Did Medicare Part D Affect National Trends in Health Outcomes or Hospitalizations? A Time-Series Analysis

Pharmaceutical policies: effects of regulating drug insurance schemes

BACKGROUND

Drug insurance schemes are systems that provide access to medicines on a prepaid basis and could potentially improve access to essential medicines and reduce out-of-pocket payments for vulnerable populations.

OBJECTIVES

To assess the effects on drug use, drug expenditure, healthcare utilisation and healthcare outcomes of alternative policies for regulating drug insurance schemes.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, nine other databases, and two trials registers between November 2014 and September 2020, including a citation search for included studies on 15 September 2021 using Web of Science. We screened reference lists of all the relevant reports that we retrieved and reports from the Background section. Authors of relevant papers, relevant organisations, and discussion lists were contacted to identify additional studies, including unpublished and ongoing studies.

SELECTION CRITERIA

We planned to include randomised trials, non-randomised trials, interrupted time-series studies (including controlled ITS [CITS] and repeated measures [RM] studies), and controlled before-after (CBA) studies. Two review authors independently assessed the search results and reference lists of relevant reports, retrieved the full text of potentially relevant references and independently applied the inclusion criteria to those studies. We resolved disagreements by discussion, and when necessary by including a third review author. We excluded studies of the following pharmaceutical policies covered in other Cochrane Reviews: those that determined how decisions were made about which conditions or drugs were covered; those that placed restrictions on reimbursement for drugs that were covered; and those that regulated out-of-pocket payments for drugs.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted data from the included studies and assessed risk of bias for each study, with disagreements being resolved by consensus. We used the criteria suggested by  Cochrane Effective Practice and Organisation of Care (EPOC)  to assess the risk of bias of included studies. For randomised trials, non-randomised trials and controlled before-after studies, we planned to report relative effects. For dichotomous outcomes, we reported the risk ratio (RR) when possible and adjusted for baseline differences in the outcome measures. For interrupted time series and controlled interrupted time-series studies, we computed changes along two dimensions: change in level; and change in slope. We undertook a structured synthesis following the EPOC guidance on this topic, describing the range of effects found in the studies for each category of outcomes.

MAIN RESULTS

We identified 58 studies that met the inclusion criteria (25 interrupted time-series studies and 33 controlled before-after studies). Most of the studies (54) assessed a single policy implemented in the United States (US) healthcare system: Medicare Part D. The other four assessed other drug insurance schemes from Canada and the US, but only one of them provided analysable data for inclusion in the quantitative synthesis. The introduction of drug insurance schemes may increase prescription drug use (low-certainty evidence). On the other hand, Medicare Part D may decrease drug expenditure measured as both out-of-pocket spending and total drug spending (low-certainty evidence). Regarding healthcare utilisation, drug insurance policies (such as Medicare Part D) may lead to a small increase in visits to the emergency department. However, it is uncertain whether this type of policy increases or decreases hospital admissions or outpatient visits by beneficiaries of the scheme because the certainty of the evidence was very low. Likewise, it is uncertain if the policy increases or reduces health outcomes such as mortality because the certainty of the evidence was very low.

AUTHORS' CONCLUSIONS

The introduction of drug insurance schemes such as Medicare Part D in the US health system may increase prescription drug use and may decrease out-of-pocket payments by the beneficiaries of the scheme and total drug expenditures. It may also lead to a small increase in visits to the emergency department by the beneficiaries of the policy. Its effects on other healthcare utilisation outcomes and on health outcomes are uncertain because of the very low certainty of the evidence. The applicability of this evidence to settings outside US healthcare is limited.

The offset effect of pharmaceutical innovation: A review study

It is well known that pharmaceutical innovation has improved the health and quality of life of patients. It is however sometimes forgotten that new drugs also have the potential of improving the efficiency and the sustainability of the healthcare system. The objective of this review is to shed light on the magnitude of the offset effect that drugs may have in the realm of the healthcare system and for society as a whole. A narrative literature review was carried out. This review demonstrated that a growing body of literature has tried to measure the magnitude of the offset effect associated with pharmaceutical innovation, both at the aggregate level and for different diseases. There is evidence that the aggregate use of new drugs can generate net savings to the healthcare system and to society, as they may release both healthcare and non-healthcare resources for alternative uses. A high degree of heterogeneity in the magnitude of the effect has been found across different pathologies and different types of drugs.

Prescription Drug Coverage and Outcomes of Myeloma Therapy Among Medicare Beneficiaries

PURPOSE

Novel parenteral (bortezomib) and oral (lenalidomide) therapies have improved survival in myeloma, but the standard Medicare benefit covers only parenteral drugs. We examined the association between prescription drug coverage, receipt of therapy, and survival among Medicare beneficiaries with myeloma.

METHODS

Using SEER-Medicare data, we identified enrollment in a Medicare Part D plan (PDP) or other creditable prescription drug coverage (OCC) among 9,755 beneficiaries who were diagnosed with myeloma in 2006 to 2011. We examined the receipt of active myeloma therapy and that of classic cytotoxic agents or bortezomib as first-line regimen and overall survival. We report relative risk (RR) for binary outcome comparisons and 3-year restricted mean survival time (RMST) ratios, with 95% CI, adjusting for baseline patient- and disease-related characteristics. Beneficiaries with diffuse large B-cell lymphoma, a cancer that is uniformly treated with parenteral chemotherapy, served as a comparison cohort.

RESULTS

Compared with beneficiaries without prescription drug coverage, PDP or OCC enrollees were more likely to receive active myeloma care, and PDP enrollees were less frequently treated with parenteral agents (adjusted RR, 0.86; 95% CI, 0.80 to 0.93) or classic cytotoxic agents in particular (RR, 0.62; 95% CI, 0.51 to 0.76). Overall survival was significantly better for beneficiaries with PDP coverage (adjusted RMST ratio, 1.16; 95% CI, 1.11 to 1.20) or OCC (RMST ratio, 1.16; 95% CI, 1.12 to 1.21). In contrast, we observed no survival differences by prescription drug coverage status in the control cohort with lymphoma.

CONCLUSION

Prescription drug coverage is associated with decreased use of classic cytotoxic chemotherapy and better survival among Medicare beneficiaries with myeloma, which suggests improved access to all existing treatment options. As oral targeted agents increasingly replace parenteral chemotherapy in oncology, adjustments in coverage policy are needed to ensure access to optimal treatment.

False Dichotomies and Health Policy Research Designs: Randomized Trials Are Not Always the Answer

Some medical scientists argue that only data from randomized controlled trials (RCTs) are trustworthy. They claim data from natural experiments and administrative data sets are always spurious and cannot be used to evaluate health policies and other population-wide phenomena in the real world. While many acknowledge biases caused by poor study designs, in this article we argue that several valid designs using administrative data can produce strong findings, particularly the interrupted time series (ITS) design. Many policy studies neither permit nor require an RCT for cause-and-effect inference. Framing our arguments using Campbell and Stanley's classic research design monograph, we show that several "quasi-experimental" designs, especially interrupted time series (ITS), can estimate valid effects (or non-effects) of health interventions and policies as diverse as public insurance coverage, speed limits, hospital safety programs, drug abuse regulation and withdrawal of drugs from the market. We further note the recent rapid uptake of ITS and argue for expanded training in quasi-experimental designs in medical and graduate schools and in post-doctoral curricula.