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The purpose of this paper is twofold: to enable hospital administrators to increase reimbursement rates under value-based purchasing (VBP) by understanding the process by which the Centers for Medicare and Medicaid Services (CMS) calculate and use performance scores from the Hospital Consumer Assessment of Healthcare Providers and Systems survey of patient experience; to apply statistical methods to determine what dimensions of patient care have the greatest impact on overall satisfaction scores and thus reimbursement.

The expository purpose was met by locating, analyzing and interpreting published CMS documentation related to VBP to explain the complex methods used to convert raw survey data to total patient satisfaction scores on seven dimensions. The raw data on 2,984 hospitals were cleaned and correlation and regression analysis used to measure the relationship between raw survey scores and overall patient satisfaction scores. Finally, Pareto analysis was used to show the relative influence of each dimension on satisfaction performance scores.

Nursing communications accounted for 75 percent of the variance in the patient satisfaction domain score in a stepwise regression.

This research focusses only on the patient satisfaction component of VBP, over which hospital administrators have significant control. Future research could explore how hospital management can improve scores on clinical outcomes, process and efficiency.

Shows hospital management the most influential methods for improving their patient satisfaction scores and reimbursement under VBP.

Offers a managerially focussed explanation of how patient satisfaction scores are computed from raw survey data and how statistical analysis of the data can be used to improve quality.

The purpose of this paper is to determine the relative influence of the different domains of healthcare quality from the Care Experience Feedback Improvement Tool (CEFIT) and identify key predictors of healthcare quality from the patients’ perspective. Measurement is necessary to determine whether the quality of healthcare is improving. The CEFIT was developed as a brief measure of patient experience. It is important to determine the relative influence of the different domains of healthcare quality to further clarify how the CEFIT can be used and identify key predictors of healthcare quality from the patients’ perspective.

In sum, 802 people with a healthcare experience during the previous 12 months were telephoned to complete the CEFIT questions and an additional 11-point global rating of patient experience. To estimate the influence of different domains of healthcare quality on patient overall ratings of quality of healthcare experience, the authors regressed the overall rating of patient experience with each component of quality (safety, effectiveness, timely, caring, enables system navigation and person-centred).

The authors found that all of the domains of the CEFIT influenced patient experience ratings of healthcare quality. Specifically, results show the degree of influence, the impact of demographics and how high scores for overall rating of patient experience can be predicted.

The findings suggest that all of the CEFIT domains are important in terms of capturing the wholeness of the patient experience of healthcare quality to direct local quality improvement.

The purpose of this paper is to explore multidisciplinary attitudes and environmental factors affecting dementia care in the Cardiac Catheter Laboratory (CCL).

Questionnaires (n=87) were distributed in a hospital CCL in the North of England. The authors utilised the Dementia Attitudes Scale which incorporates two subscales: Social Comfort and Dementia Knowledge. In addition, a newly devised questionnaire asking about perceptions of how the CCL environment affected care of patients with dementia was added.

The response rate was 71 per cent (n=62). Years’ experience in the CCL was associated with lower Social Comfort scores (p=0.026). Dementia training was associated with higher mean Dementia Attitudes Scale and Social Comfort scores (p=0.021, p=0.007). Participants who had undertaken “Professional studies” had higher Dementia Attitudes Scale and Dementia Knowledge mean scores (p=0.038, p=0.046) but “On-the-job” training was perceived as most beneficial (32 per cent, n=20). Unit co-ordinators and nurses felt the CCL was an unfavourable environment for patients with dementia. Care was perceived to be impaired by environmental functionality, equipment and the presence of ionising radiation.

The small sample limits generalisability. Although the Dementia Attitudes Scale is a validated questionnaire it has not been widely used so reliability of these results is unclear.

Caring for patients with dementia has unique challenges especially in areas like the CCL. These results suggest that practical experience and training can affect the perception of staff to patients with dementia hence there may be a need to assess what would be the most appropriate training to give health professionals in the future.

The authors believe this to be the first multi-professional research study into care of patients with dementia in a specialised acute unit. This was the most diverse sample known to have attitudes to dementia measured quantitatively in an acute hospital department and the results need to be replicated before practice should be changed.

The assignment is to design a plan that aligns patient satisfaction scores with quality care metrics. The instructor’s manual (IM) introduces models for designing and implementing a strategic plan to approach the quality improvement process.

This is a field research case. The author(s) had access to the Chief Operating Officer (COO) and other members of the management team, meeting with them on numerous occasions. Cleveland Clinic Florida (CCF) provided the data included in the appendices. Additionally, relevant hospital data, also included in the appendices, is required to be made public on Centers for Medicare and Medicaid Services (CMS) databases. Accordingly, all data and information are provided by original sources.

Osmel “Ozzie” Delgado, MBA and COO of CCF was faced with a dilemma. Under the new CMS reimbursement formula, patient satisfaction survey scores directly impacted hospital reimbursement. However, the CCF patient satisfaction surveys revealed some very unhappy patients. Delgado pondered these results that really made no sense to him because CCF received the highest national and state rankings for its clinical quality at the same time. Clearly, patients were receiving the best medical care, but they were still unhappy. Leaning back in his chair, Delgado shook his head and wondered incredulously how one of the most famous hospitals in the world could deliver such great care but receive negative patient feedback on CMS surveys. What was going wrong and how was the hospital going to fix it?

This case is designed for graduate Master’s in Business Administration (MBA), Master’s in Health Sciences Administration (MHSA) and/or Public Health (PA) audiences. While a healthcare concentration is useful, the case raises the generic business problems of satisfying the customer to increase brand recognition in the marketplace and displacing competition to increase annual revenues. Indeed, the same analysis can be applied in other heavily regulated industries also suffering from a change in liquidity and growth occasioned by regulatory change.

The principal aim of this paper is to develop an instrument to measure quality of care in the psychiatric setting from an in‐patient perspective and to describe quality of care by means of this instrument. A further aim is to investigate the influence of background variables and expectations on the experience of care.

The instrument “Quality in psychiatric care” consists of two parts: one for measuring the patient's expectations regarding quality of care, the other for measuring his or her experiences regarding it. The instrument was derived from an earlier interview study of patients' perceptions of the quality of psychiatric care. A sample of 116 patients from eight in‐patient wards in Sweden participated in the present study.

Results indicate a generally high quality of care. Experienced quality of care was significantly lower, however, than expectations in all the dimensions of the instrument: total dimension, dignity, security, participation, recovery and environment. Patients who perceived that the time of discharge was consistent with the stage of their illness experienced significantly higher Recovery; patients with good psychiatric health experienced this too, but also significantly higher participation.

This new instrument needs to be further tested before the psychometric properties can be established.

The value of the research is that instruments for measuring the quality of in‐patient psychiatric care from the patient's perspective and with a theoretical foundation are less common.

Failure to rescue events, or events involving preventable deaths from complications, are a significant contributor to inpatient mortality. While many interventions have been designed and implemented over several decades, this patient safety issue remains at the forefront of concern for most hospitals. In the first part of this study, the development and implementation of one type of highly studied and widely adopted rescue intervention, algorithm-based patient assessment tools, is examined. The analysis summarizes how a lack of systems-oriented approaches in the design and implementation of these tools has resulted in suboptimal understanding of patient risk of mortality and complications and the early recognition of patient deterioration. The gaps identified impact several critical aspects of excellent patient care, including information-sharing across care settings, support for the development of shared mental models within care teams, and access to timely and accurate patient information.

This chapter describes the use of several system-oriented design and implementation activities to establish design objectives, model clinical processes and workflows, and create an extensible information system model to maximize the benefits of patient state and risk assessment tools in the inpatient setting. A prototype based on the product of the design activities is discussed along with system-level considerations for implementation. This study also demonstrates the effectiveness and impact of applying systems design principles and practices to real-world clinical applications.

To empirically verify whether patient hospital satisfaction ratings on social media such as Yelp provide similar information as the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) surveys.

OLS and ordinal regressions performed on secondary data obtained from Yelp.com and 2016 Hospital Compare database disclosed by CMS.

Results show that the patient hospital satisfaction ratings from Yelp can predict the patient experience of care domain scores obtained through the annual HCAHPS surveys and are also positively and significantly correlated to the overall hospital quality performance scores given by CMS.

Study suggests that social media patient review information could be used to supplement the information obtained from HCAHPS surveys, thereby providing hospitals more accurate information about their patient experiences.

Hospital leaders need not wait an entire year to receive their HCHAPS scores to know about the issues related to their patient experience that need improvement and can periodically refer to free Yelp patient review scores on Yelp.com to obtain similar information.

To the best of knowledge, this research is the first to empirically demonstrate that patient reviews freely obtained from social media sites like Yelp can provide similar information as obtained from HCAHPS surveys and can thus be used to supplement HCAHPS.

The objective of this study was to check psychometric properties of a French‐language in‐patient experience questionnaire in a test sample different from the development sample. The questionnaire was sent out to 5,736 in‐patients, within two to four weeks of discharge from a teaching hospital of 2,200 beds. Overall 4,095 questionnaires (71.4 per cent) were returned. Of these, 3,879 questionnaires were analyzed. In principal component analysis, seven principal components accounted for 62.4 per cent of the total variance. Cronbach’s alpha coefficient ranged from 0.62 to 0.90, with the exception of the seventh scale (convenience scale, two items, Cronbach=0.39). The overall patient experience score increased with increasing patient age (except for patients older than 65), male sex, low education level, use of a single room, and prior stay in the department. It also differed with respect to patients’ behavioral intentions, answers to an overall satisfaction item, and open‐ended comments.

Organizational metrics – including rankings, ratings, and other forms of public assessment – are inextricably tied to uncertainty. Metrics are not only responses to uncertainty in the organizational environment, but they also create new forms of uncertainty within the organizations they evaluate. Given this, it is productive to consider these metrics in relation to the garbage can model of organizational decision making, a framework that was designed to provide insight into uncertain and ambiguous contexts. In this paper, the authors use the case of patient experience surveys to argue for the value of this model for understanding responses to metrics in particular conditions. Specifically, the authors demonstrate how the different features of the garbage can model manifest themselves within organizations managing numbers, and the authors then use these findings to discuss the measurement conditions that promote garbage can responses, the distinctive types of unintended consequences these responses might produce, and the implications of the garbage can model for the understanding of metrics more generally.

The purpose of this research is to determine whether a pessimistic or hostile personality style adversely affects satisfaction with out‐patient medical visits. Many patient and health care provider demographic characteristics have been related to patient satisfaction with a health care encounter, but little has been written about the association between patients' personality characteristics and their satisfaction ratings.

An eight‐item patient satisfaction survey was completed by 11,636 randomly selected medical out‐patients two to three months after their episode of care. Of these, 1,259 had previously completed a Minnesota Multiphasic Personality Inventory (MMPI). The association of pessimism and hostility scores with patient satisfaction ratings was assessed.

Among patients who scored high on the pessimism scale, 59 percent rated overall care by their physicians as excellent, while 72 percent with scores in the optimistic range rated it as excellent (p=0.003). Among the hostile patients, 57 percent rated their overall care by physicians as excellent, while 66 percent of the least hostile patients rated it as excellent (p=0.002).

Pessimistic or hostile patients were significantly less likely to rate their overall care as excellent than optimistic or non‐hostile patients.