Understanding the relationship between the Centers for Medicare and Medicaid Services' Hospital Compare star rating, surgical case volume, and short-term outcomes after major cancer surgery.
Ontology highlight
ABSTRACT:
SUBMITTER: Kaye DR
PROVIDER: S-EPMC5650526 | biostudies-literature | 2017 Nov
REPOSITORIES: biostudies-literature
Publications
Understanding the relationship between the Centers for Medicare and Medicaid Services' Hospital Compare star rating, surgical case volume, and short-term outcomes after major cancer surgery.
Kaye Deborah R DR Norton Edward C EC Ellimoottil Chad C Ye Zaojun Z Dupree James M JM Herrel Lindsey A LA Miller David C DC
Cancer 20170630 21
<h4>Background</h4>Both the Centers for Medicare and Medicaid Services' (CMS) Hospital Compare star rating and surgical case volume have been publicized as metrics that can help patients to identify high-quality hospitals for complex care such as cancer surgery. The current study evaluates the relationship between the CMS' star rating, surgical volume, and short-term outcomes after major cancer surgery.<h4>Methods</h4>National Medicare data were used to evaluate the relationship between hospital ...[more]
Similar Datasets
Project description:BackgroundPublic reporting of hospital quality data is a key element of US healthcare reform. Data for hospital-acquired infections (HAIs) are especially complex.ObjectiveTo assess interpretability of HAI data as presented on the Centers for Medicare and Medicaid Services Hospital Compare website among patients who might benefit from access to these data.MethodsWe randomly selected inpatients at a large tertiary referral hospital from June to September 2014. Participants performed 4 distinct tasks comparing hypothetical HAI data for 2 hospitals, and the accuracy of their comparisons was assessed. Data were presented using the same tabular formats used by Centers for Medicare and Medicaid Services. Demographic characteristics and healthcare experience data were also collected.ResultsParticipants (N=110) correctly identified the better of 2 hospitals when given written descriptions of the HAI measure in 72% of the responses (95% CI, 66%-79%). Adding the underlying numerical data (number of infections, patient-time, and standardized infection ratio) to the written descriptions reduced correct responses to 60% (55%-66%). When the written HAI measure description was not informative (identical for both hospitals), 50% answered correctly (42%-58%). When no written HAI measure description was provided and hospitals differed by denominator for infection rate, 38% answered correctly (31%-45%).ConclusionsCurrent public HAI data presentation methods may be inadequate. When presented with numeric HAI data, study participants incorrectly compared hospitals on the basis of HAI data in more than 40% of the responses. Research is needed to identify better ways to convey these data to the public.
| S-EPMC4731310 | biostudies-literature
Project description:Importance:The Centers for Medicare & Medicaid Services (CMS) Five-Star measure for nursing homes is designed with input from expert panels about the importance of multiple quality indicators. Consumers may assign different values to these indicators, creating different 5-star ratings. Objective:To compare nursing homes' rankings based on the CMS Five-Star measure with rankings based on consumers' judgment about the importance of the same quality indicators. Design, Setting, and Participants:In this quality improvement study, CMS Five-Star data were linked with a measure calculated from CMS quality indicators and consumer values obtained from a national survey. Data covered the last quarter of 2016 and the first three quarters of 2017. The study included 10?676 nursing homes, comprising 69.8% of those with reported Five-Star measures. The national survey included adults, either nursing home residents or their family members who reported being familiar with the quality of care their relative received. Data analysis was performed from January 2019 to February 2020. Main Outcomes and Measures:The contingent valuation method was administered via the survey to obtain consumers' relative values of the quality indicators, and statistical analyses were used to create the contingent valuation measure. Agreement in nursing home rankings was assessed using the Five-Star measure, which is based on weights developed by expert panels, compared with rankings based on the contingent valuation measure. Results:Among 10?676 study nursing homes with a mean (SD) of 119.4 (59.4) beds, 7845 (73.5%) were for profit, 6424 (61.8%) were part of a chain, and 8009 (75.0%) were urban. The 4310 survey respondents (mean [SD] age, 39.9 [15.6] years; 1143 [26.5%] men; 3448 [80%] white) included mostly family members (3879 participants [90.0%]). The Pearson correlation coefficient (0.65) and weighted ? statistics (0.48) indicated only moderate agreement between ranking of nursing homes' performance by the 2 measures and disagreement on ranking for approximately one-half of the nursing homes. Conclusions and Relevance:Current nursing home report cards might not reflect consumers' values and the relative importance consumers place on each of the quality indicators that compose the overall Five-Star measure. Quality report cards might be more relevant to consumers by augmenting the Five-Star measure with a measure reflecting consumers' preferences. It is unknown whether these conclusions are generalizable to other report cards, such as Hospital and Home Health Compare, without conducting similar studies for these report cards.
| S-EPMC7225897 | biostudies-literature
Project description:ImportanceUnreliable performance measures can mask poor-quality care and distort financial incentives in value-based purchasing.ObjectiveTo examine the association between test-retest reliability and the reproducibility of hospital rankings.Design, setting, and participantsIn a cross-sectional design, Centers for Medicare & Medicaid Services Hospital Compare data were analyzed for the 2017 (based on 2014-2017 data) and 2018 (based on 2015-2018 data) reporting periods. The study was conducted from December 13, 2020, to September 30, 2021. This analysis was based on 28 measures, including mortality (acute myocardial infarction, congestive heart failure, pneumonia, and coronary artery bypass grafting), readmissions (acute myocardial infarction, congestive heart failure, pneumonia, and coronary artery bypass grafting), and surgical complications (postoperative acute kidney failure, postoperative respiratory failure, postoperative sepsis, and failure to rescue).ExposuresMeasure reliability based on test-retest reliability testing.Main outcomes and measuresThe reproducibility of hospital rankings was quantified by calculating the reclassification rate across the 2017 and 2018 reporting periods after categorizing the hospitals into terciles, quartiles, deciles, and statistical outliers. Linear regression analysis was used to examine the association between the reclassification rate and the intraclass correlation coefficient for each of the classification systems.ResultsThe analytic cohort consisted of 28 measures from 4452 hospitals with a median of 2927 (IQR, 2378-3160) hospitals contributing data for each measure. The hospitals participating in the Inpatient Prospective Payment System (n = 3195) had a median bed size of 141 (IQR, 69-261), average daily census of 70 (IQR, 24-155) patients, and a median disproportionate share hospital percentage of 38.2% (IQR, 18.7%-36.6%). The median intraclass correlation coefficient was 0.78 (IQR, 0.72-0.81), ranging between 0.50 and 0.85. The median reclassification rate was 70% (IQR, 62%-71%) when hospitals were ranked by deciles, 43% (IQR, 39%-45%) when ranked by quartiles, 34% (IQR, 31%-36%) when ranked by terciles, and 3.8% (IQR, 2.0%-6.2%) when ranked by outlier status. Increases in measure reliability were not associated with decreases in the reclassification rate. Each 0.1-point increase in the intraclass correlation coefficient was associated with a 6.80 (95% CI, 2.28-11.30; P = .005) percentage-point increase in the reclassification rate when hospitals were ranked into performance deciles, 4.15 (95% CI, 1.16-7.14; P = .008) when ranked into performance quartiles, 1.47 (95% CI, 1.84, 4.77; P = .37) when ranked into performance terciles, and 3.70 (95% CI, 1.30-6.09; P = .004) when ranked by outlier status.Conclusions and relevanceIn this study, more reliable measures were not associated with lower rates of reclassifying hospitals using test-retest reliability testing. These findings suggest that measure reliability should not be assessed with test-retest reliability testing.
| S-EPMC8652605 | biostudies-literature
Project description:STUDY OBJECTIVES:Centers for Medicare and Medicaid Services (CMS) reimbursement for positive airway pressure (PAP) devices for obstructive sleep apnea treatment is dependent on patients meeting adherence expectations within the first 3 months on therapy. Adherence is defined as usage of the device for at least 4 hours per night on 70% of nights during a consecutive 30-day period. We hypothesize that the adherence pattern may be established beyond this initial period, which may limit the opportunity to treat many patients. METHODS:Treatment and adherence data from PAP devices were monitored via wireless modems for 42 consecutive PAP-naïve military veterans who completed 1 year of nightly monitoring. Their baseline characteristics were as follows: age (mean ± standard deviation) 58.5 ± 12.5 years; body mass index 33.7 ± 5.7 kg/m2; diagnostic apnea-hypopnea index (pretreatment) 28.1 ± 18.5 events/h; apnea-hypopnea index on PAP: 4.3 ± 3.3 events/h. We examined daily, monthly, quarterly, semiannual, and annual reports, and the best 30-day adherence report for each quarter. RESULTS:In the first 3 months, 19 of 42 participants were adherent by CMS criteria, and 23 of 42 participants were not. Of the 19 adherent participants, 13 remained adherent and 6 became nonadherent or stopped PAP treatment for the remainder of the year. In the 23 initially nonadherent participants, 16 stopped PAP treatment, and 7 participants (30.4%) became adherent (using CMS criteria) during the rest of the year. Thus, PAP adherence during the first 3 months was predictive for the rest of the year in only 68.4%. PAP nonadherence during the first 3 months was predictive for further nonadherence in only 69.6% of the cases. Overall, this led to a 65% sensitivity and 72% specificity of using adherence at 3 months in predicting adherence at 1 year. CONCLUSIONS:CMS adherence criteria affecting PAP coverage are restrictive and can result in the withholding of therapy in many patients who otherwise might become adherent. CLINICAL TRIAL REGISTRATION:Registry: ClinicalTrials.gov, Title: Remote Monitoring in Obstructive Sleep Apnea, Identifier: NCT01678560, URL: https:// clinicaltrials.gov/ct2/show/NCT01678560.
| S-EPMC6374085 | biostudies-literature
Project description:BackgroundThe Open Payments Database (OPD) discloses financial transactions between manufacturers and physicians. The concordance of OPD versus self-reported conflicts of interest (COI) is unknown.Materials and methodsOur objectives were to compare (1) industry and self-disclosed COI in clinical literature, (2) payments within each disclosure level, and (3) industry- and self-disclosed COI and payments by specialty. This was an observational study. PubMed was searched for clinical studies accepted for publication from January 2014 to June 2016. Author and OPD-disclosed COIs were compared. Articles and authors were divided into full disclosure, incomplete industry disclosure, incomplete self-disclosure, and no COI. Primary outcome (differences in reported COI per article) was assessed using McNemar's test. Payment differences were compared using Kruskal-Wallis test.ResultsOPD- and self-disclosed COI differed (65.0% discordance rate by article, P < 0.001). Percentages of authors within each disclosure category differed between specialties (P < 0.001). Hematology articles exhibited the highest discordance rate (79.0%) and received the highest median payment for incomplete self-disclosure ($30,812).ConclusionsSignificant discordance exists between self- and OPD-reported COI. Additional research is needed to determine reasons for these differences.
| S-EPMC5643021 | biostudies-literature
Project description:Hospitals typically use Center for Medicare and Medicaid Services' (CMS) Hospital Readmission Reduction Program (HRRP) administrative reports as the standard of heart failure (HF) admission quantification. We aimed to evaluate the HF admission population identified by CMS HRRP definition of HF hospital admissions compared with a clinically based HF definition. We evaluated all hospital admissions at an academic medical center over 16 months in patients with Medicare fee-for service benefits and age ≥65 years. We compared the CMS HRRP HF definition against an electronic HF identification algorithm. Admissions identified solely by the CMS HF definition were manually reviewed by HF providers. Admissions confirmed with having decompensated HF as the primary problem by manual review or by the HF ID algorithm were deemed "HF positive," whereas those refuted were "HF negative." Of the 1672 all-cause admissions evaluated, 708 (42%) were HF positive. The CMS HF definition identified 440 admissions: sensitivity (54%), specificity (94%), positive predictive value (87%), negative predictive value (74%). The CMS HF definition missed 324 HF admissions because of inclusion/exclusion criteria (15%) and decompensated HF being a secondary diagnosis (85%). The CMS HF definition falsely identified 56 admissions as HF. The most common admission reasons in this cohort included elective pacemaker or defibrillator implantations (n = 13), noncardiac dyspnea (n = 9), left ventricular assist device complications (n = 8), and acute coronary syndrome (n = 6). The CMS HRRP HF report is a poor representation of an institution's HF admissions because of limitations in administrative coding and the HRRP HF report inclusion/exclusion criteria.
| S-EPMC6490358 | biostudies-literature
Project description: Not available
| S-EPMC10182425 | biostudies-literature
Project description:Aim: To evaluate the availability of published comparative real-world evidence (RWE) studies in Medicare patients for the ten drugs set to undergo Centers for Medicare and Medicaid Services (CMS) price negotiations in 2026. Materials & methods: A scoping review was completed in MEDLINE/PubMed to evaluate the availability of comparative RWE investigations conducted among Medicare-eligible patient populations in the US for the following drugs: apixaban, rivaroxaban, sitagliptin, ibrutinib, empagliflozin, etanercept, dapagliflozin, sacubitril/valsartan, ustekinumab and insulin aspart. Results: Of the 170 real-world comparative studies identified, 55 (32.4%) used Medicare real-world data (RWD) while 34 (20.0%) used commercial claims data in conjunction with either Medicare Advantage or Medicare Supplementary databases. The number of studies varied considerably by drug with apixaban and rivaroxaban studies accounting for the majority (i.e., 67.1%) of comparative RWE studies. Approximately a third or less of the comparative RWE studies were conducted in CMS RWD per drug. Conclusion: Our results demonstrate there is a considerable amount of comparative RWE for apixaban, rivaroxaban, and etanercept but limited comparative RWE for the other drugs set to undergo CMS price negotiations in 2026; additionally, our findings set up a number of next steps (e.g., risk of bias assessments) for further exploration of the available evidence base. Overall, CMS and manufacturers should consider proactively generating high-quality comparative RWE studies in the Medicare population to ensure that future price negotiations are based on robust evidence.
| S-EPMC10690442 | biostudies-literature
Project description:ImportancePredicting payments for particular conditions or populations is essential for research, benchmarking, public reporting, and calculations for population-based programs. Centers for Medicare & Medicaid Services (CMS) models often group codes into disease categories, but using single, rather than grouped, diagnostic codes and leveraging present on admission (POA) codes may enhance these models.ObjectiveTo determine whether changes to the candidate variables in CMS models would improve risk models predicting patient total payment within 30 days of hospitalization for acute myocardial infarction (AMI), heart failure (HF), and pneumonia.Design, setting, and participantsThis comparative effectiveness research study used data from Medicare fee-for-service hospitalizations for AMI, HF, and pneumonia at acute care hospitals from July 1, 2013, through September 30, 2015. Payments across multiple care settings, services, and supplies were included and adjusted for geographic and policy variations, corrected for inflation, and winsorized. The same data source was used but varied for the candidate variables and their selection, and the method used by CMS for public reporting that used grouped codes was compared with variations that used POA codes and single diagnostic codes. Combinations of use of POA codes, separation of index admission diagnoses from those in the previous 12 months, and use of individual International Classification of Diseases, Ninth Revision, Clinical Modification codes instead of grouped diagnostic categories were tested. Data analysis was performed from December 4, 2017, to June 10, 2019.Main outcomes and measuresThe models' goodness of fit was compared using root mean square error (RMSE) and the McFadden pseudo R2.ResultsAmong the 1 943 049 total hospitalizations of the study participants, 343 116 admissions were for AMI (52.5% male; 37.4% aged ≤74 years), 677 044 for HF (45.5% male; 25.9% aged ≤74 years), and 922 889 for pneumonia (46.4% male; 28.2% aged ≤74 years). The mean (SD) 30-day payment was $23 103 ($18 221) for AMI, $16 365 ($12 527) for HF, and $17 097 ($12 087) for pneumonia. Each incremental model change improved the pseudo R2 and RMSE. Incorporating all 3 changes improved the pseudo R2 of the patient-level models from 0.077 to 0.129 for AMI, from 0.042 to 0.129 for HF, and from 0.114 to 0.237 for pneumonia. Parallel improvements in RMSE were found for all 3 conditions.Conclusions and relevanceLeveraging POA codes, separating index from previous diagnoses, and using single diagnostic codes improved payment models. Better models can potentially improve research, benchmarking, public reporting, and calculations for population-based programs.
| S-EPMC6694388 | biostudies-literature
Project description:ImportanceIn 2016, the Centers for Medicare & Medicaid Services (CMS) launched its first mandatory bundled payment program, the Comprehensive Care for Joint Replacement (CJR) model, by randomizing metropolitan statistical areas (MSAs) into the payment model.ObjectiveTo evaluate changes in key economic and clinical outcomes associated with the CJR model.Design, setting, and participantsA retrospective, national, population-based analysis of Medicare fee-for-service beneficiaries undergoing lower extremity joint replacement was conducted using 100% Medicare Part A data and 5% Medicare Part B data. Within an intention-to-treat framework, a difference-in-differences approach was used to compare Medicare spending, quality of care, volume of episodes, and patient selection in episodes of lower extremity joint replacements in the first 2 years of the program between propensity score-matched CJR and non-CJR hospitals (episodes initiated from April 1, 2016, through December 31, 2017, with the latter completed by March 31, 2018). Lower extremity joint replacement episodes in MSAs randomly assigned to the CJR model were compared with those in MSAs not assigned to the CJR model.ExposuresRandom assignment of MSAs into the CJR model within prespecified strata.Main outcomes and measuresSpending and its components, quality of care, volume of episodes, and patient characteristics were the main outcomes.ResultsAfter propensity score matching, there were 157 828 primary lower extremity joint replacement cases across 684 hospitals in the CJR (treatment) group (101 641 [64.4%] women; mean [SD] age, 72.8 [8.9] years) and 180 594 cases across 726 hospitals in the non-CJR (control) group (115 580 women [64.0%] women; mean [SD] age, 72.6 [8.8] years). The CJR was associated with a decrease of $582 per episode in Medicare Part A spending, a 2.5% savings on claims (95% CI, -$873 to -$290; P < .001) driven by a 5.5% decline in 90-day postacute care spending, concentrated in skilled nursing facilities (-4.5% change from baseline; 95% CI, -$460 to -$26; P = .03) and inpatient rehabilitation facilities (-22.9% change from baseline; 95% CI,-$497 to -$176; P < .001). Estimated savings on claims, while consistent with changes in practice patterns, may not have exceeded the reconciliation payments to hospitals reported by CMS to date. No significant changes in hospital length of stay, readmissions, complications, 30- or 90-day mortality, volume of episodes, or patient characteristics relative to control were found.Conclusions and relevanceThe CJR was associated with reduced Medicare Part A spending on claims over 2 years, largely through lower postacute spending. Mandatory bundled payments may serve as a useful model for policy efforts to change clinicians' and facilities' behavior without harming quality.
| S-EPMC6547121 | biostudies-literature