Using Patient-reported Outcome Measures to Improve Health Care

Background Person-generated health data (PGHD) are health data that people generate, record, and analyze for themselves. Although the health benefits of PGHD use have been reported, there is no systematic way for patients to measure and report the health effects they experience from using their PGHD. Patient-reported outcome measures (PROMs) allow patients to systematically self-report their outcomes of a health care service. They generate first-hand evidence of the impact of health care services and are able to reflect the real-world diversity of actual patients and management approaches. Therefore, this paper argues that a PROM of utilizing PGHD, or PROM-PGHD, is necessary to help build evidence-based practice in clinical work with PGHD. Objective This paper aims to describe a method for developing PROMs for people who are using PGHD in conjunction with their clinical care—PROM-PGHD, and the method is illustrated through a case study. Methods The five-step qualitative item review (QIR) method was augmented to guide the development of a PROM-PGHD. However, using QIR as a guide to develop a PROM-PGHD requires additional socio-technical consideration of the PGHD and the health technologies from which they are produced. Therefore, the QIR method is augmented for developing a PROM-PGHD, resulting in the PROM-PGHD development method. Results A worked example was used to illustrate how the PROM-PGHD development method may be used systematically to develop PROMs applicable across a range of PGHD technology types used in relation to various health conditions. Conclusions This paper describes and illustrates a method for developing a PROM-PGHD, which may be applied to many different cases of health conditions and technology categories. When applied to other cases of health conditions and technology categories, the method could have broad relevance for evidence-based practice in clinical work with PGHD.

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Article Commentary: Patient-Reported Outcomes (PROs) and Patient-Reported Outcome Measures (PROMs)

Health Services Insights ◽

10.4137/hsi.s11093 ◽

2013 ◽

Vol 6 ◽

pp. HSI.S11093 ◽

Cited By ~ 101

Author(s):

Theresa Weldring ◽

Sheree M.S. Smith

Keyword(s):

Health Care ◽

Health Service ◽

Outcome Measures ◽

Patient Reported Outcomes ◽

Care Service ◽

Clinical Care ◽

Health Care Service ◽

Patient Reported Outcome Measures ◽

Patient Reported Outcome ◽

Patient Reported

In recent years, there has been an increased focus on placing patients at the center of health care research and evaluating clinical care in order to improve their experience and ensure that research is both robust and of maximum value for the use of medicinal products, therapy, or health services. This paper provides an overview of patients’ involvement in clinical research and service evaluation along with its benefits and limitations. We describe and discuss patient-reported outcomes (PROs) and patient-reported outcome measures (PROMs), including the trends in current research. Both the patient-reported experiences measures (PREMs) and patient and public involvement (PPI) initiative for including patients in the research processes are also outlined. PROs provide reports from patients about their own health, quality of life, or functional status associated with the health care or treatment they have received. PROMs are tools and/or instruments used to report PROs. Patient report experiences through the use of PREMs, such as satisfaction scales, providing insight into the patients’ experience with their care or a health service. There is increasing international attention regarding the use of PREMS as a quality indicator of patient care and safety. This reflects the ongoing health service commitment of involving patients and the public within the wider context of the development and evaluation of health care service delivery and quality improvement.

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A View on Patient-Reported Outcome Measures

Breast cancer: Global quality care ◽

10.1093/med/9780198839248.003.0006 ◽

2019 ◽

pp. 46-49

Author(s):

François Duhoux ◽

Rishi Hazarika

Keyword(s):

Health Care ◽

Health Outcomes ◽

Outcome Measures ◽

Health Care Quality ◽

Patient Reported Outcome Measures ◽

Patient Reported Outcome ◽

Care Quality ◽

Patient Reported ◽

Related Quality ◽

Health Related

Abstract: Patient-reported outcome measures (PROMs) are being implemented more frequently in the clinical setting to monitor health-related quality of life. The breast cancer standard set developed by the International Consortium for Health Outcomes Measurement (ICHOM) aims at reducing health care costs by preventing medical errors and unnecessary treatments, supporting informed decision-making, and improving health care quality by allowing physicians to compare their health outcomes data to other providers. It encompasses survival, cancer control, and disutility of care outcomes in addition to selected case-mix factors, which are to be collected at baseline, and a combination of multiple PROM tools to capture long-term degree of health outcomes. It can be used for both the early and the metastatic settings. Implementing PROMs is both complex and time-consuming. This or a similar process will likely become mandatory in developed nations, where value-based health care is becoming increasingly popular.

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How do aggregated patient-reported outcome measures data stimulate health care improvement? A realist synthesis

Journal of Health Services Research & Policy ◽

10.1177/1355819617740925 ◽

2017 ◽

Vol 23 (1) ◽

pp. 57-65 ◽

Cited By ~ 24

Author(s):

Joanne Greenhalgh ◽

Sonia Dalkin ◽

Elizabeth Gibbons ◽

Judy Wright ◽

Jose Maria Valderas ◽

...

Keyword(s):

Health Care ◽

Quality Improvement ◽

Outcome Measures ◽

Patient Reported Outcome Measures ◽

Patient Reported Outcome ◽

Outcome Data ◽

Realist Synthesis ◽

Performance Data ◽

Patient Reported ◽

Main Programme

Objectives Internationally, there has been considerable debate about the role of data in supporting quality improvement in health care. Our objective was to understand how, why and in what circumstances the feedback of aggregated patient-reported outcome measures data improved patient care. Methods We conducted a realist synthesis. We identified three main programme theories underlying the use of patient-reported outcome measures as a quality improvement strategy and expressed them as nine ‘if then’ propositions. We identified international evidence to test these propositions through searches of electronic databases and citation tracking, and supplemented our synthesis with evidence from similar forms of performance data. We synthesized this evidence through comparing the mechanisms and impact of patient-reported outcome measures and other performance data on quality improvement in different contexts. Results Three programme theories were identified: supporting patient choice, improving accountability and enabling providers to compare their performance with others. Relevant contextual factors were extent of public disclosure, use of financial incentives, perceived credibility of the data and the practicality of the results. Available evidence suggests that patients or their agents rarely use any published performance data when selecting a provider. The perceived motivation behind public reporting is an important determinant of how providers respond. When clinicians perceived that performance indicators were not credible but were incentivized to collect them, gaming or manipulation of data occurred. Outcome data do not provide information on the cause of poor care: providers needed to integrate and interpret patient-reported outcome measures and other outcome data in the context of other data. Lack of timeliness of performance data constrains their impact. Conclusions Although there is only limited research evidence to support some widely held theories of how aggregated patient-reported outcome measures data stimulate quality improvement, several lessons emerge from interventions sharing the same programme theories to help guide the increasing use of these measures.

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Patient-Reported Outcome Measures of Utilizing Person-Generated Health Data in the Case of Simulated Stroke Rehabilitation: Development Method (Preprint)

10.2196/preprints.16827 ◽

2019 ◽

Cited By ~ 3

Author(s):

Gerardo Luis Dimaguila ◽

Kathleen Gray ◽

Mark Merolli

Keyword(s):

Health Care ◽

Outcome Measures ◽

Clinical Work ◽

Patient Reported Outcome Measures ◽

Patient Reported Outcome ◽

Health Data ◽

Health Conditions ◽

Evidence Based ◽

Development Method ◽

Patient Reported

BACKGROUND Person-generated health data (PGHD) are health data that people generate, record, and analyze for themselves. Although the health benefits of PGHD use have been reported, there is no systematic way for patients to measure and report the health effects they experience from using their PGHD. Patient-reported outcome measures (PROMs) allow patients to systematically self-report their outcomes of a health care service. They generate first-hand evidence of the impact of health care services and are able to reflect the real-world diversity of actual patients and management approaches. Therefore, this paper argues that a PROM of utilizing PGHD, or PROM-PGHD, is necessary to help build evidence-based practice in clinical work with PGHD. OBJECTIVE This paper aims to describe a method for developing PROMs for people who are using PGHD in conjunction with their clinical care—<i>PROM-PGHD</i>, and the method is illustrated through a case study. METHODS The five-step qualitative item review (QIR) method was augmented to guide the development of a PROM-PGHD. However, using QIR as a guide to develop a PROM-PGHD requires additional socio-technical consideration of the PGHD and the health technologies from which they are produced. Therefore, the QIR method is augmented for developing a PROM-PGHD, resulting in the PROM-PGHD development method. RESULTS A worked example was used to illustrate how the PROM-PGHD development method may be used systematically to develop PROMs applicable across a range of PGHD technology types used in relation to various health conditions. CONCLUSIONS This paper describes and illustrates a method for developing a PROM-PGHD, which may be applied to many different cases of health conditions and technology categories. When applied to other cases of health conditions and technology categories, the method could have broad relevance for evidence-based practice in clinical work with PGHD.

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