Patient-level predictors of temporal regularity of primary care visits.

BACKGROUND: Patients with chronic diseases should meet with their primary care doctor regularly to facilitate proactive care. Little is known about what factors are associated with more regular follow-up. METHODS: We studied 70,095 patients age 40 + with one of three chronic conditions (diabetes mellitus, heart failure, chronic obstructive pulmonary disease), cared for by Leumit Health Services, an Israeli health maintenance organization. Patients were divided into the quintile with the least temporally regular care (i.e., the most irregular intervals between visits) vs. the other four quintiles. We examined patient-level predictors of being in the least-temporally-regular quintile. We calculated the risk-adjusted regularity of care at 239 LHS clinics with at least 30 patients. For each clinic, compared the number of patients with the least temporally regular care with the number predicted to be in this group based on patient characteristics. RESULTS: Compared to older patients, younger patients (age 40-49), were more likely to be in the least-temporally-regular group. For example, age 70-79 had an adjusted odds ratio (AOR) of 0.82 compared to age 40-49 (p < 0.001 for all findings discussed here). Males were more likely to be in the least-regular group (AOR 1.18). Patients with previous myocardial infarction (AOR 1.07), atrial fibrillation (AOR 1.08), and current smokers (AOR 1.12) were more likely to have an irregular pattern of care. In contrast, patients with diabetes (AOR 0.79) or osteoporosis (AOR 0.86) were less likely to have an irregular pattern of care. Clinic-level number of patients with irregular care, compared with the predicted number, ranged from 0.36 (fewer patients with temporally irregular care) to 1.71 (more patients). CONCLUSIONS: Some patient characteristics are associated with more or less temporally regular patterns of primary care visits. Clinics vary widely on the number of patients with a temporally irregular pattern of care, after adjusting for patient characteristics. Health systems can use the patient-level model to identify patients at high risk for temporally irregular patterns of primary care. The next step is to examine which strategies are employed by clinics that achieve the most temporally regular care, since these strategies may be possible to emulate elsewhere.

Surgeon-level versus hospital-level quality variance in kidney cancer surgery.

PURPOSE: To determine whether variance in kidney cancer surgery quality indicators (QIs) is most impacted by surgeon-level or hospital-level factors in order to inform quality improvement initiatives. MATERIALS AND METHODS: The ICES and Veterans Affairs (VA) databases were queried for patients undergoing surgery for localized kidney cancer. Kidney cancer surgery QIs were defined within each cohort. Quality of care was benchmarked at a surgeon- vs. hospital-level to identify statistical outliers, using available clinicopathological data to adjust for differences in case-mix. Variance between surgeons and hospitals was calculated for each QI using a random-effects model. RESULTS: The QI with the greatest amount of variance explained by hospital and surgeon-level factors was proportion of cases performed with minimally invasive surgery (MIS). The majority of this variance was due to surgeon-level factors for both the VA and ICES cohorts. The proportion of cases performed using an MIS approach was also the QI with the greatest number of outlier hospitals and surgeons compared to the average performance. The proportion of partial nephrectomies performed for patients at risk of chronic kidney disease was the QI with the greatest amount of variance due to hospital-level factors for the ICES cohort. CONCLUSIONS: The proportion of localized kidney cancer cases performed using an MIS approach is the QI requiring the greatest attention. Quality improvement initiatives should focus on surgeon-level factors to increase the number of MIS cases being performed for patients with localized renal masses.

Impact of case-mix adjustment on observed variation in the healing of diabetic foot ulcers at 12 weeks using data from the National Diabetes Foot Care Audit of England and Wales: A cohort study.

AIM: This cohort study investigates the extent to which variation in ulcer healing between services can be explained by demographic and clinical characteristics. METHODS: The National Diabetes Foot Care Audit collated data on people with diabetic foot ulcers presenting to specialist services in England and Wales between July 2014 and March 2018. Logistic regression models were created to describe associations between risk factors and a person being alive and ulcer-free 12 weeks from presentation, and to investigate whether variation between 120 participating services persisted after risk factor adjustment. RESULTS: Of 27,030 people with valid outcome data, 12,925 (47.8%) were alive and ulcer-free at 12 weeks, 13,745 (50.9%) had an unhealed ulcer and 360 had died (1.3%). Factors associated with worse outcome were male sex, more severe ulcers, history of cardiac or renal disease and a longer time between first presentation to a non-specialist healthcare professional and first expert assessment. After adjustment for these factors, four services (3.3%) were more than 3SD above and seven services (5.8%) were more than 3SD below the national mean for proportions that were alive and ulcer-free at follow-up. CONCLUSIONS/INTERPRETATIONS: Variation in the healing of diabetic foot ulcers between specialist services in England and Wales persisted after adjusting for demographic characteristics, ulcer severity, smoking, body mass index and co-morbidities. We conclude that other factors contribute to variation in healing of diabetic foot ulcers and include the time to specialist assessment.

Different Approaches for Case-Mix Adjustment of Patient-Reported Outcomes to Compare Healthcare Providers-Methodological Results of a Systematic Review.

Patient-reported outcomes (PROs) are increasingly being used to compare the quality of outcomes between different healthcare providers (medical practices, hospitals, rehabilitation facilities). However, such comparisons can only be fair if differences in the case-mix between different types of provider are taken into account. This can be achieved with adequate statistical case-mix adjustment (CMA). To date, there is a lack of overview studies on current CMA methods for PROs. The aim of this study was to investigate which approaches are currently used to report and examine PROs for case-mix-adjusted comparison between providers. A systematic MEDLINE literature search was conducted (February 2021). The results were examined by two reviewers. Articles were included if they compared (a) different healthcare providers using (b) case-mix-adjusted (c) patient-reported outcomes (all AND conditions). From 640 hits obtained, 11 articles were included in the analysis. A wide variety of patient characteristics were used as adjustors, and baseline PRO scores and basic sociodemographic and clinical information were included in all models. Overall, the adjustment models used vary considerably. This evaluation is an initial attempt to systematically investigate different CMA approaches for PROs. As a standardized approach has not yet been established, we suggest creating a consensus-based methodological guideline for case-mix adjustment of PROs.

Determinants of self-reported functional status (EPIC-26) in prostate cancer patients prior to treatment.

PURPOSE: The self-reported functional status (sr-FS) of prostate cancer (PCa) patients varies substantially between patients and health-care providers before treatment. Information about this issue is important for evaluating comparisons between health-care providers and to assist in treatment decision-making. There have been few reports on correlates of pretherapeutic sr-FS. The objective of the article, therefore, is to describe clinical and sociodemographic correlates of pretherapeutic sr-FS, based on a subset of the TrueNTH Global Registry, a prospective cohort study. METHODS: A total of 3094 PCa patients receiving local treatment in 44 PCa centers in Germany were recruited between July 2016 and April 2018. Multilevel regression models were applied to predict five pretherapeutic sr-FS (EPIC-26) scores based on clinical characteristics (standard set suggested by the International Consortium for Health Outcomes Measurement), sociodemographic characteristics, and center characteristics. RESULTS: Impaired pretherapeutic sr-FS tended to be associated with lower educational level and poorer disease characteristics-except for "urinary incontinence" which was only associated with age. Notably, age was a risk factor ("urinary incontinence," "urinary irritative/obstructive," "sexual") as well as a protective factor ("hormonal") for pretherapeutic sr-FS. Pretherapeutic sr-FS varies little across centers. CONCLUSIONS: Pretherapeutic sr-FS varies by clinical patient characteristics and age as well as by socioeconomic status. The findings point out the benefit of collecting and considering socioeconomic information in addition to clinical and demographic patient characteristics for treatment decision-making and fair comparisons between health-care providers.

Funnel plots of patient-reported outcomes to evaluate health-care quality: Basic principles, pitfalls and considerations.

A funnel plot is a graphical method to evaluate health-care quality by comparing hospital performances on certain outcomes. So far, in nephrology, this method has been applied to clinical outcomes like mortality and complications. However, patient-reported outcomes (PROs; eg, health-related quality of life [HRQOL]) are becoming increasingly important and should be incorporated into this quality assessment. Using funnel plots has several advantages, including clearly visualized precision, detection of volume-effects, discouragement of ranking hospitals and easy interpretation of results. However, without sufficient knowledge of underlying methods, it is easy to stumble into pitfalls, such as overinterpretation of standardized scores, incorrect direct comparisons of hospitals and assuming a hospital to be in-control (ie, to perform as expected) based on underpowered comparisons. Furthermore, application of funnel plots to PROs is accompanied by additional challenges related to the multidimensional nature of PROs and difficulties with measuring PROs. Before using funnel plots for PROs, high and consistent response rates, adequate case mix correction and high-quality PRO measures are required. In this article, we aim to provide insight into the use and interpretation of funnel plots by presenting an overview of the basic principles, pitfalls and considerations when applied to PROs, using examples from Dutch routine dialysis care.

Comparison of individual and neighbourhood socioeconomic status in case mix adjustment of hospital performance in primary total hip replacement in Sweden: a register-based study.

BACKGROUND: Case mix adjustment is a pre-requisite for valid measurement of healthcare performance and socioeconomic status (SES) is important to account for. Lack of information on individual-level SES has led to investigations into using a proxy for SES based on patient area of residence. The objective of this study was to use neighbourhood SES for case mix adjustment of performance indicators in total hip replacement (THR) in Sweden, and to compare with use of individual SES. METHODS: Data from patient administrative systems and the Swedish Hip Arthroplasty Register were extracted for all patients undergoing THR in four Swedish regions. For each subject, individual data and neighbourhood data on country of birth, educational level, and income were provided by Statistics Sweden. Three variables were selected for analysis of performance; EQ-5D, hip pain and length of stay (LoS). In addition to socioeconomic information, several important clinical characteristics were used as case mix factors. Regression analysis was used to study each variable's impact on the three outcome variables and model fit was evaluated using mean squared error. RESULTS: A total of 27,121 patients operated between 2010 and 2016 were included in the study. Both educational level and income were higher when based on neighbourhood information than individual information, while proportion born in Sweden was similar. Higher SES was generally found to be associated with better outcomes and lower LoS, albeit with certain differences between the different measures of SES. The predictive ability of the models was increased when adding information on SES to the clinical characteristics. The increase in predictive ability was higher for individual SES compared to neighbourhood SES. When analysing performance for the two providers with most diverging case mix in terms of SES, the inclusion of SES altered the relative performance using individual as well as neighbourhood SES. CONCLUSIONS: Incorporating SES improves case mix adjustment marginally compared to using only clinical information. In this patient group, geographically derived SES was found to improve case mix adjustment compared to only clinical information but not to the same extent as actual individual-level SES.

Temporal and geographic changes in stage at diagnosis in England during 2008-2013: A population-based study of colorectal, lung and ovarian cancers.

BACKGROUND: Increasing diagnosis of cancer when the disease is still at early stages is a priority of cancer policy internationally. In England, reducing geographical inequalities in early diagnosis is also a key objective. Stage at diagnosis is not recorded for many patients, which may bias assessments of progress. We evaluate temporal and geographical changes in stage at diagnosis during 2008-2013 for colorectal, non-small cell lung, and ovarian cancers, using multiple imputation to minimise bias from missing data. METHODS: Population-based data from cancer registrations, routes to diagnosis, secondary care, and clinical audits were individually linked. Patient characteristics and recorded stage were summarised. Stage was imputed where missing using auxiliary information (including patient's survival time). Logistic regression was used to estimate temporal and geographical changes in early diagnosis adjusted for case mix using a multilevel model. RESULTS: We analysed 196,511 colorectal, 180,048 non-small cell lung, and 29,076 ovarian cancer patients. We estimate that there were very large increases in the percentage of patients diagnosed at stages I or II between 2008-09 and 2012-13: from 32% to 44% for colorectal cancer, 19% to 25% for non-small cell lung cancer, and 28% to 31% for ovarian cancer. Geographical inequalities reduced for colorectal and ovarian cancer. INTERPRETATION: Multiple imputation is an optimal approach to reduce bias from missing data, but residual bias may be present in these estimates. Increases in early-stage diagnosis coincided with increased diagnosis through the "two week wait" pathway and colorectal screening. Epidemiological analyses from 2013 are needed to evaluate continued progress.

Patient experiences with interdisciplinary treatment for substance dependence: an assessment of quality indicators based on two national surveys in Norway.

Purpose: The quality of health care is often measured using quality indicators, which can be utilized to compare the performance of health-care providers. Conducting comparisons in a meaningful and fair way requires the quality indicators to be adjusted for patient characteristics and other individual-level factors. The aims of the study were to develop and test a case-mix adjustment model for quality indicators based on patient-experience surveys among inpatients receiving interdisciplinary treatment for substance dependence, and to establish whether the quality indicators discriminate between health care providers. Patients and methods: Data were collected through two national surveys involving inpatients receiving residential treatment in Norway in 2013 and 2014. The same questionnaire was used in both surveys, and comprised three patient-experience scales. The scales are reported as national quality indicators, and associations between the scales and patient characteristics were tested through multilevel modeling to establish a case-mix model. The intraclass correlation coefficient was computed to assess the amount of variation at the hospital-trust level. Results: The intraclass correlation coefficient for the patient-reported experience scales varied from 2.3% for "treatment and personnel" to 8.1% for "milieu". Multivariate multilevel regression analyses showed that alcohol reported as the most frequently used substance, gender and age were significantly associated with two of the three scales. The length of stay at the institution, pressure to be admitted for treatment, and self-perceived health were significantly related to all three scales. Explained variance at the individual level was approximately 7% for all three scales. Conclusion: This study identified several important case-mix variables for the patient-based quality indicators and systematic variations at the hospital-trust level. Future research should assess the association between patient-based quality indicators and other quality indicators, and the predictive validity of patient-experience indicators based on on-site measurements.

Benchmarking Danish hospitals on mortality and readmission rates after cardiovascular admission.

OBJECTIVE: The aim of this study was to examine hospital performance measures that account more comprehensively for unique mixes of patients' characteristics. DESIGN: Nationwide cohort registry-based study within a population-based health care system. PARTICIPANTS: In this study, 331,513 patients discharged with a primary cardiovascular diagnosis from 1 of 26 Danish hospitals during 2011-2015 were included. Data covering all Danish hospitals were drawn from the Danish National Patient Registry and the Danish National Health Service Prescription Database. MAIN OUTCOME MEASURES: Thirty-day post-admission mortality rates, 30-day post-discharge readmission rates, and the associated numbers needed to harm were measured. METHODS: For each index hospital, we used a non-parametric logistic regression model to compute propensity scores. Propensity score weighted patients treated at other hospitals collectively resembled patients treated at the index hospital in terms of age, sex, primary discharge diagnosis, diagnosis history, medications, previous cardiac procedures, and comorbidities. Outcomes for the weighted patients treated at other hospitals formed benchmarks for the index hospital. Doubly robust regression formally tested whether the outcomes of patients at the index hospital differed from the outcomes of the patients used to form the benchmarks. For each index hospital, we computed the false discovery rate, ie, the probability of being incorrect if we claimed the hospital differed from its benchmark. RESULTS: Five hospitals exceeded their benchmark for 30-day mortality rates, with the number needed to harm ranging between 55 and 137. Seven hospitals exceeded their benchmark for readmission, with the number needed to harm ranging from 22 to 71. Our benchmarking approach flagged fewer hospitals as outliers compared with conventional regression methods. CONCLUSION: Conventional methods flag more hospitals as outliers than our benchmarking approach. Our benchmarking approach accounts more thoroughly for differences in hospitals' patient case mix, reducing the risk of false-positive selection of suspected outliers. A more comprehensive system of hospital performance measurement could be based on this approach.

Lumbar spinal stenosis: comparison of surgical practice variation and clinical outcome in three national spine registries.

BACKGROUND CONTEXT: Decompression surgery for lumbar spinal stenosis (LSS) is the most common spinal procedure in the elderly. To avoid persisting low back pain, adding arthrodesis has been recommended, especially if there is a coexisting degenerative spondylolisthesis. However, this strategy remains controversial, resulting in practice-based variation. PURPOSE: The present study aimed to evaluate in a pragmatic study if surgical selection criteria and variation in use of arthrodesis in three Scandinavian countries can be linked to variation in treatment effectiveness. STUDY DESIGN: This is an observational study based on a combined cohort from the national spine registries of Norway, Sweden, and Denmark. PATIENT SAMPLE: Patients aged 50 and older operated during 2011-2013 for LSS were included. OUTCOME MEASURES: Patient-Reported Outcome Measures (PROMs): Oswestry Disability Index (ODI) (primary outcome), Numeric Rating Scale (NRS) for leg pain and back pain, and health-related quality of life (Euro-Qol-5D) were reported. Analysis included case-mix adjustment. In addition, we report differences in hospital stay. METHODS: Analyses of baseline data were done by analysis of variance (ANOVA), chi-square, or logistic regression tests. The comparisons of the mean changes of PROMs at 1-year follow-up between the countries were done by ANOVA (crude) and analysis of covariance (case-mix adjustment). RESULTS: Out of 14,223 included patients, 10,890 (77%) responded at 1-year follow-up. Apart from fewer smokers in Sweden and higher comorbidity rate in Norway, baseline characteristics were similar. The rate of additional fusion surgery (patients without or with spondylolisthesis) was 11% (4%, 47%) in Norway, 21% (9%, 56%) in Sweden, and 28% (15%, 88%) in Denmark. At 1-year follow-up, the mean improvement for ODI (95% confidence interval) was 18 (17-18) in Norway, 17 (17-18) in Sweden, and 18 (17-19) in Denmark. Patients operated with arthrodesis had prolonged hospital stay. CONCLUSIONS: Real-life data from three national spine registers showed similar indications for decompression surgery but significant differences in the use of concomitant arthrodesis in Scandinavia. Additional arthrodesis was not associated with better treatment effectiveness.

Models used for case-mix adjustment of patient reported outcome measures (PROMs) in musculoskeletal healthcare: A systematic review of the literature.

BACKGROUND: Case-mix adjustment is an established method to take account of variations across cohorts in baseline patient factors, when comparing health outcomes. Although commonplace, there is a lack of evidence as to the most appropriate case-mix adjustment model to use to enable fair comparisons of PROM data in musculoskeletal services. OBJECTIVES: To conduct a systematic review summarising evidence of the development, validation, and performance of musculoskeletal case-mix adjustment models, and to make recommendations for future methods. DATA SOURCES: Searches included; AMED, CINAHL, EMBASE, HMIC, MEDLINE, and grey literature. ELIGIBILITY CRITERIA: Studies; from January 1992-May 2017, English language, musculoskeletal adult population, developing or validating a case-mix adjustment model, using a relevant PROM, and using patient factors feasible for clinical collection. DATA SYNTHESIS: Two reviewers evaluated selected papers. The CASP Cohort Tool was used to assess quality. RESULTS: Fourteen studies were included; eight US studies on the Focus on Therapeutic Outcomes model (pooled n=546,726 patients (with pre/post treatment data)) and six UK studies related to the UK National PROMs Programme model (pooled n=282,424 patients (with pre/post treatment data)). The majority used retrospective data, restricted to complete datasets. Both US and UK models showed good predictive ability (R2 18-42%). Common model variables were; baseline PROM score, age, sex, comorbidities, symptom duration, and surgical history. Reduced quality scores were mainly due to acceptability of patient recruitment, and completeness and length of patient follow up. CONCLUSION: Significant methodological crossover was found. Further studies are however needed to externally validate and develop models across musculoskeletal settings. PROSPERO database(CRD42017055948).

Development of an International Standard Set of Value-Based Outcome Measures for Patients With Chronic Kidney Disease: A Report of the International Consortium for Health Outcomes Measurement (ICHOM) CKD Working Group.

Value-based health care is increasingly promoted as a strategy for improving care quality by benchmarking outcomes that matter to patients relative to the cost of obtaining those outcomes. To support the shift toward value-based health care in chronic kidney disease (CKD), the International Consortium for Health Outcomes Measurement (ICHOM) assembled an international working group of health professionals and patient representatives to develop a standardized minimum set of patient-centered outcomes targeted for clinical use. The considered outcomes and patient-reported outcome measures were generated from systematic literature reviews. Feedback was sought from patients and health professionals. Patients with very high-risk CKD (stages G3a/A3 and G3b/A2-G5, including dialysis, kidney transplantation, and conservative care) were selected as the target population. Using an online modified Delphi process, outcomes important to all patients were selected, such as survival and hospitalization, and to treatment-specific subgroups, such as vascular access survival and kidney allograft survival. Patient-reported outcome measures were included to capture domains of health-related quality of life, which were rated as the most important outcomes by patients. Demographic and clinical variables were identified to be used as case-mix adjusters. Use of these consensus recommendations could enable institutions to monitor, compare, and improve the quality of their CKD care.

Effects of Caregiver and Decedent Characteristics on CAHPS Hospice Survey Scores.

CONTEXT: The Consumer Assessment of Healthcare Providers and Systems (CAHPS®) Hospice Survey assesses the care experiences of hospice patients and their families. Public reporting of hospice performance on these survey measures began in February 2018. OBJECTIVES: Develop an appropriate case-mix adjustment (CMA) model to allow for fair comparisons between hospices. METHODS: We analyzed CAHPS Hospice Survey data reflecting experiences of 915,442 patients who received care from 2513 hospice programs between April 2015 and March 2016. Decedent and caregiver characteristics were identified for inclusion in CMA based on their variation across hospices (as measured by intraclass correlation coefficients [ICCs]) and how predictive they were of responses to survey questions (as assessed by linear regression). RESULTS: The final CMA model included decedent age, payer for hospice care, primary diagnosis, length of final episode of hospice care, caregiver age, caregiver education, relationship to decedent, survey language/language spoken at home, and response percentile. The characteristics that varied most across hospices were language (ICC = 0.48 for Spanish survey or home language) and payer for hospice care (ICC = 0.42 for Medicare only; ICC = 0.35 for Medicare and private insurance). The characteristics that were most predictive of caregivers' survey responses were payer for hospice care, caregiver education, and survey language/language spoken at home. Lack of appropriate adjustment would incorrectly rank hospices by 1.2-5.4 percentile points. CONCLUSION: To ensure fair comparisons across hospices, CAHPS Hospice Survey measure scores should be adjusted for several caregiver and decedent characteristics.

Review of organizational effects on the outcome of mental health treatments.

OBJECTIVE: As there are theoretical, clinical, and "common sense" reasons to expect a relationship between organizational factors and outcome in clinics providing psychotherapy and other mental health treatments, a review of empirical research in this area was undertaken with the aim of finding empirical evidence for organizational effects. METHODS: A structured search for studies on organizational differences in patient mental health outcomes was performed using EBSCO host, Cochrane Library Database, and the Health Systems Evidence database at McMasters University. Finished studies published in English were included if they presented data from more than one mental health service and used change in symptom, level of functioning, or quality of life as outcome. RESULTS: The search yielded not more than 19 studies fulfilling inclusion criteria. All studies showed some evidence for organization effects, and there was some evidence for organizational climate and culture explaining differences in outcome. CONCLUSION: Given that mental health treatments are likely to be especially susceptive to organizational effects, it is remarkable that not more research has been devoted to this. Clearly, more research is needed to study the consequences of work organization for the outcome of psychotherapy. Methodological issues in organizational studies are discussed.

Do effects of common case-mix adjusters on patient experiences vary across patient groups?

BACKGROUND: Many survey studies in health care adjust for demographic characteristics such as age, gender, educational attainment and general health when performing statistical analyses. Whether the effects of these demographic characteristics are consistent between patient groups remains to be determined. This is important as the rationale for adjustment is often that demographic sub-groups differ in their so-called 'response tendency'. This rationale may be less convincing if the effects of response tendencies vary across patient groups. The present paper examines whether the impact of these characteristics on patients' global rating of care varies across patient groups. METHODS: Secondary analyses using multi-level regression models were performed on a dataset including 32 different patient groups and 145,578 observations. For each demographic variable, the 95% expected range of case-mix coefficients across patient groups is presented. In addition, we report whether the variance of coefficients for demographic variables across patient groups is significant. RESULTS: Overall, men, elderly, lower educated people and people in good health tend to give higher global ratings. However, these effects varied significantly across patient groups and included the possibility of no effect or an opposite effect in some patient groups. CONCLUSION: The response tendency attributed to demographic characteristics - such as older respondents being milder, or higher educated respondents being more critical - is not general or universal. As such, the mechanism linking demographic characteristics to survey results on patient experiences with quality of care is more complicated than a general response tendency. It is possible that the response tendency interacts with patient group, but it is also possible that other mechanisms are at play.

Medicare Advantage and Fee-for-Service Performance on Clinical Quality and Patient Experience Measures: Comparisons from Three Large States.

OBJECTIVE: To compare performance between Medicare Advantage (MA) and Fee-for-Service (FFS) Medicare during a time of policy changes affecting both programs. DATA SOURCES/STUDY SETTING: Performance data for 16 clinical quality measures and 6 patient experience measures for 9.9 million beneficiaries living in California, New York, and Florida. STUDY DESIGN: We compared MA and FFS performance overall, by plan type, and within service areas associated with contracts between CMS and MA organizations. Case mix-adjusted analyses (for measures not typically adjusted) were used to explore the effect of case mix on MA/FFS differences. DATA COLLECTION/EXTRACTION METHODS: Performance measures were submitted by MA organizations, obtained from the nationwide fielding of the Medicare Consumer Assessment of Healthcare Providers and Systems (MCAHPS) Survey, or derived from claims. PRINCIPAL FINDINGS: Overall, MA outperformed FFS on all 16 clinical quality measures. Differences were large for HEDIS measures and small for Part D measures and remained after case mix adjustment. MA enrollees reported better experiences overall, but FFS beneficiaries reported better access to care. Relative to FFS, performance gaps were much wider for HMOs than PPOs. Excluding HEDIS measures, MA/FFS differences were much smaller in contract-level comparisons. CONCLUSIONS: Medicare Advantage/Fee-for-Service differences are often large but vary in important ways across types of measures and contracts.

Hospital comparison of stroke care in Sweden: a register-based study.

BACKGROUND AND PURPOSE: The objective of this study was to estimate the level of health outcomes and resource use at a hospital level during the first year after a stroke, and to identify any potential differences between hospitals after adjusting for patient characteristics (case mix). METHOD: Data from several registries were linked on individual level: seven regional patient administrative systems, Swedish Stroke Register, Statistics Sweden, National Board of Health and Welfare and Swedish Social Insurance Agency. The study population consisted of 14 125 patients presenting with a stroke during 2010. Case-mix adjusted analysis of hospital differences was made on five aspects of health outcomes and resource use, 1 year post-stroke. RESULTS: The results indicated that 26% of patients had died within a year of their stroke. Among those who survived, almost 5% had a recurrent stroke and 40% were left with a disability. On average, the patients had 22 inpatient days and 23 outpatient visits, and 13% had moved into special housing. There were significant variations between hospitals in levels of health outcomes achieved and resources used after adjusting for case mix. CONCLUSION: Differences in health outcomes and resource use between hospitals were substantial and not entirely explained by differences in patient mix, indicating tendencies of unequal stroke care in Sweden. Healthcare organisation of regions and other structural features could potentially explain parts of the differences identified.

Charlson comorbidity index derived from chart review or administrative data: agreement and prediction of mortality in intensive care patients.

PURPOSE: This study compared the Charlson comorbidity index (CCI) information derived from chart review and administrative systems to assess the completeness and agreement between scores, evaluate the capacity to predict 30-day and 1-year mortality in intensive care unit (ICU) patients, and compare the predictive capacity with that of the Simplified Acute Physiology Score (SAPS) II model. PATIENTS AND METHODS: Using data from 959 patients admitted to a general ICU in a Norwegian university hospital from 2007 to 2009, we compared the CCI score derived from chart review and administrative systems. Agreement was assessed using % agreement, kappa, and weighted kappa. The capacity to predict 30-day and 1-year mortality was assessed using logistic regression, model discrimination with the c-statistic, and calibration with a goodness-of-fit statistic. RESULTS: The CCI was complete (n=959) when calculated from chart review, but less complete from administrative data (n=839). Agreement was good, with a weighted kappa of 0.667 (95% confidence interval: 0.596-0.714). The c-statistics for categorized CCI scores from charts and administrative data were similar in the model that included age, sex, and type of admission: 0.755 and 0.743 for 30-day mortality, respectively, and 0.783 and 0.775, respectively, for 1-year mortality. Goodness-of-fit statistics supported the model fit. CONCLUSION: The CCI scores from chart review and administrative data showed good agreement and predicted 30-day and 1-year mortality in ICU patients. CCI combined with age, sex, and type of admission predicted mortality almost as well as the physiology-based SAPS II.

Adjusted Hospital Outcomes of Abdominal Aortic Aneurysm Surgery Reported in the Dutch Surgical Aneurysm Audit.

OBJECTIVE/BACKGROUND: The Dutch Surgical Aneurysm Audit (DSAA) is mandatory for all patients with primary abdominal aortic aneurysms (AAAs) in the Netherlands. The aims are to present the observed outcomes of AAA surgery against the predicted outcomes by means of V-POSSUM (Vascular-Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity). Adjusted mortality was calculated by the original and re-estimated V(physiology)-POSSUM for hospital comparisons. METHODS: All patients operated on from January 2013 to December 2014 were included for analysis. Calibration and discrimination of V-POSSUM and V(p)-POSSUM was analysed. Mortality was benchmarked by means of the original V(p)-POSSUM formula and risk-adjusted by the re-estimated V(p)-POSSUM on the DSAA. RESULTS: In total, 5898 patients were included for analysis: 4579 with elective AAA (EAAA) and 1319 with acute abdominal aortic aneurysm (AAAA), acute symptomatic (SAAA; n = 371) or ruptured (RAAA; n = 948). The percentage of endovascular aneurysm repair (EVAR) varied between hospitals but showed no relation to hospital volume (EAAA: p = .12; AAAA: p = .07). EAAA, SAAA, and RAAA mortality was, respectively, 1.9%, 7.5%, and 28.7%. Elective mortality was 0.9% after EVAR and 5.0% after open surgical repair versus 15.6% and 27.4%, respectively, after AAAA. V-POSSUM overestimated mortality in most EAAA risk groups (p < .01). The discriminative ability of V-POSSUM in EAAA was moderate (C-statistic: .719) and poor for V(p)-POSSUM (C-statistic: .665). V-POSSUM in AAAA repair overestimated in high risk groups, and underestimated in low risk groups (p < .01). The discriminative ability in AAAA of V-POSSUM was moderate (.713) and of V(p)-POSSUM poor (.688). Risk adjustment by the re-estimated V(p)-POSSUM did not have any effect on hospital variation in EAAA but did in AAAA. CONCLUSION: Mortality in the DSAA was in line with the literature but is not discriminative for hospital comparisons in EAAA. Adjusting for V(p)-POSSUM, revealed no association between hospital volume and treatment or outcome. Risk adjustment for case mix by V(p)-POSSUM in patients with AAAA has been shown to be important.