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Centers for Medicare and Medicaid Services' readmission reports inaccurately describe an institution's decompensated heart failure admissions.

ABSTRACT: 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.

SUBMITTER: Cox ZL

PROVIDER: S-EPMC6490358 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Centers for Medicare and Medicaid Services' readmission reports inaccurately describe an institution's decompensated heart failure admissions.

Cox Zachary L ZL Lai Pikki P Lewis Connie M CM Lenihan Daniel J DJ

Clinical cardiology 20170504 9

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 ...[more]

PMID: 28471510

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Project description:ObjectivesTo determine whether high performing hospitals with low 30 day risk standardized readmission rates have a lower proportion of readmissions from specific diagnoses and time periods after admission or instead have a similar distribution of readmission diagnoses and timing to lower performing institutions.DesignRetrospective cohort study.SettingMedicare beneficiaries in the United States.ParticipantsPatients aged 65 and older who were readmitted within 30 days after hospital admission for heart failure, acute myocardial infarction, or pneumonia in 2007-09.Main outcome measuresReadmission diagnoses were classified with a modified version of the Centers for Medicare and Medicaid Services' condition categories, and readmission timing was classified by day (0-30) after hospital discharge. Hospital 30 day risk standardized readmission rates over the three years of study were calculated with public reporting methods of the US federal government, and hospitals were categorized with bootstrap analysis as having high, average, or low readmission performance for each index condition. High and low performing hospitals had ≥ 95% probability of having an interval estimate respectively less than or greater than the national 30 day readmission rate over the three year period of study. All remaining hospitals were considered average performers.ResultsFor readmissions in the 30 days after the index admission, there were 320,003 after 1,291,211 admissions for heart failure (4041 hospitals), 102,536 after 517,827 admissions for acute myocardial infarction (2378 hospitals), and 208,438 after 1,135,932 admissions for pneumonia (4283 hospitals). The distribution of readmissions by diagnosis was similar across categories of hospital performance for all three conditions. High performing hospitals had fewer readmissions for all common diagnoses. Median time to readmission was similar by hospital performance for heart failure and acute myocardial infarction, though was 1.4 days longer among high versus low performing hospitals for pneumonia (P<0.001). Findings were unchanged after adjustment for other hospital characteristics potentially associated with readmission patterns.ConclusionsHigh performing hospitals have proportionately fewer 30 day readmissions without differences in readmission diagnoses and timing, suggesting the possible benefit of strategies that lower risk of readmission globally rather than for specific diagnoses or time periods after hospital stay.

Project description:ImportanceThe Centers for Medicare & Medicaid Services is beginning to consider adjusting for social risk factors, such as dual eligibility for Medicare and Medicaid, when evaluating hospital performance under value-based purchasing programs. It is unknown whether dual eligibility represents a unique domain of social risk or instead represents clinical risk unmeasured by variables available in traditional Medicare claims.ObjectiveTo assess how dual eligibility for Medicare and Medicaid is associated with risk-adjusted readmission rates after surgery.Design, setting, and participantsA retrospective cohort study was conducted of 55 651 Medicare beneficiaries undergoing general, vascular, and gynecologic surgery at 62 hospitals in Michigan between January 1, 2014, and December 1, 2016. Representative cohorts were derived from traditional Medicare claims (n?=?29?710) and the Michigan Surgical Quality Collaborative (MSQC) clinical registry (n?=?25?941), which includes additional measures of clinical risk. Statistical analysis was conducted between April 10 and July 15, 2019. The association between dual eligibility and risk-adjusted 30-day readmission rates after surgery was compared between models inclusive and exclusive of additional measurements of clinical risk. The study also examined how dual eligibility is associated with hospital profiling using risk-adjusted readmission rates.ExposuresDual eligibility for Medicare and Medicaid.Main outcomes and measuresRisk-adjusted all-cause 30-day readmission after surgery.ResultsThere were a total of 3986 dual-eligible beneficiaries in the Medicare claims cohort (2554 women; mean [SD] age, 72.9 [6.9] years) and 1608 dual-eligible beneficiaries in the MSQC cohort (990 women; mean [SD] age, 72.9 [6.8] years). In both data sets, higher proportions of dual-eligible beneficiaries were younger, female, and nonwhite than Medicare-only beneficiaries (Medicare claims cohort: female, 2554 of 3986 [64.1%] vs 12?879 of 25?724 [50.1%]; nonwhite, 1225 of 3986 [30.7%] vs 2783 of 25?724 [10.8%]; MSQC cohort: female, 990 of 1608 [61.6%] vs 12?578 of 24?333 [51.7%]; nonwhite, 416 of 1608 [25.9%] vs 2176 of 24?333 [8.9%]). In the Medicare claims cohort, dual-eligible beneficiaries were more likely to be readmitted (15.5% [95% CI, 13.7%-17.3%]) than Medicare-only beneficiaries (13.3% [95% CI, 12.7%-13.9%]; difference, 2.2 percentage points [95% CI, 0.4-3.9 percentage points]). In the MSQC cohort, after adjustment for more granular measures of clinical risk, dual eligibility was not significantly associated with readmission (difference, 0.6 percentage points [95% CI, -1.0 to 2.2 percentage points]). In both the Medicare claims and MSQC cohorts, adding dual eligibility to risk-adjustment models had little association with hospital ranking using risk-adjusted readmission rates.Conclusions and relevanceThis study suggests that dual eligibility for Medicare and Medicaid may reflect unmeasured clinical risk of readmission in claims data. Policy makers should consider incorporating more robust measures of social risk into risk-adjustment models used by value-based purchasing programs.

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.

Project description:ImportanceLow-income older adults who are dually eligible (DE) for Medicare and Medicaid often experience worse outcomes following hospitalization. Among other federal policies aimed at improving health for DE patients, Medicare has recently begun reporting disparities in within-hospital readmissions. The degree to which disparities for DE patients are owing to differences in community-level factors or, conversely, are amenable to hospital quality improvement, remains heavily debated.ObjectiveTo examine the extent to which within-hospital disparities in 30-day readmission rates for DE patients are ameliorated by state- and community-level factors.Design setting and participantsIn this retrospective cohort study, Centers for Medicare & Medicaid Services (CMS) Disparity Methods were used to calculate within-hospital disparities in 30-day risk-adjusted readmission rates for DE vs non-DE patients in US hospitals participating in Medicare. All analyses were performed in February and March 2019. The study included Medicare patients (aged ≥65 years) hospitalized for acute myocardial infarction (AMI), heart failure (HF), or pneumonia in 2014 to 2017.Main outcomes and measuresWithin-hospital disparities, as measured by the rate difference (RD) in 30-day readmission between DE vs non-DE patients following admission for AMI, HF, or pneumonia; variance across hospitals; and correlation of hospital RDs with and without adjustment for state Medicaid eligibility policies and community-level factors.ResultsThe final sample included 475 444 patients admitted for AMI, 898 395 for HF, and 1 214 282 for pneumonia, of whom 13.2%, 17.4%, and 23.0% were DE patients, respectively. Dually eligible patients had higher 30-day readmission rates relative to non-DE patients (RD >0) in 99.0% (AMI), 99.4% (HF), and 97.5% (pneumonia) of US hospitals. Across hospitals, the mean (IQR) RD between DE vs non-DE was 1.00% (0.87%-1.10%) for AMI, 0.82% (0.73%-0.96%) for HF, and 0.53% (0.37%-0.71%) for pneumonia. The mean (IQR) RD after adjustment for community-level factors was 0.87% (0.73%-0.97%) for AMI, 0.67% (0.57%-0.80%) for HF, and 0.42% (0.29%-0.57%) for pneumonia. Relative hospital rankings of corresponding within-hospital disparities before and after community-level adjustment were highly correlated (Pearson coefficient, 0.98).Conclusions and relevanceIn this cohort study, within-hospital disparities in 30-day readmission for DE patients were modestly associated with differences in state Medicaid policies and community-level factors. This suggests that remaining variation in these disparities should be the focus of hospital efforts to improve the quality of care transitions at discharge for DE patients in efforts to advance equity.

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.

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.

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Centers for Medicare and Medicaid Services' readmission reports inaccurately describe an institution's decompensated heart failure admissions.

Publications

Centers for Medicare and Medicaid Services' readmission reports inaccurately describe an institution's decompensated heart failure admissions.

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