Organisational matters Table 1 Top ‘‘natural’’ categories of adverse event in hospital, and costs in terms of additional length of stay (from Runciman et al16) Mean additional No of events in length of stay (days) each category Total no of extra days in hospital Top principal adverse event category Ongoing pain/restricted movement following back surgery 22 No, delay, inadequate investigations ischaemic heart disease 13 Wound infection following peripheral procedure 11 Incisional hernia: postprocedural 10 Postoperative bowel obstruction/adhesions 13 Injury due to fall in nursing home 12 Failed/blocked/ruptured/aneurysm, vascular grafts 13 Recurrent incisional hernia 9 Pulmonary embolism postoperatively 8 Wound infection following abdominal/retroperitoneal/pelvic 5 procedure Catheter-related urinary-tract infection 5 Each of these outcome categories can arise from a wide variety of different causes. 22 34 29 27 21 19 17 20 22 35 37 474 451 314 271 271 219 215 190 185 178 174 attributes of MBC, and explore the types of MBC models that best suit the needs of healthcare, based upon first principles analysis and experimentation. DESIGNING A PATIENT SAFETY MARKET—‘‘CAP AND TRADE’’ So, can MBC be used to reduce avoidable patient harm? This has never been tried before. A safety-trading market might look something like this: 1. Set a patient safety price. A value is set on each preventable adverse event (PAE), based upon its estimated cost to the system. 2. Establish system-wide targets. Using an estimate of the current baseline PAE rate, set a global target and progressively reduce this over time. 3. Allocate organisational targets. For clinical organisations, estimate their current baseline PAE rate, and provide them with ‘‘credits’’ equal to a reduced target. Organisations must find ways to meet that target. 4. Create a safety market for trading safety credits. Organisations that reduce PAE rates below set targets have surplus credits, which they can sell. Organisations that miss targets must purchase market credits to meet target, or pay the regulator for credits at a set price. Failure to comply generates a large penalty. 5. Police the market through an auditing mechanism. Audit need not be universal but will need to be visible, credible, perhaps random to ensure compliance and responsive to attempts to distort, cheat or evade. 6. Allow for certification and audit of authorised third-party organisations. New organisations can independently initi- ate verifiable harm reduction projects to generate new credits. Figure 1 shows a possible safety market structure. The players include a regulator, who polices market mechanisms, health service organisations that meet harm reduction targets and authorised third-party organisations. The marketplace allows for the verifiable exchange of credits. MEASURING AND PUTTING A PRICE ON SAFETY Central to the safety market are pricing and measurement mechanisms. The Agency for Healthcare Research and Quality (AHRQ) has defined 20 hospital and seven area-level safety indicators,14 and P4P programmes lead the way in identifying meaningful safety process and outcome measures, although this is an ongoing research area. 100 MBC would require such diverse safety indicators to collapse into a few, and perhaps just a single control variable. Kyoto targets, for example, are expressed in a single unit, a tonne of CO2, which is associated with a ‘‘carbon price’’ but actually covers a basket of six separate greenhouse gasses, accounting for 92% of global warming.15 Other gases are excluded because of concerns about their measurement. A weighting index converts the impact of each gas into a CO2 equivalent, so that they are interchangeable on the market. The resultant tradable com- modity is sometimes known as an emission reduction unit (ERU). Can we develop a similar tradable patient harm reduction unit (HRU) (fig 2)? Could we identify a ‘‘basket’’ of leading PAE classes to cover a good proportion of clinical practices, and associate each class with a common measure of resource consumption, which can be assigned a cost? Recent work suggests that such an approach is indeed possible. We now know that a wide variety of PAE causes can be collapsed into a smaller basket of ‘‘natural’’ outcome categories, each category associated with a cost (additional days length of stay).16 Runciman et al’s analysis of 15 000 hospital admissions also found that 25% of PAE resources were expended on the 11 most frequent PAE categories (table 1), 50% by the top 45. Any such basket of PAEs is bound to be revised as we better understand how it relates to safety outcomes. There are several benefits of a composite indicator like the HRU over simpler more reductionist measures such as the Hospital Standardized Mortality Rate (HSMR). First, an HRU based, say, upon length of stay is a much more fine-grained measure of clinical practice. Many of the adverse events in table 1, for example, would not translate into significant changes in a service’s mortality rates. Second, the composite nature of the HRU allows it to be more specifically targeted to the practices of different sectors, via the basket of PAEs chosen for inclusion. For example, the PAE basket for primary care is likely to be quite different to that used to monitor care in the acute hospital sector. Such differences may also come some way to explaining why a single measure like the HSMR is neither a consistent nor a reliable measure of quality.17 ESTABLISHING A SAFETY BASELINE AND SETTING TARGETS Both P4P programmes and carbon markets have explored different approaches to establishing performance baselines and targets. Absolute targets set identical goals across all organisa- tions—for example, each hospital must reduce HRUs by 5000 Qual Saf Health Care 2009;18:99–103. doi:10.1136/qshc.2007.025833