Ministry of Health, New Zealand, 2004 - present
Goal: Prioritize patients for access to ‘elective’ (non-urgent) health services
- Inconsistent prioritization of patients
- Convince decision-makers there’s a problem to fix
- Need for consensus
- Geographical spread of decision-makers
- Need to iteratively improve the tool with minimal rework
Outcome: Points systems for different types of elective surgery
In public health systems in New Zealand and worldwide there is insufficient capacity to be able to treat all patients for elective health services immediately. Prioritizing patients, usually via waiting lists, is therefore inevitable.
Before being overhauled in 1998, NZ’s waiting lists were criticised for being “a diverse mix of patient cases – placed and kept on the list for a number of different reasons, and with no agreed criteria for admission to the list.” (Fraser, Alley & Morris 1993).
According to one cardiologist: “Manipulation by referring doctors, friends in high places, MP letters, or just persistent nagging, and just slight exaggeration of symptoms, is rampant, and the poor benign patient simply sits on the list and is leap frogged.” (Hadorn & Holmes 1997).
To remedy these problems, ‘Clinical Priority Assessment Criteria’ (CPAC), often implemented as points systems (ie. explicit criteria and weights), were introduced nationwide in 1998. Not long afterwards, however, these initial points systems were criticised for being largely arbitrary and resulting in significant numbers of patients being mistakenly denied treatment (sometimes with fatal consequences).
New points systems
Since 2004, using 1000minds software, NZ’s Ministry of Health has led projects to create and validate new points systems for elective services – with the ultimate goal of more equitable access and better patient outcomes overall. Inspired by NZ’s success, since 2008 the same process supported by 1000minds has been used in the public health systems of Canada’s western provinces.
The first NZ points systems created using 1000minds were for coronary artery bypass graft (CABG) surgery. They were developed in a Ministry of Health-led collaboration with the NZ Region of the Cardiac Society of Australia & NZ (CSANZ) and with advice from the National Ethics Advisory Committee, the Medical Council, the Health & Disability Commission, the Human Rights Commission and Māori representatives.
A group of cardiologists and cardiac surgeons in different locations throughout NZ used 1000minds via the Internet and teleconferences to create points systems for prioritizing patients for CABG surgery.
Measures of success
The validity of the new points systems was established by examining the face validity of the relative importance of the criteria implied by the point values and by comparing the ranking of patient case descriptions (‘vignettes’) from the points systems with clinicians’ consensus intuitive rankings (in effect, the ‘gold standard’).
A survey of the participating clinicians revealed high levels of ‘user’ satisfaction with the 1000minds method/software. The CABG points systems have been formally accepted by CSANZ and are in use throughout NZ.
Other points systems have been successively created (and clinically endorsed) via collaborations with the relevant clinical professional organizations: hip and knee replacements, varicose veins surgery, cataract surgery, gynaecology, plastic surgery, otorhinolaryngology, and heart valve surgery respectively. Other points systems are planned for the future.
Based on this body of work, 1000minds received several national and international innovation awards, and the process has been written up (Hansen et al 2012) so that it is possible for readers to appreciate how they might use 1000minds to create points systems for their own patient-prioritization applications.
Canada and the UK
As well as in NZ, 1000minds has been used since 2008 in the public health systems of Canada’s western provinces (eg. Fitzgerald et al 2011), and for prioritizing social services, including health care, for ‘people in need’ in the UK.
Other health uses of 1000minds include: health technology prioritization (Golan & Hansen 2012), measuring medical research outcomes (eg. Dobson et al 2013), planning for disasters and pandemics (eg. allocating Tamiflu), assessing students for admission to medical schools and health professionals for jobs (eg. junior doctors for hospitals), allocating research funds, etc.
F Dobson, R Hinman, E Roos et al (2013), “OARSI recommended performance-based tests to assess physical function in people diagnosed with hip or knee osteoarthritis”, Osteoarthritis & Cartilage 21, 1042-52.
A Fitzgerald, C De Coster, S McMillan et al. (2011), “Relative urgency for referral from primary care to rheumatologists: The priority referral score”, Arthritis Care & Research 63, 231-39.
G Fraser, P Alley & R Morris (1993), Waiting Lists & Waiting Times: Their Nature & Management, National Advisory Committee on Core Health & Disability Support Services.
O Golan & P Hansen (2012), “Which health technologies should be funded? A prioritization framework based explicitly on value for money”, Israel Journal of Health Policy Research 1, 44.
D Hadorn & A Holmes (1997), “The New Zealand priority criteria project. Part 2: Coronary artery bypass graft surgery, British Medical Journal 314, 135-8.
P Hansen, A Hendry, R Naden, F Ombler & R Stewart (2012), “A new process for creating points systems for prioritizing patients for elective health services”, Clinical Governance: An International Journal 17, 200-209.