Using Healthcare Data to Inform Health Policy: Quantifying Cardiovascular Disease Risk and Assessing 30-Day Readmission Measures

Health policy makers are struggling to manage health care and spending. To identify strategies for improving health quality and reducing health spending, policy makers need to first understand health risks and outcomes. Despite lacking some desirable clinical detail, existing health care databases, such as national health surveys and claims and enrollment data for insured populations, are often rich in information relating patient characteristics to heath risks and outcomes. They typically encompass more inclusive populations than can feasibly be achieved with new data collection and are valuable resources for informing health policy. This dissertation illustrates how the Medicare Current Beneficiary Survey (MCBS) and MassHealth data can be used to develop models that provide useful estimates of risks and health quality measures. It provides insights into: 1) the benefits of a proxy for the Framingham cardiovascular disease (CVD) risk score, that relies only on variables available in the MCBS, to target health interventions to policy-relevant subgroups, such as elderly Medicare beneficiaries, based on their risk of developing CVD, 2) the importance of setting appropriate risk-adjusted quality of care standards for accountable care organizations (ACOs) based on the characteristics of their enrolled members, and 3) the outsized effect of high- frequency hospital users on re-admission measures and possibly other quality measures. This work develops tools that can be used to identify and support care of vulnerable patients to both improve their health outcomes and reduce spending – an important step on the road to health equity

Nationwide Trends in Cardiovascular Disease Spending among the Elderly, 2000-2009

Background/Aims: One in every six health care dollars is spent on individuals with cardiovascular disease (CVD), and this spending will likely increase as the U.S. population ages. In order to understand the value of our substantial investment in CVD care, it is important to understand trends in CVD spending and, because value varies by patient risk, whether these trends vary across subpopulations with different CVD risk. The aim of this study was to assess national trends in CVD spending among different CVD risk subgroups. Methods: We examined trends during 2000-2009 in CVD-related and inflation-adjusted average spending using Medicare Current Beneficiary Survey data. We studied a total sample of 35,378 non-institutionalized, fee-for-Service Medicare beneficiaries 65 years or older. Analyses were conducted overall and stratified according to presence of CVD and, in those without CVD, level of CVD risk (high versus low). Results: From 2000 to 2009, among patients with CVD, overall annual spending increased by 29% (95%CI: 20-39), from $11,726 to$15,109. Medicare and out-of-pocket (OOP) spending increased by 39% (95%CI: 26-51), from $7,017 to$9,741 and by 14% (95%CI: 1-26), from $1,800 to$2,047 respectively. In individuals with high CVD risk, overall spending, Medicare, and out-of-pocket spending increased by 44% (95% CI: 12-76), from $7,204 to$10,404; by 75% (95% CI: 22-129), from $3,789 to$6,657; and by 12% (95% CI: -14-37), from $1,328 to$1,484 respectively. For those at low CVD risk, changes in spending were not statistically significant. Per capita averages in 2009 were: overall: $7,938 (SE=608), Medicare:$4,444 (SE=512), and OOP: $1,567 (SE=107). Conclusions: We observed significant increases in spending, especially among patients with pre-existing CVD and those at high CVD risk. More research is needed to investigate whether these increases in spending impacted health-related outcomes and whether different CVD subpopulations benefited differently from this spending growth

Effects of Increased Utilization of CVD Medications by Medicare Beneficiaries on Spending Vary by CVD Status

Background/Aims: To understand the value of our substantial investment in cardiovascular disease (CVD) care, it is important to understand the associations of CVD therapies and spending. The aim of this study was to assess the effect of increased utilization of CVD medications on spending among different CVD risk subgroups. Methods: We used 1999-2009 Medicare Current Beneficiary Survey data to identify 26,903 non-institutionalized, fee-for-Service 65 years or older users of angiotensin converting enzyme inhibitor (ACE), angiotensin receptor blocker (ARBs), other antihypertensives, and statins(61,741person-years). For each drug, we used generalized linear models to estimate the effect of additional prescription fills on spending (i.e. overall, Medicare, out-of-pocket); stratified according to presence of CVD and, in those without CVD, level of CVD risk (high versus low). Results: In the high CVD risk subgroup, each additional prescription fill of ACE, ARB, or statindecreased overall spending (marginal effects: -$274 (CI=-405, -143), -$139 (CI=-300, 22), and -$93 (CI=-250, 64) respectively) and Medicare spending (marginal effects: -$273 (CI=-386, -160), -$156 (CI=-314, 3), and -$160 (CI=-306, -14) respectively). Similar patterns were found in the subgroup with CVD (marginal effects of ACE, ARB, and statins on overall spending: -$184 (CI=-362, -6), -$184 (CI=-377, 8), and -$117 (CI=-235, 2); and on Medicare spending (-$232 (CI=-362, -103), -$186 (CI=-363, -9), and -$229 (CI=-328, -130)). The increased use of these drugs has the opposite effect in the low CVD risk subgroup generally. In contrast, in all 3 subgroups, each additional prescription fill of these drugs generally increased out-of-pocket spending by up to $55. Conclusions: We observed overall cost-savings associated with increased use of CVD medications among both patients with pre-existing CVD and those at high CVD risk. Eliminating or reducing copays for these drugs (i.e. value based insurance design) for such patients may improve their overall health and save money

The Health Effects of Increased CVD Medication use Varies by CVD Status of Medicare Beneficiaries

Background/Aims: Cardiovascular disease (CVD) is the leading cause of death and disability in the United States. The aim of this study was to assess the effect of increased utilization of CVD medications on MI, stroke, and all-cause mortality among different CVD risk subgroups. Methods: We used 1999-2009 Medicare Current Beneficiary Survey data to identify 26,903 non-institutionalized, fee-for-Service Medicare beneficiaries 65 years or older who were users of angiotensin converting enzyme inhibitor (ACE), angiotensin receptor blocker (ARB), other antihypertensive medications, and statin. These beneficiaries contributed a total of 61,741 person-years. For each study drug, we used logistic regression models to estimate the effect of additional prescription fills on MI, stroke, and all-cause mortality; stratified according to presence of CVD and, in those without CVD, level of CVD risk (high versus low). Results: Additional prescription fills of ACE, ARB, other antihypertensives, or statin did not affect MI occurrence among high CVD risk individuals; while in those with CVD, significant effects of ACE and statin were found: OR per 6 additional fills: 0.76 (95% CI= 0.59, 0.98) and 0.74 (CI= 0.60, 0.92) respectively. Additional drug fills did not affect stroke in either subpopulation except fills of other antihypertensives in the CVD subgroup (OR of 6 additional fills: 0.93 (CI= 0.89, 0.98). In both subgroups, an inverse relationship between increased use of the study drugs and all-cause mortality was generally found although insignificant. For those at lower CVD risk, events were generally too few to allow multivariate analyses. Conclusions: We found inverse relationships between increased use of some CVD medications; and MI, stroke, and mortality (although some were not significant) for some subpopulations but not others. Future research is needed to confirm this to justify the need to eliminate or reduce copays for these drugs for some subgroups that may benefit most from them

The impact of changing guidelines on prostate cancer screening in a population-based setting, 2000-2014

Introduction: This study evaluates the potential impact of the publication of conflicting prostate cancer (PCa) screening trial results in 2009 and changes to the US Preventive Services Task Force (USPSTF) guidelines to recommend against screening in 2012 on temporal trends in PSA testing at two participating sites in the NCI-funded Cancer Research Network. Methods: Study participants were men aged 40-80 without a history of PCa who sought care at Fallon Health (Worcester, MA) or Henry Ford Health System (Detroit, MI) between 2000-2014. We used health claims and electronic health record data to identify men who underwent PSA testing per calendar year. We also examined trends in PSA testing among high-risk men (African-American, family history of PCa). Testing rates were compared between 2000-2008, 2009-2012, and 2013-2014. Results: From a population of 279,350 eligible men, 133,038 (48%) had at least one PSA test during the study period. Mean age at PSA test was 57 years, which increased over time at both sites. Overall, PSA testing rates rose between 2000-2008 (27-32% of eligible men per year), but declined between 2009-2012 (25% of eligible men). Testing rates declined further in 2013-2014 (23% of eligible men). We observed similar rates of decline in testing for men aged 55-69 and those aged ≥70. High-risk men were less likely to be screened across all time periods, although data was limited. Conclusions: This analysis of two population-based electronic health datasets provides evidence of a recent decrease in PSA testing, following an increase in the early 2000s. Although we are unable to determine causality, it is plausible that results of recent screening trials and/or changes to the USPSTF guidelines have impacted PSA testing practices over the past 14 years

Who Opens Alerts to Physicians? (And Who Doesn’t?)

Background: Electronic medical records (EMR) provide opportunities to implement systems of information flow, such as alerts to providers. Methods: Within a group practice with an EMR, we conducted a trial of automated alerts to the in-baskets of primary care physicians and staff when patients were discharged from hospital to home. We generated alerts for new medications or monitoring needs. Staff received alerts to schedule office visits. Using EMR “digital crumbs”, we tracked when alerts were viewed. We analyzed the impact of physician age, gender, department, and employment status (full-time, part-time) as well as patient conditions (age, gender, comorbidity, and number of office visits in the previous year) on timely opening. Results: Of 763 alerts to physicians, 616 (81%) were opened within one day. Characteristics associated with timely opening were age \u3c 50 (OR 1.7, 95% CI 1.1, 2.6) and full-time employment (OR 2.9, 95% CI 1.6, 5.2). Of 1928 alerts to staff, 1173 (61%) were opened within one day. Staff of male physicians were more likely to open the alerts within one day (OR 1.8, 95% CI 1.4, 2.4) as were working for the Family Medicine department (OR 1.9, 95% CI 1.3, 2.6) or a sub-specialty department (OR 16.6, 95% CI 2.3, 122.3). Staff of full-time physicians were less likely to open alerts (OR 0.64, 95% CI 0.47, 0.87). Adjusting for patient characteristics had no impact on results. Conclusion: Special efforts may be required to reach physicians working part-time and older physicians. Characteristics related to staff opening of alerts are specific to this group practice, but the high level of variability across physician types and departments is likely to be an issue in many settings. Design of a system directed at reaching staff quickly may require in-depth assessment of work flow and communication patterns in clinical department

Adherence with urate-lowering therapies for the treatment of gout

INTRODUCTION: Adherence to urate-lowering drugs (ULDs) has not been well evaluated among those with gout. Our aim was to assess the level and determinants of non-adherence with ULDs prescribed for gout. METHODS: We identified persons using two integrated delivery systems aged 18 years or older with a diagnosis of gout who initiated use of allopurinol, probenecid or sulfinpyrazone from 1 January 2000 to 30 June 2006. Non-adherence was measured using the medication possession ratio (MPR) over the first year of therapy and defined as an MPR \u3c 0.8. Descriptive statistics were calculated and logistic regression was used to estimate the strength of the association between patient characteristics and non-adherence. RESULTS: A total of 4,166 gout patients initiated ULDs; 97% received allopurinol. Median MPR for any ULD use was 0.68 (interquartile range (IQR) 0.64). Over half of the patients (56%) were non-adherent (MPR \u3c 0.8). In adjusted analyses, predictors of poor adherence included younger age (odds ratio (OR) 2.43, 95% confidence interval (CI) 1.86 to 3.18 for ages \u3c45 and OR 1.44, 95% CI 1.08 to 1.93 for ages 45 to 49), fewer comorbid conditions (OR 1.46, 95% CI 1.20 to 1.77), no provider visits for gout prior to urate-lowering drug initiation (OR 1.28, 95% CI 1.05 to 1.55), and use of non-steroidal anti-inflammatory drugs in the year prior to urate-lowering drug initiation (OR 1.15, 95% CI 1.00 to 1.31). CONCLUSIONS: Non-adherence amongst gout patients initiating ULDs is exceedingly common, particularly in younger patients with less comorbidity and no provider visits for gout prior to ULD initiation. Providers should be aware of the magnitude of non-adherence with ULDs

Use of Electronic Health Record Access and Audit Logs to Identify Physician Actions Following Noninterruptive Alert Opening: Descriptive Study

BACKGROUND: Electronic health record (EHR) access and audit logs record behaviors of providers as they navigate the EHR. These data can be used to better understand provider responses to EHR-based clinical decision support (CDS), shedding light on whether and why CDS is effective. OBJECTIVE: This study aimed to determine the feasibility of using EHR access and audit logs to track primary care physicians\u27 (PCPs\u27) opening of and response to noninterruptive alerts delivered to EHR InBaskets. METHODS: We conducted a descriptive study to assess the use of EHR log data to track provider behavior. We analyzed data recorded following opening of 799 noninterruptive alerts sent to 75 PCPs\u27 InBaskets through a prior randomized controlled trial. Three types of alerts highlighted new medication concerns for older patients\u27 posthospital discharge: information only (n=593), medication recommendations (n=37), and test recommendations (n=169). We sought log data to identify the person opening the alert and the timing and type of PCPs\u27 follow-up EHR actions (immediate vs by the end of the following day). We performed multivariate analyses examining associations between alert type, patient characteristics, provider characteristics, and contextual factors and likelihood of immediate or subsequent PCP action (general, medication-specific, or laboratory-specific actions). We describe challenges and strategies for log data use. RESULTS: We successfully identified the required data in EHR access and audit logs. More than three-quarters of alerts (78.5%, 627/799) were opened by the PCP to whom they were directed, allowing us to assess immediate PCP action; of these, 208 alerts were followed by immediate action. Expanding on our analyses to include alerts opened by staff or covering physicians, we found that an additional 330 of the 799 alerts demonstrated PCP action by the end of the following day. The remaining 261 alerts showed no PCP action. Compared to information-only alerts, the odds ratio (OR) of immediate action was 4.03 (95% CI 1.67-9.72) for medication-recommendation and 2.14 (95% CI 1.38-3.32) for test-recommendation alerts. Compared to information-only alerts, ORs of medication-specific action by end of the following day were significantly greater for medication recommendations (5.59; 95% CI 2.42-12.94) and test recommendations (1.71; 95% CI 1.09-2.68). We found a similar pattern for OR of laboratory-specific action. We encountered 2 main challenges: (1) Capturing a historical snapshot of EHR status (number of InBasket messages at time of alert delivery) required incorporation of data generated many months prior with longitudinal follow-up. (2) Accurately interpreting data elements required iterative work by a physician/data manager team taking action within the EHR and then examining audit logs to identify corresponding documentation. CONCLUSIONS: EHR log data could inform future efforts and provide valuable information during development and refinement of CDS interventions. To address challenges, use of these data should be planned before implementing an EHR-based study.

Adherence with tobramycin inhaled solution and health care utilization

<p>Abstract</p> <p>Background</p> <p>Adherence with tobramycin inhalation solution (TIS) during routine cystic fibrosis (CF) care may differ from recommended guidelines and affect health care utilization.</p> <p>Methods</p> <p>We analyzed 2001-2006 healthcare claims data from 45 large employers. Study subjects had diagnoses of CF and at least 1 prescription for TIS. We measured adherence as the number of TIS therapy cycles completed during the year and categorized overall adherence as: low ≤ 2 cycles, medium >2 to <4 cycles, and high ≥ 4 cycles per year. Interquartile ranges (IQR) were created for health care utilization and logistic regression analysis of hospitalization risk was conducted by TIS adherence categories.</p> <p>Results</p> <p>Among 804 individuals identified with CF and a prescription for TIS, only 7% (n = 54) received ≥ 4 cycles of TIS per year. High adherence with TIS was associated with a decreased risk of hospitalization when compared to individuals receiving ≤ 2 cycles (adjusted odds ratio 0.40; 95% confidence interval 0.19-0.84). High adherence with TIS was also associated with lower outpatient service costs (IQR: $2,159-$8444 vs. $2,410-$14,423) and higher outpatient prescription drug costs (IQR: $35,125-$60,969 vs. $10,353-$46,768).</p> <p>Conclusions</p> <p>Use of TIS did not reflect recommended guidelines and may impact other health care utilization.</p