(EBSCO)—130 articles
(ELSEVIER Science Direct and Springer Link)—340 articles
Network analysis is considered a branch of graph theory. Our network analysis is based on the similarity of keywords found in identifying the eligible papers. We used visualisation of similarities (VOS) software, version 1.6.18, to construct graphical networks to understand the clustering of the keywords and their degree of dissimilarity. Our network analysis is based on the similarity of keywords found in identifying the eligible papers.
The search was performed on the following databases: Scopus, Science Direct, and PubMed, using the keywords “digital transformation”, “digitalisation”, “Ehealth or e-health”, “mhealth or m-health”, “healthcare” and “health economics”. We selected publications from the search of international journals and conference proceedings. We collected papers from 2008 until 2021. The documents sought belonged to strategy, management, computer science, medicine, and health professions. Finally, the published works were in English only. The total number of articles collected using the keywords as shown in Table 2 was 5847.
Search Strategy.
Database | Search within | Keywords | No Sources | |
---|---|---|---|---|
1. | Scopus | Article title, Abstract, Keywords | (Digital transformation or digitalization) AND (Ehealth or e-health or mhealth or m-health or healthcare) AND (health economics) | 408 |
Article title, Abstract, Keywords | (Digital transformation) AND (health) | 1.152 | ||
2. | Science Direct | Article title | (Digital transformation) AND (health) | 2.142 |
3. | PubMed | Article title, Abstract | (Digital transformation or digitalization) AND (Ehealth or e-health or mhealth or m-health or healthcare) AND (health economics) | 978 |
Article title | (Digital transformation) AND (health) | 1.167 | ||
Total | 5.847 |
We systematically checked the total number of papers 5847 by reading their titles, abstracts, and, whenever necessary, the article’s first page to conclude if each document was relevant as a first step as shown in the Figure 1 .
The diagram for the first phase of the selection process.
Then, we looked at the titles of the 378 articles, and after reading their summary, we accepted 321 articles. Further studies were rejected because their full text was not accessible. As a result, there were 255 articles in our last search. Of the selected 255 articles, 32 more were added based on backward and forward research. The investigation was completed by collecting common standards from all databases using different keyword combinations. According to the systematic literature review, we follow the standards of Webster and Watson (2002) to reject an article. Since then, we have collected the critical mass of the relevant publications, as shown in Figure 2 .
The diagram of the article selection process.
The categorisation of the articles was based on their content and the concepts discussed within them. As a result, we classify articles into the following categories: information technology in health, the educational impact on e-health, the acceptance of e-health, telemedicine, and e-health security.
Although researchers in Information and Communication Technology and digitalisation conducted studies almost two decades ago, most publications have been published in the last eight years. This exciting finding highlights the importance of this field and its continuous development. Figure 3 shows a clear upward trend in recent years. More specifically, the research field of Information and Communication Technology, in combination with digital transformation, appeared in 2008. However, the most significant number of articles was found in 2019, 2020 and 2021. The number of articles decreased to the lowest in 2009–2011 and 2013–2014. Due to the expansion of the field to new technologies, the researchers studied whether the existing technological solutions are sufficient for implementing digital transformation and what problems they may face.
Number of articles and citations per publication by year.
Figure 3 shows a combination of the articles per year and the number of citations per publication per year.
Of the document types, 59.51 per cent of the articles were categorised as “survey”, while a smaller percentage were in: “case study” (32.53%), “literature review” (5.88%) and “report” (2.08%). However, these documents focused on specific concepts: “information technology in health” (45%), “education impact of e-health” (11%), “acceptance of e-health” (19%), “telemedicine” (7%), “security of e-health” (18%).
As we can see from the following Figure 4 , we used network analysis, where the keywords related to digitalisation and digital transformation were identified in the research study. Network analysis, using keywords, came with VOSviewer software to find more breadth and information on healthcare digitalisation and transformation exploration. It was created by analysing the coexistence of keywords author and index. This analysis’s importance lies in the structure of the specific research field is highlighted. In addition, it helped map the intellectual structure of scientific literature. Keywords were obtained from the title and summary of a document. However, there was a limit to the number of individual words. The figure represents a grid focused on reproducing keywords in the literature on the general dimensions of digitalisation. The digitalisation network analysis showed that e-health, telemedicine, telehealth, mobile health, electronic health/medical record, and information systems were the main relevant backgrounds in the literature we perceived. In the healthcare literature, keywords such as “empowerment” and “multicenter study” usually do not lead to a bibliographic search on digitalisation. Figure 4 shows how e-health and telemedicine have gone beyond the essential and most crucial research framework on how they can affect hospitals and the health sector. The potentially small gaps in network analysis can be filled by utilising data in our research study, contributing to future research.
Bibliometric map of the digital transformation and healthcare.
Figure 5 shows the network analysis with the keywords concerning time publication. The yellow colour indicates keywords for most recent years.
Network visualisation of keywords per year.
Figure 6 presents the density visualisation of keywords.
Heat map of keywords.
Figure 7 shows the number of articles per each method (survey, literature review etc.) for each year.
The map of number of articles per method for each year.
It is evident from Figure 7 that the most used method paper is the survey type and that in the year 2021, we have a high number of surveys compared to previous years.
In Figure 2 , we have explained how we collected the critical mass of the 255 relevant publications. We added another 32 articles based on further research with the backward and research methods, which resulted in a total number of 287 articles.
Then, the articles were categorised according to their content. The concepts discussed in the papers are related to information technology in health, the educational impact of e-health, the acceptance of e-health, telemedicine, and e-health security. For this purpose, the following table was created, called the concept matrix table.
In this section, we provide the Concept matrix table. Academic resources are classified according to if each article belongs or not to any of the five concepts shown in Table 3 .
Concept Matrix Table.
No. | Author | Year | Method | Sample | Data Analysis | Concepts | ||||
---|---|---|---|---|---|---|---|---|---|---|
Information Technology in Health | Education Impact of E-Health | Acceptance of E-Health | Telemedicine | Security of E-Health | ||||||
1 | Kesavadev, J, et al., [ ] | 2021 | Case Study | Χ | ||||||
2 | Attila, SZ et al., [ ] | 2021 | Survey | Χ | ||||||
3 | Malachynska, M et al., [ ] | 2021 | Case Study | Χ | ||||||
4 | Lu, WC et al., [ ] | 2021 | Survey | Χ | ||||||
5 | Burmann, A et al., [ ] | 2021 | Case Study | Χ | ||||||
6 | Bogumil-Ucan, S et al., [ ] | 2021 | Case Study | Χ | ||||||
7 | Zanutto, O [ ] | 2021 | Survey | Χ | ||||||
8 | Alauddin, MS; et al., [ ] | 2021 | Survey | Χ | ||||||
9 | Alterazi, HA [ ] | 2021 | Survey | Χ | ||||||
10 | Schmidt-Kaehler, S et al., [ ] | 2021 | Case Study | Χ | ||||||
11 | Zhao, Y et al., [ ] | 2021 | Case Study | Χ | Χ | |||||
12 | Roth, CB et al., [ ] | 2021 | Systematic Literature Review | Χ | Χ | |||||
13 | Ali, NA et al., [ ] | 2021 | Case Study | Χ | ||||||
14 | Alimbaev, A et al., [ ] | 2021 | Case Study | Χ | ||||||
15 | Dick, H et al., [ ] | 2021 | Systematic Literature Review | Χ | Χ | |||||
16 | Alt, R et al., [ ] | 2021 | Survey | a Vice President | - | Χ | ||||
17 | Bartosiewicz, A et al., [ ] | 2021 | Survey | Χ | Χ | |||||
18 | Mussener, U [ ] | 2021 | Survey | Χ | ||||||
19 | Naumann, L et al., [ ] | 2021 | Case Study | 59 qualitative telephone interviews | The findings hinted at five priorities of e-health policy making: strategy, consensus-building, decision-making, implementation and evaluation that emerged from the stakeholders’ perception of the e-health policy. | Χ | ||||
20 | Saetra, HS et al., [ ] | 2021 | Case Study | Χ | ||||||
21 | Zoltan, V et al., [ ] | 2021 | Survey | Χ | Χ | |||||
22 | Hoch, P et al., [ ] | 2021 | Survey | Χ | ||||||
23 | De Vos, J [ ] | 2021 | Survey | Χ | ||||||
24 | Beaulieu, M et al., [ ] | 2021 | Survey | Χ | ||||||
25 | Dang, TH et al., [ ] | 2021 | Survey | Χ | Χ | Χ | ||||
26 | Kraus, S et al., [ ] | 2021 | Systematic Literature Review | Χ | Χ | Χ | ||||
27 | Gauthier, P et al., [ ] | 2021 | Survey | Χ | ||||||
28 | Zhang, JS et al., [ ] | 2021 | Survey | Χ | ||||||
29 | Mallmann, CA et al., [ ] | 2021 | Survey | 513 breast cancer patients from 2012 to 2020 | Statistical analysis | Χ | ||||
30 | Fons, AQ [ ] | 2021 | Survey | Χ | ||||||
31 | Chatterjee, S et al., [ ] | 2021 | Survey | Consumers of different age groups & people working in the healthcare sector (including doctors) | Qualitative analysis | Χ | Χ | |||
32 | Wasmann, JWA et al., [ ] | 2021 | Survey | Χ | ||||||
33 | Kanungo, RP et al., [ ] | 2021 | Survey | Χ | ||||||
34 | Fernandez-Luque, L et al., [ ] | 2021 | Survey | Χ | ||||||
35 | Wilson, A et al., [ ] | 2021 | Survey | Χ | ||||||
36 | Ziadlou, D [ ] | 2021 | Survey | US health care leaders | Qualitative analysis | Χ | Χ | |||
37 | Oh, SS et al., [ ] | 2021 | Survey | Χ | Χ | |||||
38 | Knitza, J et al., [ ] | 2021 | Survey | Χ | ||||||
39 | Sergi, D et al., [ ] | 2021 | Survey | Χ | ||||||
40 | Rosalia, RA et al., [ ] | 2021 | Case Study | Χ | ||||||
41 | [Anonymous] [ ] | 2021 | Survey | Χ | ||||||
42 | Prisyazhnaya, NV et al., [ ] | 2021 | Survey | Χ | ||||||
43 | Odone, A et al. [ ] | 2021 | Case Study | Variety of participants | Qualitative and quantitative analysis | Χ | ||||
44 | Balta, M et al., [ ] | 2021 | Case Study | Χ | Χ | |||||
45 | Mues, S et al., [ ] | 2021 | Survey | Χ | ||||||
46 | Frick, NRJ et al., [ ] | 2021 | Case Study | Physicians (nine female and seven male experts) | Thematic analysis | Χ | ||||
47 | Dendere, R et al., [ ] | 2021 | Survey | Χ | ||||||
48 | Neumann, M et al., [ ] | 2021 | Survey | The dean or the most senior academic individual responsible for the medical curriculum development | Descriptive statistics in Microsoft Excel (Version 16.38) | Χ | ||||
49 | Su, Y et al., [ ] | 2021 | Case Study | Χ | ||||||
50 | Masuda, Y et al., [ ] | 2021 | Survey | Χ | ||||||
51 | Frennert, S [ ] | 2021 | Survey | Χ | Χ | |||||
52 | Hasselgren, A et al., [ ] | 2021 | Survey | Χ | Χ | |||||
53 | Kim, HK et al., [ ] | 2021 | Survey | Χ | Χ | |||||
54 | Marchant, G et al., [ ] | 2021 | Survey | 569 adults | Statistical analysis | Χ | ||||
55 | Malfatti, G et al., [ ] | 2021 | Survey | Χ | ||||||
56 | Krasuska, M et al., [ ] | 2021 | Case Study | 628 interviews, observed 190 meetings and analysed 499 documents | Thematical analysis | Χ | ||||
57 | Piccialli, F et al., [ ] | 2021 | Survey | Χ | ||||||
58 | Kyllingstad, N et al., [ ] | 2021 | Survey | Χ | ||||||
59 | Frasquilho, D et al., [ ] | 2021 | Case Study | Χ | ||||||
60 | Leone, D et al., [ ] | 2021 | Case Study | Χ | ||||||
61 | Kwon, IWG et al., [ ] | 2021 | Report | Χ | ||||||
62 | Sim, SS et al., [ ] | 2021 | Systematic Literature Review | Χ | ||||||
63 | Christie, HL et al., [ ] | 2021 | Case Study | Experts (n = 483) in the fields of e-health, dementia, and caregiving were contacted via email | Qualitative analysis | Χ | ||||
64 | Eberle, C et al., [ ] | 2021 | Survey | 2887 patients | Qualitative analysis | Χ | ||||
65 | Popkova, EG et al., [ ] | 2021 | Survey | Χ | ||||||
66 | Reich, C et al., [ ] | 2021 | Survey | Χ | ||||||
67 | Hanrieder, T et al., [ ] | 2021 | Survey | Χ | ||||||
68 | Aleksashina, AA et al., [ ] | 2021 | Survey | Χ | Χ | |||||
69 | Haase, CB et al., [ ] | 2021 | Survey | Χ | ||||||
70 | Mishra, A et al., [ ] | 2021 | Survey | Χ | ||||||
71 | Kokshagina, O [ ] | 2021 | Survey | Χ | ||||||
72 | Loch, T et al., [ ] | 2021 | Survey | Χ | ||||||
73 | Cajander, A et al., [ ] | 2021 | Survey | 17 interviews with nurses ( = 9) and physicians ( = 8) | Thematical analysis | Χ | Χ | |||
74 | Botrugno, C [ ] | 2021 | Survey | Χ | ||||||
75 | Jacquemard, T et al., [ ] | 2021 | Survey | Χ | ||||||
76 | Behnke, M et al., [ ] | 2021 | Survey | Χ | ||||||
77 | Peltoniemi, T et al., [ ] | 2021 | Case Study | Χ | ||||||
78 | Glock, H et al., [ ] | 2021 | Survey | Χ | ||||||
79 | Weitzel, EC et al., [ ] | 2021 | Survey | Χ | ||||||
80 | Sullivan, C et al., [ ] | 2021 | Case Study | Χ | ||||||
81 | Luca, MM et al., [ ] | 2021 | Survey | Χ | ||||||
82 | Negro-Calduch, E et al., [ ] | 2021 | Systematic Literature Review | Χ | ||||||
83 | Werutsky, G et al.,Denninghoff, V et al., [ ] | 2021 | Survey | Χ | ||||||
84 | Piasecki, J et al., [ ] | 2021 | Survey | Χ | Χ | |||||
85 | Broenneke, JB et al., [ ] | 2021 | Survey | Χ | ||||||
86 | Faure, S et al., [ ] | 2021 | Survey | Χ | ||||||
87 | Ghaleb, EAA et al., [ ] | 2021 | Survey | Χ | Χ | |||||
88 | Verket, M et al., [ ] | 2021 | Survey | Χ | ||||||
89 | Lenz, S [ ] | 2021 | Survey | 15 interviews with persons from different areas of digital health care | Theoretical sampling | Χ | ||||
90 | De Sutter, E et al., [ ] | 2021 | Survey | 31 healthcare professionals active | Qualitative analysis | Χ | ||||
91 | Gevko, V et al., [ ] | 2021 | Survey | Χ | ||||||
92 | El Majdoubi, D et al., [ ] | 2021 | Survey | Χ | ||||||
93 | Thakur, A et al., [ ] | 2021 | Case Study | Χ | ||||||
94 | Persson, J et al., [ ] | 2021 | Survey | Χ | ||||||
95 | Zippel-Schultz, B et al., [ ] | 2021 | Survey | 49 patients and 33 of their informal caregivers. | Qualitative analysis | Χ | ||||
96 | Lam, K et al., [ ] | 2021 | Survey | Χ | ||||||
97 | Manzeschke, A [ ] | 2021 | Survey | Χ | ||||||
98 | Dyda, A et al., [ ] | 2021 | Case Study | Χ | Χ | |||||
99 | Beckmann, M et al., [ ] | 2021 | Case Study | Variety of participants | Qualitative and quantitative analysis | Χ | ||||
100 | Numair, T et al., [ ] | 2021 | Survey | Kenya: Interviewees included nurses, community health workers, and operators hired exclusively for data entry in the WIRE system. Laos: As no operators were hired in Lao PDR, interviewees included nurses, doctors, and midwives who used the WIRE system daily. (20 healthcare workers in Kenya & Laos PDR) | Qualitative and quantitative analysis | Χ | ||||
101 | Xiroudaki, S et al., [ ] | 2021 | Case Study | Χ | ||||||
102 | Droste, W et al., [ ] | 2021 | Survey | Χ | ||||||
103 | Lee, JY et al., [ ] | 2021 | Systematic Literature Review | Χ | ||||||
104 | Giovagnoli, et al., [ ] | 2021 | Survey | Χ | ||||||
105 | Daguenet, et al., [ ] | 2021 | Survey | Χ | ||||||
106 | Hubmann, et al., [ ] | 2021 | Survey | Χ | ||||||
107 | Vikhrov, et al., [ ] | 2021 | Survey | Χ | ||||||
108 | Jahn, HK et al., [ ] | 2021 | Survey | 198 complete and 45 incomplete survey responses from physicians | Statistical analysis | Χ | ||||
109 | Low et al., [ ] | 2021 | Survey | Χ | ||||||
110 | Levasluoto, et al., [ ] | 2021 | Case Study | 23 interviews | Thematical analysis | Χ | ||||
111 | Verma, et al., [ ] | 2021 | Survey | Χ | ||||||
112 | Leung, PPL et al., [ ] | 2021 | Case Study | Χ | ||||||
113 | Weber, S et al., [ ] | 2021 | Survey | Χ | ||||||
114 | Hogervorst, S et al., [ ] | 2021 | Survey | Patients (11), group HCPs (5 + 6), interviews HCPs (4) | Thematical analysis | Χ | ||||
115 | Khan, ich et al., [ ] | 2021 | Systematic Literature Review | Χ | ||||||
116 | Cherif, et al., [ ] | 2021 | Survey | Χ | ||||||
117 | Bingham, et al., [ ] | 2021 | Survey | 19 registered nurses | Descriptive statistics | Χ | ||||
118 | Broich, et al., [ ] | 2021 | Survey | Χ | ||||||
119 | Klemme, et al., [ ] | 2021 | Survey | The study consisted of 15 semi-structured interviews with academic staff ( = 7 professors and postdoctoral researchers, three female, four male) in the field of intelligent systems and technology in healthcare and staff at practice partners ( = 8 heads of department, two female, six male) in healthcare technology and economy (a hospital, a digital innovation and engineering company and a manufacturer of household appliances) and social institutions (foundations and aid organisations for people with disabilities). | Qualitative analysis | Χ | Χ | |||
120 | Dillenseger, et al., [ ] | 2021 | Survey | Χ | ||||||
121 | Wangler, et al., [ ] | 2021 | Survey | Χ | ||||||
122 | Kuhn, et al., [ ] | 2021 | Survey | Students (35) | Qualitative analysis | Χ | ||||
123 | Aldekhyyel, et al., [ ] | 2021 | Survey | Χ | ||||||
124 | Christlein, et al., [ ] | 2021 | Survey | Χ | ||||||
125 | Bergier, et al., [ ] | 2021 | Survey | Χ | ||||||
126 | Sitges-Macia, et al., [ ] | 2021 | Survey | Χ | ||||||
127 | Rani, et al., [ ] | 2021 | Survey | Χ | ||||||
128 | Fredriksen, et al., [ ] | 2021 | Case Study | Healthcare employees from a volunteer centre and from municipality healthcare units in three municipalities | Qualitative analysis | Χ | ||||
129 | Caixeta, et al., [ ] | 2021 | Survey | Χ | ||||||
130 | Gupta, et al., [ ] | 2021 | Survey | Χ | ||||||
131 | Dobson, et al., [ ] | 2021 | Survey | Χ | ||||||
132 | Choi, K et al., [ ] | 2021 | Survey | Χ | ||||||
133 | Muller-Wirtz, et al., [ ] | 2021 | Case Study | Χ | ||||||
134 | Sembekov, et al., [ ] | 2021 | Survey | Χ | ||||||
135 | Aulenkamp, et al., [ ] | 2021 | Survey | Χ | Χ | |||||
136 | Paul, et al., [ ] | 2021 | Survey | 16 key stakeholders | Thematical analysis | Χ | ||||
137 | Lemmen, et al., [ ] | 2021 | Survey | 62 citizens and 13 patients | Qualitative analysis | Χ | ||||
138 | Golz, et al., [ ] | 2021 | Survey | Χ | ||||||
139 | Tarikere, et al., [ ] | 2021 | Survey | Χ | ||||||
140 | Li, et al., [ ] | 2021 | Case Study | Χ | ||||||
141 | Rouge-Bugat, et al., [ ] | 2021 | Case Study | Χ | ||||||
142 | Iodice, et al., [ ] | 2021 | Survey | Χ | ||||||
143 | Kulzer, B [ ] | 2021 | Survey | Χ | ||||||
144 | Khosla, et al., [ ] | 2021 | Survey | Χ | ||||||
145 | Dantas, et al., [ ] | 2021 | Survey | Χ | ||||||
146 | Gaur, et al., [ ] | 2021 | Survey | Χ | ||||||
147 | Khodadad-Saryazdi, A [ ] | 2021 | Case Study | Χ | Χ | Χ | ||||
148 | Bellavista, et al., [ ] | 2021 | Case Study | Χ | ||||||
149 | Laukka, et al., [ ] | 2021 | Case Study | Χ | Χ | |||||
150 | Singh, et al., [ ] | 2021 | Survey | Χ | ||||||
151 | Patalano, et al., [ ] | 2021 | Survey | Χ | ||||||
152 | Mantel-Teeuwisse, et al., [ ] | 2021 | Survey | Χ | ||||||
153 | Mues, et al., [ ] | 2021 | Survey | Χ | ||||||
154 | Bosch-Capblanch, et al., [ ] | 2021 | Survey | Χ | ||||||
155 | Jaboyedoff, et al., [ ] | 2021 | Survey | 336 common data elements (CDEs) | Qualitative analysis | Χ | ||||
156 | Nadhamuni, et al., [ ] | 2021 | Survey | Χ | ||||||
157 | Hertling, et al., [ ] | 2021 | Survey | Χ | ||||||
158 | Khan, et al., [ ] | 2021 | Survey | Χ | ||||||
159 | Mun, et al., [ ] | 2021 | Survey | Χ | Χ | |||||
160 | Xi, et al., [ ] | 2021 | Survey | Χ | ||||||
161 | Weichert, et al., M [ ] | 2021 | Survey | Χ | ||||||
162 | Liang, et al., [ ] | 2021 | Survey | Χ | ||||||
163 | Williams, et al., [ ] | 2021 | Survey | 508 interviews, 163 observed meetings, and analysis of 325 documents. | Qualitative analysis—Sociotechnical principles, combining deductive and inductive methods | Χ | ||||
164 | Feroz, et al., [ ] | 2021 | Case Study | Χ | ||||||
165 | Huser, et al., [ ] | 2021 | Case Study | Χ | ||||||
166 | Apostolos, K [ ] | 2021 | Survey | Χ | ||||||
167 | Simsek, et al., [ ] | 2021 | Survey | Χ | Χ | |||||
168 | Khamisy-Farah, et al., [ ] | 2021 | Survey | Χ | ||||||
169 | Egarter, et al., [ ] | 2021 | Case Study | Χ | ||||||
170 | Can, et al., [ ] | 2021 | Survey | Χ | ||||||
171 | Sung, et al., [ ] | 2021 | Survey | 278 e-logbook database entries and 379 procedures in the hospital records from 14 users were analysed. Interviews with 12 e-logbook users found overall satisfaction. | Statistical analysis | Χ | Χ | |||
172 | Zoellner, et al., [ ] | 2021 | Survey | Χ | ||||||
173 | Oliveira, et al., [ ] | 2021 | Case Study | Recipients numbering 151 (21% of the universe) completed the questionnaire: trade (49), industry (41), services (28), health (15), and education (18). | Quantitative analysis | Χ | ||||
174 | Goudarzi, et al., [ ] | 2021 | Survey | Χ | ||||||
175 | Li, et al., [ ] | 2021 | Survey | Χ | Χ | |||||
176 | Klimanov, et al., [ ] | 2021 | Case Study | Χ | ||||||
177 | Nadav, et al., [ ] | 2021 | Survey | Eight focus group interviews were conducted with 30 health and social care professionals | Qualitative analysis | Χ | ||||
178 | Spanakis, et al., [ ] | 2021 | Survey | Χ | ||||||
179 | Polyakov, et al., [ ] | 2021 | Survey | Χ | ||||||
180 | Fristedt, et al., [ ] | 2021 | Survey | Intervention group ( = 80) & control group ( = 80) | Data will be coded and manually entered in SPSS | Χ | ||||
181 | Mandal, et al., [ ] | 2021 | Survey | Χ | ||||||
182 | Ozdemir, V [ ] | 2021 | Survey | Χ | ||||||
183 | Eberle, et al., [ ] | 2021 | Survey | Χ | ||||||
184 | Iakovleva, et al., [ ] | 2021 | Case Study | Χ | ||||||
185 | von Solodkoff, et al., [ ] | 2021 | Survey | In the questionnaire, the participants ( = 217). A total of 27 subjects (mean age 51 years, min: 23 years, max: 86 years) participated in the interviews. | Statistical analysis | Χ | ||||
186 | Khuntia, et al., [ ] | 2021 | Survey | Χ | Χ | |||||
187 | Ochoa, et al., [ ] | 2021 | Survey | Χ | ||||||
188 | Masłoń-Oracz, et al., [ ] | 2021 | Case Study | X | X | |||||
189 | Abrahams, et al., [ ] | 2020 | Survey | X | X | |||||
190 | Agnihothri, et al., [ ] | 2020 | Survey | X | ||||||
191 | Bukowski, et al., [ ] | 2020 | Survey | X | X | |||||
192 | Chiang, et al., [ ] | 2020 | Survey | X | X | |||||
193 | Cobelli, et al., [ ] | 2020 | Survey | Pharmacists (82) | Qualitative content analysis | X | ||||
194 | Crawford, et al., [ ] | 2020 | Survey | X | X | |||||
195 | Gjellebæk, et al., [ ] | 2020 | Case Study | Employees and middle managers | Thematic analysis | X | ||||
196 | Nascimento, et al., [ ] | 2020 | Case Study | X | ||||||
197 | Geiger, et al., [ ] | 2020 | Case Study | Specialist in neurosurery & resident (296) | Statistical Analysis | X | X | |||
198 | Eden, et al., [ ] | 2020 | Survey | Medical, nursing, allied health, administrative and executive roles (92) | Analysis of Cohen’s kappa (k) | X | X | |||
199 | Gochhait, et al., [ ] | 2020 | Case Study | X | X | |||||
200 | Kernebeck, et al., [ ] | 2020 | Case Study | X | ||||||
201 | Klinker, et al., [ ] | 2020 | Survey | Staff of health care facilities (14) | Microsoft HoloLens, Vuzix m100 | X | ||||
202 | Krasuska, et al., M.; Williams, R.; Sheikh, A.; Franklin, B. D.; Heeney, C.; Lane, W.; Mozaffar, H.; Mason, K.; Eason, et al., [ ] | 2020 | Survey | Staff of health care facilities (113) | Qualitative analysis | X | ||||
203 | Leigh, et al., [ ] | 2020 | Survey | X | ||||||
204 | Minssen, et al., [ ] | 2020 | Survey | X | ||||||
205 | Mueller, et al., [ ] | 2020 | Case Study | Staff of health care facilities (20) | Qualitative analysis | X | X | |||
206 | Nadarzynski, et al., [ ] | 2020 | Case Study | Patients (257) | Statistical analysis | X | X | |||
207 | Pekkarinen, et al., [ ] | 2020 | Case Study | Variety of participants (24) | The analytical framework is based on Nardi and O’Day’s five components of information ecology: system, diversity, co-evolution, keystone species, and locality. | X | ||||
208 | Rajamäki, et al., [ ] | 2020 | Survey | X | ||||||
209 | Salamah, et al., [ ] | 2020 | Case Study | X | ||||||
210 | Stephanie, et al., [ ] | 2020 | Survey | X | ||||||
211 | Sultana, et al., [ ] | 2020 | Survey | X | X | |||||
212 | Visconti, et al., [ ] | 2020 | Case Study | X | ||||||
213 | Yousaf et al., [ ] | 2020 | Case Study | X | ||||||
214 | Asthana, et al., [ ] | 2019 | Survey | X | ||||||
215 | Astruc, B. [ ] | 2019 | Case Study | X | X | |||||
216 | Baltaxe, et al., [ ] | 2019 | Report | X | ||||||
217 | Caumanns, J. [ ] | 2019 | Case Study | X | ||||||
218 | Diamantopoulos, et al., [ ] | 2019 | Case Study | X | X | |||||
219 | Diviani, et al., [ ] | 2019 | Survey | Variety of participants (165) | Qualitative analysis | X | ||||
220 | EYGM [ ] | 2019 | Survey | X | ||||||
221 | Hatzivasilis, et al., [ ] | 2019 | Survey | X | ||||||
222 | Go Jefferies, et al., [ ] | 2019 | Case Study | X | X | |||||
223 | Kivimaa, P., et al., [ ] | 2019 | Systematic Literature Review | X | ||||||
224 | Klocek, A., et al., [ ] | 2019 | Case Study | Variety of people (153) | Statistical analysis | X | ||||
225 | Kohl, S., et al., [ ] | 2019 | Survey | X | ||||||
226 | Kouroubali, et al., [ ] | 2019 | Case Study | X | X | |||||
227 | Manard, et al., [ ] | 2019 | Case Study | X | ||||||
228 | Mende M. [ ] | 2019 | Survey | X | ||||||
229 | Mishra et al., [ ] | 2019 | Systematic Literature Review | X | X | X | ||||
230 | Niemelä, et al., [ ] | 2019 | Survey | Health professionals, child patients’ parents, and the healthcare industry | Systematically analysed according to the process structure (pre-, intra-, post-surgery, and home care). | X | ||||
231 | Nittas, V., et al. [ ] | 2019 | Survey | X | ||||||
232 | Noor, A. [ ] | 2019 | Case Study | Students and Staff in colleges and universities | Qualitative analysis | X | ||||
233 | Pape, L., et al. [ ] | 2019 | Case Study | X | ||||||
234 | Patrício, et al., [ ] | 2019 | Survey | X | ||||||
235 | Russo Spena, T., Cristina, M. [ ] | 2019 | Survey | X | ||||||
236 | Rydenfält, C., et al., [ ] | 2019 | Case Study | Variety of people (264) | NVivo 10 (QSR International, Melbourne, Australia) | X | ||||
237 | Savikko, et al., [ ] | 2019 | Case Study | X | ||||||
238 | Vial, G [ ] | 2019 | Systematic Literature Review | X | ||||||
239 | Wangdahl, J.M., et al., [ ] | 2019 | Case Study | Variety of people (600) | Binary logistic regression analysis | X | ||||
240 | Watson, et al., [ ] | 2019 | Systematic Literature Review | X | ||||||
241 | Weigand, et al., [ ] | 2019 | Survey | X | ||||||
242 | Zanutto, A. [ ] | 2019 | Survey | Staff of health care facilities (6836) | Qualitative analysis | X | ||||
243 | Eden, et al., [ ] | 2018 | Systematic Literature Review | X | ||||||
244 | Goh, W., et al. [ ] | 2018 | Survey | X | ||||||
245 | Kayser, L., et al., [ ] | 2018 | Survey | X | ||||||
246 | Poss-Doering, R. et al., [ ] | 2018 | Case Study | Patients (11) & Doctors (3) | Statistical analysis | X | X | X | ||
247 | Khatoon, et al., [ ] | 2018 | Survey | X | X | |||||
248 | Melchiorre, M.G., et al., [ ] | 2018 | Case Study | X | ||||||
249 | Ngwenyama, et al., [ ] | 2018 | Survey | X | ||||||
250 | Öberg, U.A.-O., et al., [ ] | 2018 | Survey | Primary healthcare nurses (20) | Qualitative analysis | X | ||||
251 | Parkin, et al., [ ] | 2018 | Report | X | ||||||
252 | Tuzii, J., [ ] | 2018 | Case Study | X | ||||||
253 | Brockes, C., et al., [ ] | 2017 | Survey | Students (28) | Mann–Whitney U-Test | X | X | |||
254 | Cavusoglu, et al., [ ] | 2017 | Survey | X | ||||||
255 | Cerdan, et al., [ ] | 2017 | Case Study | Patients (29) | Qualitative analysis | X | ||||
256 | Coppolino, et al., [ ] | 2017 | Survey | X | ||||||
257 | Geiger, et al., [ ] | 2017 | Survey | X | ||||||
258 | Giacosa, et al., [ ] | 2017 | Survey | X | ||||||
259 | Hong, et al., [ ] | 2017 | Survey | X | ||||||
260 | Hüsers, J., et al., [ ] | 2017 | Case Study | Nurses (534) | All data were analysed using R (Version 3.2.1) | X | ||||
261 | Parviainen, et al., [ ] | 2017 | Survey | X | ||||||
262 | Paulin, A. [ ] | 2017 | Survey | X | ||||||
263 | Schobel, J., et al. [ ] | 2017 | Survey | X | ||||||
264 | Seddon, et al., [ ] | 2017 | Survey | X | ||||||
265 | Thorseng, et al., [ ] | 2017 | Survey | Variety of participants | Qualitative analysis | X | ||||
266 | Tuzii, J. [ ] | 2017 | Case Study | X | ||||||
267 | Amato, F., et al., [ ] | 2016 | Survey | X | ||||||
268 | Bongaerts, et al., [ ] | 2016 | Survey | X | ||||||
269 | Cucciniello, et al., [ ] | 2016 | Survey | X | ||||||
270 | Evans, R.S. [ ] | 2016 | Survey | X | ||||||
271 | Faried, et al., [ ] | 2016 | Report | X | ||||||
272 | Harjumaa, M., et al., [ ] | 2016 | Survey | Various organisations (12) | Interview data was then analysed thematically. | X | ||||
273 | Mattsson, T., [ ] | 2016 | Case Study | X | ||||||
274 | Mazor, et al., [ ] | 2016 | Survey | X | ||||||
275 | Anwar, et al., [ ] | 2015 | Survey | X | X | |||||
276 | Kostkova, P., [ ] | 2015 | Survey | X | ||||||
277 | Laur, A., [ ] | 2015 | Survey | X | ||||||
278 | Sultan, N., [ ] | 2015 | Survey | X | X | |||||
279 | Nudurupati, et al., [ ] | 2015 | Survey | X | ||||||
280 | Sanders, K., et al., [ ] | 2015 | Survey | Healthcare professionals (17) | Qualitative analysis | X | ||||
281 | Cook, et al., [ ] | 2012 | A Systematic Literature Review | X | ||||||
282 | Khan, et al., [ ] | 2012 | Survey | X | ||||||
283 | Agarwal, R., et al., [ ] | 2010 | Survey | X | ||||||
284 | Thomas, et al., [ ] | 2009 | Case Study | X | ||||||
285 | Buccoliero, et al., [ ] | 2008 | Survey | X | ||||||
286 | Hikmet, et al., [ ] | 2008 | Case Study | Variety of participants | Quantitive analysis | X | ||||
287 | Zdravković, S. [ ] | 2008 | Survey | Χ | X |
From the articles included in the present study between 2008 and 2021, they were grouped into five categories identified: (i) information technology in health, (ii) acceptance of e-health, (iii) telemedicine, (iv) security of e-health, and (v) education impact of e-health.
Researchers have studied several factors to maximise the effectiveness and success of adopting new technology to benefit patients. Hospitals can benefit from information technology when designing or modifying new service procedures. Health units can use information and communication technology applications to analyse and identify patients’ needs and preferences, enhancing their service innovation processes. Previous findings conclude that technological capability positively influences patient service and innovation in the service process [ 301 ]. These results have significant management implications as managers seek to increase technology resources’ efficiency to achieve patient-centred care as the cornerstone of medical practice [ 207 ].
Informatics facilitates the exchange of knowledge necessary for creating ideas and the development process. The internet supports health organisations in developing and distributing their services more efficiently [ 206 ]. Also, Information Technology improves the quality of services, reduces costs, and helps increase patient satisfaction. As new technologies have created opportunities for companies developing high-tech services, healthcare units can increase customer value, personalise services and adapt to their patient’s needs [ 209 ]. To this end, the “smart hospitals” should represent the latest investment frontiers impacting healthcare. Their technological characteristics are so advanced that the public authorities need know-how for their conception, construction, and operation [ 228 ].
A new example is reshaping global healthcare services in their infancy, emphasising the transition from sporadic acute healthcare to continuous and comprehensive healthcare. This approach is further refined by “anytime and everywhere access to safe eHealth services.” Recent developments in eHealth, digital transformation and remote data interchange, mobile communication, and medical technology are driving this new paradigm. Follow-up and timely intervention, comprehensive care, self-care, and social support are four added features in providing health care anywhere and anytime [ 289 ]. However, the healthcare sector’s already precarious security and privacy conditions are expected to be exacerbated in this new example due to the much greater monitoring, collection, storage, exchange, and retrieval of patient information and the cooperation required between different users, institutions, and systems.
The use of mobile telephony technologies to support health goals contributes to the transformation of healthcare benefits worldwide. The same goes for small and medium-sized healthcare companies, such as pharmacies. A potent combination of factors between companies and customers is the reason for creating new relationships. In particular, mobile technology applications represent new opportunities for integrating mobile health into existing services, facilitating the continued growth of quality service management. Service-based, service-focused strategies have changed distribution patterns and the relationship between resellers and consumers in the healthcare industry, resulting in mobile health and significant pharmacy opportunities. It has been an important research topic in the last decade because it has influenced and changed traditional communication between professionals and patients [ 211 ]. An example of a mobile healthcare platform is “Thymun”, designed and developed by Salamah et al. aiming to create intelligent health communities to improve the health and well-being of autoimmune people in Indonesia [ 225 ].
In a long-term project and a population study (1999–2002), Hsu et al. evaluated e-health usage patterns [ 302 ]. The authors conclude that access to and use of e-health services are rapidly increasing. These services are more significant in people with more medical needs. Fang (2015) shows that scientific techniques can be an essential tool for revealing patterns in medical research that could not be apparent with traditional methods of reviewing the medical literature [ 303 ]. Teleradiology and telediagnosis, electronic health records, and Computer-Aided Diagnosis (CAD) are examples of digital medical technology. France is an example of a country that invests and leads in electronic health records, based on what is written by Manard S. et al. [ 243 ]. However, the impact of technological innovation is reflected in the availability of equipment and new technical services in different or specialised healthcare sectors.
On the other hand, Mariusz Duplaga (2013) argues that the expansion of e-health solutions is related to the growing demand for flexible, integrated and cost-effective models of chronic care [ 304 ]. The scope of applications that can support patients with chronic diseases is broad. In addition to accessing educational resources, patients with chronic diseases can use various electronic diaries and systems for long-term disease monitoring. Depending on the disease and the symptoms, the devices used to assess the patient’s condition vary. However, the need to report symptoms and measurements remains the same. According to Duplaga, the success of treatments depends on the patient’s involvement in monitoring and managing the disease. The emphasis on the role of the patient is parallel to the general tendency of people and patients to participate in decisions made about their health. Involving patients in monitoring their symptoms leads to improved awareness and ability to manage diseases. Duplaga argues that the widespread use of e-health systems depends on several factors, including the acceptance and ability to use information technology tools, combined with an understanding of disease and treatment.
Sumedha Chauhan & Mahadeo Jaiswal (2017) are on the same wavelength. They claim that e-health applications provide tools, processes and communication systems to support e-health practices [ 305 ]. These applications enable the transmission and management of information related to health care and thus contribute to improving patient’s health and physicians’ performance. The human element plays a critical role in the use of e-health, according to the authors. In addition, researchers have studied the acceptance of e-health applications among patients and the general public, as they use services such as home care and search for information online. The meta-analysis they use combines and analyzes quantitative findings of multiple empirical studies providing essential knowledge. However, the reason for their research was the study of Holden and Karsh (2010) [ 306 ].
To provide a comprehensive view of the literature acceptance of e-health applications, Holden and Karsh reviewed 16 studies based on healthcare technology acceptance models [ 306 ]. Findings show them that the use and acceptance of technological medical solutions bring improvements but can be adopted by those involved in the medical field.
On the other hand, telemedicine is considered one of the most important innovations in health services, not only from a technological but also from a cultural and social point of view. It benefits the accessibility of healthcare services and organisational efficiency [ 215 ]. Its role is to meet the challenges posed by the socio-economic change in the 21st century (higher demands for health care, ageing population, increased mobility of citizens, need to manage large volumes of information, global competitiveness, and improved health care provision) in an environment with limited budgets and costs. Nevertheless, there are significant obstacles to its standardisation and complete consolidation and expansion [ 300 ].
At present, there are Telemedicine centres that mediate between the patient and the hospital or doctor. However, many factors make this communication impossible [ 300 ]. Such factors include equipment costs, connectivity problems, the patient’s trust or belief in the system or centre that applies telemedicine, and resistance to new and modern diagnostics, especially in rural and island areas. Therefore, telemedicine would make it easier to provide healthcare systems in remote areas than having a specialist in all the country’s remote regions [ 300 ]. Analysing the concept further, one can easily argue that the pros outweigh the disadvantages. Therefore, telemedicine must be adopted in a concerted effort to resolve all the obstacles we are currently facing. Telemedicine centres and services such as teleradiology, teledermatology, teleneurology, and telemonitoring will soon be included. This means that a few years from now, the patient will not have to go to a central hospital and can benefit remotely from the increased quality of health services. This will save valuable time, make good use of available resources, save patient costs, and adequately develop existing and new infrastructure.
In 2007, the World Health Organisation adopted the following broad description of telemedicine: “The delivery of health care services, where distance is a critical factor, by all health care professionals using information and communication technologies for the exchange of valid information for the diagnosis, treatment and prevention of disease and injuries, research and evaluation, and for the continuing education of health care providers, all in the interests of advancing the health of individuals and their communities ” [ 307 ]
According to the Wayback Machine, Canadian Telehealth Forum, other terms similar to telemedicine are telehealth and e-health, which are used as broader concepts of remote medical therapy. It is appropriate to clarify that telemedicine refers to providing clinical services. In contrast, telehealth refers to clinical and non-clinical services, including education, management and research in medical science. On the other hand, the term eHealth, most commonly used in the Americas and Europe, consists of telehealth and other elements of medicine that use information technology, according to the American Telemedicine Association [ 308 ].
The American Telemedicine Association divides telemedicine into three categories: storage-promotion, remote monitoring, and interactive services. The first category includes medical data, such as medical photographs, cardiograms, etc., which are transferred through new technologies to the specialist doctor to assess the patient’s condition and suggest the appropriate medication. Remote monitoring allows remote observation of the patient. This method is used mainly for chronic diseases like heart disease, asthma, diabetes, etc. Its interactive services enable direct communication between the patient and the treating doctor [ 309 ].
Telemedicine is a valuable and efficient tool for people living or working in remote areas. Its usefulness lies in the health access it provides to patients. In addition, it can be used as an educational tool for learning students and medical staff [ 310 ].
Telemedicine is an open and constantly evolving science, as it incorporates new technological developments and responds to and adapts to the necessary health changes within societies.
According to J.J. Moffatt, the most common obstacles to the spread of telemedicine are found in the high cost of equipment, the required technical training of staff and the estimated time of a meeting with the doctor, which can often be longer than the use of a standard doctor [ 311 ]. On the other hand, the World Health Organisation states that telemedicine offers excellent potential for reducing the variability of diagnoses and improving clinical management and the provision of health care services worldwide. The World Health Organisation claims, according to Craig et al. and Heinzelmann PJ, that telemedicine improves access, quality, efficiency and cost-effectiveness [ 312 , 313 ]. In particular, telemedicine can help traditionally under-served communities by overcoming barriers to the distance between healthcare providers and patients [ 314 ]. In addition, Jennett PA et al. highlight significant socio-economic benefits for patients, families, health professionals and the health system, including improved patient-provider communication and educational opportunities [ 315 ].
On the other hand, Wootton R. argues that telemedicine applications have achieved different levels of success. In both industrial and developing countries, telemedicine has yet to be used consistently in the healthcare system, and few pilot projects have been able to be maintained after the end of their initial funding [ 316 ].
However, many challenges are regularly mentioned and responsible for the need for more longevity in many efforts to adopt telemedicine. One such challenge is the complexity of human and cultural factors. Some patients and healthcare workers resist adopting healthcare models that differ from traditional approaches or home practices. In contrast, others need to have the appropriate educational background in Information and Communication Technologies to make effective use of telemedicine approaches [ 314 ]. The need for studies documenting telemedicine applications’ economic benefits and cost-effectiveness is also a challenge. Strong business acumen to persuade policymakers to embrace and invest in telemedicine has contributed to a need for more infrastructure and program funding [ 312 ]. Legal issues are also significant obstacles to the adoption of telemedicine. These include the need for an international legal framework that allows health professionals to provide services in different jurisdictions and countries. Furthermore, the lack of policies governing data confidentiality, authentication and the risk of medical liability for health professionals providing telemedicine services [ 314 ]. In any case, the technological challenges are related to legal issues. In addition, the systems used are complex, and there is a possibility of malfunction, which could cause software or hardware failure. The result is an increase in patient morbidity or mortality as well as the liability of healthcare providers [ 317 ].
According to Stanberry B., to overcome these challenges, telemedicine must be regulated by definitive and comprehensive guidelines, which are ideally and widely applied worldwide [ 318 ]. At the same time, legislation must be enacted governing health confidentiality, data access, and providers’ responsibility [ 314 ].
The possibility of the patients looking at the electronic patient folder in a cloud environment, through mobile devices anytime and anywhere, is significant. On the one hand, the advantages of cloud computing are essential, and on the other hand, a security mechanism is critical to ensure the confidentiality of this environment. Five methods are used to protect data in such environments: (1) users must encrypt the information before storing it; (2) users must transmit information through secure channels; (3) the user ID must be verified before accessing data; (4) the information is divided into small portions for handling and storage, retrieved when necessary; (5) digital signatures are added to verify that a suitable person has created the file to which a user has access. On the other hand, users of these environments will implement self-encryption to protect data and reduce over-reliance on providers [ 210 ].
At the same time, Maliha S. et al. [ 227 ] proposed the blockchain to preserve sensitive medical information. This technology ensures data integrity by maintaining a trace of control over each transaction. At the same time, zero trusts provide that medical data is encrypted and that only certified users and devices interact with the network. In this way, this model solves many vulnerabilities related to data security [ 227 ]. Another alternative approach is the KONFIDO project, which aims at the safe cross-border exchange of health data. A European H2020 project aims to address security issues through a holistic example at the system level. The project combines various cutting-edge technologies in its toolbox (such as blockchain, photonic Physical Unclonable Functions, homomorphic encryption, and trusted execution) [ 234 ]. Finally, Coppolino L. et al. [ 271 ] proposed using a SIEM framework for an e-healthcare portal developed under the Italian National eHealth Net Program. This framework allows real-time monitoring of access to the portal to identify potential threats and anomalies that could cause significant security issues [ 271 ].
But all this would only be feasible with the necessary education of both users and patients [ 11 ]. As the volume and quality of evidence in medical education continue to expand, the need for evidence synthesis will increase [ 295 ]. On the other hand, Brockers C. et al. argued that digitalisation changes jobs and significantly impacts medical work. The quality of medical data provided for support depends on telemedicine’s medical specialisation and knowledge. Adjustments to primary and further education are inevitable because physicians are well trained to support their patients satisfactorily and confidently in the increasingly complex digitalisation of healthcare. The ultimate goal of the educational community is the closest approach of students to the issues of telemedicine and e-health, the creation of a spirit of trust, and the acceptance and transmission of essential knowledge [ 268 ].
Noor also moved in this direction, seeking to discover the gaps in Saudi education for digital transformation in health [ 248 ]. The growing complexity of healthcare systems worldwide and the growing reliance of the medical profession on information technology for precise practices and treatments require specific standardised training in Information Technology (IT) health planning. Accreditation of core Information Technology (IT) is advancing internationally. Noor A. examined the state of Information Technology health programmes in the Kingdom of Saudi Arabia (KSA) to determine (1) how well international standards are met and (2) what further development is required in the light of recent initiatives of the Kingdom of Saudi Arabia on e-health [ 248 ]. Of the 109 institutions that participated in his research, only a few offered programmes specifically in Health Information Technology. As part of Saudi Vision 2030, Saudi digital transformation was deemed an urgent need. This initiative calls for applying internationally accepted Information Technology skills in education programmes and healthcare practices, which can only happen through greater collaboration between medical and technology educators and strategic partnerships with companies, medical centres and government agencies.
Another study by Diviani N. et al. adds to the knowledge of e-health education, demonstrating how online health information affects a person’s overall behaviour and enhances patients’ ability to understand, live and prepare for various health challenges. The increasing digitalisation of communication and healthcare requires further research into the digital divide and patients’ relationships with health professionals. Healthcare professionals must recognise the online information they seek and engage with patients to evaluate online health information and support joint healthcare-making [ 235 ].
The selected studies comprise a conceptual model based on bibliographic research. Using an open-ended technique, we analyse the selected 287 articles, which are grouped into categories based on their context. This methodology provides readers with a good indication of issues concerning the timeliness of health digitalisation. A limitation of the methodology is that selected criteria of the method might be subjective in terms of the search terms and how the papers are selected. The articles indicate that this field is initial, and further research is needed. Although several articles have created a theoretical basis for corporate sustainability and strategic digital management, only limited studies provided guidelines on the strategic digital transformation process and its health implementation stages. However, studies have also developed sustainable models, software or applications in this area. This is also the reason for creating opportunities for future researchers, who will be closed to investigate this gap and improve the viability of digital health strategies. In addition, any work carried out in case studies provides fruitful results by facilitating researchers through deep penetration into sustainable digitalisation. No generalised frameworks are available to guide the wording and implementation of digital action plans. Thus, the need for quantitative or qualitative research is created, providing conclusions on the impact of internal or external factors in the sustainability process, implementation, adoption, planning, and challenges of digital health solutions in general, as well as the impact of digital transformation. Most existing studies explore the issue of digitalisation in a particular part of a nursing institution or a disease rather than the management strategy perspective. In this way, researchers ignore a debate on obstacles and problems that often face in practice during integration. Such an analysis could lead to more profound knowledge.
In conclusion, our research observed a timeless analysis of systematised studies focusing on digital health developments. These studies broaden the researchers’ vision and provide vital information for further investigation. This article focuses on understanding digitalisation in healthcare, including, for the most part, the digitalisation of information and adopting appropriate parameters for further development. To build a more holistic view of digital health transformation, there is a great need for research on the management implications of digitalisation by different stakeholders. Finally, the development of telemedicine, the further enhancement of digital security and the strengthening of technological information systems will contribute to the universal acceptance of the digital health transformation by all involved.
This research received no external funding.
Conceptualisation, A.I.S., F.K. and M.A.T.; methodology, F.K. and M.A.T.; software, A.I.S.; validation, A.I.S.; data curation, A.I.S.; writing—original draft preparation, A.I.S. and M.A.T.; writing—review and editing, A.I.S. and M.A.T.; visualisation, A.I.S.; supervision, M.A.T.; project administration, M.A.T. All authors have read and agreed to the published version of the manuscript.
Informed consent statement, data availability statement, conflicts of interest.
The authors declare no conflict of interest.
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100+ Healthcare Research Topic Ideas To Fast-Track Your Project
Finding and choosing a strong research topic is the critical first step when it comes to crafting a high-quality dissertation, thesis or research project. If you’ve landed on this post, chances are you’re looking for a healthcare-related research topic , but aren’t sure where to start. Here, we’ll explore a variety of healthcare-related research ideas and topic thought-starters across a range of healthcare fields, including allopathic and alternative medicine, dentistry, physical therapy, optometry, pharmacology and public health.
NB – This is just the start…
The topic ideation and evaluation process has multiple steps . In this post, we’ll kickstart the process by sharing some research topic ideas within the healthcare domain. This is the starting point, but to develop a well-defined research topic, you’ll need to identify a clear and convincing research gap , along with a well-justified plan of action to fill that gap.
If you’re new to the oftentimes perplexing world of research, or if this is your first time undertaking a formal academic research project, be sure to check out our free dissertation mini-course. In it, we cover the process of writing a dissertation or thesis from start to end. Be sure to also sign up for our free webinar that explores how to find a high-quality research topic.
While the ideas we’ve presented above are a decent starting point for finding a healthcare-related research topic, they are fairly generic and non-specific. So, it helps to look at actual dissertations and theses to see how this all comes together.
Below, we’ve included a selection of research projects from various healthcare-related degree programs to help refine your thinking. These are actual dissertations and theses, written as part of Master’s and PhD-level programs, so they can provide some useful insight as to what a research topic looks like in practice.
Looking at these titles, you can probably pick up that the research topics here are quite specific and narrowly-focused , compared to the generic ones presented earlier. This is an important thing to keep in mind as you develop your own research topic. That is to say, to create a top-notch research topic, you must be precise and target a specific context with specific variables of interest . In other words, you need to identify a clear, well-justified research gap.
If you’re still feeling a bit unsure about how to find a research topic for your healthcare dissertation or thesis, check out Topic Kickstarter service below.
I need topics that will match the Msc program am running in healthcare research please
Hello Mabel,
I can help you with a good topic, kindly provide your email let’s have a good discussion on this.
Can you provide some research topics and ideas on Immunology?
Thank you to create new knowledge on research problem verse research topic
Help on problem statement on teen pregnancy
This post might be useful: https://gradcoach.com/research-problem-statement/
can you provide me with a research topic on healthcare related topics to a qqi level 5 student
Please can someone help me with research topics in public health ?
Hello I have requirement of Health related latest research issue/topics for my social media speeches. If possible pls share health issues , diagnosis, treatment.
I would like a topic thought around first-line support for Gender-Based Violence for survivors or one related to prevention of Gender-Based Violence
Please can I be helped with a master’s research topic in either chemical pathology or hematology or immunology? thanks
Can u please provide me with a research topic on occupational health and safety at the health sector
Good day kindly help provide me with Ph.D. Public health topics on Reproductive and Maternal Health, interventional studies on Health Education
may you assist me with a good easy healthcare administration study topic
May you assist me in finding a research topic on nutrition,physical activity and obesity. On the impact on children
I have been racking my brain for a while on what topic will be suitable for my PhD in health informatics. I want a qualitative topic as this is my strong area.
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Since Neolithic humans fashioned the first scalpel out of stone, new machines and methods have changed the way we practice medicine and learn about the human body. Physicians moved on from those early scalpels to stethoscopes, X-rays, and MRIs, the better to understand the workings of the human body. With these new understandings has come translational research that transfers findings from the lab into new, more effective treatments and medicines. Dean Robert J. Alpern, M.D., Ensign Professor of Medicine, discussed basic science and advances in clinical care; technology and patient care; and the role of serendipity in research with Yale Medicine .
What have been some of the key inventions or discoveries that have advanced clinical care and medical research? In the past 50 to 100 years, there have been so many advances that it’s hard to rank any one above the other. Obviously, some come to mind—the discovery of the structure of DNA, recombinant DNA, electron microscopy, knockout technology. The new gene editing technology, CRISPR, is really going to transform research. It’s important to point out that the major advances in health care have been based on basic scientific findings. DNA technology and the structure of DNA were basic science findings that now drive clinical genetics. The understanding of how cells grow has transformed cancer care. Basic understandings of the immune system have led to immunotherapy for cancer.
How do physicians integrate new technologies into medicine while maintaining the doctor-patient relationship? Technology is always good for improving what physicians can do, but you run the risk that doctors won’t hone their clinical skills as well as they could because they know that the technology will end up defining the diagnosis. There needs to be a combination of the two. I don’t see technology replacing the need for outstanding clinicians. Technology should enhance clinical skills, not replace them.
How important is serendipity in scientific discovery? There are stories of serendipity, but the best investigators always appear to have good luck. The best investigators are asking the right questions, the important questions. It’s a matter of staying knowledgeable about all of the technologies, including those from other fields, and thinking about how to apply them to your field. When you ask the right question and use the right technology, serendipity falls upon you.
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Dramatic improvements in information technology have the potential to transform health-care delivery, and a key question is how such changes will affect the health-care workforce of the future. As part of the MIT Task Force on the Work of the Future’s recent series of research briefs, Research Affiliate John Van Reenen teamed with Ari Bronsoler, an MIT PhD student in economics, and Joseph Doyle, the Erwin H. Schell Professor of Management and Applied Economics, MIT Sloan School of Management, to explore the rapidly changing health-care landscape due to the greater availability and use of information and communications technology. John Van Reenen is a member of the MIT Task Force on the Work of the Future, an MIT Initiative on the Digital Economy Digital Fellow, and the Ronald Coase Chair and School Professor of the London School of Economics. The brief, “ The Impact of New Technology on the Healthcare Workforce ,” describes the evolution of employment, wages, and education across the wide variety of occupations in the health-care sector since 1980. Here, Van Reenen provides an overview of the work. Q: Can you describe what health IT is, and its benefits? A: A key recent technology is the electronic health record, or EHR. This is, at its core, a digitized medical chart. Deriving value from this technology requires a broad array of functions that gather, manage, and share digital health information. This information can then be exploited to support medical decision-making and operations. Ideally, information gathering begins before a patient encounter: retrieving records from other providers or past patient encounters. This, and other information, is then updated at the beginning of the patient’s interaction with the physician or nursing staff; additional data — such as lab values, images, and progress notes — are added as the encounter progresses. This data could, ideally, be made portable so that it may be shared with other providers or accessed via patient portals. The 2009 Health Information Technology for Economic and Clinical Health (HITECH) Act, part of the Affordable Care Act, provided a major boost to health IT. It allocated around $30 billion to increase the take-up of electronic health records. Although information and communications technology (ICT) has been used in health care since at least the early 1960s, fewer than 10 percent of hospitals (and fewer than 20 percent of physicians) were using EHRs prior to HITECH. By 2014, just about all hospitals had some sort of certified EHR technology. Another example of an important health IT is telehealth. This provides a new platform to deliver health care at a distance. The coronavirus pandemic has seen rapid take-up of telehealth in the United States and around the world, and this is likely to persist even after the pandemic has abated. Often, large and sudden shocks can speed the switch to a new technology, as it gives multiple players incentives to switch simultaneously (e.g., physicians, patients, and hospital managers). In particular, the decision by Medicare to reimburse telehealth visits during the pandemic provides a valuable opportunity for providers to offer such care in lieu of in-person visits. Other key players in the longer-term evolution are federal and local regulators. Telehealth is particularly attractive for patients in hard-to-reach communities who can be treated via a video connection. Q: Why is there such a lag time to adopt IT in health care, compared to other industries? A: The factors that affect the adoption of health IT are similar to those in the broader literature on technological diffusion. Complexity, cost, competition, and complementary factors (such as skilled labor) are all important. But we can point to some factors that are particularly salient to health care: patient safety and privacy, market power, management, and misaligned incentives. Patient safety: Although health IT offers the potential to improve patient safety substantially, there is a risk that errors may be introduced. The initial adjustment costs in most industries as firms learn how to use IT are well-documented. Because patient safety may be affected by such a transition, there is a natural tendency toward greater risk aversion to all sorts of change in health care, including technology. Patient privacy: A common concern that affects health IT adoption revolves around privacy. Federal regulation in the form of the Health Insurance Portability and Accountability Act, state-specific laws, and the sheer complexity of legal obligations are thought to reduce the benefits of data sharing and, thus, health IT adoption. Market power: The EHR market is dominated by just two firms, Epic and Cerner. Many have argued that this lack of robust competition raises prices and thereby slows adoption. Rapid consolidation of the hospital and physician practices sector may have weakened competitive pressure to adopt efficient technologies, although these same forces may provide economies of scale that can promote adoption, especially in light of recent federal subsidies. Management practices and resistance to change: Many stakeholders can resist change, especially when there are large differences between the IT decision-makers (senior managers) and those who are using the tools (medical staff). Physicians have been found to play a particularly important role here. Without buy-in from senior physicians, it has been found to be very difficult to effectively diffuse IT in health care. Greater involvement in adapting to the new capabilities of health IT among the workforce throughout the health care system could improve acceptance and speed productivity gains while mitigating negative effects on the workforce. Misaligned incentives: Health care is exceptionally inefficient in generating incentives for innovation and diffusion. First, despite recent payment reforms, most providers continue to operate on a basis where greater provision of care results in greater profits, which means that there is little incentive to seek lower costs through health IT adoption and use. Second, ICT-related coordination is hampered because of the different systems run by competing health care firms. Q: What do we know about health IT and its impact on jobs, tasks, and skills? What can be done to help workers adapt? A: There is a vast amount of work on the impact of health IT. Our review of these studies suggests that health IT does, on average, improve clinical outcomes for patients. Like other industries, the effect takes time to feed through because of the need to learn and reorganize the workplace, and the impact of IT varies considerably across different health-care settings (due to the presence or absence of complementary factors such as management quality, workforce engagement, and appropriate skills). Much less is known about the impact on the workforce. A concern is that technology might automate away the jobs of health workers. Our work, consistent with a small literature, finds no significant job displacement effects or falls in wages. There may be some loss of demand in very specific settings, such as paper-based tasks made more efficient with software or the automation of reading X-rays affecting radiologists. Meanwhile, case study evidence suggests that technology does seem to affect the tasks that workers do, with many routine tasks being automated away. However, the underlying drivers of the growth in demand for health care due to an aging population appear to swamp any displacement effects. In terms of what can be done to help workers adapt, there are at least two important lessons. Poor training is frequently mentioned as a cause of inefficiency in IT use. Better training helps reduce medical error rates, empowers workers to perform new tasks, and helps define the roles and responsibilities of different health care employees. Second, engaging workers in the process of change promotes acceptance of the new systems and improves their functioning. Top-down imposition of new technologies and ways of working are often counterproductive.
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How advanced medical technologies are changing the healthcare landscape.
By James McDonough, a dad, explorer and entrepreneur who is expanding human health potential at EDISON BIO .
For most people, including busy entrepreneurs, the concept of “taking care of your body” has usually meant visiting a doctor once a year and going over some routine lab results. However, advancements in medical technology are rapidly and drastically changing the healthcare landscape to go well beyond this elementary approach.
Today, settling for a quick five-minute annual with a physician is no longer the only option. Genomics, cancer blood tests, MRIs, sleep analysis and many other innovations now allow patients to gain the most comprehensive picture of their health ever available. As a result, these advancements in technology are revolutionizing the healthcare system to become more proactive, personalized and convenient than ever before.
Proactive
Traditional healthcare systems are often criticized for their reactionary approach to medicine; health issues are addressed only once they’ve developed enough to become problematic.
But the development and increased accessibility of medical technology give patients the chance to treat diseases at their onset, giving them a higher chance of successful recovery.
For example, some healthcare innovators have begun offering full-body MRI scans as part of their executive health exams — exams designed for high-achievers such as entrepreneurs, CEOs and senior executives. These safe and painless procedures can detect multiple abnormalities before the onset of symptoms occurs, including brain tumors, spinal deterioration, pulmonary lesions, heart disease and more. Similarly, new cancer blood tests can test a patient’s blood sample for over fifty different kinds of cancer in their body at once. With these technologies, patients can be more confident that diseases aren’t growing in their bodies undetected.
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It’s not new knowledge in the healthcare community that treating diseases earlier is better. However, with the advancements in medical technology in the last few years, it is now more possible than ever to invest in proactive care that empowers patients to do just that.
Personalized
Because advancements in medical technology allow for more testing opportunities, healthcare companies can now capture billions of data points for an individual patient and use them to provide more personalized care.
For example, quantitative data from biomarker and genomic testing can be aggregated and analyzed to uncover an extensive and comprehensive understanding of a patient’s health. And by looking at a patient's entire health story and health history, providers are then able to provide more personalized care.
This incorporation of data collection into medicine underscores the shift toward a more holistic and individualized approach to healthcare. It is no longer one-size-fits-all when it comes to a patient’s wellness and health outcomes. Innovation in technology allows doctors to not only understand their patients more comprehensively than ever, but also to provide them with personalized care like never before.
As an entrepreneur, you know that time is money. And technology has allowed healthcare to become incredibly more convenient for those who need it most.
Long gone are the days of wasting time driving to and waiting around in a physician’s office. Instead, the innovation of telemedicine allows for patients to receive care through their phones or computers in real time.
Some advanced healthcare companies even offer to come to their patient’s home or office for any testing that needs to be completed — saving the patient time and hassle. Online portals also make the patient’s health data easily accessible, giving them the ability to share that data with specialists, trainers or even family members.
No longer is the healthcare landscape marked by wasted time and piles of paperwork. Telemedicine gives patients the ability to seek care on their own time and access their health information all in one place.
The Future Of Care
As advancements in technology continue to develop, so will the ways that we care for our bodies. Patients will continue to turn to companies whose incorporation of technological innovation into medicine allows patients to take control of their health like never before. Increasing longevity and improving performance has never been easier with a healthcare system that is changing to become more proactive, personalized and convenient for you.
P ocket-size ultrasound devices that cost 50 times less than the machines in hospitals (and connect to your phone). Virtual reality that speeds healing in rehab. Artificial intelligence that’s better than medical experts at spotting lung tumors. These are just some of the innovations now transforming medicine at a remarkable pace.
No one can predict the future, but it can at least be glimpsed in the dozen inventions and concepts below. Like the people behind them, they stand at the vanguard of health care. Neither exhaustive nor exclusive, the list is, rather, representative of the recasting of public health and medical science likely to come in the 2020s.
Since March, UPS has been conducting a trial program called Flight Forward, using autonomous drone deliveries of critical medical samples including blood or tissue between two branches of a hospital in Raleigh, N.C., located 150 yards apart. A fleet-footed runner could cover the distance almost as fast as the drones, but as a proof-of-concept program, it succeeded, and in October the FAA granted the company approval to expand to 20 hospitals around the U.S. over the next two years. “We expect UPS Flight Forward to one day be a very significant part of our company,” says UPS CEO David Abney of the service, which will deliver urine, blood and tissue samples, and medical essentials like drugs and transfusable blood. UPS is not alone in pioneering air deliveries. Wing, a division of Google’s parent company Alphabet, received similar, but more limited, FAA approval to make deliveries for both Walgreens and FedEx. And in Ghana and Rwanda, drones operated by Silicon Valley startup Zipline are already delivering medical supplies to rural villages. —Jeffrey Kluger
There are 7.5 billion humans, and tens of millions of us track our health with wearables like smart watches, as well as with more traditional devices like blood-pressure monitors. If there were a way to aggregate all that data from even a few million of us and make it all anonymous but searchable, medical researchers would have a powerful tool for drug development, lifestyle studies and more. California-based Big Data firm Evidation has developed just such a tool, with information from 3 million volunteers providing trillions of data points. Evidation partners with drug manufacturers like Sanofi and Eli Lilly to parse that data; that work has led to dozens of peer-reviewed studies already, on subjects ranging from sleep and diet to cognitive-health patterns. For founder Christine Lemke, one of Evidation’s ongoing projects, to see if new technologies can effectively measure chronic pain, is personal: Lemke has a rare genetic disease that causes frequent back pain. Evidation is partnering with Brigham and Women’s Hospital on the project. —Jeffrey Kluger
Type 1 diabetes affects 1.25 million Americans, but two in particular got Harvard biologist Doug Melton’s attention: his daughter Emma and son Sam. Treatment can involve a lifetime of careful eating, insulin injections and multiple daily blood-glucose tests. Melton has a different approach: using stem cells to create replacement beta cells that produce insulin. He started the work over 10 years ago, when stem-cell research was raising hopes and controversy. In 2014 he co-founded Semma Therapeutics—the name is derived from Sam and Emma—to develop the technology, and this summer it was acquired by Vertex Pharmaceuticals for $950 million. The company has created a small, implantable device that holds millions of replacement beta cells, letting glucose and insulin through but keeping immune cells out. “If it works in people as well as it does in animals, it’s possible that people will not be diabetic,” Melton says. “They will eat and drink and play like those of us who are not.” —Don Steinberg
A major limitation threatens to hamper the era of personalized medicine: people of Caucasian descent are a minority in the global population yet make up nearly 80% of the subjects in human-genome research, creating blind spots in drug research. Dr. Abasi Ene-Obong, 34, founded 54gene to change that. Named for Africa’s 54 countries, the Nigeria-based startup is sourcing genetic material from volunteers across the continent, to make drug research and development more equitable. 54gene is conscious of the ugly history of colonial exploitation in Africa. If companies are going to profit by developing marketable drugs based on the DNA of African people, Africa should benefit: so, when partnering with companies, 54gene prioritizes those that commit to including African countries in marketing plans for any resulting drugs. “If we are part of the pathway for drug creation, then maybe we can also become part of the pathway to get these drugs into Africa,” Ene-Obong says. —Corinne Purtill
One of the original disrupters of the new economy is bringing his approach to medical research. The Parker Institute for Cancer Immunotherapy, established by Napster co-founder and former Facebook president Sean Parker, is a network of top institutions including Memorial Sloan Kettering, Stanford, the MD Anderson Cancer Center and more. Its goal is to identify and remove obstacles to innovation in traditional research. For example, all of the participating institutes have agreed to accept an approval decision by any of their respective Institutional Review Boards, which “allows us to get major clinical trials off the ground in weeks rather than years,” says Parker, and at lower costs. Perhaps most important, Parker wants to infuse the project with his market sensibility: “We follow the discoveries coming from our researchers and then put our money behind commercializing them,” he says, either by licensing a product or spinning it out into a company. Since its founding in 2016, the institute has brought 11 projects to clinical trials and supported some 2,000 research papers.
A man wearing what looks like a chunky black wristwatch stares at a tiny digital dinosaur leaping over obstacles on a computer screen before him. The man’s hands are motionless, but he’s controlling the dinosaur—with his brain. The device on his wrist is the CTRL-kit, which detects the electrical impulses that travel from the motor neurons down the arm muscles and to the hand almost as soon as a person thinks about a particular movement. “I want machines to do what we want them to do, and I want us to not be enslaved by the machines,” says Thomas Reardon, CEO and co-founder of CTRL-Labs, the device maker. The hunched-over posture and fumbling keystrokes of the smartphone era represent “a step backward for humanity,” says Reardon, a neuroscientist who, in a past life, led the development of Microsoft’s Internet Explorer. The technology could open up new forms of rehabilitation and access for patients recovering from a stroke or amputation, as well as those with Parkinson’s disease, multiple sclerosis and other neurodegenerative conditions, Reardon says. —Corinne Purtill
There are more than 4 billion people globally who don’t have access to medical imaging—and could benefit from Butterfly iQ, a handheld ultrasound device. Jonathan Rothberg, a Yale genetics researcher and serial entrepreneur, figured out how to put ultrasound technology on a chip, so instead of a $100,000 machine in a hospital, it’s a $2,000 go-anywhere gadget that connects to an iPhone app. It went on sale last year to medical professionals. “Our goal is to sell to 150 countries that can pay for it. And [the Gates Foundation] is distributing it in 53 countries that can’t,” Rothberg says. The device isn’t as good as the big machines are and won’t replace them in prosperous parts of the world. But it could make scanning more routine. “There was a time when the thermometer was only used in a medical setting, when a blood-pressure cuff was only used in a medical center,” Rothberg says. “Democratizing [health] happens on multiple dimensions.” —Don Steinberg
Symptoms of lung cancer usually don’t appear until its later stages, when it’s difficult to treat. Early screening of high-risk populations with CT scans can reduce the risk of dying, but it comes with risks of its own. The U.S. National Institutes of Health found that 2.5% of patients who received CT scans later endured needlessly invasive treatments—-sometimes with fatal results—after radiologists erroneously diagnosed false positives. Shravya Shetty believes artificial intelligence may be the solution. Shetty is the research lead of a Google Health team that in the past two years built an AI system that outperforms human radiologists in diagnosing lung cancer. After being trained on more than 45,000 patient CT scans, Google’s algorithm detected 5% more cancer cases and had 11% fewer false positives than a control group of six human radiologists. The early results are promising, but “there’s a pretty big gap between where things are and where they could be,” says Shetty. “It’s that potential impact that keeps me going.” —Corinne Purtill
Every year, more than 2 million peer-reviewed research papers are published—far too many for any individual scientist to digest. Machines, however, don’t share this human limitation. BenevolentAI has created algorithms that scour research papers, clinical trial results and other sources of biomedical information in search of previously overlooked relationships between genes, drugs and disease. BenevolentAI CEO Joanna Shields was an executive at companies such as Google and Facebook, and then the U.K.’s Minister for Internet Safety and Security, before joining BenevolentAI. A frequent critic of the tech industry’s lapses in protecting young people from exploitation and abuse online, Shields sees BenevolentAI as an opportunity to harness technology’s power for good. “All of us have family members, friends who are diagnosed with diseases that have no treatment,” she says. “Unless we apply the scaling and the principles of the technology revolution to drug discovery and development, we’re not going to see a change in that outcome anytime soon.” —Corinne Purtill
Whenever the world’s biggest retailer aims its gigantic footprint at a new market, the ground shakes. In September, Walmart opened its first Health Center, a medical mall where customers can get primary care, vision tests, dental exams and root canals; lab work, X-rays and EKGs; counseling; even fitness and diet classes. The prices are affordable without insurance ($30 for an annual physical; $45 for a counseling session), and the potential is huge. In any given week, the equivalent of half of America passes through a Walmart. “When I first started here … [I] thought, That can’t be true,” says Sean Slovenski, a former Humana exec who joined Walmart last year to lead its health care push. If the concept spreads, repercussions await in every direction. Like Walmart’s merchandise suppliers, doctors and other medical pros may need to adjust to the retailer’s everyday low prices. Still, cautions Moody’s analyst Charles O’Shea: “Health care is multiple times harder than selling food.” —Don Steinberg
For too many people with suspected heart problems, invasive catheterization is necessary to diagnose blocked or narrowed arteries. Doctors must then choose the best method for improving blood flow from a handful of options, including balloon angioplasty and stenting. Charles Taylor, a former Stanford professor, started HeartFlow to help patients avoid invasive diagnostic procedures and improve treatment outcomes. The company’s system creates personalized 3-D models that can be rotated and zoomed into, so doctors can simulate various approaches on screens. In some cases, it can help avoid invasive procedures entirely. “By adding the HeartFlow … to our available resources for diagnosing stable coronary disease, we are able to provide patients with better care as we evaluate risk,” said Duke University cardiologist Manesh Patel, at the American College of Cardiology’s annual meeting in March. —Jeffrey Kluger
Isabel Van de Keere was at work one day in 2010 when a steel light fixture pulled loose from the ceiling and fell on her. The accident left Van de Keere, a Belgian-born Ph.D. in biomedical engineering, with a cervical spine injury and severe vertigo that required three years of intense neurological rehabilitation. She practiced the same tedious exercises dozens of times in a row, with progress so slow it seemed undetectable. Now 38, she’s the founder and CEO of Immersive Rehab, a London-based startup whose goal is to change the neurological-rehab experience using virtual reality. By expanding the range and type of exercises patients can try, VR creates more opportunities to harness the brain’s plasticity and repair neural pathways; increases the amount of data caregivers can use to measure progress and adapt programs; and improves the monotonous, frustrating experience of rehab. Feedback from volunteer patients and therapists has been promising; the company is now preparing to run clinical trials in the U.S. and Europe. —Corinne Purtill
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Medical research involves research in a wide range of fields, such as biology, chemistry, pharmacology and toxicology with the goal of developing new medicines or medical procedures or improving the application of those already available. It can be viewed as encompassing preclinical research (for example, in cellular systems and animal models) and clinical research (for example, clinical trials).
We performed single-nucleus chromatin accessibility mapping and RNA sequencing of breast biopsy samples obtained from healthy donors of diverse genetic ancestry and present a comprehensive single-nucleus atlas that describes specific markers of major cell types of the breast. Gene expression and signaling differences between ductal and lobular epithelial cells are also described.
In a new study, neoadjuvant immunotherapy led to major pathological responses in patients with locally advanced colon cancer harboring mismatch repair deficiency — and emerging evidence suggests that organ-sparing approaches may also be feasible.
In our study, we linked machine-learning-derived biological age gaps (BAGs) to common genetic variants in nine human organ systems, which revealed how these BAGs are causally associated with organ health and chronic diseases such as Alzheimer’s disease and diabetes. The findings provide insights into therapeutic and lifestyle interventions that might enhance organ health.
Microbe found in cat poo could be harnessed to deliver large, complex proteins across the blood–brain barrier.
Surprising results show that ‘sensory’ nerves, which carry information to the brain, have a direct role in helping tumours to metastasize.
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Technology is like a massive puzzle where each piece connects to form the big picture of our modern lives. Be it a classroom, office, or a hospital, technology has drastically changed the way we communicate and do business. But to truly understand its role, we need to explore different technology research topics.
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Technological field touches upon areas where technology, ethics, and society intersect and often disagree. This has sparked debates and, sometimes, conspiracy theories, primarily because of the profound implications technologies have for our future. Take a look at these ideas, if you are up to a more controversial research topic about technology:
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Computer science is a field that has rapidly developed over the past decades. It deals with questions of technology's influence on society, as well as applications of cutting-edge technologies in various industries and sectors. Here are some computer science research topics on technology to get started:
Information technology is a dynamic field that involves the use of computers and software to manage and process information. It's crucial in today's digital era, influencing a range of industries from healthcare to entertainment. Here are some captivating information technology related topics:
Artificial Intelligence, or AI as we fondly call it, is all about creating machines that mimic human intelligence. It's shaping everything from how we drive our cars to how we manage our calendars. Want to understand the mind of a machine? Choose a topic about technology for a research paper from the list below:
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Biotechnology is an interdisciplinary field that has been gaining a lot of traction in the past few decades. It involves the application of biological principles to understand and solve various problems. The following research topic ideas for technology explore biotechnology's impact on medicine, environment, agriculture, and other sectors:
>> Read more: Biology Topics to Research
Genetic engineering is an area of science that involves the manipulation of genes to change or enhance biological characteristics. This field has raised tremendous ethical debates while offering promising solutions in medicine and agriculture. Here are some captivating topics for a technology research paper on genetic engineering:
Reproduction technology is all about the science that aids human procreation. It's a field teeming with innovation, from IVF advancements to genetic screening. Yet, it also stirs up ethical debates and thought-provoking technology topics to write about:
The healthcare field is undergoing massive transformations thanks to cutting-edge medical technology. From revolutionary diagnostic tools to life-saving treatments, technology is reshaping medicine as we know it. To aid your exploration of this dynamic field, we've compiled medical technology research paper topics:
>> More ideas: Med Research Topics
Health technology is driving modern healthcare to new heights. From apps that monitor vital stats to robots assisting in surgeries, technology's touch is truly transformative. Take a look at these topics related to technology applied in healthcare:
>> View more: Public Health Topics to Research
With technology at the helm, our ways of communicating are changing at an unprecedented pace. From simple text messages to immersive virtual conferences, technology has rewritten the rules of engagement. So, without further ado, let's explore these communication research ideas for technology that capture the essence of this revolution.
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The intersection of technology and education is an exciting frontier with limitless possibilities. From online learning to interactive classrooms, you can explore various technology paper topics about education:
>> Learn more: Education Research Paper Topics
In the digital age, technology also impacts our relationships. It has become an integral part of how we communicate, meet people, and sustain our connections. Discover some thought-provoking angles with these research paper topics about technology:
Modern agriculture is far from just tilling the soil and harvesting crops. Technology has made remarkable strides into the fields, innovating and improving agricultural processes. Take a glance at these technology research paper topic ideas:
Our planet is facing numerous environmental challenges, and technology may hold the key to solving many of these. With innovations ranging from renewable energy sources to waste management systems, the realm of technology offers a plethora of research angles. So, if you're curious about the intersection of technology and environment, this list of research topics is for you:
>> View more: Environmental Science Research Topics
Energy and power are two pivotal areas where technology is bringing unprecedented changes. You can investigate renewable energy sources or efficient power transmission. If you're excited about exploring the intricacies of energy and power advancements, here are some engaging technology topics for research papers:
The finance sector has seen drastic changes with the rise of technology, which has revolutionized the way financial transactions are conducted and services are offered. Consider these research topics in technology applied in the finance sector:
>> More ideas: Finance Research Topics
The nature of warfare has transformed significantly with the evolution of technology, shifting the battlegrounds from land, sea, and air to the realms of cyber and space. This transition opens up a range of topics to explore. Here are some research topics in the realm of war technology:
Food technology is a field that deals with the study of food production, preservation, and safety. It involves understanding how various techniques can be applied to increase shelf life and improve nutrition value of foods. Check out our collection of food technology research paper topic ideas:
Entertainment technology is reinventing the ways we experience amusement. This industry is always presenting new angles for research and discussion, be it the rise of virtual reality in movies or the influence of streaming platforms on the music industry. Here's a list of unique research topics related to entertainment technology:
As we navigate the ever-changing landscape of technology, numerous intriguing questions arise. Below, we present new research questions about technology that can fuel your intellectual pursuit.
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Top 20 MedTech Research Topics On Advancements in Medical Imaging Technology. Emerging Trends in Medical Imaging Technology. Applications of Artificial Intelligence in Diagnostic Imaging. Role of Machine Learning in Improving Image Analysis. Advancements in 3D and 4D Medical Imaging. Augmented Reality in Surgical Navigation Systems.
Question. 1 answer. Feb 7, 2024. Sysmex DI-60 was found to be dependable in the characterization of red blood cells (RBCs). However, in the case of schistocytes, the study revealed high ...
Nanomaterials and Small Molecule-Enabled Precision Therapeutics, Biosensor and Diagnostics. Bijayananda Panigrahi. Dindyal Mandal. Dr. Nidhi Verma. ROHIT KUMAR SINGH. 755 views. An innovative journal that explores technologies which can maintain healthy lives and contribute to the global bioeconomy by addressing key medical and healthcare needs.
These issues result in health disparities and injustices. Examples of research topics about health inequities include: The impact of social determinants of health in a set population. Early and late-stage cancer stage diagnosis in urban vs. rural populations. Affordability of life-saving medications.
Jan 19, 2015. Answer. Health Technology Assessment (HTA) is defined as a specific form of policy analysis1 engaging multi-disciplinary groups to 'bridge between science and policy' and 'balancing ...
Prevention and detection are the key. Skin Checking Algorithms. A study in Nature in 2020 confirmed that on cleaned data for selected lesions, A.I. is as good as or even superior to human experts in image-based diagnosis. Which is a good thing, considering that there's a constant shortage of dermatologists, especially in rural areas.
23 Surgery Research Topics. 24 Radiology Research Paper Topics. 25 Anatomy and Physiology Research Paper Topics. 26 Healthcare Management Research Paper Topics. 27 Medical Ethics Research Paper Topics. 28 Environmental Health and Pollution Research Paper Topics. 29 Conclusion. Writing an original and compelling research paper is a daunting task ...
User-friendly rehabilitation medical devices can enhance health and the quality of life through the convergence of information communication and medical technology. Muscle contraction enables ...
In summary, acquisition of medical technology is accomplished primarily for the following five reasons: 1. To improve diagnostic, therapeutic, or rehabilitation efficiency. 2. To increase the health system's cost-effectiveness or reimbursement. 3. To reduce risk exposure and eliminate errors.
Graduate students in the Department of Medical Laboratory Science work with their research mentors on a wide array of topics, as highlighted below. Academic years 2019-2021 Academic year 2018-2019
By recognizing these topics, readers will be able to (1) set clinical and research data into the context of medical informatics, understanding what is possible to achieve with data or how data should be handled in terms of data privacy and storage; (2) distinguish current interoperability standards and obtain first insights into the processes ...
Fang (2015) shows that scientific techniques can be an essential tool for revealing patterns in medical research that could not be apparent with traditional methods of reviewing the medical literature . Teleradiology and telediagnosis, electronic health records, and Computer-Aided Diagnosis (CAD) are examples of digital medical technology.
Here, we'll explore a variety of healthcare-related research ideas and topic thought-starters across a range of healthcare fields, including allopathic and alternative medicine, dentistry, physical therapy, optometry, pharmacology and public health. NB - This is just the start….
The best investigators are asking the right questions, the important questions. It's a matter of staying knowledgeable about all of the technologies, including those from other fields, and thinking about how to apply them to your field. When you ask the right question and use the right technology, serendipity falls upon you.
Explore the latest full-text research PDFs, articles, conference papers, preprints and more on MEDICAL LABORATORY TECHNOLOGY. Find methods information, sources, references or conduct a literature ...
A: A key recent technology is the electronic health record, or EHR. This is, at its core, a digitized medical chart. Deriving value from this technology requires a broad array of functions that gather, manage, and share digital health information. This information can then be exploited to support medical decision-making and operations.
Medical technology consists of the creation of tools with the broad goal of improving the quality of life of patients. As diagnostic and therapeutic equipment are undergoing constant innovation, hopes are high for what new tools we can develop and what can be achieved through them. For example, in 2016, the Chan Zuckerberg Initiative set the ...
Over the next few decades, the practice of medicine will become increasingly virtual, aided by digital technologies like artificial intelligence, telehealth, and wearable devices. Harvard Medical School professor Jagmeet Singh is witnessing many of these changes firsthand. His new book, Future Care: Sensors, Artificial Intelligence, and the ...
Genomics, cancer blood tests, MRIs, sleep analysis and many other innovations now allow patients to gain the most comprehensive picture of their health ever available. As a result, these ...
Physicians at the Forefront of Health Care Technology Innovation. Ted A. James, MD, MHCM, FACS September 22, 2023. The technology age has ushered in a new era for the medical field. With the rapid advancement of medical devices, biotechnology breakthroughs, and digital health technology, these innovations reshape how care is delivered.
October 25, 2019 8:00 AM EDT. P ocket-size ultrasound devices that cost 50 times less than the machines in hospitals (and connect to your phone). Virtual reality that speeds healing in rehab ...
Medical research involves research in a wide range of fields, such as biology, chemistry, pharmacology and toxicology with the goal of developing new medicines or medical procedures or improving ...
Medical Technology Topics for a Research Paper. The healthcare field is undergoing massive transformations thanks to cutting-edge medical technology. From revolutionary diagnostic tools to life-saving treatments, technology is reshaping medicine as we know it. To aid your exploration of this dynamic field, we've compiled medical technology ...