How Is Quantitative Design Used in Nursing

Kango Kenkyu. Author manuscript; available in PMC 2015 Jan 8.

Published in final edited form as:

Kango Kenkyu. 2014; 47(3): 207–217.

PMCID: PMC4287271

NIHMSID: NIHMS642265

Mixed Methods in Nursing Research : An Overview and Practical Examples

Ardith Z. Doorenbos

School of Nursing, University of Washington, USA, Box 357266, Seattle, WA 98177

See other articles in PMC that cite the published article.

Abstract

Mixed methods research methodologies are increasingly applied in nursing research to strengthen the depth and breadth of understanding of nursing phenomena. This article describes the background and benefits of using mixed methods research methodologies, and provides two examples of nursing research that used mixed methods. Mixed methods research produces several benefits. The examples provided demonstrate specific benefits in the creation of a culturally congruent picture of chronic pain management for American Indians, and the determination of a way to assess cost for providing chronic pain care.

Introduction

Mixed methods is one of the three major research paradigms: quantitative research, qualitative research, and mixed methods research. Mixed methods research combines elements of qualitative and quantitative research approaches for the broad purpose of increasing the breadth and depth of understanding. The definition of mixed methods, from the first issue of the Journal of Mixed Methods Research, is "research in which the investigator collects and analyzes data, integrates the findings, and draws inferences using both qualitative and quantitative approaches or methods in a single study or program of inquiry" (Tashakkori & Creswell, 2007, p.4).

Mixed methods research began among anthropologists and sociologists in the early 1960s. In the late 1970s, the term "triangulation" began to enter methodology conversations. Triangulation was identified as a combination of methodologies in the study of the same phenomenon to decrease the bias inherent in using one particular method (Morse, 1991). Two types of sequencing for mixed methods design have been proposed: simultaneous and sequential. Type of sequencing is one of the key decisions in mixed methods study design. Simultaneous sequencing is postulated to be simultaneous use of qualitative and quantitative methods, where there is limited interaction between the two sources of data during data collection, but the data obtained is used in the data interpretation stage to support each method's findings and to reach a final understanding. Sequential sequencing is postulated to be the use of one method before the other, as when the results of one method are necessary for planning the next method.

Since the 1960s, the use of mixed methods has continued to grow in popularity (O'Cathain, 2009). Currently, although there are numerous designs to consider for mixed methods research, the four major types of mixed methods designs are triangulation design, embedded design, explanatory design, and exploratory design (Creswell & Plano Clark, 2007). The most common and well-known approach to mixed methods research continues to be triangulation design.

There are many benefits to using mixed methods. Quantitative data can support qualitative research components by identifying representative patients or outlying cases, while qualitative data can shed light on quantitative components by helping with development of the conceptual model or instrument. During data collection, quantitative data can provide baseline information to help researchers select patients to interview, while qualitative data can help researchers understand the barriers and facilitators to patient recruitment and retention. During data analysis, qualitative data can assist with interpreting, clarifying, describing, and validating quantitative results.

Four broad types of research situations have been reported as benefiting particularly from mixed methods research. The first situation is when concepts are new and not well understood. Thus, there is a need for qualitative exploration before quantitative methods can be used. The second situation is when findings from one approach can be better understood with a second source of data. The third situation is when neither a qualitative nor a quantitative approach, by itself, is adequate to understanding the concept being studied. Lastly, the fourth situation is when the quantitative results are difficult to interpret, and qualitative data can assist with understanding the results (Creswell & Plano Clark, 2007).

The purpose of this article is to illustrate mixed methods methodology by using examples of research into the chronic pain management experience among American Indians. These examples demonstrate the methodology used to provide (a) a detailed multilevel understanding of the chronic pain care experience for American Indians using triangulation design (multilevel model), and (b) a comparison of cost for two different chronic pain care delivery models, also using triangulation design (data transformation model).

An Example : Understanding the Pain Management Experience Among American Indians

Chronic pain poses unique challenges to the American health care system, including ever-escalating costs, unintentional poisonings and deaths from overdoses of painkillers, and incalculable suffering for patients as well as their families. Approximately 100 million adults in the United States are affected by chronic pain, with treatment costs and losses in productivity totaling $635 billion annually (Institute of Medicine, 2011). Symptoms of pain are the leading reason patients visit health care providers (Hing, Cherry, & Woodwell, 2006).

At the level of the community-based primary care provider, especially in tribal areas of the United States, there is often not enough capacity to manage complex chronic pain cases, and this is often due to lack of access to specialty pain care (Momper, Delva, Tauiliili, Mueller-Williams, & Goral, 2013). The American Indian population in particular is underserved by health care and the most vulnerable to the impact of chronic pain, with high rates of drug poisoning due to opioid analgesics (Warner, Chen, Makuc, Anderson, & Minino, 2011). There are 2.9 million people who report exclusive and an additional 1.6 million who report partial American Indian ancestry in the United States. They are a diverse group, residing in 35 states and organized into 564 federally recognized tribes (U.S. Census Bureau, 2010). However, there is a scarcity of published literature exploring the experience, epidemiology, and management of pain among American Indians (Haozous, Knobf, & Brant, 2010; Haozous & Knobf, 2013; Jimenez, Garroutte, Kundu, Morales, & Buchwald, 2011).

Using Mixed Methods to Overcome Barriers to Research

Barriers to effective research into chronic pain management among American Indians include the relatively small number of American Indian patients in any circumscribed area or tribe, the limitations of individual databases, and widespread racial misclassification. A mixed methods research approach is needed to understand the complex experience, epidemiology, and management of chronic pain among American Indians and to address the strengths and weaknesses of quantitative methodologies (large sample size, trends, generalizable) with those of qualitative methodologies (small sample size, details, in-depth).

This first example is from an ongoing study that uses triangulation design to provide a better understanding of the phenomenon of chronic pain management among American Indians. The study uses a multilevel model in which quantitative data collected at the national and state levels will be analyzed in parallel with the collection and analysis of the qualitative data at the patient level (see Figure 1). This allows the weakness of one approach to be offset by the strengths of the other. The results of the separate level analyses will be compared, contrasted, and blended leading to an overall interpretation of results.

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Triangulation Design: Multilevel Model

Role of quantitative data

Previous examination of U.S. national databases has reported a higher prevalence of lower back pain in American Indians than in the general population (35% compared to 26% ; Deyo, Mirza, & Martin, 2002). Thus, at level 1, quantitative administrative data sets representing health care received by American Indians, both across the United States and in broad regions, will be used to evaluate macro-level trends in utilization of health care and in basic outcomes, such as opioid-related deaths.

At level 2, more detailed quantitative Washington state tribal clinic data will be used to identify American Indian populations, evaluate breakdowns in the delivery of care, and identify processes that lead to unsuccessful outcomes. For example, in a study conducted with community health practitioners in Alaska, participants reported low levels of knowledge and comfort around discussing cancer pain (Cueva, Lanier, Dignan, Kuhnley, & Jenkins, 2005).

Role of qualitative data

At level 3, qualitative research through focus groups and key informant interviews will provide even more refined information about perceptions of recommended and received care. These interviews will provide insight into selected immediate and proximal factors. These factors include patients' choice and use of services; attitudes, motivations, and perceptions that influence their decisions; interpersonal factors, such as social support; and perceived discrimination. This qualitative data will shed light on potential barriers to care that are not easily recognized in administrative or clinical records, and thereby will provide greater detail about patient views of chronic pain care.

Role of (qualitative) indigenous methodologies

Since the focus of this study is on the chronic pain experience among American Indian patients, it is important that the qualitative work in level 3 be guided by indigenous methodologies, in both data collection and analysis. The phrase "indigenous methodologies" refers to an evolving framework for creating research that places the epistemologies of indigenous participants and communities at the center of the work, while building an equitable and respectful setting for bidirectional learning (Evans, Hole, Berg, Hutchinson, & Sookraj, 2009 ; Louis, 2007.; Smith, 2004). Although the tenets of indigenous methodologies vary according to the source, there is agreement among sources that research with indigenous populations should be wellness-oriented, holistic, community-oriented, and focused on indigenous knowledge, and should incorporate bidirectional learning (Louis, 2007 ; Smith, 2004).

The ongoing project aligns with these guidelines by building knowledge about the chronic pain experience from the perspective of American Indian patients. The data is being interpreted with the goal of designing a usable and relevant model that will resonate at the American Indian community level. The researchers have conducted focus groups with the needs and priorities of the participants placed at the forefront, to best achieve the goals of learning and building knowledge that reflects the participants' experiences. Specifically, the focus groups were scheduled within three tribes, ensuring high familiarity and social support among group members. These focus groups met either at a tribal community center or in a nearby tribally owned casino in the evening. Each focus group started with a dinner, followed by discussion.

The focus group facilitator was well-known to the community, and although not American Indian, had been an active participant in community events and had provided expert knowledge and consultation to the tribes. Additionally, each focus group was co-facilitated by a tribal elder. The high familiarity among the participants and the research team was an important component of the bidirectional learning: it helped reduce much of the mistrust that has historically prevented medical researchers from obtaining high-quality data in similarly vulnerable populations (Guadagnolo, Cina, & Helbig, 2009).

Benefits of Triangulation Design: Multilevel Model

In summary, only a mixed methods study that included quantitative and qualitative methods could provide the data required for a comprehensive multilevel assessment of the chronic pain experience among American Indians. Although this study is ongoing, the plan is for a nationwide analysis of variations in chronic pain outcomes among American Indians to examine the structure of service delivery and organization. Analysis of the state tribal clinic data will address intermediate factors and will examine community-level variation in pain management and local access to pain specialists. Preliminary analysis of the focus group data has already demonstrated that there is insufficient pain management among American Indians, due in part to lack of knowledge about pain management among providers and lack of access to pain specialists.

An Example; Comparing the Costs of Two Models for Providing Chronic Pain Care to American Indians

Telehealth is one innovative approach to providing access to high-quality interdisciplinary pain care for American Indians. A telehealth model with a unique approach based on provider-to-provider videoconference consultations allows community-based providers to present complex chronic pain cases to a panel of pain specialists through a videoconferencing infrastructure that also incorporates longitudinal outcomes tracking to monitor patient progress. Telehealth is an innovative model of health care delivery, and its use among American Indians has been expanding over the past several years (Doorenbos et al., 2010 ; Doorenbos et al., 2011a ; 2011b). Although the use of telehealth for providing chronic pain consultation is still in early stages, the long-term effectiveness of this approach and its impact on increasing capacity for pain management among community providers is being investigated (Haozous et al., 2012 ; Tauben, Towle, Gordon, Theodore, & Doorenbos, 2013). The mixed methods approach for this transaction cost analysis used a unique triangulation design with a data transformation model to build a body of evidence for telehealth pain management.

With ever increasing mandates to reduce the cost and increase the quality of pain management, health care institutions are faced with the challenge of demonstrating that new technologies provide value while maintaining or even improving the quality of care (Harries & Yellowlees, 2013). Transaction cost analysis can provide this evidence by using mixed methods research methodologies to provide comparative evaluation of the costs and consequences of using alternative technologies and the accompanying organizational arrangements for delivering care (Williamson, 2000).

The theory of transaction cost developed from the observation that our structures for governing transactions—the ways in which we organize, manage, support, and carry out exchange — have economic consequences (Williamson, 1991). Though prices matter, this theory recognizes that prices can and do deviate from the cost of production and do not include the cost of transacting (Coase, 1960). Setting aside neoclassical economic conceptions of price, output, demand, and supply, the transaction becomes the unit of analysis (Williamson, 1985).

In transactions, there are typically two parties engaging in the exchange of goods or services, and both exert effort to carry out the transaction, incurring costs in the hope or with the expectation of realizing benefits. Some ways of structuring or supporting a given transaction, such as consultation or treatment for a patient from a health care provider, may be more efficient than others. The analysis examines the actual costs incurred and the related consequences experienced by the parties over time, with the hypothesis that efficiency results from the discriminating alignment of transactions with alternative, more efficient structures of governance (Williamson, 2002).

Specialty health care services participating in the study described here included the University of Washington (UW) Center for Pain Relief and the UW TelePain program. The UW Center for Pain Relief is an outpatient multispecialty consultation and treatment clinic that uses the assembled expertise and skills of physicians and other medical team providers to assist in diagnosis and care for chronic pain, for example for people with painful disorders that have persisted beyond expected duration, or for people who have persistent uncontrolled pain despite appropriate treatment for the underlying medical condition. The clinic also offers pain consultation and treatment for a variety of new-onset or acute problems that may benefit from selective anesthetic procedures, such as nerve blocks or spinal nerve root compression.

The UW TelePain program serves tribal providers in the Washington, Wyoming, Alaska, Montana, and Idaho (WWAMI) region. These tribal providers include primary care physicians, physician assistants, and nurse practitioners. The tribal providers have access to weekly videoconferences both with other community providers and with university-based pain and symptom management experts. During videoconferences, providers manage cases, engage in evidence-based practice activities, and receive peer support. Throughout the process, these community providers are responsible for direct patient care, and they act on recommendations of the consulting pain specialists.

The two care delivery models discussed above — traditional in-clinic consultation at the Center for Pain Relief and telehealth case consultation through TelePain — provided this mixed methods study using triangulation design and a data transformation model with two comparative arrangements for delivering the same transaction: delivery of pain care to patients (see Figure 2).

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Triangulation Design: Data Transformation Model

Qualitative and Quantitative Data Collection Procedures

Participant observation and structured interviews were used to identify and describe two comparable completed transactions for patients with chronic pain. Members of the clinical care teams selected one transaction from each service for which the care could be said to represent the routines and norms of their health care organization. The chosen transactions were carried out with patients of the same gender, similar age, and similar health characteristics. For the study, clinical care teams from each service provided two qualitative on-site interviews documenting clinical work flow and processes (i.e., the steps in the transaction). For the in-clinic transaction, members of the clinical care team interviewed included a nurse care coordinator, pain specialist, medical assistant, patient outcomes assessment coordinator, nurse triage manager, patient support services supervisor, and financial authorization specialist. For the Tele-Pain transaction, team members interviewed included the TelePain nurse care coordinator, two pain specialists, an information technology specialist, and the clinic provider.

The following details the process of the mixed methods analysis. First, individual steps, or discrete tasks, within each transaction (in-clinic versus TelePain) were identified using qualitative interviews and itemized in detail. Details from the qualitative data included a description of each task, the person (s) engaged, the duration of engagement of each person in minutes, the information accrued to the patient's medical record, the technologies employed, and the locations where tasks were conducted and information was transmitted or stored.

The quantitative data collected included date and time, and therefore duration in business days, that accumulated with each step in the transaction. Finally, the costs of each step collected from the qualitative data were identified and transformed into quantitatively estimated data for each transaction. Analysis focused on the primary costs in health care: the value of people's time. These values were limited to labor costs for the in-clinic and telehealth personnel; proxies for the value of time were used with estimates of time for the patient. Costs were estimated as a function of time spent per task and per patient, and the actual wage, including benefits, of personnel engaged in the transaction.

Qualitative and Quantitative Data Analysis

Personal identifiable information was redacted from each patient's medical record, and the records were reviewed for comparability as well as for norms and routines of care for the in-clinic and telehealth organizations. The characteristics of the two patients were similar. Both were first-time patients to their respective organizations, and were referred by their primary care providers for specialized care. The reasons for seeking care and report of conditions potentially related to chronic pain were similar. Both transactions resulted in a consultation recommending referral for additional specialized care or treatment.

Two work flows, one in-clinic and one telehealth, were developed by documenting actual tasks undertaken during the transactions. In follow-up interviews, these work flows were presented to participants for review and comment. These interviews resulted in a complete itemized list of dates, personnel, and time spent per person on discrete steps or tasks. Tables and graphs expressing the steps, with cost accrual over time and in sum, were developed and compared for each transaction, to each other, and with respect to participants' rationales for the tasks in each transaction.

The equation expressing the cost per transaction is as follows, where the total cost of the transaction (C_T ) is the sum of the costs of each discrete task (k_i ) in the transaction, measured per participant (x, y, z…) on the task, as the product of time (t) and wage rate (w), or in the case of the patient (x, y, z…), a proxy for the value of time (w) and estimated time (t).

$C_{T} = \sum_{i = 0}^{n} k_{i} = (x_{t} x_{w} + y_{t} y_{w} + z_{t} z_{w} + \dots)$

Results

In total, 46 discrete steps were taken for the typical in-clinic transaction at the UW Center for Pain Relief (one patient case, reviewed by two pain specialists) versus 27 steps for the typical TelePain transaction (three patient cases, reviewed by six pain specialists). The greater number and types of administrative steps taken to schedule, execute, and follow up the in-clinic consultation resulted in greater duration of time between receipt of initial referral request and completion of the initial consultation with the pain specialists. A total of 153 business days (213 calendar days) elapsed between referral and the completion of the entire in-clinic transaction, versus 4 business days (4 calendar, days) for the TelePain transaction. Importantly, for the transaction at the UW Center for Pain Relief, 72 business days transpired before consultation concluded with a referral for the patient's record; the same conclusion was reached in 4 days in the TelePain transaction. These methods used to determine transaction costs provide an excellent example of mixed methods research, where both qualitative and quantitative data and analysis are needed to provide the transaction cost results.

Conclusion

Mixed methods are increasingly being used in nursing research. We have detailed two studies in which mixed methods research with triangulation design brought a richness to the examination of the phenomenon that a single methodology would not In the two examples described, a major advantage of the triangulation design is its efficiency, because both types of data are collected simultaneously. Each type of data can be collected and analyzed separately and independently, using the techniques traditionally associated with each data type. Both simultaneous and sequential data collection lend themselves to team research, in which the team includes researchers with both quantitative and qualitative expertise.

Challenges include the effort and expertise required due to the simultaneous data collection, and the fact that equal weight is usually given to each data type. Thus this research requires a team, or extensive training in both quantitative and qualitative methodologies, and careful adherence to the methodological rigor required for both methodologies. Nursing researchers may face the possibility of inconsistency in research findings arising from the objectivity of quantitative methods and the subjectivity of qualitative methods. In these cases, additional data collection may be required.

The first example, regarding the pain management experience among American Indians, used triangulation design in a multilevel model format. The multilevel model was useful in designing this study as different methods were needed at different levels to fully understand the complex health care system. In this example, quantitative data is being collected and analyzed at the national and state levels, and qualitative data is being collected at the patient level. Both qualitative and quantitative data are being collected simultaneously. The findings from each level will then be blended into one overall interpretation.

The second example, a transaction cost analysis, also used triangulation design, but the model used was that of data transformation. As in the multilevel model used in the first example, the data transformation model involved the separate but concurrent collection of qualitative and quantitative data. A novel step in this model involves transforming the qualitative data into quantitative data, and then comparing and interrelating the data sets. This required the development of procedures for transforming the qualitative data, related to, time spent on a step and salary of the provider, into quantitative cost data.

The two studies presented as examples demonstrate mixed methods research resulting in the creation of (a) a rich description of the American Indian chronic pain experience, and (b) a way to assess cost for providing chronic pain care via tribal clinics. In both examples, the quantitative data and their subsequent analysis provide a general understanding of the research problem. The qualitative data and their analysis refine and explain the results by exploring participants' views in more depth. Research using a single methodology would not have been able to achieve the same results.

Acknowledgments

Research reported in this paper was supported by the National Institute of Nursing Research of the National Institutes of Health under award number #R01NR012450 and the National Cancer Institute of the National Institutes of Health under award number #R42 CA141875. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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How Is Quantitative Design Used in Nursing

Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4287271/