Human-Centric Information Systems Research on the Digital Future of Healthcare

References

• Aanestad M, Vassilakopoulou P, Øvrelid E (2019) Collaborative innovation in healthcare: Boundary resources for peripheral actors. Proc. Internat. Conf. Inform. Systems (Association for Information Systems, Atlanta).Google Scholar
• Abdel-Karim BM, Pfeuffer N, Carl KV, Hinz O (2023) How AI-based systems can induce reflections: The case of AI-augmented diagnostic work. MIS Quart. 47(7):1395–1424.Crossref, Google Scholar
• Adams R, Henry KE, Sridharan A, Soleimani H, Zhan A, Rawat N, Johnson L, Hager DN, Cosgrove SE, Markowski A (2022) Prospective, multi-site study of patient outcomes after implementation of the TREWS machine learning-based early warning system for sepsis. Nature Medicine 28(7):1455–1460.Crossref, Google Scholar
• Adjerid I, Loewenstein G, Purta R, Striegel A (2022) Gain-loss incentives and physical activity: The role of choice and wearable health tools. Management Sci. 68(4):2642–2667.Link, Google Scholar
• Adler-Waxman A (2017) This is the biggest challenge to our health. World Economic Forum (December 7), https://www.weforum.org/agenda/2017/12/healthcare-future-multiple-chronic-disease-ncd/.Google Scholar
• Ahsen ME, Ayvaci MUS, Raghunathan S (2019) When algorithmic predictions use human-generated data: A bias-aware classification algorithm for breast cancer diagnosis. Inform. Systems Res. 30(1):97–116.Link, Google Scholar
• Alban A, Chick SE, Forster M (2023) Value-based clinical trials: Selecting recruitment rates and trial lengths in different regulatory contexts. Management Sci. 69(6):3516–3535.Link, Google Scholar
• Anderson C, Baskerville RL, Kaul M (2017) Information security control theory: Achieving a sustainable reconciliation between sharing and protecting the privacy of information. J. Management Inform. Systems 34(4):1082–1112.Crossref, Google Scholar
• Arora A, Barrett M, Lee E, Oborn E, Prince K (2023a) Risk and the future of AI: Algorithmic bias, data colonialism, and marginalization. Inform. Organ. 33(3):100478.Crossref, Google Scholar
• Arora A, Alderman JE, Palmer J, Ganapathi S, Laws E, McCradden MD, Oakden-Rayner L, et al. (2023b) The value of standards for health datasets in artificial intelligence-based applications. Nature Medicine 29:2929–2938.Google Scholar
• Atasoy H, Chen PY, Ganju K (2018) The spillover effects of health IT investments on regional healthcare costs. Management Sci. 64(6):2515–2534.Link, Google Scholar
• Ayabakan S, Bardhan IR, Zheng Z (2024) Impact of telehealth and process virtualization on healthcare utilization. Inform. Systems Res. 35(1):45–65.Link, Google Scholar
• Babar Y, Curley S, Ke Z, Liu D, Sheffler Z (2022) The effects of digitally delivered nudges in a corporate wellness program. J. Assoc. Inform. Systems 24(1):136–160.Google Scholar
• Baird A, Angst C, Oborn E (2020) MIS Quarterly research curation on health information technology research curation team. MIS Quart. (December 12), https://www.misqresearchcurations.org/blog/2018/6/20/health-information-technology.Google Scholar
• Bao C, Bardhan IR (2022) Performance of accountable care organizations: Health information technology and quality–efficiency trade-offs. Inform. Systems Res. 33(2):697–717.Link, Google Scholar
• Bardhan IR, Bao C, Ayabakan S (2023) Value implications of sourcing electronic health records: The role of physician practice integration. Inform. Systems Res. 34(3):1169–1190.Link, Google Scholar
• Bardhan IR, Chen H, Karahanna E (2020) Connecting systems, data, and people: A multidisciplinary research roadmap for chronic disease management. MIS Quart. 44(1):185–200.Crossref, Google Scholar
• Barrett M, Oborn E, Orlikowski W (2016) Creating value in online communities: The sociomaterial configuring of strategy, platform, and stakeholder engagement. Inform. Systems Res. 27(4):704–723.Link, Google Scholar
• Baucum M, Khojandi A, Vasudevan R, Ramdhani R (2023) Optimizing patient-specific medication regimen policies using wearable sensors in Parkinson’s disease. Management Sci. 69(10):5964–5982.Link, Google Scholar
• Blumenthal D, Gumas ED, Shah A, Gunja MZ, Williams RD II (2024) Mirror, mirror 2024: Reflecting poorly—Health care in the U.S. compared to other high-income countries. The Commonwealth Fund (September 19), https://www.commonwealthfund.org/publications/fund-reports/2024/sep/mirror-mirror-2024.Google Scholar
• Braveman P (2010) Social conditions, health equity, and human rights. Health Human Rights 12(2):31–48.Google Scholar
• Bretthauer KM, Savin S (2018) Introduction to the special issue on patient‐centric healthcare management in the age of analytics. Production Oper. Management 27(12):2101–2102.Crossref, Google Scholar
• Buckman JR, Adjerid I, Tucker C (2023) Privacy regulation and barriers to public health. Management Sci. 69(1):342–350.Link, Google Scholar
• Califf CB, Sarker S, Sarker S (2020) The bright and dark sides of technostress: A mixed-methods study involving healthcare IT. MIS Quart. 44(2):809–856.Crossref, Google Scholar
• Chatterjee S, Sarker S (2024) Toward a better digital future: Balancing the utopic and dystopic ramifications of digitalization. J. Strategic Inform. Systems 33(2):101834.Crossref, Google Scholar
• Chen C, Walker D (2023) A bitter pill to swallow? The consequences of patient evaluation in online health question-and-answer platforms. Inform. Systems Res. 34(3):867–889.Link, Google Scholar
• Chen W, Lu Y, Qiu L, Kumar S (2021) Designing personalized treatment plans for breast cancer. Inform. Systems Res. 32(3):932–949.Link, Google Scholar
• Cheng Z, Greenwood BN, Pavlou PA (2022) Location-based mobile gaming and local depression trends: A study of Pokémon Go. J. Management Inform. Systems. 39(1):68–101.Crossref, Google Scholar
• Coiera E, Liu S (2022) Evidence synthesis, digital scribes, and translational challenges for artificial intelligence in healthcare. Cell Rep. Medicine 3(12):100860.Google Scholar
• Connolly R, Sanchez OP, Compeau D, Tacco F (2023) Understanding engagement in online health communities: A trust-based perspective. J. Assoc. Inform. Systems 24(2):345–378.Google Scholar
• Dai T, Tayur S (2020) OM forum—Healthcare operations management: A snapshot of emerging research. Manufacturing Service Oper. Management 22(5):869–887.Link, Google Scholar
• Das S, Barnwal P (2018) The need to train uncertified rural practitioners in India. J. Internat. Medical Res. 46(1):522–525.Crossref, Google Scholar
• Delana K, Deo S, Ramdas K, Subburaman GBB, Ravilla T (2023) Multichannel delivery in healthcare: The impact of telemedicine centers in southern India. Management Sci. 69(5):2568–2586.Google Scholar
• Du K, Tanriverdi H (2023) Does IT enable collusion or competition: Examining the effects of IT on service pricing in multimarket multihospital systems. MIS Quart. 47(7):1425–1454.Crossref, Google Scholar
• Essén A, Oborn E (2017) The performativity of numbers in illness management: The case of Swedish rheumatology. Soc. Sci. Medicine 184(2017):134–143.Crossref, Google Scholar
• Essén A, Värlander SW (2019) How technology-afforded practices at the micro-level can generate change at the field level: Theorizing the recursive mechanism actualized in Swedish rheumatology. MIS Quart. 43(4):1155–1176.Crossref, Google Scholar
• Fan W, Zhou Q, Qiu L, Kumar S (2023) Should doctors open online consultation services? An empirical investigation of their impact on offline appointments. Inform. Systems Res. 34(2):629–651.Link, Google Scholar
• Fichman RG, Kohli R, Krishnan R (2011) Editorial overview—The role of information systems in healthcare: Current research and future trends. Inform. Systems Res. 22(3):419–428.Link, Google Scholar
• Fu S, Cai Z, Lim E, Liu Y, Tan CW, Lin Y, Deng S (2023) Unraveling the effects of mobile application usage on users’ health status: Insights from conservation of resources theory. J. Assoc. Inform. Systems 24(2):452–489.Google Scholar
• Ganju KK, Atasoy H, Pavlou PA (2022) Do electronic health record systems increase Medicare reimbursements? The moderating effect of the recovery audit program. Management Sci. 68(4):2889–2913.Link, Google Scholar
• Ganju KK, Atasoy H, McCullough J, Greenwood B (2020) The role of decision support systems in attenuating racial biases in healthcare delivery. Management Sci. 66(11):5171–5181.Link, Google Scholar
• Ghose A, Guo X, Li B, Dang Y (2022) Empowering patients using smart mobile health platforms: Evidence from a randomized field experiment. MIS Quart. 46(1):151–192.Crossref, Google Scholar
• Govindarajan V, Ramamurti R (2018) Reverse Innovation in Health Care: How to Make Value-Based Delivery Work (Harvard Business, Boston).Google Scholar
• Hur YY, Jin F, Li X, Cheng Y, Hu YJ (2023) Does social influence change with other information sources? A large-scale randomized experiment in medical crowdfunding. Inform. Systems Res. 34(4):1476–1492.Link, Google Scholar
• Hwang EH, Guo X, Tan Y, Dang Y (2022) Delivering healthcare through teleconsultations: Implications for offline healthcare disparity. Inform. Systems Res. 33(2):515–539.Link, Google Scholar
• Hydari MZ, Adjerid I, Striegel AD (2023) Health wearables, gamification, and healthful activity. Management Sci. 69(7):3920–3938.Link, Google Scholar
• James TL, Bélanger F, Lowry PB (2022) The mediating role of fitness technology enablement of psychological need satisfaction and frustration on the relationship between goals for fitness technology use and use outcomes. J. Assoc. Inform. Systems 23(4):913–965.Google Scholar
• Janakiraman R, Park E, Demirezen EM, Kumar S (2023) The effects of health information exchange access on healthcare quality and efficiency: An empirical investigation. Management Sci. 69(2):791–811.Link, Google Scholar
• Jiang J, Cameron AF (2020) IT-enabled self-monitoring for chronic disease self-management: An interdisciplinary review. MIS Quart. 44(1):451–508.Google Scholar
• Julka M, Alvarez K (2019) Real-time adverse even predictive model reduces readmissions. Accessed December 12, 2024, https://365.himss.org/sites/himss365/files/365/handouts/552693005/handout-185_FINAL.pdf.Google Scholar
• Jussupow E, Spohrer K, Heinzl A, Gawlitza J (2021) Augmenting medical diagnosis decisions? An investigation into physicians’ decision-making process with artificial intelligence. Inform. Systems Res. 32(3):713–735.Link, Google Scholar
• Kim SH, Kwon J (2019) How do EHRs and a meaningful use initiative affect breaches of patient information? Inform. Systems Res. 30(4):1184–1202.Link, Google Scholar
• Kim Y, Ayvaci MUS, Raghunathan S, Ayer T (2022) When it creates legal vulnerability: Not just overutilization but underprovisioning of health care could be a consequence. MIS Quart. 46(3):1483–1516.Crossref, Google Scholar
• Klein DB (2023) AI-enabled prescription digital therapeutics should be an investment priority. MedCity News (December 17), https://medcitynews.com/2023/12/ai-enabled-prescription-digital-therapeutics-should-be-an-investment-priority/.Google Scholar
• Kwon HE, Dewan S, Oh W, Kim T (2023) Self-regulation and external influence: The relative efficacy of mobile apps and offline channels for personal weight management. Inform. Systems Res. 34(1):50–66.Link, Google Scholar
• Lebovitz S, Levina N, Lifshitz-Assaf H (2021) Is AI ground truth really true? The dangers of training and evaluating AI tools based on experts’ know-what. MIS Quart. 45(3):1501–1525.Crossref, Google Scholar
• Liang H, Xue Y (2022) Save face or save life: Physicians’ dilemma in using clinical decision support systems. Inform. Systems Res. 33(2):737–758.Link, Google Scholar
• Liu Y, Jiang Z, Choi BCF (2023a) Pushing yourself harder: The effects of mobile touch modes on users’ self-regulation. Inform. Systems Res. 34(3):996–1016.Link, Google Scholar
• Liu Y, Xu X, Jin Y, Deng H (2023b) Understanding the digital resilience of physicians during the COVID-19 pandemic: An empirical study. MIS Quart. 47(1):391–422.Crossref, Google Scholar
• Lou B, Wu L (2021) AI on drugs: Can artificial intelligence accelerate drug development? Evidence from a large-scale examination of bio-pharma firms. MIS Quart. 45(3):1451–1482.Crossref, Google Scholar
• Lupton D (2016) The diverse domains of quantified selves: Self-tracking modes and dataveillance. Econom. Soc. 45(1):101–122.Google Scholar
• Meyers JL, Parasuraman S, Bell KF, Graham JP, Candrilli SD (2014) The high-cost, type 2 diabetes mellitus patient: An analysis of managed care administrative data. Archives of Public Health 72:1–12.Google Scholar
• Miller AR, Tucker C (2018) Privacy protection, personalized medicine, and genetic testing. Management Sci. 64(10):4648–4668.Link, Google Scholar
• Mishra AN, Tao Y, Keil M, Oh JH (2022) Functional IT complementarity and hospital performance in the United States: A longitudinal investigation. Inform. Systems Res. 33(1):55–75.Link, Google Scholar
• Montanera D, Mishra AN, Raghu TS (2022) Mitigating risk selection in healthcare entitlement programs: A beneficiary-level competitive bidding approach. Inform. Systems Res. 33(4):1221–1247.Link, Google Scholar
• Mukherjee AS, Sahay S (2024) Surveillance of antimicrobial Resistance in the environment: Imperatives for ICT4D research. Internat. Conf. Implications Inform. Digital Technologies Development (Springer Nature, Cham, Switzerland), 342–350.Google Scholar
• Nwafor O, Ma X, Johnson NA, Singh R, Aron R (2023) Differential impacts of technology-network structures on cost efficiency: Knowledge spillovers in healthcare. J. Management Inform. Systems 40(3):840–882.Crossref, Google Scholar
• Obermeyer Z, Powers B, Vogeli C, Mullainathan S (2019) Dissecting racial bias in an algorithm used to manage the health of populations. Science 366(6464):447–453.Crossref, Google Scholar
• Oborn E, Pilosof NP, Hinings B, Zimlichman E (2021) Institutional logics and innovation in times of crisis: Telemedicine as digital “PPE.” Inform. Organ. 31(1):100340.Crossref, Google Scholar
• Obuchowicz R, Strzelecki M, Piórkowski A (2024) Clinical applications of artificial intelligence in medical imaging and image processing—A review. Cancers (Basel) 16(10):1870.Crossref, Google Scholar
• Oren O, Gersh BJ, Bhatt DL (2020) Artificial intelligence in medical imaging: Switching from radiographic pathological data to clinically meaningful endpoints. Lancet Digital Health 2(9):e486–e488.Crossref, Google Scholar
• Pandey P, Zheng Y (2023) Technologies of power in digital inclusion. J. Assoc. Inform. Systems 24(5):1334–1357.Google Scholar
• Park EH, Werder K, Cao L, Ramesh B (2022) Why do family members reject AI in health care? Competing effects of emotions. J. Management Inform. Systems. 39(3):765–792.Crossref, Google Scholar
• Pinto-Coelho L (2023) How artificial intelligence is shaping medical imaging technology: A survey of innovations and applications. Bioengineering (Basel) 10(12):1435.Crossref, Google Scholar
• Pumplun L, Peters F, Gawlitza JF, Buxmann P (2023) Bringing machine learning systems into clinical practice: A design science approach to explainable machine learning-based clinical decision support systems. J. Assoc. Inform. Systems 24(4):953–979.Google Scholar
• Roderick T, Pengetnze Y, Miff S, Tremblay MC, Kohli R (2021) Building a vulnerability index of biological and socioeconomic risk factors to combat COVID-19 spread. Chandra Kruse L, Seidel S, Hausvik GI, eds. The Next Wave of Sociotechnical Design. DESRIST 2021, Lecture Notes in Computer Science (Springer, Berlin, Heidelberg), 22–33.Google Scholar
• Ruoff M, Gnewuch U, Maedche A, Scheibehenne B (2023) Designing conversational dashboards for effective use in crisis response. J. Assoc. Inform. Systems 24(6):1500–1526.Google Scholar
• Saghafian S, Tomlin B, Biller S (2022) The internet of things and information fusion: Who talks to who? Manufacturing Service Oper. Management 24(1):333–351.Link, Google Scholar
• Sahni N, Myers M (2014) What the U.S. can learn from India and Brazil about preventive health care. Harvard Bus. Rev. (November 14), https://hbr.org/2014/11/what-the-u-s-can-learn-from-india-and-brazil-about-preventive-health-care.Google Scholar
• Saifee DH, Zheng Z, Bardhan IR, Lahiri A (2020) Are online reviews of physicians reliable indicators of clinical outcomes? A focus on chronic disease management. Inform. Systems Res. 31(4):1282–1300.Google Scholar
• Salge TO, Kohli R, Barrett M (2015) Investing in information systems: On the behavioral and institutional search mechanisms underpinning hospitals’ IS investment decisions. MIS Quart. 39(1):61–89.Crossref, Google Scholar
• Salge TO, Antons D, Barrett M, Kohli R, Oborn E, Polykarpou S (2022) How IT investments help hospitals gain and sustain reputation in the media: The role of signaling and framing. Inform. Systems Res. 33(1):110–130.Link, Google Scholar
• Sarkar U, Bates DW (2024) Using artificial intelligence to improve primary care for patients and clinicians. JAMA Internal Medicine 184(4):343–344.Crossref, Google Scholar
• Scheer ER, Werner NE, Coller RJ, Nacht CL, Petty L, Tang M, Ehlenbach M, Kelly MM, Finesilver S, Warner G (2024) Designing for caregiving networks: A case study of primary caregivers of children with medical complexity. J. Amer. Medical Inform. Assoc. 31(5):1151–1162.Crossref, Google Scholar
• Singh R, Anderson C, Miranda S (2022) Physician burnout: A technology-based reification of competing logics view. Bui TX, ed. Proc. 55th Hawaii Internat. Conf. System Sci. (University of Hawai’i at Mānoa, Honolulu), 6270–6279.Google Scholar
• Sjöström J, Ågerfalk P, Hevner AR (2022) The design of a system for online psychosocial care: Balancing privacy and accountability in sensitive online healthcare environments. J. Assoc. Inform. Systems 23(1b):285–303.Google Scholar
• Son J, Flatley Brennan P, Zhou S (2020) A data analytics framework for smart asthma management based on remote health information systems with Bluetooth-enabled personal inhalers. MIS Quart. 44(1):237–263.Crossref, Google Scholar
• Sykes TA, Aljafari R (2022) We are all in this together, or are we? Job strain and coping in the context of an e-healthcare system implementation. J. Management Inform. Systems 39(4):1215–1247.Crossref, Google Scholar
• Teisberg E, Wallace S, O’Hara S (2020) Defining and implementing value-based health care: A strategic framework. Acad. Medicine 95(5):682–685.Crossref, Google Scholar
• Thakral Y, Sahay S, Mukherjee A (2022) Institutional work to routinize the use of a digital AMR monitoring system. Hatakka M, Amadi ES, Hedström MAH, eds. Freedom Social Inclusion Connected World: Proc. 16th Internat. Conf. Social Implications Comput. Developing Countries, vol. 657 (Springer, Cham, Switzerland), 89–106.Google Scholar
• Thakral Y, Sahay S, Mukherjee A (2024) Microfoundations of data-driven antimicrobial stewardship policy (ASP). Antibiotics (Basel) 13(1):24.Crossref, Google Scholar
• Thiebes S, Gao F, Briggs RO, Schmidt-Kraepelin M, Sunyaev A (2023) Design concerns for multiorganizational, multistakeholder collaboration: A study in the healthcare industry. J. Management Inform. Systems 40(1):239–270.Crossref, Google Scholar
• Thompson S, Whitaker J, Kohli R, Jones C (2020) Chronic disease management: How IT and analytics create healthcare value through the temporal displacement of care. MIS Quart. 44(1):227–256.Crossref, Google Scholar
• Tong Y, Tan CH, Sia CL, Shi Y, Teo HH (2022) Rural-urban healthcare access inequality challenge: Transformative roles of information technology. MIS Quart. 46(4):1937–1982.Crossref, Google Scholar
• Tremblay MC, Kohli R, Forsgren N (2021) Theories in flux: Reimagining theory building in the age of machine learning. MIS Quart. 45(1):455–459.Google Scholar
• Tremblay MC, Kohli R, Rivero C (2023) Data is the new protein: How the Commonwealth of Virginia built digital resilience muscle and rebounded from opioid and COVID shocks. MIS Quart. 47(1):423–450.Crossref, Google Scholar
• Valecha R, Upadhyaya S, Raghav Rao H (2021) An Activity theory approach to leak detection and mitigation in patient health information (PHI). J. Assoc. Inform. Systems 22(4):1007–1036.Google Scholar
• Venkatesh V, Sykes TA, Zhang X (2020) ICT for development in rural India: A longitudinal study of women’s health outcomes. MIS Quart. 44(2):605–629.Crossref, Google Scholar
• Venkatesh V, Rai A, Sykes TA, Aljafari R (2016) Combating infant mortality in rural India: Evidence from a field study of eHealth kiosk implementations. MIS Quart. 40(2):353–380.Crossref, Google Scholar
• Waldman SA, Terzic A (2019) Healthcare evolves from reactive to proactive. Clinical Pharmacology Therapeutics 105(1):10.Google Scholar
• Wu Y, Ye H, Jensen ML, Liu L (2024) Impact of project updates and their social endorsement in online medical crowdfunding. J. Management Inform. Systems 41(1):73–110.Crossref, Google Scholar
• Xie J, Liu X, Zeng DD, Fang X (2022) Understanding medication nonadherence from social media: A sentiment-enriched deep learning approach. MIS Quart. 46(1):341–372.Crossref, Google Scholar
• Yan L, Tan Y (2014) Feeling blue? Go online: An empirical study of social support among patients. Inform. Systems Res. 25(4):690–709.Link, Google Scholar
• Yoo Y, Henfridsson O, Kallinikos J, Gregory R, Burtch G, Chatterjee S, Sarker S (2024) The next frontiers of digital innovation research. Inform. Systems Res. 35(4):1507–1523.Link, Google Scholar
• Yu S, Chai Y, Chen H, Sherman SJ, Brown RA (2022) Wearable sensor-based chronic condition severity assessment: An adversarial attention-based deep multisource multitask learning approach. MIS Quart. 46(3):1355–1394.Crossref, Google Scholar
• Yu S, Chai Y, Samtani S, Liu H, Chen H (2024) Motion sensor–based fall prevention for senior care: A hidden Markov model with generative adversarial network approach. Inform. Systems Res. 35(1):1–15.Link, Google Scholar
• Zhou J, Kishore R, Amo L, Ye C (2022) Description and demonstration signals as complements and substitutes in an online market for mental health care. MIS Quart. 46(4):2055–2084.Crossref, Google Scholar
• Zhou J, Zhang Q, Zhou S, Li X, Zhang X (2023a) Unintended emotional effects of online health communities: A text mining-supported empirical study. MIS Quart. 47(1):195–226.Crossref, Google Scholar
• Zhou T, Wang Y, Yan L(L), Tan Y (2023b) Spoiled for choice? Personalized recommendation for healthcare decisions: A multiarmed bandit approach. Inform. Systems Res. 34(4):1493–1512.Link, Google Scholar