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Impact on Patients

Impact on Patients. Farrokh Alemi, Ph.D. Table of Content. Impact on satisfaction Impact on providers Impact on health outcomes Impact on cost Factors affecting use of services. Impact on Satisfaction With Providers.

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Impact on Patients

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  1. Impact on Patients Farrokh Alemi, Ph.D.

  2. Table of Content • Impact on satisfaction • Impact on providers • Impact on health outcomes • Impact on cost • Factors affecting use of services

  3. Impact on Satisfaction With Providers • Patients are satisfied with their experience of interactive health communications. • Not surprising as dissatisfied patients will not be online

  4. Use of Services As Measure of Satisfaction • The average use of IHC applications is high, especially for electronic support groups. • For example, Brennan and colleagues report caregivers to persons with Alzheimer's disease used electronic support groups twice a week each time for an average of 13 minutes. • Alemi and colleagues report that cocaine using pregnant patients used electronic services over 7 months period on an average of 3.22 times per week. • Extensive use is one indication of patients' satisfaction with online services.

  5. Impact on Satisfaction With Providers • The impact of online services on overall satisfaction with health care system is not understood • Patients with access to both online and face-to-face counseling, prefer online counseling • In a randomized study of recovering mothers of new infants were 8 times more likely to use electronic support groups than face-to-face groups. • These studies suggest that use of -- and by inference satisfaction with -- face-to-face treatment may go down when online treatment is available

  6. Impact on Satisfaction with Providers • One study reported that online services improved the relationship between the face-to-face counselor and the patient • When online and face-to-face visits are closely integrated (e.g. both visits are to the same clinician) then online services may increase satisfaction with face-to-face services. • When online and face-to-face visits are not fully integrated, then online services may reduce satisfaction with face-to-face visits.

  7. Provider Satisfaction • Integration of online and face-to-face services is also related to the attitude that providers have towards online services. • Providers' satisfaction with online services is not well documented. • 325 members of American Association of Diabetes rated computer instruction as less favorable than books, videotapes, audiotapes or other health education methods.

  8. A Contradiction • Provider’s negative attitudes contradict: • Patients prefer interactive health communications to other forms of health communication and sometimes to visits. • Randomized studies show that interactive health communications are effective in changing behaviors. • Providers' reported negative attitudes are held despite patients' preferences and clinical studies of effectiveness

  9. Provider Attitudes May Be Changing • More exposure to online services • May be related to difficulties they face in integrating these technologies into their practices • Providers' negative attitudes may be a function of practice changes that follow online services

  10. Impact on Providers Practice Patterns • When consumers change, providers also change their behavior. • An example of such applications are a number of studies of shared medical decision making and informed consent. • Multimedia applications can be used to assess patients' treatment preferences. Little data is available on effectiveness of shared decision making applications in changing practice patterns.

  11. Reminders • Overwhelming data show that computer reminders can change clinicians practice patterns. • when computers call and remind parents to visit a clinic, on time immunization and vaccination rates improve. • Computer interviews before visit (faxed to the record) led to improved detection of alcoholism.

  12. History Taking • Studies show that patients are more likely to be truthful to a computer than to a clinician. • Locke and colleagues found that patients donating blood are more likely to report their HIV risk factors to a computer than to a clinician.

  13. Extending Services to Home • When clinicians educate patients by telephone about Cardiac Pulmonary resuscitations (CPR) they improve survival rates after emergency calls

  14. Impact on Patients' Life Styles and Health • Online services are increasingly looking and feeling like established mass media • 26 hours of mass media promotion of healthy behaviors led to 16% reduction in cardiovascular risks across the community • A number of other investigators have directly examined the impact of interactive health communications on behavior change • Findings are mixed

  15. Online Services Can Lead to Poor Health Outcomes • Many investigators have raised concern that patients may be misled by electronic sources of health information. • 89% of medical information is provided by non-health professionals. • There are numerous reports of misinformation on the Internet.

  16. Online Services Can Lead to Poor Health Outcomes • In one study, the use of Internet was associated with depression. • communication patterns among members of 73 households were examined over time. Greater use of the Internet was associated with declines in face-to-face communications with family members and increases in depression and loneliness.

  17. Direct studies • Impact is not always sustained. • Lando and colleagues found that computer instruction improved quit-rates for 6 months but not for 18 months post baseline. • Other studies show sustained impact

  18. When Can We Expect Sustained Impact on Behavior Change? • Patient education may be more effective by combining it with role-playing and support through electronic bulletin boards. • Gustafson and colleagues report successful examples of combining patient education with online support of patients with AIDS and cancer. • Alemi and colleagues report that computer role-playing helped teenagers better assimilate health messages.

  19. When Can We Expect Sustained Impact on Behavior Change? • Tailoring the information to key issues and characteristics of the patient also improved online services. • For example, smokers who received a letter tailored to their circumstances were more likely to quit than those who received a general message. • Similar results were obtained for patients’ trying to diet and reduce fat intake.

  20. When Can We Expect Sustained Impact on Behavior Change? • Another possible way to improve patient education is to do more of it. • Growing evidence suggests that there must be a minimal level of interaction before the impact of online services can be measured. • In one study, for example, no beneficial impact was measured unless patients had used the system for at least 3 times a week over a seven-month period. • The problem of dose-response has been around in studies of drug use and may exist for effect of online services.

  21. Impact on Utilization of Services • It has been known for sometime that health education can reduce unnecessary visits. • For example, Fries and colleagues had shown that a book on self-care could reduce demand for care with no adverse health effects. They have adapted this book and presented the content of it in an IHC format. Their earlier success.

  22. Direct Evidence of Impact on Utilization • Robinson compared two randomly assigned groups of graduate and under graduate students who did or did not receive computerized health education. • The group that received the computerized health education had 22.5% lower medical visits than the group that did not receive the IHC information and continued with their usual source of information.

  23. Evidence of Impact on Cost • Gustafson and colleagues provided 200 HIV patients with several computer services, including a computer bulletin board -- where patients could post written messages to a public forum. • Patients were randomly assigned to control and experimental groups.

  24. Evidence of Impact on Cost • Impact: • The experimental patients had fewer office visit (dentists, primary provider and alternative care providers). • Shorter time per visit to the primary care provider, HIV provider or the mental health provider. • The experimental patients were also less likely to be admitted to a hospital and more likely to have a short stay. • In summary, experimental patients had lower total health care cost than control patients did.

  25. Cost Savings Confirmed • Alemi and colleagues randomly assigned 54 drug using subjects to use voice electronic bulletin boards. Subjects were less likely to come in for a visit but had the same health outcomes as controls. • Wasson and colleagues replaced office follow up visits with three scheduled telephone calls. Over a 2-year period, the telephone care group had 28% less cost per patient than the usual care group.

  26. Savings Are Not Always There • Some studies of telephone follow up have shown no effect. • Other studies of IHC have shown the opposite effect: increased visits. • In one study, substance abuse recovering patients, who used interactive health education more than 3 times a week, were 1.5 times more likely to remain in outpatient substance abuse treatment. • In another study, patients receiving calls on medication and exercise were more likely to visit a dietitian.

  27. Conclusions on Impact on Cost • Four randomized clinical studies by independent groups of investigators and using different modes of communication on different types of patients report that more than 20% of visits have been avoided. • This is not a small reduction in visits and is practically significant for many delivery systems.

  28. Factors Affecting Use: Individual Characteristics • Prior experiences. • Media preferences and style. • Attitudes towards the technology. • attitudes of the individual's reference group towards the technology. • General willingness to communicate. • Reading capability (for text based health communications).

  29. Factors Affecting Use: Impact of Age • Studies that worked with narrow band of age differences have not found any age difference. • Other studies with larger range for age have found a definitive influence for age: • Older people are less likely and. • teenagers are more likely to use services.

  30. Factors Affecting Use: Task Appropriateness • Early investigators indicated that interactive health communications (in particular text-based electronic bulletin boards) were not suitable for tasks in which group members need to arrive at consensus or need to express their emotion • Frequent users are more willing to use the system to express their emotions and express support for others • Recent studies have shown that the majority (54.6%) of comments left by patients on voice bulletin board was for positive emotional support of each other

  31. Factors Affecting Use: Organizing Strategies • The use and satisfaction with use seem to depend, in part, on the rules under which an interactive health communication is organized. For example, a group facilitator, who listens and proposes a synthesis, can affect the outcome of electronic conversations in electronic bulletin boards

  32. Factors Affecting Use: Information Organization • Asking leading questions is more likely to overcome the patients' resistance to changing behaviors than sermons

  33. Factors Affecting Use: Structure of Organization • Type and structure of organizations affect the rate of communication and the nature of messages sent • Decentralization • Networked organizations

  34. Size and Composition of Population on the Network • Two studies have shown that size and composition of networks might affect use. • If just one person is on the system, there is no benefit at all as no communication can occur. If all the population with some shared characteristic are on the system, then the reasons for using the system are more universal and the habit of turning to the system more reoccurring and reinforced. Adoption of the technology seems to depend on it being successful in reaching a critical mass of the target pop. • Composition also matters. • For example, cancer patients may find little to communicate with rape victims and vice versa.

  35. Factors Affecting Use: Stage of Illness • Applications are most likely to impact cost and quality of care in diseases in which patients compliance and behavior are a barrier to effective treatment. • Applications are most likely to be effective during early part of the illness, when patients work through denial, anger and acceptance of illness. This is a period in time when patient is most uncomfortable with the disease and information and support is likely to have the largest impact.

  36. Factors That Affect Use: Presentation • Tailoring the information to the needs of the patients • Presenting information in ways that are vivid improves the effectiveness of information

  37. Factors That Affect Use: Integration With Clinics • Because clients have multiple sources of information, providing a consistent source of information across different mediums helps • The use of interactive health communications is substantially improved when clinicians recommend it • Health messages are more likely to be followed when they are also emphasized by the clinicians

  38. Factors That Affect Use: Visibility • Increased use is associated with increased exposure; Kiosk based IHC are used more when placed in visible and high-traffic public areas

  39. Factors That Affect Use: Technology • Use of services is encouraged by the system initiating the contact with the patient as opposed to waiting for the patient to access the application. For example, the interactive voice response (IVR) systems such as computer reminders or computerized voice bulletin board discussed earlier can call patients at home. Thus these systems do not always have to wait for the patient to initiate the contact.

  40. Individual characteristics Task appropriateness Organizing strategies Size of network Composition of network Stage of illness Medium of communication Presentation style Technology driven use Integration with services Tailored information Summary of Factors Affecting Use

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