Over 150 potentially low-value health care practices: an Australian study

Internationally, there is a groundswell of activity seeking to identify and reduce the use of health care interventions that deliver marginal benefit, be it through overuse, misuse or waste. England’s National Institute for Health and Clinical Excellence (NICE) began this work in 2005,1 and most recently, the Choosing Wisely campaign led by physician groups in the United States is attracting worldwide attention.2 Other countries, and individual jurisdictions within countries, are also considering the best approaches to reducing the use of low-value health care practices. One problem has been fairness and transparency in identifying and prioritising suboptimal health care practices for consideration. Here, we report on Australian activities; in particular, on a collaborative project aiming to identify existing health care interventions that might warrant analysis from a health technology reassessment and practice optimisation perspective.

Australia’s Medicare Benefits Schedule (MBS) — a cornerstone of the Australian universal health care system — lists the rebates that are payable to patients for private medical services provided on a fee-for-service basis, and describes these services. In 2012, the MBS contains almost 6000 items (not including pharmaceuticals); only around 3% of these (accounting for about 1% of total MBS expenditure) have been formally assessed against contemporary evidence of safety, effectiveness and cost-effectiveness.3

In the 2009–10 Budget, the Australian Government announced funding over 2 years for a range of projects to develop and implement a new evidence-based MBS Quality Framework — subsequently named the Comprehensive Management Framework for the MBS (CMF)3 — for managing the MBS into the future. The CMF set out to establish new listing, fee-setting and review mechanisms to ensure that prospective and already listed items: (i) meet agreed standards for effectiveness and safety; (ii) are likely to lead to improved health outcomes for patients; and (iii) represent value for money. The CMF is consistent with international efforts to maximise health outcomes and efficiency. CMF reform sought to improve transparency and provide a stronger evidence base for services listed on the MBS. Box 1 lists the key elements and principles of the framework.

Before the initial Quality Framework was introduced on 1 January 2010, there was no formal process for evaluating existing MBS items that had not been assessed by the Medical Services Advisory Committee (MSAC). Without formalised reviews or a built-in method to update MBS items as clinical practice evolves, items on the MBS have become outdated. Thus, patients may receive treatments that have not been proven to be clinically effective, and financial incentives within the MBS may not always be aligned with best clinical practice.

A universal challenge in this area is to establish a systematic and transparent strategy to identify potential “low-value” clinical services for review.4-7 Traditional literature search strategies for “unsafe or ineffective care” offer limited utility in isolation.4 In this report, we describe one CMF project that used a range of information sources to identify items for review through an expanded “environmental scanning” approach. The 2-year CMF timeline dictated an expedited process. This work was developed and undertaken over 8 months in the financial year 2010–11.

A multiplatform approach for searching for and identifying potential medical services for review was developed. This comprised the following three key elements.

Peer-reviewed literature search: a detailed search strategy was applied to the PubMed search platform (Box 2).

Targeted database search: these were conducted of the Cochrane Library, National Institute for Health and Clinical Excellence (NICE) “do not do” recommendations,8 BlueCross BlueShield Association Technology Evaluation Center assessments9 and the Canadian Agency for Drugs and Technologies in Health (CADTH) health technology assessments.10

Opportunistic sampling: drawing on our experience (from a previous and ongoing program of work in this area) and links with clinical and non-clinical stakeholder groups, both within Australia and internationally, from whom nominations (with evidence) for candidate services were collected.

Each of these three elements contributed to the final sample that was screened for potential candidate services for reassessment.

A total of 5209 articles were screened for eligibility, resulting in 156 potentially ineffective or unsafe services being flagged for consideration (Appendix). The list includes examples where practice optimisation (ie, comparing the relative value of one treatment option against others) might be required. The Appendix details all the services we identified, including any citations that drew attention to their status as potential candidates, and an extract from the article highlighting key issues relevant to the service. Box 5 lists the 13 services identified by more than one search method; three services were identified by all three methods. While this serves to highlight the crossover points of the search strategies we used, there are other factors related to the candidate services that may influence their relative priority in any assessment process (eg, predominant safety concerns, strong evidence, high volume, cost-effective alternative, etc).4

In this project, we sought to develop and implement a systematic, evidence-based and transparent process for identifying potentially low-value services in health care. We present this list of candidate services for analysis and debate within and between clinical, research, patient and policy stakeholder communities. Services were identified through a novel search strategy and, although created for and mapped against Australia’s MBS, they offer insights for any health care system considering a health technology reassessment agenda. The specificity of services is open for critique, and we expect that context-specific clinical detailing will exclude some services from consideration and/or refine the questions that have been raised within the literature about their uses.

The process we describe in this report has a number of limitations, primarily related to the short time frame imposed on it. Sampling from the broad literature searches based on date of publication is likely to identify technologies or services for which recent evidence may suggest a level of ineffectiveness, and therefore risks missing those whose safety, effectiveness or efficacy has not recently come into question. In addition, time and resource constraints also limited the number of articles retrieved through each filter that could be reasonably evaluated. Thus, only a fraction of potentially relevant articles were included. However, combining these searches with broad reviews of key assessment agencies (CADTH, NICE, etc), as well as obtaining expert clinical input, helps to moderate this potential bias and captures a breadth of medical services that are of key interest across clinical settings and stakeholder groups. Importantly, our process was not intended to be exhaustive or to act as a tool for prioritisation; rather, it aimed to provide a transparent, evidence-based approach to identifying potentially ineffective services. Further testing and refinement of search terms, inclusion and exclusion criteria and database sources is likely to yield important insights into how this process may be improved and tailored to suit specific needs.

Our analysis has highlighted some of the tensions that exist between the paradigm of health technology assessment and the nature of guided service reimbursement, including fee-for-service. Health technology assessment and other clinical assessments of health services are, by nature, geared towards examining services and technologies in very specific populations and for very specific indications. This can be at odds with the broader nature of schedule or service item descriptors. Our work has confirmed that services that are ineffective and/or unsafe across the entire patient population to which they are applied are probably quite rare. Most often, a service shows differential effectiveness profiles, dependent on the characteristics of the population in whom it is applied. Research must indicate the populations most likely to benefit from or be harmed by services, thus allowing the development of effective policies for refining the indications for coverage and minimising use outside these indications. How this is achieved in various systems will differ: fee-for-service systems might require tighter clinical item and patient descriptors and fee refinements, whereas program budget, bundled or capitated systems can introduce incentives for optimal use of services that offer the best patient outcomes.

For groups pursuing a health technology reassessment agenda, the next steps in the process requires further prioritisation of candidate services to a shortlist of those that may go on to formal review. Numerous methods have been proposed for this, each being somewhat context-specific.4-7 The assessment type that offers the greatest efficiency needs to be decided on. For example, initial rapid reviews as opposed to full health technology assessments may offer an efficient means of generating value of information to enhance the prioritisation process.

We also acknowledge that there are challenges in reducing or removing candidate services that are confirmed as having low value. Existing technologies or practices have complexities that do not beset those that are new or emerging, mostly because of their established status in medicine and society. These challenges have been discussed elsewhere.12-19

Limited resources mean that nations cannot escape having to make difficult health care choices. Identifying and reducing the use of low-value care is becoming a priority for an increasing number of jurisdictions. Each recognises that cost savings or cost-neutral changes can be made within existing health budgets by reducing the use of existing services that offer little or no benefit relative to the cost of their public subsidy. This would allow funding to be reallocated to more beneficial or cost-effective services, thus maximising health gain. We share this project as a step towards fulfilling that objective.

4 Search process

CADTH = Canadian Agency for Drugs and Technologies in Health. HTA = health technology assessment. NICE = National Institute for Health and Clinical Excellence. RCT = randomised controlled trial. TEC = Technology Evaluation Center. * Standard filters: humans, English, not pharmaceuticals. † Final contribution to list (Appendix) after filtering and mapping evidence for relevance and applicability to existing Medicare Benefits Schedule items; the final list consists of health care services identified by more than one strategy (Box 5).