Demonstrating the value of digital health: Guidance on contextual evidence gathering for companies in different stages of maturity.

Application of value-based healthcare policies affects all actors in social and health care field, including the Digital Health Intervention (DHI) providers aiming to enter the industry or expand their market. Apparent lack of fit between evidence and expectations inhibits the growth of DHI companies. The companies need efficient and credible methods to access and demonstrate the value of their DHIs. Building on the stage-of-maturity logic presented in World Health Organization's (WHO) guide of monitoring and evaluating digital health interventions and Context-Intervention-Mechanism-Outcome (CIMO) logic, we provide a potential approach for DHI companies to assess the evidence needed in their current situation. The proposed approach takes into account the company's future development goals and the business environment, reflecting for every stage of technology maturity according to the WHO guidelines and through the CIMO lens. The focus is on specific intervention and its fit for different organizational and national contexts. The solution guides the research process of the company to understand which evidence-gathering topics should be addressed. This evidence can be beneficial for companies to enter into, occupy, expand or sustain in the domestic or international market.

Data Sharing in Pharmaceutical Supply Chains - Case European Medicines Verification System.

We study the perceived value derived from data sharing activities by the representatives of a Nordic pharmaceutical company in the introduction of the European Medicines Verification System (EMVS). The system is an end-to-end verification protocol that would potentially enable the pharmaceutical companies to access the sales-point data from within the system, while maintaining the control of their own data. The benefits of the system are most notably in developing data sharing with the wholesalers and end-customers. Development of data sharing practices might enable more transparent logistics, and more targeted services and products.

Commercial Adoption of AI in the Healthcare Sector: An Exploratory Analysis of S&P500 Companies.

The use of Artificial Intelligence (AI) technologies within the healthcare sector is growing. However, there are differences in the speed of commercial adoption of AI across sub-sectors. We employ a dataset including news mentions and executive communications of all S&P500 Health Care Index companies to explore these differences. Pharmaceutical and medicine manufacturing companies had the earliest AI-linked news presence, yet they appeared to be among the slowest commercial implementers of AI. Ambulatory health care services and hospitals, as well as insurance carriers, received media coverage later, but were the quickest to take AI into commercial use. From the theory perspective our results indicate that the classical innovation diffusion theory might not fully explain these differences.

Digital Follow-Up Application for Cancer Patients - Value Mechanisms Regarding Health Professionals' Work.

This study examined the value mechanisms of a digital cancer follow-up application (CFUA). Value is defined as the health outcomes achieved per resources used. The focus was on how the digital health intervention (DHI) affects the professionals' work. The research was conducted through interviews of healthcare professionals in the empirical context of gynecological cancer clinic at a university hospital in Finland. The identified key mechanisms were improved coordination and optimized care level. The CFUA improves coordination through reducing time restrictions of work, as the professionals have more chances to time their contacts and plan their work. The CFUA helps in optimizing care level, as the application can effectively filter patients to either nurses or physicians according to symptoms. Coordination mechanism is closely connected to other healthcare value mechanisms, such as reducing waste and supply management. This study increases understanding of DHI value potential recognition, and how value can be actualized.

Value Mechanisms in the Implementation of Intelligent Patient Flow Management System - A Multiple Case Study.

The purpose of this study was to investigate the value mechanisms in implementing a digital health intervention (DHI) in different contexts and countries. We utilized realist evaluation and the CIMO logic (Context, Intervention, Mechanism, Outcome) to analyze the mechanisms explaining the value capture of Klinik Pro, an Intelligent Patient Flow Management system (IPFM), which is a DHI for seeking of treatment and triage purposes. The study was conducted as a multiple case study using semi-structured interviews to research four market expansions in three countries. In total, seven healthcare mechanisms were discovered: co-creation, proper competence level, coordination, evidence-based medicine, integration, proper timing, demand management. The first four mechanisms were the same in all cases. CIMO framework proved to be useful in the value formulation of the IPFM.

Women's decisional conflict in the pathway of prenatal screening and testing: an explorative study within Finnish public maternity care.

Objectives To explore women's decisional conflict in the pathway of prenatal screening and testing (PreST) in Finland and to evaluate a counseling service. Methods Self-completion surveys were conducted at two medical settings (screening and further testing) of PreST. Decisional Conflict Scale (DCS) was the main measure. Different types of statistical tests were used to compare women's decisional conflict at different medical settings of PreST, and before-after pre-test counseling. Multivariable linear regressions analyzed the influences of the medical settings and other factors on women's decisional conflict. Results Compared to women in population-based screening, women in further testing (before pre-test counseling) were more likely to feel well informed (P < 0.001), had increased values clarity (P < 0.001), but more likely experienced uncertainty (P = 0.040). Besides medical settings, maternal age, gravidity and previous experience of fetal aneuploidy significantly influenced decisional conflict. After counseling, screen-positive women felt better informed (P < 0.001), had increased values clarity (P < 0.001), perceived more support (P < 0.001), and had better decision certainty (P < 0.001) than before counseling. Conclusions Medical settings influence women's decisional conflict during PreST. Individual counseling is effective in improving screen-positive women's decisional conflict. This research adds knowledge and experience on developing decision-making supports across the pathway of PreST.

Factors Affecting Venture Funding of Healthcare AI Companies.

Venture Capital (VC) funding raised by companies producing Artificial Intelligence (AI) or Machine Learning (ML) solutions is on the rise and a driver of technology development. In healthcare, VC funding is distributed unevenly and certain technologies have attracted significantly more funding than others have. We analyzed a database of 106 Healthcare AI companies collected from open online sources to understand factors affecting the VC funding of AI companies operating in different areas of healthcare. The results suggest that there is a significant connection between higher funding and having research organizations or pharmaceutical companies as the customer of the product or service. In addition, focusing on AI solutions that are applied to direct patient care delivery is associated with lower funding. We discuss the implications of our findings for public health technology funding institutions.

From Tertiary to Primary Care - Understanding Context in the Transfer of Digital Headache Service Pathway.

A digital service pathway for managing chronic headache has been designed in tertiary care in Finland. The digital tool facilitates self-management by providing exercises, information and messaging opportunities for patients. However, the largest potential benefits are in primaryand occupational care. Thus, the purpose of this study was to explore the needs and requirements of primary and occupational care actors for better understanding of the context in the transfer of the service. The study was performed as a single embedded case study. The qualitative data was collected through semi-structured interviews with 16 informants from different organizations and analyzed with Gioia-methodology. This study gathers important empirical knowledge about the meaning of context and transferring digital health interventions from one context to another from clinician and management perspective. Nine key contextual differences were identified and six main expectations emerged.

Intelligent Patient Flow Management System at a Primary Healthcare Center - The Effect on Service Use and Costs.

An intelligent patient flow management system (IPFM) was piloted at a large primary healthcare center in Finland in August 2017. The goals of the system are to help patients avoid unnecessary calls and visits to their health center and to enhance the use of professional resources through more streamlined patient pathways and the re-allocation of professionals from assessment tasks to actual patient care. These goals should be reflected in the decreased service costs through optimized contact forms. Using multiple regression analysis, we studied the associations between IPFM and patients' service utilization (17,943 patients; 73,038 service contacts) during the first five months of the pilot in 2017. The results indicated that the use of IPFM by the patient was associated with a decrease of EUR 31 in the total service costs of the patient in the study period. This decrease is 14% of patient's average total service cost.

Facilitating autonomous, confident and satisfying choices: a mixed-method study of women's choice-making in prenatal screening for common aneuploidies.

BACKGROUND: Population-based prenatal screening has become a common and widely available obstetrical practice in majority of developed countries. Under the patient autonomy principle, women should understand the screening options, be able to take their personal preferences and situations into account, and be encouraged to make autonomous and intentional decisions. The majority of the current research focuses on the prenatal screening uptake rate, women's choice on screening tests, and the influential factors. However, little attention has been paid to women's choice-making processes and experiences in prenatal screening and their influences on choice satisfaction. Understanding women's choice-making processes and experiences in pregnancy and childbirth is the prerequisite for designing women-centered choice aids and delivering women-centered maternity care. This paper presents a pilot study that aims to investigate women's experiences when they make choices for screening tests, quantify the choice-making experience, and identify the experiential factors that affect women's satisfaction on choices they made. METHOD: We conducted a mixed-method research at Helsinki and Uusimaa Hospital District (HUS) in Finland. First, the women's choice-making experiences were explored by semi-structured interviews. We interviewed 28 women who participated in prenatal screening. The interview data was processed by thematic analysis. Then, a cross-sectional self-completion survey was designed and implemented, assessing women's experiences in choice-making and identifying the experiential factors that influence choice satisfaction. Of 940 distributed questionnaires, 185 responses were received. Multivariable linear regression analysis was used to detect the effects of the variables. RESULTS: We developed a set of measurements for women's choice-making experiences in prenatal screening with seven variables: activeness, informedness, confidence, social pressure, difficulty, positive emotion and negative emotion. Regression revealed that activeness in choice-making (ß = 0.176; p = 0.023), confidence in choice-making (ß = 0.388; p < 0.001), perceived social pressure (ß = - 0.306; p < 0.001) and perceived difficulty (ß = - 0.274; p < 0.001) significantly influenced women's choice satisfaction in prenatal screening. CONCLUSIONS: This study explores the experiential dimension of women's choice-making in prenatal screening. Our result will be useful for service providers to design women-centered choice environment. Women's willingness and capabilities of making active choices, their preferences, and social reliance should be well considered in order to facilitate autonomous, confident and satisfying choices.

How Patients Talk About Care? Identifying Patient Experience Expressions from Online Discussions.

Patient experience is an emerging concept that supports the improvement of healthcare services through identified patient expectations and experiences. In addition to structured feedback through official channels, experiences about healthcare appear increasingly in digital services and social media. We explore a new patient experience harvesting process based on linguistic patterns to identify relevant expressions in online discussions about children's health. Our results from the analysis of 98 229 unique sentences suggests that the 7-step process can be useful in discovering patients' evaluations of their care experiences. We propose ways to extend the process to other care contexts by adjusting the semantic reference models.

Context-based patient choice management in healthcare.

Purpose In healthcare, there is limited knowledge of and experience with patient choice management. The purpose of this paper is to focus on patient choice, apply and test demand-supply-based operating (DSO) logic integrated with clinical setting in clarifying choice contexts, investigate patient's choice-making at different contexts and suggest context-based choice architectures to manage and develop patient choice. Design/methodology/approach Prenatal screening and testing in the Helsinki and Uusimaa Hospital District (HUS), Finland, was taken as an example. Choice points were contextualized by using the DSO framework. Women's reflections, behaviors and experience at different choice contexts were studied by interviewing women participating in prenatal screening and testing. Semi-structured interview data were processed by thematic analysis. Findings By applying DSO logic, four choice contexts (prevention, cure, electives and continuous care) were relevant in the prenatal screening and testing episode. Women had different choice-making in prevention and cure mode contexts regarding choice activeness, information needs, social influence, preferences, emotion status and choice-making difficulty. Default choice was widely accepted by women in prevention mode and individual counseling can help women make informed choice in cure mode. Originality/value The authors apply the DSO model to contextualize the patient choice in one care episode and compare patient choice-making at different contexts. The authors also suggest the possible context-based choice architectures to manage and promote patient choice.

Considering medical risk information and communicating values: A mixed-method study of women's choice in prenatal testing.

INTRODUCTION: Nowadays, an important decision for pregnant women is whether to undergo prenatal testing for aneuploidies and which tests to uptake. We investigate the factors influencing women's choices between non-invasive prenatal testing (NIPT) and invasive prenatal tests in pregnancies with elevated a priori risk of fetal aneuploidies. METHODOLOGY: This is a mixed-method study. We used medical data (1st Jan 2015-31st Dec 2015) about women participating in further testing at Fetomaternal Medical Center at Helsinki University Hospital and employed Chi-square tests and ANOVA to compare the groups of women choosing different methods. Multinomial logistic regressions revealed the significant clinical factors influencing women's choice. We explored the underlying values, beliefs, attitudes and other psychosocial factors that affect women's choice by interviewing women with the Theory of Planned Behavior framework. The semi-structured interview data were processed by thematic analysis. RESULTS: Statistical data indicated that gestational age and counseling day were strong factors influencing women's choice. Interview data revealed that women's values and moral principles on pregnancy and childbirth chiefly determined the choices. Behavioral beliefs (e.g. safety and accuracy) and perceived choice control (e.g. easiness, rapidness and convenience) were also important and the major trade-offs happened between these constructs. DISCUSSION: Values are the determinants of women's choice. Service availability and convenience are strong factors. Medical risk status in this choice context is not highly influential. Choice aids can be developed by helping women to identify their leading values in prenatal testing and by providing lists of value-matching test options and attributes.

Women's choices for invasive or non-invasive testing: influence of gestational age and service delivery.

OBJECTIVE: To investigate the factors influencing women's post-counseling choices between non-invasive prenatal testing (NIPT) and invasive prenatal diagnosis in pregnancies with elevated a priori risk of fetal chromosomal abnormalities or after the initial screening. METHODS: Data were collected from test choice database at Fetomaternal Medical Center (FMC) at Helsinki University Hospital, Finland. We focused on the women with gestational age less than 15 weeks and who were offered NIPT or invasive procedure (CVS or amniocentesis) after pre-test counseling. The Chi-square test, ANOVA test and multinomial logistic regressions were used to explore significant factors affecting women's choice. RESULTS: In 2015, 333 women in our study group participated in prenatal testing, 260 (78.1%) initially chose NIPT, 62 (18.6%) chose CVS and 11 (3.3%) chose amniocentesis. There was a statistically significant difference among these three test groups with regard to gestational age (p = 0.025), counseling day (p < 0.001), certain medical indications and serum screening risk score (p = 0.028). However, multinomial logistic regressions only confirmed the predictive value of gestational age and counseling day on women's choice. CONCLUSIONS: Maternal age was not a strong factor affecting women's choice for prenatal further tests. Medical indications and risk scores have less influence than previously thought. Gestational age and service availability were strong factors. © 2016 John Wiley & Sons, Ltd.