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Developing technological innovations in healthcare is made complex and difficult due to effects upon the practices of professional, managerial and other stakeholders. Drawing upon the concept of boundary object, this paper explores the challenges of achieving effective collaboration in the development and use of a novel healthcare innovation in the English healthcare system.

A case study is presented of the development and implementation of a smart phone application (app) for use by rheumatoid arthritis patients. Over a two-year period (2015–2017), qualitative data from recorded clinical consultations (n = 17), semi-structured interviews (n = 63) and two focus groups (n = 13) were obtained from participants involved in the app's development and use (clinicians, patients, researchers, practitioners, IT specialists and managers).

The case focuses on the use of the app and its outputs as a system of inter-connected boundary objects. The analysis highlights the challenges overcome in the innovation's development and how knowledge sharing between patients and clinicians was enhanced, altering the nature of the clinical consultation. It also shows how conditions surrounding the innovation both enabled its development and inhibited its wider scale-up.

By recognizing that technological artefacts can simultaneously enable and inhibit collaboration, this paper highlights the need to overcome tensions between the transformative capability of such healthcare innovations and the inhibiting effects simultaneously created on change at a wider system level.

The purpose of this paper is to assess the patient’s perspective on a dedicated clinic set up for patients diagnosed with an inflammatory arthritis who are being treated with a biologic. It proposes that dedicated clinics offer better overall care. The aim of this quality improvement survey is to evaluate the level of patient satisfaction with this clinic and identify any unmet needs.

This study was based on a quality improvement survey, which was developed using Zineldin’s five qualities model and assessed various aspects pertaining to service quality and improvement. A structured interview approach was used and 44 consecutive patients were recruited.

This paper explores key aspects that influence patient satisfaction within a rheumatology outpatient setting such as education on arthritis and biologics and involvement in decision making. It provides insight on what patients value most and it also addresses organizational aspects that can have an impact on patient satisfaction. It suggests that service quality can be linked to the degree of patient satisfaction.

Direct interviewing of patients could have introduced a source of bias whilst questions are being answered. On the other hand, it provided an opportunity to clarify instantly any doubts and therefore avoiding any inadvertent errors.

This paper reinforces that specialized clinics enable the caring rheumatologist to provide better care for patients on biologics. Service providers should continue developing their services around the patient’s needs and perspectives in order to continue improving the service.

Dedicated biologic clinics allow more judicious monitoring of patients who are taking these highly efficacious but costly medications.

This survey has reinforced that patients highly value dedicated clinics. These results strengthen the case that healthcare services should continue investing on specialized clinics.

Quality and value are currently convergent concepts in healthcare. The importance of patients as customers has increased the focus on quality management and value delivery. The Queen Elizabeth Hospital in Rotorua is a specialist hospital for rheumatic disease and rehabilitation. It has a clear mission for the delivery of customer quality and in fulfilling this mission uses a holistic approach (a value chain approach) to customer care. The value chain study of QEH’s product/service delivery has enabled medical, medical support staff and management to review both value delivery quality and delivery methods. The study explored the QEH value chain organisation and process structures and has identified questions concerning healthcare delivery and alternative methods for achieving current results and the future direction of the organisation. Value chain analysis encourages an intra‐ and inter‐organisational review of resource application and identifies alternative methods and structures for meeting objectives.

The purpose of this paper is to report findings from qualitative interviews with physiotherapists to demonstrate why even minor changes to clinical work resulting from the introduction of new interventions, are often difficult to implement. The paper seeks to illustrate how some of the obstacles to implementing change were managed by physiotherapists.

A total of 32 qualitative interviews with participating physiotherapists were conducted, 12 interviews prior to the introduction of the new system, and 20 afterwards. The interviews were coded and analysed thematically.

The findings reveal a number of perceived limitations of current management of low back pain and identify key themes around convergence with the new approach, such as willingness by physiotherapists to adopt the new approach, the perception of benefits to adopting the new approach, as well as some difficulty in adjusting to it. The authors refer to the positive and negative elements as “soft” and “hard” disruption. The adoption of the new approach is explored with reference to the “situated” dimensions of physiotherapy practice and normalisation process theory.

The study raises the need to conduct future observational research to support the interview findings.

The study describes the “situated” components of physiotherapy work, which have received limited research attention. The value of the study lies less in its ability to explain specifically why physiotherapists adopted or rejected the new system, but in describing the conditions and consequences of change that might be translated to other professions, contexts and interventions.

This paper assesses the patients' healthcare information needs and expectations when they attend a rheumatology outpatient clinic. It proposes that obtaining the patients' perspectives about the services they use is an essential service-development tool. The aim of this paper is to expand the current domains used to evaluate these perspectives.

This paper is an exploratory study, looking at quality assessment and improvement based on Donabedian's quality model in a rheumatology outpatient setting. A structured interview schedule addressing care pathways was used and 70 consecutive patients were recruited.

The article provides insights about how relevant change can be brought about when service development is contemplated. It suggests that patients are important stakeholders in the ongoing service development process.

Because rheumatological conditions tend to be chronic and require long-term follow-up, the results may lack generalisability. Therefore, researchers are encouraged to test propositions in different clinical settings.

The article highlights healthcare delivery areas that are not meeting patient expectations. Some recommendations (such as informing waiting patients regularly about any delays) require minimal additional resources for successful implementation. Service providers need to obtain the patients' healthcare perspectives to ensure that services are built around their needs.

This article fulfils an identified need to study how patients perceive service quality.

Only 55% of patients receive recommended care, with little difference found between care recommended for prevention, to address acute episodes, or to treat chronic conditions (McGlynn et al, 2003). The lag time between the discovery of more effective forms of medical treatment and their incorporation into routine patient care averages seventeen (17) years (IOM). Computerized provider order entry (CPOE) has been widely documented as a necessary tool to reduce preventable medication and other related errors but only 7.4% of acute care hospitals in the United States utilize CPOE with appropriate rules and evidence (HIMSS Analytics). The most fundamental building block for CPOE is the evidence based order set, but complexities associated with creating, managing and updating order sets have introduced major obstacles to CPOE implementation efforts. Chronic conditions such as heart disease, diabetes or arthritis affect more than 130 million Americans directly, and account for 7 in 10 deaths. Further, these chronic conditions consume 75% of all healthcare spending, and account for nearly two-thirds of the growth in health spending over the past 20 years -costing the U. S. economy $1 trillion annually (Almanac of Chronic Conditions, 2008 Edition). Estimates suggest the average patient upon hospitalization has 2.75 diagnoses - meaning "appropriate care" must span and synthesize multiple morbidity-specific best practices to effectively administer care to that "average" patient. The traditional approach to treating patients with evidence based protocols requires a physician to perform an ad hoc exercise of "mental merging" - reconciling duplicate candidate orders across multiple order sets to treat a patient with co-morbidities (today's norm). A more clinically effective, productive, and patient safety-centric alternative is to employ a proprietary software merging algorithm. These advanced algorithms remove duplicate orders, resolve conflicts, completes validation of the appropriate medical evidence and organizes the resulting merged order set so the physician can succinctly address the patients' often complicated treatment by focusing on the unique combination of labs, medications, etc. appropriate for the specific presenting conditions. This article describes a patent-pending propriety method of algorithmically merging multiple independent order sets for patients with co-morbid and chronic conditions into a single, maintenance free and evidence-based order set that can be immediately implemented into physician workflow to satisfy "Meaningful Use" guidelines for incremental provider reimbursement based on the American Recovery and Reinvestment Act (ARRA) legislation.

The purpose of this paper is to review the causes of long waiting time in Hong Kong public hospitals and to suggest solutions in the service, organisational, systems, financial and policy perspectives.

The paper is a review of waiting time of public hospital services. Total joint replacement, which is one of the elective surgeries in public hospitals, is presented as a case study.

The average waiting time of semi-urgent and non-urgent patients in the accident and emergency departments of public hospitals is two hours, and that of specialist outpatient (SOP) clinics is from 1 to 144 weeks. For total joint replacement, it is from 36 to 110 months. Measures like Government subsidisation programme for the replacement surgery and employing adequate physiotherapists, Chinese medicine practitioners, clinical psychologists and nurses to reduce the waiting time are suggested. Issues concerning the healthcare system of Hong Kong, such as structural reform, service delivery model, primary care, quality and process management, and policy reviews, are also discussed.

The ‬over-reliance of public services has resulted in long waiting time in public hospitals in Hong Kong, particularly in the emergency services and SOP clinics. However, the consequences of long waiting period for surgical operations, though much less discussed by the media and public, can be potentially detrimental to the patients and families, and may result in more burdens to the already stretched public hospitals‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬.

Risk‐adjustment is designed to predict healthcare costs to align capitated payments with an individual's expected healthcare costs. This can have the consequence of reducing overpayments and incentives to under treat or reject high cost individuals. This paper seeks to review recent studies presenting risk‐adjustment models.

This paper presents a brief discussion of two commonly reported statistics used for evaluating the accuracy of risk adjustment models and concludes with recommendations for increasing the predictive accuracy and usefulness of risk‐adjustment models in the context of predicting future healthcare costs.

Over the last decade, many advances in risk‐adjustment methodology have been made. There has been a focus on the part of researchers to transition away from including only demographic data in their risk‐adjustment models to incorporating patient data that are more predictive of healthcare costs. This transition has resulted in more accurate risk‐adjustment models and models that can better identify high cost patients with chronic medical conditions.

The paper shows that the transition has resulted in more accurate risk‐adjustment models and models that can better identify high cost patients with chronic medical conditions.