Dataset Information

Provider monitoring and pay-for-performance when multiple providers affect outcomes: An application to renal dialysis.

ABSTRACT:

Objective

To characterize the influence of dialysis facilities and nephrologists on resource use and patient outcomes in the dialysis population and to illustrate how such information can be used to inform payment system design.

Data sources

Medicare claims for all hemodialysis patients for whom Medicare was the primary payer in 2004, combined with the Medicare Enrollment Database and the CMS Medical Evidence Form (CMS Form 2728), which is completed at onset of renal replacement therapy.

Study design

Resource use (mainly drugs and laboratory tests) per dialysis session and two clinical outcomes (achieving targets for anemia management and dose of dialysis) were modeled at the patient level with random effects for nephrologist and dialysis facility, controlling for patient characteristics.

Results

For each measure, both the physician and the facility had significant effects. However, facilities were more influential than physicians, as measured by the standard deviation of the random effects.

Conclusions

The success of tools such as P4P and provider profiling relies upon the identification of providers most able to enhance efficiency and quality. This paper demonstrates a method for determining the extent to which variation in health care costs and quality of care can be attributed to physicians and institutional providers. Because variation in quality and cost attributable to facilities is consistently larger than that attributable to physicians, if provider profiling or financial incentives are targeted to only one type of provider, the facility appears to be the appropriate locus.

SUBMITTER: Hirth RA

PROVIDER: S-EPMC2754549 | biostudies-literature | 2009 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Provider monitoring and pay-for-performance when multiple providers affect outcomes: An application to renal dialysis.

Hirth Richard A RA Turenne Marc N MN Wheeler John R C JR Pan Qing Q Ma Yu Y Messana Joseph M JM

Health services research 20090622 5 Pt 1

<h4>Objective</h4>To characterize the influence of dialysis facilities and nephrologists on resource use and patient outcomes in the dialysis population and to illustrate how such information can be used to inform payment system design.<h4>Data sources</h4>Medicare claims for all hemodialysis patients for whom Medicare was the primary payer in 2004, combined with the Medicare Enrollment Database and the CMS Medical Evidence Form (CMS Form 2728), which is completed at onset of renal replacement t ...[more]

PMID: 19555398

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Project description:ImportanceMedicare's End-Stage Renal Disease Quality Incentive Program incorporates measures of perceived value into reimbursement calculations. In 2016, patient experience became a clinical measure in the Quality Incentive Program scoring system. Dialysis facility performance in patient experience measures has not been studied at the national level to date.ObjectiveTo examine associations among dialysis facility performance with patient experience measures and patient, facility, and geographic characteristics.DesignIn this cross-sectional analysis, patients from a national end-stage renal disease registry receiving in-center hemodialysis in the United States on December 31, 2014, were linked with dialysis facility scores on the In-Center Hemodialysis Consumer Assessment of Healthcare Providers and Systems (ICH-CAHPS) survey. Of 4977 US dialysis facilities, 2939 (59.1%) reported ICH-CAHPS scores from April 8, 2015, through January 11, 2016. Multivariable linear regression models with geographic random effects were used to examine associations of facility ICH-CAHPS scores with patient, dialysis facility, and geographic characteristics and to identify the amount of total between-facility variation in patient experience scores explained by these categories. Data were analyzed from September 15, 2017, through June 1, 2018.ExposuresDialysis facility, geographic characteristic, and 10% change in patient characteristics.Main outcomes and measuresDialysis facility ICH-CAHPS scores and the total between-facility variation explained by different categories of characteristics.ResultsOf the 2939 facilities included in the analysis, adjusted mean ICH-CAHPS scores were 2.6 percentage points (95% CI, 1.5-3.7) lower in for-profit facilities, 1.6 percentage points (95% CI, 0.9-2.2) lower in facilities owned by large dialysis organizations, and 2.3 percentage points (95% CI, 0.5-4.2) lower in free-standing facilities compared with their counterparts. More nurses per patient was associated with 0.2 percentage points (95% CI, 0.03-0.3) higher scores; a privately insured patient population was associated with 1.2 percentage points (95% CI, 0.2-2.2) higher scores. Facilities with higher proportions of black patients had 0.95 percentage points (95% CI, 0.78-1.12) lower scores; more Native American patients, 1.00 percentage point (95% CI, 0.39-1.60) lower facility scores. Geographic location and dialysis facility characteristics explained larger proportions of the overall between-facility variation in ICH-CAHPS scores than did patient characteristics.Conclusions and relevanceThis study suggests that for-profit operation, free-standing status, and large dialysis organization designation were associated with less favorable patient-reported experiences of care. Patient experience scores varied geographically, and black and Native American populations reported less favorable experiences. The study findings suggest that perceived quality of care delivered in these settings are of concern, and that there may be opportunities for improved implementation of patient experience surveys as is highlighted.

Project description:ObjectiveThe incidence and prevalence of end-stage renal disease (ESRD) in Taiwan have been ranked the highest worldwide. Therefore, the National Health Insurance Administration has implemented the pre-ESRD pay-for-performance (P4P) programme since November 2006, which had significantly reduced the incidence of dialysis and all-cause mortality. This study aimed to identify the factors associated with the enrolment in the pre-ESRD P4P programme.DesignCross-sectional study.SettingThe National Health Insurance research database 2007-2012 in Taiwan.ParticipantsPatients with prevalent pre-ESRD aged more than 18 years between January 2007 and December 2012 were enrolled. Patient demographics and hospital characteristics between P4P and non-P4P groups were compared. A logistic regression model was used to analyse the factors associated with P4P enrolment, and a generalised estimating equation was used to verify the results.Primary outcome measureEnrolment in the pre-ESRD P4P programme.ResultsIn total, 82?991 patients were enrolled in the programme, with a 45.6% participation rate. Patients who were males (adjusted OR (AOR)=0.89, 95% CI=0.86 to 0.91) and employed (AOR=0.95, 95% CI=0.92 to 0.97) had a significantly lower probability to be enrolled in the programme. Older patients (66-75 years old, AOR=1.23, 95% CI=1.14 to 1.33) and those with higher Charlson Comorbidities Index (CCI 5+, AOR=4.01, 95% CI=3.55 to 4.53) tended to be enrolled in the programme, while those in the 76+ years age group were not (AOR=1.03, 95% CI=0.95 to 1.13). Hospitals located in the central (AOR=1.48, 95% CI=1.05 to 2.08) and Kao-Ping regions (AOR=1.62, 95% CI=1.18 to 2.22) also tended to enrol patients in the pre-ESRD P4P programme. Enrolment rates increased over time.ConclusionPre-ESRD patients of the female gender, greater age and more comorbidities were more likely to be enrolled in the pre-ESRD P4P programme. Healthcare providers and health authorities should focus attention on patients who are male, younger and with less comorbidities to improve the healthcare quality and equality for all pre-ESRD patients.

Project description:ObjectiveProvider profiling of outcome performance has become increasingly common in pay-for-performance programs. For chronic conditions, a substantial proportion of patients eligible for outcome measures may be lost to follow-up, potentially compromising outcome profiling. In the context of primary care depression treatment, we assess the implications of missing data for the accuracy of alternative approaches to provider outcome profiling.DataWe used data from the Improving Mood-Promoting Access to Collaborative Treatment trial and the Depression Improvement across Minnesota, Offering a New Direction initiative to generate parameters for a Monte Carlo simulation experiment.Study designThe patient outcome of interest is the rate of remission of depressive symptoms at 6 months among a panel of patients with major depression at baseline. We considered two alternative approaches to profiling this outcome: (1) a relative, or tournament style threshold, set at the 80th percentile of remission rate among all providers, and (2) an absolute threshold, evaluating whether providers exceed a specified remission rate (30 percent). We performed a Monte Carlo simulation experiment to evaluate the total error rate (proportion of providers who were incorrectly classified) under each profiling approach. The total error rate was partitioned into error from random sampling variability and error resulting from missing data. We then evaluated the accuracy of alternative profiling approaches under different assumptions about the relationship between missing data and depression remission.Principal findingsOver a range of scenarios, relative profiling approaches had total error rates that were approximately 20 percent lower than absolute profiling approaches, and error due to missing data was approximately 50 percent lower for relative profiling. Most of the profiling error in the simulations was a result of random sampling variability, not missing data: between 11 and 21 percent of total error was attributable to missing data for relative profiling, while between 16 and 33 percent of total error was attributable to missing data for absolute profiling. Finally, compared with relative profiling, absolute profiling was much more sensitive to missing data that was correlated with the remission outcome.ConclusionsRelative profiling approaches for pay-for-performance were more accurate and more robust to missing data than absolute profiling approaches.

Project description:BACKGROUND:Telehealth technology can create a disruptive communication environment for frontline care providers who mediate virtual communication with specialists in electronic consultations. As providers are dealing with various technology features when communicating with specialists, their flexible attitude and behaviors to use various telehealth-related technology features can change the outcome of virtual care service. OBJECTIVE:The objective of this study is to examine frontline care providers' technology adaptation behaviors in the electronic consultation context. From the perspective of frontline care providers, we reapply and retest a theoretical model, reflecting a mechanism through which technology users' personal characteristics and technology adaptation behavior enhance virtual service performance, which is an important performance enabler in this online meeting context. In provider-to-provider communication, particularly, we explore the association among providers' information technology (IT)-related personal characteristics, adaptive telehealth technology use, and virtual service performance. METHODS:An online survey was administered to collect individual providers' personal traits, IT adaptation, and perception on virtual service performance. Partial least squares-structural equation modeling was used to estimate our predictive model of personal traits-IT adaptation, such as exploitative use (use the telehealth technology in a standard way), and exploratory use (use the telehealth technology as innovative way)-and virtual service performance. RESULTS:We collected 147 responses from graduate nursing students who were training to be nurse practitioners in their master's program, resulting in 121 valid responses from the cross-section online survey. Our theoretical model explained 60.0% of the variance in exploitative use of telehealth technology, 44% of the variance in exploratory use of telehealth technology, and 66% of the variance in virtual service performance. We found that exploitative IT use is an important driver to increase virtual service performance (?=0.762, P<.001), and personal characteristics such as habit are positively associated with both exploitative (?=0.293, P=.008) and exploratory use behaviors (?=0.414, P=.006), while computer self-efficacy is positively associated with exploitative use of telehealth technology (?=0.311, P=.047). CONCLUSIONS:This study discusses the unique role of frontline care providers in a virtual care service context and highlights the importance of their telehealth adaptation behavior in provider-to-provider communication. We showed that providers perceive that telehealth technologies should function as intended, otherwise it may create frustration or avoidance of the telehealth technology. Moreover, providers' habitual use of various technologies in daily lives also motivates them to adaptively use telehealth technology for improving virtual care service. Understanding providers' technology habit and adaptation can inform health care policy and further provide a better view of the design of telehealth technology for online communication.

Dataset Information

Provider monitoring and pay-for-performance when multiple providers affect outcomes: An application to renal dialysis.

Objective

Data sources

Study design

Results

Conclusions

Publications

Provider monitoring and pay-for-performance when multiple providers affect outcomes: An application to renal dialysis.

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