Mitigating Risk Selection in Health Care Entitlement Programs: A Patient-Level Competitive Bidding Approach

2020 ◽  
Author(s):  
Daniel Montanera ◽  
Abhay Mishra ◽  
T. S. Raghu
Keyword(s):  
Health Care ◽  
Competitive Bidding ◽  
Risk Selection ◽  
Patient Level

scholarly journals Novel Method for Identifying Care Home Residents in England: A Validation Study

2021 ◽  
Vol 5 (4) ◽  
Author(s):  
Stefano Conti ◽  
Filipe Oliveira dos Santos ◽  
Arne Wolters
Keyword(s):  
Health Care ◽  
Predictive Value ◽  
Care Home ◽  
Care Homes ◽  
Health Care Data ◽  
Patient Level ◽  
Home Address ◽  
Negative Rate ◽  
Routine Identification ◽  
Address Matching

IntroductionThe ability to identify residents of care homes in routinely collected health care data is key to informing healthcare planning decisions and delivery initiatives targeting the older and frail population. Health-care planning and delivery implications at national level concerning this population subgroup have considerably and suddenly grown in urgency following the onset of the COVID-19 pandemic, which has especially hit care homes. The range of applicability of this information has widened with the increased availability in England of retrospectively collected administrative databases, holding rich patient-level details on health and prognostic status who have made or are in contact with the National Health Service. In practice lack of a national registry of care homes residents in England complicates assessing an individual's care home residency status, which has been typically identified via manual address matching from pseudonymised patient-level healthcare databases linked with publicly availably care home address information. ObjectivesTo examine a novel methodology based on linking unique care home address identifiers with primary care patient registration data, enabling routine identification of care home residents in health-care data. MethodsThis study benchmarks the proposed strategy against the manual address matching standard approach through a diagnostic assessment of a stratified random sample of care home post codes in England. ResultsDerived estimates of diagnostic performance, albeit showing a non-insignificant false negative rate (21.98%), highlight a remarkable true negative rate (99.69%) and positive predictive value (99.35%) as well as a satisfactory negative predictive value (88.25%). ConclusionsThe validation exercise lends confidence to the reliability of the novel address matching method as a viable and general alternative to manual address matching.

scholarly journals Patient-Level Factors Associated With Lack of Health Care Provider Recommendation for the Human Papillomavirus Vaccine Among Young Cancer Survivors

2020 ◽  
Vol 38 (25) ◽  
pp. 2892-2901
Author(s):  
Jocelyn M. York ◽  
James L. Klosky ◽  
Yanjun Chen ◽  
James A. Connelly ◽  
Karen Wasilewski-Masker ◽  
...  
Keyword(s):  
Health Care ◽  
Cancer Survivors ◽  
Health Care Provider ◽  
Care Provider ◽  
Hpv Vaccine ◽  
Insurance Coverage ◽  
Hpv Vaccination ◽  
Factors Associated ◽  
Patient Level ◽  
Vaccine Recommendation

PURPOSE Young cancer survivors are at increased risk for morbidities related to infection with the human papillomavirus (HPV), yet their HPV vaccine initiation rates remain low. Patient-/parent-reported lack of health care provider recommendation for HPV vaccination is strongly associated with vaccine noninitiation. We aimed to identify patient-level factors associated with survivor-/parent-reported lack of provider recommendation for HPV vaccination among young cancer survivors. METHODS Cancer survivors ages 9-26 years and 1-5 years off therapy completed a cross-sectional survey (parent-completed for survivors 9-17 years of age). Lack of health care provider HPV vaccine recommendation was the outcome of interest in a multivariable logistic regression model that included relevant patient-level sociodemographic, clinical, and vaccine-related variables. RESULTS Of 955 survivors, 54% were male, 66% were non-Hispanic White, and 36% had leukemia. At survey participation, survivors were an average age (± standard deviation) of 16.3 ± 4.7 years and 32.8 ± 14.7 months off therapy. Lack of provider HPV vaccine recommendation was reported by 73% (95% CI, 70% to 75%) of survivors. For the entire cohort, patient-level factors associated with lack of reported provider recommendation included perceived lack of insurance coverage for the HPV vaccine (odds ratio [OR], 4.0; 95% CI, 2.7 to 5.9; P < .001), male sex (OR, 2.8; 95% CI, 1.9 to 4.0; P < .001), and decreased parent-survivor communication regarding HPV vaccination (OR, 1.7 per unit decrease in score; 95% CI, 1.3 to 2.2; P < .001). In the sex- and age-stratified models, perceived lack of insurance coverage (all models) and male sex (age-stratified models) were also significantly associated with lack of reported provider recommendation. CONCLUSION We identified factors characterizing survivors at risk for not reporting receipt of a health care provider HPV vaccine recommendation. Future research is needed to develop interventions that facilitate effective provider recommendations for HPV vaccination among all young cancer survivors.

scholarly journals Patient-reported outcomes 3 months after spine surgery: is it an accurate predictor of 12-month outcome in real-world registry platforms?

2015 ◽  
Vol 39 (6) ◽  
pp. E17 ◽  
Author(s):  
Scott L. Parker ◽  
Anthony L. Asher ◽  
Saniya S. Godil ◽  
Clinton J. Devin ◽  
Matthew J. McGirt
Keyword(s):  
Health Care ◽  
Spine Surgery ◽  
Real World ◽  
Patient Reported Outcomes ◽  
Lumbar Spine Surgery ◽  
Meaningful Improvement ◽  
Patient Level ◽  
Life Years ◽  
Patient Reported ◽  
Prospective Longitudinal

OBJECT The health care landscape is rapidly shifting to incentivize quality of care rather than quantity of care. Quality and outcomes registry platforms lie at the center of all emerging evidence-driven reform models and will be used to inform decision makers in health care delivery. Obtaining real-world registry outcomes data from patients 12 months after spine surgery remains a challenge. The authors set out to determine whether 3-month patient-reported outcomes accurately predict 12-month outcomes and, hence, whether 3-month measurement systems suffice to identify effective versus noneffective spine care. METHODS All patients undergoing lumbar spine surgery for degenerative disease at a single medical institution over a 2-year period were enrolled in a prospective longitudinal registry. Patient-reported outcome instruments (numeric rating scale [NRS], Oswestry Disability Index [ODI], 12-Item Short Form Health Survey [SF-12], EQ-5D, and the Zung Self-Rating Depression Scale) were recorded prospectively at baseline and at 3 months and 12 months after surgery. Linear regression was performed to determine the independent association of 3- and 12-month outcome. Receiver operating characteristic (ROC) curve analysis was performed to determine whether improvement in general health state (EQ-5D) and disability (ODI) at 3 months accurately predicted improvement and achievement of minimum clinical important difference (MCID) at 12 months. RESULTS A total of 593 patients undergoing elective lumbar surgery were included in the study. There was a significant correlation between 3-month and 12-month EQ-5D (r = 0.71; p < 0.0001) and ODI (r = 0.70; p < 0.0001); however, the authors observed a sizable discrepancy in achievement of a clinically significant improvement (MCID) threshold at 3 versus 12 months on an individual patient level. For postoperative disability (ODI), 11.5% of patients who achieved an MCID threshold at 3 months dropped below this threshold at 12 months; 10.5% of patients who did not meet the MCID threshold at 3 months continued to improve and ultimately surpassed the MCID threshold at 12 months. For ODI, achieving MCID at 3 months accurately predicted 12-month MCID with only 62.6% specificity and 86.8% sensitivity. For postoperative health utility (EQ-5D), 8.5% of patients lost an MCID threshold improvement from 3 months to 12 months, while 4.0% gained the MCID threshold between 3 and 12 months postoperatively. For EQ-5D (quality-adjusted life years), achieving MCID at 3 months accurately predicted 12-month MCID with only 87.7% specificity and 87.2% sensitivity. CONCLUSIONS In a prospective registry, patient-reported measures of treatment effectiveness obtained at 3 months correlated with 12-month measures overall in aggregate, but did not reliably predict 12-month outcome at the patient level. Many patients who do not benefit from surgery by 3 months do so by 12 months, and, conversely, many patients reporting meaningful improvement by 3 months report loss of benefit at 12 months. Prospective longitudinal spine outcomes registries need to span at least 12 months to identify effective versus noneffective patient care.

Modeling Public Health Care Expenditure Using Patient Level Data: Empirical Evidence from Italy

2016 ◽  
Author(s):  
Vincenzo Atella ◽  
Federico Belotti ◽  
Valentina Conti ◽  
Claudio Alberto Cricelli ◽  
Joanna Kopinska ◽  
...  
Keyword(s):  
Public Health ◽  
Health Care ◽  
Empirical Evidence ◽  
Health Care Expenditure ◽  
Public Health Care ◽  
Patient Level Data ◽  
Patient Level ◽  
Level Data

scholarly journals Improving Cancer Outreach Effectiveness Through Targeting and Economic Assessments: Insights from a Randomized Field Experiment

2020 ◽  
Vol 84 (3) ◽  
pp. 1-27 ◽  
Author(s):  
Yixing Chen ◽  
Ju-Yeon Lee ◽  
Shrihari (Hari) Sridhar ◽  
Vikas Mittal ◽  
Katharine McCallister ◽  
...  
Keyword(s):  
Health Care ◽  
Field Experiment ◽  
Treatment Options ◽  
Screening Tests ◽  
Outreach Program ◽  
Neighborhood Socioeconomic Status ◽  
Patient Level ◽  
Randomized Field Experiment ◽  
Patients At Risk ◽  
Patient Outreach

Patients at risk for hepatocellular carcinoma or liver cancer should undergo semiannual screening tests to facilitate early detection, effective treatment options at lower cost, better recovery prognosis, and higher life expectancy. Health care institutions invest in direct-to-patient outreach marketing to encourage regular screening. They ask the following questions: (1) Does the effectiveness of outreach vary among patients and over time?; (2) What is the return on outreach?; and (3) Can patient-level targeted outreach increase the return? The authors use a multiperiod, randomized field experiment involving 1,800 patients. Overall, relative to the usual-care condition, outreach alone (outreach with patient navigation) increases screening completion rates by 10–20 (13–24) percentage points. Causal forests demonstrate that patient-level treatment effects vary substantially across periods and by patients’ demographics, health status, visit history, health system accessibility, and neighborhood socioeconomic status, thereby facilitating the implementation of the targeted outreach program. A simulation shows that the targeted outreach program improves the return on the randomized outreach program by 74%–96% or $1.6 million to $2 million. Thus, outreach marketing provides a substantial positive payoff to the health care system.

Applying Competitive Bidding to Health Care

1987 ◽  
Vol 12 (4) ◽  
pp. 703-722 ◽  
Author(s):  
Jeffrey S. McCombs ◽  
Jon B. Christianson
Keyword(s):  
Health Care ◽  
Competitive Bidding

The Distribution of Health Care Costs and Their Statistical Analysis for Economic Evaluation

1998 ◽  
Vol 3 (4) ◽  
pp. 233-245 ◽  
Author(s):  
Andrew Briggs ◽  
Alastair Gray
Keyword(s):  
Health Care ◽  
Health Care Costs ◽  
Health Care Cost ◽  
Cost Data ◽  
Parametric Methods ◽  
Patient Level Data ◽  
Patient Level ◽  
Level Data ◽  
Care Costs ◽  
Non Parametric

Objective: Where patient level data are available on health care costs, it is natural to use statistical analysis to describe the differences in cost between alternative treatments. Health care costs are, however, commonly considered to be skewed, which could present problems for standard statistical tests. This review examines how authors report the distributional form of health care cost data and how they have analysed their results. Method: A review of cost-effectiveness studies that collected patient-level data on health care costs. To supplement the review, five datasets on health care costs are examined. Consideration is given to the use of parametric methods on the transformed scale and to non-parametric methods of analysing skewed cost data. Results: Since economic analysis requires estimation in monetary units, the usefulness of transformation-based methods is limited by the inability to retransform cost differences to the original scale. Non-parametric rank sum methods were also found to be of limited use for economic analysis, partly due to the focus on hypothesis testing rather than estimation. Overall, the non-parametric approach of bootstrapping was found to offer a useful test of the appropriateness of parametric assumptions and an alternative method of estimation where those assumptions were found not to hold. Conclusions: Guidelines for the analysis of skewed health care cost data are offered.

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