Editorial

Keith Hurst (Hurst Research Ltd., Mansfield, UK)

International Journal of Health Care Quality Assurance

ISSN: 0952-6862

Article publication date: 8 August 2016

182

Citation

Hurst, K. (2016), "Editorial", International Journal of Health Care Quality Assurance, Vol. 29 No. 7. https://doi.org/10.1108/IJHCQA-05-2016-0076

Publisher

:

Emerald Group Publishing Limited


Editorial

Article Type: Editorial From: International Journal of Health Care Quality Assurance, Volume 29, Issue 7.

Cost saving quality assurance strategies – topics and methodology

Great hopes are held for healthcare service quality assurers to reduce costs by improving service efficiency and effectiveness. Abandoning non-effective treatments, for example, seems a blindingly obvious action, but one that seems to be ignored. One jaw-dropping outcome that emerges each year from the NHS patient reported outcome study survey, is the reduced post-treatment quality of life (QoL) reported by patients undergoing certain surgical interventions (www.hscic.gov.uk/catalogue/PUB20282). Is this outcome true for life-saving surgery too? That is, despite life-saving cancer surgery and adjuvant chemotherapy/radiotherapy, is post-treatment improved QoL guaranteed or is it a moot point; i.e., merely surviving a life-threatening encounter is sufficient? Nahla Fawzy Abou Elezz et al., in this issue, highlight the QoL drivers and restrainers among post-treatment breast cancer sufferers. Most readers would not be surprised about radical mastectomy’s influence on women’s QoL. The cosmetic effects alone daunt many women. Readers, on the other hand, may be taken aback by driver and restrainer complexity, and their inter-relationships, especially the two-way interaction between breast surgery women and their family members. The study does as an excellent job spotlighting QoL issues among breast cancer sufferers, but, unfortunately, problems are intransigent and are hard to resolve without significant spending. Nevertheless, despite the competition for healthcare money; clearly, here is one group that deserve the utmost effort to help sufferers through a difficult life phase.

Perhaps one solution to redistributing resources to priority services like breast cancer treatment and care is to redirect healthcare savings achieved in one service to priority care; i.e., ring fencing, rather than money going into the health service’s general coffers? Kenneth Yip et al., in this issue, report an elegant simulation modelling study in which Hong Kong phlebotomy service efficiency and effectiveness were markedly improved. From their description, local phlebotomy services cried out for workflow analysis and improvement because services were disjointed and patients attending a high-demand service experienced lengthy waits. Mapping phlebotomy resources to peak demand in the department and obtaining stakeholder support to make changes were challenges skilfully overcome by the authors. After the study’s recommendations were implemented, knock-on positive effects in the outpatient department (OPD) were striking; e.g., shorter queues and waits, fewer patient and staff complaints, and freeing rooms for other OPD services. If ever there was an argument that analytics and simulation can improve operational planning and action, which ultimately saves money, then here it is.

Despite Kenneth Yip et al.’s reforming work, outpatient, emergency department and admission waiting times elsewhere have an inevitability in modern healthcare owing to rising demand and falling resources. It is a lose-lose situation; i.e., service providers and outpatients face daily bottlenecks and patients and their employers lose income owing to lost worktime. So, if patients wait well beyond their appointment time, then the service they receive must exceed their expectations otherwise failure to return and not recommending the service to family and friends are likely. We’d be surprised if perceptions change among patients who experience excessive waits didn’t change. If they do, then what elements are most affected? Payal Mehra, in this issue, explores the relationship between waiting time and patient perceptions. Readers may be surprised at the dependent variables selected by the author (which were exposed to high-level statistical analyses), such as provider communication styles. Variables selection was driven largely by the author’s literature review. Unsurprisingly, outpatients waiting longer were less satisfied. Other extended wait outcomes fell into drivers and moderators – and there are surprises – gender differences, for example; i.e., men and women’s waiting tolerances are different. The author has stimulated a promising research field, one in which it seems, we are only just scraping the surface. Results are important; i.e., because waiting is inevitable, providers need to spot the clues that prompt service improvement other than reducing the wait (which should take priority).

Clinical risk management (CRM) is a popular topic with our authors and readers. Its role in healthcare-spending is paramount; i.e., one clinical error could cost service providers, at fault, significant legal costs. Unsurprisingly, therefore, we regularly receive CRM related articles that follow the audit spiral: setting service standards; comparing services against standards; and changing service or standards – the last element having a significant effect on financial savings. In this issue, Pierfrancesco Tricarico et al., describe a major, multicentre CRM project that led to an impressive self-assessment tool based incorporating seven domains: governance; communication; knowledge and skills; safe environment; care processes; managing adverse events; and learning from experience. These elements were underpinned by 52 standards in which, after measurement, services were placed into four status levels. The project’s methodological foundation is impressive: a detailed literature review identifying standards topics and two independent expert panels who refined the standards and establish related measures. Benchmarking possibilities show promise once a CRM database is established. Rolling out the project to other European countries is also an aim. The project could easily overtake other accreditation systems such as ISO because self-assessment is cheaper and easier to implement, although more subjective.

We have to applaud researchers who, rather than starting an R&D project afresh (at significant cost), better use extensive healthcare data that we hold in our databases. Applauds should get louder if researchers also tap secondary data to highlight variables that influence patient survival and service costs – a steadily growing theme among IJHCQA authors. In this issue, Agim Kukeli and Skender Buci audit clinical records and extract and model liver injury patient data. Trauma is a growing problem in Albania, so the authors modelled liver trauma patient characteristics, modelling them to: predict survival; underline better treatment options; inform relatives and family; and help staff to use resources to best effect. Albanian liver trauma patient survival is relatively good. A bonus was the systematic evidence that emerged from the models, which could be used to more broadly inform liver trauma treatment and care.

Instances where personal medical history were released to the press (accidentally or deliberately) or where patient’s case notes were found in public rubbish dumps, do not inspire public confidence. The issue becomes more acute as more information is held electronically. We should not be surprised, therefore, that 1.5 m patients in one UK NHS-wide survey refused to allow their information to be shared except for clinical purposes (www.hscic.gov.uk/catalogue/PUB20527), which underlines that patients trust their healthcare professionals less than we imagine. Eva Söderström et al., explore the relationship between electronic health records and patient trust. Their case studies include patient and staff perceptions and, as in all these things, the situation is more complex than first imagined. The service flaws unearthed by the authors call for managerial action to avoid deteriorating trust between patients and professionals, which may lead to poor interaction, compliance and safety, and wasted costs. The authors’ trust matrix encapsulates, neatly and clearly, issues and actions for clinicians and managers.

The common theme in this issue is the increasing pressure healthcare staff are under to improve service efficiency and effectiveness; i.e., maintaining quality and reducing costs. Xiuzhu Gu and Kenji Itoh in this issue, explore what state-of-the-art performance indicators (PIs) might look like. The authors’ work starts on a sound footing – raising a fundamental question – how do we know what to improve if we don’t know what and how to measure services? Their literature review revealed something that we all suspected – multiple PIs that overwhelm healthcare staff. In one country-wide NHS Benchmarking Database (1,500 data sets), for example, analysts update around 80 data sets (from multiple sources) per week. Because this important information is in one place, healthcare managers, wishing to keep abreast, find locating and reviewing relevant data an easier task. There’s scope for more improvement, however, Xiuzhu Gu and Kenji Itoh employed factor analysis to reduce the PI list emerging from their literature review to a smaller, manageable, but effective eight factors. However, they unearthed unexpected problems – hospital managers have different views and priorities than clinicians, and issues that we might think are high on the agenda; i.e., staff development, seem less important to managers. There were, on the other hand, several internal and external customer-related issues that were deemed high importance; e.g., patient and staff safety; indeed, the authors’ eight factors strike a nice balance between patient and employee oriented PIs. It’s encouraging that PI contribution to healthcare efficiency and effectiveness, and their utility are becoming more user-friendly.

Keith Hurst

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