the primary means to understand and interact with the system behaviour associated with the routine tasks as well as to execute and modify it. 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Comparing comorbidity measures for predicting mortality and hospitalization in three population-based cohorts

<p>Abstract</p> <p>Background</p> <p>Multiple comorbidity measures have been developed for risk-adjustment in studies using administrative data, but it is unclear which measure is optimal for specific outcomes and if the measures are equally valid in different populations. This research examined the predictive performance of five comorbidity measures in three population-based cohorts.</p> <p>Methods</p> <p>Administrative data from the province of Saskatchewan, Canada, were used to create the cohorts. The general population cohort included all Saskatchewan residents 20+ years, the diabetes cohort included individuals 20+ years with a diabetes diagnosis in hospital and/or physician data, and the osteoporosis cohort included individuals 50+ years with diagnosed or treated osteoporosis. Five comorbidity measures based on health services utilization, number of different diagnoses, and prescription drugs over one year were defined. Predictive performance was assessed for death and hospitalization outcomes using measures of discrimination (<it>c</it>-statistic) and calibration (Brier score) for multiple logistic regression models.</p> <p>Results</p> <p>The comorbidity measures with optimal performance were the same in the general population (<it>n </it>= 662,423), diabetes (<it>n </it>= 41,925), and osteoporosis (<it>n </it>= 28,068) cohorts. For mortality, the Elixhauser index resulted in the highest <it>c</it>-statistic and lowest Brier score, followed by the Charlson index. For hospitalization, the number of diagnoses had the best predictive performance. Consistent results were obtained when we restricted attention to the population 65+ years in each cohort.</p> <p>Conclusions</p> <p>The optimal comorbidity measure depends on the health outcome and not on the disease characteristics of the study population.</p

Predictive performance of comorbidity measures in administrative databases for diabetes cohorts

BACKGROUND: The performance of comorbidity measures for predicting mortality in chronic disease populations and using ICD-9 diagnosis codes in administrative health data has been investigated in several studies, but less is known about predictive performance with ICD-10 data and for other health outcomes. This study investigated predictive performance of five comorbidity measures for population-based diabetes cohorts in administrative data. The objectives were to evaluate performance for: (a) disease-specific and general health outcomes, (b) data based on the ICD-9 and ICD-10 diagnoses, and (c) different age groups. METHODS: Performance was investigated for heart attack, stroke, amputation, renal disease, hospitalization, and death in all-age and age-specific cohorts. Hospital records, physician billing claims, and prescription drug records from one Canadian province were used to identify diabetes cohorts and measure comorbidity. The data were analysed using multiple logistic regression models and summarized using measures of discrimination, accuracy, and fit. RESULTS: In Cohort 1 (n = 29,058), for which only ICD-9 diagnoses were recorded in administrative data, the Elixhauser index showed good or excellent prediction for amputation, renal disease, and death and performed better than the Charlson index. Number of diagnoses was a good predictor of hospitalization. Similar results were obtained for Cohort 2 (n = 41,925), in which both ICD-9 and ICD-10 diagnoses were recorded in administrative data, although predictive performance was sometimes higher. For age-specific models of mortality, the Elixhauser index resulted in the largest improvement in predictive performance in all but the youngest age group. CONCLUSIONS: Cohort age and the health outcome under investigation, but not the diagnosis coding system, may influence the predictive performance of comorbidity measure for studies about diabetes populations using administrative health data

Transforming medical professionalism to fit changing health needs

<p>Abstract</p> <p>Background</p> <p>The professional organization of medical work no longer reflects the changing health needs caused by the growing number of complex and chronically ill patients. Key stakeholders enforce coordination and remove power from the medical professions in order allow for these changes. However, it may also be necessary to initiate basic changes to way in which the medical professionals work in order to adapt to the changing health needs.</p> <p>Discussion</p> <p>Medical leaders, supported by health policy makers, can consciously activate the self-regulatory capacity of medical professionalism in order to transform the medical profession and the related professional processes of care so that it can adapt to the changing health needs. In doing so, they would open up additional routes to the improvement of the health services system and to health improvement. This involves three consecutive steps: (1) defining and categorizing the health needs of the population; (2) reorganizing the specialty domains around the needs of population groups; (3) reorganizing the specialty domains by eliminating work that could be done by less educated personnel or by the patients themselves. We suggest seven strategies that are required in order to achieve this transformation.</p> <p>Summary</p> <p>Changing medical professionalism to fit the changing health needs will not be easy. It will need strong leadership. But, if the medical world does not embark on this endeavour, good doctoring will become merely a bureaucratic and/or marketing exercise that obscures the ultimate goal of medicine which is to optimize the health of both individuals and the entire population.</p

Lifecourse socioeconomic circumstances and multimorbidity among older adults

<p>Abstract</p> <p>Background</p> <p>Many older adults manage multiple chronic conditions (i.e. multimorbidity); and many of these chronic conditions share common risk factors such as low socioeconomic status (SES) in adulthood and low SES across the lifecourse. To better capture socioeconomic condition in childhood, recent research in lifecourse epidemiology has broadened the notion of SES to include the experience of specific hardships. In this study we investigate the association among childhood financial hardship, lifetime earnings, and multimorbidity.</p> <p>Methods</p> <p>Cross-sectional analysis of 7,305 participants age 50 and older from the 2004 Health and Retirement Study (HRS) who also gave permission for their HRS records to be linked to their Social Security Records in the United States. Zero-inflated Poisson regression models were used to simultaneously model the likelihood of the absence of morbidity and the expected number of chronic conditions.</p> <p>Results</p> <p>Childhood financial hardship and lifetime earnings were not associated with the absence of morbidity. However, childhood financial hardship was associated with an 8% higher number of chronic conditions; and, an increase in lifetime earnings, operationalized as average annual earnings during young and middle adulthood, was associated with a 5% lower number of chronic conditions reported. We also found a significant interaction between childhood financial hardship and lifetime earnings on multimorbidity.</p> <p>Conclusions</p> <p>This study shows that childhood financial hardship and lifetime earnings are associated with multimorbidity, but not associated with the absence of morbidity. Lifetime earnings modified the association between childhood financial hardship and multimorbidity suggesting that this association is differentially influential depending on earnings across young and middle adulthood. Further research is needed to elucidate lifecourse socioeconomic pathways associated with the absence of morbidity and the presence of multimorbidity among older adults.</p

Routine care provided by specialists to children and adolescents in the United States (2002-2006)

BACKGROUND: Specialist physicians provide a large share of outpatient health care for children and adolescents in the United States, but little is known about the nature and content of these services in the ambulatory setting. Our objective was to quantify and characterize routine and co-managed pediatric healthcare as provided by specialists in community settings. METHODS: Nationally representative data were obtained from the National Ambulatory Medical Care Survey for the years 2002-2006. We included office based physicians (excluding family physicians, general internists and general pediatricians), and a representative sample of their patients aged 18 or less. Visits were classified into mutually exclusive categories based on the major reason for the visit, previous knowledge of the health problem, and whether the visit was the result of a referral. Primary diagnoses were classified using Expanded Diagnostic Clusters. Physician report of sharing care for the patient with another physician and frequency of reappointments were also collected. RESULTS: Overall, 41.3% out of about 174 million visits were for routine follow up and preventive care of patients already known to the specialist. Psychiatry, immunology and allergy, and dermatology accounted for 54.5% of all routine and preventive care visits. Attention deficit disorder, allergic rhinitis and disorders of the sebaceous glands accounted for about a third of these visits. Overall, 73.2% of all visits resulted in a return appointment with the same physician, in half of all cases as a result of a routine or preventive care visit. CONCLUSION: Ambulatory office-based pediatric care provided by specialists includes a large share of non referred routine and preventive care for common problems for patients already known to the physician. It is likely that many of these services could be managed in primary care settings, lessening demand for specialists and improving coordination of care