Health Care Provider Organizations Research Articles

Improvements in technology and the expanding role of time-driven, activity-based costing to increase value in healthcare provider organizations: a literature review.

This study evaluated the influence of technology on accurately measuring costs using time-driven activity-based costing (TDABC) in healthcare provider organizations by identifying the most recent scientific evidence of how it contributed to increasing the value of surgical care. This is a literature-based analysis that mainly used two data sources: first, the most recent systematic reviews that specifically evaluated TDABC studies in the surgical field and, second, all articles that mentioned the use of CareMeasurement (CM) software to implement TDABC, which started to be published after the publication of the systematic review. The articles from the systematic review were grouped as manually performed TDABC, while those using CM were grouped as technology-based studies of TDABC implementations. The analyses focused on evaluating the impact of using technology to apply TDABC. A general description was followed by three levels of information extraction: the number of cases included, the number of articles published per year, and the contributions of TDABC to achieve cost savings and other improvements. Fourteen studies using real-world patient-level data to evaluate costs comprised the manual group of studies. Thirteen studies that reported the use of CM comprised the technology-based group of articles. In the manual studies, the average number of cases included per study was 160, while in the technology-based studies, the average number of cases included was 4,767. Technology-based studies, on average, have a more comprehensive impact than manual ones in providing accurate cost information from larger samples. TDABC studies supported by technologies such as CM register more cases, identify cost-saving opportunities, and are frequently used to support reimbursement strategies based on value. The findings suggest that using TDABC with the support of technology can increase healthcare value.

Characterizing user demographics in posts related to breast, lung and colon cancer on Japanese twitter (X)

Various cancer-related information is spreading on social media. Our study aimed to examine the account types associated with cancer-related tweets (currently known as posts) on Twitter (currently known as X) in Japan, specifically focusing on breast, lung, and colon cancer. Using the Twitter application programming interface, we collected tweets containing keywords of the three cancers type in August–September 2022. The accounts were categorized into seven types: Survivor, Patient’s family, Healthcare provider, Public organization, Private organization, News, and Other according to account name and texts. We analyzed the sources of the top 50 most liked and retweeted tweets. Out of 7753 identified tweets, breast cancer represented the majority (62.8%), followed by lung cancer (20.8%) and colon cancer (16.3%). Tweets came from 4976 accounts. Account types varied depending on the cancer type, with breast cancer topics more frequently from Survivor (16.0%) and lung cancer from Patient’s family (16.3%). Healthcare provider and Public organization had minimal representation across three cancer types. The trends in the top 50 tweets mirrored the distribution of accounts for each cancer type. Breast cancer-related tweets had the highest frequency. There were few from public organizations. These findings emphasize the need to consider the characteristics of cancer-related information sources when sharing and gathering information on social media.

Analytical Investigation of the Factors Affecting the Supplier-Induced Demand in Healthcare: A Case Study of CT Scanning Department

The aim of this study was to investigate the factors affecting the supplier-induced demand in health care with the help of an analytical-survey approach and using a questionnaire tool, and to analyze the role of medical technology centers, such as centers equipped with a CT scanning department, in development of this type of demand. The statistical population of the present research consisted of the patients referring to this department, out of whom 80 people were selected as the research sample using the simple random sampling method. After checking the normality of the data distribution through the Kolmogorov-Smirnov test, three research hypotheses were developed, all of which were confirmed by analyzing them using the Pearson correlation parametric test. The results of the data analysis indicated that the low patient information, high physician information, and high costs of healthcare service provider institutions have a positive effect on the supplier-induced demand in healthcare (especially in the departments with therapeutic technologies such as CT scanning). In addition, according to the results, the variable of high costs of healthcare provider organizations plays a more significant role in development of supplier-induced demand for healthcare providers, compared to the other two variables.

Evolving availability and standardization of patient attributes for matching.

Variation in availability, format, and standardization of patient attributes across health care organizations impacts patient-matching performance. We report on the changing nature of patient-matching features available from 2010-2020 across diverse care settings. We asked 38 health care provider organizations about their current patient attribute data-collection practices. All sites collected name, date of birth (DOB), address, and phone number. Name, DOB, current address, social security number (SSN), sex, and phone number were most commonly used for cross-provider patient matching. Electronic health record queries for a subset of 20 participating sites revealed that DOB, first name, last name, city, and postal codes were highly available (>90%) across health care organizations and time. SSN declined slightly in the last years of the study period. Birth sex, gender identity, language, country full name, country abbreviation, health insurance number, ethnicity, cell phone number, email address, and weight increased over 50% from 2010 to 2020. Understanding the wide variation in available patient attributes across care settings in the United States can guide selection and standardization efforts for improved patient matching in the United States.

Partnerships between anchor-med institutions and community organizations to address social determinants of health in urban populations: Do institutional pressures play a role?

ABSTRACT Social determinants of health (SDOH), the external environmental factors that determine health and well-being, often play a key role in health disparities and health inequities, and are outside the control of individuals. In urban and rural settings, hospitals have a critical role to play in addressing these SDOH; however, they cannot do so as a lone entity. Hospitals may function as anchor institution and form multi-sector partnerships with other community organizations (educational institutions, organizations addressing food insecurity, public health agencies, other healthcare provider organizations, etc.) to address these complex SDOH. However, as anchor institutions, urban hospitals may also face strong institutional pressures from their stakeholders and society at large. Based on institutional theory and resource dependency theory framework, we examine 1,191 urban hospitals in the United States reporting partnerships with community organizations to address SDOH. Our findings indicate that while addressing SDOH may be a driver, partnerships between hospitals and community organizations may also be in response to institutional pressures.

The Detection of Date Shifting in Real-World Data.

Analysis of health care real-world data (RWD) provides an opportunity to observe the actual patient diagnostic, treatment, and outcome events. However, researchers should understand the possible limitations of RWD. In particular, the dates in these data may be shifted from their actual values, which might affect the validity of study conclusions. A methodology for detecting the presence of shifted dates in RWD was developed by considering various approaches to confirm the expected occurrences of medical events, including unique temporal occurrences as well as recurring seasonal or weekday patterns in diagnoses or procedures. Diagnosis and procedure data was obtained from 71 U.S. health care data provider organizations (HCOs), members of the TriNetX global research network. Synthetic data was generated for various degrees of date shifting corresponding to the diagnoses and procedures studied, yielding the resulting patterns when various degrees of shifting (including no shift) were applied. These patterns were compared with those produced for each HCO to predict the presence and degree of date shifting. These predictions were compared with statements of date shifting by the originating HCOs to determine the predictive accuracy of the methods studied. Twenty-eight of the 71 HCOs analyzed were predicted by methodology and confirmed by their data providers to have shifted data. Likewise, 39 were predicted and confirmed to not have shifted data. With four HCOs, agreement between predicted and stated date shifting status was not obtained. The occurrence of routine medical exams, only happening during weekdays, for these U.S. HCOs was most predictive (0.92 correlation coefficient) of the presence or absence of date shifting. The presence of date shifting for U.S. HCOs may be reliably detected assessing whether the routine exams should always occur on weekdays.

Prevalence of 12 Common Health Conditions in Sexual and Gender Minority Participants in the All of Us Research Program

Limited data describe the health status of sexual or gender minority (SGM) people due to inaccurate and inconsistent ascertainment of gender identity, sex assigned at birth, and sexual orientation. To evaluate whether the prevalence of 12 health conditions is higher among SGM adults in the All of Us Research Program data compared with cisgender heterosexual (non-SGM) people. This cross-sectional study used data from a multidisciplinary research consortium, the All of Us Research Program, that links participant-reported survey information to electronic health records (EHR) and physical measurements. In total, 372 082 US adults recruited and enrolled at an All of Us health care provider organization or by directly visiting the enrollment website from May 31, 2017, to January 1, 2022, and were assessed for study eligibility. Self-identified gender identity and sexual orientation group. Twelve health conditions were evaluated: 11 using EHR data and 1, body mass index (BMI; calculated as weight in kilograms divided by height in meters squared), using participants' physical measurements. Logistic regression (adjusting for age, income, and employment, enrollment year, and US Census division) was used to obtain adjusted odds ratios (AORs) for the associations between each SGM group and health condition compared with a non-SGM reference group. The analytic sample included 346 868 participants (median [IQR] age, 55 [39-68] years; 30 763 [8.9%] self-identified as SGM). Among participants with available BMI (80.2%) and EHR data (69.4%), SGM groups had higher odds of anxiety, depression, HIV diagnosis, and tobacco use disorder but lower odds of cardiovascular disease, kidney disease, diabetes, and hypertension. Estimated associations for asthma (AOR, 0.39 [95% CI, 0.24-0.63] for gender diverse people assigned male at birth; AOR, 0.51 [95% CI, 0.38-0.69] for transgender women), a BMI of 25 or higher (AOR, 1.65 [95% CI, 1.38-1.96] for transgender men), cancer (AOR, 1.15 [95% CI, 1.07-1.23] for cisgender sexual minority men; AOR, 0.88 [95% CI, 0.81-0.95] for cisgender sexual minority women), and substance use disorder (AOR, 0.35 [95% CI, 0.24-0.52] for gender diverse people assigned female at birth; AOR, 0.65 [95% CI, 0.49-0.87] for transgender men) varied substantially across SGM groups compared with non-SGM groups. In this cross-sectional analysis of data from the All of Us Research Program, SGM participants experienced health inequities that varied by group and condition. The All of Us Research Program can be a valuable resource for conducting health research focused on SGM people.

Association of body mass index with the development of metabolic acidosis in patients with chronic kidney disease

AbstractAimsHigher body mass index (BMI) is associated with higher bone mass and bone serves as a buffer during the development of metabolic acidosis. The authors sought to examine the relationship between BMI and metabolic acidosis in patients with chronic kidney disease (CKD).Materials and MethodsThe study utilized a large US longitudinal data repository including over 103 million patients from healthcare provider organizations to evaluate the relationship between the exposure variable (BMI) and the prevalence and incidence of metabolic acidosis among patients with estimated glomerular filtration rate <60 ml/min/1.73 m2. Incident metabolic acidosis was identified at the first of two consecutive post‐index serum bicarbonate values, 10–365 days apart, between 12 and <22 mEq/L in patients with normal index serum bicarbonate. Cox proportional hazard models were adjusted for multiple variables including demographics, comorbidities, income, education, and kidney function.Results103,766 patients qualified for this study; 6472 (6.2%) had metabolic acidosis at index. An inverse association between BMI category and metabolic acidosis was observed for both baseline (prevalence) and new‐onset (incidence) metabolic acidosis. Compared to BMI category of 18.5 to <25 kg/m2, each category of incrementally higher BMI was associated with a decreasing risk of incident metabolic acidosis; the adjusted hazard ratios (95% confidence interval) were 0.866 (0.824–0.911), 0.770 (0.729–0.813), 0.664 (0.622–0.709), and 0.612 (0.571–0.655) for BMI 25 to <30, 30 to <35, 35 to <40, and 40+ kg/m2, respectively.ConclusionsAmong patients with CKD, an incremental increase in BMI was inversely associated with both the prevalence and incidence of metabolic acidosis. These associations suggest that increased body weight may protect against the development of metabolic acidosis, a risk factor for progressive loss of kidney function.

Barriers to Effective Communication about Advance Care Planning and Palliative Care: A Qualitative Study.

The purpose of this study was to identify barriers to effective conversations about advance care planning (ACP) and palliative care reported by health care and community-based service providers in Massachusetts, USA. This qualitative research analyzed open-ended responses to two survey questions, inquiring about perceived barriers to having conversations about ACP and palliative care with patients and consumers. Data were collected between November 2017 and June 2019 from nine organizations in Massachusetts, including health care provider organizations, health insurers, community-based organizations, and a nursing education institution. Two researchers reviewed and coded the responses and identified common themes inductively. Across 142 responses, primary barriers to ACP included hesitation and lack of understanding and knowledge, discomfort and resistance among service providers, lack of staff knowledge, difficulties with follow-up, and differences in ACP policies across regions. Common barriers to palliative care were misconceptions about palliative care and lack of knowledge, service providers' lack of preparedness, and limited policy support and availability. Challenges relevant to both ACP and palliative care were fear and discomfort around serious illness discussions, lack of knowledge and awareness, discussions that occur too late, and cultural and language barriers. Health care practitioners and community-based professionals reported consumer-, service provider-, and system-level barriers to facilitating conversations about ACP and palliative care with patients experiencing serious illness. There is a need for more tools and support to strengthen service providers' ACP and palliative care competencies and to promote a structured approach to health care planning conversations.

A data-driven approach to manage type 2 diabetes mellitus through digital health: The Klivo Intervention Program protocol (KIPDM).

Digital therapeutics, an emerging type of medical approach, is defined as evidence-based therapeutic interventions through qualified software programs that help prevent, manage, or treat chronic diseases such as type 2 diabetes mellitus (T2DM), which has high social and economic burden. Klivo, a startup certified by the Brazilian Society of Diabetes, developed the first digital therapeutic product for managing T2DM in Brazil, reaching 21 of 24 states. Klivo has continuously been improving its model of behavior change on the basis of an intensive lifestyle intervention method that addresses individuals' needs-the Klivo Intervention Program for T2DM (KIPDM). To test the most recent version of the KIPDM, we will evaluate the ongoing management of daily life habits in patients with T2DM by measuring clinically significant outcomes. To improve the transparency of further results, here we will present the study protocol and detail the plan for the research project, including the study design and the analysis strategies. The KIPDM will be sponsored by health plans and healthcare provider organizations and will be free for patients (adults aged ≥ 18 years and <65 years; and glycated hemoglobin ≥ 7%). The program will be based on a 6-month management process that will supervise patients remotely. The program will include educational classes via the Klivo app, text messages, or e-mails. Evaluation will include objectively assessing clinical, laboratory, and behavioral outcomes such as health-related quality of life, mental health, medication adherence, and healthcare utilization. For this, validated electronic questionnaires will be available through the Klivo app. The primary outcome will be glycated hemoglobin (HbA1c) values. The secondary outcome will be time in target blood glucose range (TIR) estimated by capillary glycemia. Other outcomes of interest will be evaluated at baseline and stipulated time points (3 and 6 months after the start of the program). KIPDM patients should present improved HbA1c and TIR along the intervention as compared to baseline values. Findings from this study will provide insights into the health improvement of T2DM and other cardiometabolic conditions such as hypertension, dyslipidemia, and obesity by using a digital therapeutic strategy. By analyzing the patient's health over time, this study will also contribute to understanding comorbidities associated with this chronic condition in the Brazilian population.

Alopecia areata in underrepresented groups: preliminary analysis of the all of us research program.

Alopecia areata (AA) is an autoimmune condition characterized by patchy, nonscarring hair loss. Few studies of AA have adequately included participants from underrepresented groups when evaluating the burden of AA in the United States. We conducted a cross-sectional study of personal/demographic factors and AA using the ongoing All of Us (AoU) Research Program. AoU enrolls adults over 18years either as direct volunteers or through participating Health Care Provider Organizations by prioritizing recruiting underrepresented groups. We linked data from surveys and electronic health records (EHRs) to estimate the prevalence of AA by race/ethnicity, physical disability, sexual orientation/gender identity (LGBTQIA +), income, and education. The latest AoU release (version 5) includes 329,038 participants. Average age was 51.8years (standard deviation, SD 16.7), and 60.2% of participants were female. Of these, 251,597 (76.5%) had EHR data and 752 were diagnosed with AA (prevalence, 0.30%; 95% CI 0.28-0.32). We used multivariate logistic regression adjusted for age and other factors to estimate the odds ratio (OR) and 95% confidence intervals (CIs) for prevalence of AA. Compared to Whites, Blacks and Hispanics had higher odds of AA (OR, 1.72; 95% CI 1.39-2.11 and OR, 2.13; 95% CI 1.74-2.59, respectively). Lower odds of AA were observed in participants with less than a high school degree (OR, 0.80; 95% CI 0.59-1.08), household income ≤ $35,000 (OR, 0.67; 95% CI 0.54-0.83), and no health insurance (OR 0.35; 95% CI 0.20-0.56). In this diverse population of US adults, participants with skin of color had higher prevalence of AA. Lower prevalence of AA among individuals with lower education and income levels and those lacking health insurance may reflect limited access to dermatologic care and potentially higher levels of undiagnosed AA in these groups.

A Brief History of Public Health Informatics-Lessons for Leaders and a Look Into the Future.

A Brief History of Public Health Informatics-Lessons for Leaders and a Look Into the Future.

How Might We Have Known? Using Administrative Data to Predict 30-Day Hospital Readmission in Clients Receiving Home Care Services from 2018 to 2021.

Reducing hospital readmissions can improve individual health outcomes and lower system-level costs. This study aimed to understand the characteristics of home care Personal Support clients who experienced a hospital admission (ie, hospital hold) and to identify factors that predict hospital readmission within 30 days of resuming home care Personal Support services. We conducted a retrospective cohort study using client administrative data from a home healthcare provider organization (2018-2021). The sample included clients (⩾18 years) who received publicly funded Personal Support services and experienced a hospital hold. Descriptive statistics and a binary logistic regression model analyzed the relationship between demographics, hospital service utilization, home care service utilization, and contextual factors on the outcome of 30-day hospital readmission. Approximately 17% (n = 662) of all clients with a hospital hold (n = 3992) were readmitted to hospital within 30 days. Compared with non-readmitted clients, those with greater home care Personal Support service intensity after the index hospital hold were less likely to experience a hospital 30-day readmission. In contrast, those with greater acuity, higher assessed care needs, more hospital holds overall, more extended hospital stays (⩾2 weeks), and lower social support had a higher likelihood of 30-day hospital readmission. The findings from this study provide a greater understanding of factors associated with home care clients' risk of hospital readmission within 30 days and can be used to inform targeted, evidence-based support to reduce home care clients' hospital readmissions.

Factors governing the adoption of artificial intelligence in healthcare providers

Artificial intelligence applications are prevalent in the research lab and in startups, but relatively few have found their way into healthcare provider organizations. Adoption of AI innovations in consumer and business domains is typically much faster. While such delays are frustrating to those who believe in the potential of AI to transform healthcare, they are largely inherent in the structure and function of provider organizations. This article reviews the factors that govern adoption and explains why adoption has taken place at a slow pace. Research sources for the article include interviews with provider executives, healthcare IT professors and consultants, and AI vendor executives. The article considers differential speed of adoption in clinical vs. administrative applications, regulatory approval issues, reimbursement and return on investments in healthcare AI, data sources and integration with electronic health record systems, the need for clinical education, issues involving fit with clinical workflows, and ethical considerations. It concludes with a discussion of how provider organizations can successfully plan for organizational deployment.

Clinical decision support malfunctions related to medication routes: a case series.

ObjectiveTo identify common medication route-related causes of clinical decision support (CDS) malfunctions and best practices for avoiding them.Materials and MethodsCase series of medication route-related CDS malfunctions from diverse healthcare provider organizations.ResultsNine cases were identified and described, including both false-positive and false-negative alert scenarios. A common cause was the inclusion of nonsystemically available medication routes in value sets (eg, eye drops, ear drops, or topical preparations) when only systemically available routes were appropriate.DiscussionThese value set errors are common, occur across healthcare provider organizations and electronic health record (EHR) systems, affect many different types of medications, and can impact the accuracy of CDS interventions. New knowledge management tools and processes for auditing existing value sets and supporting the creation of new value sets can mitigate many of these issues. Furthermore, value set issues can adversely affect other aspects of the EHR, such as quality reporting and population health management.ConclusionValue set issues related to medication routes are widespread and can lead to CDS malfunctions. Organizations should make appropriate investments in knowledge management tools and strategies, such as those outlined in our recommendations.

Ancillary Data Record Linkage to characterize the completeness of data for the All of Us Research Program.

ObjectiveThe All of Us Research Program (AoURP) is an ambitious effort to gather health data from one million Americans to accelerate research. We linked Electronic Health Records (EHR) and insurance claims data to characterize the degree to which ancillary datasets can improve data completeness for care received by AoURP participants. ApproachWe sought to link EHR data for 400,000 consented AoURP participants with insurance claims data provided by IPM.AI (Swoop Analytics), a commercial analytics company who have insurance claims data for 300M (over 90% of) Americans. We utilized a HIPAA-compliant privacy-preserving record linkage method (tokenization, provided by Datavant) to match patients between datasets. We evaluated match fidelity and the degree of overlap between AoURP EHRs and IPM.AI claims data. We characterized the association of patient and organizational level factors (demographics, healthcare provider organization, reporting site) with match performance. ResultsAs of submission of this abstract, 41% of AoURP EHRs matched with IPM.AI claims. We compared patient healthcare encounters, diagnosis codes (DX), procedure codes (PX), and national drug codes (NDC) for matched patients by month. The union of AoU and IPM.AI data greatly increased data completeness in matched patients. Only 20% of healthcare encounters were seen by AoURP and IPM.AI concurrently while 25% were unique to AoU EHRs and 55% to IPM.AI claims on a monthly level. The number of diagnosis events compared between AoURP and IPM.AI is roughly equal (AoU +6%) while procedure events are elevated in claims data (23%) and drug counts are greatly elevated in AoURP EHR data (71%). We found that matched patients had more healthcare encounters compared to unmatched patients. ConclusionTo our knowledge this is the first effort to address challenges in AoURP data completeness through complementary data linkage. Our results suggest that supplementary data linkage can improve data completeness in a large national research initiative. We identified several patient factors that require further investigation in improving match fidelity.

Moving Beyond the LGBTQIA+ Acronym: Toward Patient-Centered Care.

The LGBTQIA+ communities experience distinct health disparities and inequities in health outcomes. Healthcare providers must be conscious of factors to facilitate optimal, person-centered care. This narrative briefly covers health disparities in the LGBTQIA+ community and posits strategies to promote inclusive care. Current literature and clinical best practices from several authoritative sources on LGBTQIA+-specific issues and gender-affirming care were reviewed. Sources included several LGBTQIA+-specific healthcare organizations, national healthcare provider organizations, and federal agency policy statements. Inclusive terminology and healthcare practices were included. Healthcare providers must educate themselves on caring for gender- and sexual orientation-diverse populations to optimize the health status of these communities. It is essential that providers examine their own potential biases and maintain an openness to learning about LGBTQIA+ communities. Healthcare providers have a responsibility to not only understand issues specific to LGBTQIA+ individuals but also advocate for these groups. As nurses, we must continue to support public health policies that seek to end disparities and ensure health equity for all. Rehabilitation nurses are caring for more diverse populations than ever before and must understand how to provide compassionate, individualized care. Although this article focuses on the LGBTQIA+ community, the principles discussed are applicable across all populations.

Health System Inquiry: Is Health Sector Reforms in Bangladesh Imperative?

In Bangladesh, Government is trying to find a perfect health system that best serves its population. Here, we present the results of our study with aim to assess the opinion of various stakeholders about: what are the 1) high-priority areas, 2) moderate priority areas, and 3) low-priority areas to reform the health sectors for Bangladesh. We conducted a cross-sectional, exploratory and anonymous population-based e-survey from February to June, 2021 among individuals aged above 26 years. A semi-structured questionnaire was designed and incorporated into the Google survey tool (Google Forms) and a shareable link was generated and disseminated to physicians, Academicians/ Clinicians of Medical Colleges/ Universities, Health System administrators etc. Respondents were also given space to comment on each topic. Comments &amp; reactions of all respondents were categorized into three main headings. These were 1) high-priority areas, 2) moderate priority areas, and 3) low-priority areas to reform the health sectors for Bangladesh. Out of 483 respondents, 476 respondents (80.5% males and 19.5% female) completed the entire survey. The mean age of respondents is 44.70 SD± 10.07 with age range 26-86 years. About 27% of the respondents were from faculties from medical colleges /medical universities and 1.7% were health system administrators. The high prioritized areas where the majority (&gt;60%) of our respondents strongly agreed upon, for instance, good governance, structural referral system should be establishment, and reformation of existing health care procurement &amp; purchasing policy. The moderate prioritized areas where 50 - 60% of our respondents strongly agreed upon, such as securing sustainable financing for health care, further development of existing health infrastructure, and establishment of Health Academy of planning and development (HAPD). The low prioritized areas where less than 50% of our respondents strongly agreed upon, such as decentralization and autonomous health system, public health-oriented infection prevention and control (IPC) program, and implement the national health insurance system (NHIS) under a separate authority etc. Good governance in health departments &amp; health care provider organizations are essential elements for health sector reform. Health sector reform should be sustained, purposeful, planned and evidence-based and fundamental change addressing significant, strategic dimensions of health systems. J Bangladesh Coll Phys Surg 2022; 40: 84-94

Value-based healthcare in Latin America: a survey of 70 healthcare provider organisations from Argentina, Brazil, Chile, Colombia and Mexico

ObjectivesValue-based healthcare (VBHC) is a health system reform gradually being implemented in health systems worldwide. A previous national-level survey has shown that Latin American countries were in the early stages...

It Is “All About Relationships” in Lifestyle Programmes for Adults Living With Type Two Diabetes Underpinned by a Person/Whānau-Centred Care Approach

BackgroundLifestyle programmes are important in the management of type 2 diabetes (T2D). The Diabetes Community Exercise Programme (DCEP) is an exercise and educational programme for adults living with T2D with the aim of enhancing exercise self-efficacy and supporting wellbeing. DCEP is underpinned by a model of person/whānau-centred care and the spirit of Motivational Interviewing. Person-centred care models in the context of rehabilitation and long-term health conditions are still evolving. This paper explores what those involved in DCEP perceived important to its person/whānau-centredness.MethodAn evaluative qualitative methodological approach was used with data collected by open-ended interviews and a focus-group at completion of the initial 12-week part of DCEP. Interviews were audio-recorded and transcribed verbatim. Participants were 16 DCEP attendees and 13 healthcare professionals (HCPs) involved in DCEP delivering. Data were analysed using the General Inductive Approach.ResultsThe three interconnected themes constructed from the analysis were ‘It's all about relationships’, Balancing the Outside World, and Empowering through Knowledge. Through the experience and motivation of positive person-centred relationships, DCEP addressed attendees' T2D health needs, but they were constantly balancing these needs with those of family, employers, finances, other health needs and life interests. DCEP relationships facilitated ongoing discussions between attendees and between attendees and HCPs. The ability to discuss in a supportive and non-judgmental environment helped attendees to make sense and process the information they gained at DCEP. This empowering through knowledge in turn helped attendees to work out ways of balancing the outside world and thus better address their T2D needs.ConclusionIt is “all about relationships” was key to DCEP's person/whānau-centred approach—all other factors related back to the development and maintenance of relationships. These relationships were between all whānau involved: the attendees, their family, the wider community, the healthcare provider organisations, and the HCPs and personnel involved in delivering DCEPs. These relationships created an accepting, understanding and social atmosphere that enabled attendance and facilitated both knowledge exchange and ability to exercise, both considered to be beneficial by attendees. Importantly, these relationships took time to develop, but the benefits were worth the investment.