New QA topics and issues

Citation

Hurst, K. (2008), "New QA topics and issues", International Journal of Health Care Quality Assurance, Vol. 21 No. 7. https://doi.org/10.1108/ijhcqa.2008.06221gaa.001

New QA topics and issues

Article Type: Editorial From: International Journal of Health Care Quality Assurance, Volume 21, Issue 7

I have raised patient satisfaction article plethora in previous editorials. The main question stands – is it possible for new insights to emerge from patient perception research and development? It seems so since Nesreen and Albedaiwi, for example, clearly show that maintaining patient loyalty and ultimately Saudi hospital survival depend on understanding patient perceptions, needs and wants. They show that patients’ desires are not always complex and expensive to fulfil, indeed fairly basic, tangible rather than technical service issues, common to all staff, emerge from the study – although evidence is conflicting at times. Another issue less-often explored in the patient satisfaction literature are gender differences; that is, do women and men evaluate the same service differently? Nesreen and Albedaiwi show that women’s satisfaction scores are higher and the male-female score spread is different. The number of hard core satisfied and dissatisfied male and female patients varies, thereby requiring more subtle quality improvement strategies.

Elleuch’s Japanese outpatient satisfaction study also offers new insights. It is surprising that we do not explore country culture and patient satisfaction relationships more often. Elleuch suggests that Japan, one of four main world cultures, is characterised by courtesy, harmony and conflict avoidance, which may cause Japanese patients to respond differently to QA questions than those raised and cared for in other cultures. One important implication is that if sampling is robust then in-country evaluations are less likely to be affected by cultural variables. On the other hand, benchmarking different country satisfaction scores, even if the same research instruments are used is unsafe.

In short, Elleuch’s case is that Japanese patients are unlikely to openly criticise poor services but neither would they recommend them to family and friends. Japanese patients also are uncomfortable about questioning experts, have a tendency to stay with the “devil you know” and in their minds the other person’s grass may not always be greener. So, using a modified Parasuraman questionnaire, Elleuch explored Japanese outpatient expectations and satisfaction. Three QA factors emerge from her detailed analysis:

1. 1.

   service speed;

2. 2.

   patient-practitioner interaction; and

3. 3.

   service setting and appearance.

These maintain Japanese patient allegiance in a country where they have a wide service-provider choice. Professionals can learn much from these two user satisfaction articles about patients’ intention to return. Clearly, for example, patient loyalty strongly underpins at least two countries’ cultures and despite article surfeit, patient satisfaction studies have much to offer.

India is large and rapidly growing economy while quality health services are in demand; but the country’s affluence-deprivation range causes service developers to think carefully about service levels and cost. Consequently, we published Rahman’s LIFENET’s case study in IJHCQA Volume 21, Issue 3, where we saw the challenge of balancing-the-book in the face of maintaining service quality. In this issue, Rahman and Qureshi take us back to LIFENET and show us Fuzzy Logic’s nature and value for developing new services – including health maintenance organisations. Anything that helps managers expand services in an increasing competitive environment in which survival depends on managerial decision making, will be seized. Moreover, doing this from:

• •

  an external customer-focused standpoint; and

• •

  without ignoring internal customers.

notably workforce planning and development is a bonus. The article exudes creativity and ingenuity.

Heras and his Spanish colleagues raise important QA questions in their article about which I must confess I also have worries. Their starting point is the applicability of business generated QA models such as ISO9001 and EFQM to health and social care, especially elderly residential and care homes. Compliance and evaluation procedures using these accreditation systems are not cheap or easy to achieve and maintain. So, asking if one model fits all is a fair question. The authors treat us to brief but lucid account of some QA models that sector workers use.

Although, ISO9001 accredited homes evaluated better, the difference between those with and without certificates were not attributable to certification. Health and social care outcomes are not easy to measure, which may explain the authors’ inability to attribute cause and effect. Coal-face workers, nevertheless, were sceptical and complained about what they saw as additional workload burdens imposed by bureaucratic certification processes with little return. The authors also found differences in large and small elderly care homes; the latter of course are less likely to have the resources (notably staff numbers and mix) needed to implement accreditation systems. The authors conclude by suggesting that a more user-friendly chimera built from existing QA models may be needed to improve small nursing and residential home service quality.

Doherty and his Australian R&D team report a simple and elegant evaluation study with findings having powerful implications. The burden collecting clinical data and the way auditing eats into treatment and care time needs to be reduced. So their starting point is automated data collection designed to decrease data collection time and effort. But do automated systems increase information accuracy compared to manual systems? Surprisingly, despite its obvious importance, this is a thin research area. Fortunately, therefore, the authors select important clinical cases and measure the extent to which clinical guidelines were followed as a means of confirming that evidence-based medicine is in vogue. They compared relevant information collected manually and electronically and as good R&D reporters, they tell us about the study’s limitations, but as readers will see, their study is robust not least because researcher inter-rater reliability was checked. They found that automated systems meant fewer clinical guideline auditing forms were completed, which paradoxically, gave the department a higher clinical guideline compliance score. Another valuable element in the article is a description of the process steps where clinical guideline auditing can go wrong.

We do not receive many laboratory service-based manuscripts at IHHCQA, but clearly this service’s efficiency and effectiveness, as Harrison and McDowell show, are important to patient processes and outcomes. Their detailed literature review gives a flavour of what automated laboratory information systems (LIS) achieve, especially test turn-around time, error trapping (e.g. wrong patients), cost and workload reductions. It needed an expert to explain laboratory IT service challenges and the authors’ account is illuminating. Until this article is read, interested observers may not realise the complexity surrounding laboratory IT and hospital-wide interfaces such as LISs “talking to” electronic patient records.

The article’s mainstay is laboratory service efficiency and effectiveness and the authors’ examples are staggering. So should hospitals move towards automated LISs? Their survey results are encouraging but some US hospital staff appear tardy especially faced with government and other purchaser reimbursement demands. Clearly, LIS implementation barriers are likely to take time to resolve. Finally, the article has a bonus – an explanation of Six Sigma lean thinking in a laboratory QA context.

Keith Hurst